ReviewThe British journal of radiology2026
Advanced quantitative CT for coronary artery disease: integrating stenosis quantification, plaque quantification, and fractional flow reserve-CT.
Review in The British journal of radiology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Authors and funding
6 authors.
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Abstract
Coronary artery disease (CAD) continues to be a leading cause of death globally. Radiological evaluation of CAD generally consists of stenosis detection by cardiac CT angiography (CCTA). However, this approach can be inefficient and subject to interobserver variability. In this review, we explore the newest developments related to CAD evaluation by CCTA, with an emphasis on plaque quantification. Artificial intelligence-based quantitative CT offers an efficient and reproducible method to analyze plaque biomarkers that support more refined risk stratification for major adverse cardiovascular events. Artificial intelligence-based coronary stenosis quantification can streamline workflow and improve consistency. The utilization of a photon-counting detector CT has been demonstrated to enhance spatial resolution, thereby allowing more precise coronary lumen analysis and artifact reduction. Fractional flow reserve-CT delivers a noninvasive physiologic assessment of stenotic lesions. Finally, we discuss the impact of these changes on risk stratification and guiding preventive therapy as well as possible future directions in this rapidly evolving field.
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