Abstract
Advancements in cardiac computed tomography angiography (CCTA) have enabled the extraction of physiological data from an anatomy-based imaging modality. This review outlines the key methodologies for deriving fractional flow reserve (FFR) from CCTA, with a focus on two primary methods: 1) computational fluid dynamics-based FFR (CT-FFR) and 2) plaque-derived ischemia assessment using artificial intelligence and quantitative plaque metrics. These techniques have expanded the role of CCTA beyond anatomical assessment, allowing for concurrent evaluation of coronary physiology without the need for invasive testing. This review provides an overview of the principles, workflows, and limitations of each technique and aims to inform on the current state and future direction of non-invasive coronary physiology assessment.
| Original language | English |
|---|---|
| Pages (from-to) | 390-396 |
| Number of pages | 7 |
| Journal | Journal of cardiovascular computed tomography |
| Volume | 19 |
| Issue number | 4 |
| Early online date | 2025 |
| DOIs | |
| Publication status | Published - 1 Jul 2025 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 3 Good Health and Well-being
Keywords
- Computational fractional flow reserve
- Coronary artery disease
- Coronary computed tomography angiography
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