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An ultrasound algorithm for identification of endometrial cancer

机译:超声诊断子宫内膜癌的算法

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摘要

Objective To propose a scoring system to predict endometrial cancer using different ultrasound image characteristics at gray-scale, with and without enhancement by gel infusion, and Doppler transvaginal sonography (TVS) and to evaluate intra- and interobserver variability in assessment of these characteristics. Method Unenhanced TVS, Doppler examinations and gel infusion sonography (GIS) were performed prospectively in 174 consecutive postmenopausal women with endometrial thickness ≥ 5 mm. The reference standard in all women was hysteroscopy or hysterectomy with pathological evaluation of the malignancy. The presence of various ultrasound pattern characteristics indicative of endometrial malignancy and intra- and interobserver variability in their assessment were evaluated. Multivariate logistic regression was used to correlate image and clinical parameters to presence of endometrial cancer. Results A simple Doppler flow score (which considered only presence of vascularity and not presence of single/double dominant vessel, multiple vessels, large vessels, color splash or densely packed vessels) had an area under the receiver-operating characteristics curve (AUC) of 0.83 in the prediction of endometrial cancer. Models including endometrial thickness, Doppler score and interrupted endomyometrial junction on unenhanced TVS predicted endometrial cancer with an AUC of 0.95 (95% CI, 0.92-0.99) and, with addition of irregular surface on GIS, the AUC was 0.97 (95% CI, 0.94-0.99). A risk of endometrial cancer (REC) scoring system based on body mass index, Doppler score, endometrial thickness and interrupted endomyometrial junction on unenhanced TVS and irregular surface at GIS performed very well at identifying endometrial cancer; at a REC-score of ≥ 4 the sensitivity for detection of endometrial cancer was 91% and specificity was 94%. Observers agreed in 82.3% of cases (kappa, 0.63 (0.48-0.78)) when subjective parameters were analyzed in stored videoclips. Conclusion Our observer-dependent proposed scoring system seems to perform well in the prediction of endometrial cancer and should be tested in future studies.
机译:目的:提出一种评分系统,使用不同的灰度超声图像特征预测子宫内膜癌,并通过凝胶输注和多普勒阴道超声检查(TVS)增强或不增强,并评估观察者之间和观察者之间的变异性。方法对174例子宫内膜厚度≥5 mm的绝经后妇女进行前瞻性的TVS检查,多普勒检查和凝胶输注超声检查(GIS)。所有妇女的参考标准是宫腔镜检查或子宫切除术,并进行恶性病理评估。评估了各种超声模式特征的存在,这些特征指示子宫内膜恶性以及评估中观察者间和观察者间的差异。使用多元逻辑回归将图像和临床参数与子宫内膜癌的存在相关联。结果简单的多普勒血流评分(仅考虑血管的存在,不考虑单个/双重显性血管,多个血管,大血管,色斑或密集填充的血管的存在)在接受者操作特征曲线(AUC)下的面积为0.83预测子宫内膜癌。包括未增生的TVS上的子宫内膜厚度,多普勒评分和子宫内膜交界处中断在内的模型预测的子宫内膜癌的AUC为0.95(95%CI,0.92-0.99),并且在GIS上添加不规则表面后,AUC为0.97(95%CI, 0.94-0.99)。基于体重指数,多普勒评分,子宫内膜厚度和GIS未增强TVS和不规则表面的子宫内膜子宫内膜交界处中断的子宫内膜癌(REC)评分系统在识别子宫内膜癌方面表现很好;在REC得分≥4时,检测子宫内膜癌的敏感性为91%,特异性为94%。在存储的视频剪辑中对主观参数进行分析时,观察者同意在82.3%的情况下(kappa,0.63(0.48-0.78))。结论我们依赖观察者的拟议评分系统在子宫内膜癌的预测中似乎表现良好,应在以后的研究中进行测试。

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