CT FFR for Ischemia-Specific CAD With a New Computational Fluid Dynamics Algorithm: A Chinese Multicenter Study
Chun Xiang Tang, Chun Yu Liu, Meng Jie Lu, U Joseph Schoepf, Christian Tesche, Richard R Bayer 2nd, H Todd Hudson Jr, Xiao Lei Zhang, Jian Hua Li, Yi Ning Wang, Chang Sheng Zhou, Jia Yin Zhang, Meng Meng Yu, Yang Hou, Min Wen Zheng, Bo Zhang, Dai Min Zhang, Yan Yi, Yuan Ren, Chen Wei Li, Xi Zhao, Guang Ming Lu, Xiu Hua Hu, Lei Xu, Long Jiang Zhang, Chun Xiang Tang, Chun Yu Liu, Meng Jie Lu, U Joseph Schoepf, Christian Tesche, Richard R Bayer 2nd, H Todd Hudson Jr, Xiao Lei Zhang, Jian Hua Li, Yi Ning Wang, Chang Sheng Zhou, Jia Yin Zhang, Meng Meng Yu, Yang Hou, Min Wen Zheng, Bo Zhang, Dai Min Zhang, Yan Yi, Yuan Ren, Chen Wei Li, Xi Zhao, Guang Ming Lu, Xiu Hua Hu, Lei Xu, Long Jiang Zhang
Abstract
Objectives: The aim of this study was to validate the feasibility of a novel structural and computational fluid dynamics-based fractional flow reserve (FFR) algorithm for coronary computed tomography angiography (CTA), using alternative boundary conditions to detect lesion-specific ischemia.
Background: A new model of computed tomographic (CT) FFR relying on boundary conditions derived from structural deformation of the coronary lumen and aorta with transluminal attenuation gradient and assumptions regarding microvascular resistance has been developed, but its accuracy has not yet been validated.
Methods: A total of 338 consecutive patients with 422 vessels from 9 Chinese medical centers undergoing CTA and invasive FFR were retrospectively analyzed. CT FFR values were obtained on a novel on-site computational fluid dynamics-based CT FFR (uCT-FFR [version 1.5, United-Imaging Healthcare, Shanghai, China]). Performance characteristics of uCT-FFR and CTA in detecting lesion-specific ischemia in all lesions, intermediate lesions (luminal stenosis 30% to 70%), and "gray zone" lesions (FFR 0.75 to 0.80) were calculated with invasive FFR as the reference standard. The effect of coronary calcification on uCT-FFR measurements was also assessed.
Results: Per vessel sensitivities, specificities, and accuracies of 0.89, 0.91, and 0.91 with uCT-FFR, 0.92, 0.34, and 0.55 with CTA, and 0.94, 0.37, and 0.58 with invasive coronary angiography, respectively, were found. There was higher specificity, accuracy, and AUC for uCT-FFR compared with CTA and qualitative invasive coronary angiography in all lesions, including intermediate lesions (p < 0.001 for all). No significant difference in diagnostic accuracy was observed in the "gray zone" range versus the other 2 lesion groups (FFR ≤0.75 and >0.80; p = 0.397) and in patients with "gray zone" versus FFR ≤0.75 (p = 0.633) and versus FFR >0.80 (p = 0.364), respectively. No significant difference in the diagnostic performance of uCT-FFR was found between patients with calcium scores ≥400 and <400 (p = 0.393).
Conclusions: This novel computational fluid dynamics-based CT FFR approach demonstrates good performance in detecting lesion-specific ischemia. Additionally, it outperforms CTA and qualitative invasive coronary angiography, most notably in intermediate lesions, and may potentially have diagnostic power in gray zone and highly calcified lesions.
Keywords: computational fluid dynamics; fractional flow reserve; gray zone; intermediate lesions.
Copyright © 2020 American College of Cardiology Foundation. Published by Elsevier Inc. All rights reserved.
Source: PubMed