title: Automated detection of breast cancer in false-negative screening MRI studies from women at increased risk.
abstract: OBJECTIVE
  To evaluate the performance of an automated computer-aided detection (CAD) system to detect breast cancers that were overlooked or misinterpreted in a breast MRI screening program for women at increased risk.
  
  
  METHODS
  We identified 40 patients that were diagnosed with breast cancer in MRI and had a prior MRI examination reported as negative available. In these prior examinations, 24 lesions could retrospectively be identified by two breast radiologists in consensus: 11 were scored as visible and 13 as minimally visible. Additionally, 120 normal scans were collected from 120 women without history of breast cancer or breast surgery participating in the same MRI screening program. A fully automated CAD system was applied to this dataset to detect malignant lesions.
  
  
  RESULTS
  At 4 false-positives per normal case, the sensitivity for the detection of cancer lesions that were visible or minimally visible in retrospect in prior-negative examinations was 0.71 (95% CI=0.38-1.00) and 0.31 (0.07-0.59), respectively.
  
  
  CONCLUSIONS
  A substantial proportion of cancers that were misinterpreted or overlooked in an MRI screening program was detected by a CAD system in prior-negative examinations. It has to be clarified with further studies if such a CAD system has an influence on the number of misinterpreted and overlooked cancers in clinical practice when results are given to a radiologist.
authors.affiliation: Department of Radiology and Nuclear Medicine, Radboud University Medical Center, 6525 GA, Nijmegen, The Netherlands; Department of Computer Architecture and Technology, University of Girona, 17071 Girona, Spain. Electronic address: albert.gubernmerida@radboudumc.nl.
authors.forename: Albert
authors.initials: A
authors.lastname: Gubern-Mérida
authors.affiliation: Department of Radiology and Nuclear Medicine, Radboud University Medical Center, 6525 GA, Nijmegen, The Netherlands.
authors.forename: Suzan
authors.initials: S
authors.lastname: Vreemann
authors.affiliation: Department of Computer Architecture and Technology, University of Girona, 17071 Girona, Spain.
authors.forename: Robert
authors.initials: R
authors.lastname: Martí
authors.affiliation: Department of Radiology and Nuclear Medicine, Radboud University Medical Center, 6525 GA, Nijmegen, The Netherlands.
authors.forename: Jaime
authors.initials: J
authors.lastname: Melendez
authors.affiliation: Department of Radiology and Nuclear Medicine, Radboud University Medical Center, 6525 GA, Nijmegen, The Netherlands.
authors.forename: Susanne
authors.initials: S
authors.lastname: Lardenoije
authors.affiliation: Department of Radiology and Nuclear Medicine, Radboud University Medical Center, 6525 GA, Nijmegen, The Netherlands.
authors.forename: Ritse M
authors.initials: RM
authors.lastname: Mann
authors.affiliation: Department of Radiology and Nuclear Medicine, Radboud University Medical Center, 6525 GA, Nijmegen, The Netherlands.
authors.forename: Nico
authors.initials: N
authors.lastname: Karssemeijer
authors.affiliation: Department of Radiology and Nuclear Medicine, Radboud University Medical Center, 6525 GA, Nijmegen, The Netherlands.
authors.forename: Bram
authors.initials: B
authors.lastname: Platel
mesh_terms: D000328:Adult; D000368:Aged; D001940:Breast / Q000473:pathology; D001943:Breast Neoplasms / Q000175:diagnosis / Q000473:pathology*; D005188:False Negative Reactions; D005260:Female; D006801:Humans; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D008279:Magnetic Resonance Imaging / Q000379:methods*; D008327:Mammography; D008408:Mastectomy; D008875:Middle Aged; D012189:Retrospective Studies; D012306:Risk; D012680:Sensitivity and Specificity
keywords: Breast cancer; Computer-aided detection; Magnetic resonance imaging; Screening