Role of coronary angiography MDCT in the clinical setting: changes in diagnostic workup in the real world

PURPOSE

The authors sought to evaluate the incremental value of introducing coronary angiography with multidetector computed tomography (MDCT-CA) compared with the conventional diagnostic workup in managing patients with suspected coronary artery disease (CAD) workup.

MATERIALS AND METHODS

A total of 531 consecutive patients underwent MDCT-CA between April 2008 and August 2010. For each patient the pretest probability of CAD was obtained by using the Morise score as well as the diagnostic performance of the exercise test and of MDCT-CA, considering conventional coronary angiography (CCA) as the gold standard. Based on these results, we calculated the posttest likelihood of CAD after stress testing, comparing the incremental diagnostic value for each category of cardiovascular risk with data obtained with MDCT-CA. The conventional diagnostic workup (without MDCT-CA) was then compared with the modified workup (including MDCT-CA).

RESULTS

The diagnostic performance of the exercise test for identifying patients with significant lesions had a sensitivity and specificity of 20% and 88%, respectively, with positive (PPV) and negative (NPV) predictive value of 41% and 72%, respectively. Taking CA as the gold standard, MDCT-CA had 93% sensitivity, 89% specificity, 88% PPV and 93% NPV compared with CCA in evaluating significant stenoses in the per-patient analysis. The overall diagnostic accuracy of MDCT-CA was 91%. The exercise tests provided no significant incremental diagnostic value compared with cardiovascular history in patients with a low to intermediate risk. Comparison of the diagnostic accuracy of these protocols showed improved performance results for the modified protocol.

CONCLUSIONS

MDCT-CA is the reference modality for the noninvasive exclusion of critical CAD. It provides a very high incremental diagnostic value compared with exercise testing in patients with a low to intermediate risk of CAD. The use of diagnostic protocols based on MDCT-CA ensures improved diagnostic performance compared with those involving conventional exercise electrocardiograms.

Comparison between different kernel reformatting filters in 3D quantitative analysis of MDCT coronary angiography

PURPOSE

Coronary angiography with multidetector-row computed tomography (MDCT-CA) allows quantification of coronary artery stenosis with a high level of accuracy; however, a better estimation of stenosis can be achieved by using appropriate reformatting filters, especially in stents and calcified segments. Quantitative computed tomography angiography (QCTA) is intended to overcome the limitations of the visual score. The aim of this study was to evaluate the accuracy of QCTA with different filters in comparison with quantitative coronary angiography (QCA) and visual score.

MATERIALS AND METHODS

Two blinded operators visually scored 17 consecutive patients referred for MDCT-CA with a per-segment analysis. The degree of stenosis was classified as 0-20%, 20-50% (wall irregularities), 50-70% (significant disease) and 70-100% (vessel occlusion). Each segment was then analysed using the electronic callipers of the QCTA system with 15 different filters. No contour editing was performed. Data were compared with QCA and conventional coronary angiography (CCA). Comparison between QCTA, visual score and QCA were performed using Spearman's rank correlation.

RESULTS

Of 25 segments analysed (mean 1.4 diseased segment per patient), 375 measurements were considered. Good correlation was found between the visual score and QCA [Pearson correlation coefficient (rho=0.852; p<0.0001)] and between QCA and CCA (rho=0.804; p<0.0001). Moderate correlation was found between QCA and QCTA only using two filters (rho=0.444; p<0.0001 for YA filter and rho=0.450; p<0.0001 for YB filter).

CONCLUSIONS

Overall QCTA accuracy is low if contour editing is not applied, especially in calcified vessels. Certain filters can help to better estimate the exact percentage of stenosis.