title: Distinct patterns of active and non-active plaques using texture analysis on brain NMR images in multiple sclerosis patients: preliminary results.
abstract: The benefits of texture analysis of magnetic resonance images have been assessed in multiple sclerosis (MS) patients. Out of thirty-two lesions identified in eight MS patients, nine were considered active, judging from their gadolinium uptake. Texture analysis allowed to obtain forty-two characterizing parameters for each lesion. Using discriminant analysis as a statistical method allowed to classify the lesions into two groups: active or non-active. An attempt to classify their level of activity by using only co-occurrence matrices was unsuccessful. Alternately, the same type of analysis performed on runlength analysis criteria allowed the accurate classification of 88% of active lesions and 96% of non-active lesions. Using incremental discriminate analysis can reduce the number of useful parameters. This method showed that among the 42 parameters, 8 only were highly significant and permitted an accurate classification. Five of these parameters are runlength parameters, and three others are more directly related to the global distribution. The main interest of runlength parameters is that they allowed to demonstrate that the lesion structure was different in active and non-active plaques. This preliminary work suggests that using texture analysis could be of interest in the follow-up of MS patients because it provides an opportunity to identify active lesions without frequent gadolinium injections.
authors.affiliation: Institut de Physique Biologique (UPRES-A 7004 CNRS) Strasbourg, France. yu@alsace.u-strabg.fr
authors.forename: O
authors.initials: O
authors.lastname: Yu
authors.forename: Y
authors.initials: Y
authors.lastname: Mauss
authors.forename: G
authors.initials: G
authors.lastname: Zollner
authors.forename: I J
authors.initials: IJ
authors.lastname: Namer
authors.forename: J
authors.initials: J
authors.lastname: Chambron
mesh_terms: D000328:Adult; D001921:Brain / Q000473:pathology*; D016002:Discriminant Analysis; D005260:Female; D005682:Gadolinium / Q000378:metabolism; D006801:Humans; D008279:Magnetic Resonance Imaging / Q000379:methods / Q000706:statistics & numerical data; D008297:Male; D009103:Multiple Sclerosis / Q000473:pathology*; D012189:Retrospective Studies; D012680:Sensitivity and Specificity
chemical_list: D005682:Gadolinium