Interdisciplinary Collaborative Virtual Reality Planning for Chest Wall Resection and Reconstruction for Sarcoma and...

Area of Science:

• Surgical Oncology
• Medical Visualization
• Artificial Intelligence in Medicine

Background:

• Oncologic chest wall resection and reconstruction are complex procedures requiring precise planning for oncologic and functional outcomes.
• Advanced visualization technologies, like virtual reality (VR), offer immersive anatomical representation to enhance surgical planning.

Purpose of the Study:

• To establish a streamlined workflow using AI-enhanced VR for optimizing surgical planning in complex chest wall reconstruction.
• To evaluate the accuracy of VR-predicted parameters against intraoperative findings and assess user experience.

Main Methods:

• Retrospective analysis of eight complex chest wall resection cases using the "Medical Imaging XR" VR platform with AI-driven segmentation.
• Interdisciplinary team planning in VR, comparing predicted resection extent and defect dimensions with actual intraoperative results.
• User experience assessment using the User Experience Questionnaire (UEQ), workspace perception, and Simulator Sickness Questionnaire (SSQ).

Main Results:

• AI-enhanced VR planning facilitated interdisciplinary collaboration and improved spatial understanding.
• In 37.5% of cases, actual resection exceeded VR-predicted extent due to underestimated tumor infiltration.
• VR planning was a complementary tool for strategy selection, not a definitive predictor of resection extent, with limitations in imaging resolution and segmentation accuracy.

Conclusions:

• AI-enhanced VR planning improves preoperative planning and communication for complex chest wall surgery.
• The technology enhances spatial understanding but requires further clinical validation for full impact assessment.
• Limitations in current AI segmentation and imaging resolution necessitate viewing VR planning as an adjunct to, not a replacement for, surgical expertise.