Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA.
EuroIntervention. 2018 Feb 20;13(14):1696-1704. doi: 10.4244/EIJ-D-17-00019.
Fractional flow reserve (FFR) estimated from coronary computed tomography angiography (CT-FFR) offers non-invasive detection of lesion-specific ischaemia. We aimed to develop and validate a fast CT-FFR algorithm utilising the Lattice Boltzmann method for blood flow simulation (LBM CT-FFR).
Sixty-four patients with clinically indicated CTA and invasive FFR measurement from three institutions were retrospectively analysed. CT-FFR was performed using an onsite tool interfacing with a commercial Lattice Boltzmann fluid dynamics cloud-based platform. Diagnostic accuracy of LBM CT-FFR ≤0.8 and percent diameter stenosis >50% by CTA to detect invasive FFR ≤0.8 were compared using area under the receiver operating characteristic curve (AUC). Sixty patients successfully underwent LBM CT-FFR analysis; 29 of 73 lesions in 69 vessels had invasive FFR ≤0.8. Total time to perform LBM CT-FFR was 40±10 min. Compared to invasive FFR, LBM CT-FFR had good correlation (r=0.64), small bias (0.009) and good limits of agreement (-0.223 to 0.206). The AUC of LBM CT-FFR (AUC=0.894, 95% confidence interval [CI]: 0.792-0.996) was significantly higher than CTA (AUC=0.685, 95% CI: 0.576-0.794) to detect FFR ≤0.8 (p=0.0021). Per-lesion specificity, sensitivity, and accuracy of LBM CT-FFR were 97.7%, 79.3%, and 90.4%, respectively.
LBM CT-FFR has very good diagnostic accuracy to detect lesion-specific ischaemia (FFR ≤0.8) and can be performed in less than one hour.
基于冠状动脉计算机断层扫描血管造影（CT-FFR）估计的分流量储备（FFR）可用于非侵入性检测特定病变的缺血情况。我们旨在开发和验证一种利用格子玻尔兹曼方法进行血流模拟（LBM CT-FFR）的快速 CT-FFR 算法。
回顾性分析了来自三个机构的 64 例临床有指征行 CTA 和有创 FFR 测量的患者。使用一种与商业格子玻尔兹曼流体动力学云平台相连接的现场工具进行 CT-FFR。通过比较 CT 诊断准确性（FFR ≤0.8 时 LBM CT-FFR≤0.8 和狭窄程度＞50%），使用接受者操作特征曲线（ROC）下面积（AUC）来评估 LBM CT-FFR 的诊断性能。60 例患者成功进行了 LBM CT-FFR 分析；69 支血管中的 73 个病变中有 29 个有创 FFR ≤0.8。LBM CT-FFR 的总用时为 40±10 分钟。与有创 FFR 相比，LBM CT-FFR 具有良好的相关性（r=0.64）、较小的偏差（0.009）和良好的一致性界限（-0.223 至 0.206）。LBM CT-FFR 的 AUC（AUC=0.894，95%置信区间[CI]：0.792-0.996）显著高于 CTA（AUC=0.685，95%CI：0.576-0.794）（p=0.0021）。LBM CT-FFR 每病变的特异性、敏感性和准确性分别为 97.7%、79.3%和 90.4%。
LBM CT-FFR 具有非常高的诊断准确性，可用于检测特定病变的缺血情况（FFR ≤0.8），且用时不到 1 小时。
