Related Experiment Video
Updated: Jun 16, 2026
Tracking the Mammary Architectural Features and Detecting Breast Cancer with Magnetic Resonance Diffusion Tensor Imaging
Published on: December 15, 2014
Differentiation of HER2-Zero, -Low, and -Overexpressing Breast Cancer Using Amide Proton Transfer-Weighted Magnetic
Ting Zhan1, Yinping Leng1, XinYi Liu1
1Department of Radiology, The Second Affiliated Hospital, Jiangxi Medical College, Nanchang University, Nanchang 330006, China (T.Z., Y.L., X.L., J.D., L.G.); Jiangxi Provincial Key Laboratory of Intelligent Medical Imaging, Nanchang 330006, China (T.Z., Y.L., X.L., J.D., L.G.); Nanchang Key Laboratory of Medical-Engineering Integration and Clinical Translation, Nanchang 330006, China (T.Z., Y.L., X.L., J.D., L.G.).
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.
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.
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.
Conclusions:
MTRasym_3.5ppm is a promising biomarker for HER2 stratification, offering a non-invasive framework to optimize personalized therapy.
