title: Computer-aided diagnosis of the solitary pulmonary nodule.
abstract: OBJECTIVE
  We sought to investigate the utility of a computer-aided diagnosis in the task of differentiating malignant nodules from benign nodules based on single thin-section computed tomography image data.
  
  
  METHODS
  Eighty-one thin-section computed tomography data sets of solitary pulmonary nodules with proven diagnoses (48 malignant and 33 benign) were contoured manually on a single representative slice by a thoracic radiologist (>10 years of experience). Two separate contours were created for each nodule, one including only the solid portion of the nodule and one including any ground-glass components. For each contour 75 features were calculated that measured the attenuation, shape, and texture of the nodule. These features were than input into a feature selection step and four different classifiers to determine if the diagnosis could be predicted from the feature vector. Training and testing was conducted in a resubstitution and leave-one-out fashion and performance was evaluated using ROC techniques.
  
  
  RESULTS
  In a leave-one-out testing methodology the classifiers resulted with areas under the ROC curve (A(Z)) that ranged from 0.68 to 0.92. When evaluating with resubstitution the A(Z) ranged from 0.93 to 1.00.
  
  
  CONCLUSIONS
  Computer-aided diagnosis has the potential to assist radiologists in the task of differentiating solitary pulmonary nodules and in the management of these patients.
authors.affiliation: Department of Radiology, David Geffen School of Medicine at University of California Los Angeles, Thoracic Imaging Research Group, 924 Westwood Blvd, Suite 650, Box 957319, Los Angeles, CA 90095-7319, USA. shah@ucla.edu
authors.forename: Sumit K
authors.initials: SK
authors.lastname: Shah
authors.forename: Michael F
authors.initials: MF
authors.lastname: McNitt-Gray
authors.forename: Sarah R
authors.initials: SR
authors.lastname: Rogers
authors.forename: Jonathan G
authors.initials: JG
authors.lastname: Goldin
authors.forename: Robert D
authors.initials: RD
authors.lastname: Suh
authors.forename: James W
authors.initials: JW
authors.lastname: Sayre
authors.forename: Iva
authors.initials: I
authors.lastname: Petkovska
authors.forename: Hyun J
authors.initials: HJ
authors.lastname: Kim
authors.forename: Denise R
authors.initials: DR
authors.lastname: Aberle
mesh_terms: D003937:Diagnosis, Differential; D006801:Humans; D008175:Lung Neoplasms / Q000000981:diagnostic imaging* / Q000473:pathology; D012372:ROC Curve; D011857:Radiographic Image Interpretation, Computer-Assisted; D003074:Solitary Pulmonary Nodule / Q000000981:diagnostic imaging* / Q000473:pathology; D014057:Tomography, X-Ray Computed