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Application of Graph Theoretic measures for assessing efficacy of Stroke Rehabilitation
Publisher: IEEE
All Authors
Abstract:
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 su...
Date of Conference: 18-23 June 2023
Date Added to IEEE Xplore: 02 August 2023
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