Longjiang Zhang , Qian Chen , Chun Xiang Tang , Zhao Shi , Tongyuan Liu , Chunhong Hu , Bin Lu , Zhengyu Jin , Guangming Lu
{"title":"人工智能在冠状动脉计算机断层造影中的研究与应用共识","authors":"Longjiang Zhang , Qian Chen , Chun Xiang Tang , Zhao Shi , Tongyuan Liu , Chunhong Hu , Bin Lu , Zhengyu Jin , Guangming Lu","doi":"10.1016/j.imed.2024.11.006","DOIUrl":null,"url":null,"abstract":"<div><div>Coronary computed tomography angiography (CCTA), which enables noninvasive assessment of luminal stenosis and atherosclerotic plaque components, has become the first-line technique for evaluating coronary artery disease. Artificial intelligence (AI) has the potential to revolutionize the CCTA workflow. However, it is crucial to evaluate the effectiveness and feasibility of AI algorithms before their clinical deployment. This expert consensus proposes three fundamental elements of research designs of AI in CCTA and offers corresponding recommendations. The consensus also reviews the existing evidence on AI applications in CCTA and provides recommendations on the current clinical applications of AI, including image acquisition and reconstruction, postprocessing, diagnosis, prognostic prediction, guiding prevention and treatment, and cardiovascular disease prevention.</div></div>","PeriodicalId":73400,"journal":{"name":"Intelligent medicine","volume":"5 3","pages":"Pages 234-242"},"PeriodicalIF":6.9000,"publicationDate":"2025-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Consensus on the research and application of artificial intelligence in coronary computed tomography angiography\",\"authors\":\"Longjiang Zhang , Qian Chen , Chun Xiang Tang , Zhao Shi , Tongyuan Liu , Chunhong Hu , Bin Lu , Zhengyu Jin , Guangming Lu\",\"doi\":\"10.1016/j.imed.2024.11.006\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><div>Coronary computed tomography angiography (CCTA), which enables noninvasive assessment of luminal stenosis and atherosclerotic plaque components, has become the first-line technique for evaluating coronary artery disease. Artificial intelligence (AI) has the potential to revolutionize the CCTA workflow. However, it is crucial to evaluate the effectiveness and feasibility of AI algorithms before their clinical deployment. This expert consensus proposes three fundamental elements of research designs of AI in CCTA and offers corresponding recommendations. The consensus also reviews the existing evidence on AI applications in CCTA and provides recommendations on the current clinical applications of AI, including image acquisition and reconstruction, postprocessing, diagnosis, prognostic prediction, guiding prevention and treatment, and cardiovascular disease prevention.</div></div>\",\"PeriodicalId\":73400,\"journal\":{\"name\":\"Intelligent medicine\",\"volume\":\"5 3\",\"pages\":\"Pages 234-242\"},\"PeriodicalIF\":6.9000,\"publicationDate\":\"2025-08-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Intelligent medicine\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S2667102625000609\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Intelligent medicine","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2667102625000609","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS","Score":null,"Total":0}
Consensus on the research and application of artificial intelligence in coronary computed tomography angiography
Coronary computed tomography angiography (CCTA), which enables noninvasive assessment of luminal stenosis and atherosclerotic plaque components, has become the first-line technique for evaluating coronary artery disease. Artificial intelligence (AI) has the potential to revolutionize the CCTA workflow. However, it is crucial to evaluate the effectiveness and feasibility of AI algorithms before their clinical deployment. This expert consensus proposes three fundamental elements of research designs of AI in CCTA and offers corresponding recommendations. The consensus also reviews the existing evidence on AI applications in CCTA and provides recommendations on the current clinical applications of AI, including image acquisition and reconstruction, postprocessing, diagnosis, prognostic prediction, guiding prevention and treatment, and cardiovascular disease prevention.