BACKGROUND: A recent simulation study proposed that stenosis measurements on coronary computed tomography (CT) angiography are influenced by the improved spatial resolution of photon-counting detector (PCD)-CT. The aim of the current study was to evaluate the impact of ultrahigh-spatial-resolution (UHR) on coronary stenosis measurements and Coronary Artery Disease Reporting and Data System (CAD-RADS) reclassification rates in patients undergoing coronary CT angiography on both PCD-CT and energy-integrating detector (EID)-CT and to compare measurements against quantitative coronary angiography. METHODS: Patients with coronary calcification on EID-CT (collimation, 192×0.6 mm) were prospectively enrolled for a research coronary CT angiography with UHR PCD-CT (collimation, 120×0.2 mm) within 30 days (between April 1, 2023 and January 31, 2024). PCD-CT was acquired with the same or lower CT dose index and equivalent contrast media volume as EID-CT. Percentage diameter stenosis (PDS) for calcified, partially calcified, and noncalcified lesions were compared between scanners. Patient-level reclassification rates for CAD-RADS were evaluated. The accuracy of PDS measurements was validated against quantitative coronary angiography in patients who underwent invasive coronary angiography. RESULTS: In total, PDS of 278 plaques were quantified in 49 patients (calcified, 202; partially calcified, 51; noncalcified, 25). PCD-CT-based PDS values were lower than EID-CT measurements for calcified (45.1±20.7 versus 54.6±19.2%; P <0.001) and partially calcified plaques (44.3±19.6 versus 54.9±20.0%; P <0.001), without significant differences for noncalcified lesions (39.1±15.2 versus 39.0±16.0%; P =0.98). The reduction in stenosis degrees led to a 49.0% (24/49) reclassification rate to a lower CAD-RADS with PCD-CT. In a subset of 12 patients with 56 lesions, UHR–based PDS values showed higher agreement with quantitative coronary angiography (mean difference, 7.3%; limits of agreement, −10.7%/25.2%) than EID-CT measurements (mean difference, 17.4%; limits of agreement, −6.9%/41.7%). CONCLUSIONS: Compared with conventional EID-CT, UHR PCD-CT results in lower PDS values and more accurate stenosis measurements in coronary plaques with calcified components and leads to a substantial Coronary Artery Disease Reporting and Data System reclassification rate in 49.0% of patients.

Coronary plaque quantification using ultrahigh-spatial-resolution photon-counting detector CT reduced visualized total plaque volume by nearly one-third and improved the reproducibility of low-attenuation plaque measurements compared with that of energy-integrating detector CT.

Quantitative coronary stenosis and plaque volumes have demonstrated intra-individual differences between ultrahigh-resolution (UHR) photon-counting detector (PCD)-CT and energy-integrating detector (EID)-CT. This study aimed to assess the impact of UHR PCD-CT on semiquantitative scores of coronary artery disease (CAD) burden compared with EID-CT. Patients undergoing coronary CT angiography (CCTA) on an EID-CT system for stable chest pain or pre-transcatheter aortic valve replacement evaluation were prospectively enrolled for UHR PCD-CT scan within 30 days. Both datasets were visually evaluated using five established semiquantitative scores: Segment Involvement Score (SIS), Segment Stenosis Score (SSS), Multivessel Aggregate Stenosis Score (MVAS), CCTA-adapted Leaman score (CT-LeSc), and Coronary Artery Disease Reporting and Data System (CAD-RADS). Additionally, the total number of detected plaques and high-risk features were reported (positive remodeling, spotty calcification, low-attenuation, and napkin-ring sign). The cohort comprised 46 patients (37 men, 68.4 ​± ​6.9 years). When assessing stenosis severity, PCD-CT showed lower SSS (3.5 [1.3-5.0] vs 6.5 [3.0-9.8], p ​< ​0.001), MVAS (5.5 [4.0-7.0] vs 7.0 [5.0-9.0], p ​< ​0.001), and CT-LeSc (10.4 [8.5-13.9] vs 11.2 [8.8-15.4], p ​= ​0.032). Furthermore, 52 ​% (24/46) of patients were reclassified to a lower CAD-RADS category compared to EID-CT. In terms of CAD extent, PCD-CT demonstrated higher SIS (8.0 [6.0-9.0] vs 7.0 [6.0-8.8], p ​= ​0.018) and plaque count (9.0 [7.0-13.8] vs 7.0 [7.0-9.8] p ​< ​0.001). Positive remodeling was less frequent in PCD-CT datasets (2.0 [1.0-4.3] vs 1.0 [0.0-3.0], p ​= ​0.012), with no significant differences in other high-risk features. The use of UHR PCD-CT detects less severe, but more extensive CAD compared to EID-CT. The effect of such CCTA-based differences on individual risk stratification needs further investigation.