Qiufeng Zhao1, Tianwen Xie2, Caixia Fu3, Ling Chen4, Qianming Bai5, Robert Grimm6, Weijun Peng7, Song Wang8. 1. Department of Radiology, Longhua Hospital, Shanghai University of Traditional Chinese Medicine, Shanghai, China. 2. Department of Radiology, Fudan University Shanghai Cancer Center, Shanghai, China; Department of Oncology, Fudan University Shanghai Cancer Center, Shanghai, China. 3. MR Application Development, Siemens Shenzhen Magnetic Resonance, Shenzhen, China. 4. Department of Pathology, Longhua Hospital, Shanghai University of Traditional Chinese Medicine, Shanghai, China. 5. Department of Pathology, Fudan University Shanghai Cancer Center, Shanghai, China. 6. MR Application Predevelopment, Siemens Healthcare, Erlangen, Germany. 7. Department of Radiology, Fudan University Shanghai Cancer Center, Shanghai, China; Department of Oncology, Fudan University Shanghai Cancer Center, Shanghai, China. Electronic address: pengweijun2017@163.com. 8. Department of Radiology, Longhua Hospital, Shanghai University of Traditional Chinese Medicine, Shanghai, China. Electronic address: songwangws@163.com.
Abstract
PURPOSE: The aim of this study was to investigate whether whole-lesion histogram and texture analysis using apparent diffusion coefficient can discriminate between idiopathic granulomatous mastitis (IGM) and invasive breast carcinoma (IBC), both of which appeared as non-mass enhancement lesions without rim-enhanced masses. METHOD: This retrospective study included 58 pathology-proven female patients at two independent study sites (27 IGM patients and 31 IBC patients). Diffusion-weighted imaging (3b values, 50, 400 or 500, and 800 s/mm2) was performed using 1.5 T or 3 T MR scanners from the same vendor. Whole-lesions were segmented and 11 features were extracted. Univariate analysis and multivariate logistic regression analysis were performed to identify significant variables for differentiating IGM from IBC. Receiver operating characteristic curve was assessed. The interobserver reliability between two observers for the histogram and texture measurement was also reported. RESULTS: The 5th percentile, difference entropy and entropy of apparent diffusion coefficient showed significant differences between the two groups. An area under the curve of 0.778 (95 % CI: 0.648, 0.908), accuracy of 79.3 %, and sensitivity of 87.1 % was achieved using these three significant features. No significant feature was found with the multivariate analysis. For the interobserver reliability, all apparent diffusion coefficient parameters except skewness and kurtosis indicated good or excellent agreement, while these two features showed moderate agreement. CONCLUSIONS: Whole-lesion histogram and texture analysis using apparent diffusion coefficient provide a non-invasive analytical approach to the differentiation between IGM and IBC, both presenting with non-mass enhancement without rim-enhanced masses.
PURPOSE: The aim of this study was to investigate whether whole-lesion histogram and texture analysis using apparent diffusion coefficient can discriminate between idiopathic granulomatous mastitis (IGM) and invasive breast carcinoma (IBC), both of which appeared as non-mass enhancement lesions without rim-enhanced masses. METHOD: This retrospective study included 58 pathology-proven female patients at two independent study sites (27 IGMpatients and 31 IBCpatients). Diffusion-weighted imaging (3b values, 50, 400 or 500, and 800 s/mm2) was performed using 1.5 T or 3 T MR scanners from the same vendor. Whole-lesions were segmented and 11 features were extracted. Univariate analysis and multivariate logistic regression analysis were performed to identify significant variables for differentiating IGM from IBC. Receiver operating characteristic curve was assessed. The interobserver reliability between two observers for the histogram and texture measurement was also reported. RESULTS: The 5th percentile, difference entropy and entropy of apparent diffusion coefficient showed significant differences between the two groups. An area under the curve of 0.778 (95 % CI: 0.648, 0.908), accuracy of 79.3 %, and sensitivity of 87.1 % was achieved using these three significant features. No significant feature was found with the multivariate analysis. For the interobserver reliability, all apparent diffusion coefficient parameters except skewness and kurtosis indicated good or excellent agreement, while these two features showed moderate agreement. CONCLUSIONS: Whole-lesion histogram and texture analysis using apparent diffusion coefficient provide a non-invasive analytical approach to the differentiation between IGM and IBC, both presenting with non-mass enhancement without rim-enhanced masses.
Authors: Yan Li; Zhenlu L Yang; Wenzhi Z Lv; Yanjin J Qin; Caili L Tang; Xu Yan; Yihao H Guo; Liming M Xia; Tao Ai Journal: Front Oncol Date: 2021-09-22 Impact factor: 6.244