Abstract
A quantitative analysis of small structures such as focal lesions in patients suffering from multiple sclerosis (MS) is an important issue in both diagnosis and therapy monitoring. In order to reach clinical relevance, the reproducibility and especially the accuracy of a proposed method has to be validated. We propose a framework for the generation of realistic digital phantoms of MS lesions of known volumes and their incorporation into an MR dataset of a healthy volunteer. Due to the absence of a “ground truth” for lesions in general and MS lesions in particular, phantom data are a commonly used validation method for quantitative image analysis methods. However, currently available lesion phantoms suffer from the fact that the embedding structures are only simplifications of the real organs. We generated 54 datasets from a multispectral MR scan with incorporated MS lesion phantoms. The lesion phantoms were created using various shapes (3), sizes (6) and orientations (3). Since the common gold standard in clinical lesion volumetry is based on manual volume tracing, an evaluation is carried out from both a manual analysis of three human experts and a semi-automated approach based on regional histogram analysis. Additionally, an intra-observer study is performed. Our results clearly demonstrate the importance of an improved gold standard in lesion volumetry beyond manual tracing and voxel counting.
Chapter PDF
Similar content being viewed by others
Keywords
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
References
Miller, D.H., Grossman, R.I., Reingold, S.C., McFarland, H.F.: The role of magnetic resonance techniques in understanding and managing multiple sclerosis. Brain 121, 3–24 (1998)
Filippi, M., Horsfield, M.A., Bressi, S., et al.: Intra- and inter-observer agreement of brain MRI lesion volume measurements in multiple sclerosis, A comparison of techniques. Brain 118(6), 1593–1600 (1995)
Udupa, J.K., Wei, L., Samarasekera, S., et al.: Multiple Sclerosis Lesion Quantification Using Fuzzy-Connectedness Principles. IEEE TMI 16(5), 598–609 (1997)
Van Leemput, K., Maes, F., Vandermeulen, D., et al.: Automated segmentation of multiple sclerosis lesions by model outlier detection. IEEE TMI 20(8), 677–688 (2001)
Zijdenbos, A., Forghani, R., Evans, A.: Automatic Quantification of MS Lesions in 3D MRI Brain Data Sets: Validation of INSECT. In: Wells, W.M., Colchester, A.C.F., Delp, S.L. (eds.) MICCAI 1998. LNCS, vol. 1496, pp. 439–448. Springer, Heidelberg (1998)
Al-Zubi, S., Tönnies, K.D., Bodammer, N., Hinrichs, H.: Fusing markov random fields with anatomical knowledge and shape based analysis to segment multiple sclerosis white matter lesions in magnetic resonance images of the brain. In: Proceedings of SPIE (Medical Imaging 2002), San Diego, Febraury 23-28, vol. 4684, pp. 206–215 (2002)
Barkhof, F., Filippi, M., et al.: Improving interobserver variation in reporting gadolinium enhanced MRI lesions in multiple sclerosis. Neurology 49, 1682–1688 (1997)
Tofts, P.S., Barker, G.J., Filippi, M., Gawne-Cain, M., Lai, M.: An oblique cylinder contrast adjusted (OCCA) phantom to measure the accuracy of MRI brain lesion volume estimation schemes in multiple sclerosis. J. Magn. Reson. Imaging 15(2), 183–192 (1997)
Collins, D., Zijdenbos, A., Kollokian, V., et al.: Design and Construction of a Realistic Digital Brain Phantom. IEEE TMI 17(5), 463–468 (1998)
Filippi, M., Gawne-Cain, M.L., Gasperini, C., et al.: Effect on training and different measurement strategies on the reproducibility of brain MRI lesion load measurements in multiple sclerosis. Neurology, 238–244 (January 1998)
Hahn, H.K., Link, F., Peitgen, H.-O.: Concepts for a Rapid Prototyping Platform in Medical Image Analysis and Visualization. In: Proc. SimVis. SCS, pp. 283–298 (March 2003)
Hahn, H.K., Peitgen, H.-O.: IWT– Interactive Watershed Transform: A Hierarchical Method for Efficient Interactive and Automated Segmentation of Multidimensional Gray-Scale Images. In: Medical Imaging: Image Processing, Proc. SPIE, vol. 5032, pp. 643–653 (Febraury 2003)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2003 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Rexilius, J., Hahn, H.K., Bourquain, H., Peitgen, HO. (2003). Ground Truth in MS Lesion Volumetry – A Phantom Study. In: Ellis, R.E., Peters, T.M. (eds) Medical Image Computing and Computer-Assisted Intervention - MICCAI 2003. MICCAI 2003. Lecture Notes in Computer Science, vol 2879. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-39903-2_67
Download citation
DOI: https://doi.org/10.1007/978-3-540-39903-2_67
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-20464-0
Online ISBN: 978-3-540-39903-2
eBook Packages: Springer Book Archive