Evaluating Dynamic Contrast-enhanced MRI for Differentiating HER2-zero, HER2-low, and HER2-positive Breast Cancers in Patients Undergoing Neoadjuvant Chemotherapy

Overview

Journal Eur J Med Res

Publisher Biomed Central

Specialty General Medicine

Date 2025 Feb 26

PMID 40001120

Authors

Yangling Hu

Meizhi Li

Yalan Hu

Mengyi Wang

Yingyu Lin

Lijuan Mao

Chaoyang Wang

Yanhong Shui

Yutong Song

Huan Wang

Lin Ji

Xin Che

Nan Shao

Xiaoling Zhang

Affiliations

Soon will be listed here.

Abstract

Objectives: To quantitatively assess the differences in parameters of dynamic contrast-enhanced MRI (DCE-MRI) in HER2-zero, HER2-low, or HER2-positive tumors, and to build optimal model for early prediction of HER2-low breast cancer (BC).

Materials And Methods: Clinical and DCE-MRI data from 220 BC patients receiving neoadjuvant chemotherapy (NACT) were retrospectively analyzed. Quantitative and semi-quantitative DCE-MRI parameters were compared in the HER2-zero, HER2-low, or HER2-positive groups before and after early NACT. Empirical models were developed to predict HER2-low BC using logistic regression analysis and receiver operating characteristic (ROC) analysis.

Results: Patients of HER2-low BC have a lower pCR rate compared with HER2-zero and HER2-positive (17.9% vs. 10.4% vs. 29.5%, p < 0.001), predominantly in the HR (hormone receptor) negative group (22.2% vs. 7.7% vs. 40.5%, p < 0.001). Before NACT, HER2-low BC exhibited higher Kep, Ktrans, Washin, and lower TME intratumoral perfusion characteristics, and higher Kep and lower TME in peritumoral region compared to HER2-zero and HER2-positive BC patients. Notably, after early NACT, changes in intratumoral perfusion (Kep) and in peritumoral perfusion (Ktrans, Washin) were more pronounced in the HER2-low group compared to HER2-zero and HER2-positive group. The ROC curves (AUC) for the pre-NACT intratumoral, peritumoral, and combined perfusion models were 0.675(95% CI 0.600-0.750), 0.661(95% CI 0.585-0.738), 0.731(95% CI 0.660-0.802). The combined pre-and-post-NACT perfusion model further improved predictive performance accordingly, with AUCs of 0.764 (95% 0.637-0.865), 0.795 (95% CI 0.711-0.878), 0.850 (95% CI 0.774-0.926).

Conclusions: The study revealed perfusion heterogeneity between different HER2 statuses and identified the best imaging model as a non-invasive tool to predict HER2-low BC, which can help pre-treatment clinical decision-making.

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