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SlicerSOFA simulation for predicting soft tissue restoration after orbital fracture repair

Key Investigators

• Chi Zhang (Texas A&M College of Dentistry, USA)
• Andrew Read-Fuller (Texas A&M College of Dentistry, USA)
• Rafael Palomar (NTNU / OUH, Norway)
• Paul Baksic (INRIA, France)
• Steve Pieper (Isomics Inc., USA)

Project Description

Orbital fractures are typically caused by blunt-force trauma. Fracture repair frequently requires placing a titanium plate to reconstruct bony orbit and restore tissue position and function from disturbed conditions, such as enophthalmos (“sunken eye”) and muscle entrapment & conformational changes.

This project aims to develop a reproducible patient-specific SOFA/SlicerSOFA FEM simulation workflow to predict orbital soft tissue restoration after fracture repair using a preformed titanium plate.

The simulation processes span across multiple scenes from retracting orbital tissue to place a plate and then let the tissue fall onto the plate. The only deformable object is a unified multi-material orbital tissue mesh. The retracting tool, plate, and bony orbit are all simulated as collision-only boundary conditions.

Currently, collision constraints computation has been identified as a major simulation bottleneck because orbital tissue is confined in the bony orbit. Tissue in fracture orbit also has localized protrusions representing fat herniation that have to be retracted.

Another difficulty is about scene setups and parameter tuning, such as boundary conditions and constraints, including bone-tissue attachment and retracting tool moving trajectory and contour, and experimenting with different parameters and methods.

Objective

The main objective is to streamline workflow reproducibility and improve efficiency for patient-specific simulation:

1. Streamlining setting & simplifying constraints and boundary conditions for patient-specific simulation
2. Tracking, quantifying, and visualize tissue position and shape change.
3. Facilitate smooth transition across different SOFA scenes in Slicer and improve interactive simulation.
4. Facilitate parameter tuning, method selection, and performance tracking within Slicer

Approach and Plan

Implement Slicer methods to:

1. Streamline scene setup and interaction, such as tissue bone attachment, syncing the interactive transform with the SOFA controller, retraction trajectories, and collision regions
2. Track and visualize tissue deformation, such as using TPS, grid transform, and mark up-based methods.
3. Facilitate performance tracking and parameter tuning & method selection in SlicerSOFA (e.g., exploring using AI agents)
4. Initiate creating a Slicer module based on SlicerSOFA for multi-scene simulation

Progress and Next Steps

1. Describe specific steps you have actually done.

Illustrations

Background and References

No response