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

## TL;DR

Time-dependent diffusion MRI can help distinguish breast cancer subtypes and HER2 classifications noninvasively, offering potential for personalized treatment.

## Contribution

Td-dMRI is shown to effectively differentiate molecular subtypes and HER2 classifications, particularly the newly defined HER2-low category.

## Key findings

- ADC30ms effectively distinguishes HER2-zero from HER2-low tumors with high accuracy (AUC = 0.898).
- Cellularity and cell diameter moderately differentiate HER2-low from HER2-positive tumors (AUC = 0.770).
- Td-dMRI parameters vary significantly across molecular subtypes, such as higher ADC50Hz in Luminal A compared to Luminal B.

## Abstract

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.

To evaluate the potential of time-dependent diffusion MRI (Td-dMRI) in differentiating breast cancer molecular subtypes and to investigate its correlation with immunohistochemical biomarkers, particularly the newly established three-tier HER2 classification.

In this retrospective study, female patients with untreated invasive ductal carcinoma underwent 3T breast MRI including Td-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 (Dex, Din), cell diameter, intracellular volume fraction (fin), and intracellular water residence time (τin)—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 Td-dMRI metrics were compared across subtypes and correlated with ER, PR, HER2, and Ki-67 status using ANOVA, Kruskal–Wallis, and ROC curve analysis.

This study included 71 female participants (mean age, 51.3 ± 10.2 years). Multiple Td-dMRI parameters varied significantly across molecular and HER2 subtypes. ADC50Hz 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 Din, with lower cellularity than positive counterparts. Din effectively distinguished TN from non-TN cancers (AUC = 0.710). For HER2 stratification, ADC30ms 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 Td-dMRI differences were observed for Ki-67.

ADC30ms 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 Td-dMRI as a complementary imaging biomarker for subtype characterization, although findings were limited by small subgroup sizes and the single-center design.