title: Noninvasive characterization of the histopathologic features of pulmonary nodules of the lung adenocarcinoma spectrum using computer-aided nodule assessment and risk yield (CANARY)--a pilot study.
abstract: BACKGROUND
  Pulmonary nodules of the adenocarcinoma spectrum are characterized by distinctive morphological and radiologic features and variable prognosis. Noninvasive high-resolution computed tomography-based risk stratification tools are needed to individualize their management.
  
  
  METHODS
  Radiologic measurements of histopathologic tissue invasion were developed in a training set of 54 pulmonary nodules of the adenocarcinoma spectrum and validated in 86 consecutively resected nodules. Nodules were isolated and characterized by computer-aided analysis, and data were analyzed by Spearman correlation, sensitivity, and specificity and the positive and negative predictive values.
  
  
  RESULTS
  Computer-aided nodule assessment and risk yield (CANARY) can noninvasively characterize pulmonary nodules of the adenocarcinoma spectrum. Unsupervised clustering analysis of high-resolution computed tomography data identified nine unique exemplars representing the basic radiologic building blocks of these lesions. The exemplar distribution within each nodule correlated well with the proportion of histologic tissue invasion, Spearman R = 0.87, p < 0.0001 and 0.89 and p < 0.0001 for the training and the validation set, respectively. Clustering of the exemplars in three-dimensional space corresponding to tissue invasion and lepidic growth was used to develop a CANARY decision algorithm that successfully categorized these pulmonary nodules as "aggressive" (invasive adenocarcinoma) or "indolent" (adenocarcinoma in situ and minimally invasive adenocarcinoma). Sensitivity, specificity, positive predictive value, and negative predictive value of this approach for the detection of aggressive lesions were 95.4, 96.8, 95.4, and 96.8%, respectively, in the training set and 98.7, 63.6, 94.9, and 87.5%, respectively, in the validation set.
  
  
  CONCLUSIONS
  CANARY represents a promising tool to noninvasively risk stratify pulmonary nodules of the adenocarcinoma spectrum.
authors.affiliation: Department of Medicine, Division of Pulmonary and Critical Care Medicine, Mayo Clinic, Rochester, Minnesota 55905, USA.
authors.forename: Fabien
authors.initials: F
authors.lastname: Maldonado
authors.forename: Jennifer M
authors.initials: JM
authors.lastname: Boland
authors.forename: Sushravya
authors.initials: S
authors.lastname: Raghunath
authors.forename: Marie Christine
authors.initials: MC
authors.lastname: Aubry
authors.forename: Brian J
authors.initials: BJ
authors.lastname: Bartholmai
authors.forename: Mariza
authors.initials: M
authors.lastname: Deandrade
authors.forename: Thomas E
authors.initials: TE
authors.lastname: Hartman
authors.forename: Ronald A
authors.initials: RA
authors.lastname: Karwoski
authors.forename: Srinivasan
authors.initials: S
authors.lastname: Rajagopalan
authors.forename: Anne-Marie
authors.initials: AM
authors.lastname: Sykes
authors.forename: Ping
authors.initials: P
authors.lastname: Yang
authors.forename: Eunhee S
authors.initials: ES
authors.lastname: Yi
authors.forename: Richard A
authors.initials: RA
authors.lastname: Robb
authors.forename: Tobias
authors.initials: T
authors.lastname: Peikert
mesh_terms: D000230:Adenocarcinoma / Q000175:diagnosis*; D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D002278:Carcinoma in Situ / Q000000981:diagnostic imaging / Q000473:pathology*; D016000:Cluster Analysis; D003936:Diagnosis, Computer-Assisted; D005260:Female; D005500:Follow-Up Studies; D006801:Humans; D008168:Lung / Q000000981:diagnostic imaging / Q000473:pathology*; D008175:Lung Neoplasms / Q000175:diagnosis*; D008297:Male; D008875:Middle Aged; D055613:Multiple Pulmonary Nodules / Q000000981:diagnostic imaging / Q000473:pathology*; D009361:Neoplasm Invasiveness; D009367:Neoplasm Staging; D010865:Pilot Projects; D011379:Prognosis; D011857:Radiographic Image Interpretation, Computer-Assisted; D018570:Risk Assessment; D003074:Solitary Pulmonary Nodule / Q000000981:diagnostic imaging / Q000473:pathology*; D014057:Tomography, X-Ray Computed