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Retrospective study reveals that a misalignment correction algorithm significantly reduces breathing artifacts in post-bypass surgery patients, indicating improved diagnostic image quality.
The purpose of this study was to evaluate whether a misalignment correction algorithm reduces artifacts from breathing in patients undergoing computed tomography angiography (CTA) early after coronary artery bypass graft (CABG) surgery. In this retrospective study, consecutive patients undergoing CTA early after CABG surgery between November 2023 and March 2025 were screened. Patients exhibiting relevant breathing artifacts on standard reconstructions were included for the evaluation. CTA was acquired in the ECG-gated sequential mode on a dual-source CT. For each patient, standard reconstructions were compared with those using a misalignment correction algorithm designed to resolve discontinuities between adjacent image stacks (ZeeFree). Two blinded readers assessed artifacts across six anatomical regions (bypass grafts, coronary arteries, thoracic aorta, pulmonary trunk, lung/trachea, and sternum) using a 4-point visual analogue scale. Among 680 patients scanned at a median of 4 days (IQR 2–8 days) after CABG surgery, 75 patients (11%, mean age, 67.7 ± 8.4 years, 12 females, 63 males) with a total of 205 bypass grafts presented relevant breathing artifacts in CTA and were included. Median duration of CTA acquisition was 6.9 s (IQR 5.5–9.5 s). Inter-reader agreement of image quality was substantial to almost perfect across all anatomical structures (weighted kappa: 0.796–0.971, p < 0.001). The misalignment correction algorithm significantly reduced artifact severity across all anatomical regions for both readers compared to standard reconstructions ( p < 0.001 for all, overall median artifact score for standard reconstruction: 2 [IQR 1–3] vs. ZeeFree reconstruction: 1 [IQR 1–1]). Breathing-induced artifacts in CTA of patients undergoing imaging early after CABG surgery occurs frequently and can be significantly reduced using a novel misalignment correction algorithm.
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Nikolova et al. (2026) studied this question.
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