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Abstract #3581

Automatic Segmentation of Diffusely Abnormal White Matter in Multiple Sclerosis using Fuzzy C-means Clustering

Tigris Joseph1,2, Sharada Balaji1, Shannon Kolind1,2,3,4, Guojun Zhao3, Peng Sun5, Robert Carruthers3, Alice Schabas3, Ana-Luiza Sayao3, Virginia Devonshire3, Roger Tam4,6, G. R. Wayne Moore2,3,7, David K. B. Li3,4, Anthony Traboulsee3, Irene Vavasour2,4, and Cornelia Laule1,2,4,7
1Physics and Astronomy, University of British Columbia, Vancouver, BC, Canada, 2International Collaboration on Repair Discoveries, University of British Columbia, Vancouver, BC, Canada, 3Medicine, University of British Columbia, Vancouver, BC, Canada, 4Radiology, University of British Columbia, Vancouver, BC, Canada, 5Imaging Physics, MD Anderson Cancer Center, Houston, TX, United States, 6School of Biomedical Engineering, University of British Columbia, Vancouver, BC, Canada, 7Pathology & Laboratory Medicine, University of British Columbia, Vancouver, BC, Canada

Synopsis

Keywords: Multiple Sclerosis, Multiple Sclerosis, Diffusely Abnormal White Matter, Fuzzy Clustering, Myelin Water Imaging, Brain, Myelin, T2

Motivation: Diffusely abnormal white matter (DAWM) occurs in ~25% of multiple sclerosis patients. Currently there is no consensus on how to best automatically segment DAWM which is difficult to identify and quantify.

Goal(s): Use fuzzy c-means clustering to segment DAWM.

Approach: A data set from DAWM+ patients (n=40) was used to train a clustering algorithm on proton-density (PDw) and T2-weighted (T2w) images. This algorithm was tested on 9 patients visually identified as DAWM+ and 51 patients visually identified as DAWM–.

Results: Clustering segmented PDw/T2w hyperintensities in DAWM+ test subjects. Patients visually identified as DAWM– also had regions segmented as DAWM.

Impact: Unsupervised clustering could provide an unbiased approach to automatically segment diffusely abnormal white matter (DAWM) in multiple sclerosis patients in vivo. In this study, the subtle hyperintensities associated with DAWM were segmented on proton density and T2-weighted images.

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Abstract

Keywords