Diagnostic value of intratumoral and peritumoral ultrasound radiomics for small breast cancer
10.12354/j.issn.1000-8179.2025.20250294
- VernacularTitle:瘤周超声影像组学对小乳腺癌的诊断价值
- Author:
Si XIAOXIA
1
;
Zhao QING
;
Wang YINGYING
;
Zhou LIANG
;
Xu LEI
;
Zhang LI
;
Jing JIANGXIN
Author Information
1. 新疆医科大学第七附属医院超声诊断科(乌鲁木齐市 832000)
- Publication Type:Journal Article
- Keywords:
ultrasound radiomics;
tumor microenvironment;
small breast cancer;
Logistic regression model
- From:
Chinese Journal of Clinical Oncology
2025;52(12):603-609
- CountryChina
- Language:Chinese
-
Abstract:
Objective:To explore the diagnostic value of intratumoral area(ITA)and peritumoral area(PTA)ultrasound image-based bioin-formatics models for small breast cancer.Methods:We retrospectively analyzed data of 305 breast lesions from 292 patients with small breast nodules(diameter≤2 cm)who were treated at People's Hospital of Xinjiang Uygur Autonomous Region between January 2021 and January 2025.The lesions were randomly assigned into the training(214 lesions)and validation sets(91 lesions)in a 7:3 ratio.Radiomics fea-tures were extracted from the intertumoral area(ITA)and peritumoral area(PTA)regions at 2,4,6,and 8 mm,followed by feature selection and dimensionality reduction.A Logistic regression(LR)algorithm was used to construct a model.The performance of the models were eval-uated via receiver operating characteristic(ROC)curve analysis,Hosmer-Lemeshow test,and decision curve analysis(DCA).Results:In the training set,the areas under the ROC curves(AUC)for the ITA,2 mm PTA,and 2 mm fusion models were 0.869,0.897,and 0.909,respect-ively.In the test set,these respective AUC values were 0.813,0.825,and 0.840.For breast lesions≤2 cm,<1 cm,and 1-2 cm,the overall ac-curacies of the 2 mm fusion model were 81.0%,82.7%,and 80.1%,respectively,whereas the respective overall accuracies of BI-RADS were 76.4%,81.7%,and 73.6%.Conclusions:ITA and PTA ultrasound imaging-based radiomics models had a high diagnostic value for small breast cancers.The fusion model can effectively improve predictive performance,outperforming the BI-RADS classification in diagnosing small breast lesions of different diameters.Thus,these models have the potential to serve as an auxiliary diagnostic tool in clinical practice.
