Yuan Guo1, Qing-Cong Kong2, Ye-Qing Zhu2, Zhen-Zhen Liu2, Ling-Rong Peng2, Wen-Jie Tang1, Rui-Meng Yang1, Jia-Jun Xie1, Chun-Ling Liu3. 1. Department of Radiology, Guangzhou First People's Hospital, Guangzhou Medical University, Guangzhou, China. 2. Department of Radiology, Third Affiliated Hospital, Sun Yat-Sen University, Guangzhou, China. 3. Department of Radiology, Guangdong Academy of Medical Sciences/Guangdong General Hospital, Guangzhou, China.
Abstract
PURPOSE: To evaluate the utility of the whole-lesion histogram apparent diffusion coefficient (ADC) for characterizing the heterogeneity of mucinous breast carcinoma (MBC) and to determine which ADC metrics may help to best differentiate subtypes of MBC. MATERIALS AND METHODS: This retrospective study involved 52 MBC patients, including 37 pure MBC (PMBC) and 15 mixed MBC (MMBC). The PMBC patients were subtyped into PMBC-A (20 cases) and PMBC-B (17 cases) groups. All patients underwent preoperative diffusion-weighted imaging (DWI) at 1.5T and the whole-lesion ADC assessments were generated. Histogram-derived ADC parameters were compared between PMBC vs. MMBC and PMBC-A vs. PMBC-B, and receiver operating characteristic (ROC) curve analysis was used to determine optimal histogram parameters for differentiating these groups. RESULTS: The PMBC group exhibited significantly higher ADC values for the mean (P = 0.004), 25th (P = 0.004), 50th (P = 0.004), 75th (P = 0.006), and 90th percentiles (P = 0.013) and skewness (P = 0.021) than did the MMBC group. The 25th percentile of ADC values achieved the highest area under the curve (AUC) (0.792), with a cutoff value of 1.345 × 10-3 mm2 /s, in distinguishing PMBC and MMBC. The PMBC-A group showed significantly higher ADC values for the mean (P = 0.049), 25th (P = 0.015), and 50th (P = 0.026) percentiles and skewness (P = 0.004) than did the PMBC-B group. The 25th percentile of the ADC cutoff value (1.476 × 10-3 mm2 /s) demonstrated the best AUC (0.837) among the ADC values for distinguishing PMBC-A and PMBC-B. CONCLUSION: Whole-lesion ADC histogram analysis enables comprehensive evaluation of an MBC in its entirety and differentiating subtypes of MBC. Thus, it may be a helpful and supportive tool for conventional MRI. LEVEL OF EVIDENCE: 4 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2018;47:391-400.
PURPOSE: To evaluate the utility of the whole-lesion histogram apparent diffusion coefficient (ADC) for characterizing the heterogeneity of mucinous breast carcinoma (MBC) and to determine which ADC metrics may help to best differentiate subtypes of MBC. MATERIALS AND METHODS: This retrospective study involved 52 MBCpatients, including 37 pure MBC (PMBC) and 15 mixed MBC (MMBC). The PMBCpatients were subtyped into PMBC-A (20 cases) and PMBC-B (17 cases) groups. All patients underwent preoperative diffusion-weighted imaging (DWI) at 1.5T and the whole-lesion ADC assessments were generated. Histogram-derived ADC parameters were compared between PMBC vs. MMBC and PMBC-A vs. PMBC-B, and receiver operating characteristic (ROC) curve analysis was used to determine optimal histogram parameters for differentiating these groups. RESULTS: The PMBC group exhibited significantly higher ADC values for the mean (P = 0.004), 25th (P = 0.004), 50th (P = 0.004), 75th (P = 0.006), and 90th percentiles (P = 0.013) and skewness (P = 0.021) than did the MMBC group. The 25th percentile of ADC values achieved the highest area under the curve (AUC) (0.792), with a cutoff value of 1.345 × 10-3 mm2 /s, in distinguishing PMBC and MMBC. The PMBC-A group showed significantly higher ADC values for the mean (P = 0.049), 25th (P = 0.015), and 50th (P = 0.026) percentiles and skewness (P = 0.004) than did the PMBC-B group. The 25th percentile of the ADC cutoff value (1.476 × 10-3 mm2 /s) demonstrated the best AUC (0.837) among the ADC values for distinguishing PMBC-A and PMBC-B. CONCLUSION: Whole-lesion ADC histogram analysis enables comprehensive evaluation of an MBC in its entirety and differentiating subtypes of MBC. Thus, it may be a helpful and supportive tool for conventional MRI. LEVEL OF EVIDENCE: 4 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2018;47:391-400.