title: Novel image processing techniques to better understand white matter disruption in multiple sclerosis.
abstract: In Multiple Sclerosis (MS) patients, conventional magnetic resonance imaging (MRI) shows a pattern of white matter (WM) disruption but may also overlook some WM damage. Diffusion tensor MRI (DT-MRI) can provide important in-vivo information about fiber direction that is not provided by conventional MRI. The geometry of diffusion tensors can quantitatively characterize the local structure in tissues. The integration of both conventional MRI and DT-MRI measures together with connectivity-based regional assessment provide a better understanding of the nature and the location of WM abnormalities. Image processing and visualization techniques have been developed and applied to study conventional MRI and DT-MRI of MS patients. These include methods of: Image Segmentation for identifying the different areas of the brain as well as to discriminate normal from abnormal WM, Computerized Atlases, which include structural information obtained from a set of subjects, and Tractographies which can aid in the delineation of WM fiber tracts by tracking connected diffusion tensors. These new techniques hold out the promise of improving our understanding of WM architecture and its disruption in diseases such as MS. In the present study, we review the work that has been done in the development of these techniques and illustrate their applications.
authors.affiliation: Computational Radiology Laboratory, Department of Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA 02115, USA. daniel@bwh.harvard.edu
authors.forename: Daniel
authors.initials: D
authors.lastname: Goldberg-Zimring
authors.forename: Simon K
authors.initials: SK
authors.lastname: Warfield
mesh_terms: D001921:Brain / Q000473:pathology*; D038524:Diffusion Magnetic Resonance Imaging; D006801:Humans; D008279:Magnetic Resonance Imaging; D009103:Multiple Sclerosis / Q000473:pathology*; D009413:Nerve Fibers, Myelinated / Q000473:pathology*