Discrete element method-based simulation system for predicting natural stone evacuation pathways in patients with...

Urolithiasis is a globally prevalent disease with high incidence and recurrence rates and is often accompanied by severe pain. Its ideal treatment is spontaneous stone passage, avoiding the invasiveness associated with surgery. However, the mechanisms underlying spontaneous stone passage remain unclear. Therefore, in this study, we developed a kidney stone trajectory prediction simulation system using the discrete element method (DEM) to elucidate spontaneous passage mechanisms by analyzing and visualizing stone trajectories within the kidney. We compared this simulation system with experiments using a three-dimensional kidney replica of patients with urolithiasis to optimize critical DEM parameters, including the collision margin ε, friction coefficient C_f, and restitution coefficient C_r. The reliability of these optimized parameters was validated using kidney shapes that differed from those used in the optimization experiments. The simulation system with optimized parameters consistently demonstrated high fidelity to the experimental results, regardless of kidney shape, initial stone position, or stone size. These findings demonstrate the reliability of the simulation system, underscoring its potential contribution to developing new and effective treatments for urolithiasis by improving the accuracy of stone trajectory predictions.