Browsing by Author "Rocca, M.A. (34973365100)"

Objective: To assess the correlation between cognitive impairment and overall vs regional CNS damage, quantified using conventional and diffusion tensor (DT) MRI tractography in multiple sclerosis (MS). Methods: Brain dual-echo, T1-weighted, and DT MRI data were acquired from 82 patients with MS. DT tractography was used to produce maps of white matter (WM) tracts involved in cognition. The sensory thalamocortical projections and optic radiations were studied as "control"WMtracts. The contribution of global brain damage (T2 lesion volume, normalized brain volume, gray matter [GM] volume, WM volume, DT MRI measures of normal-appearing WM and GM damage) and damage to selected WM tracts to overall cognitive impairment and to impairment at individual neuropsychological tests was assessed using a random forest (RF) analysis. Results: Thirty-three patients had cognitive impairment. The majority of MRI measures differed significantly between cognitively impaired and cognitively preserved (CP) patients. Significant correlations were found between performance in the majority of neuropsychological tests and global or regional brain damage (r ranging from -0.60 to 0.57). The RF analysis showed a high performance in classifying cognitively impaired vs CP patients, with a classification (C)-index = 76.8%, as well as in classifying patients' impairment in individual neuropsychological tests (Cindex between 75.6% and 86.6%). Measures of lesional damage in cognitive-related tracts, rather than measures of normal- appearingWMdamage in the same tracts or global brain/WM/GM damage, resulted in the highest classification accuracy. Conclusions: Lesions in strategic brain WM tracts contribute to cognitive impairment in MS through a multisystem disconnection syndrome. Copyright © 2012 by AAN Enterprises, Inc.

BACKGROUND AND PURPOSE: The structural MR imaging correlates of cognitive impairment in multiple sclerosis are still debated. This study assessed lesional and atrophy measures of white matter and gray matter involvement in patients with MS acquired in 7 European sites to identify the MR imaging variables most closely associated with cognitive dysfunction. MATERIALS AND METHODS: Brain dual-echo, 3D T1-weighted, and double inversion recovery scans were acquired at 3T from 62 patients with relapsing-remitting MS and 65 controls. Patients with at least 2 neuropsychological tests with abnormal findings were considered cognitively impaired. Focal WM and cortical lesions were identified, and volumetric measures from WM, cortical GM, the hippocampus, and deep GM nuclei were obtained. Age- and site-adjusted models were used to compare lesion and volumetric MR imaging variables between patients with MS who were cognitively impaired and cognitively preserved. A multivariate analysis identified MR imaging variables associated with cognitive scores and disability. RESULTS: Twenty-three patients (38%) were cognitively impaired. Compared with those with who were cognitively preserved, patients with MS with cognitive impairment had higher T2 and T1 lesion volumes and a trend toward a higher number of cortical lesions. Significant brain, cortical GM, hippocampal, deepGMnuclei, andWMatrophy was found in patients with MS with cognitive impairment versus those who were cognitively preserved. Hippocampal and deep GM nuclei atrophy were the best predictors of cognitive impairment, whileWM atrophy was the best predictor of disability. CONCLUSIONS: Hippocampal and deep GM nuclei atrophy are key factors associated with cognitive impairment in MS. These MR imaging measures could be applied in a multicenter context, with cognition as clinical outcome.

BACKGROUND AND PURPOSE: In MS, the relation between clinical and MR imaging measures is still suboptimal. We assessed the correlation of disability and specific impairment of the clinical functional system with overall and regional CNS damage in a large cohort of patients with MS with different clinical phenotypes by using a random forest approach. MATERIALS AND METHODS: Brain conventional MR imaging and DTI were performed in 172 patients with MS and 46 controls. Cervical cord MR imaging was performed in a subgroup of subjects. To evaluate whether MR imaging measures were able to correctly classify impairment in specific clinical domains, we performed a random forest analysis. RESULTS: Between-group differences were found for most of the MR imaging variables, which correlated significantly with clinical measures (r ranging from -0.57 to 0.55). The random forest analysis showed a high performance in identifying impaired versus unimpaired patients, with a global error between 7% (pyramidal functional system) and 31% (Ambulation Index) in the different outcomes considered. When considering the performance in the unimpaired and impaired groups, the random forest analysis showed a high performance in identifying patients with impaired sensory, cerebellar, and brain stem functions (error below 10%), while it performed poorly in defining impairment of visual and mental systems (error of 91% and 70%, respectively). In analyses with a good level of classification, for most functional systems, damage of the WM fiber bundles subserving their function, measured by using DTI tractography, had the highest classification power. CONCLUSIONS: Random forest analysis, especially if applied to DTI tractography data, is a valuable approach, which might contribute to overcoming the MS clinical - MR imaging paradox.