人工智能在心脏CT和MRI中的应用：欧洲心血管研究基金会（ESCR）、欧洲心脏影像学会（EuSoMII）、北美心血管影像学会（NASCI）、心血管计算机断层扫描学会（SCCT）、心血管磁共振学会（SCMR）、美国医学影像学会（SIIM）和北美放射学会（RSNA）的科学声明。
Use of AI in Cardiac CT and MRI: A Scientific Statement from the ESCR, EuSoMII, NASCI, SCCT, SCMR, SIIM, and RSNA.
作者信息
Mastrodicasa Domenico, van Assen Marly, Huisman Merel, Leiner Tim, Williamson Eric E, Nicol Edward D, Allen Bradley D, Saba Luca, Vliegenthart Rozemarijn, Hanneman Kate
机构信息
From the Department of Radiology, University of Washington, UW Medical Center-Montlake, Seattle, Wash (D.M.); Department of Radiology, OncoRad/Tumor Imaging Metrics Core (TIMC), University of Washington, Seattle, Wash (D.M.); Department of Radiology and Imaging Sciences, Emory University, Atlanta, Ga (M.v.A.); Department of Radiology and Nuclear Medicine, Radboud University Medical Center, Nijmegen, the Netherlands (M.H.); Department of Radiology, Mayo Clinic, Rochester, Minn (T.L., E.E.W.); Departments of Cardiology and Radiology, Royal Brompton Hospital, London, United Kingdom (E.D.N.); School of Biomedical Engineering and Imaging Sciences, King's College, London, United Kingdom (E.D.N.); Department of Radiology, Northwestern University Feinberg School of Medicine, Chicago, Ill (B.D.A.); Department of Radiology, University of Cagliari, Cagliari, Italy (L.S.); Department of Radiology, University of Groningen, University Medical Center Groningen, Hanzeplein 1 Postbus 30 001, 9700 RB Groningen, the Netherlands (R.V.); Department of Medical Imaging, University Medical Imaging Toronto, University of Toronto, Toronto, Ontario, Canada (K.H.); and Toronto General Hospital Research Institute, University Health Network, University of Toronto, Toronto, Ontario, Canada (K.H.).
出版信息
Radiology. 2025 Jan;314(1):e240516. doi: 10.1148/radiol.240516.
Artificial intelligence (AI) offers promising solutions for many steps of the cardiac imaging workflow, from patient and test selection through image acquisition, reconstruction, and interpretation, extending to prognostication and reporting. Despite the development of many cardiac imaging AI algorithms, AI tools are at various stages of development and face challenges for clinical implementation. This scientific statement, endorsed by several societies in the field, provides an overview of the current landscape and challenges of AI applications in cardiac CT and MRI. Each section is organized into questions and statements that address key steps of the cardiac imaging workflow, including ethical, legal, and environmental sustainability considerations. A technology readiness level range of 1 to 9 summarizes the maturity level of AI tools and reflects the progression from preliminary research to clinical implementation. This document aims to bridge the gap between burgeoning research developments and limited clinical applications of AI tools in cardiac CT and MRI.
人工智能（AI）为心脏成像工作流程的多个步骤提供了有前景的解决方案，从患者和检查选择到图像采集、重建和解读，一直延伸到预后评估和报告。尽管已经开发了许多心脏成像AI算法，但AI工具正处于不同的发展阶段，并且在临床应用上面临挑战。这一由该领域多个学会认可的科学声明概述了AI在心脏CT和MRI中的当前现状及挑战。每个部分都围绕着涉及心脏成像工作流程关键步骤的问题和陈述展开，包括伦理、法律和环境可持续性方面的考量。技术就绪水平范围为1至9，总结了AI工具的成熟程度，并反映了从初步研究到临床应用的进展。本文档旨在弥合AI工具在心脏CT和MRI领域中新兴研究进展与有限临床应用之间的差距。
Zotero 插件