Diffusion MRI abnormalities detection with orientation distribution functions: A multiple sclerosis longitudinal study |
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Affiliation: | 1. National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, United States;2. Department of Neurology, University of Maryland, Baltimore, MD, United States;3. National Cancer Institute, National Institutes of Health, Bethesda, MD, United States;4. FMRIB Centre, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK;5. Department of Psychiatry, University of Michigan, Ann Arbor, MI, United States |
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Abstract: | We propose a new algorithm for the voxelwise analysis of orientation distribution functions between one image and a group of reference images. It relies on a generic framework for the comparison of diffusion probabilities on the sphere, sampled from the underlying models. We demonstrate that this method, combined to dimensionality reduction through a principal component analysis, allows for more robust detection of lesions on simulated data when compared to classical tensor-based analysis. We then demonstrate the efficiency of this pipeline on the longitudinal comparison of multiple sclerosis patients at an early stage of the disease: right after their first clinically isolated syndrome (CIS) and three months later. We demonstrate the predictive value of ODF-based scores for the early detection of lesions that will appear or heal. |
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Keywords: | Diffusion MRI Patient to controls comparison Orientation distribution functions |
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