Logistic Regression Analysis of Gallbladder Lesions of≥1 cm in Diameter Diagnosed by Ultrasound
10.3969/j.issn.1005-5185.2013.06.013
- VernacularTitle:超声诊断直径≥1 cm胆囊病变性质的Logistic回归分析
- Author:
Xiaoran CHEN
;
Shaoshan TANG
;
Dongmei YU
;
Zhan LIU
- Publication Type:Journal Article
- Keywords:
Gallbladder neoplasms;
Ultrasonography,Doppler,color;
Diagnosis,differential;
Logistic models
- From:
Chinese Journal of Medical Imaging
2013;(6):447-450
- CountryChina
- Language:Chinese
-
Abstract:
Purpose To establish Logistic regression model of gallbladder lesions of≥1 cm in diameter diagnosed by ultrasound, and to filter benign and malignant sonographic features. Materials and Methods The sonographic features were retrospectively analyzed in 165 patients with gallbladde apophysis lesions of≥1 cm in diameter which confirmed by pathology, including the number of lesions, size, shape and basal width, gallstones, continuous gallbladder wall continuous, blood flow signals detected by color Doppler flow imaging. Logistic regression model with bipartition was established by multivariate Logistic regression analysis, and the efficiency of Logistic regression model was evaluated to predict benign or malignant of these lesions. Results Three characteristic variables, including lesion morphology, basal width and flow signals, were took into the Logistic regression model by binary Logistic regression analysis, which was the sensitive indicators can differentiate the benign or malignant gallbladder lesions. The accuracy, sensitivity and specificity of this model were 97.0%, 93.8%and 97.3%for predicting the benign or malignant gallbladder apophysis lesions≥1 cm in diameter, respectively. Area under ROC was 0.979. Conclusion Binary Logistic regression analysis can filter the sonographic features which can differentiate the benign or malignant gallbladder apophysis lesions≥1 cm in diameter, and lesion morphology, basal width and flow signals are of important differential diagnosis value of benign lesions or malignant lesions.
