title: Automated assessment of malignant degree of small peripheral adenocarcinomas using volumetric CT data: correlation with pathologic prognostic factors.
abstract: OBJECTIVE
  To evaluate a custom-developed software for analyzing malignant degrees of small peripheral adenocarcinomas on volumetric CT data compared to pathological prognostic factors.
  
  
  METHODS
  Forty-six adenocarcinomas with a diameter of 2cm or less from 46 patients were included. The custom-developed software can calculate the volumetric rates of solid parts to whole nodules even though solid parts show a punctate distribution, and automatically classify nodules into the following six types according to the volumetric rates of solid parts: type 1, pure ground-glass opacity (GGO); type 2, semiconsolidation; type 3, small solid part with a GGO halo; type 4, mixed type with an area that consisted of GGO and solid parts which have air-bronchogram or show a punctate distribution; type 5, large solid part with a GGO halo; and type 6, pure solid type. The boundary between solid portion and GGO on CT was decided using two threshold selection methods for segmenting gray-scale images. A radiologist also examined two-dimensional rates of solid parts to total opacity (2D%solid) which was already confirmed with previous reports.
  
  
  RESULTS
  There were good agreements between the classification determined by the software and radiologists (weighted kappa=0.778-0.804). Multivariate logistic regression analyses showed that both 2D%solid and computer-automated classification were significantly useful in estimating lymphatic invasion (p=0.0007, 0.0027), vascular invasion (p=0.003, 0.012), and pleural invasion (p=0.021, 0.025).
  
  
  CONCLUSIONS
  Using our custom-developed software, it is feasible to predict the pathological prognostic factors of small peripheral adenocarcinomas.
authors.affiliation: Department of Radiology, Osaka University Graduate School of Medicine, 2-2 Yamadaoka, Suita-city, Osaka 565-0871, Japan. m-yanagawa@radiol.med.osaka-u.ac.jp
authors.forename: Masahiro
authors.initials: M
authors.lastname: Yanagawa
authors.forename: Yuko
authors.initials: Y
authors.lastname: Tanaka
authors.forename: Masahiko
authors.initials: M
authors.lastname: Kusumoto
authors.forename: Shunichi
authors.initials: S
authors.lastname: Watanabe
authors.forename: Ryosuke
authors.initials: R
authors.lastname: Tsuchiya
authors.forename: Osamu
authors.initials: O
authors.lastname: Honda
authors.forename: Hiromitsu
authors.initials: H
authors.lastname: Sumikawa
authors.forename: Atsuo
authors.initials: A
authors.lastname: Inoue
authors.forename: Masayoshi
authors.initials: M
authors.lastname: Inoue
authors.forename: Meinoshin
authors.initials: M
authors.lastname: Okumura
authors.forename: Noriyuki
authors.initials: N
authors.lastname: Tomiyama
authors.forename: Takeshi
authors.initials: T
authors.lastname: Johkoh
mesh_terms: D000230:Adenocarcinoma / Q000000981:diagnostic imaging* / Q000473:pathology / Q000503:physiopathology; D054893:Cone-Beam Computed Tomography / Q000379:methods; D018450:Disease Progression; D001330:Electronic Data Processing; D005240:Feasibility Studies; D006801:Humans; D007091:Image Processing, Computer-Assisted; D008175:Lung Neoplasms / Q000000981:diagnostic imaging* / Q000473:pathology / Q000503:physiopathology; D011379:Prognosis; D012986:Software Validation