Advances in the Assessment of Coronary Artery Disease Activity with PET/CT and CTA.
Jacek KwiecinskiRafał R WolnyAlicja ChwalaPiotr SlomkaPublished in: Tomography (Ann Arbor, Mich.) (2023)
Non-invasive testing plays a pivotal role in the diagnosis, assessment of progression, response to therapy, and risk stratification of coronary artery disease. Although anatomical plaque imaging by computed tomography angiography (CTA) and ischemia detection with myocardial perfusion imaging studies are current standards of care, there is a growing body of evidence that imaging of the processes which drive atherosclerotic plaque progression and rupture has the potential to further enhance risk stratification. In particular, non-invasive imaging of coronary plaque inflammation and active calcification has shown promise in this regard. Positron emission tomography (PET) with newly-adopted radiotracers provides unique insights into atheroma activity acting as a powerful independent predictor of myocardial infarctions. Similarly, by providing a quantitative measure of coronary inflammation, the pericoronary adipose tissue density (PCAT) derived from standard coronary CTA enhances cardiac risk prediction and allows re-stratification over and above current state-of-the-art assessments. In this review, we shall discuss the recent advances in the non-invasive methods of assessment of disease activity by PET and CTA, highlighting how these methods could improve risk stratification and ultimately benefit patients with coronary artery disease.
Keyphrases
- coronary artery disease
- positron emission tomography
- pet ct
- high resolution
- computed tomography
- coronary artery
- disease activity
- percutaneous coronary intervention
- coronary artery bypass grafting
- adipose tissue
- cardiovascular events
- rheumatoid arthritis
- systemic lupus erythematosus
- healthcare
- oxidative stress
- pet imaging
- stem cells
- ankylosing spondylitis
- chronic kidney disease
- rheumatoid arthritis patients
- type diabetes
- acute coronary syndrome
- insulin resistance
- heart failure
- magnetic resonance imaging
- cardiovascular disease
- palliative care
- machine learning
- quality improvement
- juvenile idiopathic arthritis
- atrial fibrillation
- contrast enhanced