一种用于识别子宫内膜癌的超声算法。

An ultrasound algorithm for identification of endometrial cancer.

作者信息

Dueholm M, Møller C, Rydbjerg S, Hansen E S, Ørtoft G

机构信息

Department of Gynecology and Obstetrics, Aarhus University Hospital, Aarhus N, Denmark.

出版信息

Ultrasound Obstet Gynecol. 2014 May;43(5):557-68. doi: 10.1002/uog.13205.

DOI:10.1002/uog.13205

PMID:24009152

Abstract

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.

摘要

目的

提出一种评分系统，利用不同的超声图像特征（包括灰阶下有无凝胶注入增强的情况）、经阴道多普勒超声（TVS）来预测子宫内膜癌，并评估观察者间和观察者内对这些特征评估的变异性。

方法

对174例连续的绝经后子宫内膜厚度≥5mm的女性进行前瞻性的未增强TVS、多普勒检查和凝胶注入超声检查（GIS）。所有女性的参考标准是宫腔镜检查或子宫切除术及恶性病变的病理评估。评估了各种提示子宫内膜恶性病变的超声图像特征的存在情况以及观察者间和观察者内对其评估的变异性。采用多因素逻辑回归分析将图像和临床参数与子宫内膜癌的存在情况相关联。

结果

一个简单的多普勒血流评分（仅考虑血管的存在，而不考虑单一/双优势血管、多条血管、大血管、彩色溢出或密集血管的存在）在预测子宫内膜癌时，受试者操作特征曲线（AUC）下面积为0.83。包括子宫内膜厚度、多普勒评分和未增强TVS上子宫内膜肌层交界中断的模型预测子宫内膜癌的AUC为0.95（95%CI，0.92 - 0.99），加上GIS上的不规则表面后，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、未增强TVS上子宫内膜肌层交界中断以及GIS上不规则表面的子宫内膜癌风险（REC）评分系统在识别子宫内膜癌方面表现良好；REC评分≥4时，检测子宫内膜癌的敏感性为91%，特异性为94%。在分析存储的视频片段中的主观参数时，观察者在82.3%的病例中意见一致（kappa值，0.63（0.48 - 0.78））。