Covarying patterns of white matter lesions and cortical atrophy predict progression in early MS

Abstract

ObjectiveWe applied longitudinal 3T MRI and advanced computational models in 2 independent cohorts of patients with early MS to investigate how white matter (WM) lesion distribution and cortical atrophy topographically interrelate and affect functional disability.MethodsClinical disability was measured using the Expanded Disability Status Scale Score at baseline and at 1-year follow-up in a cohort of 119 patients with early relapsing-remitting MS and in a replication cohort of 81 patients. Covarying patterns of cortical atrophy and baseline lesion distribution were extracted by parallel independent component analysis. Predictive power of covarying patterns for disability progression was tested by receiver operating characteristic analysis at the group level and support vector machine for individual patient outcome.ResultsIn the study cohort, we identified 3 distinct distribution types of WM lesions (cerebellar, bihemispheric, and left lateralized) that were associated with characteristic cortical atrophy distributions. The cerebellar and left-lateralized patterns were reproducibly detected in the second cohort. Each of the patterns predicted to different extents, short-term disability progression, whereas the cerebellar pattern was associated with the highest risk of clinical worsening, predicting individual disability progression with an accuracy of 88% (study cohort) and 89% (replication cohort), respectively.ConclusionThese findings highlight the role of distinct spatial distribution of cortical atrophy and WM lesions predicting disability. The cerebellar involvement is shown as a key determinant of rapid clinical deterioration.

Network Damage Predicts Clinical Worsening in Multiple Sclerosis

“…This is not the first study that highlights a significant contribution of network GM measures to MS prognosis. 14,15 Taken together, these results suggest that the assessment of specific system involvement may convey more clinically relevant pieces of information than global MRI measures in these patients.…”

“…As clinical outcomes, we selected the EDSS score, the most widely validated MS disability measure, which was used in all prognostic studies, 6 , 7 , 9 - 12 , 14 , 15 and evolution to SPMS, that is associated with a poor prognosis, mostly because of the limited DMT effect in these patients. During the 6.4-year follow-up, 45% of patients had a worsening of disability and 16% of patients with RRMS evolved to SPMS.…”

“…Prediction models of both clinical worsening and SPMS conversion were produced using RF methodology, a machine-learning technique that is less sensitive to false discoveries than classic multivariate logistic models, 36 being based on the use of different bootstrap samples of data and different subsets of predictors to construct thousands of decision trees, on which hypotheses are tested. 36 As clinical outcomes, we selected the EDSS score, the most widely validated MS disability measure, which was used in all prognostic studies, 6,7,[9][10][11][12]14,15 and evolution to SPMS, that is associated with a poor prognosis, mostly because of the limited DMT effect in these patients. During the 6.4-year followup, 45% of patients had a worsening of disability and 16% of patients with RRMS evolved to SPMS.…”

“…Studies of structural network abnormalities, which decomposed WM lesions and GM maps into distinct patterns covarying across subjects, revealed that a stronger network disruption in these 2 compartments was correlated with severe disability 13 and was able to predict the subsequent disease course. 14 , 15 Resting-state (RS) functional connectivity (FC) network studies showed complex abnormalities in patients with MS, 16 , 17 characterized by an early RS FC increase and RS FC decrease in more advanced phases. Abnormal within- and between-network RS FC contributed to explain MS phenotypic variability and cognitive deficits 16 , 18 and was able to predict clinical deterioration at medium term, 19 , 20 whereas abnormal FC during a psychological stress functional (fMRI) paradigm contributed to explain future GM atrophy.…”

Sex-specific signatures of intrinsic hippocampal networks and regional integrity underlying cognitive status in multiple sclerosis

“…This and other aspects of sex-specific differences in the hippocampal organization might be addressed in target works. As the spatial location of lesions predetermines the patterns of GM pathology, 72 identification of sex-specific responses of hippocampal networks and regional integrity to the spatial distribution of intrahippocampal lesions might be of interest.…”