Levman Jacob E D, Gallego-Ortiz Cristina, Warner Ellen, Causer Petrina, Martel Anne L
Institute of Biomedical Engineering, Department of Engineering Science, University of Oxford, Old Road Campus Research Building, Headington, Oxford, Oxfordshire, OX3 7DQ, UK.
Department of Medical Biophysics, Sunnybrook Health Sciences Centre, University of Toronto, 2075 Bayview Ave, Toronto, ON, M4N 3M5, Canada.
J Digit Imaging. 2016 Feb;29(1):126-33. doi: 10.1007/s10278-015-9796-2.
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.
磁共振成像(MRI)辅助的癌症筛查已被证明是早期检测乳腺癌的一种高度敏感的方法。计算机辅助检测系统有可能通过将放射科医生的诊断准确性标准化到高水平来改善筛查过程。这项回顾性研究得到了桑尼布鲁克健康科学中心机构审查委员会的批准。本研究比较了一种提出的计算机辅助检测方法(基于相对信号强度的二阶空间导数)与基于MRI的乳腺筛查检查中的信号增强率(SER)性能。使用接收器操作特征(ROC)曲线分析以及自由响应接收器操作特征(FROC)曲线分析进行比较。还提出了一种将所提出的方法与SER方法相结合的改进型计算机辅助检测系统。在乳腺癌检测中,所提出的方法在假阳性标记率方面比SER方法有所改进(通过FROC分析评估)。结合了所提出的方法和SER方法的改进型计算机辅助检测系统产生的ROC结果与SER产生的结果相同,但同时在每次非癌性检查中的假阳性方面比SER方法有所改进。在包含许多小病变的具有挑战性的数据集中,所提出的识别恶性肿瘤的方法在假阳性方面优于SER方法,并可能作为计算机辅助检测系统的一部分在MRI乳腺筛查中发挥有益作用。