Application of Graph Theoretic measures for assessing efficacy of Stroke Rehabilitation

One of the challenges in stroke rehabilitation is to identify bio-markers that correlate with amelioratory changes in the recovery of brain function that can be verified by a clinician. For strokes related to upper extremity, clinicians use Fugl Meyer Assessment - Upper Extremity (FMA-UE) score for verification. We hypothesize that even before clinical measures of function recovery (FMA-UE) show facilitatory changes, structural and functional changes in the brain connectome indicate early changes in stroke patients. Toward establishing such early bio-markers of rehabilitation related changes in the brain plasticity, we propose to use graph theoretic measures on the structural (SC) and functional connectivity (FC) matrices. We used longitudinal multi-modal neuroimaging data acquired within 1 to 6 months of the onset of stroke and after 3 months of rehabilitation for 15 acute ischemic stroke subjects with deficit in motor function of the upper extremity. We compared structural and functional network properties of the brain between the baseline (pre-) and post-rehabilitation stages. While significant changes are observed in the nodal properties, global network properties did not reach statistical significance. However, when correlation patterns across pre-, post-rehabilitation, and healthy controls are investigated, some interesting patterns emerge that are not captured by statistical analysis as well as the clinical assessment scores. Global functional network properties of patients post-rehabilitation resemble that of a healthy control group, than that of pre-rehabilitation (Baseline). We also observed that greater the change in normalized percent change in FMA-UE scores, closer are the correlation maps of global graph metrics of FC to that of the healthy controls. We did not observe any such resemblance in correlation patterns in structural connectivity (SC) of pre- and post-rehabilitation with that of the healthy control group. Overall, the results point out the suitability of using graph metrics for characterizing early markers of functional change in the brain regions.