Abstract

Abstract Since the approval of the first dual-source photon-counting detector CT (PCD-CT) in the fall of 2021, significant insights have been gained in its application for cardiovascular imaging. This review aims to provide a comprehensive overview of the current state of knowledge and the growing body of research literature, illustrating innovative applications and perspectives through case examples. We conducted a structured literature review, identifying relevant studies via Google Scholar and PubMed, using the keywords “photon-counting detector”, “cardiovascular CT”, “cardiac CT”, and “ultra-high-resolution CT”. We analyzed studies published since January 2015. Additionally, we integrated our own clinical experiences and case examples. In addition to the well-known benefit of increased temporal resolution offered by dual-source scanners, dual-source PCD-CT provides three key advantages: 1) Optimized geometric dose efficiency with an improved contrast-to-noise ratio, 2) intrinsic spectral sensitivity, and 3) the ability for ultrahigh-resolution CT. This technology enables improved image quality or radiation dose reduction in established cardiovascular protocols. Its use in non-invasive cardiac diagnostics for obese patients, those with a high plaque burden, or after stent implantation appears technically feasible, potentially expanding the scope of CT. The spectral sensitivity also allows tailored image acquisition, reducing metallic artifacts and contrast agent doses in patients with renal impairment. Early studies and clinical experience support these potential applications of PCD-CT in cardiovascular diagnostics, suggesting workflow optimization and improved patient management. However, challenges remain, including high costs, large data volumes, somewhat longer reconstruction times, and technical difficulties in combining spectral sensitivity with ultra-high resolution. Prospective randomized studies with clinical endpoints are lacking to confirm the clear advantage over conventional scanners. Future research should focus on endpoint-based studies and robust cost-benefit analyses to evaluate the potential of this technology and facilitate its evidence-based integration in clinical practice.