title: Chronic destructive pulmonary tuberculosis: assessment of disease activity by computed tomography.
abstract: BACKGROUND
  Determination of disease activity of chronic destructive pulmonary tuberculosis (TB) on imaging studies can be difficult because several imaging findings due to disease chronicity such as a residual cavity can be misinterpreted as an active disease.
  
  
  OBJECTIVE
  To evaluate computed tomography (CT) findings to predict active disease in patients with chronic destructive pulmonary TB.
  
  
  METHODS
  CT findings of 36 patients with chronic active destructive pulmonary TB and 78 patients with chronic inactive destructive pulmonary TB were reviewed and their patterns of lung lesions were compared. Statistical comparisons were performed using chi-square and Student's T tests for univariate analyses, and a stepwise logistic regression method was used for multivariate analysis.
  
  
  RESULTS
  Based on univariate analyses, cavitary destruction (P = 0.015), non-branching centrilobular nodules (P < 0.001), tree-in-bud pattern (P < 0.001), airspace nodules (P < 0.001), and cavities in other lobes (P = 0.001) were more frequently seen in chronic active destructive pulmonary TB. A stepwise logistic regression analysis demonstrated that tree-in-bud pattern (odds ratio, 52.3; 95% confidence interval, 6.2-437.2; P < 0.001) were significant CT findings associated with active disease.
  
  
  CONCLUSIONS
  Tree-in-bud pattern were the most characteristic CT findings to predict active disease in patients with chronic destructive pulmonary TB.
authors.affiliation: Department of Radiology, Pusan National University Hospital, Pusan National University School of Medicine and Medical Research Institute, Pusan, Korea.
authors.forename: Kyung Jin
authors.initials: KJ
authors.lastname: Nam
authors.forename: Yeon Joo
authors.initials: YJ
authors.lastname: Jeong
authors.forename: Yeong Dae
authors.initials: YD
authors.lastname: Kim
authors.forename: Kun-Il
authors.initials: KI
authors.lastname: Kim
authors.forename: Jun Woo
authors.initials: JW
authors.lastname: Lee
authors.forename: Hye Kyung
authors.initials: HK
authors.lastname: Park
authors.forename: Hoseok
authors.initials: H
authors.lastname: I
mesh_terms: D000368:Aged; D016009:Chi-Square Distribution; D002908:Chronic Disease; D003287:Contrast Media; D003937:Diagnosis, Differential; D005260:Female; D006801:Humans; D007479:Iopamidol / Q000031:analogs & derivatives; D016015:Logistic Models; D008297:Male; D008875:Middle Aged; D011237:Predictive Value of Tests; D014057:Tomography, X-Ray Computed / Q000379:methods*; D014397:Tuberculosis, Pulmonary / Q000000981:diagnostic imaging*
chemical_list: D003287:Contrast Media; C057937:iomeprol; D007479:Iopamidol