Comparison of image quality of 64-slice multidetector CT coronary CT angiography using automated and manual multiphase methods for the determination of optimal phases for image reconstruction in patients with various mean heart rates

Reduced artifacts and improved diagnostic value of 640-slice computed tomography in patients with cardiac pacemakers

Objective

The aim of this study was to compare the feasibility of 640-slice with 64-slice computed tomography (CT) coronary angiography for diagnosing coronary lesions in patients with pacemakers.

Methods

Forty-five and 50 patients with pacemakers and with suspected or known coronary artery disease underwent 64-slice (64 group) and 640-slice (640 group) CT scans, respectively. All segments of the vessels were evaluated according to the 15-segment model recommended by the American Heart Association.

Results

The incidence of moderate or severe artifacts was significantly lower (7.27% vs. 32.17%) and the diagnosable rate for coronary lesions was higher (98.91% vs. 94.19%) in the 640 compared with the 64 group. In the 64 group, the incidence of artifacts in patients with a heart rate >65 bpm (20.98%) was higher than in those with a heart rate <65 bpm (15.67%), although the difference was not significant, while the incidence of artifacts was significantly higher in patients with heart arrhythmia (21.40%) compared with in those with normal heart rhythm (15.09%).

Conclusions

Among patients with pacemakers and a higher heart rate or heart arrhythmia, 640-slice CT may be more effective than 64-slice CT for diagnosing coronary lesions, by reducing moderate and severe artifacts.

Clinical evaluation of new automatic coronary-specific best cardiac phase selection algorithm for single-beat coronary CT angiography

The aim of this study was to evaluate the workflow efficiency of a new automatic coronary-specific reconstruction technique (Smart Phase, GE Healthcare—SP) for selection of the best cardiac phase with least coronary motion when compared with expert manual selection (MS) of best phase in patients with high heart rate. A total of 46 patients with heart rates above 75 bpm who underwent single beat coronary computed tomography angiography (CCTA) were enrolled in this study. CCTA of all subjects were performed on a 256-detector row CT scanner (Revolution CT, GE Healthcare, Waukesha, Wisconsin, US). With the SP technique, the acquired phase range was automatically searched in 2% phase intervals during the reconstruction process to determine the optimal phase for coronary assessment, while for routine expert MS, reconstructions were performed at 5% intervals and a best phase was manually determined. The reconstruction and review times were recorded to measure the workflow efficiency for each method. Two reviewers subjectively assessed image quality for each coronary artery in the MS and SP reconstruction volumes using a 4-point grading scale. The average HR of the enrolled patients was 91.1±19.0bpm. A total of 204 vessels were assessed. The subjective image quality using SP was comparable to that of the MS, 1.45±0.85 vs 1.43±0.81 respectively (p = 0.88). The average time was 246 seconds for the manual best phase selection, and 98 seconds for the SP selection, resulting in average time saving of 148 seconds (60%) with use of the SP algorithm. The coronary specific automatic cardiac best phase selection technique (Smart Phase) improves clinical workflow in high heart rate patients and provides image quality comparable with manual cardiac best phase selection. Reconstruction of single-beat CCTA exams with SP can benefit the users with less experienced in CCTA image interpretation.

Reproducibility and clinical potential of myocardial mass at risk calculated by a novel software utilizing cardiac computed tomography information

To select the best revascularization strategy a correct understanding of the ischemic territory and the coronary anatomy is crucial. Stress myocardial perfusion single photon emission computed tomography (SPECT) is the gold standard to assess ischemia, however, SPECT has important limitations such as lack of coronary anatomical information or false negative results due to balanced ischemia in multi-vessel disease. Angiographic scores are based on anatomical characteristics of coronary arteries but they lack information on the extent of jeopardized myocardium. Cardiac computed tomography (CCT) has the ability to evaluate the coronary anatomy and myocardium in one sequence, which is theoretically the ideal method to assess the myocardial mass at risk (MMAR) for any target lesion located at any point in the coronary tree. In this study we analyzed MMAR of the three main coronary arteries and three major side branches; diagonal (Dx), obtuse marginal (OM), and posterior descending artery (PDA) in 42 patients with normal coronary arteries using an algorithm based on the Voronoi method. The distribution of MMAR among the three main coronary arteries was 44.3 ± 5.6 % for the left anterior descending artery, 28.2 ± 7.3 % for the left circumflex artery, and 26.8 ± 8.6 % for the right coronary artery. MMAR of the three major side branches was 11.3 ± 3.9 % for the Dx, 12.6 ± 5.2 % for the OM and 10.2 ± 3.4 % for the PDA. Intra- and inter-observer analysis showed excellent correlation (r = 0.97; p < 0.0001 and r = 0.95; p < 0.0001, respectively). In conclusion, CCT-based MMAR assessment is reliable and may offer important information for selection of the optimal revascularization procedure.

Computer-aided CT coronary artery stenosis detection: comparison with human reading and quantitative coronary angiography

To evaluate computer-aided stenosis detection for computed tomography coronary angiography (CTA) in comparison with human reading and conventional coronary angiography (CCA) as the reference standard. 50 patients underwent CTA and CCA and out of these 44 were evaluable for computer-aided stenosis detection. The diagnostic performance of the software and of human reading were compared and quantitative coronary angiography (QCA) served as the reference standard for the detection of significant stenosis (>50 %). Overall, three readers with high (reader 1), intermediate (reader 2) and low (reader 3) experience in cardiac CT imaging performed the manual CTA evaluation on a commercially available workstation, whereas the automated software processed the datasets without any human interaction. The prevalence of coronary artery disease was 41 % (18/44) and QCA indicated significant stenosis (>50 %) in 33 coronary vessels. The automated software accurately diagnosed 18 individuals with significant coronary artery disease (CAD), and correctly ruled out CAD in 10 patients. In summary the sensitivity of computer-aided detection was 100 %/94 % (per-patient/per-vessel) and the specificity was 38 %/70 %, the positive predictive value (PPV) was 53 %/42 % and the negative predictive value (NPV) was 100 %/98 %. In comparison, reader 1-3 showed per-patient sensitivities of 100/94/89 %, specificities of 73/69/50 %, PPVs of 72/68/55 % and NPVs of 100/95/87 %. Computer-aided detection yields a high NPV that is comparable to more experienced human readers. However, PPV is rather low and in the range of an unexperienced reader.