Rationale and Objectives
To prospectively evaluate the influence of the clinical pretest probability assessed by the Morise score onto image quality and diagnostic accuracy in coronary dual-source computed tomography angiography (DSCTA).
Materials and Methods
In 61 patients, DSCTA and invasive coronary angiography were performed. Subjective image quality and accuracy for stenosis detection (>50%) of DSCTA with invasive coronary angiography as gold standard were evaluated. The influence of pretest probability onto image quality and accuracy was assessed by logistic regression and chi-square testing. Correlations of image quality and accuracy with the Morise score were determined using linear regression.
Results
Thirty-eight patients were categorized into the high, 21 into the intermediate, and 2 into the low probability group. Accuracies for the detection of significant stenoses were 0.94, 0.97, and 1.00, respectively. Logistic regressions and chi-square tests showed statistically significant correlations between Morise score and image quality ( P < .0001 and P < .001) and accuracy ( P = .0049 and P = .027). Linear regression revealed a cutoff Morise score for a good image quality of 16 and a cutoff for a barely diagnostic image quality beyond the upper Morise scale.
Conclusion
Pretest probability is a weak predictor of image quality and diagnostic accuracy in coronary DSCTA. A sufficient image quality for diagnostic images can be reached with all pretest probabilities. Therefore, coronary DSCTA might be suitable also for patients with a high pretest probability.
Coronary computed tomography angiography (CTA) has evolved as a tool to noninvasively assess coronary artery disease (CAD). Several recent studies have shown the potential of 64-slice and dual-source CT (DSCT) to image the coronary tree and to detect and grade stenoses . Although excellent results have been reported for patients with low and intermediate pretest probabilities , it is known that the image quality of CTA may suffer in patients with a higher pretest probability because of obesity, blooming artifacts caused by calcified plaques, or irregular heart rates . A large study of 64-slice CTA performed by Meijboom et al has shown that this modality is severely limited in patients with a high pretest probability . DSCT with its high temporal resolution and x-ray output has the potential to improve image quality in patients with high pretest probabilities . All previous studies investigating the accuracy of coronary DSCT angiography (DSCTA) known to the authors have focused on certain patient collectives with a homogenous distribution of pretest probabilities or have not evaluated the impact of different pretest probabilities onto the diagnostic accuracy of coronary DSCTA. Furthermore, the results of these studies are hardly comparable because the pretest probability was not defined unequivocally in all studies. Therefore, in this study, the image quality and accuracy of coronary DSCTA in a heterogeneous patient collective is assessed with regards to the patients’ pretest probability.
Materials and methods
Patients and Morise Score
The local ethics committee agreed to this study. Between April 2007 and November 2007, 61 consecutive patients (42 males, mean age 63 ± 10 years) who were referred for invasive coronary angiography (ICA) because of suspected CAD were included into the study and received additional coronary DSCTA 1 day before ICA. All CT examinations were performed at the same institution (a large university hospital). All patients gave their informed consent to participate in this study. Exclusion criteria were known previous myocardial infarction, known CAD, allergic reaction to iodinated contrast media, impaired renal function, hyperthyroidism (basal thyroid-stimulating hormone <0.03 μL/L in combination with elevation of the peripheral thyroid hormones), pregnancy, and unstable clinical conditions.
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Table 1
Factors for the Calculation of the Morise Score
Points Condition Age 3 <40 (male), <50 (female) 6 40–55 (male) 50–64 (female) 9 >55 (male), >65 (female) Estrogen −3 Estrogen positive 0 Male/unknown 3 Estrogen negative Symptoms 0 Non-anginal 3 Atypical angina 5 Typical angina Hypertension 1 If positive Smoking 1 If positive Hyperlipidemia 1 If positive Family history 1 If positive Obesity 1 If positive Diabetes 2 If positive
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DSCT
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ICA
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Statistical Analysis
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Results
Patient Characteristics
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Image Quality and Accuracy
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Table 2
Numbers and Percentages of Segments of every Image Quality Score Point in each Pretest Probability Group
Image quality score 1 2 3 4 Pretest probability (#) (%) (#) (%) (#) (%) (#) (%) Low (n = 26) 22 84.6 1 3.8 2 7.7 1 3.8 Medium (n = 273) 99 36.2 122 44.7 39 14.3 13 4.8 High (n = 494) 154 31.2 200 40.5 89 18.0 51 10.3 All (n = 793) 275 34.7 323 40.7 130 16.4 65 8.2
Image quality score: 1: excellent, 2: good, 3: barely diagnostic, 4: insufficient.
Table 3
Results of DSCTA with ICA as Gold Standard in every Pretest Probability Group, Calculated Per patient and Per segment
Per patient Per segment Pretest probability TP TN FP FN TP TN FP FN Accuracy Low (n = 2) 0 2 (100%) 0 0 0 26 (100%) 0 0 1.00 Medium (n = 21) 5 (24%) 14 (67%) 2 (10%) 0 (0%) 17 (6%) 247 (90%) 7 (3%) 2 (1%) 0.97 High (n = 38) 18 (47%) 15 (39%) 4 (11%) 1 (3%) 63 (13%) 403 (82%) 25 (5%) 3 (1%) 0.94 All (n = 61) 23 (38%) 31 (51%) 6 (10%) 1 (2%) 80 (10%) 676 (85%) 32 (4%) 5 (1%) 0.95
TP, true positive; TN, true negative; TP, false positive; FN, false negative.
Table 4
Sensitivities, Specificities, Positive Predictive Values (PPV), and Negative Predictive Values (NPV) Given for each Pretest Probability Group and for the Whole
Per patient Per segment Pretest probability Sensitivity (%) Specificity (%) PPV
(%) NPV
(%) Sensitivity (%) Specificity (%) PPV
(%) NPV
(%) Low ND 100.0 ND 100.0 ND 100.0 ND 100.0 Medium 100.0 87.5 71.4 100.0 89.5 97.2 70.8 99.2 High 94.7 78.9 81.8 93.8 95.5 94.2 71.6 99.3 All 95.8 83.8 79.3 96.9 94.1 95.5 71.4 99.3
ND, not defined.
Collective calculated per patient and per segment.
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Discussion
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