MRI descriptors and ADC value in prediction of benign and malignant breast lesions of breast imaging reporting and data system category 4
10.13929/j.1003-3289.201810170
- Author:
Xiaoping YANG
1
Author Information
1. Department of Radiology, the First Affiliated Hospital of China Medical University
- Publication Type:Journal Article
- Keywords:
Apparent diffusion coefficient;
Breast neoplasms;
Magnetic resonance imaging
- From:
Chinese Journal of Medical Imaging Technology
2019;35(4):493-497
- CountryChina
- Language:Chinese
-
Abstract:
Objective To investigate the performance of MRI characteristics and ADC value in prediction of benign and malignant breast imaging reporting and data system (BI-RADS) category 4 lesions, and to establish Logistic regression predictive models. Methods Totally 79 patients with 82 BI-RADS 4 breast lesions confirmed with pathological results were enrolled. Univariate binary Logistic regression analysis and two-sample t-test were performed to analyze the difference of MRI characteristics and ADC values between benign and malignant breast lesions. The multivariate Logistic predictive model was established, and the ROC curve was drawn to evaluate the efficacy in prediction of benign and malignant lesions of BI-RADS 4. Results In mass lesions, the Logistic regression model was established based on margin, internal enhancement and ADC value (all P<0.05, Cox & Snell R2=0.62), with the AUC of ROC curve of 0.981, the sensitivity of 87.80% and the specificity of 100%. There was no statistically significant index in Logistic regression prediction model in non-mass lesions (all P>0.1). Conclusion Some MRI descriptors (margin and internal enhancement) and ADC value have a good predictive performance for benign and malignant mass lesions of BI-RADS 4. The established Logistic regression predictive model can effectively differentiate the character of BI-RADS 4 mass lesions and has potential clinical value.
