TY - JOUR
T1 - High-resolution CT for identify patients with smear-positive, active pulmonary tuberculosis
AU - Yeh, Jun Jun
AU - Yu, Joseph Kwong Leung
AU - Teng, Wen Bao
AU - Chou, Chun Hsiung
AU - Hsieh, Shih Peng
AU - Lee, Tsung Lung
AU - Wu, Ming Ting
PY - 2012/1
Y1 - 2012/1
N2 - 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.
AB - 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.
KW - High-resolution CT
KW - Patient isolation
KW - Sputum smear
KW - Tuberculosis
UR - http://www.scopus.com/inward/record.url?scp=84855562277&partnerID=8YFLogxK
U2 - 10.1016/j.ejrad.2010.09.040
DO - 10.1016/j.ejrad.2010.09.040
M3 - Article
C2 - 21030177
AN - SCOPUS:84855562277
SN - 0720-048X
VL - 81
SP - 195
EP - 201
JO - European Journal of Radiology
JF - European Journal of Radiology
IS - 1
ER -