{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,9]],"date-time":"2026-06-09T13:09:15Z","timestamp":1781010555908,"version":"3.54.1"},"reference-count":46,"publisher":"Frontiers Media SA","license":[{"start":{"date-parts":[[2026,1,14]],"date-time":"2026-01-14T00:00:00Z","timestamp":1768348800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["frontiersin.org"],"crossmark-restriction":true},"short-container-title":["Front. Oncol."],"abstract":"\n Background<\/jats:title>\n 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.<\/jats:p>\n <\/jats:sec>\n \n Purpose<\/jats:title>\n \n To evaluate the potential of time-dependent diffusion MRI (T\n d<\/jats:sub>\n -dMRI) in differentiating breast cancer molecular subtypes and to investigate its correlation with immunohistochemical biomarkers, particularly the newly established three-tier HER2 classification.\n <\/jats:p>\n <\/jats:sec>\n \n Materials and methods<\/jats:title>\n \n In this retrospective study, female patients with untreated invasive ductal carcinoma underwent 3T breast MRI including T\n d<\/jats:sub>\n -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\u2014cellularity, extracellular and intracellular diffusivity (D\n ex<\/jats:sub>\n , D\n in<\/jats:sub>\n ), cell diameter, intracellular volume fraction (f\n in<\/jats:sub>\n ), and intracellular water residence time (\u03c4\n in<\/jats:sub>\n )\u2014were 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\n in situ<\/jats:italic>\n hybridization (FISH). Quantitative T\n d<\/jats:sub>\n -dMRI metrics were compared across subtypes and correlated with ER, PR, HER2, and Ki-67 status using ANOVA, Kruskal\u2013Wallis, and ROC curve analysis.\n <\/jats:p>\n <\/jats:sec>\n \n Results<\/jats:title>\n \n This study included 71 female participants (mean age, 51.3 \u00b1 10.2 years). Multiple T\n d<\/jats:sub>\n -dMRI parameters varied significantly across molecular and HER2 subtypes. ADC\n 50Hz<\/jats:sub>\n 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&lt; 0.05). ER\u2212 and PR\u2212 tumors had higher ADCs, cell diameters, and D\n in<\/jats:sub>\n , with lower cellularity than positive counterparts. D\n in<\/jats:sub>\n effectively distinguished TN from non-TN cancers (AUC = 0.710). For HER2 stratification, ADC\n 30ms<\/jats:sub>\n 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\n d<\/jats:sub>\n -dMRI differences were observed for Ki-67.\n <\/jats:p>\n <\/jats:sec>\n \n Conclusion<\/jats:title>\n \n ADC\n 30ms<\/jats:sub>\n 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\n d<\/jats:sub>\n -dMRI as a complementary imaging biomarker for subtype characterization, although findings were limited by small subgroup sizes and the single-center design.\n <\/jats:p>\n <\/jats:sec>","DOI":"10.3389\/fonc.2025.1739008","type":"journal-article","created":{"date-parts":[[2026,1,14]],"date-time":"2026-01-14T05:15:59Z","timestamp":1768367759000},"update-policy":"https:\/\/doi.org\/10.3389\/crossmark-policy","source":"Crossref","is-referenced-by-count":0,"title":["Time-dependent diffusion MRI for noninvasive molecular subtype differentiation and biological correlation in breast cancer: emphasizing the emerging three-tier HER2 classification"],"prefix":"10.3389","volume":"15","author":[{"given":"Mingzhe","family":"Xu","sequence":"first","affiliation":[{"name":"The Department of Radiology, The Affiliated Cancer Hospital of Zhengzhou University & Henan Cancer Hospital","place":["Zhengzhou, 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