Detection and classification of contrast-enhancing masses by a fully automatic computer-assisted diagnosis system for breast MRI

被引:36
作者
Renz, Diane M. [1 ]
Boettcher, Joachim [2 ]
Diekmann, Felix
Poellinger, Alexander
Maurer, Martin H.
Pfeil, Alexander [3 ]
Streitparth, Florian
Collettini, Federico
Bick, Ulrich
Hamm, Bernd
Fallenberg, Eva M.
机构
[1] Charite Univ Med Berlin, Dept Radiol, Campus Virchow Clin, D-13353 Berlin, Germany
[2] SRH Clin Gera, Inst Diagnost & Intervent Radiol, Gera, Germany
[3] Univ Jena, Dept Internal Med 3, Jena Univ Hosp, Jena, Germany
关键词
computer-assisted diagnosis; CAD; breast MRI; sensitivity; specificity; diagnostic accuracy; ARTIFICIAL NEURAL-NETWORKS; DIFFERENTIAL-DIAGNOSIS; OBSERVER VARIABILITY; LESIONS; MAMMOGRAPHY; FEATURES; BENIGN; PERFORMANCE; PREDICTION; ALGORITHM;
D O I
10.1002/jmri.23516
中图分类号
R8 [特种医学]; R445 [影像诊断学];
学科分类号
1002 ; 100207 ; 1009 ;
摘要
Purpose: To evaluate a fully automatic computer-assisted diagnosis (CAD) method for breast magnetic resonance imaging (MRI), which considered dynamic as well as morphologic parameters and linked those to descriptions laid down in the Breast Imaging Reporting and Data System (BI-RADS) MRI atlas. Materials and Methods: MR images of 108 patients with 141 histologically proven mass-like lesions (88 malignant, 53 benign) were included. The CAD system automatically performed the following processing steps: 3D nonrigid motion correction, detection of lesions by a segmentation algorithm, extraction of multiple dynamic and morphologic parameters, and classification of lesions. As one final result, the lesions were categorized by defining their probability of malignancy; this so-called morpho-dynamic index (MDI) ranged from 0%-100%. The results of the CAD system were correlated with histopathologic findings. Results: The CAD system had a high detection rate of the histologically proven lesions, missing only two malignancies of invasive multifocal carcinomas and four benign lesions (three fibroadenomas, one atypical ductal hyperplasia). The 86 detected malignant lesions showed a mean MDI of 86.1% (615.4%); the mean MDI of the 49 coded benign lesions was 41.8% (622.0%; P < 0.001). Based on receiver-operating characteristic analysis, the diagnostic accuracy of the CAD system was 93.5%. Using an appropriate cutoff value (MDI 50%), sensitivity was 96.5% combined with specificity of 75.5%. Conclusion: The fully automatic CAD technique seems to reliably distinguish between benign and malignant mass-like breast tumors. Observer-independent CAD may be a promising additional tool for the interpretation of breast MRI in the clinical routine. Key Words: computer-assisted diagnosis; CAD; breast MRI; sensitivity; specificity; diagnostic accuracy J. Magn. Reson. Imaging 2012; 35: 1077-1088. (C) 2012 Wiley Periodicals, Inc.
引用
收藏
页码:1077 / 1088
页数:12
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