title: Airway count and emphysema assessed by chest CT imaging predicts clinical outcome in smokers.
abstract: BACKGROUND
  Recently, it has been shown that emphysematous destruction of the lung is associated with a decrease in the total number of terminal bronchioles. It is unknown whether a similar decrease is visible in the more proximal airways. We aimed to assess the relationships between proximal airway count, CT imaging measures of emphysema, and clinical prognostic factors in smokers, and to determine whether airway count predicts the BMI, airflow obstruction, dyspnea, and exercise capacity (BODE) index.
  
  
  METHODS
  In 50 smokers, emphysema was measured on CT scans and airway branches from the third to eighth generations of the right upper lobe apical bronchus were counted manually. The sum of airway branches from the sixth to eighth generations represented the total airway count (TAC). For each subject, the BODE index was determined. We used logistic regression to assess the ability of TAC to predict a high BODE index (≥ 7 points).
  
  
  RESULTS
  TAC was inversely associated with emphysema (r = -0.54, P < .0001). TAC correlated with the modified Medical Research Council dyspnea score (r = -0.42, P = .004), FEV(1)% predicted (r = 0.52, P = .0003), 6-min walk distance (r = 0.36, P = .012), and BODE index (r = -0.55, P < .0001). The C-statistics, which correspond to the area under the receiver operating characteristic curve, for the ability of TAC alone and TAC, emphysema, and age to predict a high BODE index were 0.84 and 0.92, respectively.
  
  
  CONCLUSIONS
  TAC is lower in subjects with greater emphysematous destruction and is a predictor of a high BODE index. These results suggest that CT imaging-based TAC may be a unique COPD-related phenotype in smokers.
authors.affiliation: Pulmonary and Critical Care Medicine Division, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA 02115, USA. adiaz6@Partners.org
authors.forename: Alejandro A
authors.initials: AA
authors.lastname: Diaz
authors.forename: Clarissa
authors.initials: C
authors.lastname: Valim
authors.forename: Tsuneo
authors.initials: T
authors.lastname: Yamashiro
authors.forename: Raúl San José
authors.initials: RS
authors.lastname: Estépar
authors.forename: James C
authors.initials: JC
authors.lastname: Ross
authors.forename: Shin
authors.initials: S
authors.lastname: Matsuoka
authors.forename: Brian
authors.initials: B
authors.lastname: Bartholmai
authors.forename: Hiroto
authors.initials: H
authors.lastname: Hatabu
authors.forename: Edwin K
authors.initials: EK
authors.lastname: Silverman
authors.forename: George R
authors.initials: GR
authors.lastname: Washko
mesh_terms: D000368:Aged; D000402:Airway Obstruction / Q000000981:diagnostic imaging / Q000209:etiology; D015992:Body Mass Index; D055745:Bronchioles / Q000473:pathology; D016009:Chi-Square Distribution; D004417:Dyspnea / Q000000981:diagnostic imaging / Q000209:etiology; D017079:Exercise Tolerance; D005260:Female; D006801:Humans; D016015:Logistic Models; D008297:Male; D008875:Middle Aged; D011237:Predictive Value of Tests; D011379:Prognosis; D011656:Pulmonary Emphysema / Q000000981:diagnostic imaging* / Q000209:etiology*; D012372:ROC Curve; D011857:Radiographic Image Interpretation, Computer-Assisted; D013902:Radiography, Thoracic / Q000379:methods*; D015203:Reproducibility of Results; D012720:Severity of Illness Index; D012907:Smoking / Q000009:adverse effects*; D014057:Tomography, X-Ray Computed