Artificial intelligence in atherosclerotic disease: Applications and trends

Abstract

Atherosclerotic cardiovascular disease (ASCVD) is the most common cause of death globally. Increasing amounts of highly diverse ASCVD data are becoming available and artificial intelligence (AI) techniques now bear the promise of utilizing them to improve diagnosis, advance understanding of disease pathogenesis, enable outcome prediction, assist with clinical decision making and promote precision medicine approaches. Machine learning (ML) algorithms in particular, are already employed in cardiovascular imaging applications to facilitate automated disease detection and experts believe that ML will transform the field in the coming years. Current review first describes the key concepts of AI applications from a clinical standpoint. We then provide a focused overview of current AI applications in four main ASCVD domains: coronary artery disease (CAD), peripheral arterial disease (PAD), abdominal aortic aneurysm (AAA), and carotid artery disease. For each domain, applications are presented with refer to the primary imaging modality used [e.g., computed tomography (CT) or invasive angiography] and the key aim of the applied AI approaches, which include disease detection, phenotyping, outcome prediction, and assistance with clinical decision making. We conclude with the strengths and limitations of AI applications and provide future perspectives.

An attention‐based deep learning method for right ventricular quantification using 2D echocardiography: Feasibility and accuracy

“…Machine learning applications, specifically DL, are increasing exponentially in cardiovascular medicine, 15 and particularly in cardiovascular imaging 16 . To our knowledge, we report the first non‐geometric‐based, DL method for volumetric and functional 2DE quantification of the RV.…”

Artificial Intelligence in Cardiology and Atherosclerosis in the Context of Precision Medicine: A Scoping Review

“…Also, the implementation of AI in PAD could be discussed more broadly [ 164 ]. Recently, an article raising a topic of AI in atherosclerosis has been published [ 165 ]. The article above however, discusses the problem more exhaustively, has been carefully planned and additionally focuses on precision medicine.…”

Familial hypercholesterolemia in children and the importance of early treatment

“…In a cross-sectional study of children with HoFH who underwent apheresis treatment from the age of 10, signs of atherosclerosis in the form of calcifications were observed in all of them on CTCA [ 25 ]. Next to CTCA, the use of artificial intelligence may also play a valuable role in assessment of atherosclerosis in the near future [ 26 ].…”