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.