Department of Medicine, Seoul National University Hospital, Seoul, Republic of Korea.
Department of Medicine, Inje University Ilsan Paik Hospital, Goyang, Republic of Korea.
JACC Cardiovasc Interv. 2014 Jan;7(1):72-8. doi: 10.1016/j.jcin.2013.05.024. Epub 2013 Dec 11.
This study sought to determine whether computational modeling can be used to predict the functional outcome of coronary stenting by virtual stenting of ischemia-causing stenoses identified on the pre-treatment model.
Computed tomography (CT)-derived fractional flow reserve (FFR) is a novel noninvasive technology that can provide computed (FFRct) using standard coronary CT angiography protocols.
We prospectively enrolled 44 patients (48 lesions) who had coronary CT angiography before angiography and stenting, and invasively measured FFR before and after stenting. FFRct was computed in blinded fashion using coronary CT angiography and computational fluid dynamics before and after virtual coronary stenting. Virtual stenting was performed by modification of the computational model to restore the area of the target lesion according to the proximal and distal reference areas.
Before intervention, invasive FFR was 0.70 ± 0.14 and noninvasive FFRct was 0.70 ± 0.15. FFR after stenting and FFRct after virtual stenting were 0.90 ± 0.05 and 0.88 ± 0.05, respectively (R = 0.55, p < 0.001). The mean difference between FFRct and FFR was 0.006 for pre-intervention (95% limit of agreement: -0.27 to 0.28) and 0.024 for post-intervention (95% limit of agreement: -0.08 to 0.13). Diagnostic accuracy of FFRct to predict ischemia (FFR ≤ 0.8) prior to stenting was 77% (sensitivity: 85.3%, specificity: 57.1%, positive predictive value: 83%, and negative predictive value: 62%) and after stenting was 96% (sensitivity: 100%, specificity: 96% positive predictive value: 50%, and negative predictive value: 100%).
Virtual coronary stenting of CT-derived computational models is feasible, and this novel noninvasive technology may be useful in predicting functional outcome after coronary stenting. (Virtual Coronary Intervention and Noninvasive Fractional Flow Reserve [FFR]; NCT01478100).
本研究旨在通过对术前模型中识别出的导致缺血的狭窄进行虚拟支架置入,确定计算模型是否可用于预测冠状动脉支架置入后的功能结果。
计算机断层扫描(CT)衍生的血流储备分数(FFR)是一种新型的无创技术,可通过标准的冠状动脉 CT 血管造影方案提供计算的(FFRct)。
我们前瞻性纳入了 44 名患者(48 处病变),这些患者在血管造影和支架置入前进行了冠状动脉 CT 血管造影,并且在支架置入前后进行了有创的 FFR 测量。FFRct 在盲法下使用冠状动脉 CT 血管造影和计算流体动力学在虚拟冠状动脉支架置入前后进行计算。通过修改计算模型来恢复目标病变的区域,根据近端和远端参考区域来进行虚拟支架置入。
在干预前,有创 FFR 为 0.70 ± 0.14,无创 FFRct 为 0.70 ± 0.15。支架置入后的 FFR 和虚拟支架置入后的 FFRct 分别为 0.90 ± 0.05 和 0.88 ± 0.05(R = 0.55,p < 0.001)。FFRct 与 FFR 在干预前的平均差值为 0.006(95%一致性界限:-0.27 至 0.28),在干预后的平均差值为 0.024(95%一致性界限:-0.08 至 0.13)。FFRct 在支架置入前预测缺血(FFR ≤ 0.8)的诊断准确性为 77%(敏感性:85.3%,特异性:57.1%,阳性预测值:83%,阴性预测值:62%),支架置入后为 96%(敏感性:100%,特异性:96%,阳性预测值:50%,阴性预测值:100%)。
CT 衍生计算模型的虚拟冠状动脉支架置入是可行的,这种新型的无创技术可能有助于预测冠状动脉支架置入后的功能结果。(虚拟冠状动脉介入和无创血流储备分数(FFR);NCT01478100)。