Early Neurovascular Decoupling Trajectories After Revascularization in Acute Ischemic Stroke

Background: Recanalization therapy is the standard treatment for acute ischemic stroke (AIS), yet patient outcomes remain highly heterogeneous. The underlying mechanisms of this variability are not fully understood. Neurovascular coupling (NVC), the tight link between neural activity and cerebral blood flow, is fundamental for brain function. Its disruption (neurovascular decoupling) after stroke is hypothesized to be a key determinant of recovery, but its dynamic early trajectory and predictive value for long-term functional recovery are poorly characterized. Purpose: This observational study aims to delineate the early trajectory of neurovascular decoupling following endovascular thrombectomy in AIS patients and to investigate its association with long-term functional outcome. We seek to construct a single composite biomarker by integrating multimodal data, and to evaluate its predictive value for 90-day recovery. Methods: A prospective cohort of AIS patients who undergo successful endovascular thrombectomy will be enrolled. Multimodal monitoring will be performed at specific early time points: within Days 1-3 and at Day 7 post-procedure. Assessments include: Transcranial Doppler (TCD) for cerebral hemodynamics, Electroencephalography (EEG) for neural activity, and F-wave studies for spinal motoneuron excitability. Clinical severity will be assessed using the National Institutes of Health Stroke Scale (NIHSS) concurrently. The primary outcome is the early trajectory of a composite neurovascular decoupling index. The key predictive relationship between this trajectory and 90-day functional status (assessed using the modified Rankin Scale, mRS) will be evaluated. Significance: This study will provide novel insights into the early neurophysiological changes following successful thrombectomy. By defining the trajectory of neurovascular decoupling in the critical first week and linking it to long-term function, the findings may contribute to the development of early predictive models and guide personalized rehabilitation strategies.