Decision Support Tools, Systems, and Artificial Intelligence in Cardiac Imaging

Abstract

Noninvasive cardiac imaging is widely used for the diagnosis and management of cardiac patients. The increasing demand for cardiac imaging begins to exceed the number of available interpreting physicians, leaving less time to interpret studies. In addition, the busy clinician is facing the increasingly daunting task of keeping abreast of current medical advancements and the ongoing changes in disease diagnosis and therapy. Committing to memory and recalling such large volumes of information is challenging and is responsible for difficulties in adopting the rapid changes in imaging practice, and is likely partially responsible for errors in patient diagnosis and management. Diagnostic errors rank high in the cause of death in the United States, and are more common than any other medical error and are responsible for most malpractice claims. Most of these errors are related to cognitive errors. The use of artificial intelligence systems that can serve as complementary methods to assist humans with decision making can potentially prevent these errors. The past decades witnessed the development and integration of these tools, which can assist physicians with image interpretation. These tools work to optimize image quality for better visualization and accompany all imaging modalities, starting from patient selection for the appropriate test, patient preparation, image acquisition, processing, and finally interpretation. Current and future directions for technologies that support cardiac imaging physicians are discussed in this review.