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

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

doi:10.1371/journal.pone.0145497

Nicolas Michoux, Christian Sindic + Show 5 more

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https://doi.org/10.1371/journal.pone.0145497

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Abstract

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.

Highlights

Multiple Sclerosis (MS) is a chronic autoimmune inflammatory disease of the central nervous system featured by the onset of multifocal white matter (WM) inflammatory foci resulting in irreversible parenchymal damage
Areas Under the ROC Curves (AUC) values, sensitivity and specificity of selected cut-offs are given in Table 3, while receiver operating characteristic (ROC) curves are displayed on Fig 2
The first observation drawn from the study was that all but one of the texture parameters were significantly different within white matter (WM) lesions than within normal appearing white matter (NAWM) as seen by visual examination of the T2-W images

Summary

Introduction

Multiple Sclerosis (MS) is a chronic autoimmune inflammatory disease of the central nervous system featured by the onset of multifocal white matter (WM) inflammatory foci resulting in irreversible parenchymal damage. Though diffuse involvement of the CNS with the MS disease process has been highlighted by histopathological studies, acute inflammatory foci occur, which may be assessed either by the a posteriori demonstration of lesion size enlargement and/or de novo lesion appearance on serial T2-W images at the chronic phase, or by contemporary contrast-enhancement on T1-W images of a single examination at acute phase [2] In the latter condition, the BBB breakdown allows leakage of the gadolinium chelates from the vascular compartment to intercellular interstitium resulting in a local T1 time shortening of adjacent spins producing hyper signal intensity on CE T1-W images. Despite recent technical advances in DW and diffusion tensor imaging, changes in diffusion parameters in MS remain equivocal e.g. regarding the link between ADC values and inflammation within CE lesions on T1 images [3,4,5]

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