title: Multivariate Analysis of Pleural Invasion of Peripheral Non-Small Cell Lung Cancer-Based Computed Tomography Features.
abstract: OBJECTIVE
  The aim of this study was to comprehensively analyze computed tomography features to improve the diagnostic accuracy of visceral pleural invasion of peripheral non-small cell lung cancer.
  
  
  METHODS
  The computed tomography features of 205 non-small cell lung cancer patients were retrospectively studied. The lesion's relation to the pleura was classified into 5 grades. A multivariate logistic regression analysis was conducted to identify independent factors predicting pleural invasion.
  
  
  RESULTS
  The multivariate logistic regression analysis showed that sex (odds ratio [OR], 1.822; P = 0.080), pleural indentation (OR, 4.111; P < 0.001), tumor density (OR, 2.735; P = 0.008), and distance between the lesion and pleura (OR, 1.981; P = 0.048) were independent predictors of pleural invasion. A patient with a score of 10.6 had an 80% risk of pleural invasion, whereas a score lower than 2 was associated with a lower (20%) risk of pleural invasion.
  
  
  CONCLUSIONS
  Comprehensive consideration of these factors of pleural indentation, sex, tumor density, and distance between the lesion and pleura might improve the diagnosis of pleural invasion.
authors.affiliation: From the Departments of *Radiology, and †Thoracic Oncology, Key Laboratory of Carcinogenesis and Translational Research, Ministry of Education, Peking University Cancer Hospital and Institute, Beijing, China.
authors.forename: Li-Ping
authors.initials: LP
authors.lastname: Qi
authors.forename: Xiao-Ting
authors.initials: XT
authors.lastname: Li
authors.forename: Yue
authors.initials: Y
authors.lastname: Yang
authors.forename: Jin-Feng
authors.initials: JF
authors.lastname: Chen
authors.forename: Juan
authors.initials: J
authors.lastname: Wang
authors.forename: Mai-Lin
authors.initials: ML
authors.lastname: Chen
authors.forename: Ying-Shi
authors.initials: YS
authors.lastname: Sun
mesh_terms: D000368:Aged; D000369:Aged, 80 and over; D002289:Carcinoma, Non-Small-Cell Lung / Q000000981:diagnostic imaging / Q000473:pathology*; D003627:Data Interpretation, Statistical; D005260:Female; D006801:Humans; D008175:Lung Neoplasms / Q000000981:diagnostic imaging / Q000473:pathology*; D008297:Male; D008875:Middle Aged; D015999:Multivariate Analysis; D009361:Neoplasm Invasiveness; D010994:Pleura / Q000000981:diagnostic imaging / Q000473:pathology*; D011856:Radiographic Image Enhancement / Q000379:methods; D011857:Radiographic Image Interpretation, Computer-Assisted / Q000379:methods*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D014057:Tomography, X-Ray Computed / Q000379:methods*