Nothing Special   »   [go: up one dir, main page]

AU2001290887A1 - Assessing condition of a joint and cartilage loss - Google Patents

Assessing condition of a joint and cartilage loss

Info

Publication number
AU2001290887A1
AU2001290887A1 AU2001290887A AU2001290887A AU2001290887A1 AU 2001290887 A1 AU2001290887 A1 AU 2001290887A1 AU 2001290887 A AU2001290887 A AU 2001290887A AU 2001290887 A AU2001290887 A AU 2001290887A AU 2001290887 A1 AU2001290887 A1 AU 2001290887A1
Authority
AU
Australia
Prior art keywords
cartilage
joint
thickness
imaging
diseased
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Granted
Application number
AU2001290887A
Other versions
AU2001290887B2 (en
Inventor
Philipp Lang
Daniel Steines
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Leland Stanford Junior University
Original Assignee
Leland Stanford Junior University
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Leland Stanford Junior University filed Critical Leland Stanford Junior University
Priority claimed from PCT/US2001/028679 external-priority patent/WO2002022013A1/en
Publication of AU2001290887A1 publication Critical patent/AU2001290887A1/en
Assigned to THE BOARD OF TRUSTEES OF THE LELAND STANFORD JUNIOR UNIVERSITY reassignment THE BOARD OF TRUSTEES OF THE LELAND STANFORD JUNIOR UNIVERSITY Amend patent request/document other than specification (104) Assignors: LELAND STANFORD JUNIOR UNIVERSITY
Application granted granted Critical
Publication of AU2001290887B2 publication Critical patent/AU2001290887B2/en
Priority to AU2006207884A priority Critical patent/AU2006207884A1/en
Anticipated expiration legal-status Critical
Ceased legal-status Critical Current

Links

Description

ASSESSING CONDITION OF A JOINT AND CARTILAGE LOSS
This invention was supported in part by a National Institute of Health Grant No. PAR-97- 014, and the U.S. government may have rights in this invention.
BACKGROUND OF THE INVENTION
FIELD OF INVENTION
This invention relates to assessing the condition of a joint and the use of the assessment in aiding in prevention of damage to the joint or treatment of diseased cartilage in the joint.
BACKGROUND
Osteoarthritis is the most common condition to affect human joints as well as a frequent cause of locomotor pain and disability. More particularly, osteoarthritis (OA) of the knee occurs in a substantial portion of the population over the age of fifty.
In spite of its societal impact and prevalence, however, there is a paucity of information on the factors that cause osteoarthritis to progress more rapidly in some individuals and not in others. Previously considered a "wear and tear" degenerative disease with little opportunity for therapeutic intervention, osteoarthritis is now increasingly viewed as a dynamic process with potential for new pharmacologic and surgical treatment modalites such as cartilage transplantation, osteochondral allo- or autografting, osteotomies and tibial corticotomies with angular distraction.
However, the appropriate deployment and selection of treatment interventions for OA is dependent on the development of better methods for the assessment of the condition of a patient's joint and the degeneration process.
There is, therefore, a need for improved methods for examining the factors that influence as well as quantification of the progression of the disease. Magnetic resonance imaging (MRI) is an accurate non-invasive imaging technique for visualization of articular cartilage in osteoarthritis, particularly in knees. However, current MRI techniques cannot provide information on the relationship between the location of the cartilage loss and variations in the load bearing areas during the walking cycle. This information is important since it has been shown that dynamic loads during walking are related to the progression of knee OA. Thus, the ability to locate cartilage defects or areas of cartilage thinning relative to the load bearing areas of the knee could be valuable in evaluating factors influencing the progression of osteoarthritis.
REFERENCES
1. Alexander EJ: Estimating the motion of bones from markers on the skin [Doctoral Dissertation]. University of Illinois at Chicago; 1998. 2. Alexander EJ, Andriacchi TP: Correcting for deformation in skin-based marker systems. Proceedings of the 3rd Annual Gait and Clinical Movement Analysis Meeting, San Diego, CA, 1998.
3. Alexander EJ, Andriacchi TP: Internal to external correspondence in the analysis of lower limb bone motion. Proceedings of the 1999 ASME Summer Bioengineering Conference, Big Sky, Montana, 1999.
4. Alexander EJ, Andriacchi TP: State estimation theory in human movement analysis. Proceedings of the 1998 ASME International Mechanical Engineering Congress, 1998.
5. Alexander EJ, Andriacchi TP, Lang PK: Dynamic functional imaging of the musculoskeletal system. ASME Winter International Congress and Exposition,
Nashville, Tennessee, 1999.
6. Alexander EJ, Andriacchi TP, Naylor DL: Optimization techniques for skin deformation correction, mtemational Symposium on 3-D Human Movement Conference, Chattanooga, TN, 1998. 7. Allen PR, Denham RA, Swan AN: Late degenerative changes after meniscectomy: factors affecting the knee after operations. J Bone Joint Surg 1984; 66B: 666-671.
8. Alley MT, Shifrin RY, Pelc ΝJ, Herfkens RJ: Ultrafast contrast-enhanced three dimensional MR angiography: state of the art. Radiographics 1998; 18: 273-285.
9. Andriacchi TP: Dynamics of knee malalignment. Orthop Clin North Am 1994; 25: 395-403. 10. Andriacchi TP, Alexander EJ, Toney MK, Dyrby CO, Sum J: A point cluster method for in vivo motion analysis: applied to a study of knee kinematics. J Biomech Eng 1998; 120(12): 743-749.
11. Andriacchi TP, Lang P, Alexander E, Hurwitz D: Methods for evaluating the progression of osteoarthritis. J Rehab Res Develop 2000; 37, 2: 163-170.
12. Andriacchi TP, Sen K, Toney MK, Yoder D: New developments in musculoskeletal testing. Proceedings of the Canadian Society of Biomechanics, 1994.
13. Andriacchi TP, Strickland AB: Gait analysis as a tool to assess joint kinetics biomechanics of normal and pathological human articulating joints. Nijhoff, Series E 1985; 93: 83-102.
14. Andriacchi TP, Toney MK: In vivo measurement of six-degrees-of-freedom knee movement during functional testing. Transactions of the Orthopedic Research Society 1995: 698.
15. Beaulieu CF, Hodge DK, Bergman AG: Glenohumeral relationships during physiological shoulder motion and stress testing: initial experience with open MRI and active scan-plane registration. Radiology 1999: accepted for publication.
16. Beaulieu CF, Hodge DK, Thabit G, Lang PK, Bergman AG: Dynamic imaging of glenohumeral instability with open MRI. Int. Society for Magnetic Resonance in Medicine, Sydney, Australia, 1998. 17. Benedetti MG, Cappozzo A: Anatomical landmark definition and identification in computer aided movement analysis in a rehabilitation context II (Internal Report). U Degli Studi La Sapienza 1994: 1-31.
18. Bergman AG, Beaulieu CF, Pearle AD, et al.: Joint motion: assessment by upright interactive dynamic near-real time MR imaging. Radiological Society of North America, 83rd Scientific Assembly and Annual Meeting, Chicago, IL, 1997.
19. Biswal S, Hastie T, Andriacchi T, Bergman G, Dillingham MF, Lang P: The rate of progressive cartilage loss at the knee is dependent on the location of the lesion: a longitudinal MRI study in 43 patients. Arthritis&Rheumatism 2000: (submitted for publication in 2000). 20. Bobic V: Arthoscopic osteochondral autograft transplantation in anterior cruciate ligament reconstruction: a preliminary clinical study. Knee Surg Sports Traumatol Arthrosc 1996; 3 (4): 262-264.
21. Boe S, Hansen H: Arthroscopic partial meniscectomy in patients aged over 50. J Bone Joint Surg 1986; 68B: 707. 22. Bregler C, Hertzmann A, Biermann H: Recovering non-rigid 3D shape from image streams. Proc. IEEE Conference on Computer Vision and Pattern Recognition 2000: in press. 23. Brittberg M, Lindahl A, Homminga G, Nilsson A, Isaksson O, Peterson L: A critical analysis of cartilage repair. Acta Orthop Scand 1997; 68 (2)186-191.
24. Brittberg M, Lindahl A, Nilsson A, Ohlsson C, Isaksson O, Peterson L: Treatment of deep cartilage defects in the knee with autologous chondrocyte transplantation. N Engl J Med 1994; 331 (14): 889-895.
25. Broderick LS, Turner DA, Renfrew DL, Schnitzer TJ, Huff JP, Harris C: Severity of articular cartilage abnormality in patients with osteoarthritis: evaluation with fast spin-echo MR vs arthroscopy. AJR 1994; 162: 99-103.
26. Butts K, Pauly JM, Kerr AB, Bergman AG, Beaulieu CF: Real-Time MR imaging of joint motion on an open MR imaging scanner. Radiological Society of North
America, 83rd Scientific Assembly and Annual Meeting, Chicago, IL, 1997.
27. Cohen ZA, McCarthy DM, Kwak, SD, Legrand P, Fogarasi F, Ciaccio EJ, Ateshian GA: Knee cartilage topography, thickness, and contact areas from MRI: in-vitro calibration and in-vivo measurements. Osteoarthritis and Cartilage 1999; 7: 95-109. 28. Daniel B, Butts K, Glover G, Herfkens R: Breast cancer: gadolinium-enhanced MR imaging with a 0.5T open imager and three-point Dixon technique. Radiology 1998; 207 (1): 183-190.
29. Disler DG: Fat-suppressed three-dimensional spoiled gradient-recalled MR imaging: assessment of articular and physeal hyaline cartilage. AJR 1997; 169: 1117-1123. 30. Disler DG, McCauley TR, Kelman CG, et al.: Fat-suppressed three-dimensional spoiled gradient-echo MR imaging of hyaline cartilage defects in the knee: comparison with standard MR imaging and arthroscopy. AJR 1996; 167: 127-132.
31. Disler DG, McCauley TR, Wirth CR, Fuchs MD: Detection of knee hyaline cartilage defects using fat-suppressed three-dimensional spoiled gradient-echo MR imaging: comparison with standard MR imaging and correlation with arthrosopy. AJR 1995;
165: 377-382.
32. Doherty M, Hutton C, Bayliss MT: Osteoarthritis. In: Maddison PJ, Isenberg DA, Woo P, et al., eds. Oxford Textbook of Rheumatology, vol 1. Oxford, New York, Tokyo: Oxford University Press, 1993; 959-983. 33. Dougados M, Gueguen A, Nguyen M, et al.: Longitudinal radiologic evaluation of osteoarthritis of the knee. J Rheumatol 1992; 19: 378-384.
34. Du YP, Parker DL, Davis WL: Vessel enhancement filtering in three-dimensional MR angiography. J Magn Res Imaging 1995; 5: 151-157.
35. Du YP, Parker DL, Davis WL, Cao G: Reduction of partial-volume artifacts with zero-filled interpolation in three-dimensional MR angiography. J Magn Res Imaging
1994; 4: 733-741.
36. Dumoulin CL, Souza SP, Darrow RD: Real-time position monitoring of invasive devices using magnetic resonance. Magn Reson Med 1993; 29: 411-5. 37. Dyrby CO: The three-dimensional kinematics of knee joint motion: functional differences in two populations [Master's Thesis]. University of Illinois at Chicago; 1998.
38. Eckstein F, Westhoff J, Sittek H, et al.: In vivo reproducibility of three-dimensional cartilage volume and thickness measurements with MR imaging. AJR 1998; 170(3):
593-597.
39. Elting JJ, Hubbell JC: Unilateral frame distraction: proximal tibial valgus osteotomy for medial gonarthritis. Contemp Orthop 1993; 27(6): 522-524.
40. Falcao AX, Udupa JK, Samarasekera S, Sharma S: User-steered image segmentation paradigms: Live wire and live lane. Graphical Models and Image Processing 1998;
60: 233-260.
41. Felson DT, Zhang Y, Anthony JM, Naimark A, Anderson JJ: Weight loss reduces the risk for symptomatic knee osteoarthritis in women: the Framingham study. Ann Intern Med 1992; 116: 535-539. 42. Garrett JC: Osteochondral allografts for reconstruction of articular defects of the knee, ft str Course Lect 1998; 47: 517-522.
43. Ghosh S, Newitt DC, Majumdar S: Watershed segmentation of high resolution articular cartilage image. International Society for Magnetic Resonance in Medicine, Philadelphia, 1999. 44. Gouraud H: Continuous shading of curved surfaces. LEEE Trans on Computers 1971; C-20(6).
45. Gray A: Modern Differential Geometry of Curves and Surfaces. 1993: CRC Press, Inc.
46. Hargreaves BA, Gold GE, Conolly SM, Nishimura DG: Technical considerations for DEFT imaging. International Society for Magnetic Resonance in Medicine, Sydney,
Australia, April 17-24, 1998.
47. Hargreaves BA, Gold GE, Lang PK, Bergman G, Conolly SM, Nishimura DG: Imaging of articular cartilage using driven equilibrium. International Society for Magnetic Resonane in Medicine, Sydney, Australia, April 17-24, 1998. 48. Hayes C, Conway W: Evaluation of articular cartilage: radiographic and cross- sectional imaging techniques. Radiographics 1992; 12: 409-428.
49. Henkelman RM, Stanisz G, Kim J, Bronskill M: Anisotropy of NMR properties of tissues. Magn Res Med 1994; 32: 592-601.
50. Hoppenfeld S, Huton R: Physical Examination of the Knee, hi: Hoppenfeld S, ed. Physical Examination of the Spine and Extremities: Appleton-Century-Crofts/
Prentice-Hall, 1976; 171-196. 51. Hyhlik-Durr A, Faber S, Burgkart R, et al.: Precision of tibial cartilage morphometry with a coronal water-excitation MR sequence. European Radiology 2000; 10 (2): 297-303.
52. Irarrazabal P, Nishimura DG: Fast three-dimensional magnetic resonance imaging. Mag Res Med 1995; 33: 656-662.
53. Johnson F, Leitl S, Waugh W: The distribution of load across the knee. A comparison of static and dynamic measurements. J Bone Joint Surg 1980; 62B: 346- 349.
54. Johnson TS: h vivo contact kinematics of the knee joint: Advancing the point cluster technique. Ph.D. thesis, University of Minnesota 1999.
55. Johnson TS, Andriacchi TP, Laurent M: Development of a knee wear method based on prosthetic in vivo slip velocity. Transactions of the Orthopedic Research Society, 46th Annual Meeting, March, 2000.
56. LaFortune MA, Cavanagh PR, Sommer HJ, Kalenak A: Three dimensional kinematics of the human knee during walking. J. Biomechanics 1992; 25: 347-357.
57. Lang P, Alexander E, Andriacchi T: Funcional joint imaging: a new technique integrating MRI and biomotion studies. International Society for Magnetic Resonance in Medicine, Denver, 4/18/00-4/24/00, 2000.
58. Lang P, Biswal S, Dillingham M, Bergman G, Hastie T, Andriacchi T: Risk factors for progression of cartilage loss: a longitudinal MRI study. European Society of
Musculoskeletal Radiology, 6th Annual Meeting, Edinburgh, Scotland, 1999.
59. Lang P, Hargreaves BA, Gold G, et al.: Cartilage imaging: comparison of driven equilibrium with gradient-echo, SPGR, and fast spin-echo sequences. International Society for Magnetic Resonance in Medicine, Sydney, Australia, April 17-24, 1998. 60. Ledingham J, Regan M, Jones A, Doherty M: Factors affecting radiographic progression of knee osteoarthritis. Ann Rheum Dis 1995; 54: 53-58.
61. Lorensen WE, Cline HE: Marching cubes: a high resolution 3d surface construction algorithm. Comput Graph 1987; 21: 163-169.
62. Losch A, Eckstein F, Haubner M, Englmeier KH: A non-invasive technique for 3- dimensional assessment of articular cartilage thickness based on MRI part 1: development of a computational method. Magn Res Imaging 1997; 15, 7: 795-804.
63. Lu TW, O'Connor JJ: Bone position estimation from skin marker co-ordinates using globals optimisation with joint constraints. J Biomechanics 1999; 32: 129 - 134.
64. Lucchetti L, Cappozzo A, Cappello A, Delia Croce U: Skin movement artefact assessment and compensation in the estimation of knee-joint kinematics. J
Biomechanics 1998; 31: 977-984. 65. Lynch JA, Zaim S, Zhao J, Stork A, Genant HK: Cartilage segmentation of 3D MRI scans of the osteoarthritic knee combining user knowledge and active contours. Proc. SPIE 3979 Medical Imaging, San Diego, February 2000.
66. Maki JH, Johnson GA, Cofer GP, MacFall JR: SNR improvement in NMR microscopy using DEFT. J Mag Res 1988.
67. Meyer CH, Pauly JM, Macovski A, Nishimura DG: Simultaneous spatial and spectral selective excitation. Magn Res Med 1990; 15: 287-304.
68. Mollica Q, Leonardi W, Longo G, Travaglianti G: Surgical treatment of arthritic varus knee by tibial corticotomy and angular distraction with an external fixator. Ital J Orthop Traumatol 1992; 18 (1): 17-23.
69. Nizard RS: Role of tibial osteotomy in the treatment of medial femorotibial osteoarthritis. Rev Rhum Engl Ed 1998; 65 (7-9): 443-446.
70. Noll DC, Nishimura D, Macovski A: Homodyne detection in magnetic resonance imaging. IEEE Trans Med ftnaglO 1991; 10 (2): 154-163. 71. Ogilvie-Harris DJ, Fitsialos DP: Arthroscopic management of the degenerative knee. Arthroscopy 1991; 7: 151-157.
72. Pearle A, Bergman AG, Daniels B, et al.: Use of an external MR-tracking coil for active scan plane registration during dynamic musculoskeletal MR imaging in a vertically open MRT unit. American Roentgen Ray Society, San Francisco, CA, 1998.
73. Pearle AD, Daniel BL, Bergman AG: Joint motion in an open MR unit using MR tracking. JMRI 1999; 10 (10): 1566-1576.
74. Peterfy C, van Dijke C, Lu Y, et al.: Quantification of the volume of articular cartilage in the metacaφophalangeal joints of the hand: accuracy and precision of three-dimensional MR imaging. AJR 1995; 165: 371-375.
75. Peterfy CG, Majmndar S, Lang P, van Dijke C, Sack K, Genant HK: MR imaging of the arthritic knee: improved discrimination of cartilage, synovium, and effusion with pulsed saturation transfer and fat-suppressed Tl -weighted sequences. Radiology 1994; 191(2): 413-419. 76. Peterfy CG, van Dijke CF, Janzen DL, et al.: Quantification of articular cartilage in the knee with pulsed saturation transfer subtraction and fat-suppressed MR imaging: optimization and validation. Radiology 1994; 192(2): 485-491.
77. Piplani MA, Disler DG, McCauley TR, Holmes TJ, Cousins JP: Articular cartilage volume in the knee: semiautomated determination from three-dimensional reformations of MR images. Radiology 1996; 198: 855-859.
78. Potter HG, Linklater JM, Allen AA, Hannafin JA, Haas SB: Magnetic resonance imaging of articular cartilage in the knee: an evaluation with use of fast-spin-echo imaging. J Bone Joint Surg 1998; 80-A(9): 1276-1284. 79. Prodromos CC, Andriacchi TP, Galante JO: A relationship between gait and clinical changes following high tibial osteotomy. J Bone Joint Surg 1985; 67A: 1188-1194.
80. Radin EL, Burr DB, Caterson B, Fyhrie D, Brown TD, Boyd RD: Mechanical determinants of osteoarthrosis. S em Arthr Rheum 1991; 21(3): 12-21. 81. Radin EL, Burr DB, Fyhrie D: Characteristics of joint loading as it applies to osteoarthrosis. In: Mow VC, Woo S-Y, Ratcliffe T, eds. Symposium on Biomechanics of Diarthrodial Joints, vol 2. New York, NY: Springer- Verlag, 1990; 437-451.
82. Recht MP, Piraino DW, Paletta GA, Schils JP, Belhobek GH: Accuracy of fat- suppressed three-dimensional spoiled gradient-echo FLASH MR imaging in the detection of patellofemoral articular cartilage abnormalities. Radiology 1996; 198: 209-212.
83. Recht MP, Resnick D: MR imaging of articular cartilage: current status and future directions. AJR 1994; 163: 283-290. 84. Ritter MA, Faris PM, Keating EM, Meding JB: Postoperative alignment of total knee replacement. Clin Orthop 1994; 299: 153-156.
85. Saito T, Toriwaki J-I: New algorithms for Euclidean distance transformation of an n- dimensional digitized picture with applications. Pattern Recognition 1994; 27 (11): 1551-1565. 86. Schipplein OD, Andriacchi TP: Interaction between active and passive knee stabilizers during level walking. J Orthop Res 1991; 9: 113-119.
87. Schouten JSAG, van den Ouweland FA, Valkenburg HA: A 12 year follow up study in the general population on prognostic factors of cartilage loss in osteoarthritis of the knee. Ann Rheum Dis 1992; 51: 932-937. 88. Sharif M, George E, Shepstone L, et al.: Serum hyaluronic acid level as a predictor of disease progression in osteoarthritis of the knee. Arthritis Rheum 1995; 38: 760- 767.
89. Sharma L, D.E. H, Thonar EJMA, et al.: Knee adduction moment, serum hyaluronic acid level, and disease severity in medial tibiofemoral osteoarthritis. Arthritis and Rheumatism 1998; 41(7): 1233-40.
90. Shoup RR. Becker ED: The driven equilibrium Fourier transform NMR technique: an experimental study. J Mag Res 1972; 8.
91. Slemenda C, Mazzuca S, Brandt K, Katz B: Lower extremity lean tissue mass and strength predict increases in pain and in functional impairment in knee osteoarthritis. Arthritis Rheum 1996; 39(suppl): S212.
92. Slemenda C, Mazzuca S, Brandt K, Katz B: Lower extremity strength, lean tissue mass and bone density in progression of knee osteoarthritis. Arthritis Rheum 1996; 39(suppl): SI 69. 93. Solloway S, Hutchinson CE, Waterton JC, Taylor CJ: The use of active shape models for making thickness measurements of articular cartilage from MR images. Mag Res Med 1997; 37:943-952.
94. Spoor CW, Veldpas FE: Rigid body motion calculated from spatial coordinates of markers. J Biomechanics 1980; 13: 391-393.
95. Stammberger T, Eckstein F, Englmeier KH, Reiser M: Determination of 3D cartilage thickness data from MR imaging: computational method and reproducibility in the living. Mag Res Med 1999; 41: 529-536.
96. Stammberger T, Eckstein F, Michaelis M, Englmeier KH, Reiser M: Interobserver reproducibility of quantitative cartilage measurements: Comparison of B-spline snakes and manual segmentation. Mag Res Imaging 1999; 17:1033-1042.
97. Steines D, Berger F, Cheng C, Napel S, Lang P: 3D thickness maps of articular cartilage for quantitative assessment of osteoarthritis. To be presented at ACR 64th Annual Scientific Meeting, Philadelphia, October 2000. 98. Steines D, Cheng C, Wong A, Berger F, Napel S, Lang P: Segmentation of osteoarthritic femoral cartilage from MR images. CARS - Computer- Assisted Radiology and Surgery, p. 578-583, San Francisco, 2000.
99. Steines D, Napel S, Lang P: Measuring volume of articular cartilage defects in osteoarthritis using MRI. To be presented at ACR 64th Annual Scientific Meeting, Philadelphia, October 2000.
100. Stevenson S, Dannucci GA, Sharkey NA, Pool RR: The fate of articular cartilage after transplantation of fresh and cryopreserved tissue-antigen-matched and mismatched osteochondral allografts in dogs. J Bone Joint Surg 1989; 71 (9): 1297- 1307. 101. Tieschky M, Faber S, Haubner M, et al.: Repeatability of patellar cartilage thickness patterns in the living, using a fat-suppressed magnetic resonance imaging sequence with short acquisition time and three-dimensional data processing. J Orthop Res 1997; 15(6): 808-813.
102. Tomasi C, Kanade T: Shape and motion from image streams under orthography — a factorization method. Proc Nat Acad Sci 1993; 90(21): 9795-9802.
103. Tsai J, Ashjaee S, Adalsteinsson E, et al.: Application of a flexible loop-gap resonator for MR imaging of articular cartilage at 3.0T. International Society for Magnetic Resonance in Medicine, Denver, 4/18/00-4/24/00, 2000.
104. Wang JW, Kuo KN, Andriacchi TP, Galante JO: The influence of walking mechanics and time on the results of proximal tibial osteotomy. J Bone Joint Surg
1990; 72A: 905-909.
105. Waterton JC, Solloway S, Foster JE, Keen MC, Gandy S, Middleton BJ, Maciewicz RA, Watt I, Dieppe PA, Taylor CJ: Diurnal variation in the femoral articular cartilage of the knee in young adult humans. Mag Res Med 2000, 43: 126-132. 106. Woolf SD, Chesnick F, Frank J, Lim K, Balaban R: Magnetization transfer contrast: MR imaging of the knee. Radiology 1991; 179: 623-628.
107. Worring M, Smeulders AWM: Digital curvature estimation. CVGIP: Image Understanding, 1993. 58(3): p. 366-382. 108. Yan CH: Measuring changes in local volumetric bone density: new approaches to quantitative computed tomography, Ph.D. thesis, 1998, Dept. of Electrical Engineering, Stanford University
109. Yao L, Gentili A, Thomas A: Incidental magnetization transfer contrast in fast spin- echo imaging of cartilage. J Magn Reson Imaging 1996; 6 (1): 180-184. 110. Yao L, Sinha S, Seeger L: MR imaging of joints: analytic optimization of GRE techniques at 1.5 T. AJR 1992; 158(2): 339-345.
111. Yasuda K, T. M, Tsuchida T, Kameda K: A 10 to 15 year follow up observation of high tibial osteotomy in medial compartment osteoarthritis. Clin Orthop 1992; 282: 186-195. 112. Kass M, Witkin A, Terzopoulos D: Snakes: Active contour models. Int J Comput Vision 1988; 1:321-331
113. Falcao AX, Udupa JK, Samarasekera S, Sharma S, Hirsch BE, Lotufo RA: User- steered image segmentation paradigms: Live wire and live lane. GMLP 1998; 60, 233-260 114. 114. Steines, D., et al., Segmentation of osteoarthritic femoral cartilage using live wire, ISMRM Eight Scientific Meeting, Denver Colorado, 2000
SUMMARY OF THE INVENTION
This invention relates to assessing the condition of a joint of a mammal, particularly a human subject, using the assessment to treat and monitor the subject as needed for cartilage degeneration problems. While the numerous aspects of the invention are useful for joints generally, they are particularly suited for dealing with the human knee. Some aspects related the static images and degeneration patterns of a cartilage, while others relate to the interaction of such images and patterns to provide a better means of assessing the condition of a cartilage.
One aspect of this invention is a method for assessing the condition of a cartilage. The method comprises obtaining an image of a cartilage, (preferably a magnetic resonance image), converting the image to a three-dimensional degeneration pattern, and evaluating the degree of degeneration in a volume of interest of the cartilage. By performing this method at an initial time T, and a later time T2, one can determine the change in the volume of interest and evaluate what steps to take for treatment.
Another aspect of this invention is a method of estimating the loss of cartilage in a joint. The method comprises obtaining a three-dimensional map of the cartilage at an initial time and calculating the thickness or regional volume of a region thought to contain degenerated cartilage so mapped at the initial time, obtaining a three-dimensional map of the cartilage at a later time, and calculating the thickness or regional volume of the region thought to contain degenerated cartilage so mapped at the later time, and determining the loss in thickness or regional volume of the cartilage between the later and initial times. The 3D map may be a thickness map, a biochemical map or a combination.
Another aspect of the invention is a method for assessing the condition of cartilage in a joint of a human, which method comprises electronically transferring an electronically-generated image of a cartilage of the joint from a transferring device to a receiving device located distant from the transferring device; receiving the transferred image at the distant location; converting the transferred image to a degeneration pattern of the cartilage; and transmitting the degeneration pattern to a site for analysis.
Another aspect of the invention is a method for determining the volume of cartilage loss in a region of a cartilage defect of a cartilage in joint of a mammal. The method comprises
(a) determining the thickness, DN, of the normal cartilage near the cartilage defect;
(b) obtaining the thickness of the cartilage defect, Do, of the region; (c) subtracting DD from DN to give the thickness of the cartilage loss, DL; and (d) multiplying the DL value times the area of the cartilage defect, AD, to give the volume of cartilage loss.
Still another aspect of the invention is a method of estimating the change of a region of cartilage in a joint of a mammal over time. The method comprises (a) estimating the width or area or volume of a region of cartilage at an initial time Ti, (b) estimating the width or area or volume of the region of cartilage at a later time T2, and (c) determining the change in the width or area or volume of the region of cartilage between the initial and the later times.
Still another aspect of the invention is a method of estimating the loss of cartilage in a joint. The method comprises (a) defining a 3D object coordinate system of the joint at an initial time, Ti; (b) identifying a region of a cartilage defect within the 3D object coordinate system; (c) defining a volume of interest around the region of the cartilage defect whereby the volume of interest is larger than the region of cartilage defect, but does not encompass the entire articular cartilage; (d) defining the 3D object coordinate system of the joint at a second time point, T2; (e) placing the identically-sized volume of interest into the 3D object coordinate system at time point T2 using the object coordinates of the volume of interest at time point Ti.; (f) and measuring any differences in cartilage volume within the volume of interest between time points Ti and T2.
Another aspect of this invention is a method for providing a biochemical based map of joint cartilage. The method comprises measuring a detectable biochemical component throughout the cartilage, determining the relative amounts of the biochemical component throughout the cartilage; mapping the amounts of the biochemical component through the cartilage; and determining the areas of cartilage deficit by identifying the areas having an altered amount of the biochemical component present.
Once a map is obtained, it can be used in assessing the condition of a cartilage at an initial time and over a time period. Thus, the biochemical map may be used in the method aspects of the invention in a manner similar to the cartilage thickness map.
Another aspect of this invention is a method for assessing the condition of cartilage in a joint from a distant location. The method comprises electronically transferring an electronically-generated image of a cartilage of the joint from a transferring device to a receiving device located distant from the transferring device; receiving the transferred image at the distant location; converting the transferred image to a degeneration pattern of the cartilage; and transmitting the degeneration pattern to a site for analysis. Another aspect of the invention is a kit for aiding in assessing the condition of cartilage in a joint of a mammal, which kit comprises a software program, which when installed and executed on a computer reads a cartilage degeneration pattern presented in a standard graphics format and produces a computer readout showing a cartilage thickness map of the degenerated cartilage. Another aspect of this invention is a method for assessing the condition of a subject's cartilage in a joint, the method comprises obtaining a three dimensional biochemical representation of the cartilage, obtaining a moφhological representation of the cartilage, and merging the two representations, and simultaneously displaying the merged representations on a medium. The merged representations are then used to assess the condition of a cartilage, estimate the loss of cartilage in a joint, determining the volume of cartilage loss in a region of cartilage defect, or estimating the change of a region of cartilage at a particular point in time or over a period of time.
A method for correlating cartilage image data, bone image data, and opto-electrical image data for the assessment of the condition of a joint, which method comprises (a) obtaining the bone image data of the joint with a set of skin reference markers positioned in externally near the joint, (b) obtaining the opto-electrical image data of the joint with a set of skin reference markers positioned in the same manner as (a), and (c) using the skin reference markers to correlate the images obtained in (a) and (b) with each other, wherein each skin reference marker is detectable in the bone data and the opto-electrical data. The method also can be used to further evaluate cartilage image data that is obtained using a similarly positioned set of skin reference markers.
Another aspect of the invention is a skin reference marker that comprises (a) a material detectable by an imaging technique; (b) a container for holding the material, (c) a material that causes the container to adhere to the skin of a human, and (d) a reflective material placed on the surface of the container.
Another aspect of the invention is a biochemical map of a cartilage that comprises a three- dimensional representation of the distribution of the amount of the biochemical component throughout the cartilage. Another aspect of the invention is a method for providing a biochemical based map of joint cartilage of a mammal, wherein the joint comprises cartilage and associated bones on either side of the joint, which method comprises (a) measuring a detectable biochemical component throughout the cartilage; (b) determining the relative amounts of the biochemical component throughout the cartilage; (c) mapping the amounts of the biochemical component in three dimensions through the cartilage; and (d) determining the areas of abnormal joint cartilage by identifying the areas having altered amounts of the biochemical component present. Another aspect of the invention is a method for deriving the motion of bones about a joint from markers placed on the skin, which method comprises (a) placing at least three external markers on the patient's limb segments surrounding the joint, (b) registering the location of each marker on the patient's limb while the patient is standing completely still and while moving the limb, (c) calculating the principal axis, principal moments and deformation of rigidity of the cluster of markers, and (d) calculating a correction to the artifact induced by the motion of the skin markers relative to the underlying bone.
Another aspect of the invention is a system for assessing the condition of cartilage in a joint of a human, which system comprises (a) a device for electronically transferring a cartilage degeneration pattern for the joint to a receiving device located distant from the transferring device; (b) a device for receiving the cartilage degeneration pattern at the remote location; (c) a database accessible at the remote location for generating a movement pattern for the joint of the human wherein the database includes a collection of movement patterns of human joints, which patterns are organized and can be accessed by reference to characteristics such as type of joint, gender, age, height, weight, bone size, type of movement, and distance of movement; (d) a device for generating a movement pattern that most closely approximates a movement pattern for the human patient based on the characteristics of the human patient; (e) a device for correlating the movement pattern with the cartilage degeneration pattern; and (f) a device for transmitting the correlated movement pattern with the cartilage degeneration pattern back to the source of the cartilage degeneration pattern.
A method for assessing the condition of the knee joint of a human patient, wherein the knee joint comprises cartilage and associated bones on either side of the joint, which method comprises (a) obtaining the patient's magnetic resonance imaging (MRI) data of the knee showing at least the bones on either side of the joint, (b) segmenting the MRI data from step (a), (c) generating a geometrical representation of the bone of the joint from the segmented MRI data, (d) assessing the patient's gait to determine the load pattern or the cartilage contact pattern of the articular cartilage in the joint during the gait assessment, and (e) correlating the load pattern or cartilage contact pattern obtained in step (d) with the geometrical representation obtained in step (c).
Another aspect of the invention is a method of assessing the rate of degeneration of cartilage in the joint of a mammal, wherein the joint comprises cartilage and the bones on either side of the cartilage, which method comprises (a) obtaining a cartilage degeneration pattern of the joint that shows an area of greater than normal degeneration, (b) obtaining a movement pattern of the joint that shows where the opposing cartilage surfaces contact, (c) comparing the cartilage degeneration pattern with the movement pattern of the joint, and (d) determining if the movement pattern shows contact of one cartilage surface with a portion of the opposing cartilage surface showing greater than normal degeneration in the cartilage degeneration pattern.
Another aspect of the invention is a method for monitoring the treatment of a degenerative joint condition in a mammal, wherein the joint comprises cartilage and accompanying bones on either side of the joint, which method comprises (a) comparing the movement pattern of the joint with the cartilage degeneration pattern of the joint; (b) determining the relationship between the movement pattern and the cartilage degeneration pattern; (c) treating the mammal to minimize further degeneration of the joint condition; and (d) monitoring the treatment to the mammal. Still another aspect of the invention is a method of assessing the condition of a joint in a mammal, wherein the joint comprises cartilage and accompanying bones on either side of the joint, which method comprises (a) comparing the movement pattern of the joint with the cartilage degeneration pattern of the joint; and (b) determining the relationship between the movement pattern and the cartilage degeneration pattern Other aspects of the invention may be apparent upon further reading the specification and claims of the patent application.
BRIEF DESCRIPTION OF THE DRAWINGS
hi the accompanying drawings: Figure 1 shows an overview schematic representation of some aspects of the invention of this application.
Figure 2 shows a DEFT pulse sequence.
Figure 3 shows the signal levels for cartilage and synovial fluid with RARE and DEFT pulse sequences, both TE = 14 miliseconds.
Figure 4 shows the mean contrast to noise ratio (CNR) of cartilage to joint fluid for various MRI pulse sequences. Figure 5 shows the mean contrast for cartilage and joint fluid for various MRI pulse sequences.
Figure 6 shows a DEFT acquisition using non-selective refocusing pulses to maximize the SNR efficiency and a partial K- Echo-Plainer acquisition gradients in order to minimize the required scan time for 3D volume.
Figure 7 shows four sample images acquired with a DEFT pulse sequence combined with a partial K- Echo-Plainer acquisition in order to provide efficient 3D coverage.
Figures 8 A and 8B show a 3 -point Dixon GRE image of the articular cartilage of medial fermorotibial compartment in a normal 35-year old volunteer. Figure 13 A has the subject in supine position and Figure 13B has the subject in an upright position.
Figures 9A — 9C show patient position and application of imaging coil and tracker coil for kinetic MR imaging of the knee. Patient is in upright weight-bearing position for active flexion and extension study of the knee.
Figure 9B is a 2D cartilage thickness map demonstrating abrupt decrease in cartilage thickness in the area of the defect (arrows). The Δ thickness between the neighboring pixels can be use to define the borders of the cartilage defect. Note defused cartilage thinning in the area enclosed by the asterisks (*).
Figures 10 A- IOC show a 3D surface registration of femoral condyles based on Tl - weighted spin-echo MR images. Figure 6A is a baseline with a knee and neutral position. 6B is a follow-up with knee and external rotation with a 3D view that is the identical to the one used in 6A but the difference in knee rotation is apparent. In Figure 6C, transformation and re-registration of Scan B into the object coordinate system of Scan A shows the anatomic match to A can be excellent.
Figure 11 A shows a 2D cartilage thickness map where a proton density fast spin-echo MR image demonstrates a focal cartilage defect in the posterior lateral fermoral condyle (black arrows). White arrows indicate endpoints of the thickness map.
Figure 12 shows the anatomic coordinate system in the femur and in the tibia.
Figure 13 shows calculation of the anatomic coordinate system from palpable bony landmarks.
Figure 14 shows additional marker names and locations for MR to optical cross registration.
Figure 15 shows the marker names and locations for the standard point-cluster technique protocol.
Figure 16 shows the error in the tibial location estimate for the rigid body model and the intrical deformation correction technique.
Figure 17 shows the error in tibial orientation estimate for the rigid body model and the interval deformation correction technique.
Figure 18A - 181 show functional joint imaging.
Figure 19 shows the superimposition of the tibiofemoral contact line onto the 3D cartilage thickness map.
Figure 20 shows the determination of the natural line of curvature as the cutting plain is rotated about the transepicondyear reference, the cartilage-plain intersection results in a curve.
Figure 21 shows the determination of the tibiofemoral contact line through the proximity detection and approach algorithm.
Figures 22A and 22B show a 2D MRI (3D SPGR) and 3D cartilage thickness map.
Figures 23 A - E show the matching of 3D thickness maps generated from MR images obtained with a knee neutral position and external rotation.
Figures 24A-C show inteφolation of the outer cartilage (OCS) surface across a cartilage defect using the inner cartilage surface (ICS) as a template.
Figure 24A shows that a volume of interest (VOI) is selected. The cartilage volume within this VOI is measured. Two points Pi and P2 on the OCS are selected on either side of the defect. The distances di and d2 to the ICS are measured. Figure 24B shows that the ICS-OCS distance values between Pi and P2 can be determined by means of a linear inteφolation.
Figure 24C shows that the inteφolated OCS can be constructed using the inteφolated distance values.
SPECIFIC DESCRIPTION
Overview
Figure 1 is a schematic overview of some of the various aspects of the invention. While a complete description of the many aspects of the invention is found in the specification and claims, the schematic overview gives some of the broad aspects of the invention.
This invention relates to assessing the condition of a joint in a mammal. One aspect is a method for such an assessment. The assessment can be done using internal images, or maps, of the cartilage alone or in combination with a movement pattern of the joint. If used alone, a map obtained at an initial time is compared with a map obtained at a later time to provide a view of the change in cartilage over time. Another aspect is a method is comparing the movement pattern for a joint of a subject being studied with the cartilage degeneration pattern of the subject, then determining the relationship between the movement pattern and the degeneration pattern. If, in determining the relationship between the two patterns, one finds that the movement pattern has caused the degeneration pattern or will continue to adversely affect the degeneration pattern, therapy can be prescribed to minimize the adverse effects, such as further degeneration or inflammation.
hi overview, some of the systems and methods of this invention are illustrated by the flow chart in the attached Figure 1. Figure 1 is based on the full range of processes, preferably applied to a knee and surrounding cartilage.
In Figure 1, the first step 10 represents obtaining an image of the cartilage itself. This is typically achieved using MRI techniques to take an image of the entire knee and then, optionally, manipulating (e.g., "subtracting out" or "extracting") the non-cartilage images as shown in step 12. Non-cartilage images typically come from bone and fluid. Preferably, the MRI is taken using external markers to provide reference points to the MRI image (step 11).
If the cartilage is imaged with a 2D MRI acquisition technique, the resulting stack of 2D images so obtained can be combined into a 3D image, as indicated in step 14. A preferred alternative is to use 3D MRI acquisition techniques to acquire a 3D image directly. In either case, the same "non-cartilage image extraction techniques referred to in step 12 can be used.
With a full 3D image captured, various "maps" or displays of the cartilage can be constructed to give a cartilage degeneration pattern. This is represented by step 16. One such display can, for example, be a color-coding of a displayed image to reflect the thickness for the cartilage. This will allow easy visual identification of actual or potential defects in the cartilage.
Together with or independently of the cartilage imaging, and as represented by parallel step 20, a 3D image of the knee joint is taken, again preferably using MRI. Many of the same techniques as applied in steps 10 to 14 are used to do this. However, as illustrated by sub- step 22, it is useful to define and register a skin-external frame of reference around the joint. This is achieved by placing fiduciary markers on the skin around the outside of the knee (step 22) prior to taking the image.
In addition to an image extraction technique (as described above in step 12), an image is manipulated to enhance the image of the position of the markers (step 24). The resulting manipulated image is used to give a 3D image of the joint and associated bones (step 26).
With the markers in place, and as shown by step 30, an additional set of markers is placed on the skin along the outside of the leg, and an external image of the limb is obtained. Using at least two cameras, images are then taken of the subject in a static state. In addition, images are also taken of the subject while moving. This is shown collectively by step 32. The images obtained are then processed to relate the movement of the skin relative to the bone. In addition, certain calculations are performed, for example, the center of mass is calculated. These manipulations are shown in Step 34. Further, as the fiduciary markers are still in place during the video image capture, a correlation between the fiduciary and the additional set of markers can be made. This is shown in step 36. Once this marker-to-marker correlation is made, the static 3D image of the joint (with associated fiduciary markers) and the movement images of the leg bones (also with fiduciary markers in place) can be combined. The fiduciary markers, therefore, serve as baseline references. The combination (step 40) of 3D cartilage image (from step 14), 3D knee joint image (step 26), and the moving leg co-ordinates (step 34) will, after appropriate corrections, result in a displayable, 3D motion image of the joint moving as per step 46.
The moving images, showing the contact areas of the knee joint can be used in conjunction with the various "maps" or displays generated at step 16 to provide a visual indication of potential or actual cartilage defects and help in determining their relation between movement and degeneration patterns. This is shown in step 48.
Furthermore, as the various images are supported by actual mathematical quantification, real measurements (such as cartilage thickness) can be taken and compared with later or earlier measurements and/or imaging. This allows the tracking of the progression of a defect, or conversely, continued tracking of healthy cartilage. This aids a health worker in providing therapy for the patients. The method allows monitoring and evaluation of remedial actions as well as possible treatment prescriptions.
Thus, this invention discloses, for example, a method to examine the relationship between articular cartilage moφhology and the functional load bearing areas of a knee joint measured during movement. The method includes enhanced imaging techniques to reconstruct the volumetric and biochemical parameters of the articular cartilage in three dimensions; and a method for in vivo kinematic measurements of the knee. The kinematic measurement permits direct in vivo measurements of complete six-degrees of freedom motion of the femur or the tibia or associated bones during normal activities. This permits the study of load bearing of articular cartilage during movement, hi particular, this method can aid in locating cartilage defects relative to the changing load bearing areas of the knee joint during daily activities. While the various aspects of the invention are useful in mammals generally, they are particularly useful for human patients. Obtaining the Cartilage Degeneration Pattern
Imaging Articular Cartilage
hi general, the joint of a patient is that place of union, more or less movable, between two or more bones. A joint comprises cartilage and other elements such as the accompanying bones on either side of the joint, fluid, and other anatomical elements. Joints are classified into three general moφhological types: fibrous, cartilaginous, and synovial. This invention is particularly useful for assessing synovial joints, particularly the knee.
In obtaining an image of the cartilage of a joint in a mammal, a number of internal imaging techniques known in the art are useful for electronically generating a cartilage image. These include magnetic resonance imaging (MRI), computed tomography scanning (CT, also known as computerized axial tomography or CAT), and ultrasound imaging techniques. Others maybe apparent to one of skill in the art. MRI techniques are preferred.
MRI, with its superior soft tissue contrast, is the best technique available for assessing tissue and its defects, for example articular cartilage and cartilage lesions, to obtain a cartilage degeneration can provide moφhologic information about the area of damage. Specifically, changes such as fissuring, partial or full thickness cartilage loss, and signal changes within residual cartilage can be detected.
The reason MR imaging techniques are particularly suitable for cartilage is because they can provide accurate assessment of cartilage thickness, demonstrate internal cartilage signal changes, evaluate the subchondral bone for signal abnormalities, and demonstrate moφhologic changes of the cartilage surface.
MRI provides several important advantages over other techniques in this invention. (However, other imaging techniques, such as ultra sound imaging, are adequate for many purposes and can be used in the practice of the invention without limit.) One advantage of MRI is good contrast between cartilage, bone, joint fluid, ligaments, and muscle in order to facilitate the delineation and segmentation of the data sets. Another is the coverage of the entire region of interest in a single scan within acceptable acquisition times. For a brief discussion of the basic MRI principles and techniques, see MRI Basic Principles and Applications, Second Edition, Mark A. Brown and Richard C. Semelka, Wiley-Liss, Inc. (1999).
MRI employs pulse sequences that allow for better contrast of different parts of the area being imaged. Different pulse sequences are better fitted for visualization of different anatomic areas, for example, hyaline cartilage or joint fluid. More than one pulse sequence can be employed at the same time. A brief discussion of different types of pulse sequences is provided below.
High Resolution 3D MRI Pulse Sequences
Routine MRI pulse sequences available for imaging tissue, such as cartilage, include conventional Tl and T2-weighted spin-echo imaging, gradient recalled echo (GRE) imaging, magnetization transfer contrast (MTC) imaging, fast spin-echo (FSE) imaging, contrast enhanced imaging, rapid acquisition relaxation enhancement, (RARE) imaging, gradient echo acquisition in the steady state, (GRASS), and driven equilibrium Fourier transform (DEFT) imaging. As these imaging techniques are well known to one of skill in the art, e.g. someone having an advanced degree in imaging technology, each is discussed only generally hereinafter. While each technique is useful for obtaining a cartilage degeneration pattern, some are better than others.
Conventional Tl and T2-Weighted Spin-Echo Imaging
Conventional Tl and T2-weighted MRI depicts articular cartilage, and can demonstrate defects and gross moφhologic changes. Tl -weighted images show excellent intra- substance anatomic detail of hyaline cartilage. However, Tl -weighted imaging does * not show significant contrast between joint effusions and the cartilage surface, making surface irregularities difficult to detect. T2-weighted imaging demonstrates joint effusions and thus surface cartilage abnormalities, but since some components of cartilage have relatively short T2 relaxation times, these are not as well depicted as other preferred imaging. Gradient-Recalled Echo Imaging
Gradient-recalled echo imaging has 3D capability and ability to provide high resolution images with relatively short scan times. Fat suppressed 3D spoiled gradient echo (FS-3D- SPGR) imaging has been shown to be more sensitive than standard MR imaging for the detection of hyaline cartilage defects in the knee.
Magnetization Transfer Contrast Imaging
Cartilage, as well as other ordered tissues, demonstrate the effects of magnetization transfer. Magnetization transfer imaging can be used to separate articular cartilage from adjacent joint fluid and inflamed synovium.
Fast Spin-Echo Imaging
Fast spin-echo imaging is another useful pulse sequence to evaluate articular cartilage. Incidental magnetization transfer contrast contributes to the signal characteristics of articular cartilage on fast spin-echo images and can enhance the contrast between cartilage and joint fluid. Sensitivity and specificity of fast spin-echo imaging have been reported to be 87% and 94% in a study with arthroscopic correlation.
Contrast Enhanced Imaging
The use of gadolinium for imaging of articular cartilage has been applied in several different forms. Direct magnetic resonance (MR) arthrography, wherein a dilute solution containing gadolinium is injected directly into the joint, improves contrast between cartilage and the arthrographic fluid. Indirect MR arthrography, with a less invasive intravenous injection, can also been applied. Gadolinium enhanced imaging has the potential to monitor glycosaminoglycan content within the cartilage, which may have implications for longitudinal evaluations of injured cartilage. Driven Equilibrium Fourier Transform
Another 3D imaging method that has been developed is based on the driven equilibrium fourier transform (DEFT) pulse sequence (U.S. Patent No. 5,671,741), and is specifically designed for cartilage imaging. DEFT provides an effective tradeoff between T2/T1 weighting and spin density contrast that delineates the structures of interest in the knee. Contrast-to-noise ratio between cartilage and joint fluid is greater with DEFT than with spoiled gradient echo (SPGR). DEFT is an alternative approach to SPGR. DEFT contrast is very well suited to imaging articular cartilage. Synovial fluid is high in signal intensity, and articular cartilage intermediate in signal intensity. Bone is dark, and lipids are suppressed using a fat saturation pulse. Hence, cartilage is easily distinguished from all of the adjacent tissues based on signal intensity alone, which will greatly aid segmentation and subsequent volume calculations.
The basic DEFT pulse sequence is shown in Fig. 2. A conventional spin echo pulse sequence was followed by an additional refocusing pulse to form another echo, and then a reversed, negated, excitation pulse to return any residual magnetization to the +z axis. This preserved the magnetization of longer T2 species, such as synovial fluid. Typical MRI parameters for cartilage are a Tl -relaxation time of 900 Milliseconds (ms) and a T2- relaxation time of 40 ms, while synovial fluid has a Tl -relaxation time of 3000 ms and a T2- relaxation time of 200 ms. In addition, synovial fluid has a 30% greater proton density than cartilage. The signal levels of cartilage and synovial fluid were plotted in Fig. 3 for a RARE pulse sequence and for DEFT, and show that DEFT maintains excellent contrast for any relaxation time (TR). It achieves this contrast while maintaining a signal-to-noise ratio (SNR) efficiency (SNR/ (Tacqu Sition)) that is equal to or better than other methods with much lower contrast, such as Tl -weighted GRASS.
DEFT was compared with a fast spin-echo (FSE), a gradient-echo (GRE), and a spoiled gradient-echo (SPGR) sequence with parameters similar to the ones published by Disler et al. The patella was scanned in 10 normal volunteer knees using a 1.5T whole-body system (GE Signa) with a 3 inch surface coil. All images were acquired with field of view (FOV) 10x10 cm, matrix 256x256 elements, slice thickness 4 mm using fat-saturation. DEFT (400/15 [TR/TE in msec], 2 NEX (number of excitations), FSE (3500/15, echo train length [ETL] 8, 2 NEX (number of excitations), FSE (3500/15, ETL 4, 2 NEX), GRE (400/20, 30°, 2 NEX), and SPGR (50/15, 30° [flip angle], 2 NEX) images were obtained. Contrast-to- noise ratios (CNR) between cartilage and joint fluid were calculated as:
CNR = I (Sl oint Fluid - Si-Cartilage) / Slβackground Noise I Eq. 1
Contrast (C) between cartilage and joint fluid was calculated as:
C = I [(Sljoint Fluid - SIcartilage) / Sljoint Fluid ] X 100 | Eq. 2.
In the equations SI is signal intensity. DEFT demonstrated greater contrast-to-noise ratio and contrast between cartilage and joint fluid than SPGR, GRE, and FSE sequences (Figs. 4 & 5). Cartilage had intermediate signal intensity with DEFT, while joint fluid was high in signal intensity. The difference in CNR between DEFT and SPGR was statistically significant (p<0.001). Cartilage moφhology, i.e. cartilage layers, were consistently best delineated with the DEFT sequence. At the resolution used in this study, FSE sequences suffered from image blurring. Blurring was improved with ETL 4 when compared to ETL8; nonetheless, even with ETL 4, cartilage moφhology seen on FSE images was inferior to the DEFT sequence. In light of these results, DEFT imaging is a preferred MRI technique.
Another Application of DEFT
DEFT was combined with a partial k-space echo-planar data acquisition. This pulse sequence is illustrated in Fig. 6 above. A slab selective pulse in z defines the imaging volume, which is then resolved with phase-encoding gradients in the y and z axes, and an oscillating EPI gradient in the x axis.
Example images acquired with this approach are shown in Fig. 7. This case was optimized for resolution, in order to image the patellar cartilage. The EPI readout acquired 5 echoes for each DEFT sequence. Partial k-space acquisition collected only 60% of the data along the x-axis. Correction for the missing data was performed using a homodyne reconstruction. The image matrix was 192x192x32, with a resolution of 0.5x0.5x2.5 mm, resulting in a 10x10x8 cm FOV. The echo time TE was 22 ms, and the TR was 400 ms. Fat was suppressed with a fat presaturation pulse. The total scan time for this acquisition was 5 minutes. Additional image studies that can be performed using this approach may require greater spatial coverage, but one can permit slightly less spatial resolution, and a longer scan time similar to the one used with the 3D SPGR approach. If one relaxes the resolution to 0.75x0.75x1.5 mm, and doubles the z slab thickness and z phase encodes, the result will be a FOV of 15x15x16 cm, and a total scan time of approximately 15 minutes, which exactly fits the desired scan protocol. Similar to the 3D SPGR acquisition, one can acquire a first 3D DEFT scan in the sagittal plane with fat saturation. The 3D DEFT acquisition can then be repeated without fat saturation using the identical parameters and slice coordinates used during the previous acquisition with fat saturation. The resultant non-fat-saturated 3D DEFT images can be used for 3D rendering of the femoral and tibial bone contours.
h summary, Driven Equilibrium Fourier Transform is a pulse sequence preferred for cartilage imaging that provides higher contrast-to-noise ratios and contrast between cartilage and joint fluid than SPGR, GRE, and FSE sequences. Cartilage moφhology is better delineated with DEFT sequences than with SPGR, GRE, and FSE images. The combination of high anatomic detail and high cartilage-joint fluid CNR and contrast may render this sequence particularly useful for longitudinal studies of cartilage in patients with osteoarthritis.
A Representative Example of MR Imaging is described below:
A MR image can be performed using a whole body magnet operating at a field strength of 1.5 T (GE Signa , for example, equipped with the GE SR-120 high speed gradients [2.2 Gauss/cm in 184μsec risetimes]). Prior to MR imaging, external markers filled with Gd- DTPA (Magnevist®, Berlex Inc., Wayne, N.J.) doped water (Tl relaxation time approximately 1.0 sec) can be applied to the skin around the knee joint and optionally at the same positions used for gait analysis in a biomotion laboratory (discussed below). The external markers can be included in the field of view of all imaging studies. Patients can be placed in the scanner in supine position. After an axial scout sequence, coronal and sagittal Tl-weighted images of the femur can be acquired using the body coil (spin-echo, TR=500msec, TE=15msec, 1 excitation (NEX), matrix 256x128 elements, field of view (FOV) 48 cm, slice thickness 7 mm, interslice spacing 1 mm). The scanner table can then be moved to obtain coronal and sagittal images of the knee joint and tibia using the same sequence parameters. These Tl-weighted scans can be employed to identify axes through the femur and tibia which can be used later for defining the geometry of the knee joint. The knee can then be placed in the knee coil with the joint space located in the center of the coil. The knee can be secured in the coil with padding. Additionally, the foot and ankle region can be secured in neutral position to the scanner table using adhesive tape in order to minimize motion artifacts. A rapid scout scan can be acquired in the axial plane using a gradient echo sequence (GRASS, 2D Fourier Transform (2DFT), TR=50msec, TE=10msec, flip angle 40°, 1 excitation (NEX), matrix 256x128 elements, field of view (FOV) 24 cm, slice thickness 7 mm, interslice spacing 3 mm). This scout scan can be used to demonstrate the position of the knee joint space in the coil and to prescribe all subsequent high resolution imaging sequences centered over the joint space. Additionally, using the graphic, image based sequence prescription mode provided with the scanner software, the scout scan can help to ensure that all external markers around the knee joint are included in the field of view of the high resolution cartilage sensitive MR sequences.
There are several issues to consider in obtaining a good image. One issue is good contrast between cartilage, bone, joint fluid, ligaments, and muscle in order to facilitate the delineation and segmentation of the data sets. Another is the coverage of both condyles of the knee in a single scan within acceptable acquisition times. In addition, if there are external markers, these must be visualized. One way to address these issues is to use a three-dimensional spoiled gradient-echo sequence in the sagittal plane with the following parameters (SPGR, 3DFT, fat-saturated, TR=60msec, TE=5msec, flip angle 40°, 1 excitation (NEX), matrix 256x160 elements, rectangular FOV 16x12 cm, slice thickness 1.3 mm, 128 slices, acquisition time approximately 15 min). Using these parameters, one can obtain complete coverage across the knee joint and the external markers both in mediolateral and anteroposterior direction while achieving good spatial resolution and contrast-to-noise ratios between cartilage, bone and joint fluid (Figs. 8 and 9). The fat-saturated 3D SPGR sequences can be used for rendering the cartilage in three dimensions (see description below). The 3D SPGR sequence can then be repeated in the sagittal plane without fat saturation using the identical parameters and slice coordinates used during the previous acquisition with fat saturation. The resultant non-fat-saturated 3D SPGR images demonstrate good contrast between low signal intensity cortical bone and high signal intensity bone marrow thereby facilitating 3D rendering of the femoral and tibial bone contours. It is to be understood that this approach is representative only and should not be viewed as limiting in any way.
Volumes of Interest (VOI)
The invention allows a health practitioner to determine cartilage loss in a reproducible fashion and thus follow the progression of a cartilage defect over time.
In one embodiment of the invention, one can use a 2D or a 3D surface detection technique to extract the surface of the joint, e.g. the femoral condyles, on both baseline and follow-up scans. For example, a Tl-weighted spin-echo sequence can be used for surfaces extraction of the femoral condyles. The Tl-weighted spin-echo sequence provides high contrast between low signal intensity cortical bone and high signal intensity fatty marrow. For detection of the surface of the femoral condyles, a step-by-step problem solving procedure, i.e., an algorithm, can convolve a data set with a 3D kernel to locate the maximum gradient location. The maximum gradient location corresponds to the zero crossing of a spatial location. When the kernel is designed properly, then there will be only one zero crossing in the mask. Thus, that zero crossing is the surface. This operation is preferably three- dimensional rather than two-dimensional. The surface of the joint, e.g. the femoral condyles, on the baseline scan can be registered in an object coordinate system A. The surface of the joint, e.g. the femoral condyles, on the follow-up scan can be registered in an object coordinate system B. Once these surfaces have been defined, a transformation B to B' can be performed that best matches B' with A. Such transformations can, for example, be performed using a Levenberg Marquardt technique. Alternatively, the transformations and matching can be applied to the cartilage only. The same transformation can be applied to the cartilage sensitive images on the follow-up scan in order to match the cartilage surfaces.
Using the 3D surface registration of the joint on the baseline scan and resultant object coordinate system A, one can place volumes of interest over the area of a cartilage defect seen on the cartilage sensitive images. For example, in the knee joint, the size of the targeted volumes of interest can be selected to exceed that of the cartilage defect in anteroposterior and mediolateral direction, e.g. by 0.5 to 1 cm. If the defect is located high on the femoral condyle or in the trochlear region, the targeted VOI can be chosen so that its size exceeds that of the cartilage defect in superoinferior and mediolateral direction. The third dimension of the targeted VOI (parallel to the surface normal of the cartilage) can be fixed, for example at 1 cm. VOI size and placement can be manual or automatic on the baseline study. Once the targeted VOI has been placed on the image using visual or automated computer control, the 3D coordinates of the targeted VOI relative to the 3D contour of the joint and object coordinate system A can be registered and saved. On follow- up studies, e.g. scans inadvertently obtained with slightly different patient position, the 3D surface of the joint is registered to match the orientation of the baseline scan and the targeted VOI is then automatically placed on the joint using object coordinate system B' and the coordinates saved on the baseline study. Cartilage volume within the targeted VOI on baseline and follow-up studies can, for example, be determined using standard thresholding and seed growing techniques.
Reference markers
When obtaining the MR images for use in this invention, whether the MRI is of cartilage or of bone, external reference markers can be placed on the skin around the joint of the subject being imaged. The external marker can be designed not only to show up in the MRI, but also to show up if an external image of the joint is obtained. The importance and value of such unique reference markers will be discussed in more detail hereinafter.
Thus, one embodiment of the invention is a skin reference marker that can be used in the assessment of the condition of a joint of a human. Multiple skin reference markers can be placed upon one or more limbs of a patient prior to internal imaging and external imaging. Each skin reference marker comprises a material detectable by an imaging technique, a container for the material in which the container preferably has multiple surfaces, a means for affixing the container to the skin (e.g. an adhesive placed on at least one surface of the container in an amount sufficient to adhere the container to the skin of a human), and a reflective material (preferably retro-reflective) placed on another surface of the container located away from the adhesive. Several imaging techniques can be used that are able to detect the marker. For example, magnetic resonance imaging is preferred, but, ultrasound, or X-ray are also useful. In the case of X-ray, further manipulations must be performed in which multiple X-ray images are assimilated by a computer into a 2 dimensional cross- sectional image called a Computed Tomography (CT) Scan. The material detectable by an imaging can be either in a liquid form or a solid form. The material can be any imaging contrast agent or solution, e.g. a paramagnetic material. The material can be a lanthanide, such as one belonging to the yttrium group of rare earth metals. More specifically, the material can be gadolinium. The shape of the container can be any shape allowing it to be placed on the skin of a human. For example, it can be cubical, spherical, elliptical, discoid or cylindrical. The size of the container can be any size, but optimally a size allowing it to be recorded by an imaging machine. The longest dimension of the container can be up to 5.0 cm, but preferably is about 0.25 to 2.0 cm. The reflective or retro-reflective material can be any material that is able to reflect light directly back to the source of the light so that the position of the reference marker is captured by the opto-electrical recording means, e.g. a video camera. 3M Coφoration makes several retro-reflective materials.
Manipulating Images
Once a magnetic resonance image is obtained, it can be manipulated to improve the image by reducing unwanted, non-cartilage images.
Segmentation
To prepare the data set for 3D rendering, the cartilage can be segmented image by image using a signal-intensity-based threshold combined with a seed growing technique. The femoral, tibial, and patellar cartilage can be segmented separately based on the fat-saturated 3D SPGR or 3D DEFT sequence. Manual disarticulation can be performed by outlining the cartilage contour in areas where the signal intensity of the articular cartilage is similar to that of adjacent structures. The contours of the femoral, tibial, and patellar bone can be segmented separately using the non-fat-saturated 3D SPGR or 3D DEFT sequence. Segmentation software can allow for manual editing of cartilage thickness maps and cartilage defects detected using the above embodiments. In this fashion, the operator can correct erroneous detection of cartilage defects in areas where the cartilage may be naturally thinner. Such software includes seed-growing algorithms and active-contour algorithms that are run on standard PC's. A shaφ interface is present between the high signal intensity bone marrow and the low signal intensity cortical bone thereby facilitating seed growing. Fat-saturated and non-fat-saturated 3D sequences can be acquired with the same field of view, slice thickness and slice positions, thereby enabling superimposition and cross registration of any resultant 3D renderings of the femoral, tibial, and patellar cartilage and bone. External reference markers can aid in registering the 3D data in the same object coordinate system.
3D maps of cartilage thickness can be generated using several different techniques. One representative, but not limiting, approach uses a 3D surface detection technique which is based on a 2D edge detector (Wang-Binford) that has been extended to 3D. This surface detection technique can generate surface points and their corresponding surface normal. To smooth the contour, the program samples 25 percent of the surface points and fits a cubic spline to the sample points. The program can compute the curvature along sample spline points and find two sample points that have the maximum curvature and are separated by about half the number of voxels on the contour. These points partition the spline into two subcontours. For each subcontour, the program can compute the average distance between the points and the center of the mass. The program can designate the subcontour with the smaller average distance as the inner cartilage surface and the other subcontour as the outer cartilage surface (OCS). The intersect between the inner cartilage surface (ICS) (located at the subchondral bone interface) and the outer cartilage surface with the surface normal can be used to compute the 3D thickness of the articular cartilage on a pixel-by-pixel basis.
Creating A Three Dimensional (3D) Image of the Cartilage
Three Dimensional Geometric Model Generation
After the 3D image of cartilage and the 3D image of joint with bones (as discussed hereinafter), are obtained, for example, the set of segmented two dimensional MR images can be transformed to a voxel representation using a computer program developed in the AVS Express (Advanced Visual Systems, Inc., Waltham, MA). Every voxel has a value of zero if it is not within an object of interest or a value ranging from one to 4095, depending on the signal intensity as recorded by the MRI machine. An isosurface can then be calculated that corresponds to the boundary elements of the volume of interest. A tesselation of this isosurface can be calculated, along with the outward pointing normal of each polygon of the tesselation. These polygons are written to a file in a standard graphics format (Virtual Reality Modeling Language Version 1.0: VRML output language).
Visualization Software One possible choice for the software program used to assess the cartilage degeneration pattern, the bones of the joint, and the motion pattern of the patient is a user controllable 3D visual analysis tool. The program can read in a scene, which scene consists of the various 3D geometric representations or "actors" (for example, VRML files of the tibia, tibia cartilage, femur, femoral cartilage), the static relationship transformations between these actors, and, if available, sequence of transformations describing how these actors move with respect to each other as the patient performs some activity, such as walking, jogging, etc.
The program can allow the user, through the use of the mouse and or keyboard, the ability to observe the scene from arbitrary angles; to start and stop the animation derived from the motion profiles and to observe the contact line and any cartilage lesions while the animation is running. Additionally, the user can derive quantitative information on the scene through selecting points with the mouse.
The software program can be written in the CTT computer language and can be compiled to run on both Silicon Graphics Workstations and Windows/Intel personal computers.
Cartilage thickness maps
Cartilage thickness can be determined by several methods. One example is detecting the locations of the bone - cartilage and the cartilage - joint fluid interface along the surface normal using the same edge detector described below, and subtracting them. This procedure can be repeated for each pixel located along the bone - cartilage interface. The x, y, and z position of each pixel located along the bone - cartilage interface can be registered on a 3D map or multiple 2D maps and thickness values are translated into color values. In this fashion, the anatomic location of each pixel at the bone cartilage interface can be displayed simultaneously with the thickness of the cartilage in this location. The edge detector can produce accurate surface points and their corresponding surface normal. The detector can be applied to the baseline and the follow-up data set. For the baseline data set, both the surface points and surface normals can be used to form locally supporting planes (for each voxel). These planes can form an approximated surface for the baseline skeletal site. As for the follow-up data set, the surface points can be matched in the registration procedure onto the surface of the baseline data set. One can use a newly developed 3D surface detection technique to extract the surface of the skeletal site on both the baseline scan and the follow-up scan. Once these surfaces are detected, one can use the Levenberg Marquardt procedure to find the transformation that best matches these two surfaces.
A possible approach for calculating the cartilage thickness is based on a 3D Euclidian distance transformation (EDT). After thresholding, the voxels on the edge of the cartilage stiucture can be extracted using a slice by slice 8-neighbor search, resulting in a binary volume with the voxels on the cartilage surface having a value of 1 and all others being 0. To classify these surface points as part of the ICS or OCS, a semi-automatic approach, which requires the user to enter a point that lies outside the cartilage structure and faces the ICS, can be useful. From this point, rays are cast in all directions of the volume using a modified Bresenham's line drawing algorithm. If a ray hits a voxel with a value of 1, this point is classified as part of the ICS. After a complete sweep of the volume, for initialization of the EDT the ICS voxels are given a value of 0, whereas all other voxels are set to 1.
For computation of the EDT, the following representative algorithm can be useful. It can decompose the calculation into a series of 3 one-dimensional transformations and can use the square of the actual distances, which accelerates the process by avoiding the determination of square roots.
First, for a binary input picture F = { } (l ≤ i ≤ L, l ≤ j ≤ M, l ≤ k ≤ N) a new picture G={gijk} can be derived using equations (3-5) (α, β, and γ denote the voxel dimensions). Here F is a set of all voxels initially and G is a set of all voxels at the later time.
gijk = in{( (i -x))2;fxjk = 0;X ≤ x ≤ L} [Eq. 3] Thus, each point can be assigned the square of the distance to the closest feature point in the same row in i-direction. Second, G can be converted into using equation (4).
hiJk = min{giyk + (^ (j - y)Y;X ≤ y ≤ M} [Eq. 4]
The algorithm can search each column in the j -direction. According to the Pythagorean theorem, the sum of the square distance between a point (i,j,k) and a point (i,y,k) in the same column, (β(j - y))2, and the square distance between (i,y,k) and a particular feature point, giyk, equals the square distance between the point (i,j,k) and that feature point. The minimum of these sums is the square distance between (i,j,k) and the closest feature point in the two- dimensional i-j -plane.
The third dimension can be added by equation (5), which is the same transformation as described in the equation for the k-direction (4).
sijk = min{hϋ, + (y (k -z))2;X ≤ z ≤ N} [Eq. 5]
After completion of the EDT, the thickness of the cartilage for a given point (a,b,c) on the OCS equals the square root of sa C. The x, y, and z position of each pixel located along the bone - cartilage interface can be registered on a 3D map and thickness values are translated into color values. In this fashion, the anatomic location of each pixel at the bone cartilage interface can be displayed simultaneous with the thickness of the cartilage in this location.
Displaying the Degeneration Pattern
In an approach the cartilage thickness maps obtained using the algorithm described above display only a visual assessment of cartilage thickness along the articular surface. In another approach, in order to derive a true quantitative assessment of the location, size, and depth of a focal cartilage defect, one can use an iterative approach comparing cartilage thickness of neighboring pixels located along the bone cartilage interface.
For example, assuming an image resolution of 0.5 x 0.5 x 1.0 mm and an average thickness of the articular cartilage in the femoral condyles ranging between 2 to 3 mm, a 25% decrement in cartilage thickness will be the smallest change that can be observed with most current imaging sequences. Therefore, for example, pixels along the bone - cartilage interface that demonstrate a decrease exceeding the smallest change observable on a given MRI pulse sequence, in this example 25% or greater, in overlying cartilage thickness when compared to cartilage thickness at the neighboring bone - cartilage interface pixels, can be used to define the margins of a focal cartilage defect. Other criteria can be employed to define a cartilage defect based on comparisons of neighboring pixels. For example, a fixed value can be used. If the difference in cartilage thickness between neighboring pixels exceeds the fixed value, e.g. 1 mm, the pixel where this difference is observed can be used to define the margin of the cartilage defect. This comparison can be performed for each pixel located along the bone — cartilage interface for the entire data set. This comparison is preferably performed in three dimensions. Pixels that demonstrate a decrease in cartilage thickness exceeding defined criteria but that are completely surrounded by other pixels fulfilling the same criteria may not be considered to be part of the margin of the cartilage defect, but will typically be considered to lie inside the cartilage defect.
The invention provides for means for calculating the area covered by the cartilage defect Acartiiage defect and the mean thickness of the cartilage in the region of the defect Dcartiiage defect as well as the mean thickness of a defined area of surrounding normal cartilage. The thickness of the cartilage previously lost in the defect can be estimated then as:
■ 'cartilage loss — AAiormal cartilage " Dcartilage defect LE .Oj .
Since the area A of the cartilage defect is known, the volume of cartilage loss can be computed as:
V cartilage loss ~ -"-cartilage defect X cartilage loss L-^Q- ' J •
Thus, the invention provides for means of estimating the thickness, area or volume of cartilage tissue that has been lost.
In another embodiment, the cartilage is segmented slice by slice from MR images.
This can be achieved, for example, using the live wire method or snakes. After segmentation, a volume of interest (VOI) containing a single cartilage defect can be selected. The cartilage volume Ni within this NOI can be determined. In each slice that contains the defect, two points Pi and P2 on the outer cartilage surface (OCS) can be selected on either side of the defect (Fig.24, A). The OCS contour of the cartilage defect between Pi and P can be erased and inteφolated using the inner cartilage surface (ICS) as a guiding line. For this puφose, the distances di and d2 between the OCS at Pi and P2 and the ICS can be measured. For OCS reconstruction the OCS-ICS distance can be determined by linear inteφolation between di and d2 (Fig.24, B). The inteφolated distance values can be used to determine a set of inteφolated surface points for the reconstructed OCS (Fig.24, C). The surface contour between Pi and P2 can be determined with a spline curve that inteφolates this set of OCS points. Subsequently, the cartilage volume N2 can be measured, using the same NOI as for Ni.. The difference N2-Nι between the two volumes can yield the volume of the cartilage defect.
The depth of the cartilage defect can, for example, be determined as follows: for all points on the inteφolated OCS in all the slices containing the defect contour the distance to the closest point of the original OCS can be measured by means of a 3-dimensional
Euclidean distance transfonn. The longest distance value resulting from this computation is typically the depth of the cartilage defect.
The area of the cartilage defect can, for example, be determined as follows: for all the slices that contain the defect, the length of the inteφolated OCS can be computed. The sum of these length values, multiplied by the slice thickness, can yield an estimation of the total area of the inteφolated OCS contour and thus the area of the cartilage defect.
In another embodiment, the invention provides for means to directly compare the volume, depth, and area of an articular cartilage defect between different MR examinations without having to register the data sets. Thus, the invention can be used to monitor the progression of osteoarthritis. As an additional example of how this technique can be applied, the invention can be used to monitor the effect of disease therapy. In another embodiment, the invention can be used to collect epidemiological data on the volume, depth, and area of articular cartilage defects in different locations of the femur, tibia, and patella.
The invention provides means to accurately measure the volume, depth, and area of a cartilage defect. Furthermore, the comparison between the values for different MR examinations can be performed without registration of the data sets. Turning now to Figures 22A and 22B, one can see a 2D MRI (3D SPGR) and 3D cartilage thickness map. In A, the 2D MRI demonstrates a full thickness cartilage defect in the posterior lateral femorl condyle (arrows). Figure 22B shows a 3D cartilage thickness map generated using a 3D Euclidian distance transformation. The thickness of the articular cartilage is color encoded and displayed on a pixel-by-pixel basis along the 3D surface of the articular cartilage. The cartilage defect is black reflecting a thickness of zero (arrows) (M: medial, L: lateral, S: superior, I: inferior).
In Figures 23 A - 23E, one can see the matching of 3D thickness maps generated from MR images obtained with the knee in neutral position and in external rotation. A. Sagittal baseline MR image (3D SPGR) with the knee in neutral position. B. Sagittal follow-up MR image of the same volunteer obtained two weeks later with the knee in 40 degree external rotation (note the artificially widened appearance of the femur resulting from the rotation). C. 3D thickness map generated based on baseline MRI in neutral position. D. 3D thickness map generated based on follow-up MRI in external rotation (note segmentation error between condyles in trochlear region). E. Transformation of D into the object coordinate system of C. Despite extreme differences in joint orientation between baseline and follow- up MRI scans and despite segmentation errors, the thickness distribution on the matched follow-up scan demonstrates great similarity with that seen on the baseline scan in neutral position (in C).
Having now described how to obtain an image of a cartilage of a joint, both with and without external reference markers; how to enhance the image by manipulating non- cartilage images, and creating and displaying 3-D images of the cartilage, t.e. a 3-D map, certain aspects of the invention are apparent.
One aspect is a method of estimating the loss of cartilage in a joint. The method comprises
(a) obtaining a three-dimensional map of the cartilage at an initial time and calculating the thickness or regional volume of a region thought to contain degenerated cartilage so mapped at the initial time,
(b) obtaining a three-dimensional map of the cartilage at a later time, and calculating the thickness or regional volume of the region thought to contain degenerated cartilage so mapped at the later time, and (c) determining the loss in thickness or regional volume of the cartilage between the later and initial times.
Preferably, this aspect of the invention is directed to a volume of interest in the cartilage, i.e., a region of the cartilage that includes a cartilage defect. Such a defect may be the result of a disease of the cartilage (e.g., osteoarthritis) or the result of degeneration due to overuse or age. This invention allows a health practitioner to evaluate and treat such defects. The volume of interest may include only the region of cartilage that has the defect, but preferably will also include contiguous parts of the cartilage surrounding the cartilage defect.
Another aspect of the invention is a method for assessing the condition of cartilage in a joint of a human, which method comprises
(a) electronically transferring an electronically-generated image of a cartilage of the joint from a transferring device to a receiving device located distant from the transferring device; (b) receiving the transferred image at the distant location;
(c) converting the transferred image to a degeneration pattern of the cartilage; and
(d) transmitting the degeneration pattern to a site for analysis.
Another aspect of the invention is a method for determining the volume of cartilage loss in a region of a cartilage defect of a cartilage in joint of a mammal. The method comprises
(a) determining the thickness, DN, of the normal cartilage near the cartilage defect;
(b) obtaining the thickness of the cartilage defect, DD, of the region; (c) subtracting DD from DN to give the thickness of the cartilage loss, DL; and (d) multiplying the DL value times the area of the cartilage defect, AD, to give the volume of cartilage loss. The method is useful for situations wherein the region of cartilage defect is limited to the defective cartilage and preferably wherein the region of the cartilage defect includes a portion of the cartilage contiguous to the defect.
Alternatively, for step (a) the normal thickness of the defect area could be estimated. It may be estimated from measurements of cartilage of other subjects having similar characteristics such as gender, age, body type, height, weight, and other factors. It may be estimated from measurements of a similar 'normal" cartilage from another corresponding joint (e.g., if the right knee has the defect, measure the normal left knee). It may have been measured at an initial time Ti when the cartilage was normal to provide a baseline. Other means of determining the normal thickness may be available to one of skill in the art. Once the thickness D is obtained and the thickness DD is obtained the two are subtracted to give the DL. The DL is multiplied by the area of the defect AD to give the volume of cartilage loss. By determining the volume of cartilage loss at an initial Ti and again at a later time T , one can determine the change in volume loss over time.
Still another aspect of the invention is a method of estimating the change of a region of cartilage in a joint of a mammal over time. The method comprises (a) estimating the thickness or width or area or volume of a region of cartilage at an initial time Ti, (b) estimating the thickness or width or area or volume of the region of cartilage at a later time T2, and (c) determining the change in the thickness or width or area or volume of the region of cartilage between the initial and the later times. The method is particularly useful for regions of degenerated cartilage or diseased cartilage.
Still another aspect of the invention is a method of estimating the loss of cartilage in a joint. The method comprises (a) defining a 3D object coordinate system of the joint at an initial time, Ti; (b) identifying a region of a cartilage defect within the 3D object coordinate system; (c) defining a volume of interest around the region of the cartilage defect whereby the volume of interest is larger than the region of cartilage defect, but does not encompass the entire articular cartilage; (d) defining the 3D object coordinate system of the joint at a second timepoint, T ; (e) placing the identically-sized volume of interest into the 3D object coordinate system at timepoint T2 using the object coordinates of the volume of interest at timepoint Ti.; (f) and measuring any differences in cartilage volume within the volume of interest between timepoints Ti. and T2. Display of Biochemical Information
hi addition to providing a 2D or 3D representation of the moφhological properties of cartilage, the invention provides for techniques to represent a biochemical components of articular cartilage. A biochemical component includes, but is not limited to, glycosaminoglycan, water, sodium, or hyaluronic acid. Biochemical data can be generated with other magnetic resonance based techniques including the use of paramagnetic and other contrast media and sodium rather than proton MR imaging. Other imaging tests such as positron emission tomography scanning can also be used for this p pose. Thus, one aspect of this invention is a method for providing a biochemically-based map of joint cartilage. The method comprises
(a) measuring a detectable biochemical component throughout the cartilage,
(b) determining the relative amounts of the biochemical component throughout the cartilage;
(c) mapping the amounts of the biochemical component through the cartilage; and
(d) determining the areas of cartilage deficit by identifying the areas having an altered amount of the biochemical component present.
Once a map is obtained, it can be used in assessing the condition of a cartilage at an initial time and over a time period. Thus, the biochemical map may be used in the method aspects of the invention in a manner similar to the cartilage thickness map.
For example, one aspect is a method of estimating the loss of cartilage in a joint. The method comprises
(a) obtaining a biochemical map of the cartilage at an initial time and analyzing the biochemical content of a region thought to contain degenerated cartilage so mapped at the initial time, (b) obtaining a biochemical map of the cartilage at a later time, and time analyzing the biochemical content of the region thought to contain degenerated cartilage so mapped at the later time, and
(c) determining the change in biochemical content of the cartilage between the later and initial times. Preferably, this aspect of the invention is directed to a volume of interest in the cartilage, i.e., a region of the cartilage that includes a cartilage defect. Such a defect may be the result of a disease of the cartilage (e.g., osteoarthritis) or the result of degeneration due to overuse or age. This invention allows a health practitioner to evaluate and treat such defects. The volume of interest may include only the region of cartilage that has the defect, but preferably will also include contiguous parts of the cartilage surrounding the cartilage defect.
As discussed herein before, another aspect of the invention is a method for assessing the condition of cartilage in a joint using the biochemical map. The method comprises
(a) electronically transferring an electronically-generated biochemically based image of a cartilage of the joint from a transferring device to a receiving device located distant from the transferring device;
(b) receiving the transferred image at the distant location; (c) converting the transferred image to a degeneration pattern of the cartilage; and (d) transmitting the degeneration pattern to a site for analysis. Another aspect of the invention is a method for determining the change of biochemical content in a region of a cartilage defect of a cartilage in joint of a mammal. The method comprises (a) determining the biochemical content (BCN) of the normal cartilage near the cartilage defect; (b) obtaining the biochemical content of the cartilage defect (BCD) of the region; and (c) subtracting BCD from BCN to give the value of the cartilage change, BCD. The method is useful for situations wherein the region of cartilage defect is limited to the defective cartilage and preferably wherein the region of the cartilage defect includes a portion of the cartilage contiguous to the defect.
Alternatively, for step (a) the normal content of the defect area could be estimated. It may be estimated from measurements of cartilage of other subjects having similar characteristics such as gender, age, body type, height, weight, and other factors. It may be estimated from measurements of a similar 'normal" cartilage from another corresponding joint (e.g., if the right knee has the defect, measure the normal left knee). It may have been measured at an initial time Ti when the cartilage was normal to provide a baseline. Other means of determimng the normal content may be available to one of skill in the art. Once BCN is obtained and BCD is obtained the two are subtracted to give the Δ. By determining the change of content at an initial Ti. and again at a later time T2, one can determine the change in biochemical content over time. Once the biochemically-based map is provided, moφhological maps of articular cartilage obtained with MR imaging can be superimposed, merged or fused with the biochemical map or data. Several different techniques can be applied in order to superimpose, merge, or fuse moφhological data with biochemical data. For example, 2D or 3D moφhological data of articular cartilage can be acquired with the same object coordinates as the biochemical data. Moφhological data and biochemical data can then be easily displayed simultaneously using different colors, opacities, and or gray scales. Alternatively, 2D or 3D moφhological data or articular cartilage can be acquired with different object coordinates as the biochemical data. In this case, a 3D surface registration can be applied in order to superimpose, merge, or fuse the moφhological data and the biochemical data. As an alternative to 3D object coordinates, anatomic landmarks can be used to register the moφhological data and subsequently the biochemical data in a 3D object coordinate system. 3D object coordinate systems can then be matched by matching the landmarks obtained from the moφhological data with those obtained from the biochemical data.
Thus, another aspect of this invention is a method for assessing the condition of a subject's cartilage in a joint, the method comprises obtaining a three dimensional biochemical representation of the cartilage, obtaining a moφhological representation of the cartilage, and merging the two representations, and simultaneously displaying the merged representations on a medium. The merged representations are then used to assess the condition of a cartilage, estimate the loss of cartilage in a joint, determining the volume of cartilage loss in a region of cartilage defect, or estimating the change of a region of cartilage at a particular point in time or over a period of time. One can see that similar steps would be followed as spelled out for the use of a thickness map or biochemical map.
Simultaneous display of moφhological data with biochemical data provides a useful tool to assess longitudinal changes in moφhology or articular cartilage and biochemical composition of articular cartilage, for example during treatment with chondroprotective and chondroregenerative agents. Part of the unique aspect of this technology is that it lends itself to assessment of a patient from a distant position after an image is taken of the joint under evaluation. Thus one aspect of this invention is a method for assessing the condition of cartilage in a joint from a distant location. The method comprises (a) electronically transferring an electronically-generated image of a cartilage of the joint from a transferring device to a receiving device located distant from the transferring device;
(b) receiving the transferred image at the distant location;
(c) converting the transferred image to a degeneration pattern of the cartilage; and
(d) transmitting the degeneration pattern to a site for analysis.
The degeneration pattern includes a measure of cartilage thickness or regional cartilage volume.
The electronically generated image of the cartilage preferably is an MR image and the degeneration pattern can be displayed as a three-dimensional image as a thickness pattern, a biochemical content pattern or a merged thickness biochemical pattern. The electronically generated image is transmitted via Dicom, using the international standards for transmission of such images.
Another aspect of the invention is a kit for aiding in assessing the condition of cartilage in a joint of a mammal, which kit comprises a software program, which that when installed and executed on a computer reads a cartilage degeneration pattern presented in a standard graphics format and produces a computer readout showing a cartilage thickness map of the degenerated cartilage.
The software can be installed in a PC, a Silicon Graphics, hie. (SGI) computer or a Macintosh computer. Preferably, the software calculates the thickness or regional volume of a region of degeneration of the cartilage which does not include the entire volume of the articular cartilage.
THE MOVEMENT PATTERN To acquire a movement pattern of a joint in accordance with this invention, one obtains an internal image of the bones in a joint, preferably using MRI techniques, and obtains an external image of the bones in motion. The images are correlated, preferably through the use of external marker sets, to give a pattern that shows a static or moving condition. The correlated images are then displayed and the relation between the movement and degeneration patterns is determined.
Obtaining An Internal Image of Joint with Bones
To obtain an internal image of a joint with the associated bones, one preferably uses MRI techniques that provide an image of the bones on either side of the joint. Here, it is important to use the imaging technique that gives the best image of the bones and how they interact. Because the internal image of the bones can be combined with the image of the bones obtained by external measurements, it is particularly useful, and therefore preferred, to use external reference markers that can be similarly-positioned to the markers used in obtaining the external measurements. The external markers can be placed at any landmarks about the joint of interest. At least three markers are used for each limb being imaged. Preferably the markers will be made of a material that not only will be detected by MRI imaging techniques, but also will be detected by external imaging techniques. The markers will be associated with a means to affix them to the skin and preferably have an adhesive portion for adhering to the skin and a detectable entity that will show up on the MRI image.
The preferred MRI imaging technique useful for obtaining an internal image is a spoiled 3D gradient echo, a water selective 3D gradient echo or a 3D DEFT sequence. A further discussion may be found hereinbefore or in the 2nd Edition of Brown and Semelka's book entitled "MRI Basic Principles and Applications."
Oiice an MR image is obtained the image is manipulated to enhance the image of the bones. Procedures similar to those discussed hereinbefore for cartilage may be used, but modified for application to bone images.
Creating Three-Dimensional (3D) Image of Joint/Bones Three-Dimensional Geometric Model Generation
After the 3D image of a joint with bones, the set of segmented two dimensional MR images can be transformed to a voxel representation inside AVS Express (Advanced Visual Systems, Inc., Waltham, MA). Every voxel has a value of zero if it is not within an object of interest or a value ranging from one to 4095, depending on the signal intensity as recorded by the 1.5 T MR. An isosurface can then be calculated that corresponds to the boundary elements of the region of interest. A tesselation of this isosurface can be calculated, along with the outward pointing normal of each polygon of the tesselation. These polygons can then be written to a file in a standard graphics format (Virtual Reality Modeling Language Version 1.0).
As discussed hereinbefore, the use of reference markers on the skin around the joint and the bones can provide an image that can later be matched to the reference markers for the cartilage image and the bone images obtained from external measurements.
Alternatively, a semi-automated, 3D surface-based registration technique that does not require the use of an external frame or fiducial markers can be used. This 3D surface-based registration technique can be used to match the anatomic orientation of a skeletal structure on a baseline and a follow-up CT or MRI scan. We extended a robust and accurate 2D edge detector (Wang-Binford) to 3D. This detector is described hereinbefore.
A registration technique for the femoral condyles and the tibial plateau is shown in Figure 10. It shows an example where 3D surfaces of the femoral condyles were extracted from two differently oriented Tl-weighted spin-echo MRI scans (baseline A and follow-up B, respectively) obtained in the same patient in neutral position (A) and in 40 degree external rotation (B). The 3D surfaces were used to derive a coordinate transformation relating the two scans. Fig. 10C demonstrates the use of the derived transformation to reregister scan B in the object coordinate system of scan A. Such a transformation relating two Tl-weighted scans can then be used to register DEFT cartilage-sensitive scans that are acquired in the same respective orientations as the A and B Tl-weighted scans.
We performed the registration using a Sun Sparc 20 workstation with 128MBytes of memory. The surface detection algorithm extracted approximately 12,000 surface patches from each data set. The surface extraction and registration routines took about 1 hour in total.
Since the algorithm for 3D surface registration of the femoral condyles also computes the surface normals for the medial and lateral femoral condyles on a pixel-by-pixel basis, it can form the basis for developing maps of cartilage thickness. Fig. 11 shows an example of a 2D map of cartilage thickness derived from the surface normals of the lateral femoral condyle. Figure 11A shows a proton density fast spin-echo MR image that demonstrates a focal cartilage defect in the posterior lateral femoral condyle (black arrows). White arrows indicate endpoints of thickness map. Figure 1 IB is a 2D cartilage thickness map that demonstrates abrupt decrease in cartilage thickness in the area of the defect (arrows). The Δ thickness between neighboring pixels can be used to define the borders of the cartilage defect. Note diffuse cartilage thinning in area enclosed by the astericks (*).
In another embodiment, cartilage sensitive images can be used instead of Tl-weighted or T2-weighted scans and the surface match can be performed based on the cartilage contour.
Alternatively, anatomic landmarks present on both baseline and follow-up scans can be used to match the data obtained during the baseline and those obtained during the follow-up scan. Another alternative for matching the baseline and the follow-up scan includes the use of external or internal fiducial markers that can been detected with MR imaging. In that case, a transformation is performed that matches the position of the markers on the follow-up scan with the position of the markers on the baseline scan or vice versa.
Obtaining An External Image of Joint/Bones
Before merging or superimposing moφhological maps of articular cartilage obtained by MR imaging with biomechanical data, one must obtain the biomechanical data. Such biomechanical data include, but are not limited to, estimations of static loading alignment in standing or weight-bearing position and lying or non- weight-bearing position, as well as during joint motion, e.g., the movement of load-bearing pathway on the cartilage in the knee joint during gait. Biomechanical data may be generated using theoretical computations, based on data stored in a database that can be accessed by calling up and screening for certain characteristics. Alternatively, gait analysis may be performed for an individual and data obtained during gait analysis may be merged or fused with moφhological MRI data. Moφhological data and biomechanical data can then be easily displayed simultaneously using different colors, opacities, and or gray scales. Additionally, the load-bearing pathway, for example around a cartilage defect, can be plotted or superimposed onto moφhological maps.
Preferably, reference markers or fiducial markers can be applied to the external surface on the skin overlying the joint. These markers adhere to the skin are typically made of materials that can be detected with MRI and that can be used to register joint motion during biomechanical analysis, e.g. gait analysis. These markers can then be used to correlate the moφhological with the biomechanical data.
Simultaneous display of moφhological data with biomechanical data provides a useful tool to assess the load pathway applied to articular cartilage and inside and around cartilage defects. Estimation of load pathway applied in and around a cartilage defect can be used to assess a cartilage defect and to guide the choice of therapy, e.g. treatment with chondroprotective or chondroregenerative agents, osteochondral allografting, cartilage transplantation, femoral or tibial osteotomy, or joint replacement surgery.
Recording Static Joint/Bones and Joint/Bones in Movement
In obtaining an external image of the bones on either side of a joint, one must record a static image as well as a moving image of the subject joint and bones. For analysis of the knee joint, gait analysis techniques have been shown to be very effective in generating accurate, reproducible data on the six degree of freedom motion of the knee. The motion of the knee joint can be quantified in teπns of flexion, rotation and displacement. Fidelity in the dynamic visualizations of subject specific MR generated knee geometry and subsequent contact surface determination call for a high degree of accuracy for the motion capture portion of the studies. Gait Analysis Activities
In performing a gait analysis, a subject is tested standing still, laying down, walking or running on a level surface, flexing a leg in a standing position, ascending and descending stairs, flexing the leg in a seated position, and the like. The level walking measurements can include, but is not limited to, six stride cycles for each side over a range of walking speeds. The subject can be instructed to walk at a comfortable speed (normal), slower than normal and faster than normal. Typically, this protocol produces gait measurements over a range of walking speeds. The standing and laying portions of the protocol can be used in the cross registration to the MR data. The instrumentation preferably includes, at least a two camera, video-based opto-electronic system for 3-D motion analysis, a multi-component force plate for measurement of foot-ground reaction force and a computer system for acquisition, processing and analysis of data.
Anatomic Coordinate Systems
Currently, the anatomic coordinate systems are defined through bony landmarks which can be identified through palpation. To describe the motion of the underlying bones in terms of the global coordinate system a subset of the markers in a point cluster technique (discussed hereinafter) are referenced to bony landmarks on the femur and tibia. Techniques described previously by Hopenfeld and Benedetti can be used to locate these bony landmarks. The anatomic coordinate systems used can be similar to that previously described by LaFortune with the exception of the origin of the femoral coordinate system. For the thigh segment, a coordinate system is located in the femoral condyles. The femoral condyles medial(M)- lateral(L) axis (Fig. 12) runs through the trans-epicondylar line (a line drawn between the medial-lateral femoral epicondyles). The midpoint of this axis is the origin. The inferior(I)- superior(S) axis runs parallel to the long axis of the femur, passing through the midpoint of the trans-epicondylar line. The anterior(A)-posterior(P) axis is the cross product of the medial-lateral and inferior-superior axes. The final position of the inferior-superior axis is made orthogonal to the anterior-posterior and medial-lateral axis through a cross product operation (Fig. 13). For the shank segment, the tibial coordinate system begins with the medial-lateral axis running through the most medial and lateral edges of the plateau. The inferior-superior axis is peφendicular to the medial-lateral axis passing through the tibial eminence. The anterior-posterior axis is the cross product of the medial-lateral and inferior- superior axes.
Placement of Markers Prior to Activity
In assessing a joint, the lower extremity can be idealized as 3 segments with six degree-of- freedom joints at the knee and ankle. For the mobile activities described above, at least 3 markers per segment are used. Figure 14 shows 21 passive retro-reflective markers located on the leg: some at bony prominences (greater trochanter, lateral malleolus, lateral epicondyle, lateral tibial plateau), some clustered on the thigh and shank (Fal-3,11-3, Fpl- 3; Tal-3, Tll-13). Additionally, two markers are placed on the foot at the lateral aspect of the calcaneus and base of the fifth metatarsal and one on the pelvis at theiliac crest). During the static activities (standing still, laying down) 7 additional markers are placed: medial malleolus, medial epicondyle, medial tibial plateau, medial and lateral superior patella, medial and lateral inferior patella. The eight markers nearest to the knee joint can be filled with Gadolinium, and can be be replaced at these same locations prior to the MR images (Fig. 15). The locations can be marked with a non-toxic marker-pen.
Reference Database The reference database is typically a compendium of demographic and motion analysis data for all subjects whose data has been processed by a central processing site. This database can contain fields describing each of the subject's name, age, height, weight, injury types, orthopedic medical history, other anatomic measurements (thigh length, shank length, shoe size, etc.). The database can also contain the results of any and all gait analysis run on these patients. This can include, for all activities tested (walk, run, jog, etc.), a number of peak valves (peak knee flexing, peak hip adduction movement; toe-out, angle, etc), along with the motion trajectories of the limb segments while the subjects are performing different activities.
In order to obtain a typical motion profile, the sex, age, height, weight, limb length, and type of activity desired can be entered as an average into the database. The database searches for a set of subjects most closely watching the input average. From this set of data, a typical motion pattern is distilled and a data set is output. This data set can include, over a time interval, the motion characteristics: hip / knee / ankle / flexion / extension angles, knee / hip / ankle adduction / abduction angles, movement, stride length, cadence, etc. This data can then be used to drive an animation of the motion of the desired joint.
Process Image of Joint/Bones
Calculation of Limb Segment Parameters
Each limb segment (thigh, shank and foot) can idealized as a rigid body with a local coordinate system defined to coincide with a set of anatomical axes (the assumption of rigidity is dropped in calculating the location of the femur and tibia). The intersegmental moments and forces can be calculated from the estimated position of the bones, the ground reaction force measurements, and the limb segment mass/inertia properties. The moment at the knee can be resolved into a coordinate system fixed in a tibial reference system with axes defining flexion-extension, abduction-adduction, and internal-external rotation.
This approach provides results in a range of patients in a highly reproducible manner. Typically the magnitudes of the moments are dependent on walking speed. To control for the influence of walking speed, the walking speed closest to 1 meter/second is used. This speed is within the normal range for the type of patients for which the invention is particularly useful. In addition to the gait trial collected at 1 meter/second, self-selected speeds can also be evaluated to give a good correlation between gait-quantitative estimates of joint load lines and other measures when using self-selected speeds. In order to test patients under their typical daily conditions, medications should not be modified prior to gait analyses.
Point Cluster Technique
The Point Cluster Technique (PCT) movement analysis protocol is an extensible and accurate approach to bone motion estimation. Basically, a number of retro-reflective markers (e.g. retro-reflective material from 3M, Coφ.) are attached to each limb segment under observation. Multiple video cameras can acquire data with the subject standing still and during activities of interest. An over-abundance of markers on each limb segment is used to define a cluster coordinate system, which is tied to an anatomically relevant coordinate system calculated with the subject at rest.
The standard PCT transformations are described below. In short, each marker is assigned a unit mass and the inertia tensor, center of mass, principal axes and principal moments of inertia are calculated. By treating the center of mass and principal axes as a transformation, local coordinates are calculated. Another set of coordinate systems is established; limb segment specific anatomic landmarks are identified through palpation and a clinically relevant coordinate system defined. For the femur and tibia, these anatomic coordinate systems are shown in Fig. 12. The transformation from the reference cluster coordinate system to the anatomic coordinate system is determined with the subject at rest by vector operations. During an activity, the transformation from the global coordinate system to the cluster coordinate system is calculated at each time step. To place the anatomic coordinate in the global system during the activity, the reference coordinate system to anatomic system transformation is applied, followed by the inverse global coordinate system to cluster coordinate system transfonnation for each time step.
In the Point Cluster Technique (PCT) a cluster of N markers can be placed on a limb segment of the subject. The location vector of each marker in the laboratory coordinate system is denoted as G(i,t) for marker i, (i = 1,2,...,N) at time t, t0 ≤ t < tf. A unit weight factor is assigned to each marker for the p pose of calculating the center of mass, inertia tensor, principal axes and principal moments of inertia of the cluster of markers. The cluster center of mass and principal axes form an orthogonal coordinate system described as the cluster system. The local coordinates of each of the markers relative to this coordinate system are calculated. Then
G(i,t) = C(t) + E(t) • L(i,t) = Tc (t) • L(i,t) i = 1 ... N
where G(t) is a matrix of all marker coordinate vectors, C(t) is the center of mass of G(t), E(t) is the matrix of eigenvectors of the inertia tensor of G(t), and L(i,t) are the local coordinates of marker i. These markers are observed by opto-electronic means while the subject performs activities and while standing completely still in a reference position. With the subject in this same reference position, a subset of the markers is observed relative to the underlying bones by other techniques, which might include x-rays, CT scan, or palpation.
The measured marker locations are defined with respect to the unobservable location and orientation of the bone by
G(i,t) = P(t) + O(t) • R(i,t) = Tb (t) • R(i,t) i = 1 ... N
where P(t) is the location and O(t) is the orientation of a coordinate system embedded in the bone and R(i,t), also unobservable, are the trajectories of the markers relative to the underlying rigid body coordinate system at time t. The bone and cluster systems are each orthogonal systems, related by the rigid body transformation Tbc(t):
L(i,t) = Tbc (t) . R(i,t)
substituting and eliminating R(i,t) yields
Tb (t) = Tc (t) . Tcb (t)
To maintain physical consistency, Tcb(t) = Tbc(t)_1 must be the inertia tensor eigendecomposition transformation of R(i,t). Once R(i,t) are specified, Tcb(t) and subsequently Tb(t) are calculable.
Point Cluster to Anatomic Coordinate System Transformation
From these equations one can also relate the global coordinate system with respect to a limb segment system. As an example of how these systems can be used to describe joint motion, one can consider the tibio-femoral joint. The motion that is of interest is how the femoral condyles move with respect to the tibial plateau. This is done by first defining a set of coordinate axes in the femoral condyles and the tibial plateau. A coordinate system is located in both the femoral condyles and the tibial plateau. The femoral condyles medial-lateral (ML) axis runs through the trans-epicondylar line (TEL), a line drawn between the ML femoral epicondyles. The midpoint of this axis is the origin. The inferior-superior (IS) runs parallel to the long axis of the femur, passing through the midpoint of the TEL. The anterior-posterior (AP) is the cross product of the ML and IS axes. The tibial coordinate system begins with the ML axis running through the most medial and lateral edges of the plateau. The IS axis is peφendicular to the ML axis passing through the tibial eminence. The AP axis is the cross product of the ML and IS axes. These are known as the anatomic coordinate system (A(t)thigh, A(t)shank)-
Relating the cluster system to the anatomic coordinate system is done by use of another transformation matrix. This is done by relating the thigh cluster to a cluster of markers, a sub cluster, that is related to the femoral condyles and femur (cluster to anatomic transformation).
R(t)thigh - U(t)thigh A(t)tnigh
The tibia has a similar transformation matrix.
R(f)shank = U(t)shank A(t)shank
Therefore, from a cluster of markers in the global system, motion of the femur with respect to the tibia can be determined by:
TS(t) = A(t)thigh • G(t)thigh • R(t)shank • A(t)shank
Here TS(t) is the motion of the thigh with respect to the shank.
Angles are calculated by a projection angle system, an axis from the femoral anatomic system and one from the tibia are projected onto a plane in the tibial coordinate system. For example, flexion/extension can be determined by projecting the IS axis of the femur and tibia onto the sagittal plane (AP-IS plane) of the tibia. Validation of the Point Cluster Technique
The point cluster technique was evaluated as a method for measuring in vivo limb segment movement from skin placed marker clusters. An Ilizarov device is an external fixture where 5 mm diameter pins are placed directly into the bone on either side of a bony defect. The rigid external struts affixed to these pins form a rigid system fixed in the underlying bone. Two subjects were tested with Ilizarov fixation devices. One subject had the Ilizarov device placed on the femur and second subject had the device placed on the tibia. Each subject was instrumented with point clusters placed on the thigh and shank segment. In addition, markers were placed on the Ilizarov device to establish a system fixed in the underlying bone.
The relative angular movement and translational displacement between the system affixed in the bone and the point cluster coordinate system were calculated while ascending a 20-cm step (Step Test). Angular changes between the three orthogonal axes fixed in the bone versus three axes in the point cluster were calculated. The average difference over the trials for three axes were 0.95 + 1.26, 2.33 +1.63, and 0.58 + 0.58 degrees. Similarly, the average error for the distance between coordinate systems was 0.28 + 0.14 cm. The second subject with the Ilizarov device placed on the femur could not perform the Step-Test, but was able to perform a weight-bearing flexion test where his knee flexed to approximately 20° from a standing position. The average change between the coordinate origin was 0.28 + 0.14 cm. The changes in axis orientation were 1.92 + 0.42, 1.11 + .69 and 1.24 + 0.16 degrees.
The simultaneously acquired motion for a coordinate system embedded in bone (Ilizarov system) and a set of skin-based markers was compared. At every time instant the location and orientation of the Ilizarov system, the rigid body model skin marker system, and the interval deformation technique skin marker system were determined. The change in the transformation from the Ilizarov system to one of the skin marker systems over time is a measure of the deformation unaccounted for in the skin marker system.
The interval deformation technique produced a substantial improvement in the estimate of the location and orientation of the underlying bone. For perfectly modeled motion there would be no relative motion between the Ilizarov system and the skin marker system over the time interval. The change in the transformation from the Ilizarov system to the skin marker systems are shown in Figures 14 and 15, for location and orientation respectively, for both a rigid body model and the interval deformation technique. For this single data set, the location error was reduced from 7.1 cm to 2.3 cm and the orientation error from 107 degrees to 24 degrees, with the error summed over the entire time interval. The subject performed a 10 cm step-up; the marker deformation was modeled as a single Gaussian function.
Deformation Correction
There are a number of algorithmic alternatives available to minimize the effects of skin motion, soft tissue deformation, or muscle activation that deform the externally applied markers relative to the underlying bone. The Point Cluster Technique decreases the effects of marker movement relative to the underlying bone through averaging. If more correction is required, one of a number of deformation correction techniques may be added. In order of increasing computational complexity and deformation correction ability, these are rigid body linear least square error correction, global optimization correction, anatomic artifact correlation correction and interval deformation correction.
An overview of the Interval Deformation Correction Technique is given below. In short, the technique provides a maximum likelihood estimate of the bone pose, assuming that each marker on a limb segment deforms relative to the underlying bone in some functional form. The technique parameterizes these functional forms and then performs a multi-objective non-linear optimization with constraints to calculate these parameters. This is an extremely computationally intensive technique, with the current instantiation of the algorithm requiring 6 - 8 hours per limb segment of running time on 266 MHz Pentium 2 computer.
Interval Deformation Technique
Since Tc can be calculated directly from the global coordinates of the markers, the remainder of this development only examines the determination of R(i,t) and subsequently Tcb(t). For this reduced problem, the input data is the local coordinates in the cluster system L(i,t) for all i, T0 ≤ t ≤ tf. It can be assumed that each marker has some parameterized trajectory, d(a--j, t), relative to the underlying bone at each time step, with independent and identically distributed noises v(i,j,t)
Rj(i,t) = d(aiJ, t) + v(i,j,t) j = 1 .. 3 i = l .. N
or, equivalently
R(i,t) = Ffø, t) + v(i,t) i = 1 .. N
where ay is a vector of parameters for marker i, ordinate j; a, is a vector of parameters combining all of the parameters for all of the ordinates of marker i. Then the estimate of the data, M(i,t), can be given by
M(i,t) = Tbc (t) . R(i,t)
Without further restrictions the problem is indeterminate, as the locations of the markers in the bone system R(i,t) are never observable with the opto-electronic system. The indeterminate problem can be converted to a chi-squared estimate problem through a series of steps. An observation of the truly unobservables at the time boundaries is inferred; that is, it is assumed that Tcb (t ≤ t0) and Tcb (t > tf) are observed. The value of Tcb can be selected depending on the activity being studied. For example, consider the step up activity, where the subject starts and stops in the reference position. For this activity the body is not deforming outside the estimation interval; that is, the markers are not moving with respect to the bone:
Tc (t < t0) = Tcb (t = t0) and Tcb (t > tf) = Tcb (tf). It can now be assumed that the noise functions v(i, j, t) are normal distributions with individual standard deviations σ(i, j, t), the probability P(ij,t) of the data for ordinate j, marker i, time t being a realization of the stochastic process is given by:
1 .L(i,j,t) -M(i,j,t). 2
P(i,j,t) c exp (- X )2) σ(i,j,t)
Provided the noise functions v(i, j, t) are independent of each other, the probability of the entire data set being a realization is a product of each of the individual probabilities:
Maximizing this probability can be equivalent to minimizing the negative of its logarithm, yielding the familiar chi-square criteria. As an intermediate step the following error matrices can be defined:
I l B ^ ^ ^ ^ 2 i = l - N j = 1 .. 3 σ(ι,J,t)
X(a) = ∑ X(a,t)
and seek a which in some sense minimizes X(a), a matrix whose elements represent the error over the entire time interval for each ordinate of each marker. If the normal noise distribution assumption is true, then this minimization results in the maximum likelihood estimate of the parameterization, and by inference maximum likelihood estimate of the transformation from the bone system to the cluster system. If the normal noise assumption is not true, the chi-squared estimate is still appropriate for parameter estimation; the results cannot be inteφreted as a maximum likelihood estimate, but, for example, confidence regions on the estimate or the formal covariance matrix of the fit can be determined.
Obtaining the parameter set a is a computationally complex operation. The approach taken was to define a scalar to represent this entire error matrix, /(a) = ∑ ∑ (a),, i=l J-ι
and seek a that minimizes f(a).
The limits on marker motion previously discussed can now be converted into deformation constraints, which allow the formulation of the problem as a general non-linear programming problem. The constraints arise from two sources; human limb segments do not deform outside a small range, and the locations of the markers are chosen with specific properties in mind. For computational puφoses, the deformation constraints are selected to be:
1. The axes of the cluster system moves by less than 15 degrees relative to the bone system. 2. The center of mass of the cluster system moves by less than 3 cm relative to the bone system.
3. The markers move by less than 4 cm relative to the bone system.
4. Each of the principal moments of inertia of the cluster system change by less than 25 percent from the reference values.
The Point Cluster Technique marker set was designed to ensure that the cluster of points is non-coplanar and possess no axes of rotational symmetry. These properties ensure a local coordinate system that is well defined and unambiguous over the entire time interval. The constraints are then: 5. The ratio of the smallest principal moment of inertia of the cluster system to the largest is more than 5 percent; the magnitude of the smallest principal moment of inertia of the cluster system is greater than some small positive value.
6. The principal moments of each axis are different from each other by at least 5 percent.
The general problem can then be formulated: Minimize f(a) e RD
Subject to: gi(a) = 0 i = 1 .. m *ee gi(a) < 0 i = me + 1 .. m aι< a < au
where D is the total number of parameters; me, the number of equality constraints, is 0; and m, the total number of constraints, is 10.
The approach taken to verify the operation of the algorithm implementation began with generating a set of 50 synthetic data sets with known characteristics. The program was then applied to all of the data sets. The program results were then compared to the known, generated deformation. Error results were calculated for both the interval deformation technique descried herein and for the standard rigid body model formulation.
The 50 trial data sets were processed through the algorithm. The results over all of the trial sets are summarized in Table I, where the center of mass and direction cosine error of the interval deformation technique and the rigid body model are compared. After processing by the interval deformation algorithm the center of mass error has been reduced to 29% and the direction cosine error has been reduced to 19% of the rigid body model error. In a t-test for paired samples, both of these decreases were significant at p < 0.001.
Validation of the Interval Deformation Correction Technique
A subject fitted with an Ilizarov external fixation was observed with the optoelectronic system. The Point Cluster Marker set was affixed to the subject's shank (6 markers), along with a set of four markers rigidly attached to the Ilizarov device, which is rigidly connected to the tibia with bone pins. These four markers define a true bone embedded coordinate system. Data were acquired by GaitLink software (Computerized Functional Testing Coφoration) controlling four Qualisys cameras operating at a video frequency of 120 Hz. Three dimensional coordinates were calculated using the modified direct linear transform. The subject was a 46 year old male (height 1.75 m, weight 84.1 kg) fitted with a tibial Ilizarov external fixation device. The device was rigidly attached to the tibia with nine bone pins, located in three sets (top, middle, and bottom) of three (medial, anterior, and lateral). The clinical pvupose of the device was tibial lengthening; the test on the subject was performed two days prior to final removal of the device. The subject exhibited a limited range of motion and was tested performing a 10 cm step-up onto a platform.
The simultaneously acquired motion for a coordinate system embedded in bone (Ilizarov system) and a set of skin-based markers was compared. At every time instant the location and orientation of the Ilizarov system, the rigid body model skin marker system, and the interval deformation technique skin marker system was determined. The change in the transformation from the Ilizarov system to one of the skin marker systems over time is a measure of the deformation unaccounted for in the skin marker system.
The interval deformation technique produced a substantial improvement in the estimate of the location and orientation of the underlying bone. For perfectly modeled motion there would be no relative motion between the Ilizarov system and the skin marker system over the time interval. The change in the transformation from the Ilizarov system to the skin marker systems are shown in Figs. 14 and 15 for location and orientation respectively, for both a rigid body model and the interval deformation technique. For this single data set, the location error was reduced from 7.1 cm to 2.3 cm and the orientation error from 107 degrees to 24 degrees, with the error summed over the entire time interval. The subject performed a 10 cm step-up; the marker deformation was modeled as a single Gaussian function.
CORRELATING RESULTS FROM GAIT ANALYSIS AND GEOMETRICAL REPRESENTATIONS OF THE BONE
In correlating the load pattern obtained from a gait analysis using, e.g. the PCT, with the geometrical representation of the bone from the segmented MRI data, one can be guided by the general process as described below. The process allows for dynamic visualization (i.e. animations) of high-resolution geometrical representations derived from MRI scans (or other imaging techniques). The motion of the subject specific anatomic elements is generally driven by data acquired from the motion (gait) lab. Fidelity of these animations requires calculation and application of a sequence of rigid body transformations, some of which are directly calculable and some of which are the result of optimizations (the correction for skin marker deformation from rigidity does not use the rigid body assumption, but generates a correction that is applied as a rigid body transform).
The process comprises:
a) acquiring data from MRI (or other imaging techniques), and PCT gait protocols;
b) directly calculating a set of transformations from the data;
c) calculating a set of transformations from optimizations, as needed;
d) generating a 3D geometric representation of the anatomic element from the
MR data; and
e) applying the transformations of (b) and (c) to the 3D geometric representation.
Each of these steps are described in detail below.
Acquiring the Data from MRI (or other imaging techniques) and PCT Gait Protocols
In the Point Cluster Technique (PCT) protocol, a patient can have a number of retro- reflective markers attached to each limb segment under observation. Multiple video cameras acquire data with the subject standing still and during activities of interest.
In addition, in order to correspond activities in the gait lab with the MRI scans, another reference data set (subject standing still, prescribed posture) can be acquired using 8 additional markers clustered about the knee. These markers are filled with gadolinium- DTPA and covered with a retro-reflective material to allow for correlation between the MRI image and the video data. Directly Calculating a Set of Transformations from the Data
The transformations are described in detail in Andriacchi et al., J. Biomech. Eng., 1998. In short, each marker can be assigned a unit mass and the inertia tensor, center of mass, principal axes and principal moments of inertia can be calculated. By treating the center of mass and principal axes as a transformation, local coordinates arcan be e calculated. Another set of coordinate systems can also be required for this technique; limb segment specific anatomic landmarks can be identified through palpation and a clinically relevant coordinate system can be defined. The required transformations are summarized in Table 1 below.
Calculating a Set of Transformations from Optimizations
There are three required transformations:
Optimization 1. One can calculate the linear least square error rigid body transformation from the MRI common local coordinate system to the VTX) common local coordinate system.
Optimization 2. For each limb segment, one can calculate the linear least square rigid body transformation from the MRI limb segment anatomic coordinate system to the video limb segment anatomic coordinate system (obtained from the gait analysis), using a subset of common markers appropriate for each segment.
Optimization 3. One can calculate a correction for the deviation of the limb segment from rigidity during each time step of the activity, using the PCT with either the mass redistribution (Andriacchi et al., J. Biomech Eng., 1998) or interval deformation algorithms (Alexander et al., Proceedings of the 3rd Annual Gait and Clinical Movement Analysis Meeting, San Diego, CA, 1998).
Generating a 3D Geometric Representation of the Anatomic Element from the MR data
The MR slices are segmented for the multiple anatomic and fiducial elements. The slices are combined to a voxel representation. An isosurface can be calculated from the boundary voxel elements. A tessellation of the isosurface can be calculated, along with the outward pointing normal for each surface element. This data can then be stored in a standard 3D graphic format, the Virtual Reality Modeling Language (VRML).
Appling the Transformation Sequence to the Geometric Representation
The transformation sequence is provided below in Table 1. This transformation sequence can be applied to each of the anatomic elements over each time step of the activity, starting with sequence 6.
TABLE 1
Correlating Marker Sets
As pointed out at numerous places in the specification, the use of external reference markers that are detectable by both MRI and optical techniques can be an important and useful tool in the method of this invention. The use of the reference markers can form the basis for an aspect of this invention that is a method for correlating cartilage image data, bone image data, and/or opto-electrical image data for the assessment of the condition of a joint of a human. This method comprises, obtaining the cartilage image data of the joint with a set of skin reference markers placed externally near the joint, obtaining the bone image data of the joint with a set of skin reference markers placed externally near the joint, obtaining the external bone image data opto-electrical image data of the joint with a set of skin reference markers placed externally near the joint. Using the skin reference markers, one can then correlate the cartilage image, bone image and opto-electrical image with each other, due to the fact that each skin reference marker is detectable in the cartilage, bone and opto- electrical data. The cartilage image data and the bone image data can be obtained by magnetic resonance imaging, positron emission tomography, single photon emission computed tomography, ultrasound, computed tomography or X-ray. Typically, MRI will be preferred. In the case of X-ray, further manipulations must be performed in which multiple X-ray images are assimilated by a computer into a 2 dimensional cross-sectional image called a Computed Tomography (CT) Scan. The opto-electrical image data can be obtained by any means, for example, a video camera or a movie camera. Multiple skin reference markers can be placed on one or more limbs of the patient prior to imaging. The skin reference markers are described hereinbefore.
By a sequence of calculations a set of transformations that will take the subject specific geometric representation of anatomic elements determined from the MR image set to the optical reference coordinate system. From the optical reference coordinate system, the standard Point Cluster Technique transformation sequence is applied to generate dynamic visualizations of these anatomic elements during activities previously recorded in the motion lab. Fidelity of these dynamic visualizations (and subsequent contact surface determination) requires the calculation and application of a sequence of rigid body transformations. Some of these are directly calculable and some are the result of optimizations (the correction for skin marker deformation from rigidity does not use the rigid body assumption, but generates a correction that is applied as a rigid body transform).
The first required transformation can be from the MR global coordinate system to the MR center of mass / principal axis coordinate system. This can be done by calculating the center of mass of each of the individual markers, resulting in a set of eight three dimensional points. Each of these points can be assigned a unit mass, and the center of mass, inertia tensor, and principal axes can be calculated. The same procedure can be performed on these markers as determined by the optical system, providing a transformation from the optical global system to a center of mass / principal axis system.
If the relative orientation of the tibia and femur as determined by the MR system and the optical system are identical, it is only necessary to apply the optical reference system to the anatomic system transformation of the MR local data. If this is not the case, an optimization calculation can be performed to determine the rotation and translation of, for example, the femur with respect to the tibia. One then can calculate the linear least square rigid body transformation from the MR limb segment anatomic coordinate system to the video limb segment anatomic coordinate system prior to applying the Point Cluster Transformations.
For visualization or contact surface determination, one can examine the relative motion of one segment to the other, for example the motion of the femur relative to a fixed tibial frame. This can be accomplished by applying the global to tibial anatomic system transform to all of the elements. An example of this type of visualization is given in Figure 18. The Figure shows what can be referred to as functional joint imaging. Figure 18A is a photograph demonstrating the position of the external markers positioned around the knee joint. The markers are filled with dilute Gd-solution. B is Sagittal 3D SPGR image through the medial femorotibial compartment. Two of the external markers are seen anteriorly as rounded structures with high signal intensity. C is 3D reconstruction of femoral and tibial bones (light grey), external markers (dark grey), femoral cartilage (red), and tibial cartilage (blue) based on the original SPGR MR images. D-I show a functional joint imaging sequence at selected phases of leg extension from a seated position, D-F, anterior projection. The vectors represent the relative location and orientation of the femur with respect to the tibia. G-I is a lateral projection. These dynamic visualizations can be used to demonstrate tibiofemoral contact areas during various phases if gait or other physical activities.
Superimposition of cartilage thickness map onto subject specific anatomic model and determination of distance of cartilage defect from load bearing line
Superimposing the cartilage thickness maps onto the subject specific geometric models can follow the same approach taken to bring the MR generated geometries into the optical reference system. Since the thickness maps and the geometric models are initially in the same coordinate system; one possible approach is to perform a simple surface mapping of the thickness map onto the geometric model. Another alternative approach is to convert the thickness map directly into a geometric representation (Fig. 19).
Once the thickness map is embedded in the femoral geometry, one can define a scalar metric that characterizes the location of any cartilage lesions relative to the point of contact line. One approach is a simple 3D distance along the surface from the center of the cartilage lesion to the point of closest approach of the contact line. Another metric that could be useful would be to multiply the area of the lesion by the adduction moment at that time instant, then divide by the distance from lesion center to point of closest approach. This could result in a metric that increases with lesion area, adduction moment, and closeness of approach.
46 Display Correlated Images
Determination of Anatomic and Natural Reference Lines
There are two alternative approaches one can consider for determining a reference line on the cartilage surfaces. One skilled in the art will easily recognize other approaches that can be suitable for this pvnpose. The first approach is based on anatomic planes; the second is a natural approach building on the three dimensional cartilage thickness map.
The location of the pathway of loading relative to the femoral and tibial anatomy and geometry can be assessed by defining sagittal planes bisecting the medial femoral condyle, the lateral femoral condyle, the medial tibial plateau, and the lateral tibial plateau. For the medial femoral condyle, the operator can manually delete surface points located along the trochlea. Then, a sagittal plane parallel to the sagittal midfemoral plane can be defined through the most medial aspect of the medial femoral condyle followed by a sagittal plane parallel to the sagittal midfemoral plane through the most lateral aspect of the medial femoral condyle. The sagittal plane that is located halfway between these two planes can be defined as the "midcondylar sagittal plane". The intersection between the midcondylar sagittal plane and the external cartilage surface yields the "anatomic midcondylar cartilage line". The location of the pathway of loading can be assessed relative to the anatomic midcondylar cartilage line of the medial femoral condyle. The identical procedure can be repeated for the lateral femoral condyle.
The following method can be used for the medial tibial plateau: A plane parallel to the sagittal tibial plateau plane can be defined through the most medial point of the medial tibial plateau. A parallel plane located halfway between this plane and the sagittal tibial plateau plane can yield the "midsagittal plane of the medial tibial plateau." The intersection of the midsagittal plane of the medial tibial plateau and the external cartilage surface can yield the "anatomic midtibial plateau cartilage line" of the medial tibial plateau. The identical procedure can be repeated for the lateral tibial plateau.
In the second approach, one can calculate a "natural" line of curvature for each femoral cartilage component (Fig. 20). Intuitively, if one could roll the femoral condyles along a hard, flat surface, the line of contact with the flat surface would be the natural line of curvature. One can compare the actual tibiofemoral contact line to this reference line. Since one cannot physically remove the femur and roll it around, one can apply some geometric calculations to estimate this reference line. One can begin with the trans-epicondylar reference line previously described. One can then generate a plane coincident with this line oriented in an arbitrary initial position. The intersection of this plane and the external surface of the cartilage will produce a curve. One can then take the point furthest from the trans-epicondylar reference line as the natural contact point for this plane location. The next step is to rotate the plane by some increment, for example by one degree, and repeat the procedure. The operator can identify the rotation angles where the plane is intersecting the distinct medial - lateral compartments of the cartilage, and two points can be chosen, one from the medial femoral condyle and one from the lateral femoral condyle. If cartilage defects are present, in which case a compartment will not intersect in a curve but in a set of points, one can fit a spline through the points, then take the peak point of the spline as the contact point.
This can be repeated for the entire extent of the cartilage, resulting in a set of points that branch at the intercondylar notch. One can treat these points as two lines, and fit them with two splines. These can be the "natural" lines of curvature for each compartment.
Load Bearing Line Determination
The calculations in this section can begin with the relative motion of the subject specific femoral anatomy with respect to the subject specific tibial anatomy, and end with a line describing the point of closest approach between the femur and tibia during some activity of daily living. A number of approaches to this problem have been described in the literature; Crosset, Dennis, Stiehl, and Johnson have all described techniques which might be applicable. One can implement a proximity detection and approach algorithm (PDAA) as it was specifically designed to work with the Point Cluster Technique (albeit with prosthetic knee j oint components) .
Physically, the tibial and femoral cartilage components deform under load, leading in general to a contact patch between opposing surfaces. As the geometric models are rigid, they will not deform under this load, but will instead intersect in a non-realizable manner. The PDAA has been designed to incrementally displace and rotate one of the surfaces until a realizable contact is achieved. It is understood that this is not a true point contact line, but rather a reproducible representation of contact location (Fig. 21).
The MR generated subject specific geometries can be used to detect rigid body contact proximity when the subject is in full extension. The femoral component can then be incrementally displaced until simultaneous medial and lateral condyle contact occur. This is a first order approximation to the location of the contact point; slip velocity calculations can then be used to determine the final estimate of the contact point. The next time step in the activity can now be examined, using the previous time step solution as a starting point for the calculation. The full extension time step can be chosen to match with the static reference posture; should it be necessary, one can add in other reference postures.
Once the contact points have been determined for all time steps of the activity, one can map the locations of these points onto the femoral cartilage. A coordinate system can be defined on the surface of the femoral cartilage, choosing as a reference line the point of contact the femoral component would have had were it rolled along a flat plane. This allows one to determine a contact line relative to the subject specific anatomy.
Provide Therapy
A 2D or 3D surface registration technique can be used as an aid to providing therapy to match the anatomic orientation of the cartilage thickness map of a baseline and follow-up scan of a patient. The re-registered cartilage thickness map of the follow-up scan can then be subtracted from the baseline scan. This will yield the thickness difference, i.e. cartilage loss, as a function of x, y, and z. This can also be expressed as percentage difference.
The invention provides for techniques to assess biomechanical loading conditions of articular cartilage in vivo using magnetic resonance imaging and to use the assessment as an aid in providing therapy to a patient. In one embodiment, biomechanical loading conditions can be assessed in normal articular cartilage in various anatomic regions. In the knee joint, these anatomic regions include the posterior, central, and anterior medial femoral condyle, the posterior, central, and anterior medial tibial plateau, the posterior, central, and anterior lateral femoral condyle, the posterior, central, and anterior lateral tibial plateau, the medial and lateral aspect of the trochlea, and the medial and lateral facet and the median ridge of the patella. Since biomechanical loading conditions are assessed in vivo based on the anatomic features of each individual patient, a risk profile can be established for each individual based on the biomechanical stresses applied to cartilage. In this fashion, patients who are at risk for developing early cartilage loss and osteoarthritis can be identified. For example, patients with a valgus or varus deformity of the knee joint will demonstrate higher biomechanical stresses applied to the articular cartilage in the medial femorotibial or lateral femorotibial or patellofemoral compartments than patients with normal joint anatomy. Similarly, patients with disturbances of joint congruity will demonstrate higher biomechanical stress applied to certain regions of the articular cartilage. Such disturbances of joint congruity are often difficult to detect using standard clinical and imaging assessment. The amount of stress applied to the articular cartilage can be used to determine the patient's individual prognosis for developing cartilage loss and osteoarthritis. In another embodiment, biomechanical loading conditions can be assessed in normal and diseased articular cartilage. An intervention that can alter load bearing can then be simulated. Such interventions include but are not limited to braces, orthotic devices, methods and devices to alter neuromuscular function or activation, arthroscopic and surgical procedures. The change in load bearing induced by the intervention can be assessed prior to actually performing the intervention in a patient. In this fashion, the most efficacious treatment modality can be determined. For example, a tibial osteotomy can be simulated in the manner and the optimal degree of angular correction with regard to biomechanical loading conditions of normal and diseased cartilage can be determined before the patient will actually undergo surgery.
Estimation of biomechanical forces applied to normal cartilage can be used to deteπnine a patient's risk for developing cartilage loss and osteoarthritis. Estimation offerees applied in and around a cartilage defect can be used to determine the prognosis of a cartilage defect and to guide the choice of therapy, e.g. treatment with chondroprotective or chondroregenerative agents, osteochondral allografting, cartilage transplantation, femoral or tibial osteotomy, or joint replacement surgery.
Having now provided a full discussion of various aspects of the technology relating to this invention, several further aspects of the invention can be seen.
One aspect of the invention is a method of assessing the condition of a joint in a mammal. The method comprises:
(a) comparing the movement pattern of the joint with the cartilage degeneration pattern of the joint; and
(b) determining the relationship between the movement pattern and the cartilage degeneration pattern Another aspect of the invention is a method for monitoring the treatment of a degenerative joint condition in a mammal. The method comprises
(a) comparing the movement pattern of the joint with the cartilage degeneration pattern of the joint:
(b) determining the relationship between the movement pattern and the cartilage degeneration pattern;
(c) treating the mammal to minimize further degeneration of the joint condition; and
(d) monitoring the treatment to the mammal.
Still another aspect of the invention is a method of assessing the rate of degeneration of cartilage in the joint of a mammal, wherein the joint comprises cartilage and the bones on either side of the cartilage, which method comprises
(a) obtaining a cartilage degeneration pattern of the joint that shows an area of greater than normal degeneration,
(b) obtaining a movement pattern of the joint that shows where the opposing cartilage surface contact,
(c) comparing the cartilage degeneration pattern with the movement pattern of the joint, and
(d) determining if the movement pattern shows contact of one cartilage surface with a portion of the opposing cartilage surface showing greater than normal degeneration in the cartilage degeneration pattern.
Another aspect of the specification is a method for assessing the condition of the knee joint of a human patient, wherein the knee joint comprises cartilage and associated bones on either side of the joint. The method comprises
(a) obtaining the patient's magnetic resonance imaging (MRI) data of the knee showing at least the cartilage on at least one side of the joint, (b) segmenting the MRI data from step (a),
(c) generating a geometrical or biochemical representation of the cartilage of the joint from the segmented MRI data,
(d) assessing the patient's gait to determine the cartilage surface contact pattern in the joint during the gait assessment, and
(e) correlating the contact pattern obtained in step (d) with the geometrical representation obtained in step (c).
Still another aspect of this invention is a method for assessing the condition of the knee joint of a human patient, wherein the knee joint comprises cartilage and associated bones on either side of the j oint. The method comprises
(a) obtaining the patient's magnetic resonance imaging (MRI) data of the knee showing at least the bones on either side of the joint,
(b) segmenting the MRI data from step (a),
(c) generating a geometrical representation of the bone of the joint from the segmented MRI data,
(d) assessing the patient's gait to determine the load pattern of the articular cartilage in the joint during the gait assessment,
(e) correlating the load pattern obtained in step (d) with the geometrical representation obtained in step (c).
Another aspect of this invention is a method for deriving the motion of bones about a joint from markers placed on the skin, which method comprises
(a) placing at least three external markers on the patient's limb segments surrounding the joint,
(b) registering the location of each marker on the patient's limb while the patient is standing completing still and while moving the limb, (c) calculating the principal axis, principal moments and deformation of rigidity of the cluster of markers, and
(d) calculating a correction to the artifact induced by the motion of the skin markers relative to the underlying bone.
Another aspect of the invention is a system for assessing the condition of cartilage in a joint of a human, which system comprises
(a) a device for electronically transferring a cartilage degeneration pattern for the joint to receiving device located distant from the transferring device;
(b) a device for receiving the cartilage degeneration pattern at the remote location;
(c) a database accessible at the remote location for generating a movement pattern for the joint of the human wherein the database includes a collection of movement patterns for human joints, which patterns are organized and can be accessed by reference to characteristics such as type of joint, gender, age, height, weight, bone size, type of movement, and distance of movement;
(d) a device for generating a movement pattern that most closely approximates a movement pattern for the human patient based on the characteristics of the human patient;
(e) a device for correlating the movement pattern with the cartilage degeneration pattern; and
(f) a device for transmitting the correlated movement pattern with the cartilage degeneration pattern back to the source of the cartilage degeneration pattern.
In each of these aspects of the invention it is to be understood that a cartilage degeneration pattern may be, i.a., 2D or 3D thickness map of the cartilage or a biochemical map of the cartilage.
All publications and patent applications mentioned in this specification are herein incoφorated by reference to the same extent as if each individual publication or patent application was specifically and individually indicated to be incoφorated by reference. The invention now being fully described, it will be apparent to one of ordinary skill in the art that many changes and modifications can be made thereto without departing from the spirit or scope of the appended claims.

Claims (16)

CLAIMSWhat is claimed is:
1. A method of assessing cartilage damage or disease in a joint comprising cartilage and accompanying bone on either side of the joint, which method comprises
(a) obtaining a three-dimensional map of cartilage of said joint in which said map demonstrates thickness or biochemical contents or relaxation time of both normal and damaged or diseased cartilage of said joint, and
(b) determining at least one margin between damaged or diseased cartilage and normal cartilage in said three-dimensional map.
2. The method of claim 1, wherein said margin is determined by detecting a difference in said thickness, said biochemical contents or said relaxation time between said normal and said damaged or diseased cartilage.
3. The method of claim 1, wherein said margin of said damaged or diseased cartilage is used to determine an area, volume, or thickness of damaged or diseased cartilage in said joint or a percentage of total cartilage surface area or of articular surface area or of weight-bearing surface area represented by said damaged or diseased cartilage in said joint.
4. The method of Claim 1, wherein the joint is a knee joint.
5. The method of Claim 1, wherein said map is used to devise a treatment for damaged or diseased cartilage or bone.
6. The method of Claim 1, wherein said method is carried out at an initial time Ti and at a later time T2 and said method includes an analysis of degree of degeneration of the cartilage between Ti and T2.
7. The method claim 1, wherein the three-dimensional map of cartilage is obtained by a magnetic resonance imaging (MRI) technique.
8. The method of Claim 7, wherein the MRI technique first obtains a series of two- dimensional views of the joint, which are then mathematically integrated to give a three- dimensional image.
9. The method of Claim 7, wherein the MRI technique employs a gradient echo, spin echo, fast-spin echo, driven equilibrium fournier transform, or spoiled gradient echo technique.
10. A method of assessing cartilage disease or damage in a joint comprising cartilage and accompanying bone on either side of the joint, which method comprises:
" (a) obtaining a three-dimensional map of cartilage of said joint demonstrating thickness or biochemical contents or relaxation time of both normal and diseased or damaged cartilage of said joint, and
(b) estimating thickness or area or volume of lost cartilage tissue relative to expected cartilage tissue in absence of disease or damage.
11. The method of claim 10, wherein said thickness, area or volume of said cartilage tissue that has been lost is performed by determining a margin between said diseased or damaged cartilage and said normal cartilage in said three-dimensional map.
12. The method of claim 11, wherein said margin is determined by measuring changes in said thickness of said normal and said diseased cartilage, in said biochemical content of said normal and said diseased cartilage, or in said relaxation time of said normal and said diseased cartilage.
13. The method of Claim 10, wherein said method is carried out at an initial time Ti and at a later time T and said determination includes a determination of amount of cartilage lost between Ti and T2.
14. The method of claim 13, wherein said amount of cartilage tissue lost is determined as thickness or area or volume or content in one or more biochemical components of said cartilage tissue lost.
15. The method of claim 14, wherein said thickness, area, volume, or content of said cartilage tissue lost is determined by determining a margin between diseased or damaged cartilage and normal cartilage.
16. The method of claim 13, wherein said change in said diseased cartilage or said cartilage tissue lost is determined without matching data obtained at Ti and T2.
AU2001290887A 2000-09-14 2001-09-14 Assessing condition of a joint and cartilage loss Ceased AU2001290887B2 (en)

Priority Applications (1)

Application Number Priority Date Filing Date Title
AU2006207884A AU2006207884A1 (en) 2000-09-14 2006-09-07 Assessing condition of a joint and cartilage loss

Applications Claiming Priority (5)

Application Number Priority Date Filing Date Title
US23263700P 2000-09-14 2000-09-14
US23263900P 2000-09-14 2000-09-14
US60232637 2000-09-14
US60232639 2000-09-14
PCT/US2001/028679 WO2002022013A1 (en) 2000-09-14 2001-09-14 Assessing condition of a joint and cartilage loss

Related Child Applications (1)

Application Number Title Priority Date Filing Date
AU2006207884A Division AU2006207884A1 (en) 2000-09-14 2006-09-07 Assessing condition of a joint and cartilage loss

Publications (2)

Publication Number Publication Date
AU2001290887A1 true AU2001290887A1 (en) 2002-06-13
AU2001290887B2 AU2001290887B2 (en) 2006-06-08

Family

ID=26926188

Family Applications (2)

Application Number Title Priority Date Filing Date
AU2001290887A Ceased AU2001290887B2 (en) 2000-09-14 2001-09-14 Assessing condition of a joint and cartilage loss
AU9088701A Pending AU9088701A (en) 2000-09-14 2001-09-14 Assessing condition of a joint and cartilage loss

Family Applications After (1)

Application Number Title Priority Date Filing Date
AU9088701A Pending AU9088701A (en) 2000-09-14 2001-09-14 Assessing condition of a joint and cartilage loss

Country Status (7)

Country Link
US (2) US7184814B2 (en)
EP (2) EP2036495A1 (en)
AT (2) ATE414310T1 (en)
AU (2) AU2001290887B2 (en)
CA (1) CA2425089A1 (en)
DE (1) DE60136474D1 (en)
WO (1) WO2002022013A1 (en)

Families Citing this family (268)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US8735773B2 (en) 2007-02-14 2014-05-27 Conformis, Inc. Implant device and method for manufacture
US7634119B2 (en) 2002-12-04 2009-12-15 Conformis, Inc. Fusion of multiple imaging planes for isotropic imaging in MRI and quantitative image analysis using isotropic or near-isotropic imaging
US8480754B2 (en) 2001-05-25 2013-07-09 Conformis, Inc. Patient-adapted and improved articular implants, designs and related guide tools
US20110071645A1 (en) * 2009-02-25 2011-03-24 Ray Bojarski Patient-adapted and improved articular implants, designs and related guide tools
US8556983B2 (en) 2001-05-25 2013-10-15 Conformis, Inc. Patient-adapted and improved orthopedic implants, designs and related tools
US7618451B2 (en) * 2001-05-25 2009-11-17 Conformis, Inc. Patient selectable joint arthroplasty devices and surgical tools facilitating increased accuracy, speed and simplicity in performing total and partial joint arthroplasty
US7468075B2 (en) 2001-05-25 2008-12-23 Conformis, Inc. Methods and compositions for articular repair
US20090222103A1 (en) * 2001-05-25 2009-09-03 Conformis, Inc. Articular Implants Providing Lower Adjacent Cartilage Wear
US8545569B2 (en) 2001-05-25 2013-10-01 Conformis, Inc. Patient selectable knee arthroplasty devices
US8882847B2 (en) 2001-05-25 2014-11-11 Conformis, Inc. Patient selectable knee joint arthroplasty devices
US7534263B2 (en) 2001-05-25 2009-05-19 Conformis, Inc. Surgical tools facilitating increased accuracy, speed and simplicity in performing joint arthroplasty
US8771365B2 (en) 2009-02-25 2014-07-08 Conformis, Inc. Patient-adapted and improved orthopedic implants, designs, and related tools
US20070233269A1 (en) * 2001-05-25 2007-10-04 Conformis, Inc. Interpositional Joint Implant
US20110071802A1 (en) * 2009-02-25 2011-03-24 Ray Bojarski Patient-adapted and improved articular implants, designs and related guide tools
US8617242B2 (en) 2001-05-25 2013-12-31 Conformis, Inc. Implant device and method for manufacture
US9603711B2 (en) 2001-05-25 2017-03-28 Conformis, Inc. Patient-adapted and improved articular implants, designs and related guide tools
US8083745B2 (en) * 2001-05-25 2011-12-27 Conformis, Inc. Surgical tools for arthroplasty
ATE439806T1 (en) 1998-09-14 2009-09-15 Univ Leland Stanford Junior DETERMINING THE CONDITION OF A JOINT AND PREVENTING DAMAGE
US7239908B1 (en) 1998-09-14 2007-07-03 The Board Of Trustees Of The Leland Stanford Junior University Assessing the condition of a joint and devising treatment
US9289153B2 (en) * 1998-09-14 2016-03-22 The Board Of Trustees Of The Leland Stanford Junior University Joint and cartilage diagnosis, assessment and modeling
EP1230561B1 (en) * 1999-11-01 2005-10-26 Arthrovision, Inc. Evaluating disease progression using magnetic resonance imaging
US7467892B2 (en) 2000-08-29 2008-12-23 Imaging Therapeutics, Inc. Calibration devices and methods of use thereof
US20020186818A1 (en) * 2000-08-29 2002-12-12 Osteonet, Inc. System and method for building and manipulating a centralized measurement value database
WO2002017789A2 (en) * 2000-08-29 2002-03-07 Imaging Therapeutics Methods and devices for quantitative analysis of x-ray images
US6904123B2 (en) * 2000-08-29 2005-06-07 Imaging Therapeutics, Inc. Methods and devices for quantitative analysis of x-ray images
ATE414310T1 (en) 2000-09-14 2008-11-15 Univ Leland Stanford Junior METHOD FOR MANIPULATION OF MEDICAL IMAGES
WO2002022014A1 (en) 2000-09-14 2002-03-21 The Board Of Trustees Of The Leland Stanford Junior University Assessing the condition of a joint and devising treatment
US7660453B2 (en) 2000-10-11 2010-02-09 Imaging Therapeutics, Inc. Methods and devices for analysis of x-ray images
US8639009B2 (en) 2000-10-11 2014-01-28 Imatx, Inc. Methods and devices for evaluating and treating a bone condition based on x-ray image analysis
US7339375B1 (en) * 2001-01-26 2008-03-04 Fonar Corporation Driven equilibrium and fast-spin echo scanning
US7664297B2 (en) * 2001-04-26 2010-02-16 Teijin Limited Three-dimensional joint structure measuring method
EP1399068A1 (en) * 2001-05-16 2004-03-24 Koninklijke Philips Electronics N.V. Automatic prescription of tomographic parameters
US20070083266A1 (en) * 2001-05-25 2007-04-12 Vertegen, Inc. Devices and methods for treating facet joints, uncovertebral joints, costovertebral joints and other joints
EP1389980B1 (en) 2001-05-25 2011-04-06 Conformis, Inc. Methods and compositions for articular resurfacing
EP1389947B1 (en) 2001-05-25 2009-08-26 Imaging Therapeutics, Inc. Methods to diagnose treat and prevent bone loss
US8439926B2 (en) 2001-05-25 2013-05-14 Conformis, Inc. Patient selectable joint arthroplasty devices and surgical tools
US20050033151A1 (en) * 2001-10-19 2005-02-10 Wu Ed X Combined magnetic resonance data acquisition of multi-contrast images using variable acquisition parameters and k-space data sharing
US20030086596A1 (en) * 2001-11-07 2003-05-08 Medical Metrics, Inc. Method, computer software, and system for tracking, stabilizing, and reporting motion between vertebrae
US8724865B2 (en) * 2001-11-07 2014-05-13 Medical Metrics, Inc. Method, computer software, and system for tracking, stabilizing, and reporting motion between vertebrae
DE10210050A1 (en) * 2002-03-07 2003-12-04 Siemens Ag Method and device for repetitive relative positioning of a patient
JP3639825B2 (en) * 2002-04-03 2005-04-20 キヤノン株式会社 Moving image display method, program, computer-readable storage medium, and moving image display device
US8801720B2 (en) 2002-05-15 2014-08-12 Otismed Corporation Total joint arthroplasty system
US7490012B2 (en) * 2002-05-29 2009-02-10 Japan Science And Technology Agency Body dynamics calculation method, body dynamics model and model data thereof, and body-model generation method
EP1519681B1 (en) * 2002-07-09 2006-11-29 Anglo-European College of Chiropractic Ltd Method for imaging the relative motion of skeletal segments
AU2003252124A1 (en) * 2002-07-22 2004-02-09 Compumed, Inc. Method, code, and system for assaying joint deformity
US7840247B2 (en) 2002-09-16 2010-11-23 Imatx, Inc. Methods of predicting musculoskeletal disease
US8965075B2 (en) 2002-09-16 2015-02-24 Imatx, Inc. System and method for predicting future fractures
WO2004025541A1 (en) * 2002-09-16 2004-03-25 Imaging Therapeutics, Inc. Imaging markers in musculoskeletal disease
ATE497740T1 (en) 2002-10-07 2011-02-15 Conformis Inc MINIMALLY INVASIVE JOINT IMPLANT WITH A THREE-DIMENSIONAL GEOMETRY ADAPTED TO THE JOINT SURFACES
JP2004147930A (en) * 2002-10-31 2004-05-27 Fuji Photo Film Co Ltd Image diagnostic apparatus
US7796791B2 (en) 2002-11-07 2010-09-14 Conformis, Inc. Methods for determining meniscal size and shape and for devising treatment
US20040147830A1 (en) * 2003-01-29 2004-07-29 Virtualscopics Method and system for use of biomarkers in diagnostic imaging
DE10312711A1 (en) * 2003-03-21 2004-10-07 Universität Leipzig Magnetic resonance tomography method for zonal resolved determination of the order parameter of the collagen network of articular cartilage in a single MRT image
CA2519187A1 (en) 2003-03-25 2004-10-14 Imaging Therapeutics, Inc. Methods for the compensation of imaging technique in the processing of radiographic images
US8243876B2 (en) 2003-04-25 2012-08-14 Rapiscan Systems, Inc. X-ray scanners
GB0525593D0 (en) 2005-12-16 2006-01-25 Cxr Ltd X-ray tomography inspection systems
WO2004112580A2 (en) * 2003-06-19 2004-12-29 Compumed, Inc. Method and system for analyzing bone conditions using dicom compliant bone radiographic image
US20050015002A1 (en) * 2003-07-18 2005-01-20 Dixon Gary S. Integrated protocol for diagnosis, treatment, and prevention of bone mass degradation
US7905924B2 (en) * 2003-09-03 2011-03-15 Ralph Richard White Extracapsular surgical procedure
ITSV20030033A1 (en) * 2003-09-09 2005-03-10 Esaote Spa METHOD AND DEVICE FOR DIAGNOSTIC EXTREME IMAGING,
US8290564B2 (en) * 2003-09-19 2012-10-16 Imatx, Inc. Method for bone structure prognosis and simulated bone remodeling
WO2005027732A2 (en) 2003-09-19 2005-03-31 Imaging Therapeutics, Inc. Method for bone structure prognosis and simulated bone remodeling
US20050113663A1 (en) * 2003-11-20 2005-05-26 Jose Tamez-Pena Method and system for automatic extraction of load-bearing regions of the cartilage and measurement of biomarkers
US7310435B2 (en) 2003-11-25 2007-12-18 General Electric Company Method and apparatus for extracting multi-dimensional structures using dynamic constraints
US7460737B2 (en) 2004-02-12 2008-12-02 Hoshiko Llc Method and apparatus for photograph finding
US7555153B2 (en) * 2004-07-01 2009-06-30 Arthrovision Inc. Non-invasive joint evaluation
US7042219B2 (en) 2004-08-12 2006-05-09 Esaote S.P.A. Method for determining the condition of an object by magnetic resonance imaging
US7519210B2 (en) * 2004-09-09 2009-04-14 Raphael Hirsch Method of assessing localized shape and temperature of the human body
DE102004044433A1 (en) * 2004-09-14 2006-01-05 Siemens Ag Bone displaying method for diagnosis of malicious tumor, involves creating data record of bones by magnetic resonance examination, and segmenting record of bones, where bones are marked in record by user, before segmentation
CA2580726A1 (en) 2004-09-16 2006-03-30 Imaging Therapeutics, Inc. System and method of predicting future fractures
US8043315B2 (en) * 2004-09-23 2011-10-25 Arthrex, Inc. Osteochondral repair using plug fashioned from partial distal allograft femur or condyle
CN101147158B (en) * 2004-11-18 2012-04-18 计算医学公司 Methods and systems for analyzing bone conditions using mammography device
TWI268148B (en) * 2004-11-25 2006-12-11 Univ Chung Yuan Christian Image analysis method for vertebral disease which comprises 3D reconstruction method and characteristic identification method of unaligned transversal slices
WO2006085387A1 (en) * 2005-02-08 2006-08-17 Kouki Nagamune Noninvasive moving body analytic system and its using method
DE102005017337B4 (en) * 2005-04-14 2008-06-19 Siemens Ag Method, device and data carrier with a computer program product for the analysis of three-dimensional digital image data
US20060247864A1 (en) * 2005-04-29 2006-11-02 Jose Tamez-Pena Method and system for assessment of biomarkers by measurement of response to surgical implant
US7352370B2 (en) * 2005-06-02 2008-04-01 Accuray Incorporated Four-dimensional volume of interest
DE602006010089D1 (en) * 2005-08-11 2009-12-10 Philips Intellectual Property REPRODUCING A VIEW FROM AN IMAGE RECORD
AU2006297137A1 (en) * 2005-09-30 2007-04-12 Conformis Inc. Joint arthroplasty devices
CN102599960B (en) 2006-02-06 2015-08-12 康复米斯公司 The arthroplasty devices that patient-selectable selects and surgical instrument
US8623026B2 (en) 2006-02-06 2014-01-07 Conformis, Inc. Patient selectable joint arthroplasty devices and surgical tools incorporating anatomical relief
US9808262B2 (en) * 2006-02-15 2017-11-07 Howmedica Osteonics Corporation Arthroplasty devices and related methods
US9017336B2 (en) * 2006-02-15 2015-04-28 Otismed Corporation Arthroplasty devices and related methods
US9345548B2 (en) 2006-02-27 2016-05-24 Biomet Manufacturing, Llc Patient-specific pre-operative planning
US9339278B2 (en) 2006-02-27 2016-05-17 Biomet Manufacturing, Llc Patient-specific acetabular guides and associated instruments
US8603180B2 (en) 2006-02-27 2013-12-10 Biomet Manufacturing, Llc Patient-specific acetabular alignment guides
US8535387B2 (en) 2006-02-27 2013-09-17 Biomet Manufacturing, Llc Patient-specific tools and implants
US8608749B2 (en) 2006-02-27 2013-12-17 Biomet Manufacturing, Llc Patient-specific acetabular guides and associated instruments
US9907659B2 (en) 2007-04-17 2018-03-06 Biomet Manufacturing, Llc Method and apparatus for manufacturing an implant
US9113971B2 (en) 2006-02-27 2015-08-25 Biomet Manufacturing, Llc Femoral acetabular impingement guide
US8858561B2 (en) * 2006-06-09 2014-10-14 Blomet Manufacturing, LLC Patient-specific alignment guide
US8241293B2 (en) 2006-02-27 2012-08-14 Biomet Manufacturing Corp. Patient specific high tibia osteotomy
US8282646B2 (en) 2006-02-27 2012-10-09 Biomet Manufacturing Corp. Patient specific knee alignment guide and associated method
US9918740B2 (en) 2006-02-27 2018-03-20 Biomet Manufacturing, Llc Backup surgical instrument system and method
US20150335438A1 (en) 2006-02-27 2015-11-26 Biomet Manufacturing, Llc. Patient-specific augments
US8133234B2 (en) 2006-02-27 2012-03-13 Biomet Manufacturing Corp. Patient specific acetabular guide and method
US8473305B2 (en) 2007-04-17 2013-06-25 Biomet Manufacturing Corp. Method and apparatus for manufacturing an implant
US8608748B2 (en) 2006-02-27 2013-12-17 Biomet Manufacturing, Llc Patient specific guides
US8568487B2 (en) * 2006-02-27 2013-10-29 Biomet Manufacturing, Llc Patient-specific hip joint devices
US8377066B2 (en) 2006-02-27 2013-02-19 Biomet Manufacturing Corp. Patient-specific elbow guides and associated methods
US8298237B2 (en) * 2006-06-09 2012-10-30 Biomet Manufacturing Corp. Patient-specific alignment guide for multiple incisions
US9173661B2 (en) * 2006-02-27 2015-11-03 Biomet Manufacturing, Llc Patient specific alignment guide with cutting surface and laser indicator
US8591516B2 (en) 2006-02-27 2013-11-26 Biomet Manufacturing, Llc Patient-specific orthopedic instruments
US20110190899A1 (en) * 2006-02-27 2011-08-04 Biomet Manufacturing Corp. Patient-specific augments
US8864769B2 (en) * 2006-02-27 2014-10-21 Biomet Manufacturing, Llc Alignment guides with patient-specific anchoring elements
US8092465B2 (en) * 2006-06-09 2012-01-10 Biomet Manufacturing Corp. Patient specific knee alignment guide and associated method
US8070752B2 (en) 2006-02-27 2011-12-06 Biomet Manufacturing Corp. Patient specific alignment guide and inter-operative adjustment
US8407067B2 (en) 2007-04-17 2013-03-26 Biomet Manufacturing Corp. Method and apparatus for manufacturing an implant
US10278711B2 (en) 2006-02-27 2019-05-07 Biomet Manufacturing, Llc Patient-specific femoral guide
US7967868B2 (en) 2007-04-17 2011-06-28 Biomet Manufacturing Corp. Patient-modified implant and associated method
US9289253B2 (en) 2006-02-27 2016-03-22 Biomet Manufacturing, Llc Patient-specific shoulder guide
US8676293B2 (en) * 2006-04-13 2014-03-18 Aecc Enterprises Ltd. Devices, systems and methods for measuring and evaluating the motion and function of joint structures and associated muscles, determining suitability for orthopedic intervention, and evaluating efficacy of orthopedic intervention
US9795399B2 (en) 2006-06-09 2017-10-24 Biomet Manufacturing, Llc Patient-specific knee alignment guide and associated method
US8284202B2 (en) * 2006-06-30 2012-10-09 Two Pic Mc Llc Methods and apparatus for capturing and rendering dynamic surface deformations in human motion
US8331635B2 (en) * 2006-07-06 2012-12-11 University Of South Florida Cartesian human morpho-informatic system
US20080139922A1 (en) * 2006-07-21 2008-06-12 Jean-Pierre Pelletier Evaluation of cartilage of the hip using MRI images
US20080063301A1 (en) * 2006-09-12 2008-03-13 Luca Bogoni Joint Segmentation and Registration
WO2008041946A1 (en) * 2006-10-03 2008-04-10 Agency For Science, Technology And Research Segmenting infarct in diffusion-weighted imaging volume
EP1913868A1 (en) * 2006-10-19 2008-04-23 Esaote S.p.A. System for determining diagnostic indications
US8460302B2 (en) * 2006-12-18 2013-06-11 Otismed Corporation Arthroplasty devices and related methods
US7792379B2 (en) * 2007-02-06 2010-09-07 Accenture Global Services Gmbh Transforming a submitted image of a person based on a condition of the person
DE102007006142A1 (en) * 2007-02-07 2008-08-14 Siemens Ag Method and apparatus for automatically determining a flow of body fluid within vessels of a living being
US7778488B2 (en) * 2007-03-23 2010-08-17 Varian Medical Systems International Ag Image deformation using multiple image regions
CA2686260A1 (en) * 2007-05-03 2008-11-13 Centocor Ortho Biotech Inc. Matrix marker model and methods for assessing and treating arthritis and related disorders
WO2008144539A1 (en) * 2007-05-17 2008-11-27 Yeda Research & Development Co. Ltd. Method and apparatus for computer-aided diagnosis of cancer and product
WO2008157412A2 (en) 2007-06-13 2008-12-24 Conformis, Inc. Surgical cutting guide
US7959742B2 (en) * 2007-07-11 2011-06-14 Whirlpool Corporation Outer support body for a drawer-type dishwasher
US8027430B2 (en) * 2007-07-30 2011-09-27 Varian Medical Systems International Ag Systems and methods for adapting a movement model based on an image
GB0714940D0 (en) * 2007-08-01 2007-09-12 Depuy Orthopaedie Gmbh Image processing
US20090060366A1 (en) * 2007-08-27 2009-03-05 Riverain Medical Group, Llc Object segmentation in images
EP2194836B1 (en) 2007-09-25 2015-11-04 Perception Raisonnement Action En Medecine Apparatus for assisting cartilage diagnostic and therapeutic procedures
US8265949B2 (en) 2007-09-27 2012-09-11 Depuy Products, Inc. Customized patient surgical plan
US8357111B2 (en) 2007-09-30 2013-01-22 Depuy Products, Inc. Method and system for designing patient-specific orthopaedic surgical instruments
CN102670275B (en) 2007-09-30 2016-01-20 德普伊产品公司 The patient-specific orthopaedic surgical instrumentation of customization
US20090099481A1 (en) 2007-10-10 2009-04-16 Adam Deitz Devices, Systems and Methods for Measuring and Evaluating the Motion and Function of Joints and Associated Muscles
USD642263S1 (en) 2007-10-25 2011-07-26 Otismed Corporation Arthroplasty jig blank
US8460303B2 (en) * 2007-10-25 2013-06-11 Otismed Corporation Arthroplasty systems and devices, and related methods
US9171344B2 (en) 2007-10-30 2015-10-27 Onemednet Corporation Methods, systems, and devices for managing medical images and records
US8065166B2 (en) 2007-10-30 2011-11-22 Onemednet Corporation Methods, systems, and devices for managing medical images and records
US10582934B2 (en) * 2007-11-27 2020-03-10 Howmedica Osteonics Corporation Generating MRI images usable for the creation of 3D bone models employed to make customized arthroplasty jigs
US8715291B2 (en) * 2007-12-18 2014-05-06 Otismed Corporation Arthroplasty system and related methods
US8737700B2 (en) * 2007-12-18 2014-05-27 Otismed Corporation Preoperatively planning an arthroplasty procedure and generating a corresponding patient specific arthroplasty resection guide
US8160345B2 (en) * 2008-04-30 2012-04-17 Otismed Corporation System and method for image segmentation in generating computer models of a joint to undergo arthroplasty
US8221430B2 (en) 2007-12-18 2012-07-17 Otismed Corporation System and method for manufacturing arthroplasty jigs
US8480679B2 (en) * 2008-04-29 2013-07-09 Otismed Corporation Generation of a computerized bone model representative of a pre-degenerated state and useable in the design and manufacture of arthroplasty devices
US8311306B2 (en) 2008-04-30 2012-11-13 Otismed Corporation System and method for image segmentation in generating computer models of a joint to undergo arthroplasty
US8777875B2 (en) * 2008-07-23 2014-07-15 Otismed Corporation System and method for manufacturing arthroplasty jigs having improved mating accuracy
US8617171B2 (en) * 2007-12-18 2013-12-31 Otismed Corporation Preoperatively planning an arthroplasty procedure and generating a corresponding patient specific arthroplasty resection guide
US8545509B2 (en) * 2007-12-18 2013-10-01 Otismed Corporation Arthroplasty system and related methods
US8734455B2 (en) * 2008-02-29 2014-05-27 Otismed Corporation Hip resurfacing surgical guide tool
US8682052B2 (en) 2008-03-05 2014-03-25 Conformis, Inc. Implants for altering wear patterns of articular surfaces
EP2901969B1 (en) * 2008-03-05 2018-07-04 ConforMIS, Inc. Method of making an edge-matched articular implant
US8050493B2 (en) * 2008-03-31 2011-11-01 Konica Minolta Laboratory U.S.A., Inc. Method for generating a high quality scanned image of a document
AU2009246474B2 (en) 2008-05-12 2015-04-16 Conformis, Inc. Devices and methods for treatment of facet and other joints
US9020577B2 (en) * 2008-05-29 2015-04-28 Yale University Systems, devices and methods for cartilage and bone grafting
TWI426889B (en) * 2008-06-19 2014-02-21 Univ Ishou Multi - media Full - size Orthodontic Bone Plate Fixation Surgery Preoperative Planning System
US8617175B2 (en) * 2008-12-16 2013-12-31 Otismed Corporation Unicompartmental customized arthroplasty cutting jigs and methods of making the same
WO2010010193A1 (en) * 2008-07-24 2010-01-28 Universiteit Gent A scoring system to monitor natural or drug-modified disease progression in “erosive osteoarthritis" of the interphalangeal finger joints
US8696603B2 (en) * 2008-12-04 2014-04-15 Fujifilm Corporation System for measuring space width of joint, method for measuring space width of joint and recording medium
US8538102B2 (en) * 2008-12-17 2013-09-17 Synarc Inc Optimised region of interest selection
US8444564B2 (en) 2009-02-02 2013-05-21 Jointvue, Llc Noninvasive diagnostic system
US8939917B2 (en) * 2009-02-13 2015-01-27 Imatx, Inc. Methods and devices for quantitative analysis of bone and cartilage
US8170641B2 (en) 2009-02-20 2012-05-01 Biomet Manufacturing Corp. Method of imaging an extremity of a patient
US8808297B2 (en) 2009-02-24 2014-08-19 Microport Orthopedics Holdings Inc. Orthopedic surgical guide
US8808303B2 (en) 2009-02-24 2014-08-19 Microport Orthopedics Holdings Inc. Orthopedic surgical guide
WO2010099231A2 (en) 2009-02-24 2010-09-02 Conformis, Inc. Automated systems for manufacturing patient-specific orthopedic implants and instrumentation
US9017334B2 (en) 2009-02-24 2015-04-28 Microport Orthopedics Holdings Inc. Patient specific surgical guide locator and mount
CN102365061B (en) * 2009-02-25 2015-06-17 捷迈有限公司 Customized orthopaedic implants and related methods
DE102009015116B4 (en) * 2009-03-31 2016-03-03 Tomtec Imaging Systems Gmbh Method and device for registering image data sets and for reducing position-dependent gray scale fluctuations, together with associated objects
AU2010236263A1 (en) 2009-04-16 2011-11-10 Conformis, Inc. Patient-specific joint arthroplasty devices for ligament repair
WO2010126797A1 (en) 2009-04-29 2010-11-04 Onemednet Corporation Methods, systems, and devices for managing medical images and records
US20110028981A1 (en) * 2009-07-29 2011-02-03 Warsaw Orthopedic, Inc. Bone graft measuring apparatus and method of use
DE102009028503B4 (en) 2009-08-13 2013-11-14 Biomet Manufacturing Corp. Resection template for the resection of bones, method for producing such a resection template and operation set for performing knee joint surgery
JP5355316B2 (en) * 2009-09-10 2013-11-27 キヤノン株式会社 Template image evaluation method and biological motion detection apparatus
WO2011038236A2 (en) 2009-09-25 2011-03-31 Ortho Kinematics, Inc. Systems and devices for an integrated imaging system with real-time feedback loops and methods therefor
AU2010327987B2 (en) 2009-12-11 2015-04-02 Conformis, Inc. Patient-specific and patient-engineered orthopedic implants
US8632547B2 (en) * 2010-02-26 2014-01-21 Biomet Sports Medicine, Llc Patient-specific osteotomy devices and methods
US9066727B2 (en) 2010-03-04 2015-06-30 Materialise Nv Patient-specific computed tomography guides
US9532732B2 (en) * 2010-05-03 2017-01-03 Emovi Inc. Method and system for knee joint evaluation and diagnostic aid in normal and pathologic state
US8974459B1 (en) 2010-05-21 2015-03-10 Howmedica Osteonics Corp. Natural alignment knee instruments
JP5845253B2 (en) * 2010-06-16 2016-01-20 エーツー・サージカル Method and system for automatically determining geometric elements characterizing bone deformation from 3D images
US9271744B2 (en) 2010-09-29 2016-03-01 Biomet Manufacturing, Llc Patient-specific guide for partial acetabular socket replacement
US9968376B2 (en) 2010-11-29 2018-05-15 Biomet Manufacturing, Llc Patient-specific orthopedic instruments
AU2012217654B2 (en) 2011-02-15 2016-09-22 Conformis, Inc. Patient-adapted and improved articular implants, procedures and tools to address, assess, correct, modify and/or accommodate anatomical variation and/or asymmetry
US9241745B2 (en) 2011-03-07 2016-01-26 Biomet Manufacturing, Llc Patient-specific femoral version guide
US8306299B2 (en) * 2011-03-25 2012-11-06 Wisconsin Alumni Research Foundation Method for reconstructing motion-compensated magnetic resonance images from non-Cartesian k-space data
US8715289B2 (en) 2011-04-15 2014-05-06 Biomet Manufacturing, Llc Patient-specific numerically controlled instrument
US9675400B2 (en) 2011-04-19 2017-06-13 Biomet Manufacturing, Llc Patient-specific fracture fixation instrumentation and method
US8668700B2 (en) 2011-04-29 2014-03-11 Biomet Manufacturing, Llc Patient-specific convertible guides
US8956364B2 (en) 2011-04-29 2015-02-17 Biomet Manufacturing, Llc Patient-specific partial knee guides and other instruments
US8532807B2 (en) 2011-06-06 2013-09-10 Biomet Manufacturing, Llc Pre-operative planning and manufacturing method for orthopedic procedure
US9084618B2 (en) 2011-06-13 2015-07-21 Biomet Manufacturing, Llc Drill guides for confirming alignment of patient-specific alignment guides
US20130001121A1 (en) 2011-07-01 2013-01-03 Biomet Manufacturing Corp. Backup kit for a patient-specific arthroplasty kit assembly
US8764760B2 (en) 2011-07-01 2014-07-01 Biomet Manufacturing, Llc Patient-specific bone-cutting guidance instruments and methods
US8597365B2 (en) 2011-08-04 2013-12-03 Biomet Manufacturing, Llc Patient-specific pelvic implants for acetabular reconstruction
US9295497B2 (en) 2011-08-31 2016-03-29 Biomet Manufacturing, Llc Patient-specific sacroiliac and pedicle guides
US9066734B2 (en) 2011-08-31 2015-06-30 Biomet Manufacturing, Llc Patient-specific sacroiliac guides and associated methods
KR101828411B1 (en) * 2011-09-21 2018-02-13 삼성전자주식회사 Image processing method and image processing apparatus
US9386993B2 (en) 2011-09-29 2016-07-12 Biomet Manufacturing, Llc Patient-specific femoroacetabular impingement instruments and methods
KR20130046336A (en) 2011-10-27 2013-05-07 삼성전자주식회사 Multi-view device of display apparatus and contol method thereof, and display system
US9301812B2 (en) 2011-10-27 2016-04-05 Biomet Manufacturing, Llc Methods for patient-specific shoulder arthroplasty
US9451973B2 (en) 2011-10-27 2016-09-27 Biomet Manufacturing, Llc Patient specific glenoid guide
US9554910B2 (en) 2011-10-27 2017-01-31 Biomet Manufacturing, Llc Patient-specific glenoid guide and implants
EP3384858A1 (en) 2011-10-27 2018-10-10 Biomet Manufacturing, LLC Patient-specific glenoid guides
US9408686B1 (en) 2012-01-20 2016-08-09 Conformis, Inc. Devices, systems and methods for manufacturing orthopedic implants
US9237950B2 (en) 2012-02-02 2016-01-19 Biomet Manufacturing, Llc Implant with patient-specific porous structure
WO2013144791A1 (en) * 2012-03-26 2013-10-03 Koninklijke Philips N.V. Through-plane navigator
US9486226B2 (en) 2012-04-18 2016-11-08 Conformis, Inc. Tibial guides, tools, and techniques for resecting the tibial plateau
US9675471B2 (en) 2012-06-11 2017-06-13 Conformis, Inc. Devices, techniques and methods for assessing joint spacing, balancing soft tissues and obtaining desired kinematics for joint implant components
US9402637B2 (en) 2012-10-11 2016-08-02 Howmedica Osteonics Corporation Customized arthroplasty cutting guides and surgical methods using the same
US9204977B2 (en) 2012-12-11 2015-12-08 Biomet Manufacturing, Llc Patient-specific acetabular guide for anterior approach
US9060788B2 (en) 2012-12-11 2015-06-23 Biomet Manufacturing, Llc Patient-specific acetabular guide for anterior approach
US9091628B2 (en) 2012-12-21 2015-07-28 L-3 Communications Security And Detection Systems, Inc. 3D mapping with two orthogonal imaging views
JP5982726B2 (en) * 2012-12-28 2016-08-31 株式会社日立製作所 Volume data analysis system and method
CN104837410B (en) * 2012-12-28 2017-09-22 古野电气株式会社 Soft tissue cartilage boundary face detection method, soft tissue cartilage boundary face detection means
US9387083B2 (en) 2013-01-30 2016-07-12 Conformis, Inc. Acquiring and utilizing kinematic information for patient-adapted implants, tools and surgical procedures
US9839438B2 (en) 2013-03-11 2017-12-12 Biomet Manufacturing, Llc Patient-specific glenoid guide with a reusable guide holder
US9579107B2 (en) 2013-03-12 2017-02-28 Biomet Manufacturing, Llc Multi-point fit for patient specific guide
US9826981B2 (en) 2013-03-13 2017-11-28 Biomet Manufacturing, Llc Tangential fit of patient-specific guides
US9498233B2 (en) 2013-03-13 2016-11-22 Biomet Manufacturing, Llc. Universal acetabular guide and associated hardware
US9517145B2 (en) 2013-03-15 2016-12-13 Biomet Manufacturing, Llc Guide alignment system and method
US10912571B2 (en) * 2013-03-15 2021-02-09 Howmedica Osteonics Corporation Generation of a mating surface model for patient specific cutting guide based on anatomical model segmentation
USD702349S1 (en) 2013-05-14 2014-04-08 Laboratories Bodycad Inc. Tibial prosthesis
USD752222S1 (en) 2013-05-14 2016-03-22 Laboratoires Bodycad Inc. Femoral prosthesis
CN103494613B (en) * 2013-09-06 2015-10-14 沈阳东软医疗系统有限公司 A kind of plain film scan method and device
US20150112349A1 (en) 2013-10-21 2015-04-23 Biomet Manufacturing, Llc Ligament Guide Registration
US10362961B2 (en) * 2014-01-10 2019-07-30 Northshore University Healthsystem System and method for neutral contrast magnetic resonance imaging of calcifications
CN106132341B (en) 2014-01-27 2019-04-12 物化股份有限公司 The prediction of shape
WO2015142877A1 (en) 2014-03-17 2015-09-24 Core Sports Technology Group Method and system for delivering biomechanical feedback to human and object motion
US10282488B2 (en) 2014-04-25 2019-05-07 Biomet Manufacturing, Llc HTO guide with optional guided ACL/PCL tunnels
US10013743B2 (en) * 2014-05-01 2018-07-03 The Arizona Board Of Regents On Behalf Of The University Of Arizona Systems, methods and devices for performing motion artifact correction
US9408616B2 (en) 2014-05-12 2016-08-09 Biomet Manufacturing, Llc Humeral cut guide
US9839436B2 (en) 2014-06-03 2017-12-12 Biomet Manufacturing, Llc Patient-specific glenoid depth control
US9561040B2 (en) 2014-06-03 2017-02-07 Biomet Manufacturing, Llc Patient-specific glenoid depth control
KR101579740B1 (en) 2014-09-01 2015-12-23 삼성메디슨 주식회사 Untrasound dianognosis apparatus, method and computer-readable storage medium
US9743879B2 (en) * 2014-09-26 2017-08-29 Rush University Medical Center Kinematic analysis based on MRI bone marrow signals
US9833245B2 (en) 2014-09-29 2017-12-05 Biomet Sports Medicine, Llc Tibial tubercule osteotomy
US9826994B2 (en) 2014-09-29 2017-11-28 Biomet Manufacturing, Llc Adjustable glenoid pin insertion guide
JP2016096889A (en) * 2014-11-19 2016-05-30 株式会社東芝 Image analysis apparatus, image analysis method and program
US20160180520A1 (en) * 2014-12-17 2016-06-23 Carestream Health, Inc. Quantitative method for 3-d joint characterization
US11432734B2 (en) * 2014-12-19 2022-09-06 New York Society For The Relief Of The Ruptured And Crippled, Maintaining The Hospital For Special Surgery System and apparatus for securing knee joint with a load for magnetic resonance imaging
US20160174878A1 (en) * 2014-12-22 2016-06-23 Avon Products, Inc. System and Method for Measuring Skin Firmness
US9820868B2 (en) 2015-03-30 2017-11-21 Biomet Manufacturing, Llc Method and apparatus for a pin apparatus
US20160354161A1 (en) 2015-06-05 2016-12-08 Ortho Kinematics, Inc. Methods for data processing for intra-operative navigation systems
DE102015211714B4 (en) 2015-06-24 2020-10-22 Siemens Healthcare Gmbh Medical image processing method and image processing system
US10226262B2 (en) 2015-06-25 2019-03-12 Biomet Manufacturing, Llc Patient-specific humeral guide designs
US10568647B2 (en) 2015-06-25 2020-02-25 Biomet Manufacturing, Llc Patient-specific humeral guide designs
EP3181050B1 (en) 2015-12-18 2020-02-12 Episurf IP Management AB System and method for creating a decision support material indicating damage to an anatomical joint
US11526988B2 (en) 2015-12-18 2022-12-13 Episurf Ip-Management Ab System and method for creating a decision support material indicating damage to an anatomical joint
KR101828174B1 (en) * 2016-10-17 2018-02-09 연세대학교 산학협력단 Magenetic Resonance Imaging for arthrography Apparatus, Method and recording medium using the same
USD808524S1 (en) 2016-11-29 2018-01-23 Laboratoires Bodycad Inc. Femoral implant
US10722310B2 (en) 2017-03-13 2020-07-28 Zimmer Biomet CMF and Thoracic, LLC Virtual surgery planning system and method
US11250561B2 (en) 2017-06-16 2022-02-15 Episurf Ip-Management Ab Determination and visualization of damage to an anatomical joint
RU2681923C1 (en) * 2017-12-04 2019-03-13 Федеральное государственное бюджетное образовательное учреждение высшего образования Ставропольский государственный медицинский университет Министерства здравоохранения Российской Федерации (ФГБОУ ВО СтГМУ Минздрава России) Method for diagnosis of knee joint arthrosis
RU2682119C1 (en) * 2017-12-29 2019-03-14 Федеральное государственное бюджетное образовательное учреждение высшего образования "Санкт-Петербургский государственный педиатрический медицинский университет" Министерства здравоохранения Российской Федерации (ФГБОУ ВО СПбГПМУ Минздрава России) Method of diagnostics of inflammatory changes in the joints in juvenile idiopathic arthritis
US10709374B2 (en) * 2018-03-12 2020-07-14 Physimax Technologies Ltd. Systems and methods for assessment of a musculoskeletal profile of a target individual
WO2019175870A1 (en) * 2018-03-12 2019-09-19 Persimio Ltd. Automated bone segmentation in images
US11051829B2 (en) 2018-06-26 2021-07-06 DePuy Synthes Products, Inc. Customized patient-specific orthopaedic surgical instrument
CN109124639A (en) * 2018-07-20 2019-01-04 南方医科大学 A kind of upper limb healing brace limbs model data acquisition methods
US11645749B2 (en) 2018-12-14 2023-05-09 Episurf Ip-Management Ab Determination and visualization of damage to an anatomical joint
CN109662716B (en) * 2018-12-19 2021-10-22 上海联影医疗科技股份有限公司 Cartilage thickness measuring method, cartilage thickness measuring device, computer equipment and storage medium
CN110037659A (en) * 2019-04-27 2019-07-23 瞿志雄 Function of joint loses degree computing system in a kind of Forensic Identification
WO2020227463A1 (en) * 2019-05-07 2020-11-12 Tufts Medical Center, Inc. Objective assessment of joint damage
AU2020283377B2 (en) 2019-05-29 2022-08-04 Wright Medical Technology, Inc. Preparing a tibia for receiving tibial implant component of a replacement ankle
CN110677245B (en) * 2019-09-26 2020-09-25 昆明市测绘研究院 Coordinate transformation parameter encryption and decryption method based on dongle
WO2022056271A1 (en) * 2020-09-11 2022-03-17 University Of Iowa Research Foundation Methods and apapratus for machine learning to analyze musculo-skeletal rehabilitation from images
CN116507276A (en) 2020-09-11 2023-07-28 爱荷华大学研究基金会 Method and apparatus for machine learning to analyze musculoskeletal rehabilitation from images
CN113331828B (en) * 2021-06-05 2022-06-24 吉林大学 Marking system for human body leg-foot multi-joint fine motion analysis and dividing method of leg and foot sections

Family Cites Families (527)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US568886A (en) * 1896-10-06 Automatic fire-extinguisher
US3314420A (en) 1961-10-23 1967-04-18 Haeger Potteries Inc Prosthetic parts and methods of making the same
US3605123A (en) 1969-04-29 1971-09-20 Melpar Inc Bone implant
GB1324990A (en) 1969-08-25 1973-07-25 Nat Res Dev Prosthetic shoulder joint devices
CA962806A (en) 1970-06-04 1975-02-18 Ontario Research Foundation Surgical prosthetic device
US3938198A (en) * 1970-08-04 1976-02-17 Cutter Laboratories, Inc. Hip joint prosthesis
GB1395896A (en) 1971-06-01 1975-05-29 Nat Res Dev Endoprosthetic knee joint devices
US3798679A (en) * 1971-07-09 1974-03-26 Ewald Frederick Joint prostheses
US3808606A (en) 1972-02-22 1974-05-07 R Tronzo Bone implant with porous exterior surface
DE2306552B2 (en) 1973-02-10 1975-07-03 Friedrichsfeld Gmbh Steinzeug- Und Kunststoffwerke, 6800 Mannheim Joint endoprosthesis
US3852830A (en) 1973-02-15 1974-12-10 Richards Mfg Co Knee prosthesis
US3843975A (en) 1973-04-09 1974-10-29 R Tronzo Prosthesis for femoral shaft
DE2340546A1 (en) 1973-08-10 1975-02-27 Pfaudler Werke Ag METALLIC IMPLANT AND PROCEDURE FOR ITS MANUFACTURING
US4085466A (en) 1974-11-18 1978-04-25 National Research Development Corporation Prosthetic joint device
US4219893A (en) 1977-09-01 1980-09-02 United States Surgical Corporation Prosthetic knee joint
US3991425A (en) 1975-11-20 1976-11-16 Minnesota Mining And Manufacturing Company Prosthetic bone joint devices
US4055862A (en) 1976-01-23 1977-11-01 Zimmer Usa, Inc. Human body implant of graphitic carbon fiber reinforced ultra-high molecular weight polyethylene
US4052753A (en) 1976-08-02 1977-10-11 Dedo Richard G Knee spacer and method of reforming sliding body surfaces
US4098626A (en) 1976-11-15 1978-07-04 Thiokol Corporation Hydroxy terminated polybutadiene based polyurethane bound propellant grains
DE2703059C3 (en) 1977-01-26 1981-09-03 Sanitätshaus Schütt & Grundei, Werkstätten für Orthopädie-Technik, 2400 Lübeck Knee joint endoprosthesis
US4203444A (en) 1977-11-07 1980-05-20 Dyonics, Inc. Surgical instrument suitable for closed surgery such as of the knee
US4164793A (en) 1978-04-26 1979-08-21 Swanson Alfred B Lunate implant
US4213816A (en) 1978-06-12 1980-07-22 Glasrock Products, Inc. Method for bonding porous coating to rigid structural member
US4280231A (en) 1979-06-14 1981-07-28 Swanson Alfred B Elbow prosthesis
US4340978A (en) 1979-07-02 1982-07-27 Biomedical Engineering Corp. New Jersey meniscal bearing knee replacement
US4309778A (en) 1979-07-02 1982-01-12 Biomedical Engineering Corp. New Jersey meniscal bearing knee replacement
JPS6026892Y2 (en) 1979-11-30 1985-08-14 ナショナル住宅産業株式会社 Screw tightener adjustment device
DE3010421A1 (en) 1980-03-19 1981-09-24 Waldemar Link (Gmbh & Co), 2000 Hamburg INSTRUMENT FOR HOLDING AND INSERTING THE TIBIA PLATE FOR A KNEE-JOINT SLIDING PROSTHESIS
US4344193A (en) * 1980-11-28 1982-08-17 Kenny Charles H Meniscus prosthesis
US4575805A (en) * 1980-12-24 1986-03-11 Moermann Werner H Method and apparatus for the fabrication of custom-shaped implants
US4368040A (en) * 1981-06-01 1983-01-11 Ipco Corporation Dental impression tray for forming a dental prosthesis in situ
US4502161A (en) * 1981-09-21 1985-03-05 Wall W H Prosthetic meniscus for the repair of joints
US4436684A (en) * 1982-06-03 1984-03-13 Contour Med Partners, Ltd. Method of forming implantable prostheses for reconstructive surgery
US4459985A (en) 1983-03-04 1984-07-17 Howmedica Inc. Tibial prosthesis extractor and method for extracting a tibial implant
US4501266A (en) * 1983-03-04 1985-02-26 Biomet, Inc. Knee distraction device
US4631676A (en) * 1983-05-25 1986-12-23 Hospital For Joint Diseases Or Computerized video gait and motion analysis system and method
US4601290A (en) 1983-10-11 1986-07-22 Cabot Medical Corporation Surgical instrument for cutting body tissue from a body area having a restricted space
DE8406730U1 (en) 1984-03-05 1984-04-26 Waldemar Link (Gmbh & Co), 2000 Hamburg Surgical chisel
US4609551A (en) 1984-03-20 1986-09-02 Arnold Caplan Process of and material for stimulating growth of cartilage and bony tissue at anatomical sites
US4673409A (en) 1984-04-25 1987-06-16 Minnesota Mining And Manufacturing Company Implant with attachment surface
JPS61247448A (en) 1985-04-25 1986-11-04 日石三菱株式会社 Production of artificial joint
US4594380A (en) 1985-05-01 1986-06-10 At&T Bell Laboratories Elastomeric controlled release formulation and article comprising same
DE3516743A1 (en) 1985-05-09 1986-11-13 orthoplant Endoprothetik GmbH, 2800 Bremen Endoprosthesis for a femoral head
US4627853A (en) 1985-05-29 1986-12-09 American Hospital Supply Corporation Method of producing prostheses for replacement of articular cartilage and prostheses so produced
US4699156A (en) 1985-06-06 1987-10-13 Diagnospine Research Inc. Non invasive method and equipment for the detection of torsional injuries in the lumar spine of a patient
US4655227A (en) 1985-06-06 1987-04-07 Diagnospine Research Inc. Equipment for the detection of mechanical injuries in the lumbar spine of a patient, using a mathematical model
DE3535112A1 (en) 1985-10-02 1987-04-16 Witzel Ulrich TIBI PLATE PART OF A KNEE-KNEE ENDOPROTHESIS
FR2589720A1 (en) 1985-11-14 1987-05-15 Aubaniac Jean KNEE JOINT PROSTHETIC ASSEMBLY
US4721104A (en) * 1985-12-02 1988-01-26 Dow Corning Wright Corporation Femoral surface shaping apparatus for posterior-stabilized knee implants
US5266480A (en) 1986-04-18 1993-11-30 Advanced Tissue Sciences, Inc. Three-dimensional skin culture system
US4714474A (en) 1986-05-12 1987-12-22 Dow Corning Wright Corporation Tibial knee joint prosthesis with removable articulating surface insert
US4822365A (en) 1986-05-30 1989-04-18 Walker Peter S Method of design of human joint prosthesis
US4936862A (en) 1986-05-30 1990-06-26 Walker Peter S Method of designing and manufacturing a human joint prosthesis
US4769040A (en) 1986-11-18 1988-09-06 Queen's University At Kingston Tibial prosthesis
US5041138A (en) 1986-11-20 1991-08-20 Massachusetts Institute Of Technology Neomorphogenesis of cartilage in vivo from cell culture
CN86209787U (en) 1986-11-29 1987-11-18 于也宽 Sleeve-shaped artificial elbow joint
US4714472A (en) 1987-01-20 1987-12-22 Osteonics Corp. Knee prosthesis with accommodation for angular misalignment
US5002547A (en) * 1987-02-07 1991-03-26 Pfizer Hospital Products Group, Inc. Apparatus for knee prosthesis
US5250050A (en) 1987-02-07 1993-10-05 Pfizer Hospital Products Group, Inc. Apparatus for knee prosthesis
US4841975A (en) 1987-04-15 1989-06-27 Cemax, Inc. Preoperative planning of bone cuts and joint replacement using radiant energy scan imaging
US4846835A (en) 1987-06-15 1989-07-11 Grande Daniel A Technique for healing lesions in cartilage
US5306311A (en) 1987-07-20 1994-04-26 Regen Corporation Prosthetic articular cartilage
US5681353A (en) 1987-07-20 1997-10-28 Regen Biologics, Inc. Meniscal augmentation device
US4880429A (en) 1987-07-20 1989-11-14 Stone Kevin R Prosthetic meniscus
US5007934A (en) 1987-07-20 1991-04-16 Regen Corporation Prosthetic meniscus
US4813436A (en) 1987-07-30 1989-03-21 Human Performance Technologies, Inc. Motion analysis system employing various operating modes
US5303148A (en) 1987-11-27 1994-04-12 Picker International, Inc. Voice actuated volume image controller and display controller
US6228116B1 (en) 1987-12-22 2001-05-08 Walter J. Ledergerber Tissue expander
US4888021A (en) 1988-02-02 1989-12-19 Joint Medical Products Corporation Knee and patellar prosthesis
GB8802671D0 (en) 1988-02-05 1988-03-02 Goodfellow J W Orthopaedic joint components tools & methods
US4823807A (en) * 1988-02-11 1989-04-25 Board Of Regents, Univ. Of Texas System Device for non-invasive diagnosis and monitoring of articular and periarticular pathology
JP2784766B2 (en) 1988-03-30 1998-08-06 京セラ株式会社 Artificial knee joint
FR2629339B1 (en) 1988-04-01 1997-09-12 Broc Christian LAYING MATERIAL FOR PARTICULARLY A TIBIAL AND / OR FEMORAL ELEMENT OF A BI-COMPARTMENTAL KNEE JOINT PROSTHESIS
US4979949A (en) 1988-04-26 1990-12-25 The Board Of Regents Of The University Of Washington Robot-aided system for surgery
GB8817908D0 (en) 1988-07-27 1988-09-01 Howmedica Tibial component for replacement knee prosthesis
US4944757A (en) 1988-11-07 1990-07-31 Martinez David M Modulator knee prosthesis system
US5162430A (en) 1988-11-21 1992-11-10 Collagen Corporation Collagen-polymer conjugates
US5510418A (en) 1988-11-21 1996-04-23 Collagen Corporation Glycosaminoglycan-synthetic polymer conjugates
US5099859A (en) * 1988-12-06 1992-03-31 Bell Gene D Method and apparatus for comparative analysis of videofluoroscopic joint motion
US4872452A (en) 1989-01-09 1989-10-10 Minnesota Mining And Manufacturing Company Bone rasp
US5108452A (en) 1989-02-08 1992-04-28 Smith & Nephew Richards Inc. Modular hip prosthesis
US5234433A (en) 1989-09-26 1993-08-10 Kirschner Medical Corporation Method and instrumentation for unicompartmental total knee arthroplasty
US5059216A (en) 1989-09-29 1991-10-22 Winters Thomas F Knee joint replacement apparatus
DE3933459A1 (en) 1989-10-06 1991-04-18 Karsten Dipl Ing Reumann Biomedical implant production equipment - uses computer tomographic image to generate implant profile for component mfr.
EP0425714A1 (en) * 1989-10-28 1991-05-08 Metalpraecis Berchem + Schaberg Gesellschaft Für Metallformgebung Mbh Process for manufacturing an implantable joint prosthesis
EP0528080A1 (en) 1989-12-13 1993-02-24 Stryker Corporation Articular cartilage repair piece
US5067964A (en) 1989-12-13 1991-11-26 Stryker Corporation Articular surface repair
US5246013A (en) * 1989-12-22 1993-09-21 Massachusetts Institute Of Technology Probe, system and method for detecting cartilage degeneration
US5129908A (en) 1990-01-23 1992-07-14 Petersen Thomas D Method and instruments for resection of the patella
US5171322A (en) 1990-02-13 1992-12-15 Kenny Charles H Stabilized meniscus prosthesis
US5246530A (en) 1990-04-20 1993-09-21 Dynamet Incorporated Method of producing porous metal surface
US5523843A (en) 1990-07-09 1996-06-04 Canon Kabushiki Kaisha Position detecting system
US5021061A (en) 1990-09-26 1991-06-04 Queen's University At Kingston Prosthetic patello-femoral joint
US5274565A (en) 1990-10-03 1993-12-28 Board Of Regents, The University Of Texas System Process for making custom joint replacements
US5154178A (en) * 1990-10-09 1992-10-13 Sri International Method and apparatus for obtaining in-vivo nmr data from a moving subject
US5226914A (en) 1990-11-16 1993-07-13 Caplan Arnold I Method for treating connective tissue disorders
US5197985A (en) * 1990-11-16 1993-03-30 Caplan Arnold I Method for enhancing the implantation and differentiation of marrow-derived mesenchymal cells
US5123927A (en) 1990-12-05 1992-06-23 University Of British Columbia Method and apparatus for antibiotic knee prothesis
US5206023A (en) * 1991-01-31 1993-04-27 Robert F. Shaw Method and compositions for the treatment and repair of defects or lesions in cartilage
US5853746A (en) 1991-01-31 1998-12-29 Robert Francis Shaw Methods and compositions for the treatment and repair of defects or lesions in cartilage or bone using functional barrier
GB9102348D0 (en) 1991-02-04 1991-03-20 Inst Of Orthopaedics The Prosthesis for knee replacement
JP3007903B2 (en) 1991-03-29 2000-02-14 京セラ株式会社 Artificial disc
CA2041532C (en) * 1991-04-30 2002-01-01 Hamdy Khalil Urethane sealant having improved sag properties
US5133759A (en) 1991-05-24 1992-07-28 Turner Richard H Asymmetrical femoral condye total knee arthroplasty prosthesis
US5417210A (en) 1992-05-27 1995-05-23 International Business Machines Corporation System and method for augmentation of endoscopic surgery
US5282868A (en) 1991-06-17 1994-02-01 Andre Bahler Prosthetic arrangement for a complex joint, especially knee joint
US5245282A (en) 1991-06-28 1993-09-14 University Of Virginia Alumni Patents Foundation Three-dimensional magnetic resonance imaging
GB9114603D0 (en) * 1991-07-05 1991-08-21 Johnson David P Improvements relating to patella prostheses
US5306307A (en) 1991-07-22 1994-04-26 Calcitek, Inc. Spinal disk implant
US5147365A (en) 1991-08-19 1992-09-15 Intermedics Orthopedics, Inc. Patellar osteotomy guide
US5270300A (en) 1991-09-06 1993-12-14 Robert Francis Shaw Methods and compositions for the treatment and repair of defects or lesions in cartilage or bone
US5291401A (en) * 1991-11-15 1994-03-01 Telescan, Limited Teleradiology system
GB2261672A (en) 1991-11-18 1993-05-26 Michael Braden The use of biomaterials for tissue repair
US5344459A (en) 1991-12-03 1994-09-06 Swartz Stephen J Arthroscopically implantable prosthesis
US6044289A (en) * 1991-12-04 2000-03-28 Bonutti; Peter M. Apparatus and method for controlling bending of a joint of a patient during imaging
US5329924A (en) 1991-12-04 1994-07-19 Apogee Medical Products, Inc. Sequential imaging apparatus
DE4202717C1 (en) 1991-12-11 1993-06-17 Dietmar Prof. Dr. 3350 Kreiensen De Kubein-Meesenburg
US5258032A (en) 1992-04-03 1993-11-02 Bertin Kim C Knee prosthesis provisional apparatus and resection guide and method of use in knee replacement surgery
US5326365A (en) 1992-04-10 1994-07-05 Alvine Franklin G Ankle implant
US5503162A (en) * 1992-04-21 1996-04-02 Board Of Regents, University Of Texas System Arthroscopic cartilage evaluator and method for using the same
CA2118507A1 (en) * 1992-04-21 1993-10-28 Kyriacos Athanasiou Arthroscopic indenter and method for using the same
DE4213597A1 (en) 1992-04-24 1993-10-28 Klaus Draenert Femoral prosthesis component to be anchored with bone cement and process for its production
US5423828A (en) 1992-05-14 1995-06-13 Bentwood Place, Inc. Method and apparatus for simplifying prosthetic joint replacements
US5365996A (en) 1992-06-10 1994-11-22 Amei Technologies Inc. Method and apparatus for making customized fixation devices
DE4219939C2 (en) 1992-06-18 1995-10-19 Klaus Dipl Ing Radermacher Device for aligning, positioning and guiding machining tools, machining or measuring devices for machining a bony structure and method for producing this device
US5824102A (en) 1992-06-19 1998-10-20 Buscayret; Christian Total knee prosthesis
US5478739A (en) 1992-10-23 1995-12-26 Advanced Tissue Sciences, Inc. Three-dimensional stromal cell and tissue culture system
FR2697743B1 (en) * 1992-11-09 1995-01-27 Fabrication Mat Orthopedique S Spinal osteosynthesis device applicable in particular to degenerative vertebrae.
WO1994010914A1 (en) * 1992-11-16 1994-05-26 Wright Medical Technology, Inc. System and method for profiling a patella
US5320102A (en) 1992-11-18 1994-06-14 Ciba-Geigy Corporation Method for diagnosing proteoglycan deficiency in cartilage based on magnetic resonance image (MRI)
EP0598964B1 (en) * 1992-11-20 1999-07-07 Sulzer Orthopädie AG Bone cement dispenser body for implant fixation
US5445152A (en) 1992-11-23 1995-08-29 Resonex Holding Company Kinematic device for producing precise incremental flexing of the knee
FR2698537B1 (en) 1992-12-01 1995-01-06 Medinov Sa Three-compartment knee prosthesis.
AU691162B2 (en) 1992-12-14 1998-05-14 Biomedical Engineering Trust I Fixed bearing joint endoprosthesis
FR2699271B1 (en) * 1992-12-15 1995-03-17 Univ Joseph Fourier Method for determining the femoral anchor point of a cruciate knee ligament.
US5360446A (en) 1992-12-18 1994-11-01 Zimmer, Inc. Interactive prosthesis design system for implantable prosthesis
US5728162A (en) * 1993-01-28 1998-03-17 Board Of Regents Of University Of Colorado Asymmetric condylar and trochlear femoral knee component
US5387216A (en) * 1993-02-18 1995-02-07 Thornhill; Thomas S. Intramedullary based instrument systems for total knee revision
US6001895A (en) 1993-03-22 1999-12-14 Johnson & Johnson Medical, Inc. Composite surgical material
US5724970A (en) 1993-04-06 1998-03-10 Fonar Corporation Multipositional MRI for kinematic studies of movable joints
FR2705785B1 (en) 1993-05-28 1995-08-25 Schlumberger Ind Sa Method for determining the attenuation function of an object with respect to the transmission of a reference thickness of a reference material and device for implementing the method.
US5480430A (en) * 1993-06-04 1996-01-02 Mcghan Medical Corporation Shape-retaining shell for a fluid filled prosthesis
US5413116A (en) 1993-06-24 1995-05-09 Bioresearch Method and apparatus for diagnosing joints
US5474559A (en) 1993-07-06 1995-12-12 Zimmer, Inc. Femoral milling instrumentation for use in total knee arthroplasty with optional cutting guide attachment
US5961454A (en) * 1993-08-13 1999-10-05 The Brigham And Women's Hospital Fusion of anatomical data sets into stereotactic coordinates
AU684546B2 (en) 1993-09-10 1997-12-18 University Of Queensland, The Stereolithographic anatomical modelling process
US5522900A (en) 1993-12-17 1996-06-04 Avanta Orthopaedics Prosthetic joint and method of manufacture
JPH07194569A (en) * 1994-01-11 1995-08-01 Toshiba Medical Eng Co Ltd Knee joint fixing tool for mri
US5759205A (en) 1994-01-21 1998-06-02 Brown University Research Foundation Negatively charged polymeric electret implant
NZ279442A (en) 1994-01-26 1998-02-26 Mark A Reiley Bone treatment device; inflatable balloon for insertion into a bone; balloon details
US5885298A (en) * 1994-02-23 1999-03-23 Biomet, Inc. Patellar clamp and reamer with adjustable stop
JP2980805B2 (en) 1994-03-01 1999-11-22 株式会社三協精機製作所 Artificial aggregate and its processing method
US5427099A (en) * 1994-03-17 1995-06-27 Adams; Timothy L. Marker for magnetic resonance imaging
GB9407153D0 (en) 1994-04-11 1994-06-01 Corin Medical Ltd Unicompartmental knee prosthesis
BE1008372A3 (en) 1994-04-19 1996-04-02 Materialise Nv METHOD FOR MANUFACTURING A perfected MEDICAL MODEL BASED ON DIGITAL IMAGE INFORMATION OF A BODY.
FR2719466B1 (en) 1994-05-04 1997-06-06 Ysebaert Sa Knee prosthesis with movable meniscus.
US5723331A (en) 1994-05-05 1998-03-03 Genzyme Corporation Methods and compositions for the repair of articular cartilage defects in mammals
US5888220A (en) 1994-05-06 1999-03-30 Advanced Bio Surfaces, Inc. Articulating joint repair
US5616146A (en) 1994-05-16 1997-04-01 Murray; William M. Method and apparatus for machining bone to fit an orthopedic surgical implant
GB9413607D0 (en) 1994-07-06 1994-08-24 Goodfellow John W Endoprosthetic knee joint device
FR2722392A1 (en) 1994-07-12 1996-01-19 Biomicron APPARATUS FOR RESECTING KNEE CONDYLES FOR PLACING A PROSTHESIS AND METHOD FOR PLACING SUCH AN APPARATUS
US5769899A (en) 1994-08-12 1998-06-23 Matrix Biotechnologies, Inc. Cartilage repair unit
US5632745A (en) 1995-02-07 1997-05-27 R&D Biologicals, Inc. Surgical implantation of cartilage repair unit
US5597379A (en) * 1994-09-02 1997-01-28 Hudson Surgical Design, Inc. Method and apparatus for femoral resection alignment
US5755803A (en) 1994-09-02 1998-05-26 Hudson Surgical Design Prosthetic implant
US6695848B2 (en) 1994-09-02 2004-02-24 Hudson Surgical Design, Inc. Methods for femoral and tibial resection
US5810827A (en) 1994-09-02 1998-09-22 Hudson Surgical Design, Inc. Method and apparatus for bony material removal
DE4434539C2 (en) 1994-09-27 1998-06-04 Luis Dr Med Schuster Process for the production of an endoprosthesis as a joint replacement for knee joints
CA2160198C (en) 1994-10-27 2003-12-30 Michael J. Pappas Prosthesis fixturing device
JPH10507953A (en) 1994-10-28 1998-08-04 アイシーズ、テクノロジーズ、インコーポレーテッド Corneal analyzer for compound camera
US5578037A (en) 1994-11-14 1996-11-26 Johnson & Johnson Professional, Inc. Surgical guide for femoral resection
US5630820A (en) 1994-12-05 1997-05-20 Sulzer Orthopedics Inc. Surgical bicompartmental tensiometer for revision knee surgery
JP3490520B2 (en) 1994-12-12 2004-01-26 株式会社ニデック Ophthalmic equipment
JP3419931B2 (en) 1994-12-26 2003-06-23 京セラ株式会社 Artificial knee joint
US5540696A (en) 1995-01-06 1996-07-30 Zimmer, Inc. Instrumentation for use in orthopaedic surgery
US6102955A (en) 1995-01-19 2000-08-15 Mendes; David Surgical method, surgical tool and artificial implants for repairing knee joints
US5560096B1 (en) 1995-01-23 1998-03-10 Smith & Nephew Richards Inc Method of manufacturing femoral knee implant
US5749874A (en) 1995-02-07 1998-05-12 Matrix Biotechnologies, Inc. Cartilage repair unit and method of assembling same
US5575793A (en) 1995-02-15 1996-11-19 Smith & Nephew Richards Inc. Patella clamp apparatus
US5609642A (en) 1995-02-15 1997-03-11 Smith & Nephew Richards Inc. Tibial trial prosthesis and bone preparation system
US5593450A (en) 1995-02-27 1997-01-14 Johnson & Johnson Professional, Inc. Oval domed shaped patella prosthesis
US5683468A (en) 1995-03-13 1997-11-04 Pappas; Michael J. Mobile bearing total joint replacement
US5906934A (en) 1995-03-14 1999-05-25 Morphogen Pharmaceuticals, Inc. Mesenchymal stem cells for cartilage repair
US5571191A (en) 1995-03-16 1996-11-05 Fitz; William R. Artificial facet joint
US5900245A (en) 1996-03-22 1999-05-04 Focal, Inc. Compliant tissue sealants
US5832422A (en) 1995-04-11 1998-11-03 Wiedenhoefer; Curt Measuring device
US5542947A (en) 1995-05-12 1996-08-06 Huwmedica Inc. Slotted patella resection guide and stylus
US6132463A (en) 1995-05-19 2000-10-17 Etex Corporation Cell seeding of ceramic compositions
US6046379A (en) 1995-06-07 2000-04-04 Stone; Kevin R. Meniscal xenografts
US5865849A (en) 1995-06-07 1999-02-02 Crosscart, Inc. Meniscal heterografts
US6447783B1 (en) 1995-06-12 2002-09-10 Yeda Research And Development Co., Ltd. Compositions comprising FGF9 and use thereof for stimulating cartilage and bone repair
US5649929A (en) 1995-07-10 1997-07-22 Callaway; George Hadley Knee joint flexion-gap distraction device
US5968051A (en) 1995-07-27 1999-10-19 Johnson & Johnson Professional, Inc. Patella clamping device
US5671741A (en) 1995-08-04 1997-09-30 The Regents Of The University Of California Magnetic resonance imaging technique for tissue characterization
GB2304051B (en) 1995-08-09 1999-01-27 Corin Medical Ltd A knee prosthesis
US5601563A (en) * 1995-08-25 1997-02-11 Zimmer, Inc. Orthopaedic milling template with attachable cutting guide
US20020143402A1 (en) 1995-09-04 2002-10-03 Limber Ltd. Hip joint prostheses
US5871546A (en) * 1995-09-29 1999-02-16 Johnson & Johnson Professional, Inc. Femoral component condyle design for knee prosthesis
FR2740326B1 (en) 1995-10-31 1998-02-20 Osteal Medical Lab FEMORO-PATELLAR PROSTHESIS OF THE KNEE
US5716361A (en) * 1995-11-02 1998-02-10 Masini; Michael A. Bone cutting guides for use in the implantation of prosthetic joint components
CA2193451C (en) 1995-12-21 2005-11-01 Diana F. Mccue Instrument system for knee prosthesis implantation with universal handle or slap hammer
US5682886A (en) * 1995-12-26 1997-11-04 Musculographics Inc Computer-assisted surgical system
US6200606B1 (en) 1996-01-16 2001-03-13 Depuy Orthopaedics, Inc. Isolation of precursor cells from hematopoietic and nonhematopoietic tissues and their use in vivo bone and cartilage regeneration
CA2168283A1 (en) 1996-01-29 1997-07-30 John Michael Lee Preparation of biological material for implants
JP2965137B2 (en) 1996-02-02 1999-10-18 瑞穂医科工業株式会社 Artificial knee joint
US5702463A (en) 1996-02-20 1997-12-30 Smith & Nephew Inc. Tibial prosthesis with polymeric liner and liner insertion/removal instrument
US5681354A (en) 1996-02-20 1997-10-28 Board Of Regents, University Of Colorado Asymmetrical femoral component for knee prosthesis
US5842477A (en) 1996-02-21 1998-12-01 Advanced Tissue Sciences, Inc. Method for repairing cartilage
US6352558B1 (en) * 1996-02-22 2002-03-05 Ed. Geistlich Soehne Ag Fuer Chemische Industrie Method for promoting regeneration of surface cartilage in a damage joint
HU219444B (en) * 1996-02-26 2001-04-28 Gábor Krakovits Sliding surface for knee-joint prothesis
US5861175A (en) * 1996-03-15 1999-01-19 Alliance Pharmaceutical Corp. Use of fluorocarbons for diagnosis and treatment of articular disorders
US5683466A (en) 1996-03-26 1997-11-04 Vitale; Glenn C. Joint surface replacement system
CA2201057C (en) 1996-03-29 2002-01-01 Kenji Morimoto A method of processing a sectional image of a sample bone including a cortical bone portion and a cancellous bone portion
US6299905B1 (en) 1996-04-16 2001-10-09 Depuy Orthopaedics, Inc. Bioerodable polymeric adhesives for tissue repair
WO1997045532A1 (en) 1996-05-28 1997-12-04 Brown University Research Foundation Hyaluronan based biodegradable scaffolds for tissue repair
GB9611060D0 (en) 1996-05-28 1996-07-31 Howmedica Tibial element for a replacment knee prosthesis
GB9611074D0 (en) 1996-05-28 1996-07-31 Howmedica Surgical apparatus
JP3754708B2 (en) 1996-06-04 2006-03-15 ツィマー ゲーエム ベーハー Method for producing cartilage tissue and implant for repairing endochondral and osteochondral defects and arrangement for carrying out the method
US6126690A (en) 1996-07-03 2000-10-03 The Trustees Of Columbia University In The City Of New York Anatomically correct prosthesis and method and apparatus for manufacturing prosthesis
US5964808A (en) 1996-07-11 1999-10-12 Wright Medical Technology, Inc. Knee prosthesis
US5871540A (en) * 1996-07-30 1999-02-16 Osteonics Corp. Patellar implant component and method
US6569172B2 (en) 1996-08-30 2003-05-27 Verigen Transplantation Service International (Vtsi) Method, instruments, and kit for autologous transplantation
US5989269A (en) 1996-08-30 1999-11-23 Vts Holdings L.L.C. Method, instruments and kit for autologous transplantation
US6175655B1 (en) 1996-09-19 2001-01-16 Integrated Medical Systems, Inc. Medical imaging system for displaying, manipulating and analyzing three-dimensional images
SE9603540D0 (en) 1996-09-27 1996-09-27 Ingvar Eriksson Orthopedic device
US5824085A (en) * 1996-09-30 1998-10-20 Integrated Surgical Systems, Inc. System and method for cavity generation for surgical planning and initial placement of a bone prosthesis
US5895428A (en) 1996-11-01 1999-04-20 Berry; Don Load bearing spinal joint implant
DE19646891A1 (en) 1996-11-13 1998-05-14 Kubein Meesenburg Dietmar Artificial joint, especially an endoprosthesis to replace natural joints
DE19647155C2 (en) 1996-11-14 1998-11-19 Plus Endoprothetik Ag Implant
JP2002505592A (en) 1996-11-15 2002-02-19 アドバンスト バイオ サーフェイシズ，インコーポレイティド Biomaterial systems used to repair tissue in situ
US5928945A (en) 1996-11-20 1999-07-27 Advanced Tissue Sciences, Inc. Application of shear flow stress to chondrocytes or chondrocyte stem cells to produce cartilage
US6203576B1 (en) * 1996-12-09 2001-03-20 Groupe Controle Dedienne Gcd Societe De Droit Francais Complete knee joint prosthesis
US20070233269A1 (en) 2001-05-25 2007-10-04 Conformis, Inc. Interpositional Joint Implant
US7534263B2 (en) 2001-05-25 2009-05-19 Conformis, Inc. Surgical tools facilitating increased accuracy, speed and simplicity in performing joint arthroplasty
US7618451B2 (en) 2001-05-25 2009-11-17 Conformis, Inc. Patient selectable joint arthroplasty devices and surgical tools facilitating increased accuracy, speed and simplicity in performing total and partial joint arthroplasty
US8083745B2 (en) 2001-05-25 2011-12-27 Conformis, Inc. Surgical tools for arthroplasty
US8617242B2 (en) 2001-05-25 2013-12-31 Conformis, Inc. Implant device and method for manufacture
US8882847B2 (en) 2001-05-25 2014-11-11 Conformis, Inc. Patient selectable knee joint arthroplasty devices
US8545569B2 (en) 2001-05-25 2013-10-01 Conformis, Inc. Patient selectable knee arthroplasty devices
US7634119B2 (en) 2002-12-04 2009-12-15 Conformis, Inc. Fusion of multiple imaging planes for isotropic imaging in MRI and quantitative image analysis using isotropic or near-isotropic imaging
US7468075B2 (en) 2001-05-25 2008-12-23 Conformis, Inc. Methods and compositions for articular repair
GB9700508D0 (en) 1997-01-11 1997-02-26 Smith & Nephew Hydrogels
US5866165A (en) 1997-01-15 1999-02-02 Orquest, Inc. Collagen-polysaccharide matrix for bone and cartilage repair
AU737097B2 (en) 1997-01-28 2001-08-09 New York Society For The Relief Of The Ruptured And Crippled, Maintaining The Hospital For Special Surgery Method and apparatus for femoral resection
GB9702202D0 (en) 1997-02-04 1997-03-26 Osteometer Meditech As Diagnosis of arthritic conditions
WO1998034655A1 (en) 1997-02-07 1998-08-13 Stryker Corporation Matrix-free osteogenic devices, implants and methods of use thereof
US5779651A (en) * 1997-02-07 1998-07-14 Bio Syntech Medical apparatus for the diagnosis of cartilage degeneration via spatial mapping of compression-induced electrical potentials
US6146385A (en) * 1997-02-11 2000-11-14 Smith & Nephew, Inc. Repairing cartilage
AU6160798A (en) * 1997-02-14 1998-09-08 Government Of The United States Of America, As Represented By The Secretary Of The Department Of Health And Human Services, The Method for measuring mechanical properties of the collagen network in cartilage
US5880976A (en) * 1997-02-21 1999-03-09 Carnegie Mellon University Apparatus and method for facilitating the implantation of artificial components in joints
US6205411B1 (en) * 1997-02-21 2001-03-20 Carnegie Mellon University Computer-assisted surgery planner and intra-operative guidance system
GB2323036B (en) 1997-03-14 2001-04-11 Finsbury Prosthetic implant and surgical tool
DE19721661A1 (en) 1997-05-23 1998-11-26 Zimmer Markus Bone and cartilage replacement structures
CN2305966Y (en) 1997-06-09 1999-02-03 山东省文登整骨医院 Bone and joint generating body
JPH1119104A (en) 1997-06-30 1999-01-26 Kazumasa Itokazu Artificial bone replenishing material for knee tibia round part sinking fracture
US6311083B1 (en) 1997-07-21 2001-10-30 Siemens Aktiengesellschaft Method for determining an examination point for the diaphanoscopic examination of a being and device for realizing the same
US6078680A (en) 1997-07-25 2000-06-20 Arch Development Corporation Method, apparatus, and storage medium for detection of nodules in biological tissue using wavelet snakes to characterize features in radiographic images
US6110209A (en) 1997-08-07 2000-08-29 Stone; Kevin R. Method and paste for articular cartilage transplantation
EP0896825B1 (en) 1997-08-14 2002-07-17 Sulzer Innotec Ag Composition and device for in vivo cartilage repair comprising nanocapsules with osteoinductive and/or chondroinductive factors
FR2767675B1 (en) 1997-08-26 1999-12-03 Materiel Orthopedique En Abreg INTERSOMATIC IMPLANT AND ANCILLARY OF PREPARATION SUITABLE FOR ALLOWING ITS POSITION
WO1999008598A1 (en) 1997-08-19 1999-02-25 Mendlein John D Ultrasonic transmission films and devices, particularly for hygienic transducer surfaces
US5913821A (en) 1997-10-14 1999-06-22 Cornell Research Foundation, Inc. Diagnostic method and apparatus for assessing canine hip dysplasia
FR2769826B1 (en) 1997-10-21 1999-12-03 Aesculap Sa KNEE PROSTHESIS COMPRISING A TIBIAL THICKNESS
US6161080A (en) * 1997-11-17 2000-12-12 The Trustees Of Columbia University In The City Of New York Three dimensional multibody modeling of anatomical joints
WO1999025263A1 (en) * 1997-11-18 1999-05-27 Pappas Michael J Anterior-posterior femoral resection guide with set of detachable collets
JPH11155142A (en) 1997-11-19 1999-06-08 Mitsubishi Electric Corp Medical treatment support system
US6082364A (en) 1997-12-15 2000-07-04 Musculoskeletal Development Enterprises, Llc Pluripotential bone marrow cell line and methods of using the same
DE19803673A1 (en) 1998-01-30 1999-08-05 Norbert M Dr Meenen Biohybrid joint replacement
US5916220A (en) 1998-02-02 1999-06-29 Medidea, Llc Bone cutting guide and method to accommodate different-sized implants
EP0943297B1 (en) 1998-02-11 2000-03-08 PLUS Endoprothetik AG Femoral part for a hip joint prosthesis
DE19807603A1 (en) 1998-02-17 1999-08-19 Krehl Inlet for knee joint endoprosthesis adjusts flexible to radius of femur
JPH11239165A (en) * 1998-02-20 1999-08-31 Fuji Photo Film Co Ltd Medical network system
US6057927A (en) 1998-02-25 2000-05-02 American Iron And Steel Institute Laser-ultrasound spectroscopy apparatus and method with detection of shear resonances for measuring anisotropy, thickness, and other properties
US6171340B1 (en) * 1998-02-27 2001-01-09 Mcdowell Charles L. Method and device for regenerating cartilage in articulating joints
WO1999047186A1 (en) 1998-03-18 1999-09-23 University Of Pittsburgh Chitosan-based composite materials containing glycosaminoglycan for cartilage repair
US6074352A (en) 1998-03-26 2000-06-13 Brigham And Women's Hospital Method for the treatment of joint diseases characterized by unwanted pannus
JP3694584B2 (en) 1998-03-31 2005-09-14 京セラ株式会社 Surface-modified bone prosthesis member and method for manufacturing the same
US6219571B1 (en) 1998-04-06 2001-04-17 Board Of Trustees Of The Leland Stanford Junior University Magnetic resonance imaging using driven equilibrium fourier transform
US5882929A (en) 1998-04-07 1999-03-16 Tissue Engineering, Inc. Methods and apparatus for the conditioning of cartilage replacement tissue
EP2133725B1 (en) 1998-04-21 2018-06-06 University of Connecticut Fabrication method for nanofabrication using multi-photon excitation
US5997582A (en) 1998-05-01 1999-12-07 Weiss; James M. Hip replacement methods and apparatus
US6090144A (en) 1998-05-12 2000-07-18 Letot; Patrick Synthetic knee system
US6835377B2 (en) 1998-05-13 2004-12-28 Osiris Therapeutics, Inc. Osteoarthritis cartilage regeneration
WO1999060939A1 (en) * 1998-05-28 1999-12-02 Orthosoft, Inc. Interactive computer-assisted surgical system and method thereof
US6007537A (en) 1998-06-15 1999-12-28 Sulzer Orthopedics Inc. Nested cutting block
JP2954576B1 (en) 1998-06-29 1999-09-27 三菱電機株式会社 Insertion / extraction device and electronic equipment system
US6010509A (en) * 1998-07-01 2000-01-04 The Dana Center For Orthopaedic Implants Patella resection drill and prosthesis implantation device
US6175619B1 (en) * 1998-07-08 2001-01-16 At&T Corp. Anonymous voice communication using on-line controls
US6081577A (en) 1998-07-24 2000-06-27 Wake Forest University Method and system for creating task-dependent three-dimensional images
US6056756A (en) 1998-08-11 2000-05-02 Johnson & Johnson Professional, Inc. Femoral tensing and sizing device
TR200100482T2 (en) 1998-08-14 2001-06-21 Verigen Transplantation Service International(Vtsi)Ag Methods for chondrocyte cell transplantation; instruments and items
US6530956B1 (en) 1998-09-10 2003-03-11 Kevin A. Mansmann Resorbable scaffolds to promote cartilage regeneration
US6132468A (en) 1998-09-10 2000-10-17 Mansmann; Kevin A. Arthroscopic replacement of cartilage using flexible inflatable envelopes
US7239908B1 (en) * 1998-09-14 2007-07-03 The Board Of Trustees Of The Leland Stanford Junior University Assessing the condition of a joint and devising treatment
US9289153B2 (en) * 1998-09-14 2016-03-22 The Board Of Trustees Of The Leland Stanford Junior University Joint and cartilage diagnosis, assessment and modeling
ATE439806T1 (en) * 1998-09-14 2009-09-15 Univ Leland Stanford Junior DETERMINING THE CONDITION OF A JOINT AND PREVENTING DAMAGE
US6443991B1 (en) 1998-09-21 2002-09-03 Depuy Orthopaedics, Inc. Posterior stabilized mobile bearing knee
ATE413841T1 (en) 1998-10-02 2008-11-15 Synthes Gmbh INTERVERBAL DISC SPACE DISTRACTOR
US6063091A (en) 1998-10-13 2000-05-16 Stryker Technologies Corporation Methods and tools for tibial intermedullary revision surgery and associated tibial components
US6585666B2 (en) 1998-10-13 2003-07-01 The Administrators Of The Tulane Educational Fund Arthroscopic diagnostic probe to measure mechanical properties of articular cartilage
US6500208B1 (en) 1998-10-16 2002-12-31 Biomet, Inc. Nonmodular joint prosthesis convertible in vivo to a modular prosthesis
US6310619B1 (en) 1998-11-10 2001-10-30 Robert W. Rice Virtual reality, tissue-specific body model having user-variable tissue-specific attributes and a system and method for implementing the same
US6328765B1 (en) 1998-12-03 2001-12-11 Gore Enterprise Holdings, Inc. Methods and articles for regenerating living tissue
US6106529A (en) 1998-12-18 2000-08-22 Johnson & Johnson Professional, Inc. Epicondylar axis referencing drill guide
US6302582B1 (en) 1998-12-22 2001-10-16 Bio-Imaging Technologies, Inc. Spine phantom simulating cortical and trabecular bone for calibration of dual energy x-ray bone densitometers
US6623526B1 (en) 1999-01-08 2003-09-23 Corin Limited Knee prosthesis
US6146422A (en) 1999-01-25 2000-11-14 Lawson; Kevin Jon Prosthetic nucleus replacement for surgical reconstruction of intervertebral discs and treatment method
US6156069A (en) 1999-02-04 2000-12-05 Amstutz; Harlan C. Precision hip joint replacement method
EP1161201A4 (en) 1999-02-16 2006-07-19 Zimmer Orthobiologics Inc Device and method for regeneration and repair of cartilage lesions
GB2348373B (en) 1999-03-09 2001-03-14 Corin Medical Ltd A knee prosthesis
US6120541A (en) 1999-03-23 2000-09-19 Johnson; Lanny L. Apparatus for use in grafting articular cartilage
ES2395057T3 (en) * 1999-03-25 2013-02-07 Metabolix, Inc. Medical devices and applications of polyhydroxyalkanoate polymers
EP1173119B1 (en) 1999-04-02 2006-01-11 FELL, Barry M. Surgically implantable knee prosthesis
US6206927B1 (en) * 1999-04-02 2001-03-27 Barry M. Fell Surgically implantable knee prothesis
US6558421B1 (en) 2000-09-19 2003-05-06 Barry M. Fell Surgically implantable knee prosthesis
US6866684B2 (en) * 1999-05-10 2005-03-15 Barry M. Fell Surgically implantable knee prosthesis having different tibial and femoral surface profiles
US6310477B1 (en) 1999-05-10 2001-10-30 General Electric Company MR imaging of lesions and detection of malignant tumors
US6966928B2 (en) * 1999-05-10 2005-11-22 Fell Barry M Surgically implantable knee prosthesis having keels
US6911044B2 (en) * 1999-05-10 2005-06-28 Barry M. Fell Surgically implantable knee prosthesis having medially shifted tibial surface
US6855165B2 (en) * 1999-05-10 2005-02-15 Barry M. Fell Surgically implantable knee prosthesis having enlarged femoral surface
US6923831B2 (en) * 1999-05-10 2005-08-02 Barry M. Fell Surgically implantable knee prosthesis having attachment apertures
US6893463B2 (en) * 1999-05-10 2005-05-17 Barry M. Fell Surgically implantable knee prosthesis having two-piece keyed components
DE19922279A1 (en) 1999-05-11 2000-11-16 Friedrich Schiller Uni Jena Bu Procedure for generating patient-specific implants
US6178225B1 (en) * 1999-06-04 2001-01-23 Edge Medical Devices Ltd. System and method for management of X-ray imaging facilities
US6251143B1 (en) 1999-06-04 2001-06-26 Depuy Orthopaedics, Inc. Cartilage repair unit
DE19926083A1 (en) 1999-06-08 2000-12-14 Universitaetsklinikum Freiburg Biological joint construct
FR2795945B1 (en) 1999-07-09 2001-10-26 Scient X ANATOMICAL INTERSOMATIC IMPLANT AND GRIPPER FOR SUCH AN IMPLANT
US6179840B1 (en) 1999-07-23 2001-01-30 Ethicon, Inc. Graft fixation device and method
US6203546B1 (en) * 1999-07-27 2001-03-20 Macmahon Edward B Method and apparatus for medial tibial osteotomy
DE19936682C1 (en) 1999-08-04 2001-05-10 Luis Schuster Process for the production of an endoprosthesis as a joint replacement for knee joints
GB9918884D0 (en) 1999-08-10 1999-10-13 Novarticulate Bv Method and apparatus for delivering cement to bones
US6322588B1 (en) 1999-08-17 2001-11-27 St. Jude Medical, Inc. Medical devices with metal/polymer composites
US6429013B1 (en) 1999-08-19 2002-08-06 Artecel Science, Inc. Use of adipose tissue-derived stromal cells for chondrocyte differentiation and cartilage repair
FR2798671A1 (en) 1999-09-16 2001-03-23 Univ Paris Curie CHONDROCYTE COMPOSITIONS, PREPARATION AND USES
US6322563B1 (en) 1999-09-17 2001-11-27 Genzyme Corporation Small tissue and membrane fixation apparatus and methods for use thereof
US6436101B1 (en) 1999-10-13 2002-08-20 James S. Hamada Rasp for use in spine surgery
EP1230561B1 (en) * 1999-11-01 2005-10-26 Arthrovision, Inc. Evaluating disease progression using magnetic resonance imaging
US20030173695A1 (en) 1999-11-12 2003-09-18 Therics, Inc. Rapid prototyping and manufacturing process
WO2001035968A1 (en) 1999-11-19 2001-05-25 Children's Medical Center Corporation Methods for inducing chondrogenesis and producing de novo cartilage in vitro
US7013191B2 (en) 1999-11-30 2006-03-14 Orametrix, Inc. Interactive orthodontic care system based on intra-oral scanning of teeth
US6379388B1 (en) 1999-12-08 2002-04-30 Ortho Development Corporation Tibial prosthesis locking system and method of repairing knee joint
US6623963B1 (en) 1999-12-20 2003-09-23 Verigen Ag Cellular matrix
US6334066B1 (en) 1999-12-21 2001-12-25 Siemens Aktiengesellschaft Method for monitoring growth disorder therapy
US7104996B2 (en) * 2000-01-14 2006-09-12 Marctec. Llc Method of performing surgery
US6702821B2 (en) * 2000-01-14 2004-03-09 The Bonutti 2003 Trust A Instrumentation for minimally invasive joint replacement and methods for using same
US6508821B1 (en) 2000-01-28 2003-01-21 Depuy Orthopaedics, Inc. Soft tissue repair material fixation apparatus and method
US6342075B1 (en) 2000-02-18 2002-01-29 Macarthur A. Creig Prosthesis and methods for total knee arthroplasty
US6382028B1 (en) 2000-02-23 2002-05-07 Massachusetts Institute Of Technology Ultrasonic defect detection system
US6371958B1 (en) 2000-03-02 2002-04-16 Ethicon, Inc. Scaffold fixation device for use in articular cartilage repair
US6332894B1 (en) 2000-03-07 2001-12-25 Zimmer, Inc. Polymer filled spinal fusion cage
WO2001068800A1 (en) 2000-03-11 2001-09-20 The Trustees Of Columbia University In The City Of New York Bioreactor for generating functional cartilaginous tissue
US6626945B2 (en) 2000-03-14 2003-09-30 Chondrosite, Llc Cartilage repair plug
US6632246B1 (en) 2000-03-14 2003-10-14 Chondrosite, Llc Cartilage repair plug
US6712856B1 (en) * 2000-03-17 2004-03-30 Kinamed, Inc. Custom replacement device for resurfacing a femur and method of making the same
US6629997B2 (en) * 2000-03-27 2003-10-07 Kevin A. Mansmann Meniscus-type implant with hydrogel surface reinforced by three-dimensional mesh
GB0007392D0 (en) 2000-03-27 2000-05-17 Benoist Girard & Cie Prosthetic femoral component
US6998841B1 (en) * 2000-03-31 2006-02-14 Virtualscopics, Llc Method and system which forms an isotropic, high-resolution, three-dimensional diagnostic image of a subject from two-dimensional image data scans
WO2001077988A2 (en) 2000-04-05 2001-10-18 Therics, Inc. System and method for rapidly customizing a design and remotely manufacturing biomedical devices using a computer system
US6772026B2 (en) 2000-04-05 2004-08-03 Therics, Inc. System and method for rapidly customizing design, manufacture and/or selection of biomedical devices
US20020016543A1 (en) * 2000-04-06 2002-02-07 Tyler Jenny A. Method for diagnosis of and prognosis for damaged tissue
AU2001256992A1 (en) * 2000-04-07 2001-10-23 Stephen R. Aylward Systems and methods for tubular object processing
US6375658B1 (en) 2000-04-28 2002-04-23 Smith & Nephew, Inc. Cartilage grafting
EP2314257B9 (en) * 2000-05-01 2013-02-27 ArthroSurface, Inc. System for joint resurface repair
JP2003531657A (en) 2000-05-01 2003-10-28 アースロサーフェス， インク． Joint resurfacing repair system and method
US8177841B2 (en) 2000-05-01 2012-05-15 Arthrosurface Inc. System and method for joint resurface repair
US6679917B2 (en) * 2000-05-01 2004-01-20 Arthrosurface, Incorporated System and method for joint resurface repair
US6373250B1 (en) 2000-05-19 2002-04-16 Ramot University Authority For Applied Research And Industrial Development Ltd. Method of magnetic resonance imaging
GB0015430D0 (en) 2000-06-24 2000-08-16 Victrex Mfg Ltd Bio-compatible polymeric materials
GB0015424D0 (en) 2000-06-24 2000-08-16 Victrex Mfg Ltd Bio-compatible polymeric materials
GB0015433D0 (en) 2000-06-24 2000-08-16 Victrex Mfg Ltd Bio-compatible polymeric materials
US6296646B1 (en) 2000-06-29 2001-10-02 Richard V. Williamson Instruments and methods for use in performing knee surgery
US6478799B1 (en) 2000-06-29 2002-11-12 Richard V. Williamson Instruments and methods for use in performing knee surgery
US6479996B1 (en) 2000-07-10 2002-11-12 Koninklijke Philips Electronics Magnetic resonance imaging of several volumes
DK177997B1 (en) * 2000-07-19 2015-02-23 Ed Geistlich Söhne Ag Für Chemische Ind Bone material and collagen combination for healing of damaged joints
DE10036207B4 (en) 2000-07-25 2006-11-30 Siemens Ag Method for performing a perfusion measurement by means of magnetic resonance imaging
US6249692B1 (en) * 2000-08-17 2001-06-19 The Research Foundation Of City University Of New York Method for diagnosis and management of osteoporosis
AU2001285488A1 (en) 2000-08-28 2002-03-13 Advanced Bio Surfaces, Inc Method for mammalian joint resurfacing
US20020186818A1 (en) 2000-08-29 2002-12-12 Osteonet, Inc. System and method for building and manipulating a centralized measurement value database
WO2002017789A2 (en) 2000-08-29 2002-03-07 Imaging Therapeutics Methods and devices for quantitative analysis of x-ray images
US7467892B2 (en) 2000-08-29 2008-12-23 Imaging Therapeutics, Inc. Calibration devices and methods of use thereof
US7050534B2 (en) 2000-08-29 2006-05-23 Imaging Therapeutics, Inc. Methods and devices for quantitative analysis of x-ray images
US6904123B2 (en) 2000-08-29 2005-06-07 Imaging Therapeutics, Inc. Methods and devices for quantitative analysis of x-ray images
AU2001296873A1 (en) * 2000-09-14 2002-03-26 Leland Stanford Junior University Technique for manipulating medical images
WO2002022014A1 (en) * 2000-09-14 2002-03-21 The Board Of Trustees Of The Leland Stanford Junior University Assessing the condition of a joint and devising treatment
ATE414310T1 (en) 2000-09-14 2008-11-15 Univ Leland Stanford Junior METHOD FOR MANIPULATION OF MEDICAL IMAGES
US20070047794A1 (en) 2000-10-11 2007-03-01 Philipp Lang Methods and devices for analysis of x-ray images
CA2425656A1 (en) * 2000-10-11 2002-04-18 Philipp Lang Methods and devices for analysis of x-ray images
US7660453B2 (en) 2000-10-11 2010-02-09 Imaging Therapeutics, Inc. Methods and devices for analysis of x-ray images
EP1351628B1 (en) 2000-10-17 2007-04-25 Maria-Grazia Ascenzi System and method for modeling bone structure
JP2004512099A (en) 2000-10-25 2004-04-22 エスディージーアイ・ホールディングス・インコーポレーテッド Self-conforming orthopedic implant
CA2427483C (en) 2000-10-31 2011-07-26 Ecole De Technologie Superieure High precision modeling of a body part using a 3d imaging system
AU2002211850B2 (en) 2000-10-31 2006-07-13 Depuy Spine, Inc. Mineralized collagen-polysaccharide matrix for bone and cartilage repair
DE10055465A1 (en) 2000-11-09 2002-05-23 Blz Gmbh Material useful for making bone replacement implants comprises nonmetallic inorganic filler particles embedded in a laser-sinterable biocompatible polymer matrix
US6510334B1 (en) * 2000-11-14 2003-01-21 Luis Schuster Method of producing an endoprosthesis as a joint substitute for a knee joint
US6786930B2 (en) 2000-12-04 2004-09-07 Spineco, Inc. Molded surgical implant and method
US6494914B2 (en) 2000-12-05 2002-12-17 Biomet, Inc. Unicondylar femoral prosthesis and instruments
US7192445B2 (en) 2000-12-06 2007-03-20 Astra Tech Ab Medical prosthetic devices and implants having improved biocompatibility
US20020072821A1 (en) 2000-12-11 2002-06-13 Baker Gregg S. Parametric input to a design and production system
US6503280B2 (en) 2000-12-26 2003-01-07 John A. Repicci Prosthetic knee and method of inserting
US6942670B2 (en) 2000-12-27 2005-09-13 Depuy Orthopaedics, Inc. Prosthesis evaluation assembly and associated method
FR2819714B1 (en) 2001-01-19 2004-02-06 Frederic Fortin INTERVERTEBRAL DISC PROSTHESIS AND ITS IMPLEMENTATION METHOD
WO2002061688A2 (en) 2001-01-29 2002-08-08 The Acrobot Company Limited Modelling for surgery
BR0116855B1 (en) 2001-02-07 2012-06-12 process for establishing a virtual three-dimensional representation of a bone or bone fragment from x-ray images.
US6743232B2 (en) 2001-02-26 2004-06-01 David W. Overaker Tissue scaffold anchor for cartilage repair
US6575986B2 (en) 2001-02-26 2003-06-10 Ethicon, Inc. Scaffold fixation device for use in articular cartilage repair
US20030045935A1 (en) * 2001-02-28 2003-03-06 Angelucci Christopher M. Laminoplasty implants and methods of use
US6632235B2 (en) 2001-04-19 2003-10-14 Synthes (U.S.A.) Inflatable device and method for reducing fractures in bone and in treating the spine
US7664297B2 (en) 2001-04-26 2010-02-16 Teijin Limited Three-dimensional joint structure measuring method
US6719794B2 (en) 2001-05-03 2004-04-13 Synthes (U.S.A.) Intervertebral implant for transforaminal posterior lumbar interbody fusion procedure
US6444222B1 (en) 2001-05-08 2002-09-03 Verigen Transplantation Services International Ag Reinforced matrices
US6816607B2 (en) 2001-05-16 2004-11-09 Siemens Corporate Research, Inc. System for modeling static and dynamic three dimensional anatomical structures by 3-D models
EP1389980B1 (en) 2001-05-25 2011-04-06 Conformis, Inc. Methods and compositions for articular resurfacing
US20070083266A1 (en) 2001-05-25 2007-04-12 Vertegen, Inc. Devices and methods for treating facet joints, uncovertebral joints, costovertebral joints and other joints
US8439926B2 (en) 2001-05-25 2013-05-14 Conformis, Inc. Patient selectable joint arthroplasty devices and surgical tools
EP1389947B1 (en) * 2001-05-25 2009-08-26 Imaging Therapeutics, Inc. Methods to diagnose treat and prevent bone loss
US20130211531A1 (en) 2001-05-25 2013-08-15 Conformis, Inc. Patient-adapted and improved articular implants, designs and related guide tools
US6482209B1 (en) 2001-06-14 2002-11-19 Gerard A. Engh Apparatus and method for sculpting the surface of a joint
WO2003000857A2 (en) * 2001-06-22 2003-01-03 The Regents Of The University Of Michigan Design methodology for tissue engineering scaffolds and biomaterial implants
US7163563B2 (en) 2001-07-16 2007-01-16 Depuy Products, Inc. Unitary surgical device and method
DE10135771B4 (en) 2001-07-23 2006-02-16 Aesculap Ag & Co. Kg Facet joint implant
US7058209B2 (en) 2001-09-20 2006-06-06 Eastman Kodak Company Method and computer program product for locating facial features
FR2830433B1 (en) 2001-10-04 2005-07-01 Stryker Spine ASSEMBLY FOR OSTEOSYNTHESIS OF THE SPINACH COMPRISING AN ANCHORING MEMBER HEAD AND A TOOL FOR HEAD FIXING
RO128189A2 (en) 2001-11-02 2013-03-29 International Patent Owners (Cayman) Limited Apparatuses and methods for bone surgery
CN1612713A (en) 2001-11-05 2005-05-04 计算机化医学体系股份有限公司 Apparatus and method for registration, guidance, and targeting of external beam radiation therapy
US7020314B1 (en) 2001-11-13 2006-03-28 Koninklijke Philips Electronics N.V. Black blood angiography method and apparatus
US7141053B2 (en) 2001-11-28 2006-11-28 Wright Medical Technology, Inc. Methods of minimally invasive unicompartmental knee replacement
AU2002365379A1 (en) 2001-11-28 2003-06-10 Wright Medical Technology, Inc. Knee joint prostheses
WO2003045256A2 (en) 2001-11-28 2003-06-05 Wright Medical Technology, Inc. Instrumentation for minimally invasive unicompartmental knee replacement
US7572295B2 (en) 2001-12-04 2009-08-11 Active Implants Corporation Cushion bearing implants for load bearing applications
US6873741B2 (en) 2002-01-10 2005-03-29 Sharp Laboratories Of America Nonlinear edge-enhancement filter
DE60304233T2 (en) 2002-01-11 2007-01-18 Zimmer Gmbh Implantable knee prosthesis with keels
CA2473858A1 (en) 2002-01-22 2003-07-31 Advanced Bio Surfaces, Inc. Interpositional arthroplasty system and method
US20020106625A1 (en) 2002-02-07 2002-08-08 Hung Clark T. Bioreactor for generating functional cartilaginous tissue
NO20020647A (en) 2002-02-08 2003-07-28 Scandinavian Customized Prosthesis Asa System and procedure for preparation and transfer of specifications for patient-adapted prostheses
US6689139B2 (en) * 2002-02-15 2004-02-10 Paul C. Horn Long oblique ulna shortening osteotomy jig
JP4193177B2 (en) 2002-02-20 2008-12-10 ジンマー インコーポレーテッド Prosthesis and tibial implant device for knee arthroplasty
CA2475142C (en) 2002-02-26 2009-04-28 Donald M. Smucker Patella resection guide
US6911045B2 (en) 2002-04-04 2005-06-28 Osteotech, Inc. Bio-implant insertion instrument
US6946001B2 (en) 2003-02-03 2005-09-20 Zimmer Technology, Inc. Mobile bearing unicompartmental knee
US8801720B2 (en) 2002-05-15 2014-08-12 Otismed Corporation Total joint arthroplasty system
WO2003099159A2 (en) 2002-05-24 2003-12-04 Medicinelodge, Inc. Femoral components for knee arthroplasty
US7615081B2 (en) 2002-05-24 2009-11-10 Zimmer, Inc. Femoral components for knee arthroplasty
US7922772B2 (en) * 2002-05-24 2011-04-12 Zimmer, Inc. Implants and related methods and apparatus for securing an implant on an articulating surface of an orthopedic joint
US8211113B2 (en) 2002-06-21 2012-07-03 Depuy Products, Inc. Prosthesis cutting guide, cutting tool and method
AU2003247952A1 (en) 2002-07-11 2004-02-02 Advanced Bio Surfaces, Inc. Method and kit for interpositional arthroplasty
WO2004025541A1 (en) 2002-09-16 2004-03-25 Imaging Therapeutics, Inc. Imaging markers in musculoskeletal disease
US7840247B2 (en) 2002-09-16 2010-11-23 Imatx, Inc. Methods of predicting musculoskeletal disease
ATE497740T1 (en) 2002-10-07 2011-02-15 Conformis Inc MINIMALLY INVASIVE JOINT IMPLANT WITH A THREE-DIMENSIONAL GEOMETRY ADAPTED TO THE JOINT SURFACES
US7796791B2 (en) 2002-11-07 2010-09-14 Conformis, Inc. Methods for determining meniscal size and shape and for devising treatment
US20060147332A1 (en) 2004-12-30 2006-07-06 Howmedica Osteonics Corp. Laser-produced porous structure
US6770099B2 (en) 2002-11-19 2004-08-03 Zimmer Technology, Inc. Femoral prosthesis
US20040102852A1 (en) 2002-11-22 2004-05-27 Johnson Erin M. Modular knee prosthesis
AU2003302375A1 (en) 2002-11-22 2004-06-18 Juridical Foundation Osaka Industrial Promotion Organization Artificial joint, medical implant, and methods of producing the artificial joint and medical implant
US6749638B1 (en) 2002-11-22 2004-06-15 Zimmer Technology, Inc. Modular knee prosthesis
ES2465090T3 (en) 2002-12-20 2014-06-05 Smith & Nephew, Inc. High performance knee prostheses
US6869447B2 (en) 2002-12-20 2005-03-22 Depuy Products, Inc. Prosthetic knee implant with modular augment
EP1437101A3 (en) 2002-12-31 2004-12-22 DePuy Spine, Inc. Prosthetic facet joint ligament
US7008430B2 (en) 2003-01-31 2006-03-07 Howmedica Osteonics Corp. Adjustable reamer with tip tracker linkage
US7033397B2 (en) 2003-02-03 2006-04-25 Zimmer Technology, Inc. Mobile bearing unicondylar tibial knee prosthesis
US7309339B2 (en) * 2003-02-04 2007-12-18 Howmedica Osteonics Corp. Apparatus for aligning an instrument during a surgical procedure
US6916324B2 (en) 2003-02-04 2005-07-12 Zimmer Technology, Inc. Provisional orthopedic prosthesis for partially resected bone
US20040162561A1 (en) 2003-02-13 2004-08-19 Howmedica Osteonics Corp. Modular patella instrument
WO2004073550A2 (en) 2003-02-20 2004-09-02 Murray Ian P Knee spacer
US6916341B2 (en) 2003-02-20 2005-07-12 Lindsey R. Rolston Device and method for bicompartmental arthroplasty
DE20303498U1 (en) 2003-02-26 2003-07-03 Aesculap AG & Co. KG, 78532 Tuttlingen Surgical adjusting and holding device for tool guiding arrangement, in particular for performance of operation at femur or tibia
CA2519187A1 (en) 2003-03-25 2004-10-14 Imaging Therapeutics, Inc. Methods for the compensation of imaging technique in the processing of radiographic images
US7364590B2 (en) 2003-04-08 2008-04-29 Thomas Siebel Anatomical knee prosthesis
DE50301302D1 (en) 2003-04-25 2005-11-10 Zimmer Gmbh Winterthur Device for preparing a femoral condyle
US7104997B2 (en) 2003-06-19 2006-09-12 Lionberger Jr David R Cutting guide apparatus and surgical method for use in knee arthroplasty
US20070067032A1 (en) 2003-06-27 2007-03-22 Felt Jeffrey C Meniscus preserving implant method and apparatus
AU2003904379A0 (en) * 2003-08-18 2003-08-28 David John Wood Two thirds prosthetic arthroplasty
US9254137B2 (en) 2003-08-29 2016-02-09 Lanterna Medical Technologies Ltd Facet implant
US7905924B2 (en) 2003-09-03 2011-03-15 Ralph Richard White Extracapsular surgical procedure
US8290564B2 (en) * 2003-09-19 2012-10-16 Imatx, Inc. Method for bone structure prognosis and simulated bone remodeling
WO2005027732A2 (en) 2003-09-19 2005-03-31 Imaging Therapeutics, Inc. Method for bone structure prognosis and simulated bone remodeling
US20080058613A1 (en) 2003-09-19 2008-03-06 Imaging Therapeutics, Inc. Method and System for Providing Fracture/No Fracture Classification
US7799085B2 (en) 2003-11-18 2010-09-21 Depuy Products, Inc. Modular implant system with fully porous coated sleeve
US20050119751A1 (en) 2003-11-28 2005-06-02 Lawson Kevin J. Intervertebral bone fusion device
US7282054B2 (en) 2003-12-26 2007-10-16 Zimmer Technology, Inc. Adjustable cut block
US8025663B2 (en) 2003-12-30 2011-09-27 Depuy Products, Inc. Augments for surgical instruments
US8175683B2 (en) 2003-12-30 2012-05-08 Depuy Products, Inc. System and method of designing and manufacturing customized instrumentation for accurate implantation of prosthesis by utilizing computed tomography data
CA2490673C (en) 2003-12-30 2011-11-29 Medicinelodge, Inc. Tethered implant systems for mounting on an articulation surface of an orthopedic joint
US7867236B2 (en) 2003-12-30 2011-01-11 Zimmer, Inc. Instruments and methods for preparing a joint articulation surface for an implant
ATE547998T1 (en) 2004-01-12 2012-03-15 Depuy Products Inc SYSTEMS FOR COMPARTMENT REPLACEMENT IN ONE KNEE
US20050192588A1 (en) 2004-02-27 2005-09-01 Garcia Daniel X. Instrumentation and method for prosthetic knee
CA2580726A1 (en) 2004-09-16 2006-03-30 Imaging Therapeutics, Inc. System and method of predicting future fractures
US20060069318A1 (en) 2004-09-30 2006-03-30 The Regents Of The University Of California Method for assessment of the structure-function characteristics of structures in a human or animal body
US8979857B2 (en) 2004-10-06 2015-03-17 DePuy Synthes Products, LLC Modular medical tool and connector
DE102004063977A1 (en) 2004-10-19 2006-06-22 Mathys Ag Bettlach Ligament Tension Device, Cutting Guide and Osteotomy Technique
US20060111722A1 (en) 2004-11-19 2006-05-25 Hacene Bouadi Surgical cutting tool
MX2007006808A (en) 2004-12-13 2007-10-08 St Francis Medical Tech Inc Inter-facet implant.
US20060136058A1 (en) 2004-12-17 2006-06-22 William Pietrzak Patient specific anatomically correct implants to repair or replace hard or soft tissue
US7776044B2 (en) 2004-12-21 2010-08-17 Zimmer Technology, Inc. Tibial tray inserter
CN101123928A (en) 2005-01-12 2008-02-13 R·I·W·理查森 Prosthetic knee
US20060184176A1 (en) 2005-02-17 2006-08-17 Zimmer Technology, Inc. Tibial trialing assembly and method of trialing a tibial implant
US20060200162A1 (en) 2005-02-21 2006-09-07 Zimmer Technology, Inc. Total knee arthroplasty instruments
US20060195196A1 (en) 2005-02-26 2006-08-31 Zimmer Technology, Inc. Modular tibial implant with a mortise coupling
US7695477B2 (en) 2005-05-26 2010-04-13 Zimmer, Inc. Milling system and methods for resecting a joint articulation surface
US7983777B2 (en) 2005-08-19 2011-07-19 Mark Melton System for biomedical implant creation and procurement
AU2006297137A1 (en) 2005-09-30 2007-04-12 Conformis Inc. Joint arthroplasty devices
WO2007045000A2 (en) 2005-10-14 2007-04-19 Vantus Technology Corporation Personal fit medical implants and orthopedic surgical instruments and methods for making
US20070118055A1 (en) 2005-11-04 2007-05-24 Smith & Nephew, Inc. Systems and methods for facilitating surgical procedures involving custom medical implants
WO2007062080A2 (en) 2005-11-21 2007-05-31 Philipp Lang Intervetebral devices and methods
WO2007062103A1 (en) 2005-11-23 2007-05-31 Conformis, Inc. Implant grasper
EP1803513B1 (en) * 2005-12-30 2017-03-29 Howmedica Osteonics Corp. Method of manufacturing implants using laser
US10034674B2 (en) 2006-02-02 2018-07-31 Steven C Chudik Universal anterior cruciate ligament repair and reconstruction system
CN102599960B (en) 2006-02-06 2015-08-12 康复米斯公司 The arthroplasty devices that patient-selectable selects and surgical instrument
US7967868B2 (en) 2007-04-17 2011-06-28 Biomet Manufacturing Corp. Patient-modified implant and associated method
JP5121816B2 (en) 2006-03-13 2013-01-16 マコ サージカル コーポレーション Prosthetic device and system and method for implanting a prosthetic device
CA2646288A1 (en) 2006-03-21 2007-09-27 Conformis, Inc. Interpositional joint implant
US8246680B2 (en) 2006-05-25 2012-08-21 Spinemedica, Llc Patient-specific spinal implants and related systems and methods
DE502006005408D1 (en) 2006-08-08 2009-12-31 Brainlab Ag Planning procedure and system for free-form implant adaptation
DE102006037067B4 (en) 2006-08-08 2011-06-16 Metoxit Ag Method for producing an implant with a porous, ceramic surface layer
TW200821888A (en) 2006-08-18 2008-05-16 Smith & Amp Nephew Inc Systems and methods for designing, analyzing and using orthopaedic devices
US8214016B2 (en) 2006-12-12 2012-07-03 Perception Raisonnement Action En Medecine System and method for determining an optimal type and position of an implant
US8313530B2 (en) 2007-02-12 2012-11-20 Jmea Corporation Total knee arthroplasty system
WO2008112996A1 (en) 2007-03-14 2008-09-18 Conformis, Inc. Surgical tools for arthroplasty
WO2008157412A2 (en) 2007-06-13 2008-12-24 Conformis, Inc. Surgical cutting guide
EP2265199A4 (en) 2008-03-05 2012-03-07 Conformis Inc Patient selectable joint arthroplasty devices and surgical tools
AU2009246474B2 (en) 2008-05-12 2015-04-16 Conformis, Inc. Devices and methods for treatment of facet and other joints
WO2010099231A2 (en) 2009-02-24 2010-09-02 Conformis, Inc. Automated systems for manufacturing patient-specific orthopedic implants and instrumentation
CN102405032B (en) 2009-02-25 2016-08-03 康复米斯公司 Orthopaedic implants, design and the related tool that patient adapts to and improves
AU2010236263A1 (en) 2009-04-16 2011-11-10 Conformis, Inc. Patient-specific joint arthroplasty devices for ligament repair
WO2010138841A2 (en) 2009-05-29 2010-12-02 Smith & Nephew, Inc. Methods and apparatus for performing knee arthroplasty
SG178836A1 (en) 2009-08-26 2012-04-27 Conformis Inc Patient-specific orthopedic implants and models
AU2010315099B2 (en) 2009-11-04 2014-08-21 Conformis, Inc. Patient-adapted and improved orthopedic implants, designs and related tools
AU2010327987B2 (en) 2009-12-11 2015-04-02 Conformis, Inc. Patient-specific and patient-engineered orthopedic implants

Similar Documents

Publication Publication Date Title
EP1322224B1 (en) Assessing condition of a joint and cartilage loss
EP1322225B1 (en) Assessing the condition of a joint and devising treatment
USRE43282E1 (en) Assessing the condition of a joint and devising treatment
US9289153B2 (en) Joint and cartilage diagnosis, assessment and modeling
EP1139872B1 (en) Assessing the condition of a joint and preventing damage
AU2001290887A1 (en) Assessing condition of a joint and cartilage loss
AU2001290888A1 (en) Assessing the condition of a joint and devising treatment
AU2007209792A1 (en) Assessing the condition of a joint and preventing damage
AU2006207884A1 (en) Assessing condition of a joint and cartilage loss