title: Feasibility of mathematical models to predict success in video-assisted thoracic surgery lung nodule excision.
abstract: BACKGROUND
  Pulmonary nodules are occasionally difficult to excise using video-assisted thoracic surgery (VATS).
  
  
  METHODS
  To predict operative success, mathematical models using preoperative computerized tomography (CT) measurements were tested in 50 consecutive patients who underwent attempted or successful thoracoscopic lung biopsy. Unrelated technical problems resulted in the exclusion of 3 patients.
  
  
  RESULTS
  No differences were noted with respect to lobar location, thoracic dimensions, gender, presence of chronic obstructive pulmonary disease, or nodule pathology. The expression S/(D + 1), where S = nodule size (cm) and D = distance (cm) to the nearest visceral pleura, yielded significantly higher values for visible nodules (P < 0.001). Resectable nodules had a higher score using the expression 1/(S + D + 1), (P < 0.001). Simple cases (n = 19) were defined as those in which nodules were both visible and resectable with very basic VATS techniques. All others (n = 28) were considered complex. The derived expression for Simplicity [1/(S(D + 1))] yielded significantly higher values for simple cases (0.8 +/- 0.3 vs. 0.3 +/- 0.2 cm(-2), P < 0.001) and all simple cases had a score > or = 0.4. Logistic regression analysis showed that the formulas for resectability and simplicity were significant independent predictors for resectability and simplicity.
  
  
  CONCLUSIONS
  Equations based on objective CT measurements may be useful for planning VATS nodulectomy or studying the outcome of these minimally invasive operations.
authors.affiliation: Division of Cardiothoracic Surgery, University of Missouri, Columbia 65212, USA.
authors.forename: T L
authors.initials: TL
authors.lastname: Demmy
authors.forename: C C
authors.initials: CC
authors.lastname: Wagner-Mann
authors.forename: M A
authors.initials: MA
authors.lastname: James
authors.forename: J J
authors.initials: JJ
authors.lastname: Curtis
authors.forename: R A
authors.initials: RA
authors.lastname: Schmaltz
authors.forename: J T
authors.initials: JT
authors.lastname: Walls
mesh_terms: D005240:Feasibility Studies; D005260:Female; D006801:Humans; D008171:Lung Diseases / Q000601:surgery*; D008175:Lung Neoplasms / Q000601:surgery*; D008297:Male; D008433:Mathematics; D008875:Middle Aged; D008962:Models, Theoretical; D012044:Regression Analysis; D013903:Thoracic Surgery / Q000379:methods*; D016896:Treatment Outcome; D014741:Video Recording