科研之友
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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 x 10(-3)mm(2)/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 x 10(-3)mm(2)/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.
