摘要
Abstract
Objective To study the clinical value and imaging features of color Doppler ultrasound in the diagnosis of thyroid tumors.Methods A total of 80 patients with thyroid tumors diagnosed and treated in our hospital from March 2020 to March 2023 were selected as the research objects.All patients were examined by color Doppler ultrasound with pathological diagnosis as the standard(49 patients were benign tumors and 31 patients were malignant tumors).The detection rate,diagnostic efficiency(sensitivity,specificity,accuracy,positive predictive value and negative predictive value),consistency with pathological diagnosis results,resistance index of benign tumors,peak systolic and end diastolic blood flow velocity and imaging characteristics of color Doppler ultrasound were observed.Results Among the 80 cases,75 cases were detected by color Doppler ultrasound,and the diagnostic accuracy was 93.75％,including 29 cases of papilloma,2 cases of follicular tumor,41 cases of thyroid tumor and 8 cases of cyst.The sensitivity of color Doppler ultrasound in the diagnosis of thyroid tumors was 93.88％,the specificity was 93.55％,the positive predictive value was 95.83％,and the negative predictive value was 90.63％.The peak systolic velocity and resistance index of patients with malignant thyroid tumors were higher than those of benign thyroid tumors,and the end-diastolic blood flow velocity was higher than that of benign thyroid tumors(P＜0.05).The incidence of echo attenuation,unclear boundary,irregular shape,microcalcification and uneven echo in patients with malignant thyroid tumors was higher than that in patients with benign thyroid tumors(P＜0.05).Conclusion Color Doppler ultrasound has high clinical value in the diagnosis of thyroid tumors,and the peak systolic velocity,resistance index,end-diastolic blood flow velocity and imaging features are significant,which is conducive to the differential diagnosis of benign and malignant thyroid tumors.关键词
彩色多普勒超声/甲状腺肿瘤/影像特征Key words
Color Doppler ultrasound/Thyroid tumors/Imaging features分类
医药卫生
