Department of Radiology, Jinshan Hospital, Fudan University, Longhang Road, Shanghai, 201508, People's Republic of China.
Department of Radiology, Obstetrics and Gynecology Hospital, Fudan University, Shenyang Road, 200090, Shanghai, People's Republic of China.
Eur J Radiol. 2021 Jul;140:109745. doi: 10.1016/j.ejrad.2021.109745. Epub 2021 Apr 30.
To assess the value of volumetric ADC histogram metrics in evaluating the histological subtype and grade of endometrial cancer.
Preoperative MRI datasets of 317 patients with endometrial cancer were used to obtain volumetric ADC histogram metrics (tumour volume; minADC, maxADC and meanADC; 10th, 25th, 50th, 75th and 90th percentiles of ADC; skewness; and kurtosis). The Mann-Whitney test or Student's t-test was used to compare the difference in ADC histogram metrics between endometrioid adenocarcinomas (EACs) and serous endometrial cancers (SECs) and between different tumour grades (G1, G2, G3). The area under the curve (AUC) of the receiver operating characteristic (ROC) curve was used to evaluate the performance of ADC histogram metrics or combined models in predicting the tumour subtype and grade.
SECs showed a significantly larger tumour volume (P < 0.001) and lower meanADC, 50th, 75th and 90th percentiles of ADC than EACs (all P < 0.05). MinADC, maxADC, meanADC, 10th, 25th, 50th, 75th, 90th percentiles of ADC were significantly higher in G1 than in G2 and G3 EACs (all P < 0.05), while were not significantly different between G2 and G3 EACs (all P > 0.05). A tumour volume ≥ 7.752 cm allowed for the prediction of SECs, with an AUC of 0.765 (0.714-0.810). A meanADC ≥ 0.892 × 10 mm/s enabled to discriminate G1 from G2 and G3 EACs, with an AUC of 0.818 (0.769-0.861).
Volumetric ADC histogram analysis is helpful for non-invasive preoperatively predicting the subtype of endometrial cancer and differentiating G1 from G2 and G3 EACs.
评估容积 ADC 直方图指标在评估子宫内膜癌组织学亚型和分级中的价值。
使用 317 例子宫内膜癌患者的术前 MRI 数据集获得容积 ADC 直方图指标（肿瘤体积；最小 ADC、最大 ADC 和平均 ADC；ADC 的第 10、25、50、75 和 90 百分位数；偏度；和峰度）。 Mann-Whitney 检验或 Student's t 检验用于比较子宫内膜样腺癌（EAC）和浆液性子宫内膜癌（SEC）之间以及不同肿瘤分级（G1、G2、G3）之间 ADC 直方图指标的差异。受试者工作特征（ROC）曲线下面积（AUC）用于评估 ADC 直方图指标或联合模型预测肿瘤亚型和分级的性能。
SEC 的肿瘤体积明显较大（P < 0.001），平均 ADC、50 百分位数、75 百分位数和 90 百分位数 ADC 明显低于 EAC（均 P < 0.05）。G1 比 G2 和 G3 EAC 的 minADC、maxADC、平均 ADC、10 百分位数、25 百分位数、50 百分位数、75 百分位数和 90 百分位数 ADC 均显著升高（均 P < 0.05），而 G2 和 G3 EAC 之间无显著差异（均 P > 0.05）。肿瘤体积≥7.752 cm 可预测 SEC，AUC 为 0.765（0.714-0.810）。平均 ADC≥0.892×10 mm/s 可区分 G1 与 G2 和 G3 EAC，AUC 为 0.818（0.769-0.861）。
容积 ADC 直方图分析有助于术前无创预测子宫内膜癌的亚型，并区分 G1 与 G2 和 G3 EAC。
