Associations between subcortical gray matter volume and motor performance post-stroke are unclear, partly because many stroke MRI studies are underpowered. Potential influences of the severity of motor impairment, lesion laterality, and time since stroke on these associations is also unknown.
Here, we addressed these questions using a large dataset (n=629) from the ENIGMA Stroke Recovery working group (http://enigma.usc.edu). Regression analyses examined brain volumes as predictors of motor scores. ENIGMA FreeSurfer protocols extracted volumes from 16 subcortical regions on T1-weighted MRIs; segmentations were manually quality controlled. Motor scores were calculated as a percentage of the maximum possible score (100% = no impairment). Covariates (e.g., age, sex, intracranial volume) were modeled. Statistical significance was assessed nonparametrically by permutation. Separate analyses were performed, stratifying by motor severity and time since stroke. Each analysis was also subdivided by lesioned hemisphere.
The motor severity analysis (Table 1A) used subgroups of mild (66.7-99.9%), moderate (33.3-66.6%), and severe (0-33.2%). Significant associations were found for mild and moderate, but not severe, stroke; only the left hemisphere stroke group showed further significant results.
The time since stroke analysis (Table 1B) used subgroups of acute (<1 month), subacute (1-6 months), and chronic (>6 months). Significant associations were found in chronic stroke, but not acute, subacute. Left versus right hemisphere lesions generated different results in chronic stroke.
Overall, these results show that the most significant associations between subcortical volumes and motor outcomes are in chronic mild-to-moderate stroke. Stroke subgroups may recover via disparate mechanisms; establishing biomarkers of impairment and disability across stroke subgroups may be useful for clinical trials.