OBJECTIVES This study sought to assess the ability of a novel virtual coronary intervention (VCI) tool based on invasive angiography to predict the patient's physiological response to stenting. BACKGROUND Fractional flow reserve (FFR)-guided percutaneous coronary intervention (PCI) is associated with improved clinical and economic outcomes compared with angiographic guidance alone. Virtual (v)FFR can be calculated based upon a 3-dimensional (3D) reconstruction of the coronary anatomy from the angiogram, using computational fluid dynamics (CFD) modeling. This technology can be used to perform virtual stenting, with a predicted post-PCI FFR, and the prospect of optimized treatment planning. METHODS Patients undergoing elective PCI had pressure-wire-based FFR measurements pre- and post-PCI. A 3D reconstruction of the diseased artery was generated from the angiogram and imported into the VIRTUheart workflow, without the need for any invasive physiological measurements. VCI was performed using a radius correction tool replicating the dimensions of the stent deployed during PCI. Virtual FFR (vFFR) was calculated pre- and post-VCI, using CFD analysis. vFFR pre- and post-VCI were compared with measured (m)FFR pre- and post-PCI, respectively. RESULTS Fifty-four patients and 59 vessels underwent PCI. The mFFR and vFFR pre-PCI were 0.66 ± 0.14 and 0.68 ± 0.13, respectively. Pre-PCI vFFR deviated from mFFR by ±0.05 (mean Δ = -0.02; SD = 0.07). The mean mFFR and vFFR post-PCI/VCI were 0.90 ± 0.05 and 0.92 ± 0.05, respectively. Post-VCI vFFR deviated from post-PCI mFFR by ±0.02 (mean Δ = -0.01; SD = 0.03). Mean CFD processing time was 95 s per case. CONCLUSIONS The authors have developed a novel VCI tool, based upon the angiogram, that predicts the physiological response to stenting with a high degree of accuracy.

中文翻译：

---

虚拟冠状动脉介入治疗：基于血管造影的治疗计划工具。

目标 本研究旨在评估一种基于有创血管造影的新型虚拟冠状动脉介入治疗 (VCI) 工具预测患者对支架置入术的生理反应的能力。背景 与单独的血管造影指导相比，血流储备分数 (FFR) 指导的经皮冠状动脉介入治疗 (PCI) 与改善的临床和经济结果相关。可以使用计算流体动力学 (CFD) 建模基于血管造影的冠状动脉解剖结构的 3 维 (3D) 重建来计算虚拟 (v)FFR。该技术可用于执行虚拟支架置入术，具有预测的 PCI 后 FFR 和优化治疗计划的前景。方法 接受择期 PCI 的患者在 PCI 前后进行基于压力丝的 FFR 测量。病变动脉的 3D 重建从血管造影中生成并导入 VIRTUheart 工作流程，无需任何侵入性生理测量。VCI 是使用半径校正工具进行的，该工具复制了 PCI 期间部署的支架的尺寸。使用 CFD 分析计算 VCI 前后的虚拟 FFR (vFFR)。VCI 前后的 vFFR 分别与 PCI 前后测量的 (m)FFR 进行了比较。结果 54 名患者和 59 条血管接受了 PCI。PCI 前的 mFFR 和 vFFR 分别为 0.66 ± 0.14 和 0.68 ± 0.13。PCI 前 vFFR 与 mFFR 的偏差为 ±0.05（平均值 Δ = -0.02；SD = 0.07）。PCI/VCI 后的平均 mFFR 和 vFFR 分别为 0.90 ± 0.05 和 0.92 ± 0.05。VCI 后 vFFR 与 PCI 后 mFFR 的偏差为 ±0.02（平均值 Δ = -0.01；SD = 0.03）。每个案例的平均 CFD 处理时间为 95 秒。结论 作者开发了一种基于血管造影的新型 VCI 工具，可以高度准确地预测对支架置入术的生理反应。