Institute of Biomedical Manufacturing and Life Quality Engineering, School of Mechanical Engineering, Shanghai Jiao Tong University, China.
Department of Second Dental Center, Shanghai Ninth People's Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
Comput Methods Programs Biomed. 2024 Jan;243:107940. doi: 10.1016/j.cmpb.2023.107940. Epub 2023 Nov 22.
BACKGROUND AND OBJECTIVE: Zygomatic implant surgery is challenging due to the complex structure of the zygomatic bone, limited visual range during surgery, and lengthy implant path. Moreover, traditional training methods are costly, and experimental subjects are scarce. METHODS: To overcome these challenges, we propose a novel training system that integrates visual, haptic, and auditory feedback to create a more immersive surgical experience. The system uses dynamic bounding volume hierarchy (BVH) and Symplectic Euler to detect global collisions between surgical tools and models, while an optimized finite element method (FEM) model simulates soft tissue and detects collisions. Compared to previous works, our system achieves global rigid-body collisions between surgical tools and patient models, while also providing stable and realistic simulation and collisions of soft tissues. This advancement offers a more realistic simulation for zygomatic implant surgery. RESULTS: We conducted three experiments and evaluations. The first experiment measured the axial force generated during the zygomatic implant simulation process and compared it with actual surgery, demonstrating the realistic force rendering feedback of our system. The second evaluation involved 15 novice surgeons who experienced the system and completed a questionnaire survey focusing on five aspects. The results showed satisfactory evaluations. The third experiment involved six surgeons who underwent in-depth training for two hours daily and were tested on the first, third, and fifth days. We collected data and combined it with the doctors' feedback to prove that our system can improve surgeons' proficiency in zygomatic implant surgery and provide a novel training solution for this procedure. CONCLUSION: We have innovatively integrated global collision detection and optimized soft tissue simulation into our system. Furthermore, we have conducted experimental validation to demonstrate the effectiveness of this implementation. We present a novel solution for zygomatic implant surgery training.
背景与目的：颧骨种植手术具有挑战性，原因在于颧骨结构复杂、手术可视范围有限且种植体路径较长。此外，传统的培训方法成本高，实验对象稀缺。
方法：为了克服这些挑战，我们提出了一种新的培训系统，该系统将视觉、触觉和听觉反馈相结合，以创造更具沉浸感的手术体验。该系统使用动态包围盒层次结构（BVH）和辛普森-欧拉算法来检测手术工具和模型之间的全局碰撞，而优化的有限元方法（FEM）模型则用于模拟软组织并检测碰撞。与之前的工作相比，我们的系统实现了手术工具和患者模型之间的全局刚体碰撞，同时还提供了稳定且逼真的软组织模拟和碰撞。这一进展为颧骨种植手术提供了更逼真的模拟。
结果：我们进行了三项实验和评估。第一项实验测量了颧骨种植模拟过程中产生的轴向力，并与实际手术进行了比较，证明了我们系统具有逼真的力反馈渲染功能。第二项评估涉及 15 名新手外科医生，他们体验了该系统，并完成了一项重点关注五个方面的问卷调查。结果表明评估满意度较高。第三项实验涉及六名外科医生，他们每天接受两小时的深入培训，并在第一天、第三天和第五天进行测试。我们收集数据并结合医生的反馈，证明我们的系统可以提高外科医生在颧骨种植手术方面的熟练度，并为该手术提供新的培训解决方案。
结论：我们创新性地将全局碰撞检测和优化的软组织模拟集成到我们的系统中。此外，我们进行了实验验证，以证明该实现的有效性。我们为颧骨种植手术培训提供了一种新的解决方案。
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