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Texture Analysis of T2-Weighted MR Images to Assess Acute Inflammation in Brain MS Lesions

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Michoux, Nicolas [UCL] Guillet, Alain [UCL] Rommel, Denis [UCL] Mazzamuto, Giosué [UCL] Sindic, Christian [UCL] Duprez, Thierry [UCL] Lenglet, Christophe

Brain blood barrier breakdown as assessed by contrast-enhanced (CE) T1-weighted MR imaging is currently the standard radiological marker of inflammatory activity in multiple sclerosis (MS) patients. Our objective was to evaluate the performance of an alternative model assessing the inflammatory activity of MS lesions by texture analysis of T2-weighted MR images. Twenty-one patients with definite MS were examined on the same 3.0T MR system by T2-weighted, FLAIR, diffusion-weighted and CE-T1 sequences. Lesions and mirrored contralateral areas within the normal appearing white matter (NAWM) were characterized by texture parameters computed from the gray level co-occurrence and run length matrices, and by the apparent diffusion coefficient (ADC). Statistical differences between MS lesions and NAWM were analyzed. ROC analysis and leave-one-out cross-validation were performed to evaluate the performance of individual parameters, and multi-parametric models using linear discriminant analysis (LDA), partial least squares (PLS) and logistic regression (LR) in the identification of CE lesions. ADC and all but one texture parameter were significantly different within white matter lesions compared to within NAWM (p < 0.0167). Using LDA, an 8-texture parameter model identified CE lesions with a sensitivity Se = 70% and a specificity Sp = 76%. Using LR, a 10-texture parameter model performed better with Se = 86% / Sp = 84%. Using PLS, a 6-texture parameter model achieved the highest accuracy with Se = 88% / Sp = 81%. Texture parameter from T2-weighted images can assess brain inflammatory activity with sufficient accuracy to be considered as a potential alternative to enhancement on CE T1-weighted images

Document type Article de périodique (Journal article) – Article de recherche
Access type Accès libre
Publication date 2015
Language Anglais
Journal information "PLoS One" - Vol. 10, no. 12, p. e0145497 [1-13] (2015)
Peer reviewed yes
Publisher Public Library of Science ((United States) San Francisco, CA)
issn 1932-6203
e-issn 1932-6203
Publication status Publié
Affiliations UCL - SSH/LIDAM/SMCS - Support en méthodologie et calcul statistique (plate-forme technologique)
UCL - SSS/IREC - Institut de recherche expérimentale et clinique
UCL - (SLuc) Service de radiologie
UCL - (SLuc) Service de neurologie
CISM:CECI - CISM:CECI
UCL - SSS/IONS/NEUR - Clinical Neuroscience
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Bibliographic reference Michoux, Nicolas ; Guillet, Alain ; Rommel, Denis ; Mazzamuto, Giosué ; Sindic, Christian ; et. al. Texture Analysis of T2-Weighted MR Images to Assess Acute Inflammation in Brain MS Lesions. In: PLoS One, Vol. 10, no. 12, p. e0145497 [1-13] (2015)
Permanent URL http://hdl.handle.net/2078.1/170395