A novel dura mater cutting simulation model based on fracture mechanics and PBD constraints.

BACKGROUND AND

OBJECTIVE

Virtual reality-based neurosurgical simulators show increasing potential for surgical training and preoperative planning. However, existing cutting models often lack a physics-based rupture mechanism and fail to preserve the biomechanical characteristics of soft tissue incisions, limiting their applicability to dura mater cutting simulations. Given the thin structure of the dura mater and its proximity to soft brain tissues, predicting rupture occurrences is essential. To address these challenges, this study presents a novel dura mater cutting model that enhances rupture prediction, incision realism, and simulation visualization.

METHODS

A novel approach integrating Position-Based Dynamics with fracture mechanics to model dura mater cutting is introduced. The model employs the von Mises stress threshold criterion to estimate rupture initiation and location. Incision smoothing and mass redistribution techniques are employed to enhance incision geometry while preserving mass conservation. Additionally, adaptive constraints are used to simulate the post-cutting shrinkage effect of the dura mater.

RESULTS

The presented model provides stable and realistic results during dura mater cutting simulation. The physics-based rupture results achieved are well aligned with those from ABAQUS finite element software, with a maximum discrepancy of 11.3%, while enabling real-time fracture prediction. Validation through stress distribution and cutting force analysis confirms the accuracy of the model, which in the meantime preserves computational efficiency and supports interactive visualization. Furthermore, the incision optimization and shrinkage simulation reproduce smooth incision and characteristic shrinkage behavior of the dura mater.

CONCLUSIONS

The presented model offers a new approach to the simulation of dura mater cutting, integrating rupture prediction, incision optimization, and post-incision shrinkage. This is very important and meaningful in virtual neurosurgical simulation, enhancing surgical training and planning.