Chun Xiang Tang1, Hong Yan Qiao1, Xiao Lei Zhang1, Meng Di Jiang1, U Joseph Schoepf1,2, Piotr Nikodem Rudziński2,3, Dominic P Giovagnoli2, Meng Jie Lu1, Jian Hua Li4, Yi Ning Wang5, Jia Yin Zhang6, Yang Hou7, Min Wen Zheng8, Bo Zhang9, Dai Min Zhang10, Xiu Hua Hu11, Lei Xu12, Hui Liu13, Guang Ming Lu14, Long Jiang Zhang15. 1. Department of Diagnostic Radiology, Jinling Hospital, Medical School of Nanjing University, Nanjing, 210002, Jiangsu, China. 2. Division of Cardiovascular Imaging, Department of Radiology and Radiological Science, Medical University of South Carolina, Ashley River Tower, MSC 226, 25 Courtenay Dr, Charleston, SC, 29425, USA. 3. Department of Coronary and Structural Heart Diseases, The Cardinal Stefan Wyszyński Institute of Cardiology, Warsaw, 200233, Poland. 4. Department of Cardiology, Jinling Hospital, Medical School of Nanjing University, Nanjing, 210002, Jiangsu, China. 5. Department of Radiology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100730, China. 6. Institute of Diagnostic and Interventional Radiology, and Department of Cardiology, Shanghai Jiao Tong University Affiliated Sixth People's Hospital, No. 600 Yi Shan Rd, Shanghai, 200233, China. 7. Department of Radiology, Shengjing Hospital of China Medical University, Shenyang, 110001, China. 8. Department of Radiology, Xijing Hospital, Fourth Military Medical University, Xi'an, Shanxi, China. 9. Department of Radiology, Jiangsu Taizhou People's Hospital, Taizhou, 225300, China. 10. Department of Cardiology, Nanjing First Hospital, Nanjing Medical University, Nanjing, 210006, Jiangsu, China. 11. Department of Radiology, School of Medicine, Sir Run Run Shaw Hospital, Zhejiang University, 3 East Qingchun Road, Zhejiang, 310006, Hangzhou, China. 12. Department of Radiology, Beijing Anzhen Hospital, Capital Medical University, Beijing, 10029, China. 13. Department of Radiology, Guangdong Provincial People's Hospital, Guangzhou, 510000, China. 14. Department of Diagnostic Radiology, Jinling Hospital, Medical School of Nanjing University, Nanjing, 210002, Jiangsu, China. cjr.luguangming@vip.163.com. 15. Department of Diagnostic Radiology, Jinling Hospital, Medical School of Nanjing University, Nanjing, 210002, Jiangsu, China. kevinzhlj@163.com.
Abstract
OBJECTIVES: To propose a novel functional Coronary Artery Disease-Reporting and Data System (CAD-RADS) category system integrated with coronary CT angiography (CCTA)-derived fractional flow reserve (FFRCT) and to validate its effect on therapeutic decision and prognosis in patients with coronary artery disease (CAD). METHODS: Firstly, we proposed a novel functional CAD-RADS and evaluated the performance of functional CAD-RADS for guiding treatment strategies with actual clinical treatment as a reference standard in a retrospective multicenter cohort with CCTA and invasive FFR performed in all patients (n = 466). Net reclassification improvement (NRI) of functional CAD-RADS over anatomical CAD-RADS was calculated. Secondly, the prognostic value of functional CAD-RADS in a prospective two-arm cohort (566 [FFRCT arm] vs. 567 [CCTA arm]) was calculated, after a 1-year follow-up, functional CAD-RADS in FFRCT arm (n = 513) and anatomical CAD-RADS in CCTA arm (n = 511) to determine patients at risk of adverse outcomes were compared with a Cox hazard proportional model. RESULTS: Functional CAD-RADS demonstrated superior value over anatomical CAD-RADS (AUC: 0.828 vs. 0.681, p < 0.001) and comparable performance to FFR (AUC: 0.828 vs. 0.848, p = 0.253) in guiding therapeutic decisions. Functional CAD-RADS resulted in the revision of management plan as determined by anatomical CAD-RADS in 30.0% of patients (n = 140) (NRI = 0.369, p < 0.001). Functional CAD-RADS was an independent predictor for 1-year outcomes with indexes of concordance of 0.795 and the corresponding value was 0.751 in anatomical CAD-RADS. CONCLUSION: The novel functional CAD-RADS gained incremental value in guiding therapeutic decision-making compared with anatomical CAD-RADS and comparable power in 1-year prognosis with anatomical CAD-RADS in a real-world scenario. KEY POINTS: • The novel functional CAD-RADS category system with FFRCT integrated into the anatomical CAD-RADS categories was originally proposed. • The novel functional CAD-RADS category system was validated superior value over anatomical CAD-RADS (AUC: 0.828 vs. 0.681, p < 0.001) in guiding therapeutic decisions and revised management plan in 30.0% of patients as determined by anatomical CAD-RADS (net reclassification improvement index = 0.369, p < 0.001). • Functional CAD-RADS was an independent predictor with an index of concordance of 0.795 and 0.751 in anatomical CAD-RADS for 1-year prognosis of adverse outcomes.
OBJECTIVES: To propose a novel functional Coronary Artery Disease-Reporting and Data System (CAD-RADS) category system integrated with coronary CT angiography (CCTA)-derived fractional flow reserve (FFRCT) and to validate its effect on therapeutic decision and prognosis in patients with coronary artery disease (CAD). METHODS: Firstly, we proposed a novel functional CAD-RADS and evaluated the performance of functional CAD-RADS for guiding treatment strategies with actual clinical treatment as a reference standard in a retrospective multicenter cohort with CCTA and invasive FFR performed in all patients (n = 466). Net reclassification improvement (NRI) of functional CAD-RADS over anatomical CAD-RADS was calculated. Secondly, the prognostic value of functional CAD-RADS in a prospective two-arm cohort (566 [FFRCT arm] vs. 567 [CCTA arm]) was calculated, after a 1-year follow-up, functional CAD-RADS in FFRCT arm (n = 513) and anatomical CAD-RADS in CCTA arm (n = 511) to determine patients at risk of adverse outcomes were compared with a Cox hazard proportional model. RESULTS: Functional CAD-RADS demonstrated superior value over anatomical CAD-RADS (AUC: 0.828 vs. 0.681, p < 0.001) and comparable performance to FFR (AUC: 0.828 vs. 0.848, p = 0.253) in guiding therapeutic decisions. Functional CAD-RADS resulted in the revision of management plan as determined by anatomical CAD-RADS in 30.0% of patients (n = 140) (NRI = 0.369, p < 0.001). Functional CAD-RADS was an independent predictor for 1-year outcomes with indexes of concordance of 0.795 and the corresponding value was 0.751 in anatomical CAD-RADS. CONCLUSION: The novel functional CAD-RADS gained incremental value in guiding therapeutic decision-making compared with anatomical CAD-RADS and comparable power in 1-year prognosis with anatomical CAD-RADS in a real-world scenario. KEY POINTS: • The novel functional CAD-RADS category system with FFRCT integrated into the anatomical CAD-RADS categories was originally proposed. • The novel functional CAD-RADS category system was validated superior value over anatomical CAD-RADS (AUC: 0.828 vs. 0.681, p < 0.001) in guiding therapeutic decisions and revised management plan in 30.0% of patients as determined by anatomical CAD-RADS (net reclassification improvement index = 0.369, p < 0.001). • Functional CAD-RADS was an independent predictor with an index of concordance of 0.795 and 0.751 in anatomical CAD-RADS for 1-year prognosis of adverse outcomes.
Authors: Ibrahim Danad; Jackie Szymonifka; Jos W R Twisk; Bjarne L Norgaard; Christopher K Zarins; Paul Knaapen; James K Min Journal: Eur Heart J Date: 2017-04-01 Impact factor: 35.855