Longitudinal DCE MRI Vascular Textures: Radiologic and Biologic Insights for pCR Prediction in HER2-Negative Breast Cancer.

Purpose To develop a pathologic complete response (pCR) prediction model for human epidermal growth factor receptor 2 (HER2)-negative breast cancer by analyzing longitudinal changes in dynamic contrast-enhanced MRI (DCE MRI)-derived vascular textures. Materials and Methods Retrospective baseline and midtreatment DCE MRI data from I-SPY2 (May 2010-November 2016) and ACRIN 6698 (August 2012-January 2015) trials were used for development and internal tests (ClinicalTrials.gov no. NCT01042379). An independent hospital cohort (December 2023-December 2024) served as the external test. Image Biomarker Standardization Initiative-standardized vascular textures were extracted from the functional tumor volume (FTV). The DCE MRI vascularization-based response tracking (DCE-VASC-TRACK) model incorporated repeatable vascular texture changes associated with pCR at surgery, alongside hormone receptor status, age, baseline FTV, and midtreatment FTV change. Performance was evaluated using the area under the receiver operating curve (AUC). Biologic associations were explored using gene set enrichment analysis. Results The study included 417 (development), 162 (internal test), and 167 (external test) women (mean ± SD ages: 49 years ± 10, 48 years ± 10, 48 years ± 10, respectively). Changes in two features-complexity and run-length variance-were significantly associated with pCR (adjusted odds ratios per SD increase: 2.13 [95% CI: 1.75, 2.63] and 2.34 [95% CI: 1.87, 2.92]; P < .001). In the external test cohort, DCE-VASC-TRACK outperformed the FTV-based model (AUC, 0.86 [95% CI: 0.79, 0.92] vs 0.72 [95% CI: 0.62, 0.79]; P < .001). Vascular textures showed enrichment in angiogenesis, protein secretion, and transforming growth factor-β signaling pathways compared with clinical factors. Conclusion Incorporating DCE MRI vascular texture dynamics at midtreatment significantly improved pCR prediction compared with clinical and functional tumor volume features alone. Keywords: Breast Cancer, Molecular Imaging, Dynamic Contrast-enhanced MRI, Radiogenomics Supplemental material is available for this article. © The Author(s) 2026. Published by the Radiological Society of North America under a CC BY 4.0 license. Clinical trial registration no. NCT01042379 See also commentary by Schnitzler in this issue.