Role of the Emphysema Index Combined with the Chronic Obstructive Pulmonary Disease Assessment Test Score in the Evaluation of Chronic Obstructive Pulmonary Disease.

Background: This study aimed to evaluate the efficacy of the emphysema index (EI) in distinguishing chronic bronchitis (CB) from chronic obstructive pulmonary disease (COPD) and its role, combined with the COPD Assessment Test (CAT) score, in the evaluation of COPD. Methods: A total of 92 patients with CB and 277 patients with COPD were enrolled in this study. Receiver operating characteristic (ROC) curves were analyzed to evaluate whether the EI can preliminarily distinguish chronic bronchitis from COPD. Considering the heterogeneity of COPD, there might be missed diagnosis of some patients with bronchitis type when differentiating COPD patients only by EI. Therefore, patients with COPD were classified according to the CAT score and EI into four groups: Group 1 (EI < 16%, CAT < 10), Group 2 (EI < 16%, CAT ≥ 10), Group 3 (EI ≥ 16%, CAT < 10), and Group 4 (EI ≥ 16%, CAT ≥ 10). The records of pulmonary function and quantitative computed tomography findings were retrospectively analyzed. Results: ROC curve analysis showed that EI = 16.2% was the cutoff value for distinguishing COPD from CB. Groups 1 and 2 exhibited significantly higher maximal voluntary ventilation (MVV) percent predicted (pred), forced expiratory volume in 1 second (FEV1)/forced vital capacity (FVC), maximal midexpiratory flow of 25-75% pred, carbon monoxide-diffusing capacity (DLCO)/alveolar ventilation (VA), FEV1 % pred (p ≤ 0.013), and maximal expiratory flow 50% pred (all p < 0.05) than Group 4. FEV1/FVC and DLCO/VA were significantly lower in Group 3 than in Group 2 (p=0.002 and p < 0.001, respectively). The residual volume/total lung capacity was higher in Group 3 than in Groups 1 and 2 (p < 0.05). Conclusions: The combination of EI and CAT was effective in the evaluation of COPD.

Assessment of Acute Pulmonary Embolism by Computer-Aided Technique: A Reliability Study.

BACKGROUND Acute pulmonary embolism is one of the most common cardiovascular diseases. Computer-aided technique is widely used in chest imaging, especially for assessing pulmonary embolism. The reliability and quantitative analyses of computer-aided technique are necessary. This study aimed to evaluate the reliability of geometry-based computer-aided detection and quantification for emboli morphology and severity of acute pulmonary embolism. MATERIAL AND METHODS Thirty patients suspected of acute pulmonary embolism were analyzed by both manual and computer-aided interpretation of vascular obstruction index and computer-aided measurements of emboli quantitative parameters. The reliability of Qanadli and Mastora scores was analyzed using computer-aided and manual interpretation. RESULTS The time costs of manual and computer-aided interpretation were statistically different (374.90±150.16 versus 121.07±51.76, P<0.001). The difference between the computer-aided and manual interpretation of Qanadli score was 1.83±2.19, and 96.7% (29 out of 30) of the measurements were within 95% confidence interval (intraclass correlation coefficient, ICC=0.998). The difference between the computer-aided and manual interpretation of Mastora score was 1.46±1.62, and 96.7% (29 out of 30) of the measurements were within 95% confidence interval (ICC=0.997). The emboli quantitative parameters were moderately correlated with the Qanadli and Mastora scores (all P<0.001). CONCLUSIONS Computer-aided technique could reduce the time costs, improve the and reliability of vascular obstruction index and provided additional quantitative parameters for disease assessment.

Diagnostic accuracy of first generation dual-source computed tomography in the assessment of coronary artery disease: a meta-analysis from 24 studies.

The objective of this study is to evaluate the diagnostic accuracy of the first generation dual-source computed tomography (DSCT) in the diagnosis of coronary artery disease (CAD). We selected articles from four databases (Pubmed, Embase, the Cochrane central register of controlled trials (CENTRAL) and Chinese biomedical literature database. The strict study selection was made, and two reviewers independently extracted data back-to-back from included studies. Meta-Disc version 1.4 was used to obtain the pooled results. 24 studies were included in meta-analysis. A cut off point of ≥50% stenosis was used in all the studies to define significant coronary artery stenosis. In patient-based analysis (n = 801), pooled sensitivity was 0.980 [95% confidence interval (CI):0.970-0.990], specificity 0.870 (95% CI: 0.830-0.900), median positive predictive value (PPV) across studies 0.876 (range from 0.741 to 0.943) and negative predictive value (NPV) 0.964 (range from 0.900 to 1.000). In vessel-based analysis (n = 3,620) DSCT pooled sensitivity was 0.957 (95% CI: 0.943-0.969), specificity 0.930 (95% CI: 0.910-0.940), median PPV across studies 0.838 (range from 0.534 to 0.964) and NPV 0.973 (range from 0.885 to 0.996). In segment-based analysis (n = 6,177) DSCT pooled sensitivity was 0.915 (95% CI: 0.901-0.928), specificity 0.959 (95% CI: 0.956-0.963), median PPV 0.782 (range from 0.320 to 0.927) and NPV 0.985 (range from 0.929 to 0.999). In subgroups analysis, pooled sensitivity and specificity in segment based analysis were 93.1 and 92.3% when heart rate (HR) is beyond 70 bpm; when HR was below 70 bpm, the sensitivity was similar (93%), but specificity increased a little from 92.3 to 94%. When analysed based on segment with a cut-off calcium score of 400, the sensitivity was slightly higher in the subgroup with a score over 400 than in the subgroup with a score below 400 (94 vs. 91%), while the specificity was much lower in the subgroup with the high calcium score than the subgroup with the low calcium score (85 vs. 96%). For subgroups with heart rate beyond and below 65 bpm in patient-based analysis, sensitivities were 0.95 (95% CI: 0.86-0.99) and 0.98 (95% CI 0.91-1.00), respectively, while the specificities were 0.88 (95% CI 0.81-0.94) and 0.85 (95% CI 0.77-0.91), respectively. The area under the receiver operating characteristic curve (AUC) in the two subgroups were 0.9608 and 0.9786, respectively. DSCT is highly sensitive for patient-based analysis of CAD and has high specificity and NPV for segment-based analysis of CAD. First generation DSCT may have a role in the evaluation of patients with chest pain as a simple non-invasive examination because of its ability to diagnose or exclude significant CAD.