{"title":"肌肉骨骼成像方面的近期主题侧重于人工智能的临床应用:放射科医生应如何对待和使用人工智能?","authors":"Taiki Nozaki, Masahiro Hashimoto, Daiju Ueda, Shohei Fujita, Yasutaka Fushimi, Koji Kamagata, Yusuke Matsui, Rintaro Ito, Takahiro Tsuboyama, Fuminari Tatsugami, Noriyuki Fujima, Kenji Hirata, Masahiro Yanagawa, Akira Yamada, Tomoyuki Fujioka, Mariko Kawamura, Takeshi Nakaura, Shinji Naganawa","doi":"10.1007/s11547-024-01947-z","DOIUrl":null,"url":null,"abstract":"<p><p>The advances in artificial intelligence (AI) technology in recent years have been remarkable, and the field of radiology is at the forefront of applying and implementing these technologies in daily clinical practice. Radiologists must keep up with this trend and continually update their knowledge. This narrative review discusses the application of artificial intelligence in the field of musculoskeletal imaging. For image generation, we focused on the clinical application of deep learning reconstruction and the recently emerging MRI-based cortical bone imaging. For automated diagnostic support, we provided an overview of qualitative diagnosis, including classifications essential for daily practice, and quantitative diagnosis, which can serve as imaging biomarkers for treatment decision making and prognosis prediction. Finally, we discussed current issues in the use of AI, the application of AI in the diagnosis of rare diseases, and the role of AI-based diagnostic imaging in preventive medicine as part of our outlook for the future.</p>","PeriodicalId":20817,"journal":{"name":"Radiologia Medica","volume":" ","pages":""},"PeriodicalIF":9.7000,"publicationDate":"2025-02-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Recent topics in musculoskeletal imaging focused on clinical applications of AI: How should radiologists approach and use AI?\",\"authors\":\"Taiki Nozaki, Masahiro Hashimoto, Daiju Ueda, Shohei Fujita, Yasutaka Fushimi, Koji Kamagata, Yusuke Matsui, Rintaro Ito, Takahiro Tsuboyama, Fuminari Tatsugami, Noriyuki Fujima, Kenji Hirata, Masahiro Yanagawa, Akira Yamada, Tomoyuki Fujioka, Mariko Kawamura, Takeshi Nakaura, Shinji Naganawa\",\"doi\":\"10.1007/s11547-024-01947-z\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>The advances in artificial intelligence (AI) technology in recent years have been remarkable, and the field of radiology is at the forefront of applying and implementing these technologies in daily clinical practice. Radiologists must keep up with this trend and continually update their knowledge. This narrative review discusses the application of artificial intelligence in the field of musculoskeletal imaging. For image generation, we focused on the clinical application of deep learning reconstruction and the recently emerging MRI-based cortical bone imaging. For automated diagnostic support, we provided an overview of qualitative diagnosis, including classifications essential for daily practice, and quantitative diagnosis, which can serve as imaging biomarkers for treatment decision making and prognosis prediction. Finally, we discussed current issues in the use of AI, the application of AI in the diagnosis of rare diseases, and the role of AI-based diagnostic imaging in preventive medicine as part of our outlook for the future.</p>\",\"PeriodicalId\":20817,\"journal\":{\"name\":\"Radiologia Medica\",\"volume\":\" \",\"pages\":\"\"},\"PeriodicalIF\":9.7000,\"publicationDate\":\"2025-02-24\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Radiologia Medica\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.1007/s11547-024-01947-z\",\"RegionNum\":1,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Radiologia Medica","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1007/s11547-024-01947-z","RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING","Score":null,"Total":0}
Recent topics in musculoskeletal imaging focused on clinical applications of AI: How should radiologists approach and use AI?
The advances in artificial intelligence (AI) technology in recent years have been remarkable, and the field of radiology is at the forefront of applying and implementing these technologies in daily clinical practice. Radiologists must keep up with this trend and continually update their knowledge. This narrative review discusses the application of artificial intelligence in the field of musculoskeletal imaging. For image generation, we focused on the clinical application of deep learning reconstruction and the recently emerging MRI-based cortical bone imaging. For automated diagnostic support, we provided an overview of qualitative diagnosis, including classifications essential for daily practice, and quantitative diagnosis, which can serve as imaging biomarkers for treatment decision making and prognosis prediction. Finally, we discussed current issues in the use of AI, the application of AI in the diagnosis of rare diseases, and the role of AI-based diagnostic imaging in preventive medicine as part of our outlook for the future.
期刊介绍:
Felice Perussia founded La radiologia medica in 1914. It is a peer-reviewed journal and serves as the official journal of the Italian Society of Medical and Interventional Radiology (SIRM). The primary purpose of the journal is to disseminate information related to Radiology, especially advancements in diagnostic imaging and related disciplines. La radiologia medica welcomes original research on both fundamental and clinical aspects of modern radiology, with a particular focus on diagnostic and interventional imaging techniques. It also covers topics such as radiotherapy, nuclear medicine, radiobiology, health physics, and artificial intelligence in the context of clinical implications. The journal includes various types of contributions such as original articles, review articles, editorials, short reports, and letters to the editor. With an esteemed Editorial Board and a selection of insightful reports, the journal is an indispensable resource for radiologists and professionals in related fields. Ultimately, La radiologia medica aims to serve as a platform for international collaboration and knowledge sharing within the radiological community.