Optimizing coronary computed tomography angiography image quality with motion-compensated reconstruction: a...

The recently developed motion-compensated reconstruction (MCR) algorithm provides a fully automated process to generate motion-corrected images. This study aimed to assess the image quality and radiation dose of prospective electrocardiogram (ECG)-triggered coronary computed tomography angiography (CCTA) using MCR on second-generation dual-layer spectral detector computed tomography (DLCT), and to investigate the influence of heart rate (HR) on the motion-correction effect of this algorithm.

This prospective study enrolled 73 patients who underwent CCTA on DLCT utilizing prospective ECG-gating. Patients were divided into two subgroups with a regular rhythm HR of <75 bpm and HR of ≥75 bpm and/or an irregular heart rhythm, respectively. Both subjective and objective quality were compared between images with and without MCR in the whole population and within each subgroup.

The overall mean effective dose was 3.3±0.7 mSv. MCR significantly enhanced subjective image quality and interpretability on the per-segment, per-artery and per-patient levels in the entire population and high HR and/or arrythmias group (P<0.05). In the low HR group, although images with MCR provided higher image quality scores (P<0.05), no significant difference was found in interpretability in the major coronary arteries (P>0.05). For objective image quality, the application of MCR significantly reduced image noise and improved signal-to-noise ratio and contrast-to-noise ratio in the whole population (P<0.05). Similar results were also observed for both subgroup analysis, except in the left main artery.

The integration of the MCR algorithm with prospective ECG-triggered mode performed using second-generation DLCT demonstrated good image quality and maintained reasonably low radiation exposure in CCTA. Notably, the MCR algorithm significantly improved motion artifact correction, particularly in patients with elevated or irregular HRs, highlighting its strong clinical utility in real-world scenarios where HR variability is common.