Lior Orbach1,2, Shay Menascu3,4, Chen Hoffmann3,4, Shmuel Miron3, Anat Achiron3,4. 1. Multiple Sclerosis Center, Sheba Medical Center, Tel-Hashomer, Israel. Lior.orbach@gmail.com. 2. Sackler School of Medicine, Tel-Aviv University, Tel-Aviv, Israel. Lior.orbach@gmail.com. 3. Multiple Sclerosis Center, Sheba Medical Center, Tel-Hashomer, Israel. 4. Sackler School of Medicine, Tel-Aviv University, Tel-Aviv, Israel.
Abstract
PURPOSE: The aim of our study is to identify radiological patterns of cortical gray matter atrophy (CGMA) that correlate with disease duration in patients with relapsing-remitting multiple sclerosis (RRMS). METHODS: RRMS patients were randomly selected from the Sheba Multiple Sclerosis (MS) center computerized data registry based on stratification of disease duration up to 10 years. Patients were scanned by 3.0 T (Signa, GE) MRI, using a T1 weighted 3D high resolution, FSPGR, MS protocol. Neurological disability was assessed by the Expanded Disability Status Scale (EDSS). FreeSurfer was used to obtain brain volumetric segmentation and to perform cortical thickness surface-based analysis. Clusters of change in cortical thickness with correlation to disease duration were produced. RESULTS: Two hundred seventy-one RRMS patients, mean ± SD age 33.0 ± 7.0 years, EDSS 1.6 ± 1.2, disease duration 5.0 ± 3.4 years. Cortical thickness analysis demonstrated focal areas of cerebral thinning that correlated with disease duration. Seven clusters accounting for 11.7% of the left hemisphere surface and eight clusters accounting for 10.6% of the right hemisphere surface were identified, with cluster-wise probability of p < 0.002 and p < 0.02, respectively.The clusters included bilateral involvement of areas within the cingulate, precentral, postcentral, paracentral, superior-parietal, superior-frontal gyri and insular cortex. Mean and cluster-wise cortical thickness negatively correlated with EDSS score, p < 0.001, with stronger Spearman rho for cluster-wise measurements. CONCLUSIONS: We identified CGMA patterns in sensitive brain regions which give insight and better understanding of the progression of cortical gray matter loss in relation to dissemination in space and time. These patterns may serve as markers to modulate therapeutic interventions to improve the management of MS patients.
PURPOSE: The aim of our study is to identify radiological patterns of cortical gray matter atrophy (CGMA) that correlate with disease duration in patients with relapsing-remitting multiple sclerosis (RRMS). METHODS: RRMS patients were randomly selected from the Sheba Multiple Sclerosis (MS) center computerized data registry based on stratification of disease duration up to 10 years. Patients were scanned by 3.0 T (Signa, GE) MRI, using a T1 weighted 3D high resolution, FSPGR, MS protocol. Neurological disability was assessed by the Expanded Disability Status Scale (EDSS). FreeSurfer was used to obtain brain volumetric segmentation and to perform cortical thickness surface-based analysis. Clusters of change in cortical thickness with correlation to disease duration were produced. RESULTS: Two hundred seventy-one RRMS patients, mean ± SD age 33.0 ± 7.0 years, EDSS 1.6 ± 1.2, disease duration 5.0 ± 3.4 years. Cortical thickness analysis demonstrated focal areas of cerebral thinning that correlated with disease duration. Seven clusters accounting for 11.7% of the left hemisphere surface and eight clusters accounting for 10.6% of the right hemisphere surface were identified, with cluster-wise probability of p < 0.002 and p < 0.02, respectively.The clusters included bilateral involvement of areas within the cingulate, precentral, postcentral, paracentral, superior-parietal, superior-frontal gyri and insular cortex. Mean and cluster-wise cortical thickness negatively correlated with EDSS score, p < 0.001, with stronger Spearman rho for cluster-wise measurements. CONCLUSIONS: We identified CGMA patterns in sensitive brain regions which give insight and better understanding of the progression of cortical gray matter loss in relation to dissemination in space and time. These patterns may serve as markers to modulate therapeutic interventions to improve the management of MSpatients.
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