Purpose:

First studies in photon-counting detector-CT prototypes have shown benefits of using ultra

high-resolution coronary computed tomography angiography (UHR-CCTA) over standard

resolution for stenosis detection. However, its use in clinical routine for risk stratification has

not yet been thoroughly investigated. The aim of the present study was to compare UHR-

CCTA on stenosis grading with standard resolution imaging in a clinical cohort with stable

chest pain.

Methods:

Retrospective analysis including all consecutive patients who had undergone UHR-CCTA for

the assessment of coronary artery disease (CAD) with an Agatston Score >0 at the University

Medical Center Mainz since 07/2022. Images were subsequently reconstructed with a slice

thickness of 0.6, 0.4 and UHR 0.2 mm. Stenoses were assessed based on the CAD - Reporting

and Data System (CAD-RADS 2.0). Classification differences between reconstructions were

evaluated using the related samples Friedman’s two-way analysis of variance by ranks. Post

hoc analysis was performed with Wilcoxon signed-rank tests.

Results:

The cohort included 114 patients (37% female; mean age 68±10 years; mean BMI 27±5

kg/m2; mean heart rate 65±10 bpm). Median Agatston score was 242 (range 71-786). CT

identified 190 stenoses with 25% non-calcified, 45% calcified and 30% mixed plaque

composition. Median per-patient CAD-RADS score was 2 (2-3). With decreasing slice

thickness, the degree of stenosis declined leading to a significant per-patient reclassification

to a lower CAD-RADS category (Figure 1, p<0.001). Compared to the standard 0.6 mm

reconstruction, UHR 0.2 mm reclassified 61% of patients in a lower CAD-RADS category, 31%

in the same category and 8% in a higher category. In the latter patients, the stenoses were

predominantly of non-calcified plaque composition.

Conclusions:
The increased spatial resolution of PCD-CCTA leads to clinically relevant CAD-

RADS reclassification rates in stable chest pain patients. Larger trials are necessary to further

investigate plaque characteristics influencing UHR-CCTA stenosis grading.