甲状腺微小癌的超声影像学特征及其诊断价值分析
Imaging features and clinicopathological correlation of thyroid microcarcinoma
廖明珍 1覃文聪 1罗家林 1黄虹儒 1银园精1
作者信息
- 1. 河池市第一人民医院超声诊断科 广西 河池 546300
- 折叠
摘要
目的:探讨甲状腺微小癌的超声影像学特征及其对甲状腺微小癌的诊断价值.方法:收集 2020 年 1 月—2023 年 9 月在河池市第一人民医院接受超声检查的 180 例最大长径≤10mm的甲状腺结节患者作为研究对象,以临床病理结果为金标准分析良性甲状腺结节与甲状腺微小癌的超声影像学特征,并采用Logistic回归分析甲状腺微小癌的超声影像学特征、ROC曲线分析超声影像学相关指标对甲状腺微小癌的诊断价值.结果:180例甲状腺结节患者共检出结节234个,且病理检查结果显示良性结节33个、恶性结节(甲状腺微小癌)201 个.超声检查结果显示,甲状腺微小癌边界不清晰、形态不规则、呈低回声、质地不均匀、有微钙化、纵横比＞1 的比例明显高于良性甲状腺结节(P＜0.05);Logistic回归分析结果显示,边界不清晰、形态不规则、呈低回声、质地不均匀、有微钙化、纵横比＞1是甲状腺结节为微小癌的独立危险因素(P＜0.05);受试者工作特征(ROC)曲线分析结果显示,超声影像学中边界、形态、回声、质地、钙化、纵横比诊断恶性甲状腺结节为微小癌的AUC分别为0.704、0.619、0.712、0.702、0.722、0.716(P＜0.05).结论:甲状腺微小癌的超声影像学特征对其临床诊断具有较高的应用价值.
Abstract
Objective To investigate the correlation between imaging features and clinicopathology of thyroid microcarcinoma.Methods Collect data from January 2020 to September 2023 in Hechi City 180 patients with thyroid nodules with a maximum length diameter≤10 mm who underwent ultrasound examination at the First People's Hospital were selected as the study subjects,and the clinical and pathological results were used as the gold standard to analyze benign thyroid nodules.The ultrasound imaging characteristics of thyroid microcarcinoma were analyzed using logistic regression and ROC curve analysis.The ultrasound imaging related indicators of thyroid microcarcinoma were compared with those of thyroid microcarcinoma.The diagnostic value of squamous cell carcinoma.Results The boundary,shape,echo,texture,calcification and aspect ratio of benign and malignant thyroid nodules were significantly different(P＜0.05).Binary Logistic regression analysis showed that the above imaging features were risk factors for thyroid microcarcinoma(P＜0.05).ROC curve showed that imaging features had certain diagnostic value for thyroid microcarcinoma(P＜0.05).Conclusion There is a correlation between imaging features and clinicopathology of thyroid microcarcinoma.
关键词
甲状腺微小癌/影像学特征/临床病理/相关性分析Key words
Thyroid microcarcinoma/Imaging features/Clinical pathology/Correlation analysis引用本文复制引用
出版年
2024
NETL
NSTL
万方数据