阴道彩色多普勒超声血流显像对子宫肌瘤检查的图像特征及诊断效能分析

Image Characteristics and Diagnostic Efficacy Analysis of Transvaginal Color Doppler Ultrasound Blood Flow Imaging in Uterine Fibroids

目的:探讨阴道彩色多普勒超声血流显像(CDFI)对子宫肌瘤的诊断效能及其图像特征.方法:选取 2020年1 月至 2022 年 12 月本院收治的 53 例子宫肌瘤患者为研究对象,纳入观察组.选取同期本院收治的 51 例子宫肉瘤患者作为对照,纳入对照组.比较两组经阴道CDFI检查的图像特征、瘤体内部血流信号,CDFI检查对两组患者的诊断效能.结果:观察组CDFI图像呈低回声、瘤体边界清楚、肌瘤内部实性患者,瘤体内部无血流信号、少量血流信号患者占比均大于对照组;瘤体边界欠清楚、肌瘤内部囊性患者、瘤体内部血流信号丰富患者占比,均小于对照组,差异均有统计学意义(P<0.05).阴道CDFI检查诊断子宫肌瘤和子宫肉瘤的特异度、灵敏度、准确率、阳性预测值、阴性预测值分别为 98.03%、96.22%、97.11%、98.07%、96.15%.结论:采取阴道CDFI检查对子宫肌瘤诊断具有较高诊断效能,可清楚显示子宫肌瘤患者图像特征.

Objective:To explore the diagnostic efficacy and image characteristics of transvaginal color Doppler ultrasound blood flow imaging in uterine fibroids.Method:Fifty-three patients with uterine fibroids admitted to our hospital from January 2020 to December 2022 were selected as the observation group,and 51 patients with uterine sarcoma admitted to our hospital during the same period were selected as the control group.The image features and internal blood flow signals of the two groups were compared,and the efficacy of transvaginal color Doppler ultrasonography on the two groups was calculated.Results:The images in the observation group were hypoechoic,the tumor boundaries were clear,the patients with solid fibroids,no blood flow signal in the tumor,and the patients with few blood flow signal were more than those in the control group.The proportion of patients with poor tumor boundary,cystic fibroids and rich blood flow signal in tumor was lower than that in control group,and the differences were statistically significant(P<0.05).The specificity,sensitivity,accuracy,negative predictive value,and positive predictive value of transvaginal color Doppler ultrasound blood flow imaging in distinguishing uterine fibroids and uterine sarcomas were 98.03%,96.22%,97.11%,96.15%and 98.07%,respectively.Conclusion:Transvaginal color Doppler ultrasound blood flow imaging has a high diagnostic efficiency in the diagnosis of uterine fibroids,and can clearly display the image features of the disease.