中国临床医学影像杂志2026，Vol.37Issue(3)：173-177,5.DOI:10.12117/jccmi.2026.03.005
基于DBT瘤内、瘤周影像组学的列线图对乳腺BI-RADS 4类病变良恶性的鉴别诊断价值研究
A Study on the nomogram based on DBT intra-tumoral and peri-tumoral radiomics for benign and malignant differentiation of breast BI-RADS 4 lesions
摘要
Abstract
Objective:To investigate whether the nomogram model constructed based on intratumoral and peritumoral ra-diomic features of digital breast tomosynthesis(DBT)combined with clinical imaging features can distinguish benign from malig-nant breast BI-RADS category 4 lesions.Methods:A retrospective analysis was conducted on the DBT images of 190 female patients who underwent DBT at the Second Affiliated Hospital of Nanjing Medical University from August 2021 to December 2024.All patients were randomly assigned to a training group of 133 cases and a validation group of 57 cases in a 7:3 ratio.Delineate the intratumoral region of interest(ROI)using 3D-Slicer,and expand outward by 2 mm to obtain the peritumoral ROI.Radiomics features were extracted and analyzed using Python(Version 3.5).The t-test and least absolute shrinkage and selection operator(LASSO)method were used to screen the optimal features,and the intra-tumoral and peri-tumoral radiomics models were constructed.Then the radiomics signature's score(RadScore)was calculated.Logistic regression analysis was used to screen the independent risk factors and after that,a clinical model was constructed.The nomogram was constructed using RadScore and the independent risk factors.The differential diagnostic performance of the each model was evaluated using the area under the ROC curve(AUC),calibration and decision curves.Results:The AUC of intra-tumoral and intra-tumoral+peri-tumoral model was 0.808,0.856 in the training set and 0.702,0.830 in the validation set.Logistic regression analysis showed that irregular tumor morphology,enlarged lymph nodes and age were independent risk factors for benign and malignant differ-entiation of BI-RADS 4 lesions.The AUC values for the clinical model in the training and validation sets were 0.674 and 0.684,respectively.The AUC values of the nomogram model in the training set and validation set were 0.900 and 0.872,re-spectively,and its performance was superior to that of the single model(P<0.05).Conclusion:The nomogram model based on DBT intra-tumoral and peri-tumoral radiomics and clinical imaging features shows good performance in predicting the benign and malignant lesions of BI-RADS 4.关键词
乳腺肿瘤/放射摄影术Key words
Breast Neoplasms/Radiography分类
医药卫生引用本文复制引用
雍千叶,李海歌,马玉萍,王梅,郭浩东..基于DBT瘤内、瘤周影像组学的列线图对乳腺BI-RADS 4类病变良恶性的鉴别诊断价值研究[J].中国临床医学影像杂志,2026,37(3):173-177,5.基金项目
南京医科大学科技发展基金项目(NMUB20230032). （NMUB20230032）
