Oral Presentation Australian and New Zealand Stroke Organisation Conference 2025

A systematic review of early neuroimaging and neurophysiological biomarkers of long-term mobility recovery post-stroke. (121522)

Cristina Levy 1 2 , Emily Dalton 1 3 , Jennifer Ferris 4 , Leonid Churilov 5 , Bruce Campbell 5 , Amy Brodtmann 5 6 , Sandra Brauer 7 , Kate Hayward 1 5
  1. Department of Physiotherapy, University of Melbourne, Parkville, Australia
  2. Department of Physiotherapy, Royal Melbourne Hospital, Parkville, Australia
  3. Department of Occupational Therapy, Royal Melbourne Hospital, Parkville, Australia
  4. Gerontology Research Centre, Simon Fraser University, Vancouver, Canada
  5. Department of Medicine and Neurology, Royal Melbourne Hospital, University of Melbourne, Parkville, Australia
  6. Department of Neurosciences, Monash University, Clayton, Australia
  7. Department of Physiotherapy, University of Queensland, Brisbane, Australia

Background/Aim: Early stroke recovery biomarkers may improve prognostication of long-term mobility post-stroke. Our aim was to examine early neuroimaging and neurophysiological biomarkers of long-term mobility recovery post-stroke.

Methods: MEDLINE/EMBASE were systematically searched. Eligible cohort studies reported the prognostic capacity of early (≤14days post-stroke) neuroimaging or neurophysiological biomarkers for mobility outcomes (impairment/activity) at a future time-point (≥14days but ≤24months post-stroke). Statistical analysis methods were categorised as associative, discriminative or validated predictive.

Results: Fourteen studies (biomarker measurement median 6.9(1.8-14) days) were included. Sixty-seven biomarker analyses were completed: 52 neuroimaging (most common lesion location n=22) and 15 neurophysiological (most common motor evoked potential status n=8). Most analyses related to 3-months post-stroke follow-up (n=31). Forty-one impairment (most common Fugl Meyer Lower Limb n=20) and 26 activity (most common Functional Ambulation Category n=17) measures were used. Analyses were largely associative (n=65, 97%, all high risk of bias due to confounding factors and low risk of bias for outcome measurement). Eighteen (27.6%) neuroimaging (most common lesion location n=7) and six (9.2%) neurophysiological (most common tibial nerve somatosensory evoked potential amplitude parameters n=4) biomarkers were significantly associated (p≤0.05) with their respective mobility outcome. One internally validated neural network model using magnetic resonance imaging data (low risk of bias) well-discriminated (AUC 0.83) independent walking ability at 6-months post-stroke.

Conclusion: Few promising early neuroimaging/neurophysiological biomarkers of mobility recovery post-stroke were identified. This may suggest that biomarkers measured early are not prognostic of long-term mobility outcomes, or that we are yet to identify the right biomarkers.