Integrated Intraoperative Guidance for Neurosurgery: Develop Surgical Planning To

我们的总体目标是显著提高影像引导神经外科手术的疗效和效率 通过建立一个系统来改进手术中的可视化、导航和监测。这个 该系统将创建一个增强现实可视化的术中病人的大脑结构 与高分辨率的术前成像数据合并，包括扩散张量和功能磁学 磁共振成像(DTI和功能磁共振成像)，以便更好地定位肿瘤和关键的健康组织。在……里面 目前的做法是，神经外科医生获取新的术中图像以研究当前的 以监测患者的大脑结构和肿瘤切除的进展情况。第一个关键限制是 神经外科医生被要求对何时需要获得新的 体积采集。这涉及到对可用导航信息质量的主观估计 从现有的数据来看，根据外科医生的评估，脑移位和肿瘤切除的数量 自从上一次获得核磁共振后就发生了。此外，现有状况的第二个关键限制是 ART系统无法提供关键的术前获取的数据与患者的术中融合 当大脑发生显著变形时的位置。相反，外科医生必须在精神上融合 术前功能磁共振成像和弥散张量成像的信息通过三维空间和时间的心理投射 病人大脑所经历的变化。我们建议开发、实施和评估小说 改进图像制导的术中导航、瞄准和可视化系统的算法 神经外科。我们将改变目前不经常主观计时的整个大脑的做法 术中MRI采集到客观计时的全脑MRI并辅以近实时 稀疏成像。提供近乎实时更新的术前fMRI和DT-MRI可视化 当大脑发生变化时与患者的大脑融合有望极大地提高患者的 神经外科医生保留能言善辩的皮质和关键功能连接，同时最大限度地切除 肿瘤组织。我们将改进我们的脑变形模型，以便能够实现良好的对准 更长，包括更大的大脑变形。这将有助于克服Intra-One的显著限制 手术核磁共振：需要中断手术，转移病人，延长手术时间，以获得 更新的图像。 该项目将通过开发一种系统来促进公众健康，从而在 神经外科。这将为神经外科医生提供更完整的信息，帮助完成 尽可能多地切除肿瘤，同时最大限度地减少健康组织的损失。

Our overall objective is to significantly improve the efficacy and efficiency of image-guided neurosurgery for brain tumors by building a system to improve intraoperative visualization, navigation and monitoring. The system will create an augmented reality visualization of the intraoperative configuration of the patient's brain merged with high resolution preoperative imaging data, including diffusion tensor- and functional magnetic resonance imaging (DTIand fMRI), in order to better localize the tumor and critical healthy tissues. In current practice, the neurosurgeon acquires new intraoperative images in order to study the current configuration of the patient's brain and to monitor the progress of tumor resection. The first key limitation is that the neurosurgeon is required to make a subjective judgment as to when it is necessary to obtain a new volumetric acquisition. This involves a subjective estimate of the quality of navigation information available from the existing data based on the surgeon's assessment the amount of brain shift and tumor resection that has occurred since the last MRI was acquired. Furthermore, a second key limitation of existing state-of-the- art systems is an inability to present key preoperatively acquired data fused with the patient's intraoperative position when the brain has undergone significant deformation. Rather, the surgeon must mentally fuse the information from preoperative fMRI and DTI by mentally projecting it through the 3D spatial and temporal changes the patient's brain has undergone. We propose to develop, implement and evaluate novel algorithms to improve intraoperative navigation, targeting and visualization system for image-guided neurosurgery. We will shift from the current practice of infrequent subjectively timed whole brain intraoperative MRI acquisition to an objectively timed whole brain MRI supplemented with near real-time sparse imaging. The provision of near real-time updated visualizations of preoperative fMRI and DT-MRI fused with the patient's brain as brain shift occurs is expected to dramatically improve the capacity of the neurosurgeon to preserve eloquent cortex and functionally critical connectivity while maximizing the removal of tumor tissue. We will improve our model of brain deformation so that good alignment can be achieved for longer, encompassing larger brain deformations. This will help to overcome a significant limitation of intra- operative MRI: the need to interrupt surgery, move the patient, and extend operative time in order to acquire updated images. This project will contribute to public health by developing a system enabling accurate navigation during neurosurgery. This will provide more complete information to the neurosurgeon, aiding in the task of removing as much tumor as possible while minimizing the loss of healthy tissue.