Logistic regression analysis of ultrasonography in diagnosis of malignant thyroid nodules
10.13929/j.1672-8475.201709014
- VernacularTitle:超声征象Logistic回归分析诊断甲状腺恶性结节
- Author:
Hong TIAN
1
;
Rong XIAO
;
Xiaodan HU
;
Zhaohui YANG
;
Ling YU
;
Qing XU
;
Xiaoli WEN
Author Information
1. 西藏自治区人民政府驻成都办事处医院功能科
- Keywords:
Ultrasonography;
Thyroid nodule;
Malignant;
Logistic regression models
- From:
Chinese Journal of Interventional Imaging and Therapy
2017;14(12):742-746
- CountryChina
- Language:Chinese
-
Abstract:
Objective To investigate the value of conventional ultrasound and CEUS in diagnosis of thyroid nodules with Logistic regression models.Methods A total of 218 cases of thyroid nodules (74 cases of malignant,144 cases of benign nodules) confirmed by pathology were enrolled.The boundary,morphology,anteroposterior and transverse diameter ratio,microcalcification,internal echogenicity,blood distribution and enhanced pattern of nodules were observed and analyzed with univariate analysis.The Logistic regression model was established with parameters which were significantly different of those features,and the receiver operating characteristic curves (ROC) were constructed.Results Hypoechoic,irregular morphology,blurred boundary,anteroposterior and transverse diameter ratio≥ 1,microcalcifications,blood distribution (Ⅰ,Ⅱ),heterogeneous enhanced pattern and low enhanced were significantly prognostic factors (all P＜0.01).Irregular morphology,microcalcifications,heterogeneous enhanced and low enhanced were independent prognostic factors (all P＜0.05).The accuracy of Logistic regression model was 82.57％,and the area under ROC curve was 0.906.Conclusion The Logistic regression model of boundary,morphology,anteroposterior and transverse diameter ratio,microcalcifica tions,internal echogenicity,blood distribution and enhanced pattern can help to diagnose malignant thyroid nodules.
