title: A method for evaluating the performance of computer-aided detection of pulmonary nodules in lung cancer CT screening: detection limit for nodule size and density.
abstract: OBJECTIVE
  We propose the application of virtual nodules to evaluate the performance of computer-aided detection (CAD) of lung nodules in cancer screening using low-dose CT.
  
  
  METHODS
  The virtual nodules were generated based on the spatial resolution measured for a CT system used in an institution providing cancer screening and were fused into clinical lung images obtained at that institution, allowing site specificity. First, we validated virtual nodules as an alternative to artificial nodules inserted into a phantom. In addition, we compared the results of CAD analysis between the real nodules (n = 6) and the corresponding virtual nodules. Subsequently, virtual nodules of various sizes and contrasts between nodule density and background density (ΔCT) were inserted into clinical images (n = 10) and submitted for CAD analysis.
  
  
  RESULTS
  In the validation study, 46 of 48 virtual nodules had the same CAD results as artificial nodules (kappa coefficient = 0.913). Real nodules and the corresponding virtual nodules showed the same CAD results. The detection limits of the tested CAD system were determined in terms of size and density of peripheral lung nodules; we demonstrated that a nodule with a 5-mm diameter was detected when the nodule had a ΔCT > 220 HU.
  
  
  CONCLUSIONS
  Virtual nodules are effective in evaluating CAD performance using site-specific scan/reconstruction conditions. Advances in knowledge: Virtual nodules can be an effective means of evaluating site-specific CAD performance. The methodology for guiding the detection limit for nodule size/density might be a useful evaluation strategy.
authors.affiliation: 1 Graduate School of Health Sciences, Niigata University, Niigata, Japan.|2 Department of Radiology, Sannocho Hospital, Niigata, Japan.
authors.forename: Hajime
authors.initials: H
authors.lastname: Kobayashi
authors.affiliation: 1 Graduate School of Health Sciences, Niigata University, Niigata, Japan.
authors.forename: Masaki
authors.initials: M
authors.lastname: Ohkubo
authors.affiliation: 1 Graduate School of Health Sciences, Niigata University, Niigata, Japan.
authors.forename: Akihiro
authors.initials: A
authors.lastname: Narita
authors.affiliation: 1 Graduate School of Health Sciences, Niigata University, Niigata, Japan.|3 Department of Radiography and Radiotherapy, Faculty of Allied Health Sciences, University of Peradeniya, Peradeniya, Sri Lanka.
authors.forename: Janaka C
authors.initials: JC
authors.lastname: Marasinghe
authors.affiliation: 4 Fujitsu Ltd, Tokyo, Japan.
authors.forename: Kohei
authors.initials: K
authors.lastname: Murao
authors.affiliation: 5 Chiba Kensei Hospital, Chiba, Japan.
authors.forename: Toru
authors.initials: T
authors.lastname: Matsumoto
authors.affiliation: 6 JA Nagano Azumi General Hospital, Nagano, Japan.|7 Present Address: Chest Imaging Division, Nagano Health Promotion Corporation, Nagano, Japan.
authors.forename: Shusuke
authors.initials: S
authors.lastname: Sone
authors.affiliation: 1 Graduate School of Health Sciences, Niigata University, Niigata, Japan.
authors.forename: Shinichi
authors.initials: S
authors.lastname: Wada
mesh_terms: D006801:Humans; D007091:Image Processing, Computer-Assisted / Q000379:methods*; D057230:Limit of Detection; D008175:Lung Neoplasms / Q000000981:diagnostic imaging*; D055613:Multiple Pulmonary Nodules / Q000000981:diagnostic imaging*; D019047:Phantoms, Imaging; D011857:Radiographic Image Interpretation, Computer-Assisted / Q000379:methods; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D003074:Solitary Pulmonary Nodule / Q000178:diet therapy*; D014057:Tomography, X-Ray Computed / Q000379:methods*