Value of multiparametric MRI texture analysis in predicting axillary lymph node metastasis of small-sized breast cancer
10.3969/j.issn.1673-9701.2024.23.005
- VernacularTitle:多参数MRI纹理分析预测小病灶乳腺癌腋窝淋巴结转移
- Author:
Xiaxia HE
1
;
Chao CHEN
;
Xiaoping YANG
;
Guoyu WANG
Author Information
1. 浙江省台州市中心医院(台州学院附属医院)放射科,浙江台州 3180001
- Keywords:
Multiparametric magnetic resonance imaging(MRI);
Axillary lymph nodes;
Invasive ductal carcinoma;
Texture analysis
- From:
China Modern Doctor
2024;62(23):21-25
- CountryChina
- Language:Chinese
-
Abstract:
Objective To investigate the value of multiparametric magnetic resonance imaging(MRI)texture analysis based on T2 weighted image(T2WI),diffusion weighted imaging(DWI),and dynamic contrast enhanced-MRI(DCE-MRI)in predicting the axillary lymph node status of small-sized invasive ductal carcinoma(IDC)of the breast.Methods A retrospective analysis was conducted on the medical records of 139 patients with newly diagnosed IDC,who were treated at Taizhou Central Hospital from January 2018 to June 2023.Based on the postoperative pathological results,the patients were divided into two groups:85 cases without axillary lymph node metastasis and 54 cases with axillary lymph node metastasis.All patients underwent preoperative MRI examination,including sequences such as T2WI,DWI,and DCE-MRI.After delineating the region of interest(ROI)on the slice with the largest tumor diameter in each sequence,texture analysis was performed using Firevoxel software,which yielded five major parameters,including mean,standard deviation,skewness,kurtosis,and entropy.Univariate analysis was employed to evaluate the effectiveness of each parameter in distinguishing the axillary lymph node status.Variables that showed significant results in the univariate analysis were then included in binary Logistic regression analysis to explore the relationship between these parameters and lymph node metastasis status.Receiver operating characteristic(ROC)curves were plotted,and the area under the curve(AUC)was calculated.Results Significant differences were observed between the two groups in the entropy and mean values of the ROI delineated on the DCE-MRI sequence,as well as the skewness of the T2WI(P<0.001).Among these texture parameters,the entropy of the DCE-MRI sequence showed the highest AUC value of 0.719 in the univariate analysis.Multivariate analysis of the selected parameters yielded an optimal diagnostic model,with an AUC of 0.769 in differentiating lymph node metastasis from non-metastasis.Conclusion Texture analysis of small-sized breast cancer based on multiparametric MRI can effectively predict the preoperative axillary lymph node status of breast cancer.
