Spatial Configuration of Pancreatic Cancer Is Associated with Disease Recurrence after Neoadjuvant Therapy and Curative-Intent Resection

PURPOSE: Pancreatic ductal adenocarcinoma (PDAC) frequently recurs after neoadjuvant therapy (NT) and curative-intent resection. Although major pathologic response predicts favorable outcomes, most patients achieve only minor response with heterogeneous recurrence risk. We asked whether the spatial organization of residual PDAC encodes clinically relevant biology beyond residual tumor burden. EXPERIMENTAL DESIGN: In a retrospective cohort of 203 resected PDAC patients treated with NT and restricted to minor pathologic response, routine H&E whole-slide images were segmented into cancer and stroma using an AI-enabled pipeline. Spatial composition (patch density, edge density) and configuration (compactness/complexity, intermixing) were quantified and tested associations with disease-free survival (DFS) using multivariable models adjusted for standard clinicopathologic factors. RESULTS: Shorter DFS was associated with a fragmented, interface-rich tumor-stroma ecology featuring higher edge density and diversity and reduced homotypic aggregation, independent of clinicopathologic variables. Two spatial risk models were independently prognostic: (i) cancer mean shape index plus stromal shape-index variability (adjusted HR 1.71; P=0.003) and (ii) mean stromal patch area plus edge density (adjusted HR 2.19; P=0.002). Both models stratified outcomes where pathologic response grading and residual cancer area did not. High-risk configurations were further associated with reduced intratumoral tumor-infiltrating lymphocyte (TIL) density and infiltration ratio, with relative TIL accumulation at the cancer periphery and within the stroma, consistent with an immune-excluded phenotype. CONCLUSIONS: Residual cancer-stroma topology quantified from standard H&E slides yields independent prognostic signals after NT in PDAC, provides a cellular immune correlate for spatial risk, and motivates prospective validation and spatially informed adjuvant strategies.