Radiology Associates of North Texas, Dallas, TX, USA.
The Department of Diagnostic Radiology, The University of Texas M. D. Anderson Cancer Center, 1400 Pressler St., Houston, TX, 77030, USA.
Abdom Radiol (NY). 2020 Apr;45(4):1141-1154. doi: 10.1007/s00261-019-02096-y.
To determine whether staging pelvic magnetic resonance imaging (MRI) can distinguish malignant mixed Müllerian tumor (MMMT) from EC.
Thirty-seven treatment-naïve patients with histologically proven uterine MMMT and 42 treatment-naïve patients with EC, treated at our institution, were included in our retrospective study. Staging pelvic MRI scans were reviewed for tumor size, prolapse through cervical os, and other features. Time-intensity curves for tumor and surrounding myometrium regions of interest were generated, and positive enhancement integral (PEI), maximum slope of increase (MSI), and signal enhancement ratio (SER) were measured. The Fisher's exact test or Wilcoxon rank-sum test was used to compare characteristics between disease groups. Multivariate and univariate logistic regression models were used to distinguish MMMT from EC. Receiver operating characteristic analysis and the area under the curve (AUC) were used to evaluate prediction ability.
MMMTs were larger than ECs with higher rate of tumor prolapse and more heterogeneous tumor enhancement compared to ECs. During the late phase of contrast enhancement, 100% of ECs, but only 84% of MMMTs, had lower signal intensity than the myometrium. Threshold PEI ratio ≥ 0.67 predict MMMT with 76% sensitivity, 84%, specificity and 0.83 AUC. Threshold SER ≤ 125 predict MMMT with 90% sensitivity, 50% specificity, and 0.72 AUC.
MMMTs may show more frequent tumor prolapse, more heterogeneous enhancement, delayed iso- or hyper-enhancement, higher PEI ratios, and lower tumor SERs compared with EC. MRI can be used as a biomarker to distinguish MMMT from EC based on the enhancement pattern.
确定盆腔磁共振成像（MRI）分期是否能区分恶性混合性 Müllerian 肿瘤（MMMT）与 EC。
我们对 37 例经组织学证实的子宫 MMMT 患者和 42 例 EC 患者进行了回顾性研究，这些患者均为我院治疗初治患者。对盆腔 MRI 分期扫描的肿瘤大小、宫颈口脱垂以及其他特征进行了回顾性评估。生成肿瘤和周围子宫肌层 ROI 的时间-强度曲线，并测量阳性增强积分（PEI）、最大斜率（MSI）和信号增强比（SER）。Fisher 确切检验或 Wilcoxon 秩和检验用于比较疾病组之间的特征。多变量和单变量逻辑回归模型用于区分 MMMT 和 EC。受试者工作特征分析和曲线下面积（AUC）用于评估预测能力。
MMMT 比 EC 大，肿瘤脱垂率更高，与 EC 相比，肿瘤增强不均匀。在对比增强的晚期，100%的 EC 肿瘤信号强度比子宫肌层低，而只有 84%的 MMMT 肿瘤信号强度比子宫肌层低。阈值 PEI 比值≥0.67 预测 MMMT 的灵敏度为 76%、特异性为 84%、准确性为 83%、AUC 为 0.83。阈值 SER≤125 预测 MMMT 的灵敏度为 90%、特异性为 50%、准确性为 72%、AUC 为 0.72。
与 EC 相比，MMMT 可能表现为更频繁的肿瘤脱垂、不均匀的增强、延迟的等或高增强、更高的 PEI 比值和更低的肿瘤 SER。基于增强模式，MRI 可作为区分 MMMT 和 EC 的生物标志物。
