Haouchine Nazim, Juvekar Pariskhit, Golby Alexandra, Frisken Sarah
Harvard Medical School, Boston, MA, USA.
Brigham and Women's Hospital, Boston, MA, USA.
Comput Methods Biomech Biomed Eng Imaging Vis. 2020;9(4):407-413. doi: 10.1080/21681163.2020.1834874. Epub 2020 Oct 30.
During a craniotomy, the skull is opened to allow surgeons to have access to the brain and perform the procedure. The position and size of this opening are chosen in a way to avoid critical structures, such as vessels, and facilitate the access to tumors. Planning the operation is done based on pre-operative images and does not account for intra-operative surgical events. We present a novel image-guided neurosurgical system to optimize the craniotomy opening. Using physics-based modeling we define a cortical deformation map that estimates the displacement field at candidate craniotomy locations. This deformation map is coupled with an image analogy algorithm that produces realistic synthetic images that can be used to predict both the geometry and the appearance of the brain surface before opening the skull. These images account for cortical vessel deformations that may occur after opening the skull and is rendered in a way that increases the surgeon's understanding and assimilation. Our method was tested retrospectively on patients data showing good results and demonstrating the feasibility of practical use of our system.
在开颅手术中，打开颅骨以便外科医生能够接触到大脑并进行手术。这个开口的位置和大小的选择方式是为了避开关键结构，如血管，并便于接近肿瘤。手术规划是基于术前图像进行的，并未考虑术中的手术事件。我们提出了一种新型的图像引导神经外科系统，以优化开颅开口。通过基于物理的建模，我们定义了一个皮质变形图，该图估计候选开颅位置处的位移场。这个变形图与一个图像类比算法相结合，该算法生成逼真的合成图像，可用于在打开颅骨之前预测脑表面的几何形状和外观。这些图像考虑了打开颅骨后可能发生的皮质血管变形，并以一种增强外科医生理解和认知的方式呈现。我们的方法在患者数据上进行了回顾性测试，结果良好，证明了我们系统实际应用的可行性。
