Department of Cardiology, Erasmus University Medical Center, Rotterdam, the Netherlands; Department of Radiology, Erasmus University Medical Center, Rotterdam, the Netherlands.
Department of Cardiology, Erasmus University Medical Center, Rotterdam, the Netherlands; Centre for Advanced Cardiovascular Imaging, NIHR Cardiovascular Biomedical Research Unit at Barts, William Harvey Research Institute, Barts and The London School of Medicine and Dentistry, Queen Mary University of London & St. Bartholomew's Hospital, London, United Kingdom.
JACC Cardiovasc Imaging. 2017 Jul;10(7):760-770. doi: 10.1016/j.jcmg.2016.09.028. Epub 2017 Jan 18.
The aim of this study was to investigate the individual and combined accuracy of dynamic computed tomography (CT) myocardial perfusion imaging (MPI) and computed tomography angiography (CTA) fractional flow reserve (FFR) for the identification of functionally relevant coronary artery disease (CAD).
Coronary CTA has become an established diagnostic test for ruling out CAD, but it does not allow interpretation of the hemodynamic severity of stenotic lesions. Two recently introduced functional CT techniques are dynamic MPI and CTA FFR using computational fluid dynamics.
From 2 institutions, 74 patients (n = 62 men, mean age 61 years) planned for invasive angiography with invasive FFR measurement in 142 vessels underwent CTA imaging and dynamic CT MPI during adenosine vasodilation. A patient-specific myocardial blood flow index was calculated, normalized to remote myocardial global left ventricular blood flow. CTA FFR was computed using an on-site, clinician-operated application. Using binary regression, a single functional CT variable was created combining both CT MPI and CTA FFR. Finally, stepwise diagnostic work-up of CTA FFR with selective use of CT MPI was simulated. The diagnostic performance of CT MPI, CTA FFR, and CT MPI integrated with CTA FFR was evaluated using C statistics with invasive FFR, with a threshold of 0.80 as a reference.
Sensitivity, specificity, and accuracy were 73% (95% confidence interval [CI]: 61% to 86%), 68% (95% CI: 56% to 80%), and 70% (95% CI: 62% to 79%) for CT MPI and 82% (95% CI: 72% to 92%), 60% (95% CI: 48% to 72%), and 70% (63% to 80%) for CTA FFR. For CT MPI integrated with CTA FFR, diagnostic accuracy was 79% (95% CI: 71% to 87%), with improvement of the area under the curve from 0.78 to 0.85 (p < 0.05). Accuracy of the stepwise approach was 77%.
CT MPI and CTA FFR both identify functionally significant CAD, with comparable accuracy. Diagnostic performance can be improved by combining the techniques. A stepwise approach, reserving CT MPI for intermediate CTA FFR results, also improves diagnostic performance while omitting nearly one-half of the population from CT MPI examinations.
本研究旨在探讨动态计算机断层扫描（CT）心肌灌注成像（MPI）和 CT 血管造影（CTA）血流储备分数（FFR）对功能性相关冠状动脉疾病（CAD）的识别的个体和联合准确性。
冠状动脉 CTA 已成为排除 CAD 的既定诊断测试，但它无法解释狭窄病变的血流动力学严重程度。两种最近引入的功能 CT 技术是使用计算流体动力学的动态 MPI 和 CTA FFR。
来自 2 家机构的 74 名患者（n = 62 名男性，平均年龄 61 岁）计划进行血管造影检查，其中 142 个血管进行有创 FFR 测量，在腺苷血管扩张期间进行 CTA 成像和动态 CT MPI。计算患者特异性心肌血流指数，标准化为远程心肌左心室整体血流。使用现场操作的临床医生操作的应用程序计算 CTA FFR。使用二元回归，创建一个将 CT MPI 和 CTA FFR 结合在一起的单一功能 CT 变量。最后，模拟 CTA FFR 的逐步诊断工作流程，并选择性使用 CT MPI。使用 C 统计量评估 CT MPI、CTA FFR 和与 CTA FFR 相结合的 CT MPI 的诊断性能，以 0.80 作为参考。
CT MPI 的敏感性、特异性和准确性分别为 73%（95%CI：61%至 86%）、68%（95%CI：56%至 80%）和 70%（95%CI：62%至 79%），CTA FFR 的敏感性、特异性和准确性分别为 82%（95%CI：72%至 92%）、60%（95%CI：48%至 72%）和 70%（63%至 80%）。对于与 CTA FFR 相结合的 CT MPI，诊断准确性为 79%（95%CI：71%至 87%），曲线下面积从 0.78 提高到 0.85（p < 0.05）。逐步方法的准确性为 77%。
CT MPI 和 CTA FFR 均能识别功能性重要的 CAD，准确性相当。通过结合这两种技术可以提高诊断性能。逐步方法通过保留中间 CTA FFR 结果来保留 CT MPI，在排除近一半人群进行 CT MPI 检查的同时，还可以提高诊断性能。
