Mokhtari Ali, Corso Pascal, Jung Bernd, Ferrari Lorenzo, Zheng Shaokai, Obrist Dominik
ARTORG Center for Biomedical Engineering Research, University of Bern, Bern, Switzerland.
ARTORG Center for Biomedical Engineering Research, University of Bern, Bern, Switzerland; Swiss Data Science Center, ETH Zurich, Zurich, Switzerland.
Comput Biol Med. 2025 Aug;194:110405. doi: 10.1016/j.compbiomed.2025.110405. Epub 2025 Jun 10.
Internal carotid artery (ICA) stenoses are a major source of stroke. In addition to traditional cardiovascular risk factors, hemodynamic parameters such as wall shear stress (WSS) are recognized as critical contributors to the progression and rupture of ICA plaques. This study evaluates the ability of 4D flow MRI to predict the velocity and WSS fields in three models of carotid bifurcations representing stenosis ratios of 0% (healthy), 40% (mildly stenosed), and 80% (severely stenosed) in the ICA. The stenosis ratio significantly impacts hemodynamics, increasing peak velocity, WSS, and flow disturbances. Compared to the healthy model, peak velocity rises by 38% in severe stenosis, generating a high-velocity jet and post-stenotic recirculation. Spatially averaged WSS increases by 21.5% in the mildly stenosed model and 99% in the severely stenosed model. Additionally, flow separation and vortex formation intensify as stenosis severity increases. A robust experimental setup with carotid bifurcation phantoms has been developed to eliminate the major sources of uncertainty in the boundary conditions. This enables a detailed quantitative comparison of 4D flow MRI measurements (obtained with a 7T scanner) against results from a CFD simulation. Moreover, the CFD results were validated against results obtained from Direct Numerical Simulations (DNS). Therefore, the CFD data could be used as a reliable high-fidelity reference for the flow within the carotid models. The comparison indicates that 4D flow MRI on a 7T scanner captures the major flow patterns with reasonable accuracy, though quantitative discrepancies increase with the stenosis ratio. Specifically, the peak velocity error rises from 6.1% in healthy arteries to 11.9% in severely stenosed arteries. Similarly, the error in spatially averaged WSS magnitude in the bifurcation region increases from 18% in healthy cases to 38% in severely stenosed cases. These findings underscore the need for validated approaches to accurately analyze complex flow patterns within carotid arteries, especially as even high-quality 4D flow MRI measurements using a 7T scanner with 0.5 mm resolution show diminishing accuracy in such challenging cases.
颈内动脉（ICA）狭窄是中风的主要来源。除了传统的心血管危险因素外，诸如壁面剪应力（WSS）等血流动力学参数被认为是ICA斑块进展和破裂的关键因素。本研究评估了四维流磁共振成像（4D流MRI）预测三种颈动脉分叉模型中血流速度和WSS场的能力，这些模型分别代表ICA狭窄率为0%（健康）、40%（轻度狭窄）和80%（重度狭窄）。狭窄率对血流动力学有显著影响，会增加峰值速度、WSS和血流紊乱。与健康模型相比，严重狭窄时峰值速度上升38%，产生高速射流和狭窄后血流再循环。在轻度狭窄模型中，空间平均WSS增加21.5%，在严重狭窄模型中增加99%。此外，随着狭窄程度的增加，血流分离和涡流形成加剧。已开发出一种使用颈动脉分叉模型的稳健实验装置，以消除边界条件中的主要不确定来源。这使得能够将4D流MRI测量结果（使用7T扫描仪获得）与计算流体动力学（CFD）模拟结果进行详细的定量比较。此外，CFD结果已根据直接数值模拟（DNS）获得的结果进行了验证。因此，CFD数据可作为颈动脉模型内血流的可靠高保真参考。比较表明，7T扫描仪上的4D流MRI以合理的准确度捕捉到了主要的血流模式，尽管定量差异随狭窄率增加。具体而言，峰值速度误差从健康动脉中的6.1%上升至严重狭窄动脉中的11.9%。同样，分叉区域空间平均WSS大小的误差从健康病例中的18%增加到严重狭窄病例中的38%。这些发现强调了需要经过验证的方法来准确分析颈动脉内的复杂血流模式，特别是因为即使使用具有0.5毫米分辨率的7T扫描仪进行的高质量4D流MRI测量，在这种具有挑战性的情况下准确性也会降低。
