Impact of an intra-cycle motion correction algorithm on overall evaluability and diagnostic accuracy of computed tomography coronary angiography.

Abstract

The aim of this study was to evaluate the impact of a novel intra-cycle motion correction algorithm (MCA) on overall evaluability and diagnostic accuracy of cardiac computed tomography coronary angiography (CCT). From a cohort of 900 consecutive patients referred for CCT for suspected coronary artery disease (CAD), we enrolled 160 (18 %) patients (mean age 65.3 ± 11.7 years, 101 male) with at least one coronary segment classified as non-evaluable for motion artefacts. The CCT data sets were evaluated using a standard reconstruction algorithm (SRA) and MCA and compared in terms of subjective image quality, evaluability and diagnostic accuracy. The mean heart rate during the examination was 68.3 ± 9.4 bpm. The MCA showed a higher Likert score (3.1 ± 0.9 vs. 2.5 ± 1.1, p < 0.001) and evaluability (94%vs.79 %, p < 0.001) than the SRA. In a 45-patient subgroup studied by clinically indicated invasive coronary angiography, specificity, positive predictive value and accuracy were higher in MCA vs. SRA in segment-based and vessel-based models, respectively (87%vs.73 %, 50%vs.34 %, 85%vs.73 %, p < 0.001 and 62%vs.28 %, 66%vs.51 % and 75%vs.57 %, p < 0.001). In a patient-based model, MCA showed higher accuracy vs. SCA (93%vs.76 %, p < 0.05). MCA can significantly improve subjective image quality, overall evaluability and diagnostic accuracy of CCT. Cardiac computed tomographic coronary angiography (CCT) allows non-invasive evaluation of coronary arteries. Intra-cycle motion correction algorithm (MCA) allows for compensation of coronary motion. An MCA improves image quality, CCT evaluability and diagnostic accuracy.