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Methods: In this retrospective, multicenter study, 652 cardiac CT scans from 581 patients with lung cancer were analyzed using a commercial AI-CAD system. Detection rates were compared alone and combined with radiologist performance, with lesion characteristics evaluated. Results: Similar standalone detection rates were observed (76.2% vs 77.4%, P=0.551), while AI-CAD plus radiologists improved detection to 90.4% (P\u003C0.001).",{"@graph":69,"@context":122},[70,84,105],{"@type":71,"itemListElement":72},"BreadcrumbList",[73,77,79,82],{"item":74,"name":75,"@type":76,"position":8},"https://docshare.wps.com","Home","ListItem",{"item":78,"name":9,"@type":76,"position":14},"https://docshare.wps.com/document/",{"item":80,"name":40,"@type":76,"position":81},"https://docshare.wps.com/document/research-report/",3,{"item":83,"name":65,"@type":76,"position":19},"https://docshare.wps.com/document/retrospective-evaluation-of-an-ai-based-computer-aided-detection-algorithm-for-lung-cancer-detection-on-cardiac-ct-a-multicenter-study/349542/",{"url":83,"name":65,"@type":85,"image":86,"author":91,"headline":65,"publisher":94,"fileFormat":97,"inLanguage":63,"description":67,"dateModified":98,"datePublished":99,"encodingFormat":97,"isAccessibleForFree":100,"interactionStatistic":101},"DigitalDocument",{"url":87,"@type":88,"width":89,"height":90},"https://docshare.wps.com/thumbnails/retrospective-evaluation-of-an-ai-based-computer-aided-detection-algorithm-for-lung-cancer-detection-on-cardiac-ct-a-multicenter-study/349542.png","ImageObject",300,407,{"name":92,"@type":93},"RuangKosong","Person",{"url":74,"name":95,"@type":96},"DocShare","Organization","application/pdf","2026-09-23","2026-09-22",true,{"@type":102,"interactionType":103,"userInteractionCount":14},"InteractionCounter",{"@type":104},"ViewAction",{"@type":106,"mainEntity":107},"FAQPage",[108,114,118],{"name":109,"@type":110,"acceptedAnswer":111},"What was the main objective of the study?","Question",{"text":112,"@type":113},"To assess how effective an AI-based CAD system is at detecting incidental lung cancer on cardiac CT and to compare its performance with that of radiologists.","Answer",{"name":115,"@type":110,"acceptedAnswer":116},"How did the AI-CAD performance compare with radiologists when used alone?",{"text":117,"@type":113},"Radiologists and AI-CAD showed similar lung cancer detection rates (76.2% vs 77.4%, P=0.551).",{"name":119,"@type":110,"acceptedAnswer":120},"What improvement was observed when combining AI-CAD with radiologists?",{"text":121,"@type":113},"Combining radiologists and AI-CAD significantly increased the detection rate to 90.4% (P\u003C0.001) compared with radiologists alone.","https://schema.org",{"og:url":83,"og:type":124,"og:title":65,"og:site_name":95,"og:description":67},"article",{"robots":126,"canonical":83},"index,follow",{"doc_id":128,"site_id":62},349542,1790156041,{"code":4,"msg":5,"data":131},{"doc_id":128,"user_id":132,"nickname":92,"user_avatar":133,"doc_module":4,"category_id":39,"category_name":40,"doc_title":65,"doc_description":67,"doc_content":134,"file_id":135,"file_url":136,"file_type":137,"file_size":138,"view_count":14,"is_deleted":4,"is_public":8,"is_downloadable":8,"audit_status":8,"page_count":139,"language":140,"language_code":63,"site_id":62,"html_lang":63,"table_of_contents":141,"faqs":142,"seo_title":143,"seo_description":67,"update_tm":144,"read_time":36},962090883219,"https://ap-avatar.wpscdn.com/davatar_276721f389ce27ea32af1340a28f341c","J Korean Med Sci. 2026 Aug 17;41(32):e208 [https://doi.org/10.3346/jkms.2026.41.e208](https://doi.org/10.3346/jkms.2026.41.e208)[ ](https://doi.org/10.3346/jkms.2026.41.e208)eISSN 1598-6357·pISSN 1011-8934  \nOriginal Article  \nMedical Imaging  \nReceived: Jun 17, 2025  \nAccepted: Nov 20, 2025  \nPublished online: May 13, 2026  \nAddress for Correspondence:  \nYoung JooSuh, MD, PhD  \nDepartment of Radiology and Research Institute of Radiological Science, Severance Hospital, Yonsei University College of Medicine, 50-1 Yonsei-ro, Seodaemun-gu, Seoul 03722, Korea.  \nEmail: [rongzusuh@gmail.com](rongzusuh@gmail.com)  \nSuyon Chang, MD, PhD  \nDepartment of Radiology, Seoul St. Mary’s Hospital, College of Medicine, The Catholic University of Korea, 222 Banpo-daero, Seochogu, Seoul 06591, Korea. [Email: ohyes723@gmail.com](Email: ohyes723@gmail.com)  \n*Jinwoo Son and Jin Young Kim contributed equally to this work.  \n© 2026 The Korean Academy of Medical Sciences.  \nThis is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License ([https://](https://)[ ](https://)[creativecommons.org/licenses/by-nc/4.0/](creativecommons.org/licenses/by-nc/4.0/)) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.  \nRetrospective Evaluation of an  \nAI-Based Computer-Aided Detection Algorithm for Lung Cancer Detection on Cardiac CT: A Multicenter Study  \nJinwoo Son ,1* Jin Young Kim ,2,3* Suyon Chang ,4 and Young Joo Suh  1  \n1Department of Radiology and Research Institute of Radiological Science, Severance Hospital, Yonsei University College of Medicine, Seoul, Korea  \n2Department of Radiology, Dongsan Medical Center, Keimyung University College of Medicine, Daegu, Korea 3Department of Radiology and Imaging Sciences, Emory University, Atlanta, GA, USA  \n4Department of Radiology, Seoul St. Mary’s Hospital, College of Medicine, The Catholic University of Korea, Seoul, Korea  \nABSTRACT  \nBackground: To investigate the effectiveness of an artificial intelligence (AI)-based computer-aided detection (CAD) system in identifying incidental lung cancer on cardiac computed tomography (CT) scans and to compare its performance with that of radiologists. Methods: In this retrospective, multicenter study, 652 cardiac CT scans from 581 patients subsequently diagnosed with lung cancer were analyzed. A commercial AI-CAD system was employed to detect pulmonary lesions on cardiac CT. The detection rate of AI-CAD was compared to that of the radiologist, based on the radiology report, as well as to the detection rate when combining AI-CAD and the radiologist. The characteristics of the lesions detected and missed by the radiologist and AI-CAD were compared.  \nResults: Radiologists and AI-CAD demonstrated similar detection rates for lung cancer (76.2% vs. 77.4%, P = 0.551). However, combining radiologists and AI-CAD significantly improved the detection rate to 90.4%(P \u003C 0.001) compared to that of the radiologist alone. AI-CAD showed a higher detection rate in identifying small, peripheral, and partsolid lesions (all P \u003C 0.001). Furthermore, AI-CAD outperformed radiologists in detecting limited-stage lung cancer (80.3% vs. 74.7%, P = 0.006). Among lung cancer cases missed by radiologists, 94.2% experienced diagnostic delays of > 100 days, with 78.2% leading to stage progression. AI-CAD identified 58.5% of these diagnostic delays.  \nConclusion: AI-CAD demonstrated the potential to improve the detection rate of incidental lung cancer by identifying a subset of lesions that were initially overlooked by radiologists on cardiac CT. It exhibited particular strength in identifying early-stage cancers and small, subsolid lesions.  \nKeywords: Heart; Computed Tomography; Artificial Intelligence; Lung Cancer  \n[https://jkms.org](https://jkms.org) 1/16   \nAI-CAD Enhances Lung Cancer Detection on Cardiac CT  \nORCID iDs  \nJinwoo Son  [https://orcid.org/0000-","cbCaihaQNJqVr3Ue","https://ap.wps.com/l/cbCaihaQNJqVr3Ue","pdf",2421245,16,"English","# Background\n# Methods\n# Results\n## Detection performance\n## Lesion characteristics\n## Diagnostic delays\n# Conclusion","[{\"question\":\"What was the main objective of the study?\",\"answer\":\"To assess how effective an AI-based CAD system is at detecting incidental lung cancer on cardiac CT and to compare its performance with that of radiologists.\"},{\"question\":\"How did the AI-CAD performance compare with radiologists when used alone?\",\"answer\":\"Radiologists and AI-CAD showed similar lung cancer detection rates (76.2% vs 77.4%, P=0.551).\"},{\"question\":\"What improvement was observed when combining AI-CAD with radiologists?\",\"answer\":\"Combining radiologists and AI-CAD significantly increased the detection rate to 90.4% (P\\u003c0.001) compared with radiologists alone.\"}]","Retrospective Evaluation of an AI-Based Computer-Aided Detection Algorithm for Lung Cancer Detection on Cardiac CT - A Multicenter Study | PDF",1790084257]