Non-invasive Assessment of Pancreatic Duct Hypertension Using Computational Flow Modeling

Chronic pancreatitis (CP) is a progressive inflammatory disease frequently associated with severe, treatment-resistant abdominal pain, which is hypothesized to result from pancreatic ductal hypertension (PDH) secondary to ductal strictures or obstructions. However, direct measurement of pancreatic duct pressure (PDP) remains technically demanding and invasive, thereby significantly limiting its routine clinical application. Here, we propose and validate a novel, non-invasive approach for estimating PDP. The method integrates patient-specific magnetic resonance cholangiopancreatography (MRCP) imaging with computational fluid dynamics (CFD) modeling. Three-dimensional ductal models reconstructed from MRCP data enabled simulation of intraductal pressure distributions with high anatomical fidelity. The simulated pressure gradients showed strong correlation with in vivo measurements obtained via endoscopic retrograde cholangiopancreatography (ERCP), as well as with clinical outcomes such as pain relief following ductal decompression. To improve clinical usability, we developed a quasi-one-dimensional analytical model that accurately predicted PDP from ductal geometry and flow parameters, showing strong concordance with CFD results. These findings establish the feasibility and clinical relevance of MRCP-based PDP estimation, and underscore its potential as a non-invasive diagnostic tool for detecting PDH and informing therapeutic decisions in patients with CP.