Domenico Mastrodicasa, Marly van Assen, Merel Huisman, Tim Leiner, Eric E Williamson, Edward D Nicol, Bradley D Allen, Luca Saba, Rozemarijn Vliegenthart, Kate Hanneman
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引用次数: 0
Abstract
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.
期刊介绍:
Published regularly since 1923 by the Radiological Society of North America (RSNA), Radiology has long been recognized as the authoritative reference for the most current, clinically relevant and highest quality research in the field of radiology. Each month the journal publishes approximately 240 pages of peer-reviewed original research, authoritative reviews, well-balanced commentary on significant articles, and expert opinion on new techniques and technologies.
Radiology publishes cutting edge and impactful imaging research articles in radiology and medical imaging in order to help improve human health.