Artificial intelligence in coronary artery calcium score: rationale, different approaches, and outcomes.
Journal:
The international journal of cardiovascular imaging
Published Date:
May 3, 2024
Abstract
Almost 35 years after its introduction, coronary artery calcium score (CACS) not only survived technological advances but became one of the cornerstones of contemporary cardiovascular imaging. Its simplicity and quantitative nature established it as one of the most robust approaches for atherosclerotic cardiovascular disease risk stratification in primary prevention and a powerful tool to guide therapeutic choices. Groundbreaking advances in computational models and computer power translated into a surge of artificial intelligence (AI)-based approaches directly or indirectly linked to CACS analysis. This review aims to provide essential knowledge on the AI-based techniques currently applied to CACS, setting the stage for a holistic analysis of the use of these techniques in coronary artery calcium imaging. While the focus of the review will be detailing the evidence, strengths, and limitations of end-to-end CACS algorithms in electrocardiography-gated and non-gated scans, the current role of deep-learning image reconstructions, segmentation techniques, and combined applications such as simultaneous coronary artery calcium and pulmonary nodule segmentation, will also be discussed.
Authors
Keywords
Artificial Intelligence
Cardiac-Gated Imaging Techniques
Computed Tomography Angiography
Coronary Angiography
Coronary Artery Disease
Coronary Vessels
Deep Learning
Humans
Predictive Value of Tests
Prognosis
Radiographic Image Interpretation, Computer-Assisted
Reproducibility of Results
Severity of Illness Index
Vascular Calcification