Department of Psychiatry, Columbia University, New York, NY 10032, USA.
IEEE Trans Med Imaging. 2012 Aug;31(8):1607-19. doi: 10.1109/TMI.2012.2197407. Epub 2012 May 2.
During neurosurgery, nonrigid brain deformation may affect the reliability of tissue localization based on preoperative images. To provide accurate surgical guidance in these cases, preoperative images must be updated to reflect the intraoperative brain. This can be accomplished by warping these preoperative images using a biomechanical model. Due to the possible complexity of this deformation, intraoperative information is often required to guide the model solution. In this paper, a linear elastic model of the brain is developed to infer volumetric brain deformation associated with measured intraoperative cortical surface displacement. The developed model relies on known material properties of brain tissue, and does not require further knowledge about intraoperative conditions. To provide an initial estimation of volumetric model accuracy, as well as determine the model's sensitivity to the specified material parameters and surface displacements, a realistic brain phantom was developed. Phantom results indicate that the linear elastic model significantly reduced localization error due to brain shift, from > 16 mm to under 5 mm, on average. In addition, though in vivo quantitative validation is necessary, preliminary application of this approach to images acquired during neocortical epilepsy cases confirms the feasibility of applying the developed model to in vivo data.
在神经外科手术中，非刚性的脑组织变形可能会影响基于术前图像的组织定位的可靠性。为了在这些情况下提供准确的手术指导，必须更新术前图像以反映术中的大脑。这可以通过使用生物力学模型对这些术前图像进行变形来实现。由于这种变形可能很复杂，因此通常需要术中信息来指导模型求解。本文开发了一种大脑的线性弹性模型，以推断与测量的术中皮质表面位移相关的容积性脑变形。所开发的模型依赖于已知的脑组织材料特性，并且不需要关于术中条件的进一步知识。为了提供对体积模型准确性的初始估计，并确定模型对指定材料参数和表面位移的敏感性，开发了一个现实的脑体模。体模结果表明，线性弹性模型显著降低了由于脑移位导致的定位误差，平均从超过 16 毫米降低到 5 毫米以下。此外，尽管需要进行体内定量验证，但该方法在新皮质癫痫病例中获取的图像中的初步应用证实了将所开发的模型应用于体内数据的可行性。
