Abstract
Coronary computed tomography (CT) angiography (CCTA) is increasingly recognized for diagnosing obstructive coronary artery disease (CAD) among patients presenting with chest pain. In this review, we summarize the utility of CCTA to determine luminal stenosis and identifying coronary plaques with high-risk features. We review different scoring systems that can quantify total plaque burden including how artificial intelligence can facilitate more detailed plaque assessment. We discuss how CCTA can also be used to detect the hemodynamic significance of CAD lesions (fractional flow reserve CT and CT perfusion) and also local factors outside the vessel wall that may predispose to plaque rupture (fat attenuation index and wall shear stress). We conclude with technological advances in imaging acquisition using photon counting CT and post-image processing techniques especially those that can mitigate blooming artifacts.
| Original language | English (US) |
|---|---|
| Pages (from-to) | 12-20 |
| Number of pages | 9 |
| Journal | Progress in Cardiovascular Diseases |
| Volume | 75 |
| DOIs | |
| State | Published - Nov 1 2022 |
Keywords
- Artificial intelligence
- Blooming artifact
- Computed tomography perfusion
- Coronary artery calcification
- Coronary computed tomography
- Fractional flow reserve computed tomography
- Perivascular fat attenuation index
- Photon counting computed tomography
- Plaque burden
- Plaques with high-risk features
- Wall shear stress
ASJC Scopus subject areas
- Cardiology and Cardiovascular Medicine
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