ArticleThe international journal of cardiovascular imaging2026
Clinical evaluation of a motion correction software based on partial angle reconstruction in coronary CT angiography.
Article in The international journal of cardiovascular imaging, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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Who cites it
1 citing paper in PubMed.
- Three-dimensional image metric maps for characterizing local image changes associated with AI-based motion correction in coronary CT.Radiological physics and technology · 2026Article
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8 authors.
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No grant is acknowledged in the PubMed record.
Abstract
To evaluate a new deep learning (DL) motion correction (MC) software based on partial angle reconstruction (PAR) to reduce motion artifacts in patients with increased heart rate (HR) in coronary CT angiography (CCTA). This retrospective single-center study included consecutive patients with HR > 70 bpm who underwent single-beat wide-area-detector CCTA over a 6-month period. A DL PAR-based MC software was applied to each image, and corrected and uncorrected reconstructions were scored by two blinded independent cardiothoracic radiologists for coronary motion artifact severity. Scores were obtained on a per-vessel and on a per-patient level using a 5-point Likert scale (1 = non-interpretable, 2 = severe, 3 = moderate, 4 = mild, 5 = no artifacts). Scoring differences were analyzed with Chi-Squared test and interrater agreement with Gwet agreement coefficients. 62 patients (35 female) with (mean ± std.dev.) BMI 29.4 ± 6.8 kg/m2 and HR 81.9 ± 13.1 bpm were included. Without MC, the number of cases scored 3 or higher on a per-patient level were 40/62 (64.5%) and 43/62 (69.4%), respectively for reader 1 and 2. With MC, they improved to 50/62 (80.6%) and 55/62 (88.7%), respectively for reader 1 and 2. Improvements in scoring were significant for both readers (p < 0.02). Per-vessel scores followed a similar trend, but showed significance for both readers only for the right coronary artery (p < 0.001). The fraction of diagnostically-interpretable cases (score ≥ 2) were 91.9% (uncorrected) and 98.4% (motion-corrected) (reader 1), and 93.5% (uncorrected) and 96.8% (motion-corrected) (reader 2). Interrater agreement was between (0.67-0.78). The MC software significantly improved image quality by reducing coronary motion artifacts in CCTA patients with increased HR.
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