Predicting disability progression and cognitive worsening in multiple sclerosis using patterns of grey matter volumes.
Elisa ColatoJonathan StuttersCarmen TurSridar NarayananDouglas Lorne ArnoldClaudia A M Gandini Wheeler-KingshottFrederik BarkhofOlga CiccarelliDeclan T ChardE Ann YehPublished in: Journal of neurology, neurosurgery, and psychiatry (2021)
The disability progression was better predicted by some of the covarying GM regions patterns, than by single regional or whole-brain measures. ICA, which may represent structural brain networks, can be applied to clinical trials and may play a role in stratifying participants who have the most potential to show a treatment effect.