Ultrasonographic diagnostic characteristics and prediction model of benign, borderline and malignant ovarian epithelial tumors
10.3760/cma.j.cn131148-20191111-00694
- VernacularTitle:卵巢上皮性肿瘤超声鉴别特征及预测模型
- Author:
Yaduan GAN
1
;
Guorong LYU
;
Shuping YANG
;
Xiaoling SHEN
;
Xinying ZHENG
Author Information
1. 福建医科大学附属漳州市医院超声医学科 363000
- From:
Chinese Journal of Ultrasonography
2020;29(6):534-539
- CountryChina
- Language:Chinese
-
Abstract:
Objective:To explore ultrasonographic diagnostic characteristics of ovarian epithelial tumors and establish prediction models.Methods:The ultrasonographic images of 427 cases from multicenter with ovarian epithelial tumors confirmed by pathology from January 2015 to July 2019 were retrospectively analyzed according to the International Ovarian Tumor Analysis (IOTA). Ultrasonographic signs with distinguishing significance were obtained through univariate analysis and included into multivariate Logistic regression analysis to obtain important ultrasonagraphic indicators for distinguishing borderline, benign and malignant ovarian tumors, and to establish prediction models.Results:The microcystic pattern of papillary projections and solid components was the diagnostic characteristic between borderline and benign, malignant ovarian epithelial tumors( OR value 10.97 and 19.22, respectively). Irregular morphology, septa thickness, solid lesions, rich blood supply and ascites were diagnostic characteristics between benign and malignant tumors, with the irregular morphology having the highest value. Irregular morphology, large papillary, septa thickness and rich blood supply could be used to identify borderline and malignant tumors. At the same time, irregular morphology was the valuable sign to distinguish borderline and benign tumors. In this study, the total coincidence rate of the proposed model was 72.4%, among which the predicted coincidence rate of the borderline model was 57.2%, 78.6% for benign, and 80.7% for malignant. Conclusions:The microcystic pattern of papillary projections and solid components are the specific sonographic characteristics of borderline ovarian tumors. Irregularity, solid lesions, rich blood supply and ascites have important value in differentiating ovarian epithelial tumors. The prediction models of benign, malignant and borderline ovarian tumors in this study have higher diagnostic efficacy.
