神经导航术中脑组织变形线弹性模型的建立

目的 纠正神经导航手术中的脑组织变形,提高导航手术的精确性.方法 通过有限元方法,构建猪脑组织的线弹性模型.在开颅手术中,通过三维激光扫描获取脑皮层表面的变形,以此作为边界条件,驱动模型,模拟全脑变形情况.并以植入猪脑内的聚甲基内烯酸甲酯微粒为标志点,通过术中实时磁共振扫描获得的脑袋组织实际变形数据对该模型进行验证.结果 该模型的预测误差0.20～1.54mm,平均(0.97±0.44)mm;校正精度56.5%～90.0%,平均(68.0±9.6)%.其中对浅表标志点位移的校正精度高于对深部标志点位移的校正精度[(70.7±9.1)%:(65.4±10.8)%,P＜0.05].结论 模型校正技术是一种简便、快速、可靠的纠正术中脑变形的途径.

Construction & validation of linear elastic model of intraoperative brain deformation during neurosurgical navigtion

Objietive To compensate for the intraoperative brain deformation for the purpose of increasing the accuracy of neurosurgical navigation. Methods A linear elastic model of porcine brain based on finite element method ( FEM ) was established. After craniotomy in swine,the deformation of cortical surface was tracked by a 3D laser range scanner (LRS) as a boundary condition. This boundary condition was then applied on the finite element equation to simulate the entire brain deformation. Polymethyl methacrylate (PMMA) beads were implanted into the porcine brain as markers of tissue shift,and the predictive accuracy of the model was validated by the real-time data of brain deformation acquired by MR imaging during operation. Results The predictive error of this model ranged from 0.20 to 1.54mm,( mean 0.97±0.44 mm). The accuracy of calibration ranged from 56.5% to 90.0% (mean 68.0±9.6% ). The predictive accuracy on the displacement of superficial markers was higher than that of deeper markers (70.7±9.1% : 65.4±10.8%,P ＜ 0.05 ). Conclusions Model-updated image was proved to be efficient,convenient,and reliable in animal research,therefore,it is an ideal approach to compensate for the brain deformation during neurosurgical navigation.