基于杆-质点模型实现的脑膜瘤术前训练系统

Preoperative Training System for Meningioma Based on Rod-Particle Model Implementation

脑膜瘤是中枢神经系统最为常见的原发性肿瘤,手术摘除是该疾病的首选治疗方案。脑神经外科疾病发病紧急、专家少、会诊难度大,且病灶易与周围组织粘连,手术操作空间狭小。因此,设计术前培训系统帮助医生模拟手术过程是非常必要的,而如何实时模拟手术过程中手术器具与脑膜瘤及周边正常脑组织的交互力是亟待解决的问题。采用改进的杆-质点模型建立脑膜瘤摘除过程中手术器具与病灶的交互过程模型,实时计算交互力,并通过手控器反馈给医生,使医生能够真实感受手术过程。基于C#、Unity 3D等软硬件系统构建虚拟手术系统平台进行实验,验证了所提出的方法具有实时性,可以满足神经外科手术需求。

Meningioma is the most common primary tumor of the central nervous system,and surgical removal is the preferred treatment option.Cerebral neurosurgical diseases are urgent,with few experts and difficult consultation.The lesions are prone to adhere with surrounding tissues,and the surgical operation space is limited.Therefore,it is necessary to design a preoperative training system to help surgeons simulate the surgical process,and how to simulate the interaction between the surgical instruments and the meningioma and the surrounding normal brain tissue during the operation is an urgent problem to be solved.The improved rod-particle model is used to establish an interaction process between surgical instruments and lesions during meningioma removal.The interaction force is calculated in real-time and fed back to surgeons via a haptic robot,allowing surgeons to truly experience the surgical process.Based on software and hardware systems such as C#and Unity 3D,a virtual surgical system platform is constructed for experiment,the proposed method is verified to have real-time performance and can meet the requirements of neurosurgery surgery.