title: Small pulmonary nodules: effect of two computer-aided detection systems on radiologist performance.
abstract: OBJECTIVE
  To prospectively compare the effects of two computer-aided detection (CAD) systems on the detection of small pulmonary nodules at multi-detector row computed tomography (CT) by using a consensus panel decision as the reference standard.
  
  
  METHODS
  Institutional review board approval and informed consent were obtained. Multi-detector row CT scans were randomly chosen and prospectively evaluated in 25 patients. Two dedicated CAD systems-ImageChecker CT (R2 Technologies, Sunnyvale, Calif) and Nodule Enhanced Viewing (NEV) (Siemens Medical Solutions, Forchheim, Germany)-were used. Results were interpreted by three radiologists with 1, 3, and 6 years of experience. Images were evaluated without and with CAD software. The reference standard was assessed by a consensus panel consisting of all three radiologists and an adjudicator with 8 years of experience.
  
  
  RESULTS
  A total of 116 pulmonary nodules (average diameter, 3.4 mm; average volume, 32.05 mm3) were found in all data sets during consensus interpretation, which included findings from the CAD software and all radiologists. Overall sensitivity was 73% with ImageChecker CT and 75% with NEV. Overall sensitivity without CAD was 68% for radiologist 1, 78% for radiologist 2, and 82% for radiologist 3. With ImageChecker CT, sensitivity increased to 79% for radiologist 1, 90% for radiologist 2, and 84% for radiologist 3. With NEV, sensitivity increased to 79% for radiologist 1, 90% for radiologist 2, and 86% for radiologist 3. The average number of false-positive findings was six (range, 0-14) with ImageChecker CT and eight (range, 0-22) with NEV.
  
  
  CONCLUSIONS
  Radiologist performance in the interpretation of multi-detector row CT scans can be improved by using CAD systems, with a reduction in the number of false-negative diagnoses. No statistically significant difference in sensitivity was found between the two CAD systems.
authors.affiliation: Department of Diagnostic Radiology, Institute of Medical Statistics, and Department of Occupational Health, Rheinisch-Westfâlische Technische Hochschule Aachen University, Pauwelsstrasse 30, D-52074 Aachen, Germany. das@rad.rwth-aachen.de
authors.forename: Marco
authors.initials: M
authors.lastname: Das
authors.forename: Georg
authors.initials: G
authors.lastname: Mühlenbruch
authors.forename: Andreas H
authors.initials: AH
authors.lastname: Mahnken
authors.forename: Thomas G
authors.initials: TG
authors.lastname: Flohr
authors.forename: Lutz
authors.initials: L
authors.lastname: Gündel
authors.forename: Sven
authors.initials: S
authors.lastname: Stanzel
authors.forename: Thomas
authors.initials: T
authors.lastname: Kraus
authors.forename: Rolf W
authors.initials: RW
authors.lastname: Günther
authors.forename: Joachim E
authors.initials: JE
authors.lastname: Wildberger
mesh_terms: D000328:Adult; D000368:Aged; D002983:Clinical Competence; D003936:Diagnosis, Computer-Assisted / Q000379:methods*; D005260:Female; D006801:Humans; D008175:Lung Neoplasms / Q000000981:diagnostic imaging*; D008297:Male; D008875:Middle Aged; D013902:Radiography, Thoracic; D012680:Sensitivity and Specificity; D012984:Software; D003074:Solitary Pulmonary Nodule / Q000000981:diagnostic imaging*; D018709:Statistics, Nonparametric; D014057:Tomography, X-Ray Computed