Super-Resolution MRI-Derived Tumor-Stroma Ratio Phenotyping for Prognostic and Therapeutic Stratification in Pancreatic Ductal Adenocarcinoma.

Abstract

Pancreatic ductal adenocarcinoma (PDAC) exhibits profound stromal heterogeneity that influences tumor progression, recurrence risk, and therapeutic response; however, stromal phenotypes are currently assessed by postoperative histopathology. Here, we developed a super-resolution MRI (srMRI)-based radiomics model to enable noninvasive tumor-stroma ratio (TSR) phenotyping in PDAC. Using multicenter cohorts comprising 737 patients, we constructed a srMRI-derived TSR-radscore capable of predicting pathological TSR with high accuracy (AUC = 0.870 and 0.791 in training and external validation cohorts). The TSR-radscore independently stratified recurrence-free survival and, when integrated with clinicopathological variables, improved early recurrence prediction in an independent surgical cohort. In a locally advanced PDAC cohort, srMRI-derived TSR was associated with distinct therapeutic outcomes, with H-TSR tumors showing improved survival under systemic therapy and an association with outcomes following immune checkpoint inhibitor-based combination therapy. Transcriptomic analyses revealed that L-TSR tumors were enriched in extracellular matrix remodeling and TGF-β-related signaling pathways. Single-cell profiling further uncovered distinct cancer-associated fibroblast and T-cell states across TSR phenotypes, linking imaging-derived TSR patterns to underlying stromal and immune microenvironmental programs. Collectively, srMRI-derived TSR phenotyping provides a noninvasive and biologically interpretable biomarker for stromal characterization in PDAC, enabling improved recurrence-risk stratification and pre-treatment clinical assessment.