Abstract:

Photon-counting computed tomography （PCCT） is a revolutionary technological breakthrough in CT imaging over the past decade. Compared with traditional energy-integrating detector CT, PCCT performs imaging at the single-photon level at the detector layer, offering higher spatial resolution, fewer artifacts, and more accurate spectral imaging. PCCT shows great application potential in the diagnosis of cardiovascular diseases, especially in reducing beam-hardening artifacts and achieving ultra-high spatial resolution, which can further improve the specifi-city and positive predictive value in the assessment of coronary artery stenosis. This also contributes to the accurate evaluation of in-stent restenosis， reliable identification of plaque components, and characterization of vulnerable plaques. PCCT can obtain stable calcium scoring at low radiation doses. The virtual non-contrast （VNC） algorithm supports reliable calcium scoring from contrast-enhanced images, further reducing the radiation dose. PCCT can improve the reproducibility of features in pericoronary fat radiomics analysis. The VNC algorithm can accurately assess epicardial fat volume and significantly reduce radiation dose. Spectral images acquired by PCCT at high temporal resolution enable single-phase measurement of myocardial extracellular volume. They can also provide multidimensional anatomical information and functional parameters for preoperative planning and postoperative follow-up of transcatheter aortic valve implantation/replacement （TAVI/TAVR）. Although PCCT holds great potential in the diagnosis of coronary artery disease and quantitative analysis of myocardial tissues, its quantitative results remain affected by reconstruction parameters such as convolution kernels, virtual monoenergetic levels, and iterative strength. Currently, a lack of unified standards and validation from multicenter studies, along with the increased radiation dose in ultra-high-resolution modes, still limits its wide clinical application. Future studies should focus on large-sample, multicenter prospective studies to optimize imaging parameters, standardize post-processing workflows, and integrate artificial intelligence tools to enhance the clinical application of PCCT in cardiovascular disease diagnosis.

Key words: Photon-counting computed tomography, Cardiovascular disease, Cardiac CT angiography