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To conduct a comparison of the diagnostic performance of exercise bicycle testing and single-photon emission computed tomography (SPECT) with computed tomography coronary angiography (CTCA) for the detection of obstructive coronary artery disease (CAD) in patients with stable angina. 376 symptomatic patients (254 men, 122 women, mean age 60.4 ± 10.0 years) referred for noninvasive stress testing (exercise bicycle test and/or SPECT) and invasive coronary angiography were included. All patients underwent additional 64-slice CTCA. The diagnostic performance of exercise bicycle testing (ST segment depression), SPECT (reversible perfusion defect) and CTCA (≥50% lumen diameter reduction) was presented as sensitivity, specificity, positive and negative predictive value (PPV and NPV) to detect or rule out obstructive CAD with quantitative coronary angiography as reference standard. Comparisons of exercise bicycle testing versus CTCA (n = 334), and SPECT versus CTCA (n = 61) were performed. The diagnostic performance of exercise bicycle testing was significantly (P value < 0.001) lower compared to CTCA: sensitivity of 76% (95% CI, 71-82) vs. 100% (95% CI, 97-100); specificity of 47% (95% CI, 36-58) vs. 74% (95% CI, 63-82). We observed a PPV of 70% (95% CI, 65-75) vs. 91% (95% CI, 87-94); and NPV of 30% (95%, 25-35) vs. 99% (95%, 90-100). There was a statistically significant difference in sensitivity (P value < 0.05) between SPECT and CTCA: 89% (95% CI, 75-96) vs. 98% (95% CI, 87-100); but not in specificity (P value > 0.05): 77% (95% CI, 50-92) vs. 82% (95% CI, 56-95). We observed a PPV of 91% (95% CI, 77-97) vs. 93% (95% CI, 81-98); and NPV of 72% (95%, 46-89) vs. 93% (95%, 66-100). SPECT and CTCA yielded higher diagnostic performance compared to traditional exercise bicycle testing for the detection and rule out of obstructive CAD in patients with stable angina.

Objective: We evaluated the ability of 64-slice multidetector computed tomography (MDCT)-derived plaque parameters to detect and quantify coronary atherosclerosis, using intravascular ultrasound (IVUS) as the reference standard., Methods: In 32 patients, IVUS and 64-MDCT was performed. The MDCT and IVUS datasets of 44 coronary arteries were co-registered using a newly developed fusion technique and quantitative parameters were derived from both imaging modalities. The threshold of >0.5 mm of maximum wall thickness was used to establish plaque presence on MDCT and IVUS., Results: We analyzed 1364 coregistered 1-mm coronary cross-sections and 255 segments of 5-mm length. Compared with IVUS, 64-MDCT enabled correct detection in 957 of 1109 cross-sections containing plaque (sensitivity 86%). In 180 of 255 cross-sections atherosclerosis was correctly excluded (specificity 71%). On the segmental level, MDCT detected 213 of 220 segments with any atherosclerotic plaque (sensitivity 96%), whereas the presence of any plaque was correctly ruled out in 28 of 32 segments (specificity 88%). Interobserver agreement for the detection of atherosclerotic cross-sections was moderate (Cohen's kappa coefficient K=0.51), but excellent for the atherosclerotic segments (K=1.0). Pearson's correlation coefficient for vessel plaque volumes measured by MDCT and IVUS was r=0.91 (p<0.001). Bland-Altman analysis showed a slight non-significant underestimation of any plaque volume by MDCT (p=0.5), with a trend to underestimate noncalcified and overestimate mixed/calcified plaque volumes (p=0.22 and p=0.87 respectively)., Conclusion: MDCT is able to detect and quantify atherosclerotic plaque. Further improvement in CT resolution is necessary for more reliable assessment of very small and distal coronary plaques., (Copyright © 2011 Elsevier Ireland Ltd. All rights reserved.)

We present an approach to derive patient specific coronary models from ECG-gated CTA data and their application for the alignment of CTA with mono-plane X-ray imaging during interventional cardiology. A 4D (3D+t) deformation model of the coronary arteries is derived by (i) extraction of a 3D coronary model at an appropriate cardiac phase and (ii) non-rigid registration of the CTA images at different ECG phases to obtain a deformation model. The resulting 4D coronary model is aligned with the X-ray data using a novel 2D+t/3D+t registration approach. Model consistency and accuracy is evaluated using manually annotated coronary centerlines at systole and diastole as reference. Improvement of registration robustness by using the 2D+t/3D+t registration is successfully demonstrated by comparison of the actual X-ray cardiac phase with the automatically determined best matching phase in the 4D coronary model.