Diffuse domain method for needle insertion simulations.

Area of Science:

• Computational mechanics
• Medical simulation
• Image-guided interventions

Background:

• Accurate needle insertion simulation is crucial for surgical planning and training.
• Traditional methods require complex meshing and precise organ boundary definition, limiting efficiency and adaptability.
• Handling uncertainties in medical image segmentation poses a significant challenge for simulation accuracy.

Purpose of the Study:

• To develop a novel, meshing-free simulation strategy for needle insertion.
• To integrate diffuse domain and phase field methods for seamless tissue parameter transitions.
• To enable patient-specific elastomechanical simulations directly from voxel data, incorporating segmentation uncertainties.

Main Methods:

• A diffuse domain approach on a regular grid was employed, utilizing a phase field function to represent tissue property transitions.
• Implicit imposition of boundary conditions and approximation of needle-tissue interaction forces via the phase field gradient eliminated explicit boundary parameterization.
• A three-class U-Net was used to generate tissue probability maps from computed tomography data for patient-specific simulations.

Main Results:

• The diffuse domain approach yielded deformation fields comparable to conforming mesh simulations.
• The method successfully incorporated uncertainties from volume segmentation by adjusting the phase field width.
• Simulations were performed directly on voxel-based probability maps, demonstrating feasibility for patient-specific cases.

Conclusions:

• The proposed diffuse domain strategy offers an efficient and robust alternative for needle insertion simulations.
• This meshing-free approach simplifies the simulation pipeline and enhances adaptability to medical imaging data.
• The method facilitates patient-specific elastomechanical modeling, directly addressing segmentation uncertainties and enabling direct application on voxel data.