The purpose of this review is to serve as a concise learning tool for clinicians interested in quickly learning more about cardiac magnetic resonance imaging (CMR) and its physical principles. There is heavy coverage of the basic physical fundamentals of CMR as well as updates on the history, clinical indications, cost-effectiveness, role of artificial intelligence in CMR, and examples of common late gadolinium enhancement (LGE) patterns. This literature review was performed by searching the PubMed database for the most up-to-date literature regarding these topics. Relevant, less up-to-date articles, covering the history and physics of CMR, were also obtained from the PubMed database. Clinical indications for CMR include adult congenital heart disease, cardiac ischemia, cardiomyopathies, and heart failure. CMR has a projected cost-benefit ratio of 0.58, leading to potential savings for patients. Despite its utility, CMR has some drawbacks including long image processing times, large space requirements for equipment, and patient discomfort during imaging. Artificial intelligence-based algorithms can address some of these drawbacks by decreasing image processing times and may have reliable diagnostic capabilities. CMR is quickly rising as a high-resolution, non-invasive cardiac imaging modality with an increasing number of clinical indications. Thanks to technological advancements, especially in artificial intelligence, the benefits of CMR often outweigh its drawbacks.
Keywords: artificial intelligence in radiology; cardiac imaging-mri; cost-utility analysis; physics of cardiac mri; radiology history.
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