Differentiation of HER2-Zero, -Low, and -Overexpressing Breast Cancer Using Amide Proton Transfer-Weighted Magnetic Resonance Imaging: A Single-center Preliminary Study

Abstract

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  Breast cancers exhibiting distinct HER2 expression levels demonstrate unique clinical and MRI morphological features, with significant differences also observed in quantitative parameters derived from DWI and APTWI.
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  MTRasym_3.5ppm demonstrates exceptional diagnostic performance for HER2 subtype classification in invasive breast cancer, serving as a key component within an imaging-derived framework to refine HER2 stratification and optimize personalized treatment strategies.
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  This comprehensive model, combining MRI qualitative and quantitative features, enables reliable tripartite HER2 stratification, providing a non-invasive, non-contrast alternative for patients with uncertain IHC/FISH results or contraindications to contrast-enhanced MRI, thus reducing the need for repeated biopsies.

Rationale and Objectives

To assess amide proton transfer-weighted imaging (APTWI) for identifying HER2 expression in breast cancer (BC) and to evaluate multiparametric model performance.

To assess amide proton transfer-weighted imaging (APTWI) for identifying HER2 expression in breast cancer (BC) and to evaluate multiparametric model performance.

Materials and Methods

This study finally included 173 BC patients who underwent MRI between July 2023 and December 2024 and received pathological examination. All participants were evaluated with diffusion weighted imaging (DWI) and APTWI sequences. Group comparisons of clinical, MRI qualitative, and quantitative features, including apparent diffusion coefficient (ADC) and magnetization transfer ratio asymmetry (MTRasym) at 3.5 ppm, were conducted using one-way ANOVA, the Kruskal–Wallis test, or the χ² test as appropriate. Multivariate logistic regression identified independent predictors of HER2 status, with receiver operating characteristic analysis assessing models' performance for subclass discrimination.

This study finally included 173 BC patients who underwent MRI between July 2023 and December 2024 and received pathological examination. All participants were evaluated with diffusion weighted imaging (DWI) and APTWI sequences. Group comparisons of clinical, MRI qualitative, and quantitative features, including apparent diffusion coefficient (ADC) and magnetization transfer ratio asymmetry (MTRasym) at 3.5 ppm, were conducted using one-way ANOVA, the Kruskal–Wallis test, or the χ² test as appropriate. Multivariate logistic regression identified independent predictors of HER2 status, with receiver operating characteristic analysis assessing models' performance for subclass discrimination.

Results

Clinically, estrogen receptor and progesterone receptor status, histological grade, Ki-67 index, and axillary lymph node differed significantly across HER2 subtypes (all P<0.05). In MRI analyses, morphological features, including margin and blood supply condition, varied significantly among subtypes(all P = 0.01). Quantitatively, both ADC and MTRasym_3.5ppm values were significantly higher in HER2-low and HER2-overexpressing groups than in HER2-zero (all p<0.001). MTRasym_3.5ppm was further identified as an independent predictor for stratifying HER2 subtypes. The combined model integrating MRI qualitative and quantitative features demonstrated optimal performance, with AUCs of 0.811 and 0.911 for distinguishing HER2-zero from HER2-low and HER2-overexpressing BCs, respectively. MTRasym_3.5ppm alone achieved the highest accuracy (AUC = 0.739) in differentiating HER2-low from HER2-overexpressing groups.

Clinically, estrogen receptor and progesterone receptor status, histological grade, Ki-67 index, and axillary lymph node differed significantly across HER2 subtypes (all P<0.05). In MRI analyses, morphological features, including margin and blood supply condition, varied significantly among subtypes(all P = 0.01). Quantitatively, both ADC and MTRasym_3.5ppm values were significantly higher in HER2-low and HER2-overexpressing groups than in HER2-zero (all p<0.001). MTRasym_3.5ppm was further identified as an independent predictor for stratifying HER2 subtypes. The combined model integrating MRI qualitative and quantitative features demonstrated optimal performance, with AUCs of 0.811 and 0.911 for distinguishing HER2-zero from HER2-low and HER2-overexpressing BCs, respectively. MTRasym_3.5ppm alone achieved the highest accuracy (AUC = 0.739) in differentiating HER2-low from HER2-overexpressing groups.

Conclusions

MTRasym_3.5ppm is a promising biomarker for HER2 stratification, offering a non-invasive framework to optimize personalized therapy.

MTRasym_3.5ppm is a promising biomarker for HER2 stratification, offering a non-invasive framework to optimize personalized therapy.