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Review
. 2025 Oct 6:S1936-878X(25)00475-9.
doi: 10.1016/j.jcmg.2025.07.022. Online ahead of print.

Photon-Counting Computed Tomography in Cardiac Imaging

Arthur Shiyovich  1 , Avinainder Singh  1 , Camila V Blair  1 , Rhanderson Cardoso  1 , Daniel Huck  1 , Gary Peng  1 , Leslee J Shaw  2 , Jonathon A Leipsic  3 , Christoph Gräni  4 , Charalambos Antoniades  5 , Pál Maurovich-Horvat  6 , Eric E Williamson  7 , Filippo Cademartiri  8 , Stephan Achenbach  9 , Ron Blankstein  10
Affiliations
Review

Photon-Counting Computed Tomography in Cardiac Imaging

Arthur Shiyovich et al. JACC Cardiovasc Imaging. .

Abstract

Coronary computed tomography (CT) angiography plays a pivotal role in the diagnosis, risk stratification, and treatment of patients with known or suspected coronary artery disease. However, conventional CT technologies are limited by spatial resolution, artifact susceptibility, and radiation exposure. Photon-counting computed tomography (PCCT) introduces substantial technological improvements over conventional CT. This includes improved spatial and contrast resolution, energy discrimination, and reduction of various artifacts. As a result, PCCT enables superior coronary lumen and plaque evaluation, even in complex cases with severe calcification or smaller coronary stents. Beyond the coronary arteries, PCCT offers improved visualization of cardiac anatomy and myocardial tissue characterization with the potential to reduce downstream testing, improve diagnosis and treatment, and ultimately improve clinical outcomes. PCCT is poised to become the dominant technology for cardiovascular CT; however, challenges such as high costs, increased data demands, and a need for more validation, standardized image acquisition, and post-processing protocols remain. This review explores the technical principles of PCCT, its advantages over conventional CT, and its current and potential future applications in cardiac imaging, highlighting opportunities for future research.

Keywords: coronary artery disease; diagnosis; image quality; photon-counting CT.

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Conflict of interest statement

Funding Support and Author Disclosures Dr Shiyovich has received honoraria from Pfizer. Dr Singh is supported by National Institutes of Health (NIH) Grant: 5T32HL007604-39. Dr Gräni has received funding from the Swiss National Science Foundation, InnoSuisse, Center for Artificial Intelligence in Medicine University Bern, GAMBIT foundation, Novartis Foundation for Medical-Biological Research, Swiss Heart Foundation, Schmieder-Bohrisch Foundation, and the Gottfried and Julia Bangerter-Rhyner Foundation. Funding to Dr Gräni’s institution was received by Alnylam Pharmaceuticals, AstraZeneca, Pfizer, and Bayer without impact on his personal remuneration. Prof Antoniades declares several patents (US10,695,023B2, PCT/GB2017/053262, GB2018/1818049.7, GR20180100490, GR20180100510) licensed to Caristo Diagnostics. He is the immediate past-chair of the British Atherosclerosis Society, and he is founder, shareholder, and director of Caristo Diagnostics, a University of Oxford Spinout company. Prof Antoniades declares honoraria from Amarin, Silence Therapeutics, Abcentra, Amgen, Nodthera, Novartis, Lilly, Novo Nordisk, and Caristo Diagnostics; and is supported by British Heart Foundation grants (FS/CRTF/23/24460, CH/F/21/90009, and RG/F/21/110040) and the NIHR Oxford Biomedical Research Centre. Dr Blankstein has received research support/consultant fees from Amgen Inc, Novartis Inc, Heartflow Inc, and Nanox AI; and has been a consultant for Siemens Inc. and Cartisto Inc. Dr Leipsic has received consultant fees and stock options from Heartflow and Circle CVI. Prof Dr Cademartiri has received consultant and speakers fees from Siemens Healthineers and Bracco. Dr Maurovich-Horvat has received an institutional research grant and speakers fee from Siemens Healthineers. Dr Huck is supported by American Heart Association Career Development Award 23CDA1037589. All other authors have reported that they have no relationships relevant to the contents of this paper to disclose.

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