OBJECTIVE. Motion artifact can reduce the diagnostic accuracy of coronary CT angiography (CCTA) for coronary artery disease (CAD). The purpose of this study was to compare the diagnostic performance of an algorithm dedicated to correcting coronary motion artifact with the performance of standard reconstruction methods in a prospective international multicenter study. SUBJECTS AND METHODS. Patients referred for clinically indicated invasive coronary angiography (ICA) for suspected CAD prospectively underwent an investigational CCTA examination free from heart rate–lowering medications before they underwent ICA. Blinded core laboratory interpretations of motion-corrected and standard reconstructions for obstructive CAD (= 50% stenosis) were compared with ICA findings. Segments unevaluable owing to artifact were considered obstructive. The primary endpoint was per-subject diagnostic accuracy of the intracycle motion correction algorithm for obstructive CAD found at ICA. RESULTS. Among 230 patients who underwent CCTA with the motion correction algorithm and standard reconstruction, 92 (40.0%) had obstructive CAD on the basis of ICA findings. At a mean heart rate of 68.0 ± 11.7 beats/min, the motion correction algorithm reduced the number of nondiagnostic scans compared with standard reconstruction (20.4% vs 34.8%; p < 0.001). Diagnostic accuracy for obstructive CAD with the motion correction algorithm (62%; 95% CI, 56–68%) was not significantly different from that of standard reconstruction on a per-subject basis (59%; 95% CI, 53–66%; p = 0.28) but was superior on a per-vessel basis: 77% (95% CI, 74–80%) versus 72% (95% CI, 69–75%) (p = 0.02). The motion correction algorithm was superior in subgroups of patients with severely obstructive (= 70%) stenosis, heart rate = 70 beats/min, and vessels in the atrioventricular groove. CONCLUSION. The motion correction algorithm studied reduces artifacts and improves diagnostic performance for obstructive CAD on a per-vessel basis and in selected subgroups on a per-subject basis.
Bibliographical noteFunding Information:
D. Andreini is a member of the speakers bureau of GE Healthcare and receives funding for Centro Cardiologico Monzino from Bracco and GE Healthcare. G. Pontone receives research grants from GE Healthcare, Medtronic, Ayer, Bracco, and HeartFlow. P. Carrascosa receives speaking fees from and serves as a consultant for GE Healthcare. H. J. Chang receives funding from the Leading Foreign Research Institute Recruitment Program through the National Research Foundation of Korea funded by the Ministry of Science, ICT, and Future Planning (grant 2012027176). J. Leipsic serves as a consultant to HeartFlow and Circle Cardiovascular Imaging and receives speaking fees from GE Healthcare. J. K. Min receives funding from the National Institutes of Health (grants R01 HL111141, R01 HL115150, R01 118019, and U01 HL 105907), the Qatar National Priorities Research Program (grant 09-370-3-089), and GE Healthcare; serves as a consultant to HeartFlow; serves on the scientific advisory board of Arineta; and has an equity interest in MDDX.
All Science Journal Classification (ASJC) codes
- Radiology Nuclear Medicine and imaging