Recent topics in musculoskeletal imaging focused on clinical applications of AI: How should radiologists approach and use AI?

IF 9.7 1区 医学 Q1 RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING Radiologia Medica Pub Date : 2025-02-24 DOI:10.1007/s11547-024-01947-z
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
{"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}
引用次数: 0

Abstract

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.

查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
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?
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
Radiologia Medica
Radiologia Medica 医学-核医学
CiteScore
14.10
自引率
7.90%
发文量
133
审稿时长
4-8 weeks
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.
期刊最新文献
Spatial-demographic analysis model for brain metastases distribution. The radiologist as an independent "third party" to the patient and clinicians in the era of generative AI. Predictive value of tumoral and peritumoral radiomic features in neoadjuvant chemotherapy response for breast cancer: a retrospective study. Recent topics in musculoskeletal imaging focused on clinical applications of AI: How should radiologists approach and use AI? Shapley-based saliency maps improve interpretability of vertebral compression fractures classification: multicenter study.
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1