Detection of DTI white matter abnormalities in multiple sclerosis patients. - Inria - Institut national de recherche en sciences et technologies du numérique Access content directly
Conference Papers Medical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention Year : 2008

Detection of DTI white matter abnormalities in multiple sclerosis patients.

Abstract

The emergence of new modalities such as Diffusion Tensor Imaging (DTI) is of great interest for the characterization and the temporal study of Multiple Sclerosis (MS). DTI indeed gives information on water diffusion within tissues and could therefore reveal alterations in white matter fibers before being visible in conventional MRI. However, recent studies generally rely on scalar measures derived from the tensors such as FA or MD instead of using the full tensor itself. Therefore, a certain amount of information is left unused. In this article, we present a framework to study the benefits of using the whole diffusion tensor information to detect statistically significant differences between each individual MS patient and a database of control subjects. This framework, based on the comparison of the MS patient DTI and a mean DTI atlas built from the control subjects, allows us to look for differences both in normally appearing white matter but also in and around the lesions of each patient. We present a study on a database of 11 MS patients, showing the ability of the DTI to detect not only significant differences on the lesions but also in regions around them, enabling an early detection of an extension of the MS disease.

Dates and versions

inria-00502709 , version 1 (15-07-2010)

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Olivier Commowick, Pierre Fillard, Olivier Clatz, Simon K Warfield. Detection of DTI white matter abnormalities in multiple sclerosis patients.. International Conference on Medical Image Computing and Computer Assisted Intervention, Sep 2008, New York City, United States. pp.975-82, ⟨10.1007/978-3-540-85988-8_116⟩. ⟨inria-00502709⟩

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