The Clinical Study of Intratumoral and Peritumoral Radiomics Based on DCE-MRI for HER-2 Positive and Low Expression Prediction in Breast Cancer

作者：Yiyan Shang, Yunxia Wang, Yaxin Guo, Shunian Li, Jun Liao, Menglu Hai, Meiyun Wang, Hongna Tan · 发表于：Breast Cancer Targets and Therapy · 年份：2024 · DOI：10.2147/bctt.s497770 · 被引用次数：5 · 研究领域：Radiomics and Machine Learning in Medical Imaging、MRI in cancer diagnosis、HER2/EGFR in Cancer Research

Background: Core biopsy sampling may not fully capture tumor heterogeneity. Radiomics provides a non-invasive method to assess tumor characteristics, including both the core and surrounding tissue, with the potential to improve the accuracy of HER-2 status prediction. Objective: To explore the clinical value of intratumoral and peritumoral radiomics features from dynamic contrast enhanced magnetic resonance imaging (DCE-MRI) for preoperative prediction of human epidermal growth factor receptor-2 (HER-2) expression status in breast cancer. Methods: Two tasks were designed, including Task1-distinguished HER-2 positive and HER-2 negative from 382 breast cancer patients and Task2-distinguished HER-2 low and HER-2 zero expression from 249 patients with HER-2 negative. Three radiomics models (intratumoral, peritumoral 5 mm, intratumoral+peritumoral 5 mm) were constructed based on decision tree, and clinical combined radiomics models were constructed with logistic regression based on clinicopathological features and radscore. The area under the curve (AUC), sensitivity, specificity, accuracy and decision curve analysis (DCA) were used to evaluate the predictive performance of models. Results: Estrogen receptor (ER), progesterone receptor (PR) and Ki67 showed statistically significant in the different groups of HER-2 expression. Additionally, magnetic resonance imaging-reported axillary lymph nodes (MRI-reported ALN) in the positive and negative groups and histological grade in the l...