Woo Sungmin, Cho Jeong Yeon, Kim Sang Youn, Kim Seung Hyup
Department of Radiology, Seoul National University College of Medicine, Seoul, Republic of Korea.
Department of Radiology, Seoul National University College of Medicine, Seoul, Republic of Korea Institute of Radiation Medicine and Kidney Research Institute, Seoul National University Medical Research Center, Seoul, Republic of Korea
Acta Radiol. 2014 Dec;55(10):1270-7. doi: 10.1177/0284185113514967. Epub 2013 Dec 6.
Until now, several investigators have explored the value of diffusion-weighted magnetic resonance imaging (DWI) for the preoperative tumor grading of endometrial cancer. However, the diagnostic value of DWI with quantitative analysis of apparent diffusion coefficient (ADC) has been controversial.
To explore the role of histogram analysis of ADC maps based on entire tumor volume in determining the grade of endometrial cancer.
This study was IRB-approved with waiver of informed consent. Thirty-three patients with endometrial cancer underwent DWI (b = 0, 600, 1000 s/mm(2)), and corresponding ADC maps were acquired. Regions of interest (ROIs) were drawn on all slices of the ADC map in which the tumor was visualized including areas of necrosis to derive volume-based histographic ADC data. Histogram parameters (5th-95th percentiles, mean, standard deviation, skewness, kurtosis) were correlated with histological grade using one-way ANOVA with Tukey-Kramer test for post hoc comparisons, and were compared between high (grade 3) and low (grades 1/2) grade using Student t-test. ROC curve analysis was performed to determine the optimum threshold value for each parameter, and their corresponding sensitivity and specificity.
The standard deviation, quartile, 75th, 90th, and 95th percentiles of ADC showed significant differences between grades (P ≤ 0.03 for all) and between high and low grades (P ≤ 0.024 for all). There were no significant correlations between tumor grade and other parameters. ROC curve analysis yielded sensitivities and specificities of 75% and 96%, 62.5% and 92%, 100% and 52%, 100% and 72%, and 100% and 88%, using standard deviation, quartile, 75th, 90th, and 95th percentiles for determining high grade with corresponding areas under the curve (AUCs) of 0.787, 0.792, 0.765, 0.880, and 0.925, respectively.
Histogram analysis of ADC maps based on entire tumor volume can be useful for predicting the histological grade of endometrial cancer. The 90th and 95th percentiles of ADC were the most promising parameters for differentiating high from low grade.
迄今为止，已有多位研究者探讨了扩散加权磁共振成像（DWI）在子宫内膜癌术前肿瘤分级中的价值。然而，DWI结合表观扩散系数（ADC）定量分析的诊断价值一直存在争议。
探讨基于整个肿瘤体积的ADC图直方图分析在确定子宫内膜癌分级中的作用。
本研究经机构审查委员会（IRB）批准，豁免知情同意。33例子宫内膜癌患者接受了DWI检查（b = 0、600、1000 s/mm(2)），并获取了相应的ADC图。在可见肿瘤的ADC图的所有层面上绘制感兴趣区（ROI），包括坏死区域，以获取基于体积的直方图ADC数据。使用单向方差分析和Tukey-Kramer检验进行事后比较，将直方图参数（第5至95百分位数、均值、标准差、偏度、峰度）与组织学分级相关联，并使用学生t检验比较高级别（3级）和低级别（1/2级）之间的差异。进行ROC曲线分析以确定每个参数的最佳阈值及其相应的敏感性和特异性。
ADC的标准差、四分位数、第75、90和95百分位数在不同分级之间（所有P≤0.03）以及高级别和低级别之间（所有P≤0.024）均显示出显著差异。肿瘤分级与其他参数之间无显著相关性。ROC曲线分析显示，使用标准差、四分位数、第75、90和95百分位数来确定高级别时，敏感性和特异性分别为75%和96%、62.5%和92%、100%和52%、100%和72%、100%和88%，相应的曲线下面积（AUC）分别为0.787、0.792、0.765、0.880和0.925。
基于整个肿瘤体积的ADC图直方图分析可用于预测子宫内膜癌的组织学分级。ADC的第90和95百分位数是区分高级别和低级别最有前景的参数。
