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首页> 外文期刊>Medical image analysis >Brain-skull contact boundary conditions in an inverse computational deformation model.
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Brain-skull contact boundary conditions in an inverse computational deformation model.

机译：逆计算变形模型中的脑-颅接触边界条件。

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摘要

Biomechanical models simulating brain motion under loading and boundary conditions in the operating room (OR) are gaining attention as alternatives for brain shift compensation during open cranial neurosurgeries. Although the significance of brain-skull boundary conditions (BCs) in these models has been explored in dynamic simulations, it has not been fully investigated in models representing the quasi-static brain motion that prevails during neurosurgery. In this study, we extend the application of a brain-skull contact BC by incorporating it into an inversion estimation scheme for the deformation field using the steepest gradient descent (SGD) framework. The technique allows parenchymal surface motion normal to the skull while maintaining stress-free BCs at the craniotomy and minimizing the effect of measurement noise. Application of the algorithm in five clinical cases using sparse data generated at the tumor boundary confirms the significance of brain-skull BCs in the model response. Specifically, the results demonstrate that the contact BC enhances model flexibility and achieves improved or comparable performance at the tumor boundary (recovering about 85% of the deformation) relative to that obtained when normal motion of the parenchymal surface is not allowed. It also significantly improves model estimation accuracy at the craniotomy (1.6mm on average), especially when the normal motion is large. The importance of the method is that model performance significantly improves when brain-skull contact influences the deformation field but does not degrade when the contact is less critical and simpler BCs would suffice. The computational cost of the technique is currently 3.9 min on average, but may be further reduced by applying an iterative solver to the linear systems of equations involved and/or by local refinement of the mesh in regions of interest.
机译：作为在颅内神经外科手术中进行脑移位补偿的替代方法，模拟在负荷和边界条件下在手术室（OR）中进行脑运动的生物力学模型正在引起关注。尽管已经在动态模拟中探索了这些模型中脑-颅边界条件（BCs）的重要性，但尚未在代表神经外科手术中普遍存在的准静态脑运动的模型中对其进行充分研究。在这项研究中，我们通过使用最陡峭的梯度下降（SGD）框架将脑-头骨接触BC合并到变形场的反演估计方案中，从而扩展了它的应用。该技术可以使颅骨正常的实质表面运动，同时在开颅手术中保持无应力的BC并最小化测量噪声的影响。该算法在五个临床案例中的应用（使用在肿瘤边界处生成的稀疏数据）证实了脑头骨BC在模型响应中的重要性。具体而言，结果表明，与不允许实质表面正常运动时相比，接触BC增强了模型的灵活性，并在肿瘤边界处实现了改善或相当的性能（恢复了约85％的变形）。它还在开颅手术（平均1.6mm）时显着提高了模型估计的准确性，尤其是在法向运动较大时。该方法的重要性在于，当脑-头骨接触影响变形场时，模型性能会显着提高，但当接触不太关键且简单的BC足够时，模型性能不会降低。该技术的计算成本目前平均平均为3.9分钟，但可以通过将迭代求解器应用于所涉及方程的线性系统和/或通过对目标区域中的网格进行局部优化来进一步降低。

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