Soft tissue modelling for applications in virtual surgery and surgical robotics

Area of Science:

• Computational mechanics
• Biomedical engineering
• Surgical simulation

Background:

• Soft tissue modeling is vital for developing realistic surgical training simulators, particularly for minimally invasive surgery (MIS).
• Existing continuum-mechanical models vary in complexity and their ability to represent diverse soft tissue properties.
• Selecting an appropriate model is challenging due to the need to balance simulation fidelity with computational efficiency.

Purpose of the Study:

• To provide a structured overview of continuum-mechanical models for soft tissue simulation.
• To guide the selection of appropriate models for specific soft tissue modeling applications.
• To highlight the trade-offs between model complexity and simulation realism.

Main Methods:

• Review and categorization of various continuum-mechanical models based on incorporated features.
• Discussion of models incorporating nonlinearity, viscoelasticity, anisotropy, heterogeneity, and tissue damage.
• Inclusion of summaries on experimental material characterization and geometric modeling techniques.

Main Results:

• Different models capture distinct soft tissue characteristics, ranging from basic nonlinear behavior to complex damage mechanics.
• Model choice is dependent on the specific organ and tissue types being simulated.
• Real-time simulation capability requires a balance between model complexity and the accurate representation of organ deformation.

Conclusions:

• The optimal soft tissue model is organ- and tissue-dependent, requiring careful consideration of specific application needs.
• This overview facilitates informed model selection for applications like surgical simulation.
• Further research may focus on optimizing models for real-time performance while maintaining biological accuracy.