Quantifying Brain Health in Acute Ischemic Stroke Through Effective Reserve

Area of Science:

• Neurology
• Radiology
• Biostatistics

Background:

• Brain health assessment often overlooks pre-existing pathology.
• Quantifying brain reserve is crucial for predicting neurological outcomes.
• Existing metrics may not fully capture an individual's resilience to brain injury.

Purpose of the Study:

• To develop and validate a novel measure of brain health, termed effective reserve (eR).
• To incorporate pre-existing pathological markers into the assessment of brain reserve.
• To evaluate the association between eR and clinical outcomes in ischemic stroke patients.

Main Methods:

• Analysis of two retrospective ischemic stroke cohorts (GASROS and SALVO) with neuroimaging and clinical data.
• Automated extraction of white matter hyperintensity (WMHv), brain, and intracranial volumes to calculate brain parenchymal fraction (BPF).
• Modeling of effective reserve (eR) using age, WMHv, and brain volume or BPF, with model comparison via Bayes Information Criterion (BIC).

Main Results:

• Effective reserve (eR) was modeled, with brain volume demonstrating superior performance over BPF (path coefficients: -0.67 vs -0.48, p < 0.001).
• A significant inverse association was observed between eR and 90-day modified Rankin Scores (mRS) in both cohorts.
• Stratification by eR quartiles revealed consistently worse outcomes in lower reserve groups across both GASROS and SALVO studies.

Conclusions:

• The concept of effective reserve (eR) offers a clinically translatable metric for brain health.
• Higher effective reserve is strongly associated with better neurological outcomes post-stroke.
• eR serves as a valuable indicator of brain resilience and protective capacity.