Your browser doesn't support javascript.
loading
Logistic regression analysis of ultrasonography in diagnosis of malignant thyroid nodules / 中国介入影像与治疗学
Chinese Journal of Interventional Imaging and Therapy ; (12): 742-746, 2017.
Article in Chinese | WPRIM | ID: wpr-664511
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.

Full text: Available Index: WPRIM (Western Pacific) Type of study: Diagnostic study / Prognostic study Language: Chinese Journal: Chinese Journal of Interventional Imaging and Therapy Year: 2017 Type: Article

Similar

MEDLINE

...
LILACS

LIS

Full text: Available Index: WPRIM (Western Pacific) Type of study: Diagnostic study / Prognostic study Language: Chinese Journal: Chinese Journal of Interventional Imaging and Therapy Year: 2017 Type: Article