Lehocky Craig A, Riviere Cameron N
Annu Int Conf IEEE Eng Med Biol Soc. 2014;2014:6530-3. doi: 10.1109/EMBC.2014.6945124.
Deep needle insertion into brain is important for both diagnostic and therapeutic clinical interventions. We have developed an automated system for robotically steering flexible needles within the brain to improve targeting accuracy. In this work, we have developed a finite element needle-tissue interaction model that allows for the investigation of safe parameters for needle steering. The tissue model implemented contains both hyperelastic and viscoelastic properties to simulate the instantaneous and time-dependent responses of brain tissue. Several needle models were developed with varying parameters to study the effects of the parameters on tissue stress, strain and strain rate during needle insertion and rotation. The parameters varied include needle radius, bevel angle, bevel tip fillet radius, insertion speed, and rotation speed. The results will guide the design of safe needle tips and control systems for intracerebral needle steering.
脑深部穿刺对于临床诊断和治疗干预都很重要。我们开发了一种自动化系统,用于在脑内通过机器人操控柔性针,以提高靶向准确性。在这项工作中,我们开发了一个有限元针 - 组织相互作用模型,用于研究针操控的安全参数。所实现的组织模型包含超弹性和粘弹性特性,以模拟脑组织的瞬时和时间依赖性响应。开发了几种具有不同参数的针模型,以研究这些参数在针插入和旋转过程中对组织应力、应变和应变率的影响。变化的参数包括针半径、斜角、斜角尖端圆角半径、插入速度和旋转速度。研究结果将指导用于脑内针操控的安全针尖和控制系统的设计。