title: A Metric for Reducing False Positives in the Computer-Aided Detection of Breast Cancer from Dynamic Contrast-Enhanced Magnetic Resonance Imaging Based Screening Examinations of High-Risk Women.
abstract: Magnetic resonance imaging (MRI)-enabled cancer screening has been shown to be a highly sensitive method for the early detection of breast cancer. Computer-aided detection systems have the potential to improve the screening process by standardizing radiologists to a high level of diagnostic accuracy. This retrospective study was approved by the institutional review board of Sunnybrook Health Sciences Centre. This study compares the performance of a proposed method for computer-aided detection (based on the second-order spatial derivative of the relative signal intensity) with the signal enhancement ratio (SER) on MRI-based breast screening examinations. Comparison is performed using receiver operating characteristic (ROC) curve analysis as well as free-response receiver operating characteristic (FROC) curve analysis. A modified computer-aided detection system combining the proposed approach with the SER method is also presented. The proposed method provides improvements in the rates of false positive markings over the SER method in the detection of breast cancer (as assessed by FROC analysis). The modified computer-aided detection system that incorporates both the proposed method and the SER method yields ROC results equal to that produced by SER while simultaneously providing improvements over the SER method in terms of false positives per noncancerous exam. The proposed method for identifying malignancies outperforms the SER method in terms of false positives on a challenging dataset containing many small lesions and may play a useful role in breast cancer screening by MRI as part of a computer-aided detection system.
authors: Institute of Biomedical Engineering, Department of Engineering Science, University of Oxford, Old Road Campus Research Building, Headington, Oxford, Oxfordshire, OX3 7DQ, UK. jacob.levman@childrens.harvard.edu.
authors: Jacob E D
authors: JE
authors: Levman
authors: Department of Medical Biophysics, Sunnybrook Health Sciences Centre, University of Toronto, 2075 Bayview Ave, Toronto, ON, M4N 3M5, Canada.
authors: Cristina
authors: C
authors: Gallego-Ortiz
authors: Division of Medical Oncology, Department of Medicine, Sunnybrook Health Sciences Centre, 2075 Bayview Ave, Toronto, ON, M4N 3M5, Canada.
authors: Ellen
authors: E
authors: Warner
authors: Medical Imaging Department, North York General Hospital, 4001 Leslie Street, Toronto, ON, M2K 1E1, Canada.
authors: Petrina
authors: P
authors: Causer
authors: Department of Medical Biophysics, Sunnybrook Health Sciences Centre, University of Toronto, 2075 Bayview Ave, Room S668, Toronto, ON, M4N 3M5, Canada.
authors: Anne L
authors: AL
authors: Martel
mesh_terms: D001943:Breast Neoplasms / Q000000981:diagnostic imaging* / Q000473:pathology; D003287:Contrast Media; D055088:Early Detection of Cancer / Q000379:methods; D005189:False Positive Reactions; D005260:Female; D019786:Gadolinium DTPA; D006801:Humans; D007089:Image Enhancement; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D008279:Magnetic Resonance Imaging / Q000379:methods*; D010363:Pattern Recognition, Automated / Q000379:methods; D015203:Reproducibility of Results; D012189:Retrospective Studies; D012306:Risk; D012680:Sensitivity and Specificity
chemical_list: D003287:Contrast Media; D019786:Gadolinium DTPA
keywords: Breast cancer; Computer-aided detection; Free response receiver operating characteristic curve analysis; Magnetic resonance imaging; Receiver operating characteristic curve analysis