PURPOSE

The cerebral anterior circulation arteries are the primary vessels supplying blood to the brain, and severe stenosis in these arteries can lead to ischemic stroke. Traditional imaging-based methods for assessing stenosis severity primarily focus on the diameter reduction at the narrowest point, which often fails to accurately reflect the functional severity of arterial stenosis. The FFR is considered the gold standard for assessing coronary artery stenosis. This study aims to revisit the original definition of FFR and develop a method for functionally assessing stenosis in the cerebral anterior circulation arteries.

METHODS

Patient-specific artery models representing both stenosed and post-repair conditions were generated based on clinical data. Numerical simulation models were then developed, and BFFR was calculated as an assessment metric. The accuracy of the numerical simulation model was validated through in vitro experiments.

RESULTS

The average bifurcation coefficient across the 9 cases was 2.82. The numerical simulation results for all cases were consistent with the clinical CTP measurements, accurately distinguishing the relative blood flow between the left and right arteries. The mean BFFR for patients with mild stenosis was 1.53 times higher than that of patients with moderate and severe stenosis. The relative error between the total flow obtained from the numerical simulations and the experimental measurements was less than 3%.

CONCLUSION

Compared to traditional diameter stenosis rates, BFFR offers a significant advantage in evaluating cerebral artery stenosis. Furthermore, the numerical simulation model developed in this study demonstrated high accuracy.