Artificial Intelligence in Coronary Artery Calcium Scoring.
Afolasayo A AromiwuraDinesh K KalraPublished in: Journal of clinical medicine (2024)
Cardiovascular disease (CVD), particularly coronary heart disease (CHD), is the leading cause of death in the US, with a high economic impact. Coronary artery calcium (CAC) is a known marker for CHD and a useful tool for estimating the risk of atherosclerotic cardiovascular disease (ASCVD). Although CACS is recommended for informing the decision to initiate statin therapy, the current standard requires a dedicated CT protocol, which is time-intensive and contributes to radiation exposure. Non-dedicated CT protocols can be taken advantage of to visualize calcium and reduce overall cost and radiation exposure; however, they mainly provide visual estimates of coronary calcium and have disadvantages such as motion artifacts. Artificial intelligence is a growing field involving software that independently performs human-level tasks, and is well suited for improving CACS efficiency and repurposing non-dedicated CT for calcium scoring. We present a review of the current studies on automated CACS across various CT protocols and discuss consideration points in clinical application and some barriers to implementation.
Keyphrases
- artificial intelligence
- coronary artery
- cardiovascular disease
- image quality
- machine learning
- deep learning
- dual energy
- computed tomography
- big data
- contrast enhanced
- pulmonary artery
- coronary artery disease
- positron emission tomography
- type diabetes
- healthcare
- endothelial cells
- primary care
- randomized controlled trial
- high throughput
- heart failure
- mesenchymal stem cells
- atrial fibrillation
- aortic valve
- pulmonary arterial hypertension
- decision making