研究目的
To assess the effect of a second-generation motion correction algorithm on the diagnostic accuracy of coronary computed tomography angiography in patients with increased heart rates.
研究成果
The second-generation motion correction algorithm (MC2) significantly improves image quality, interpretability, and diagnostic accuracy for coronary CT angiography in patients with increased heart rates compared to standard and first-generation algorithms, reducing false positives and enhancing specificity and positive predictive value across various analysis levels.
研究不足
The study has a small sample size from a single center, excludes patients with high heart rate variability (≥20 bpm), irregular rhythms, atrial fibrillation, and severe coronary calcification, which may limit generalizability. The MC2 algorithm is vendor-specific, and disease prevalence was high, potentially affecting diagnostic accuracy assessments.
1:Experimental Design and Method Selection:
A prospective diagnostic study was conducted to compare the image quality and diagnostic performance of three reconstruction algorithms (STD, MC1, MC2) for CCTA in patients with elevated heart rates, using ICA as the reference standard.
2:Sample Selection and Data Sources:
Eighty-one symptomatic cardiac patients with heart rates ≥75 bpm and regular rhythm were enrolled; exclusion criteria included arrhythmias, high heart rate variability, prior stents or bypass surgery, and other contraindications.
3:List of Experimental Equipment and Materials:
A 256-detector row CT scanner (Revolution CT, GE Healthcare), contrast agent iopromide (Ultravist, Bayer Schering Pharma), saline solution, and workstations for image reconstruction (AW
4:6 Advantage Workstation, GE Healthcare). Experimental Procedures and Operational Workflow:
CCTA was performed using a prospectively ECG-triggered single-beat protocol with specific scanning parameters (e.g., z-coverage 12-16 cm, tube voltage 100/120 kV). Images were reconstructed with STD, MC1, and MC2 algorithms. Two radiologists assessed image quality and stenosis using a 4-point scale and 18-segment model.
5:Data Analysis Methods:
Statistical analysis included Wilcoxon tests for image quality scores, McNemar's tests for interpretability and diagnostic performance, and ROC curve analysis using SPSS and MedCalc software.
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