Department of Radiology, Guangzhou First People's Hospital, Guangzhou Medical University, Guangzhou, China.
Department of Radiology, Third Affiliated Hospital, Sun Yat-Sen University, Guangzhou, China.
J Magn Reson Imaging. 2018 Feb;47(2):391-400. doi: 10.1002/jmri.25794. Epub 2017 Jun 22.
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.
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.
The PMBC group exhibited significantly higher ADC values for the mean (P = 0.004), 25 (P = 0.004), 50 (P = 0.004), 75 (P = 0.006), and 90 percentiles (P = 0.013) and skewness (P = 0.021) than did the MMBC group. The 25 percentile of ADC values achieved the highest area under the curve (AUC) (0.792), with a cutoff value of 1.345 × 10 mm /s, in distinguishing PMBC and MMBC. The PMBC-A group showed significantly higher ADC values for the mean (P = 0.049), 25 (P = 0.015), and 50 (P = 0.026) percentiles and skewness (P = 0.004) than did the PMBC-B group. The 25 percentile of the ADC cutoff value (1.476 × 10 mm /s) demonstrated the best AUC (0.837) among the ADC values for distinguishing PMBC-A and PMBC-B.
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.
4 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2018;47:391-400.
评估全病变直方图表观扩散系数（ADC）用于描述黏液性乳腺癌（MBC）异质性的效用，并确定哪些 ADC 指标可帮助最佳区分 MBC 亚型。
本回顾性研究纳入了 52 例 MBC 患者，包括 37 例单纯 MBC（PMBC）和 15 例混合 MBC（MMBC）。PMBC 患者进一步分为 PMBC-A（20 例）和 PMBC-B（17 例）组。所有患者均在 1.5T 行术前弥散加权成像（DWI），并生成全病变 ADC 评估。比较 PMBC 与 MMBC、PMBC-A 与 PMBC-B 之间的直方图 ADC 参数，采用受试者工作特征（ROC）曲线分析确定区分这些组的最佳直方图参数。
PMBC 组的平均 ADC 值（P=0.004）、25% ADC 值（P=0.004）、50% ADC 值（P=0.004）、75% ADC 值（P=0.006）和 90% ADC 值（P=0.013）以及峰度（P=0.021）均显著高于 MMBC 组。ADC 值 25%的截断值（1.345×10mm/s）鉴别 PMBC 和 MMBC 的曲线下面积（AUC）最大（0.792）。PMBC-A 组的平均 ADC 值（P=0.049）、25% ADC 值（P=0.015）和 50% ADC 值（P=0.026）以及峰度（P=0.004）均显著高于 PMBC-B 组。ADC 值 25%的截断值（1.476×10mm/s）鉴别 PMBC-A 和 PMBC-B 的 AUC 最大（0.837）。
全病变 ADC 直方图分析可全面评估 MBC，并区分 MBC 亚型。因此，它可能是常规 MRI 的一种有帮助和支持性工具。
4 技术疗效：2 级 J. 磁共振成像 2018；47：391-400.
