Virtual reality-augmented differentiable simulations for digital twin applications in surgical planning

Area of Science:

• Medical Imaging and Simulation
• Surgical Planning Technologies
• Virtual Reality in Medicine

Background:

• Current surgical planning lacks immersive, interactive tools for complex trajectory analysis.
• Accurate path generation in segmented medical images remains a challenge.

Purpose of the Study:

• To develop an integrated digital twin for enhanced surgical planning.
• To improve the precision and efficiency of preoperative decision-making.

Main Methods:

• Utilized Langevin random walkers for stochastic path planning within segmented medical images.
• Developed a custom VR shader for seamless integration of medical data and surgical trajectories.
• Implemented real-time trajectory adjustments based on surgeon feedback.

Main Results:

• Demonstrated effective navigation of complex medical imaging data without extensive modeling.
• Created an immersive VR platform for intuitive surgical path exploration.
• Showcased potential for improved preoperative decision-making and surgical outcomes.

Conclusions:

• The integrated digital twin approach enhances surgical planning precision.
• VR-based visualization and real-time adjustments offer significant benefits for surgeons.
• This novel strategy promises to improve overall surgical success rates.