Hemodynamic biomarkers in symptomatic intracranial atherosclerotic stenosis: evidence boundaries and research pathways from prognostic stratification to treatment-effect prediction
Year: 2026
Type: review
Abstract: Symptomatic intracranial atherosclerotic stenosis (sICAS) has traditionally been stratified primarily according to angiographic stenosis severity. However, this anatomical approach does not adequately capture the heterogeneity of ischemic mechanisms, distal hemodynamic compromise, or treatment response, prompting increasing interest in hemodynamic biomarkers for mechanism-based risk stratification. In this review, we propose an evidence framework that evaluates these biomarkers across measurement validity, mechanistic coherence, prognostic association, treatment-effect prediction, external validation, and clinical utility, while integrating lesion function, distal perfusion, compensatory capacity, and parallel embolic and perforator pathways. Although several measures, particularly distal hypoperfusion and borderzone infarction, have shown prognostic value, the evidence identified in this review remains dominated by single-center studies, platform-specific definitions, and incompletely validated thresholds. Among the completed direct sICAS studies identified, we found no prospective validation of a hemodynamic biomarker as a treatment-effect modifier. Translation requires standardized measurement, prespecified biomarker definitions, and external validation. Claims of treatment-effect modification additionally require prespecified interaction analyses within appropriate treatment comparisons, preferably randomized. Biomarker-guided treatment selection should be supported by reliable estimates of absolute benefits and harms and evidence of clinical utility.
Source: Frontiers in Neurology
Language: English
Subfield: Cardiology and Cardiovascular Medicine
Field: Medicine
Domain: Health Sciences
Open Access status: gold
Estimated APC paid: $3,801
Funder: Shenzhen Research Foundation
Award: G1145696711
OpenAlex ID: W7221879680
