Fractional flow reserve (FFR) is the gold standard for diagnosing coronary artery disease (CAD). FFRCT uses computational fluid dynamics (CFD) to evaluate FFR non-invasively by simulating coronary flow in geometries reconstructed from computed tomography (CT). However, it faces challenges related to the cost of computing and uncertainties in defining patient-specific boundary conditions (BCs). We investigated using time-averaged steady BCs instead of pulsatile ones to reduce computational time and deployed a self-adjusting method for tuning BCs to patient clinical data. 133 coronary arteries were reconstructed from CT images of CAD patients. For each vessel, invasive FFR was measured. Steady BCs for CFD were defined in two steps: i) rest BCs were extrapolated from clinical and image-derived data; ii) hyperemic BCs were computed from resting conditions. Flow rate was iteratively adjusted during the simulation until patient aortic pressure was matched. Pulsatile BCs were defined using the convergence values of steady BCs. Lesion-specific hemodynamic indexes were computed and compared between groups of patients indicated for surgery and those not. The whole pipeline was implemented as a straightforward, fully automated process. Steady and pulsatile FFRCT showed a strong correlation (r=0.988) and correlated with invasive FFR (r=0.797). The per-point difference between the pressure and FFRCT field predicted by the two methods was below 0.01 and 0.02, respectively. Both approaches exhibited good diagnostic performance: accuracy was 0.860 and 0.864, with AUCs of 0.923 and 0.912, for steady and pulsatile cases, respectively. Computational time for steady BCs CFD was approximately 30-fold lower than for the pulsatile case. This work demonstrates the feasibility of using steady BCs CFD for computing FFRCT in coronary arteries and its performance in a fully automated pipeline.

翻译：血流储备分数（FFR）是诊断冠状动脉疾病（CAD）的金标准。FFRCT 通过计算流体动力学（CFD）模拟基于计算机断层扫描（CT）重建的几何结构中的冠状动脉血流，从而实现无创FFR评估。然而，该方法面临计算成本高以及定义患者特异性边界条件（BCs）存在不确定性等挑战。为减少计算时间，我们研究了使用时均稳态边界条件替代脉动边界条件的方法，并部署了一种根据患者临床数据自动调节边界条件的自适应方法。本研究从CAD患者的CT图像中重建了133条冠状动脉。对每条血管均测量了有创FFR。CFD的稳态边界条件通过两个步骤定义：i）静息状态边界条件根据临床和影像数据推算得出；ii）充血状态边界条件由静息状态计算得出。在模拟过程中，血流量被迭代调整直至与患者主动脉压力相匹配。脉动边界条件则利用稳态边界条件的收敛值进行定义。计算了病变特异性血流动力学指标，并在建议手术与不建议手术的患者组间进行了比较。整个流程实现为一个简单、全自动化的处理过程。稳态与脉动FFRCT显示出强相关性（r=0.988），且均与有创FFR相关（r=0.797）。两种方法预测的压力场与FFRCT场的逐点差异分别低于0.01和0.02。两种方法均表现出良好的诊断性能：稳态与脉动情况下的准确度分别为0.860和0.864，受试者工作特征曲线下面积（AUC）分别为0.923和0.912。稳态边界条件CFD的计算时间约为脉动情况的1/30。本工作证明了使用稳态边界条件CFD计算冠状动脉FFRCT的可行性及其在全自动化流程中的性能。