Bourgioti Charis, Chatoupis Konstantinos, Panourgias Evangelia, Tzavara Chara, Sarris Kyrillos, Rodolakis Alexandros, Moulopoulos Lia Angela
Department of Radiology, Aretaieion Hospital, Medical School, University of Athens, 76 Vassilisis Sofias Ave., 11528, Athens, Greece.
Department of Health, Epidemiology and Medical Statistics, Medical School, University of Athens, 25 Alexandroupoleos Str., 11527, Athens, Greece.
Abdom Imaging. 2015 Oct;40(7):2529-40. doi: 10.1007/s00261-015-0399-7.
To report discriminant MRI features between cervical and endometrial carcinomas and to design an MRI- scoring system, with the potential to predict the origin of uterine cancer (cervix or endometrium) in histologically indeterminate cases.
Dedicated pelvic MRIs of 77 patients with uterine tumors involving both cervix and corpus were retrospectively analyzed by two experts in female imaging. Seven MRI tumor characteristics were statistically tested for their discriminant ability for tumor origin compared to final histology: tumor location, perfusion pattern, rim enhancement, depth of myometrial invasion, cervical stromal integrity, intracavitary mass, and retained endometrial secretions. Kappa values were estimated to assess the levels of inter-rater reliability. On the basis of positive likelihood ratio values, an MRI-score was assigned.
K value was excellent for most of the imaging criteria. Using ROC curve analysis, the estimated optimal cut-off for the MRI-scoring system was 4 with 96.6% sensitivity and 100% specificity. Using a ≥4 cut-off for cervical cancers and <4 for endometrial cancers, 97.4% of the patients were correctly classified. 2/58 patients with cervical cancer had MRI score <4 and none of the patients with endometrial cancer had MRI score >4. The area under curve of the MRI-scoring system was 0.99 (95% CI 0.98-1.00). When the MRI-score was applied to 20/77 patients with indeterminate initial biopsy and to 5/26 surgically treated patients with erroneous pre-op histology, all cases were correctly classified.
The produced MRI-scoring system may be a reliable problem-solving tool for the differential diagnosis of cervical vs. endometrial cancer in cases of equivocal histology.
报告宫颈癌和子宫内膜癌之间的鉴别性MRI特征,并设计一种MRI评分系统,以预测组织学诊断不明确的子宫癌(宫颈或子宫内膜)的起源。
由两位女性影像学专家对77例子宫肿瘤累及宫颈和宫体的患者进行的专用盆腔MRI进行回顾性分析。对七个MRI肿瘤特征与最终组织学结果相比的肿瘤起源鉴别能力进行了统计学检验:肿瘤位置、灌注模式、边缘强化、肌层浸润深度、宫颈基质完整性、腔内肿块和保留的子宫内膜分泌物。估计kappa值以评估评分者间的可靠性水平。根据阳性似然比值,分配一个MRI评分。
大多数成像标准的K值都很好。使用ROC曲线分析,MRI评分系统的估计最佳截断值为4,敏感性为96.6%,特异性为100%。使用宫颈癌截断值≥4,子宫内膜癌截断值<4,97.4%的患者被正确分类。58例宫颈癌患者中有2例MRI评分<4,子宫内膜癌患者中无一例MRI评分>4。MRI评分系统的曲线下面积为0.99(95%CI 0.98-1.00)。当将MRI评分应用于77例中20例初始活检不明确的患者以及26例手术治疗的术前组织学错误的患者时,所有病例均被正确分类。
所产生的MRI评分系统可能是一种可靠的解决问题的工具,用于在组织学不明确的情况下鉴别宫颈癌和子宫内膜癌。