国际医学放射学杂志2025，Vol.48Issue(3)：306-311,6.DOI:10.19300/j.2025.L21656
基于临床及MRI特征预测HER-2阳性型和低表达型乳腺癌的价值
Value of clinical and MRI features in predicting HER-2-positive and HER-2-low expression breast cancer
摘要
Abstract
Objective To evaluate the value of models based on clinical and MRI features in predicting HER-2-positive and HER-2-low expression breast cancers.Methods A retrospective analysis was conducted on 213 female patients(mean age 50.8±10.6 years)with surgically and pathologically confirmed mass-forming breast cancer.Based on postoperative pathological results,patients were categorized into HER-2-zero(65 cases),HER-2-low(79 cases),and HER-2-positive(69 cases)groups.Clinical and MRI characteristics were compared among the three HER-2 expression groups using one-way ANOVA and chi-square tests,including estrogen receptor(ER)status,progesterone receptor(PR)status,T stage,clinical stage,maximum lesion diameter,and apparent diffusion coefficient(ADC)values.Multivariate logistic regression was used to identify independent predictive factors for the HER-2-positive and HER-2-low expression subtypes,followed by predictive model construction.Receiver operating characteristic(ROC)analysis was used to assess model performance.Results Significant differences were observed among the HER-2-zero,HER-2-low,and HER-2-positive groups in ER status,PR status,T stage,clinical stage,maximum lesion diameter,and ADC values(all P<0.05).Multivariate analysis demonstrated that clinical stage and ADC value were independent predictors for both HER-2-positive and HER-2-low breast cancer(both P<0.05).The model constructed using clinical stage and ADC demonstrated high predictive efficacy for both HER-2 positive and HER-2-low expressing breast cancers,with areas under the curve(AUC)of 0.899 and 0.861,respectively.Conclusion A model integrating clinical stage and ADC values shows high efficacy for the noninvasive prediction of HER-2-positive and HER-2-low expression breast cancers.关键词
乳腺癌/人表皮生长因子受体-2/动态增强/磁共振成像/表观扩散系数/扩散加权成像Key words
Breast cancer/Human epidermal growth factor receptor 2/Dynamic contrast enhanced/Magnetic resonance imaging/Apparent diffusion coefficient/Diffusion weighted imaging分类
临床医学引用本文复制引用
李思恩,杨志企,林裕霖,邓君良,张志强,李小苑,程凤燕,陈小凤..基于临床及MRI特征预测HER-2阳性型和低表达型乳腺癌的价值[J].国际医学放射学杂志,2025,48(3):306-311,6.基金项目
梅州市社会发展科技计划项目(2024C0301077) （2024C0301077）
广东省医学科研基金项目(B2021280) （B2021280）
北京医学奖励基金会-睿影科研基金项目(YXJL-2024-0350-0242) （YXJL-2024-0350-0242）
