Evaluating dynamic contrast-enhanced MRI for differentiating HER2-zero, HER2-low, and HER2-positive breast cancers in patients undergoing neoadjuvant chemotherapy.

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.