Yu Long, Zhu Deyuan, Cai Yunhan, Fang Yibin, Wang Shengzhang
Department of Aeronautics and Astronautics, Institute of Biomechanics, Fudan University, Handan Road, Shanghai, 200433, China.
Transvascular Implantation Devices Research Institute, Zhejiang University, Jianta Street, Hangzhou, 310053, China.
Ann Biomed Eng. 2025 Jul 21. doi: 10.1007/s10439-025-03810-2.
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.
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.
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%.
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.
大脑前循环动脉是向大脑供血的主要血管，这些动脉的严重狭窄可导致缺血性中风。传统的基于影像学评估狭窄严重程度的方法主要关注最狭窄点处的直径缩小情况，这往往无法准确反映动脉狭窄的功能严重程度。血流储备分数（FFR）被认为是评估冠状动脉狭窄的金标准。本研究旨在重新审视FFR的原始定义，并开发一种在功能上评估大脑前循环动脉狭窄的方法。
基于临床数据生成代表狭窄和修复后情况的患者特异性动脉模型。然后建立数值模拟模型，并计算脑血流储备分数（BFFR）作为评估指标。通过体外实验验证数值模拟模型的准确性。
9例患者的平均分叉系数为2.82。所有病例的数值模拟结果与临床CTP测量结果一致，准确区分了左右动脉之间的相对血流。轻度狭窄患者的平均BFFR比中度和重度狭窄患者高1.53倍。数值模拟得到的总流量与实验测量值之间的相对误差小于3%。
与传统的直径狭窄率相比，BFFR在评估脑动脉狭窄方面具有显著优势。此外，本研究开发的数值模拟模型显示出很高的准确性。
