title: Semiquantitative Computed Tomography Characteristics for Lung Adenocarcinoma and Their Association With Lung Cancer Survival.
abstract: In this study we developed 25 computed tomography descriptors among 117 patients with lung adenocarcinoma to semiquantitatively assess their association with overall survival. Pleural attachment was significantly associated with an increased risk of death and texture was most important for distinguishing histological subtypes. This approach has the potential to support automated analyses and develop decision-support clinical tools.
  
  
  BACKGROUND
  Computed tomography (CT) characteristics derived from noninvasive images that represent the entire tumor might have diagnostic and prognostic value. The purpose of this study was to assess the association of a standardized set of semiquantitative CT characteristics of lung adenocarcinoma with overall survival.
  
  
  METHODS
  An initial set of CT descriptors was developed to semiquantitatively assess lung adenocarcinoma in patients (n = 117) who underwent resection. Survival analyses were used to determine the association between each characteristic and overall survival. Principle component analysis (PCA) was used to determine characteristics that might differentiate histological subtypes.
  
  
  RESULTS
  Characteristics significantly associated with overall survival included pleural attachment (P < .001), air bronchogram (P = .03), and lymphadenopathy (P = .02). Multivariate analyses revealed pleural attachment was significantly associated with an increased risk of death overall (hazard ratio [HR], 3.21; 95% confidence interval [CI], 1.53-6.70) and among patients with lepidic predominant adenocarcinomas (HR, 5.85; 95% CI, 1.75-19.59), and lymphadenopathy was significantly associated with an increased risk of death among patients with adenocarcinomas without a predominant lepidic component (HR, 3.07; 95% CI, 1.09-8.70). A PCA model showed that texture (ground-glass opacity component) was most important for separating the 2 subtypes.
  
  
  CONCLUSIONS
  A subset of the semiquantitative characteristics described herein has prognostic importance and provides the ability to distinguish between different histological subtypes of lung adenocarcinoma.
authors.affiliation: Department of Radiology, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center of Cancer, Key Laboratory of Cancer Prevention and Therapy, Tianjin, PR China; Department of Cancer Imaging and Metabolism, H. Lee Moffitt Cancer Center and Research Institute, Tampa, FL.
authors.forename: Hua
authors.initials: H
authors.lastname: Wang
authors.affiliation: Department of Cancer Epidemiology, H. Lee Moffitt Cancer Center and Research Institute, Tampa, FL.
authors.forename: Matthew B
authors.initials: MB
authors.lastname: Schabath
authors.affiliation: Department of Radiology, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center of Cancer, Key Laboratory of Cancer Prevention and Therapy, Tianjin, PR China; Department of Cancer Imaging and Metabolism, H. Lee Moffitt Cancer Center and Research Institute, Tampa, FL.
authors.forename: Ying
authors.initials: Y
authors.lastname: Liu
authors.affiliation: Department of Biomedical Informatics, H. Lee Moffitt Cancer Center and Research Institute, Tampa, FL.
authors.forename: Anders E
authors.initials: AE
authors.lastname: Berglund
authors.affiliation: Department of Biomedical Informatics, H. Lee Moffitt Cancer Center and Research Institute, Tampa, FL.
authors.forename: Gregory C
authors.initials: GC
authors.lastname: Bloom
authors.affiliation: Department of Biostatistics, H. Lee Moffitt Cancer Center and Research Institute, Tampa, FL.
authors.forename: Jongphil
authors.initials: J
authors.lastname: Kim
authors.affiliation: Department of Cancer Imaging and Metabolism, H. Lee Moffitt Cancer Center and Research Institute, Tampa, FL.
authors.forename: Olya
authors.initials: O
authors.lastname: Stringfield
authors.affiliation: Department of Radiology, H. Lee Moffitt Cancer Center and Research Institute, Tampa, FL.
authors.forename: Edward A
authors.initials: EA
authors.lastname: Eikman
authors.affiliation: Department of Radiology, H. Lee Moffitt Cancer Center and Research Institute, Tampa, FL.
authors.forename: Donald L
authors.initials: DL
authors.lastname: Klippenstein
authors.affiliation: Department of Cancer Imaging and Metabolism, H. Lee Moffitt Cancer Center and Research Institute, Tampa, FL.
authors.forename: John J
authors.initials: JJ
authors.lastname: Heine
authors.affiliation: Department of Biomedical Informatics, H. Lee Moffitt Cancer Center and Research Institute, Tampa, FL.
authors.forename: Steven A
authors.initials: SA
authors.lastname: Eschrich
authors.affiliation: Department of Radiology, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center of Cancer, Key Laboratory of Cancer Prevention and Therapy, Tianjin, PR China. Electronic address: yezhaoxiang@163.com.
authors.forename: Zhaoxiang
authors.initials: Z
authors.lastname: Ye
authors.affiliation: Department of Cancer Imaging and Metabolism, H. Lee Moffitt Cancer Center and Research Institute, Tampa, FL; Department of Radiology, H. Lee Moffitt Cancer Center and Research Institute, Tampa, FL. Electronic address: robert.gillies@moffitt.org.
authors.forename: Robert J
authors.initials: RJ
authors.lastname: Gillies
mesh_terms: D000230:Adenocarcinoma / Q000000981:diagnostic imaging* / Q000401:mortality / Q000473:pathology; D000368:Aged; D005260:Female; D006801:Humans; D008175:Lung Neoplasms / Q000000981:diagnostic imaging* / Q000401:mortality / Q000473:pathology; D008198:Lymph Nodes / Q000473:pathology*; D008297:Male; D008875:Middle Aged; D009367:Neoplasm Staging; D010994:Pleura / Q000473:pathology*; D011237:Predictive Value of Tests; D025341:Principal Component Analysis; D011379:Prognosis; D016019:Survival Analysis; D014057:Tomography, X-Ray Computed / Q000379:methods
keywords: CT; Feature; Lepidic growth; Prognosis; Quantitative