Nothing Special   »   [go: up one dir, main page]
Skip to main content
Springer Nature Link
Log in

Diffusion tensor magnetic resonance imaging of the breast: a pilot study

  • Breast
  • Published:
European Radiology Aims and scope Submit manuscript

Abstract

Objectives

Diffusion-weighted MR imaging has shown diagnostic value for differential diagnosis of breast lesions. Diffusion tensor imaging (DTI) adds information about tissue microstructure by addressing diffusion direction. We have examined the diagnostic application of DTI of the breast.

Methods

A total of 59 patients (71 lesions: 54 malignant, 17 benign) successfully underwent prospective echo planar imaging–DTI (EPI-DTI) (1.5 T). First, diffusion direction both of parenchyma as well as lesions was assessed on parametric maps. Subsequently, apparent diffusion coefficient (ADC) and fractional anisotropy (FA) values were measured. Statistics included univariate (Mann–Whitney U test, receiver operating analysis) and multivariate (logistic regression analysis, LRA) tests.

Results

Main diffusion direction of parenchyma was anterior–posterior in the majority of cases (66.1%), whereas lesions (benign, malignant) showed no predominant diffusion direction in the majority of cases (23.9%). ADC values showed highest differences between benign and malignant lesions (P < 0.001) with resulting area under the curve (AUC) of 0.899. FA values were lower in benign (interquartile range, IR, 0.14–0.24) compared to malignant lesions (IR 0.21–0.35, P < 0.002) with an AUC of 0.751–0.770. Following LRA, FA did not prove to have incremental value for differential diagnosis over ADC values.

Conclusions

Microanatomical differences between benign and malignant breast lesions as well as breast parenchyma can be visualized by using DTI.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Subscribe and save

Springer+ Basic
$34.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6

Similar content being viewed by others

References

  1. Peters NH, Borel Rinkes IH, Zuithoff NP et al (2008) Meta-analysis of MR imaging in the diagnosis of breast lesions. Radiology 246:116–124

    Article  PubMed  Google Scholar 

  2. Warner E, Messersmith H, Causer P et al (2008) Systematic review: using magnetic resonance imaging to screen women at high risk for breast cancer. Ann Intern Med 148:671–679

    PubMed  Google Scholar 

  3. Kaiser WA, Zeitler E (1989) MR imaging of the breast: fast imaging sequences with and without Gd-DTPA. Preliminary observations. Radiology 170:681–686

    CAS  PubMed  Google Scholar 

  4. Kuhl C (2007) The current status of breast MR imaging. Part I. Choice of technique, image interpretation, diagnostic accuracy, and transfer to clinical practice. Radiology 244:356–378

    Article  PubMed  Google Scholar 

  5. Naumov GN, Bender E, Zurakowski D et al (2006) A model of human tumor dormancy: an angiogenic switch from the nonangiogenic phenotype. J Natl Cancer Inst 98:316–325

    Article  PubMed  Google Scholar 

  6. Baltzer PA, Freiberg C, Beger S et al (2009) Clinical MR-mammography: are computer-assisted methods superior to visual or manual measurements for curve type analysis? A systematic approach. Acad Radiol 16:1070–1076

    Article  PubMed  Google Scholar 

  7. Gibbs P, Liney GP, Lowry M et al (2004) Differentiation of benign and malignant sub-1 cm breast lesions using dynamic contrast enhanced MRI. Breast 13:115–121

    Article  CAS  PubMed  Google Scholar 

  8. Siegmann KC, Muller-Schimpfle M, Schick F et al (2002) MR imaging-detected breast lesions: histopathologic correlation of lesion characteristics and signal intensity data. AJR Am J Roentgenol 178:1403–1409

    PubMed  Google Scholar 

  9. Zwick S, Brix G, Tofts PS et al (2009) Simulation-based comparison of two approaches frequently used for dynamic contrast-enhanced MRI. Eur Radiol 20:432–442

    Article  PubMed  Google Scholar 

  10. Tofts PS, Berkowitz B, Schnall MD (1995) Quantitative analysis of dynamic Gd-DTPA enhancement in breast tumors using a permeability model. Magn Reson Med 33:564–568

    Article  CAS  PubMed  Google Scholar 

  11. Ikeda DM, Hylton NM, Kuhl CK et al (2003) MRI breast imaging reporting and data system atlas, 1st edn. American College of Radiology, Reston

    Google Scholar 

  12. Malich A, Fischer DR, Wurdinger S et al (2005) Potential MRI interpretation model: differentiation of benign from malignant breast masses. AJR Am J Roentgenol 185:964–970

    Article  PubMed  Google Scholar 

  13. Mountford C, Ramadan S, Stanwell P et al (2009) Proton MRS of the breast in the clinical setting. NMR Biomed 22:54–64

    Article  CAS  PubMed  Google Scholar 

  14. Schnall MD, Blume J, Bluemke DA et al (2006) Diagnostic architectural and dynamic features at breast MR imaging: multicenter study. Radiology 238:42–53

    Article  PubMed  Google Scholar 

  15. Tsushima Y, Takahashi-Taketomi A, Endo K (2009) Magnetic resonance (MR) differential diagnosis of breast tumors using apparent diffusion coefficient (ADC) on 1.5-T. J Magn Reson Imaging 30:249–255

    Article  PubMed  Google Scholar 

  16. Baltzer PA, Benndorf M, Dietzel M et al (2009) Sensitivity and specificity of unenhanced MR mammography (DWI combined with T2-weighted TSE imaging, ueMRM) for the differentiation of mass lesions. Eur Radiol 20:1101–1110

    Article  PubMed  Google Scholar 

  17. Baltzer PA, Dietzel M, Vag T et al (2009) Diffusion weighted imaging - useful in all kinds of lesions? A systematic review. Eur Radiol 19:765–769

    Article  Google Scholar 

  18. Baltzer PA, Renz DM, Herrmann KH et al (2009) Diffusion-weighted imaging (DWI) in MR mammography (MRM): clinical comparison of echo planar imaging (EPI) and half-Fourier single-shot turbo spin echo (HASTE) diffusion techniques. Eur Radiol 19:1612–1620

    Article  CAS  PubMed  Google Scholar 

  19. Guo Y, Cai YQ, Cai ZL et al (2002) Differentiation of clinically benign and malignant breast lesions using diffusion-weighted imaging. J Magn Reson Imaging 16:172–178

    Article  PubMed  Google Scholar 

  20. Hatakenaka M, Soeda H, Yabuuchi H et al (2008) Apparent diffusion coefficients of breast tumors: clinical application. Magn Reson Med Sci 7:23–29

    Article  PubMed  Google Scholar 

  21. Kinoshita T, Yashiro N, Ihara N et al (2002) Diffusion-weighted half-Fourier single-shot turbo spin echo imaging in breast tumors: differentiation of invasive ductal carcinoma from fibroadenoma. J Comput Assist Tomogr 26:1042–1046

    Article  PubMed  Google Scholar 

  22. Kuroki Y, Nasu K, Kuroki S et al (2004) Diffusion-weighted imaging of breast cancer with the sensitivity encoding technique: analysis of the apparent diffusion coefficient value. Magn Reson Med Sci 3:79–85

    Article  PubMed  Google Scholar 

  23. Kuroki-Suzuki S, Kuroki Y, Nasu K et al (2007) Detecting breast cancer with non-contrast MR imaging: combining diffusion-weighted and STIR imaging. Magn Reson Med Sci 6:21–27

    Article  PubMed  Google Scholar 

  24. Marini C, Iacconi C, Giannelli M et al (2007) Quantitative diffusion-weighted MR imaging in the differential diagnosis of breast lesion. Eur Radiol 17:2646–2655

    Article  CAS  PubMed  Google Scholar 

  25. Park MJ, Cha ES, Kang BJ et al (2007) The role of diffusion-weighted imaging and the apparent diffusion coefficient (ADC) values for breast tumors. Korean J Radiol 8:390–396

    Article  PubMed  Google Scholar 

  26. Rubesova E, Grell AS, De Maertelaer V et al (2006) Quantitative diffusion imaging in breast cancer: a clinical prospective study. J Magn Reson Imaging 24:319–324

    Article  PubMed  Google Scholar 

  27. Wenkel E, Geppert C, Schulz-Wendtland R et al (2007) Diffusion weighted imaging in breast MRI: comparison of two different pulse sequences. Acad Radiol 14:1077–1083

    Article  PubMed  Google Scholar 

  28. Woodhams R, Kakita S, Hata H et al (2009) Diffusion-weighted imaging of mucinous carcinoma of the breast: evaluation of apparent diffusion coefficient and signal intensity in correlation with histologic findings. AJR Am J Roentgenol 193:260–266

    Article  PubMed  Google Scholar 

  29. Woodhams R, Matsunaga K, Iwabuchi K et al (2005) Diffusion-weighted imaging of malignant breast tumors: the usefulness of apparent diffusion coefficient (ADC) value and ADC map for the detection of malignant breast tumors and evaluation of cancer extension. J Comput Assist Tomogr 29:644–649

    Article  PubMed  Google Scholar 

  30. Woodhams R, Matsunaga K, Kan S et al (2005) ADC mapping of benign and malignant breast tumors. Magn Reson Med Sci 4:35–42

    Article  PubMed  Google Scholar 

  31. Charles-Edwards EM, deSouza NM (2006) Diffusion-weighted magnetic resonance imaging and its application to cancer. Cancer Imaging 6:135–143

    Article  PubMed  Google Scholar 

  32. Hagmann P, Jonasson L, Maeder P et al (2006) Understanding diffusion MR imaging techniques: from scalar diffusion-weighted imaging to diffusion tensor imaging and beyond. Radiographics 26(Suppl 1):S205–S223

    Article  PubMed  Google Scholar 

  33. Partridge SC, Murthy RS, Ziadloo A et al (2010) Diffusion tensor magnetic resonance imaging of the normal breast. Magn Reson Imaging 28:320–328

    Article  PubMed  Google Scholar 

  34. Partridge SC, Ziadloo A, Murthy R et al (2010) Diffusion tensor MRI: preliminary anisotropy measures and mapping of breast tumors. J Magn Reson Imaging 31:339–347

    Article  PubMed  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Institute of Diagnostic and Interventional Radiology, Friedrich Schiller University Jena, Erlanger Allee 101, 07740, Jena, Germany

    Pascal A. T. Baltzer, Anja Schäfer, Matthias Dietzel & Werner A. Kaiser

  2. Institut für Neurowissenschaften & Medizin (INM-1), Forschungszentrum Jülich GmbH, 52425, Jülich, Germany

    David Grässel

  3. Institute of Pathology, Friedrich Schiller University Jena, Ziegmühlenweg 1, 07740, Jena, Germany

    Mieczyslaw Gajda

  4. Clinic of Gynecology, Friedrich Schiller University Jena, Bachstr. 18, 07740, Jena, Germany

    Oumar Camara

Authors
  1. Pascal A. T. Baltzer
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Anja Schäfer
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Matthias Dietzel
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. David Grässel
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Mieczyslaw Gajda
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Oumar Camara
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Werner A. Kaiser
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Pascal A. T. Baltzer.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Baltzer, P.A.T., Schäfer, A., Dietzel, M. et al. Diffusion tensor magnetic resonance imaging of the breast: a pilot study. Eur Radiol 21, 1–10 (2011). https://doi.org/10.1007/s00330-010-1901-9

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00330-010-1901-9

Keywords

Search

Navigation