Clinical value of 16-slice multidetector computed tomography in symptomatic patients with suspected coronary artery disease

Lipid profile as a strong indicator of coronary plaques: noninvasive assessment by multislice computerized tomography

BACKGROUND

Most acute coronary syndrome disorders occur as a consequence of atherosclerotic plaque rupture. Lipids are involved in atherosclerotic plaque buildup. Advances in image quality of coronary computed tomography have enabled improved characterization of coronary plaques. The aim of our study was to evaluate the association between lipid profile and coronary plaque presence in general and soft plaques in particular.

METHODS

In this cross-sectional survey, 258 consecutive patients presenting with chest pain either or both with low-to-moderate risk for coronary artery disease, were included. All patients were tested for lipid profile prior to cardiac imaging on a 64-slice computer tomography. Multivariate logistic regression models were used to assess the odds ratios (ORs) and 95% confidence interval (CI) for the relationship between blood lipid levels and prevalence of coronary plaques.

RESULTS

Age, total cholesterol levels, hypertension, hyperlipidemia (dichotomous) and risk factor index, all were independently associated with prevalence all kind of plaques, especially with soft plaques. No significant relationships were detected among BMI, current smoking, diabetes or triglycerides levels. In a multivariate logistic regression, hyperlipidemia was associated with presence of coronary plaque risk with adjusted OR of 2.28 (95% CI 1.30-4.01), total cholesterol with adjusted OR = 1.05 (95% CI 1.01-1.06), and risk factor index (1-6) with adjusted OR = 2.23 (95% CI 1.40-3.55).

CONCLUSION

Hyperlipidemia is strongly associated with prevalence of coronary plaques (P < 0.001) in individuals with low-to-intermediate risk for coronary artery disease, based on cardiac CT. Cardiac CT may serve as a noninvasive alternative for the early diagnosis of CAD in such individuals.

Methodological quality of diagnostic accuracy studies on non-invasive coronary CT angiography: influence of QUADAS (Quality Assessment of Diagnostic Accuracy Studies included in systematic reviews) items on sensitivity and specificity

OBJECTIVES

To evaluate the methodological quality of diagnostic accuracy studies on coronary computed tomography (CT) angiography using the QUADAS (Quality Assessment of Diagnostic Accuracy Studies included in systematic reviews) tool.

METHODS

Each QUADAS item was individually defined to adapt it to the special requirements of studies on coronary CT angiography. Two independent investigators analysed 118 studies using 12 QUADAS items. Meta-regression and pooled analyses were performed to identify possible effects of methodological quality items on estimates of diagnostic accuracy.

RESULTS

The overall methodological quality of coronary CT studies was merely moderate. They fulfilled a median of 7.5 out of 12 items. Only 9 of the 118 studies fulfilled more than 75 % of possible QUADAS items. One QUADAS item ("Uninterpretable Results") showed a significant influence (P = 0.02) on estimates of diagnostic accuracy with "no fulfilment" increasing specificity from 86 to 90 %. Furthermore, pooled analysis revealed that each QUADAS item that is not fulfilled has the potential to change estimates of diagnostic accuracy.

CONCLUSIONS

The methodological quality of studies investigating the diagnostic accuracy of non-invasive coronary CT is only moderate and was found to affect the sensitivity and specificity. An improvement is highly desirable because good methodology is crucial for adequately assessing imaging technologies.

KEY POINTS

• Good methodological quality is a basic requirement in diagnostic accuracy studies. • Most coronary CT angiography studies have only been of moderate design quality. • Weak methodological quality will affect the sensitivity and specificity. • No improvement in methodological quality was observed over time. • Authors should consider the QUADAS checklist when undertaking accuracy studies.

Use of 3x2 tables with an intention to diagnose approach to assess clinical performance of diagnostic tests: meta-analytical evaluation of coronary CT angiography studies

OBJECTIVE

To determine whether a 3 × 2 table, using an intention to diagnose approach, is better than the "classic" 2 × 2 table at handling transparent reporting and non-evaluable results, when assessing the accuracy of a diagnostic test.

DESIGN

Based on a systematic search for diagnostic accuracy studies of coronary computed tomography (CT) angiography, full texts of relevant studies were evaluated to determine whether they could calculate an alternative 3 × 2 table. To quantify an overall effect, we pooled diagnostic accuracy values according to a meta-analytical approach.

DATA SOURCES

Medline (via PubMed), Embase (via Ovid), and ISI Web of Science electronic databases.

ELIGIBILITY CRITERIA

Prospective English or German language studies comparing coronary CT with conventional coronary angiography in all patients and providing sufficient data for a patient level analysis.

RESULTS

120 studies (10,287 patients) were eligible. Studies varied greatly in their approaches to handling non-evaluable findings. We found 26 studies (including 2298 patients) that allowed us to calculate both 2 × 2 tables and 3 × 2 tables. Using a bivariate random effects model, we compared the 2 × 2 table with the 3 × 2 table, and found significant differences for pooled sensitivity (98.2 (95% confidence interval 96.7 to 99.1) v 92.7 (88.5 to 95.3)), area under the curve (0.99 (0.98 to 1.00) v 0.93 (0.91 to 0.95)), positive likelihood ratio (9.1 (6.2 to 13.3) v 4.4 (3.3 to 6.0)), and negative likelihood ratio (0.02 (0.01 to 0.04) v 0.09 (0.06 to 0.15); (P<0.05)).

CONCLUSION

Parameters for diagnostic performance significantly decrease if non-evaluable results are included by a 3 × 2 table for analysis (intention to diagnose approach). This approach provides a more realistic picture of the clinical potential of diagnostic tests.

Radiation dose and diagnostic accuracy of multidetector computed tomography for the detection of significant coronary artery stenoses: a meta-analysis

We conducted a meta-analysis evaluating the critical ratio between effective radiation dose (ED), feasibility (Fe) and diagnostic accuracy (Ac) of multidetector computed tomography (MDCT) for the detection of significant coronary artery disease. By using our predetermined criteria, we selected human studies published in English in which the ED and raw data of Ac vs. invasive coronary angiography in a segment based model were specified. Data from 31 studies including 3661 patients (mean age 61.9 ± 4.5 years, heart rate 62.5 ± 6.7 bpm) and 50,236 coronary artery segments were analysed and are reported. Overall, Fe, sensitivity, specificity, negative predictive value, positive predictive value, Ac and ED were 95%, 90%, 96%, 99%, 69%, 95% and 10.4 ± 5.4 mSv, respectively. Multivariate analysis showed that prospective ECG-gating (-8.8 mSv CI95% -13.4 to -4.3 mSv, p=0.001), dual-source (-3.7 mSv CI95% -7.9 to 0 mSv, p=0.05) and BMI-adapted scanning protocols (-4.5 mSv CI95% -8.7 to -2.7 mSv, p=0.03) were independent predictors of ED reduction. In patients with low heart rate, the best compromise between ED, Fe and Ac (2.5 mSv, 97% and 98%, respectively) was obtained combining prospective ECG-gating and BMI-adapted scanning protocols, while in patients with high heart rate the strategy associated with the best results (10 mSv, 98% and 97%, respectively) was the use of dual-source MDCT with retrospective ECG gating and modulation dose. In conclusion, careful selection of CT scanning protocols according to the patient's characteristics is critical for keeping the radiation exposure "as low as reasonably achievable" (ALARA) without impairing Fe and Ac.

Influence of coronary artery disease prevalence on predictive values of coronary CT angiography: a meta-regression analysis

OBJECTIVE

To evaluate the impact of coronary artery disease (CAD) prevalence on the predictive values of coronary CT angiography.

METHODS

We performed a meta-regression based on a generalised linear mixed model using the binomial distribution and a logit link to analyse the influence of the prevalence of CAD in published studies on the per-patient negative and positive predictive values of CT in comparison to conventional coronary angiography as the reference standard. A prevalence range in which the negative predictive value was higher than 90%, while at the same time the positive predictive value was higher than 70% was considered appropriate.

RESULTS

The summary negative and positive predictive values of coronary CT angiography were 93.7% (95% confidence interval [CI] 92.8-94.5%) and 87.5% (95% CI, 86.5-88.5%), respectively. With 95% confidence, negative and positive predictive values higher than 90% and 70% were available with CT for a CAD prevalence of 18-63%. CT systems with >16 detector rows met these requirements for the positive (P < 0.01) and negative (P < 0.05) predictive values in a significantly broader range than systems with ≤16 detector rows.

CONCLUSION

It is reasonable to perform coronary CT angiography as a rule-out test in patients with a low-to-intermediate likelihood of disease.

Evaluation of a multi-atlas based method for segmentation of cardiac CTA data: a large-scale, multicenter, and multivendor study

PURPOSE

Computed tomography angiography (CTA) is increasingly used for the diagnosis of coronary artery disease (CAD). However, CTA is not commonly used for the assessment of ventricular and atrial function, although functional information extracted from CTA data is expected to improve the diagnostic value of the examination. In clinical practice, the extraction of ventricular and atrial functional information, such as stroke volume and ejection fraction, requires accurate delineation of cardiac chambers. In this paper, we investigated the accuracy and robustness of cardiac chamber delineation using a multiatlas based segmentation method on multicenter and multivendor CTA data.

METHODS

A fully automatic multiatlas based method for segmenting the whole heart (i.e., the outer surface of the pericardium) and cardiac chambers from CTA data is presented and evaluated. In the segmentation approach, eight atlas images are registered to a new patient's CTA scan. The eight corresponding manually labeled images are then propagated and combined using a per voxel majority voting procedure, to obtain a cardiac segmentation.

RESULTS

The method was evaluated on a multicenter/multivendor database, consisting of (1) a set of 1380 Siemens scans from 795 patients and (2) a set of 60 multivendor scans (Siemens, Philips, and GE) from different patients, acquired in six different institutions worldwide. A leave-one-out 3D quantitative validation was carried out on the eight atlas images; we obtained a mean surface-to-surface error of 0.94 +/- 1.12 mm and an average Dice coefficient of 0.93 was achieved. A 2D quantitative evaluation was performed on the 60 multivendor data sets. Here, we observed a mean surface-to-surface error of 1.26 +/- 1.25 mm and an average Dice coefficient of 0.91 was achieved. In addition to this quantitative evaluation, a large-scale 2D and 3D qualitative evaluation was performed on 1380 and 140 images, respectively. Experts evaluated that 49% of the 1380 images were very accurately segmented (below 1 mm error) and that 29% were accurately segmented (error between 1 and 3 mm), which demonstrates the robustness of the presented method.

CONCLUSIONS

A fully automatic method for whole heart and cardiac chamber segmentation was presented and evaluated using multicenter/multivendor CTA data. The accuracy and robustness of the method were demonstrated by successfully applying the method to 1420 multicenter/ multivendor data sets.