Augmentation of Accuracy for Image-guided Neurosurgery

描述（由申请人提供）： 这项工作的最终目标是提高微电极引导手术的成功率，从而改善运动障碍患者的生活质量。为了实现这一目标，提出了在不干扰手术的标准部分的情况下增强手术的导航准确性的方法。为了成功地瞄准特定的大脑位置（例如，植入永久性刺激电极的最佳位置），需要准确地知道感兴趣的相邻结构的边界（在这种情况下：基底神经节、丘脑、丘脑下、视束）。在标准程序中，这些边界是从大脑图谱中获得的。然而，以下因素会对3rocket的准确性产生不利影响：脑图谱和患者解剖结构的形状和大小差异，以及术中脑变形。为了解决这些问题，提出了以下目标：目标1。将探索现有的大脑图谱，并选择分辨率最高的图谱。将设计用于从图谱图像构建感兴趣结构的3D表面模型的方法。该图集将由堆叠成3D图像体积的图像和3D表面模型的集合来表示。AIM 2.将开发一种高度精确的方法，用于寰椎3D图像和患者术前MR扫描的非刚性对准。此对齐将应用于图谱模型，以调整其位置、形状和大小。这将使模型与患者MR扫描配准，使其具有患者特异性。AIM 3.术中记录沿微电极轨迹沿着感兴趣结构之间的边界位置。该信息将用于微调患者特定模型，以使其更准确。目标4.将分析术中脑变形，研究其对微电极引导手术准确性的影响，并探索其补偿方法。AIM 5.所提出的方法将在50例微电极引导手术中进行临床试验。虽然所提出的方法将应用于微电极引导手术，但它们可以扩展到其他图像引导的神经外科手术，包括肿瘤切除和癫痫手术。

DESCRIPTION (provided by applicant): The ultimate goal of this work is to increase the success rate of the microelectrode-guided surgery and consequently improve the quality of life of patients suffering from movement disorders. To achieve this goal, methods are proposed to augment the navigational accuracy of the surgery without interfering with standard portions of the procedure. To successfully target a specific brain location (e.g. the best location for implantation of a permanent stimulating electrode), one needs to accurately know the boundaries of the neighboring structures of interest (in this case: Basal Ganglia, Thalamus, Sub-thalamus, optic tract). In the standard procedure, these boundaries are obtained from a brain atlas. However, the accuracy of the 3rocedure is adversely affected by: the shape and size difference in anatomy of the brain atlas and of the 3atient, and by intraoperative brain deformation. To address these problems the following aims are proposed: AIM 1. Available brain atlases will be explored and the highest-resolution one will be selected. A method for building 3D surface models of the structures of interest from the atlas images will be designed. The atlas will be represented by its images stacked into a 3D image volume and by a collection of 3D surface models. AIM 2. A highly accurate method for nonrigid alignment of the atlas 3D image and the patient's preoperative MR scan will be developed. This alignment will be applied to the atlas models to adjust their position, shape, and size. This will bring the models into registration with the patient MR scan making them patient specific. AIM 3. The locations of boundaries between structures of interest along the microelectrode tracks are recorded intraoperatively. This information will be used to fine-tune the patient specific models in order to make them more accurate. AIM 4. The intraoperative brain deformation will be analyzed, its affect on the accuracy of the microelectrode-guided surgery will be investigated, and methods for its compensation will be explored. AIM 5. The proposed methods will be clinically tested on 50 cases of microelectrode-guided surgery. Although the proposed methods will be applied to the microelectrode-guided surgery, they can be extended to other image-guided neurosurgical procedures, including tumor removal and epilepsy surgery.