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서울대학교병원

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Radiology, Feb 2025, 314 (2) | https://doi.org/10.1148/radiol.240650 AI Applications for Thoracic Imaging: Considerations for Best Practice

Eui Jin Hwang¹, Jin Mo Goo¹, Chang Min Park¹

¹Department of Radiology, Seoul National University Hospital and Seoul National University College of Medicine, 101 Daehak-ro, Jongno-gu, Seoul 03080, Korea.

Address correspondence to: C.M.P.

Abstract

Artificial intelligence (AI) technology is rapidly being introduced into thoracic radiology practice. Current representative use cases for AI in thoracic imaging show cumulative evidence of effectiveness. These include AI assistance for reading chest radiographs and low-dose (1.5-mSv) chest CT scans for lung cancer screening and triaging pulmonary embolism on chest CT scans. Other potential use cases are also under investigation, including filtering out normal chest radiographs, monitoring reading errors, and automated opportunistic screening of nontarget diseases. However, implementing AI tools in daily practice requires establishing practical strategies. Practical AI implementation will require objective on-site performance evaluation, institutional information technology infrastructure integration, and postdeployment monitoring. Meanwhile, the remaining challenges of adopting AI technology need to be addressed. These challenges include educating radiologists and radiology trainees, alleviating liability risk, and addressing potential disparities due to the uneven distribution of data and AI technology. Finally, next-generation AI technology represented by large language models (LLMs), including multimodal models, which can interpret both text and images, is expected to innovate the current landscape of AI in thoracic radiology practice. These LLMs offer opportunities ranging from generating text reports from images to explaining examination results to patients. However, these models require more research into their feasibility and efficacy.

논문정보

형식Review Paper
게재일2025년 02월 (BRIC 등록일 2025-03-13)
연구진국내 연구진
분야 의약학 > 응용의학

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