电生理学家的心血管成像技术。

IF 9.4 Q1 CARDIAC & CARDIOVASCULAR SYSTEMS
Nature cardiovascular research Pub Date : 2025-05-01 Epub Date: 2025-05-13 DOI:10.1038/s44161-025-00648-8
Albert J Rogers, Olga Reynbakh, Adnan Ahmed, Mina K Chung, Rishi Charate, Hirad Yarmohammadi, Rakesh Gopinathannair, Hassan Khan, Dhanunjaya Lakkireddy, Miguel Leal, Uma Srivatsa, Natalia Trayanova, Elaine Y Wan
{"title":"电生理学家的心血管成像技术。","authors":"Albert J Rogers, Olga Reynbakh, Adnan Ahmed, Mina K Chung, Rishi Charate, Hirad Yarmohammadi, Rakesh Gopinathannair, Hassan Khan, Dhanunjaya Lakkireddy, Miguel Leal, Uma Srivatsa, Natalia Trayanova, Elaine Y Wan","doi":"10.1038/s44161-025-00648-8","DOIUrl":null,"url":null,"abstract":"<p><p>Rapid technological advancements in noninvasive and invasive imaging including echocardiography, computed tomography, magnetic resonance imaging and positron emission tomography have allowed for improved anatomical visualization and precise measurement of cardiac structure and function. These imaging modalities allow for evaluation of how cardiac substrate changes, such as myocardial wall thickness, fibrosis, scarring and chamber enlargement and/or dilation, have an important role in arrhythmia initiation and perpetuation. Here, we review the various imaging techniques and modalities used by clinical and basic electrophysiologists to study cardiac arrhythmia mechanisms, periprocedural planning, risk stratification and precise delivery of ablation therapy. We also review the use of artificial intelligence and machine learning to improve identification of areas for triggered activity and isthmuses in reentrant arrhythmias, which may be favorable ablation targets.</p>","PeriodicalId":74245,"journal":{"name":"Nature cardiovascular research","volume":" ","pages":"514-525"},"PeriodicalIF":9.4000,"publicationDate":"2025-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Cardiovascular imaging techniques for electrophysiologists.\",\"authors\":\"Albert J Rogers, Olga Reynbakh, Adnan Ahmed, Mina K Chung, Rishi Charate, Hirad Yarmohammadi, Rakesh Gopinathannair, Hassan Khan, Dhanunjaya Lakkireddy, Miguel Leal, Uma Srivatsa, Natalia Trayanova, Elaine Y Wan\",\"doi\":\"10.1038/s44161-025-00648-8\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>Rapid technological advancements in noninvasive and invasive imaging including echocardiography, computed tomography, magnetic resonance imaging and positron emission tomography have allowed for improved anatomical visualization and precise measurement of cardiac structure and function. These imaging modalities allow for evaluation of how cardiac substrate changes, such as myocardial wall thickness, fibrosis, scarring and chamber enlargement and/or dilation, have an important role in arrhythmia initiation and perpetuation. Here, we review the various imaging techniques and modalities used by clinical and basic electrophysiologists to study cardiac arrhythmia mechanisms, periprocedural planning, risk stratification and precise delivery of ablation therapy. We also review the use of artificial intelligence and machine learning to improve identification of areas for triggered activity and isthmuses in reentrant arrhythmias, which may be favorable ablation targets.</p>\",\"PeriodicalId\":74245,\"journal\":{\"name\":\"Nature cardiovascular research\",\"volume\":\" \",\"pages\":\"514-525\"},\"PeriodicalIF\":9.4000,\"publicationDate\":\"2025-05-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Nature cardiovascular research\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1038/s44161-025-00648-8\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"2025/5/13 0:00:00\",\"PubModel\":\"Epub\",\"JCR\":\"Q1\",\"JCRName\":\"CARDIAC & CARDIOVASCULAR SYSTEMS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Nature cardiovascular research","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1038/s44161-025-00648-8","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2025/5/13 0:00:00","PubModel":"Epub","JCR":"Q1","JCRName":"CARDIAC & CARDIOVASCULAR SYSTEMS","Score":null,"Total":0}
引用次数: 0

摘要

超声心动图、计算机断层扫描、磁共振成像和正电子发射断层扫描等非侵入性和侵入性成像技术的快速发展,使得心脏结构和功能的解剖可视化和精确测量得以改进。这些成像方式可以评估心脏底物的变化,如心肌壁厚度、纤维化、瘢痕形成和心室扩大和/或扩张,在心律失常的发生和延续中发挥重要作用。在这里,我们回顾了临床和基础电生理学家用于研究心律失常机制、围手术期计划、风险分层和消融治疗的精确交付的各种成像技术和模式。我们还回顾了人工智能和机器学习的应用,以提高对可再入性心律失常触发活动和峡部区域的识别,这些区域可能是有利的消融目标。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Cardiovascular imaging techniques for electrophysiologists.

Rapid technological advancements in noninvasive and invasive imaging including echocardiography, computed tomography, magnetic resonance imaging and positron emission tomography have allowed for improved anatomical visualization and precise measurement of cardiac structure and function. These imaging modalities allow for evaluation of how cardiac substrate changes, such as myocardial wall thickness, fibrosis, scarring and chamber enlargement and/or dilation, have an important role in arrhythmia initiation and perpetuation. Here, we review the various imaging techniques and modalities used by clinical and basic electrophysiologists to study cardiac arrhythmia mechanisms, periprocedural planning, risk stratification and precise delivery of ablation therapy. We also review the use of artificial intelligence and machine learning to improve identification of areas for triggered activity and isthmuses in reentrant arrhythmias, which may be favorable ablation targets.

求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
CiteScore
5.70
自引率
0.00%
发文量
0
×
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:481959085
Book学术官方微信