Time-dependent diffusion MRI for noninvasive molecular subtype differentiation and biological correlation in breast cancer: emphasizing the emerging three-tier HER2 classification

利用时间依赖性扩散磁共振成像技术进行乳腺癌非侵入性分子亚型鉴别和生物学相关性分析:重点关注新兴的三级HER2分类

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Abstract

BACKGROUND: Breast cancer is a heterogeneous disease, and accurate subtype characterization is essential for guiding personalized treatment. In particular, HER2-low tumors have recently emerged as a distinct clinical entity with potential responsiveness to novel HER2-targeted therapies. However, reliable noninvasive imaging methods to identify these subgroups remain lacking. PURPOSE: To evaluate the potential of time-dependent diffusion MRI (T(d)-dMRI) in differentiating breast cancer molecular subtypes and to investigate its correlation with immunohistochemical biomarkers, particularly the newly established three-tier HER2 classification. MATERIALS AND METHODS: In this retrospective study, female patients with untreated invasive ductal carcinoma underwent 3T breast MRI including T(d)-dMRI between June 2023 and October 2024. A custom protocol combining oscillating gradient spin-echo (OGSE) and pulsed gradient spin-echo (PGSE) sequences enabled diffusion sampling at multiple diffusion times and frequencies. Microstructural parameters-cellularity, extracellular and intracellular diffusivity (D(ex), D(in)), cell diameter, intracellular volume fraction (f(in)), and intracellular water residence time (τ(in))-were estimated using a Bayesian model based on a joint multicompartmental framework. Molecular subtypes (Luminal A/B, HER2-enriched, triple-negative [TN]) and HER2 expression levels (HER2-zero, HER2-low, HER2-positive) were determined via IHC and fluorescence in situ hybridization (FISH). Quantitative T(d)-dMRI metrics were compared across subtypes and correlated with ER, PR, HER2, and Ki-67 status using ANOVA, Kruskal-Wallis, and ROC curve analysis. RESULTS: This study included 71 female participants (mean age, 51.3 ± 10.2 years). Multiple T(d)-dMRI parameters varied significantly across molecular and HER2 subtypes. ADC(50Hz) was significantly higher in Luminal A compared to Luminal B (P = 0.003). HER2-enriched tumors showed higher ADC values and cell diameters but lower cellularity compared to Luminal B (P< 0.05). ER- and PR- tumors had higher ADCs, cell diameters, and D(in), with lower cellularity than positive counterparts. D(in) effectively distinguished TN from non-TN cancers (AUC = 0.710). For HER2 stratification, ADC(30ms) distinguished HER2-zero from HER2-low tumors with high accuracy (AUC = 0.898), and cell diameter and cellularity were most effective for differentiating HER2-low from HER2-positive tumors (AUC = 0.770). No significant T(d)-dMRI differences were observed for Ki-67. CONCLUSION: ADC(30ms) most effectively distinguished HER2-zero from HER2-low tumors, while microstructural parameters such as cellularity and cell diameter moderately differentiated HER2-low from HER2-positive cancers. These results support the potential of T(d)-dMRI as a complementary imaging biomarker for subtype characterization, although findings were limited by small subgroup sizes and the single-center design.

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