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 validation, (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). Biological associations were explored using gene set enrichment analysis. Results The study included 417 (development), 162 (internal validation), and 167 (external test) women (mean ages: 49 ± 10, 48 ± 10, 48 ± 10 years). 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]; < .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: 0.63, 0.80]; < .001). Vascular textures showed enrichment in angiogenesis, protein secretion, and TGF-beta 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. © RSNA, 2026.