title: New predictive equation for lung volume using chest computed tomography for size matching in lung transplantation.
abstract: OBJECTIVE
  Lung size matching is important in lung transplantation (LT). With advances in computed tomography (CT) technology, multidetector row CT can accurately measure the thoracic cage and lung volumes. The objective of this study was to generate a new regression equation using demographic data based on the measured CT lung volume in a healthy population to predict the CT lung volume of the donor in LT size matching.
  
  
  METHODS
  The medical records of healthy subjects who underwent chest CT scans to screen for lung cancer were retrospectively reviewed. CT lung volume was semi-automatically measured using a threshold-based auto-segmentation technique. New regression equations for CT lung volume were generated by multiple linear regression analysis using demographic data including height (H, cm), weight (W, kg), and age (A, years). The percentage error rate (%) of the equations were calculated as ([Estimated CT lung volume--Measured CT lung volume]/Measured CT lung volume × 100). A percentage error rate within ± 20% was considered acceptable.
  
  
  RESULTS
  A total of 141 men aged 27 to 55 years (mean, 46.7 ± 6.2 years) and 128 women aged 20 to 55 years (mean, 45.4 ± 7.2 years) were enrolled. The final regression equations for CT lung volume were (-5.890 + 0.067 H - 0.030 W + 0.020 A) in men and (-6.698 + 0.072 H - 0.024 W) in women. The mean absolute error rate was 10.9 ± 9.0% and 11.0 ± 8.5% in men and women, respectively. Percentage error rates were within ± 20% in 121 of 141 (85.8%) men and 113 of 128 (88.3%) women.
  
  
  CONCLUSIONS
  These equations could predict the CT lung volume of healthy subjects using demographic data. Using these equations, the predicted CT lung volume of donors could be matched to the measured CT lung volume of recipients in lung transplantation.
authors.affiliation: Department of Radiology and the Research Institute of Radiological Science, Yonsei University Health System, Seoul, Republic of Korea.
authors.forename: C H
authors.initials: CH
authors.lastname: Park
authors.affiliation: Department of Radiology and the Research Institute of Radiological Science, Yonsei University Health System, Seoul, Republic of Korea.
authors.forename: T H
authors.initials: TH
authors.lastname: Kim
authors.affiliation: Department of Thoracic and Cardiovascular Surgery, Gangnam Severance Hospital, Yonsei University College of Medicine, Seoul, Republic of Korea.
authors.forename: S
authors.initials: S
authors.lastname: Lee
authors.affiliation: Department of Thoracic and Cardiovascular Surgery, Severance Hospital, Yonsei University College of Medicine, Seoul, Republic of Korea.
authors.forename: H C
authors.initials: HC
authors.lastname: Paik
authors.affiliation: Department of Thoracic and Cardiovascular Surgery, Gangnam Severance Hospital, Yonsei University College of Medicine, Seoul, Republic of Korea. Electronic address: HAMSJ@yuhs.ac.
authors.forename: S J
authors.initials: SJ
authors.lastname: Haam
mesh_terms: D000328:Adult; D000367:Age Factors; D000465:Algorithms; D001827:Body Height; D001835:Body Weight; D046148:Donor Selection; D005260:Female; D006801:Humans; D016014:Linear Models; D008168:Lung / Q000033:anatomy & histology / Q000000981:diagnostic imaging*; D016040:Lung Transplantation; D008176:Lung Volume Measurements / Q000379:methods; D008297:Male; D008875:Middle Aged; D061330:Multidetector Computed Tomography; D009929:Organ Size; D011237:Predictive Value of Tests; D012189:Retrospective Studies; D012737:Sex Factors; D055815:Young Adult