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Proceedings Paper

Multiple sclerosis lesions evolution in patients with clinically isolated syndrome
Author(s): A. Crimi; O. Commowick; J. C. Ferre; A. Maarouf; G. Edan; C. Barillot
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Paper Abstract

Multiple sclerosis (MS) is a disease with heterogeneous evolution among the patients. Some classifications have been carried out according to either the clinical course or the immunopathological profiles. Epidemiological data and imaging are showing that MS is a two-phase neurodegenerative inflammatory disease. At the early stage it is dominated by focal inflammation of the white matter (WM), and at a later stage it is dominated by diffuse lesions of the grey matter and spinal cord. A Clinically Isolated Syndrome (CIS) is a first neurological episode caused by inflammation/demyelination in the central nervous system which may lead to MS. Few studies have been carried out so far about this initial stage. Better understanding of the disease at its onset will lead to a better discovery of pathogenic mechanisms, allowing suitable therapies at an early stage. We propose a new data processing framework able to provide an early characterization of CIS patients according to lesion patterns, and more specifically according to the nature of the inflammatory patterns of these lesions. The method is based on a two layers classification. Initially, the spatio-temporal lesion patterns are classified using a tensor-like representation. The discovered lesion patterns are then used to identify group of patients and their correlation to 15 months follow-up total lesion loads (TLL), which is so far the only image-based figure that can potentially infer future evolution of the pathology. We expect that the proposed framework can infer new prospective figures from the earliest imaging sign of MS since it can provide a classification of different types of lesion across patients.

Paper Details

Date Published: 13 March 2013
PDF: 8 pages
Proc. SPIE 8669, Medical Imaging 2013: Image Processing, 86690I (13 March 2013); doi: 10.1117/12.2006647
Show Author Affiliations
A. Crimi, INRIA Rennes (France)
O. Commowick, INRIA Rennes (France)
J. C. Ferre, Ctr. Hospitalier Univ. de Rennes (France)
A. Maarouf, Univ. Hospital Reims (France)
CRMBM, CNRS, Aix-Marseille Univ. (France)
G. Edan, Ctr. Hospitalier Univ. de Rennes (France)
C. Barillot, INRIA Rennes (France)

Published in SPIE Proceedings Vol. 8669:
Medical Imaging 2013: Image Processing
Sebastien Ourselin; David R. Haynor, Editor(s)

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