Cardiovascular Center Aalst, OLV Clinic, Aalst, Belgium; Department of Advanced Biomedical Sciences University Federico II, Naples, Italy.
Cardiovascular Center Aalst, OLV Clinic, Aalst, Belgium; Department of Cardiology, Showa University Fujigaoka Hospital, Kanagawa, Japan.
JACC Cardiovasc Imaging. 2022 Jul;15(7):1242-1255. doi: 10.1016/j.jcmg.2022.02.003. Epub 2022 Apr 13.
Low fractional flow reserve (FFR) values after percutaneous coronary intervention (PCI) carry a worse prognosis than high post-PCI FFR values. Therefore, the ability to predict post-PCI FFR might play an important role in procedural planning. Post-PCI FFR values can now be computed from pre-PCI coronary computed tomography angiography (CTA) using the fractional flow reserve derived from coronary computed tomography angiography revascularization planner (FFR Planner).
The aim of this study was to validate the accuracy of the FFR Planner.
In this multicenter, investigator-initiated, prospective study, patients with chronic coronary syndromes and significant lesions based on invasive FFR ≤0.80 were recruited. The FFR Planner was applied to the fractional flow reserve derived from coronary computed tomography angiography (FFR) model, simulating PCI. The primary objective was the agreement between the predicted post-PCI FFR by the FFR Planner and measured post-PCI FFR. Accuracy of the FFR Planner's luminal dimensions was assessed by using post-PCI optical coherence tomography as the reference.
Overall, 259 patients were screened, with 120 patients (123 vessels) included in the final analysis. The mean patient age was 64 ± 9 years, and 24% had diabetes. Measured FFR post-PCI was 0.88 ± 0.06, and the FFR Planner FFR was 0.86 ± 0.06 (mean difference: 0.02 ± 0.07 FFR unit; limits of agreement: -0.12 to 0.15). Optical coherence tomography minimal stent area was 5.60 ± 2.01 mm, and FFR Planner minimal stent area was 5.0 ± 2.2 mm (mean difference: 0.66 ± 1.21 mm; limits of agreement: -1.7 to 3.0). The accuracy and precision of the FFR Planner remained high in cases with focal and diffuse disease and with low and high calcium burden.
The FFR-based technology was accurate and precise for predicting FFR after PCI. (Precise Percutaneous Coronary Intervention Plan Study [P3]; NCT03782688).
经皮冠状动脉介入治疗（PCI）后低分数血流储备（FFR）值比高 PCI 后 FFR 值预后更差。因此，预测 PCI 后 FFR 的能力可能在手术规划中发挥重要作用。现在可以使用冠状动脉计算机断层血管造影（CTA）的 FFR 计算，从冠状动脉计算机断层血管造影再血管化规划师（FFR 规划师）获得的分数血流储备。
本研究旨在验证 FFR 规划师的准确性。
在这项多中心、研究者发起的前瞻性研究中，招募了基于有创 FFR≤0.80 的慢性冠状动脉综合征和显著病变的患者。FFR 规划师应用于基于冠状动脉计算机断层血管造影的分数血流储备（FFR）模型，模拟 PCI。主要目的是 FFR 规划师预测的 PCI 后 FFR 与测量的 PCI 后 FFR 之间的一致性。通过使用 PCI 后光学相干断层扫描作为参考，评估 FFR 规划师管腔尺寸的准确性。
总体而言，筛选了 259 例患者，最终分析纳入了 120 例患者（123 支血管）。患者平均年龄为 64±9 岁，24%患有糖尿病。测量的 PCI 后 FFR 为 0.88±0.06，FFR 规划师的 FFR 为 0.86±0.06（平均差异：0.02±0.07 FFR 单位；一致性范围：-0.12 至 0.15）。光学相干断层扫描最小支架面积为 5.60±2.01mm，FFR 规划师最小支架面积为 5.0±2.2mm（平均差异：0.66±1.21mm；一致性范围：-1.7 至 3.0）。FFR 规划师在局灶性和弥漫性疾病以及低钙和高钙负荷的情况下，其准确性和精确性仍然很高。
基于 FFR 的技术可准确、精确地预测 PCI 后的 FFR。（精确经皮冠状动脉介入治疗计划研究 [P3]；NCT03782688）。
