Microvascular plasticity in stroke recovery: Longitudinal snapshots, network statistical analysis, and dynamics

Abstract

AbstractThis research article quantitatively investigates neuro-microvascular network remodeling dynamics following stroke using a novel in vivo two-photon angiography (cubic millimeter volume, weekly snapshots) and high throughput (thousands of connected capillaries) vascular vectorization method. The results suggest distinct temporal patterns of cere-brovascular plasticity, with acute remodeling peaking at one week post-stroke. The network architecture then gradually stabilizes, returning to a new steady state after four weeks. These findings align with previous literature on neuronal plasticity, highlighting the correlation between neuronal and neurovascular remodeling. Quantitative analysis of neurovascular networks using length- and strand-based statistical measures reveals intri-cate changes in network anatomy and topology. The distance and strand-length statistics show significant alterations, with a peak of plasticity observed at one week post-stroke, followed by a gradual return to baseline. The orientation statistic plasticity peaks at two weeks, gradually approaching the (conserved across subjects) stroke signature. The underlying mechanism of the vascular response (angiogenesis vs. tissue deformation), however, is yet unelucidated, requiring network registration advancements. Overall, the combination of two-photon angiography, vectorization, reconstruction/visualization, and statistical analysis enables both qualitative and quantitative assessments of neu-rovascular remodeling dynamics, demonstrating an impactful method for investigating neuro-microvascular network disorders and the therapeutic modes of action thereof. Understanding the timing and nature of neurovascular remodeling allows for optimized interventions, including personalized medicine for stroke rehabilitation. Additionally, the evaluation of pharmaceutical interventions using these tools may facilitate targeted drug development. Furthermore, neurovascular coupling dynamics have implications for neurodegenerative diseases, brain aging, and the field of brain-computer interfaces.