摘要
Currently,clinically available coronary CT angiography(CCTA)derived fractional flow reserve(CT-FFR)is time-consuming and complex.We propose a novel artificial intelligence-based fully-automated,on-site CT-FFR technology,which combines the automated coronary plaque segmentation and luminal extraction model with reduced order 3 dimentional(3D)computational fluid dynamics.A total of 463 consecutive patients with 600 vessels from the updated China CT-FFR study in Cohort 1 undergoing both CCTA and invasive fractional flow reserve(FFR)within 90 d were collected for diagnostic performance evaluation.For Cohort 2,a total of 901 chronic coronary syndromes patients with index CT-FFR and clinical outcomes at 3-year follow-up were retrospectively analyzed.In Cohort 3,the association between index CT-FFR from triple-rule-out CTA and major adverse cardiac events in patients with acute chest pain from the emergency department was further evaluated.The diagnostic accuracy of this CT-FFR in Cohort 1 was 0.82 with an area under the curve of 0.82 on a per-patient level.Compared with the manually dependent CT-FFR techniques,the operation time of this technique was substantially shortened by 3 times and the number of clicks from about 60 to 1.This CT-FFR technique has a highly successful(>99%)calculation rate and also provides superior prediction value for major adverse cardiac events than CCTA alone both in patients with chronic coronary syndromes and acute chest pain.Thus,the novel artificial intelligencebased fully automated,on-site CT-FFR technique can function as an objective and convenient tool for coronary stenosis functional evaluation in the real-world clinical setting.
作者
郭邦俊
姜孟春
郭翔
唐春香
钟健
陆梦洁
刘春雨
张晓蕾
乔红艳
周帆
许棚棚
薛艺
郑敏文
侯阳
王怡宁
张佳胤
张波
张代民
徐磊
胡秀华
周长圣
李建华
杨志文
毛新生
卢光明
张龙江
Bangjun Guo;Mengchun Jiang;Xiang Guo;Chunxiang Tang;Jian Zhong;Mengjie Lu;Chunyu Liu;Xiaolei Zhang;Hongyan Qiao;Fan Zhou;Pengpeng Xu;Yi Xue;Minwen Zheng;Yang Hou;Yining Wang;Jiayin Zhang;Bo Zhang;Daimin Zhang;Lei Xu;Xiuhua Hu;Changsheng Zhou;Jianhua Li;Zhiwen Yang;Xinsheng Mao;Guangming Lu;Longjiang Zhang(Department of Radiology,Jinling Hospital,Affiliated Hospital of Medical School,Nanjing University,Nanjing 210002,China;Department of Radiology,Affiliated Hospital of Jining Medical University,Jining 272007,China;Department of Radiology,Xijing Hospital,Fourth Military Medical University,Xi’an 733399,China;Department of Radiology,Shengjing Hospital of China Medical University,Shenyang 110022,China;Department of Radiology,Peking Union Medical College Hospital,Chinese Academy of Medical Sciences and Peking Union Medical College,Beijing 100005,China;Institute of Diagnostic and Interventional Radiology,and Department of Cardiology,Shanghai Jiao Tong University Affiliated Sixth People’s Hospital,Shanghai 200235,China;Department of Radiology,Jiangsu Taizhou People’s Hospital,Taizhou 225399,China;Department of Cardiology,Nanjing First Hospital,Nanjing Medical University,Nanjing 210012,China;Department of Radiology,Beijing Anzhen Hospital,Capital Medical University,Beijing 100029,China;Department of Radiology,Sir Run Run Shaw Hospital,Zhejiang University School of Medicine,Hangzhou 310020,China;Department of Cardiology,Jinling Hospital,Affiliated Hospital of Medical School,Nanjing University,Nanjing 210002,China;Shukun(Beijing)Network Technology Co.,Ltd.,Beijing 102200,China)
基金
supported by the National Key Research and Development Program of China(2022YFC2010004)
Jiangsu Province Key Project of Comprehensive Prevention and Control of Chronic Diseases(BE2020699)
Top Talent Support Program for young and middle-aged people of Wuxi Health Committee(BJ2023044).
