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Virtual plate placement for orbital surgery
Key Investigators
- Chi Zhang (Texas A&M University School of Dentistry, USA)
- Braedon Gunn (Texas A&M University School of Dentistry, USA)
- Andrew Read-Fuller (Texas A&M University School of Dentistry, USA)
Project Description
We are developing a Slicer module to simulating registering titanium plate to orbital fracture sites to aid surgical planning and investigating the fitness of different commercial preformed plates across a large sample of patients.
Objective
Make a module to allow the plate to properly sits above the bone at the orbital fracture site
Approach and Plan
See below.
Progress and Next Steps
I have complied existing methods in Slicer and VTK into one preliminary module https://github.com/chz31/surgical_plate_registration to do the semi-automatic registration:
- An initial fiducial registration and a refined registration based on only allowing the plate to rotate while pivoting on the posterior stop, an important landmark for place the nail.
2. Use VTKCollisionDetector() and intersect marker to detect collision and mark the intersection
3. Use Probe Volume with Model to paint both the orbit and the plate to mark the overlapping areas.
4. Use the new Interaction Transform Handle to manually fine tune the position
7. Update new intersection and overlapping areas until they ar minimized.
Next steps:
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Improving the use of the Interaction Transform Handle and intersection marker to more efficiently adjust plate position so that it sits just above the bone. Converting transform matrix into standard descriptor: yaw, roll, and pitch.
(from https://doi.org/10.1371/journal.pone.0150162)
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Design measurements to quantify plate fitness. Comparing the shape of the plate with the unfractured orbit.
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Automated segmentation for segmenting fractured orbit.
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Explore methods such as reinforcement learning and SOFA for actual simulating how the plate is placed.
Illustrations
No response
Background and References
The repo for the current module: surgical_plate_registration Other studies using commercial software iPlan from BrainLab, which should still be based on manual adjustment: Schreur et al. 2017 and Schreur et al. 2021