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CT FFR for Ischemia-Specific CAD With a New Computational Fluid Dynamics Algorithm: A Chinese Multicenter Study.
Tang, Chun Xiang; Liu, Chun Yu; Lu, Meng Jie; Schoepf, U Joseph; Tesche, Christian; Bayer, Richard R; Hudson, H Todd; Zhang, Xiao Lei; Li, Jian Hua; Wang, Yi Ning; Zhou, Chang Sheng; Zhang, Jia Yin; Yu, Meng Meng; Hou, Yang; Zheng, Min Wen; Zhang, Bo; Zhang, Dai Min; Yi, Yan; Ren, Yuan; Li, Chen Wei; Zhao, Xi; Lu, Guang Ming; Hu, Xiu Hua; Xu, Lei; Zhang, Long Jiang.
Afiliación
  • Tang CX; Department of Medical Imaging, Jinling Hospital, Medical School of Nanjing University, Nanjing, China.
  • Liu CY; Department of Medical Imaging, Jinling Hospital, Medical School of Nanjing University, Nanjing, China.
  • Lu MJ; Department of Medical Imaging, Jinling Hospital, Medical School of Nanjing University, Nanjing, China.
  • Schoepf UJ; 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.
  • Tesche C; Division of Cardiovascular Imaging, Department of Radiology and Radiological Science, Medical University of South Carolina, Charleston, South Carolina.
  • Bayer RR; Division of Cardiovascular Imaging, Department of Radiology and Radiological Science, Medical University of South Carolina, Charleston, South Carolina.
  • Hudson HT; Division of Cardiovascular Imaging, Department of Radiology and Radiological Science, Medical University of South Carolina, Charleston, South Carolina.
  • Zhang XL; Department of Medical Imaging, Jinling Hospital, Medical School of Nanjing University, Nanjing, China.
  • Li JH; Department of Cardiology, Jinling Hospital, Medical School of Nanjing University, Nanjing, China.
  • Wang YN; Department of Radiology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.
  • Zhou CS; Department of Medical Imaging, Jinling Hospital, Medical School of Nanjing University, Nanjing, China.
  • Zhang JY; Institute of Diagnostic and Interventional Radiology and Department of Cardiology, Shanghai Jiao Tong University Affiliated Sixth People's Hospital, Shanghai, China.
  • Yu MM; Institute of Diagnostic and Interventional Radiology and Department of Cardiology, Shanghai Jiao Tong University Affiliated Sixth People's Hospital, Shanghai, China.
  • Hou Y; Department of Radiology, Shengjing Hospital of China Medical University, Shenyang, China.
  • Zheng MW; Department of Radiology, The First Affiliated Hospital of Fourth Military Medical University, Xi'an, China.
  • Zhang B; Department of Radiology, Jiangsu Taizhou People's Haspital, Taizhou, China.
  • Zhang DM; Department of Cardiology, Nanjing First Hospital, Nanjing Medical University, Nanjing, China.
  • Yi Y; Department of Radiology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.
  • Ren Y; Shanghai United Imaging Healthcare, Shanghai, China.
  • Li CW; Shanghai United Imaging Healthcare, Shanghai, China.
  • Zhao X; Shanghai United Imaging Healthcare, Shanghai, China.
  • Lu GM; Department of Medical Imaging, Jinling Hospital, Medical School of Nanjing University, Nanjing, China.
  • Hu XH; 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. Electronic address: medhxh@163.com.
  • Xu L; Department of Radiology, Beijing Anzhen Hospital, Capital Medical University, Beijing, China. Electronic address: leixu2001@hotmail.com.
  • Zhang LJ; Department of Medical Imaging, Jinling Hospital, Medical School of Nanjing University, Nanjing, China. Electronic address: kevinzhlj@163.com.
JACC Cardiovasc Imaging ; 13(4): 980-990, 2020 04.
Article en En | MEDLINE | ID: mdl-31422138
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.
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Algoritmos / Enfermedad de la Arteria Coronaria / Interpretación de Imagen Radiográfica Asistida por Computador / Angiografía Coronaria / Reserva del Flujo Fraccional Miocárdico / Calcificación Vascular / Tomografía Computarizada Multidetector / Angiografía por Tomografía Computarizada Tipo de estudio: Observational_studies / Prognostic_studies / Qualitative_research / Risk_factors_studies Límite: Aged / Female / Humans / Male / Middle aged País/Región como asunto: Asia Idioma: En Revista: JACC Cardiovasc Imaging Asunto de la revista: ANGIOLOGIA / CARDIOLOGIA / DIAGNOSTICO POR IMAGEM Año: 2020 Tipo del documento: Article País de afiliación: China

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Algoritmos / Enfermedad de la Arteria Coronaria / Interpretación de Imagen Radiográfica Asistida por Computador / Angiografía Coronaria / Reserva del Flujo Fraccional Miocárdico / Calcificación Vascular / Tomografía Computarizada Multidetector / Angiografía por Tomografía Computarizada Tipo de estudio: Observational_studies / Prognostic_studies / Qualitative_research / Risk_factors_studies Límite: Aged / Female / Humans / Male / Middle aged País/Región como asunto: Asia Idioma: En Revista: JACC Cardiovasc Imaging Asunto de la revista: ANGIOLOGIA / CARDIOLOGIA / DIAGNOSTICO POR IMAGEM Año: 2020 Tipo del documento: Article País de afiliación: China
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