Coronary Atherosclerotic Plaque Burden Assessment by Computed Tomography and Its Clinical Implications.
Nishant VatsaChristian C Faaborg-AndersenTiffany DongMichael J BlahaLeslee J ShawRaymundo A QuintanaPublished in: Circulation. Cardiovascular imaging (2024)
Recent studies have demonstrated that coronary plaque burden carries greater prognostic value in predicting adverse atherosclerotic cardiovascular disease outcomes than myocardial ischemia, thereby challenging the existing paradigm. Advances in plaque quantification through both noncontrast and contrast-enhanced computed tomography (CT) methods have led to earlier and more cost-effective detection of coronary disease compared with traditional stress testing. The 2 principal techniques of noninvasive coronary plaque quantification assessment are coronary artery calcium scoring by noncontrast CT and coronary CT angiography, both of which correlate with disease burden on invasive angiography. Plaque quantification from these imaging modalities has shown utility in risk stratification and prognostication of adverse cardiovascular events, leading to increased incorporation into clinical practice guidelines and preventive care pathways. Furthermore, due to their expanding clinical value, emerging technologies such as artificial intelligence are being integrated into plaque quantification platforms, placing more advanced measures of plaque burden at the forefront of coronary plaque evaluation. In this review, we summarize recent clinical data on coronary artery calcium scoring and coronary CT angiography plaque quantification in the evaluation of adverse atherosclerotic cardiovascular disease in patients with and without chest pain, highlight how these methods compare to invasive quantification approaches, and directly compare the performance characteristics of coronary artery calcium scoring and coronary CT angiography.
Keyphrases
- coronary artery disease
- coronary artery
- cardiovascular events
- computed tomography
- contrast enhanced
- pulmonary artery
- cardiovascular disease
- dual energy
- artificial intelligence
- magnetic resonance imaging
- positron emission tomography
- image quality
- aortic stenosis
- machine learning
- magnetic resonance
- diffusion weighted
- type diabetes
- high resolution
- deep learning
- metabolic syndrome
- left ventricular
- atrial fibrillation
- pain management
- pulmonary hypertension
- adipose tissue
- aortic valve
- drug induced