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Diagnostic Performance of CT FFR With a New Parameter Optimized Computational Fluid Dynamics Algorithm From the CT-FFR-CHINA Trial: Characteristic Analysis of Gray Zone Lesions and Misdiagnosed Lesions.
Gao, Yang; Zhao, Na; Song, Lei; Hu, Hongjie; Jiang, Tao; Chen, Wenqiang; Zhang, Feng; Dou, Kefei; Mu, Chaowei; Yang, Weixian; Fu, Guosheng; Xu, Li; Li, Dumin; Fan, Lijuan; An, Yunqiang; Wang, Yang; Li, Wei; Xu, Bo; Lu, Bin.
Afiliación
  • Gao Y; Department of Radiology, Fuwai Hospital, National Center for Cardiovascular Diseases, Peking Union Medical College and Chinese Academy of Medical Sciences, Beijing, China.
  • Zhao N; Department of Radiology, Fuwai Hospital, National Center for Cardiovascular Diseases, Peking Union Medical College and Chinese Academy of Medical Sciences, Beijing, China.
  • Song L; Department of Cardiology, Fuwai Hospital, National Center for Cardiovascular Diseases, Peking Union Medical College and Chinese Academy of Medical Sciences, Beijing, China.
  • Hu H; Department of Radiology, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou, China.
  • Jiang T; Department of Radiology, Beijing Chao-Yang Hospital, Capital Medical University, Beijing, China.
  • Chen W; Department of Cardiology, Qilu Hospital, Shandong University, Jinan, China.
  • Zhang F; Department of Cardiology, TEDA International Cardiovascular Hospital, Tianjin, China.
  • Dou K; Department of Cardiology, Fuwai Hospital, National Center for Cardiovascular Diseases, Peking Union Medical College and Chinese Academy of Medical Sciences, Beijing, China.
  • Mu C; Department of Cardiology, Fuwai Hospital, National Center for Cardiovascular Diseases, Peking Union Medical College and Chinese Academy of Medical Sciences, Beijing, China.
  • Yang W; Department of Cardiology, Fuwai Hospital, National Center for Cardiovascular Diseases, Peking Union Medical College and Chinese Academy of Medical Sciences, Beijing, China.
  • Fu G; Department of Cardiology, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou, China.
  • Xu L; Department of Cardiology, Beijing Chao-Yang Hospital, Capital Medical University, Beijing, China.
  • Li D; Department of Radiology, Qilu Hospital, Shandong University, Jinan, China.
  • Fan L; Department of Radiology, TEDA International Cardiovascular Hospital, Tianjin, China.
  • An Y; Department of Radiology, Fuwai Hospital, National Center for Cardiovascular Diseases, Peking Union Medical College and Chinese Academy of Medical Sciences, Beijing, China.
  • Wang Y; Medical Research and Biometrics Center, Fuwai Hospital, National Center for Cardiovascular Diseases, Peking Union Medical College and Chinese Academy of Medical Sciences, Beijing, China.
  • Li W; Medical Research and Biometrics Center, Fuwai Hospital, National Center for Cardiovascular Diseases, Peking Union Medical College and Chinese Academy of Medical Sciences, Beijing, China.
  • Xu B; Department of Cardiology, Fuwai Hospital, National Center for Cardiovascular Diseases, Peking Union Medical College and Chinese Academy of Medical Sciences, Beijing, China.
  • Lu B; Department of Radiology, Fuwai Hospital, National Center for Cardiovascular Diseases, Peking Union Medical College and Chinese Academy of Medical Sciences, Beijing, China.
Front Cardiovasc Med ; 9: 819460, 2022.
Article en En | MEDLINE | ID: mdl-35391840
To assess the diagnostic performance of fractional flow reserve (FFR) derived from coronary computed tomography angiography (CTA) (CT-FFR) obtained by a new computational fluid dynamics (CFD) algorithm to detect ischemia, using FFR as a reference, and analyze the characteristics of "gray zone" and misdiagnosed lesions. This prospective multicenter clinical trial (NCT03692936, https://clinicaltrials.gov/) analyzed 317 patients with coronary stenosis between 30 and 90% in 366 vessels from five centers undergoing CTA and FFR between November 2018 and March 2020. CT-FFR were obtained from a CFD algorithm (Heartcentury Co., Ltd., Beijing, China). Diagnostic performance of CT-FFR and CTA in detecting ischemia was assessed. Coronary atherosclerosis characteristics of gray zone and misdiagnosed lesions were analyzed. Per-vessel sensitivity, specificity and accuracy for CT-FFR and CTA were 89.9, 87.8, 88.8% and 89.3, 35.5, 60.4%, respectively. Accuracy of CT-FFR was 80.0% in gray zone lesions. In gray zone lesions, lumen area and diameter were significantly larger than lesions with FFR < 0.76 (both p < 0.001), lesion length, non-calcified and calcified plaque volume were all significantly higher than non-ischemic lesions (all p < 0.05). In gray zone lesions, Agatston score (OR = 1.009, p = 0.044) was the risk factor of false negative results of CT-FFR. In non-ischemia lesions, coronary stenosis >50% (OR = 2.684, p = 0.03) was the risk factor of false positive results. Lumen area (OR = 0.567, p = 0.02) and diameter (OR = 0.296, p = 0.03) had a significant negative effect on the risk of false positive results of CT-FFR. In conclusion, CT-FFR based on the new parameter-optimized CFD model provides better diagnostic performance for lesion-specific ischemia than CTA. For gray zone lesions, stenosis degree was less than those with FFR < 0.76, and plaque load was heavier than non-ischemic lesions.
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Tipo de estudio: Diagnostic_studies / Prognostic_studies Idioma: En Revista: Front Cardiovasc Med Año: 2022 Tipo del documento: Article País de afiliación: China Pais de publicación: Suiza

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Tipo de estudio: Diagnostic_studies / Prognostic_studies Idioma: En Revista: Front Cardiovasc Med Año: 2022 Tipo del documento: Article País de afiliación: China Pais de publicación: Suiza