Department of Diagnostic Radiology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, No 17, Panjiayuannanli, Chaoyang District, Beijing, 100021, PR China.
Department of Pathology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, No 17, Panjiayuannanli, Chaoyang District, Beijing, 100021, PR China.
Eur J Radiol. 2020 Sep;130:109190. doi: 10.1016/j.ejrad.2020.109190. Epub 2020 Jul 24.
This prospective study aimed to investigate the value of kinetic parameters derived from dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) in differentiating uterine endometrioid adenocarcinoma (EAC) from adenocarcinoma of cervix (AdC).
Seventy-five newly diagnosed patients with distinctive pathology underwent DCE-MRI. Observers independently calculated the tumor diameters and DCE-MRI parameters using both population and individual-based arterial input function (AIF). Inter-observer consistency was evaluated, and a comparative analysis between EAC (n = 47) and AdC (n = 28) was performed. Regression analysis was used to select parameters that best distinguished EAC from AdC, and to generate predictive models. Receiver operating characteristic curve (ROC) was applied to calculate the diagnostic efficiency of single parameter and the predictive models.
Inter-observer consistency was excellent (intra-class correlation [ICC] = 0.902-0.981), especially when calculated via population AIF with relatively higher ICC and smaller SD on Bland-Altman plot. Tumor diameters were not correlated with tumor types. All the DCE-MRI parameters were lower in EAC compared to AdC, except K by population AIF and TTP by both sets of AIFs. The statistical parameters were V, Maxslop, and Maxconc by population AIF, and Maxslop and K by individual AIF included in the predictive models, respectively. The two predictive models with combined parameters showed improved diagnostic efficiency in differentiating these two diseases compared with a single parameter.
DCE-MRI can quantitatively evaluate the perfusion difference between EAC and AdC, thus improving the identification of uterine adenocarcinoma with uncertain biopsy pathology.
本前瞻性研究旨在探讨动态对比增强磁共振成像（DCE-MRI）衍生的动力学参数在鉴别子宫子宫内膜样腺癌（EAC）与子宫颈腺癌（AdC）中的价值。
75 例经病理明确诊断的新发病例接受了 DCE-MRI 检查。观察者分别使用基于群体和个体的动脉输入函数（AIF）独立计算肿瘤直径和 DCE-MRI 参数。评估了观察者间的一致性，并对 EAC（n=47）和 AdC（n=28）进行了对比分析。采用回归分析选择最佳鉴别 EAC 和 AdC 的参数，并生成预测模型。应用受试者工作特征曲线（ROC）计算单个参数和预测模型的诊断效率。
观察者间的一致性非常好（组内相关系数[ICC]=0.902-0.981），尤其是使用群体 AIF 计算时 ICC 较高，Bland-Altman 图上的标准差较小。肿瘤直径与肿瘤类型无相关性。除了基于群体 AIF 的 K 和基于两种 AIF 的 TTP 外，EAC 的所有 DCE-MRI 参数均低于 AdC。预测模型中包含的参数是群体 AIF 的 V、Maxslop 和 Maxconc，以及个体 AIF 的 Maxslop 和 K。与单个参数相比，包含联合参数的两个预测模型在鉴别这两种疾病方面显示出了更高的诊断效率。
DCE-MRI 可以定量评估 EAC 和 AdC 之间的灌注差异，从而提高对活检病理不确定的子宫腺癌的识别能力。
