title: Noninvasive Computed Tomography-based Risk Stratification of Lung Adenocarcinomas in the National Lung Screening Trial.
abstract: BACKGROUND
  Screening for lung cancer using low-dose computed tomography (CT) reduces lung cancer mortality. However, in addition to a high rate of benign nodules, lung cancer screening detects a large number of indolent cancers that generally belong to the adenocarcinoma spectrum. Individualized management of screen-detected adenocarcinomas would be facilitated by noninvasive risk stratification.
  
  
  OBJECTIVE
  To validate that Computer-Aided Nodule Assessment and Risk Yield (CANARY), a novel image analysis software, successfully risk stratifies screen-detected lung adenocarcinomas based on clinical disease outcomes.
  
  
  METHODS
  We identified retrospective 294 eligible patients diagnosed with lung adenocarcinoma spectrum lesions in the low-dose CT arm of the National Lung Screening Trial. The last low-dose CT scan before the diagnosis of lung adenocarcinoma was analyzed using CANARY blinded to clinical data. Based on their parametric CANARY signatures, all the lung adenocarcinoma nodules were risk stratified into three groups. CANARY risk groups were compared using survival analysis for progression-free survival.
  
  
  RESULTS
  A total of 294 patients were included in the analysis. Kaplan-Meier analysis of all the 294 adenocarcinoma nodules stratified into the Good, Intermediate, and Poor CANARY risk groups yielded distinct progression-free survival curves (P < 0.0001). This observation was confirmed in the unadjusted and adjusted (age, sex, race, and smoking status) progression-free survival analysis of all stage I cases.
  
  
  CONCLUSIONS
  CANARY allows the noninvasive risk stratification of lung adenocarcinomas into three groups with distinct post-treatment progression-free survival. Our results suggest that CANARY could ultimately facilitate individualized management of incidentally or screen-detected lung adenocarcinomas.
authors.affiliation: 1 Division of Pulmonary and Critical Care Medicine.
authors.forename: Fabien
authors.initials: F
authors.lastname: Maldonado
authors.affiliation: 2 Department of Biostatistics and Center for Statistical Sciences, Brown University School of Public Health, Providence, Rhode Island.
authors.forename: Fenghai
authors.initials: F
authors.lastname: Duan
authors.affiliation: 3 Department of Physiology and Biomedical Engineering, and.|4 Department of Radiology, Mayo Clinic, Rochester, Minnesota.
authors.forename: Sushravya M
authors.initials: SM
authors.lastname: Raghunath
authors.affiliation: 3 Department of Physiology and Biomedical Engineering, and.
authors.forename: Srinivasan
authors.initials: S
authors.lastname: Rajagopalan
authors.affiliation: 3 Department of Physiology and Biomedical Engineering, and.
authors.forename: Ronald A
authors.initials: RA
authors.lastname: Karwoski
authors.affiliation: 5 Department of Radiology, University of Colorado, Denver, Colorado; and.
authors.forename: Kavita
authors.initials: K
authors.lastname: Garg
authors.affiliation: 2 Department of Biostatistics and Center for Statistical Sciences, Brown University School of Public Health, Providence, Rhode Island.
authors.forename: Erin
authors.initials: E
authors.lastname: Greco
authors.affiliation: 6 Department of Medicine, University of Alabama at Birmingham, Birmingham, Alabama.
authors.forename: Hrudaya
authors.initials: H
authors.lastname: Nath
authors.affiliation: 3 Department of Physiology and Biomedical Engineering, and.
authors.forename: Richard A
authors.initials: RA
authors.lastname: Robb
authors.affiliation: 4 Department of Radiology, Mayo Clinic, Rochester, Minnesota.
authors.forename: Brian J
authors.initials: BJ
authors.lastname: Bartholmai
authors.affiliation: 1 Division of Pulmonary and Critical Care Medicine.
authors.forename: Tobias
authors.initials: T
authors.lastname: Peikert
mesh_terms: D000230:Adenocarcinoma / Q000000981:diagnostic imaging* / Q000401:mortality; D000077192:Adenocarcinoma of Lung; D000368:Aged; D000369:Aged, 80 and over; D000066491:Clinical Decision-Making / Q000379:methods*; D003661:Decision Support Techniques; D055088:Early Detection of Cancer / Q000379:methods*; D005260:Female; D006801:Humans; D008175:Lung Neoplasms / Q000000981:diagnostic imaging* / Q000401:mortality; D008297:Male; D008875:Middle Aged; D011857:Radiographic Image Interpretation, Computer-Assisted; D012189:Retrospective Studies; D018570:Risk Assessment; D016037:Single-Blind Method; D016019:Survival Analysis; D014057:Tomography, X-Ray Computed / Q000379:methods
keywords: image analysis; individualized medicine; lung adenocarcinoma; risk stratification