Wang Xiali, Yang Shuping, Lv Guorong, Liao Jianmei, Wu Shufen, Zhang Weina
Department of Clinical Medicine, Quanzhou Medical College, Quanzhou 362000, China.
Department of Ultrasound, Zhangzhou Affiliated Hospital of Fujian Medical University, Zhangzhou 363000, China.
Rev Assoc Med Bras (1992). 2019 Aug 5;65(7):959-964. doi: 10.1590/1806-9282.65.7.959.
The purpose of this study is to evaluate the efficacy of the combination of gynecologic imaging reporting and data system (GI-RADS) ultrasonographic stratification and three-dimensional contrast-enhanced ultrasonography (3D-CEUS) in order to distinguish malignant from benign ovarian masses.
In this study, 102 patients with ovarian masses were examined by both two-dimensional ultrasound(2D-US) and 3D-CEUS. Sonographic features of ovarian masses obtained from 3D-CEUS were analyzed and compared with 2D-US. All patients with ovarian masses were confirmed by operational pathology or long-term follow-up results.
(1)The Chi-square test and multiple Logistic regression analysis confirmed that there were only eight independent predictors of malignant masses, including thick septa (≥3mm), thick papillary projections(≥7mm), solid areas, presence of ascites, central vascularization, contrast enhancement, distribution of contrast agent, and vascular characteristics of the solid part and their odds ratios which were 5.52, 5.39, 4.94, 4.34, 5.92, 7.44, 6.09, and 7.67, respectively (P<0.05). (2)These eight signs were used to combine the GI-RADS with 3D-CEUS scoring system in which the corresponding value of the area under the curve (AUC) was 0.969, which was superior to using GI-RADS lonely (Z-value=1.64, P<0.025). Using 4 points as the cut-off, the scoring system showed the performance was clearly better than using GI-RADS alone (P<0.05). (3) The Kappa value was 0.872 for two different clinicians with equal experience.
The combination of GI-RADS and 3D-CEUS scoring system would be a more effective method to distinguish malignant from benign ovarian masses.
本研究旨在评估妇科影像报告和数据系统（GI-RADS）超声分层与三维对比增强超声检查（3D-CEUS）相结合，以区分卵巢良恶性肿块的疗效。
本研究中，102例卵巢肿块患者接受了二维超声（2D-US）和3D-CEUS检查。分析从3D-CEUS获得的卵巢肿块的超声特征，并与2D-US进行比较。所有卵巢肿块患者均经手术病理或长期随访结果证实。
（1）卡方检验和多元逻辑回归分析证实，恶性肿块仅有八个独立预测因素，包括厚分隔（≥3mm）、厚乳头样突起（≥7mm）、实性区域、腹水、中央血管化、对比增强、造影剂分布以及实性部分的血管特征，其比值比分别为5.52、5.39、4.94、4.34、5.92、7.44、6.09和7.67（P<0.05）。（2）将这八个征象用于GI-RADS与3D-CEUS评分系统相结合，其中曲线下面积（AUC）的相应值为0.969，优于单独使用GI-RADS（Z值=1.64，P<0.025）。以4分为临界值，该评分系统的性能明显优于单独使用GI-RADS（P<0.05）。（3）两名经验相当的不同临床医生的Kappa值为0.872。
GI-RADS与3D-CEUS评分系统相结合是区分卵巢良恶性肿块的更有效方法。
