Scientific Reports (Feb 2021)

Exploring the predictive value of lesion topology on motor function outcomes in a porcine ischemic stroke model

  • Kelly M. Scheulin,
  • Brian J. Jurgielewicz,
  • Samantha E. Spellicy,
  • Elizabeth S. Waters,
  • Emily W. Baker,
  • Holly A. Kinder,
  • Gregory A. Simchick,
  • Sydney E. Sneed,
  • Janet A. Grimes,
  • Qun Zhao,
  • Steven L. Stice,
  • Franklin D. West

DOI
https://doi.org/10.1038/s41598-021-83432-5
Journal volume & issue
Vol. 11, no. 1
pp. 1 – 15

Abstract

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Abstract Harnessing the maximum diagnostic potential of magnetic resonance imaging (MRI) by including stroke lesion location in relation to specific structures that are associated with particular functions will likely increase the potential to predict functional deficit type, severity, and recovery in stroke patients. This exploratory study aims to identify key structures lesioned by a middle cerebral artery occlusion (MCAO) that impact stroke recovery and to strengthen the predictive capacity of neuroimaging techniques that characterize stroke outcomes in a translational porcine model. Clinically relevant MRI measures showed significant lesion volumes, midline shifts, and decreased white matter integrity post-MCAO. Using a pig brain atlas, damaged brain structures included the insular cortex, somatosensory cortices, temporal gyri, claustrum, and visual cortices, among others. MCAO resulted in severely impaired spatiotemporal gait parameters, decreased voluntary movement in open field testing, and higher modified Rankin Scale scores at acute timepoints. Pearson correlation analyses at acute timepoints between standard MRI metrics (e.g., lesion volume) and functional outcomes displayed moderate R values to functional gait outcomes. Moreover, Pearson correlation analyses showed higher R values between functional gait deficits and increased lesioning of structures associated with motor function, such as the putamen, globus pallidus, and primary somatosensory cortex. This correlation analysis approach helped identify neuroanatomical structures predictive of stroke outcomes and may lead to the translation of this topological analysis approach from preclinical stroke assessment to a clinical biomarker.