CT FFR for Ischemia-Specific CAD With a New Computational Fluid Dynamics Algorithm A Chinese Multicenter Study,JACC: Cardiovascular Imaging

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CT FFR for Ischemia-Specific CAD With a New Computational Fluid Dynamics Algorithm A Chinese Multicenter Study
JACC: Cardiovascular Imaging ( IF 12.8 ) Pub Date : 2020-04-01 , DOI: 10.1016/j.jcmg.2019.06.018
Chun Xiang Tang ₁ , Chun Yu Liu ₁ , Meng Jie Lu ₁ , U Joseph Schoepf ₂ , Christian Tesche ₃ , Richard R Bayer ₃ , H Todd Hudson ₃ , Xiao Lei Zhang ₁ , Jian Hua Li ₄ , Yi Ning Wang ₅ , Chang Sheng Zhou ₁ , Jia Yin Zhang ₆ , Meng Meng Yu ₆ , Yang Hou ₇ , Min Wen Zheng ₈ , Bo Zhang ₉ , Dai Min Zhang ₁₀ , Yan Yi ₅ , Yuan Ren ₁₁ , Chen Wei Li ₁₁ , Xi Zhao ₁₁ , Guang Ming Lu ₁ , Xiu Hua Hu ₁₂ , Lei Xu ₁₃ , Long Jiang Zhang ₁

Affiliation

Department of Medical Imaging, Jinling Hospital, Medical School of Nanjing University, Nanjing, China.
Department of Medical Imaging, Jinling Hospital, Medical School of Nanjing University, Nanjing, China; Division of Cardiovascular Imaging, Department of Radiology and Radiological Science, Medical University of South Carolina, Charleston, South Carolina.
Division of Cardiovascular Imaging, Department of Radiology and Radiological Science, Medical University of South Carolina, Charleston, South Carolina.
Department of Cardiology, Jinling Hospital, Medical School of Nanjing University, Nanjing, China.
Department of Radiology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.
Institute of Diagnostic and Interventional Radiology and Department of Cardiology, Shanghai Jiao Tong University Affiliated Sixth People's Hospital, Shanghai, China.
Department of Radiology, Shengjing Hospital of China Medical University, Shenyang, China.
Department of Radiology, The First Affiliated Hospital of Fourth Military Medical University, Xi'an, China.
Department of Radiology, Jiangsu Taizhou People's Haspital, Taizhou, China.
Department of Cardiology, Nanjing First Hospital, Nanjing Medical University, Nanjing, China.
Shanghai United Imaging Healthcare, Shanghai, China.
Department of Radiology, School of Medicine, Sir Run Run Shaw Hospital, Zhejiang University, 3 East Qingchun Road, Hangzhou 310006, Zhejiang, People's Republic of China.
Department of Radiology, Beijing Anzhen Hospital, Capital Medical University, Beijing, China.

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.

更新日期：2020-04-01

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