title: Computer-aided detection (CAD) of lung nodules in CT scans: radiologist performance and reading time with incremental CAD assistance.
abstract: OBJECTIVE
  The diagnostic performance of radiologists using incremental CAD assistance for lung nodule detection on CT and their temporal variation in performance during CAD evaluation was assessed.
  
  
  METHODS
  CAD was applied to 20 chest multidetector-row computed tomography (MDCT) scans containing 190 non-calcified > or =3-mm nodules. After free search, three radiologists independently evaluated a maximum of up to 50 CAD detections/patient. Multiple free-response ROC curves were generated for free search and successive CAD evaluation, by incrementally adding CAD detections one at a time to the radiologists' performance.
  
  
  RESULTS
  The sensitivity for free search was 53% (range, 44%-59%) at 1.15 false positives (FP)/patient and increased with CAD to 69% (range, 59-82%) at 1.45 FP/patient. CAD evaluation initially resulted in a sharp rise in sensitivity of 14% with a minimal increase in FP over a time period of 100 s, followed by flattening of the sensitivity increase to only 2%. This transition resulted from a greater prevalence of true positive (TP) versus FP detections at early CAD evaluation and not by a temporal change in readers' performance. The time spent for TP (9.5 s +/- 4.5 s) and false negative (FN) (8.4 s +/- 6.7 s) detections was similar; FP decisions took two- to three-times longer (14.4 s +/- 8.7 s) than true negative (TN) decisions (4.7 s +/- 1.3 s).
  
  
  CONCLUSIONS
  When CAD output is ordered by CAD score, an initial period of rapid performance improvement slows significantly over time because of non-uniformity in the distribution of TP CAD output and not to a changing reader performance over time.
authors.affiliation: Department of Radiology, Stanford University Medical Center, 300 Pasteur Drive, Room S-072, Stanford, CA 94305-5105, USA. justus.roos@stanford.edu
authors.forename: Justus E
authors.initials: JE
authors.lastname: Roos
authors.forename: David
authors.initials: D
authors.lastname: Paik
authors.forename: David
authors.initials: D
authors.lastname: Olsen
authors.forename: Emily G
authors.initials: EG
authors.lastname: Liu
authors.forename: Lawrence C
authors.initials: LC
authors.lastname: Chow
authors.forename: Ann N
authors.initials: AN
authors.lastname: Leung
authors.forename: Robert
authors.initials: R
authors.lastname: Mindelzun
authors.forename: Kingshuk R
authors.initials: KR
authors.lastname: Choudhury
authors.forename: David P
authors.initials: DP
authors.lastname: Naidich
authors.forename: Sandy
authors.initials: S
authors.lastname: Napel
authors.forename: Geoffrey D
authors.initials: GD
authors.lastname: Rubin
mesh_terms: D000293:Adolescent; D000328:Adult; D000368:Aged; D005260:Female; D006801:Humans; D008175:Lung Neoplasms / Q000000981:diagnostic imaging*; D008297:Male; D008875:Middle Aged; D015588:Observer Variation; D010820:Physicians / Q000706:statistics & numerical data*; D011361:Professional Competence / Q000706:statistics & numerical data*; D011856:Radiographic Image Enhancement / Q000379:methods*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D003074:Solitary Pulmonary Nodule / Q000000981:diagnostic imaging*; D013647:Task Performance and Analysis; D014057:Tomography, X-Ray Computed / Q000379:methods*; D016526:Workload / Q000706:statistics & numerical data*; D055815:Young Adult