Radiology: Cardiothoracic Imaging Highlights 2024.

IF 3.8 Q1 RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING
Roberta Catania, Aprateem Mukherjee, Jordan H Chamberlin, Francisco Calle, Preethi Philomina, Domenico Mastrodicasa, Bradley D Allen, Dominika Suchá, Suhny Abbara, Kate Hanneman
{"title":"<i>Radiology: Cardiothoracic Imaging</i> Highlights 2024.","authors":"Roberta Catania, Aprateem Mukherjee, Jordan H Chamberlin, Francisco Calle, Preethi Philomina, Domenico Mastrodicasa, Bradley D Allen, Dominika Suchá, Suhny Abbara, Kate Hanneman","doi":"10.1148/ryct.250064","DOIUrl":null,"url":null,"abstract":"<p><p><i>Radiology: Cardiothoracic Imaging</i> publishes research, technical developments, and reviews related to cardiac, vascular, and thoracic imaging. The current review article, led by the <i>Radiology: Cardiothoracic Imaging</i> trainee editorial board, highlights the most impactful articles published in the journal between November 2023 and October 2024. The review encompasses various aspects of cardiac, vascular, and thoracic imaging related to coronary artery disease, cardiac MRI, valvular imaging, congenital and inherited heart diseases, thoracic imaging, lung cancer, artificial intelligence, and health services research. Key highlights include the role of CT fractional flow reserve analysis to guide patient management, the role of MRI elastography in identifying age-related myocardial stiffness associated with increased risk of heart failure, review of MRI in patients with cardiovascular implantable electronic devices and fractured or abandoned leads, imaging of mitral annular disjunction, specificity of the Lung Imaging Reporting and Data System version 2022 for detecting malignant airway nodules, and a radiomics-based reinforcement learning model to analyze serial low-dose CT scans in lung cancer screening. Ongoing research and future directions include artificial intelligence tools for applications such as plaque quantification using coronary CT angiography and growing understanding of the interconnectedness of environmental sustainability and cardiovascular imaging. <b>Keywords:</b> CT, MRI, CT-Coronary Angiography, Cardiac, Pulmonary, Coronary Arteries, Heart, Lung, Mediastinum, Mitral Valve, Aortic Valve, Artificial Intelligence © RSNA, 2025.</p>","PeriodicalId":21168,"journal":{"name":"Radiology. Cardiothoracic imaging","volume":"7 3","pages":"e250064"},"PeriodicalIF":3.8000,"publicationDate":"2025-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Radiology. Cardiothoracic imaging","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1148/ryct.250064","RegionNum":0,"RegionCategory":null,"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

Radiology: Cardiothoracic Imaging publishes research, technical developments, and reviews related to cardiac, vascular, and thoracic imaging. The current review article, led by the Radiology: Cardiothoracic Imaging trainee editorial board, highlights the most impactful articles published in the journal between November 2023 and October 2024. The review encompasses various aspects of cardiac, vascular, and thoracic imaging related to coronary artery disease, cardiac MRI, valvular imaging, congenital and inherited heart diseases, thoracic imaging, lung cancer, artificial intelligence, and health services research. Key highlights include the role of CT fractional flow reserve analysis to guide patient management, the role of MRI elastography in identifying age-related myocardial stiffness associated with increased risk of heart failure, review of MRI in patients with cardiovascular implantable electronic devices and fractured or abandoned leads, imaging of mitral annular disjunction, specificity of the Lung Imaging Reporting and Data System version 2022 for detecting malignant airway nodules, and a radiomics-based reinforcement learning model to analyze serial low-dose CT scans in lung cancer screening. Ongoing research and future directions include artificial intelligence tools for applications such as plaque quantification using coronary CT angiography and growing understanding of the interconnectedness of environmental sustainability and cardiovascular imaging. Keywords: CT, MRI, CT-Coronary Angiography, Cardiac, Pulmonary, Coronary Arteries, Heart, Lung, Mediastinum, Mitral Valve, Aortic Valve, Artificial Intelligence © RSNA, 2025.

放射学:心胸影像学亮点2024。
《放射学:心胸影像》发表与心脏、血管和心胸影像相关的研究、技术发展和综述。目前的综述文章由《Radiology: Cardiothoracic Imaging》实习编辑委员会领导,重点介绍了2023年11月至2024年10月期间在该杂志上发表的最具影响力的文章。这篇综述涵盖了与冠状动脉疾病相关的心脏、血管和胸部成像、心脏MRI、瓣膜成像、先天性和遗传性心脏病、胸部成像、肺癌、人工智能和健康服务研究的各个方面。主要亮点包括CT血流储备分数分析对指导患者管理的作用,MRI弹性成像在识别与心力衰竭风险增加相关的年龄相关心肌僵硬的作用,对心血管植入式电子设备和断裂或废弃导联患者的MRI回顾,二尖瓣环分离的成像,肺成像报告和数据系统版本2022检测恶性气道结节的特异性。以及基于放射组学的强化学习模型,用于分析肺癌筛查中的一系列低剂量CT扫描。正在进行的研究和未来的方向包括用于应用的人工智能工具,例如使用冠状动脉CT血管造影进行斑块量化,以及对环境可持续性和心血管成像之间相互联系的日益了解。关键词:CT、MRI、CT冠状动脉造影、心、肺、冠状动脉、心、肺、纵隔、二尖瓣、主动脉瓣、人工智能©RSNA, 2025
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 求助全文
来源期刊
CiteScore
20.40
自引率
1.40%
发文量
0
期刊介绍:
×
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
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
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 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:604180095
Book学术官方微信