Detection of calcified plaques: comparison between coronary CT angiography and thin-slice non-contrast CT with deep...

To investigate whether coronary CT angiography (CCTA) misses calcified plaques detected by thin-slice non-contrast CT (NCCT).

This study included patients from two sites in the DISCHARGE trial for whom both 0.5 mm thin-slice NCCT and CCTA were available. Plaques on CCTA were defined as missed if they showed no spatial overlap with NCCT-detected plaques after deep learning-aided co-registration. Comparisons of plaque volume, density, and local coronary luminal attenuation between plaques missed and those detected by CCTA were performed using the Mann-Whitney U-test. In addition, the presence of these plaques on standard calcium scoring CT was assessed. Interobserver agreement was assessed using the intraclass correlation coefficient and Bland‒Altman analysis.

This study included 45 patients (40% female, mean age 62 ± 11 years), in whom CCTA missed 37.6% of calcified plaques detected by NCCT (121/322). Missing calcified plaques on CCTA misclassified 8.9% of patients (4/45) as having no plaques. Compared with detected plaques, plaques missed by CCTA were both significantly smaller in volume (3.0 mm³ [IQR, 1.5-4.9] vs. 9.2 mm³ [IQR, 4.3-21.9], p < 0.001) and had lower density (212.7 HU [IQR, 174.5-242.4] vs. 292.7 HU [IQR, 243.2-361.3], p < 0.001). Only 44.0% of plaques (53/121) missed by CCTA were detected by standard calcium scoring CT. Interobserver analysis demonstrated excellent agreement for calcified plaque volume on CCTA (ICC = 0.91) and NCCT (ICC = 0.98).

CCTA missed more than one-third of coronary calcified plaques that are identifiable on co-registered thin-slice NCCT, which suggests an underutilized role of thin-slice NCCT in clinical practice.

Question Accurate detection of all coronary plaques is crucial for risk stratification. CCTA misses calcified plaques, which are detectable by thin-slice non-contrast CT (NCCT). Findings CCTA misses over one-third of calcified plaques, nearly half of which are also missed by calcium scoring CT. NCCT detected these calcified plaques. Clinical relevance Deep learning-aided registration enables multimodal CCTA-NCCT assessment, improving detection of calcified plaques overlooked by CCTA alone and providing more accurate plaque burden quantification that may support better clinical decision-making, which should be investigated in future studies.