Digital Angiography-Derived Fractional Flow Assessment for Intracranial Stenosis

Intracranial atherosclerotic stenosis (ICAS) is a major cause of ischemic stroke, representing ~15% of cases in Western populations and up to 46.6% in Asia. Even with intensive medical therapy, annual stroke recurrence remains high (7.2-20%), prompting exploration of additional treatment strategies. Early trials such as SAMMPRIS and VISSIT suggested worse outcomes with stenting compared with aggressive medical therapy, largely due to concerns over operator experience, patient selection, and timing. Subsequent analyses showed that patients with hemodynamic compromise-such as watershed infarction and poor collaterals-have recurrence rates up to 37%, underscoring the central role of impaired cerebral perfusion.

Although more recent studies (CASSISS, BASIS) demonstrated that endovascular therapy may be safe and effective in carefully selected patients, current ICAS assessment relies primarily on stenosis severity, which correlates only weakly with true hemodynamic impairment and is insufficient for accurate risk stratification. Because symptoms arise principally from reduced perfusion, physiologic evaluation is essential.

Fractional flow reserve (FFR) is the gold standard for assessing coronary lesion significance and guiding intervention through translesional pressure gradients. Attempts to translate this approach to ICAS using invasive pressure wires have shown feasibility but remain limited by anatomical differences, lack of dedicated devices, procedural risks, and unclear outcome thresholds.

Our prior work demonstrated that intracranial translesional pressure gradients correlate strongly with cerebral blood flow in both animal models and clinical settings, validating hemodynamic relevance. To overcome the limitations of invasive measurements, the present study seeks to develop and evaluate a noninvasive, angiography-derived pressure ratio (DPR) using routine digital subtraction angiography. This method allows physiologic assessment without pressure wires and may reduce procedural risk.

The objectives of this project are to establish a computational DPR technique, determine its association with clinical outcomes, identify a hemodynamic threshold for stroke-risk stratification, and validate its performance in a prospective multicenter cohort. By enabling early identification of high-risk ICAS patients who may respond poorly to medical therapy, DPR has the potential to improve treatment selection and outcomes, ultimately advancing strategies for stroke prevention.