Identifying the most infectious lesions in pulmonary tuberculosis by high-resolution multi-detector computed tomography.

OBJECTIVE: This study aimed to determine whether characteristics detected by multi-detector computed tomography (MDCT) were predictive of highly infectious, smear-positive, active pulmonary tuberculosis (PTB). METHODS: Among 124 patients with active PTB, 84 had positive (group 1) and 40 had negative (group 2) smear results for acid-fast bacilli. Multiplanar MDCT, axial conventional CT and chest X-ray images were analysed retrospectively for morphology, number, and segmental (lobe) distribution of lesions. RESULTS: By multivariate analysis, consolidation over any segment of the upper, middle, or lingual lobes, cavitations, and clusters of nodules were associated with group 1, while centrilobular nodules were predictive of group 2. Using five independent variables associated with risk in group 1, a prediction model was created to distinguish between group 1 and group 2. ROC curve analysis showed an area under the curve of 0.951 +/- 0.021 for this prediction model. With the ideal cutoff point score of 1, the sensitivity, specificity, and positive predictive values were 84.5%, 97.5%, and 98.0%, respectively. CONCLUSIONS: A model to predict smear-positive active PTB on the basis of findings from MDCT may be a useful tool for clinical decisions about isolating patients pending sputum smear results.

High-resolution CT for identify patients with smear-positive, active pulmonary tuberculosis.

PURPOSE: This study evaluates the use of high-resolution computed tomography (HRCT) to differentiate smear-positive, active pulmonary tuberculosis (PTB) from other pulmonary infections in the emergency room (ER) setting. METHODS: One hundred and eighty-three patients diagnosed with pulmonary infections in an ER were divided into an acid fast bacillus (AFB) smear-positive, active PTB group (G1=84) and a non-AFB smear-positive, pulmonary infection group (G2=99). HRCT images from a 64-Multidetector CT were analyzed, retrospectively, for the morphology, number, and segmental distribution of pulmonary lesions. RESULTS: Utilizing multivariate analysis, five variables were found to be independent risk factors predictive of G1: (1) consolidation involving the apex segment of right upper lobe, posterior segment of the right upper lobe, or apico-posterior segment of the left upper lobe; (2) consolidation involving the superior segment of the right or left lower lobe; (3) presence of a cavitary lesion; (4) presence of clusters of nodules; (5) absence of centrilobular nodules. A G1 prediction score was generated based on these 5 criteria to help differentiate G1 from G2. The area under the receiver operating characteristic (ROC) curve was 0.96 ± 0.012 in our prediction model. With an ideal cut-off point score of 3, the specificity, sensitivity, positive predictive value (PPV), and negative predictive value (NPV) are 90.9%, 96.4%, 90.0% and 96.8%, respectively. CONCLUSION: The use of this AFB smear-positive, active PTB prediction model based on 5 key HRCT findings may help ER physicians determine whether or not isolation is required while awaiting serial sputum smear results in high risk patients.