Numerical Calculation Method for Brain Shift Based on Hydrostatics and Dynamic FEM
Numerical Calculation Method for Brain Shift Based on Hydrostatics and Dynamic FEM
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基于流体静力学和动态有限元的脑移数值计算方法
DOI：
10.1109/tmrb.2022.3168075
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发表时间：
2022
期刊：
影响因子：
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通讯作者：
Konno Atsushi
中科院分区：
文献类型：
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作者：
Chen Xiaoshuai;Shirai Ryosuke;Masamune Ken;Tamura Manabu;Muragaki Yoshihiro;Sase Kazuya;Tsujita Teppei;Konno Atsushi
在神经外科手术中，由于重力和脑脊液（CSF）的泄漏而发生脑变形，这被称为脑移位。脑移位是神经导航中的一个严重问题，因为神经导航依赖于术前拍摄的医学图像。本文提出了一种基于流体静力学和动力学有限元的脑移位估计方法，假设重力和脑脊液泄漏是脑移位的主要原因。所提出的方法的准确性进行了验证，通过使用弹性明胶立方体进行的基础实验。此外，使用患者的术前医学图像创建3D脑模型，并进行脑移位估计模拟。通过将仿真结果与神经外科手术中的实际脑移位进行比较，验证了其准确性。假设在脑移位之前额叶的最前位置中的节点和顶叶的最高位置中的节点即使在脑移位之后也分别保持在最前位置和最高位置中，搜索脑移位之前和之后的对应区域并且评估变形。在该误差分析中，最大估计误差为4.4 mm。此外，选择额叶中40 mm 30 mm的区域作为感兴趣区域（ROI），并分析术中MRI图像与模拟移位脑之间的ROI中的表面误差。ROI中沿着z轴（重力方向）表面之间的平均绝对误差（MAE）为3.7 mm（最大绝对误差为8.8 mm）。所提出的方法足够简单，可以实时计算大脑的变化。本研究对改善神经导航错误和提高神经外科手术安全性的预期贡献将有利于医院，特别是在无法进行术中MRI时。
During neurosurgery, brain deformation occurs because of gravity and leakage of the cerebrospinal fluid (CSF), which is referred to as brain shift. Brain shift is a serious problem in neuronavigation because neuronavigation relies on preoperatively taken medical images. This paper presents a brain shift estimation method based on hydrostatics and dynamic FEM, assuming that gravity and leakage of CSF are the main reasons for brain shift. The accuracy of the proposed method was verified via basic experiments conducted using elastic gelatin cubes. In addition, a 3D brain model was created using preoperative medical images of a patient and brain shift estimation simulations were performed. Their accuracy was verified by comparing the simulation results with the actual brain shift during neurosurgery. Assuming that the node in the most anterior position of the frontal lobe and the node in the highest position of the parietal lobe before the brain shift respectively remain in the most anterior position and the highest position even after the brain shift, the corresponding regions before and after the brain shift were searched and the deformations were evaluated. In this error analysis, the maximum estimation error was 4.4 mm. Furthermore, a region of 40 mm30 mm in the frontal lobe was chosen as the region of interest (ROI), and the surface errors in the ROI between the intraoperative MRI images and the simulated shifted brain were analyzed. The mean absolute error (MAE) between the surfaces along the z-axis (the direction of gravity) in the ROI was 3.7 mm (maximum absolute error was 8.8 mm). The proposed method was sufficiently simple for computing the brain shift in real-time. The expected contribution of this study toward improving the neuronavigational error and enhancing the safety of neurosurgery will be beneficial for hospitals, especially when the intraoperative MRI cannot be performed.