Assessment of Improved Navigation for Pediatric Brain Tumor Surgery

描述(由申请人提供)：这项研究提案是一项新的R01申请，以响应项目公告“生物医学计算科学和技术的创新”，为期五年的资金，用于应用和评估新的手术导航技术，以改善儿童脑肿瘤手术的结果。商业上可用的手术导航系统可以在手术开始时对齐多模式数据，并提供对手术器械的实时跟踪。然而，现有的系统无法在软组织变形后对齐数据，例如在儿童脑肿瘤切除过程中发生的变形。其结果是，在手术开始时建立的精确对齐丢失了，随着神经外科手术的继续，术前到术中数据融合的准确性逐渐恶化。在肿瘤边缘最后切除的关键时期，对位的准确性最差，术前数据并不能直接指导神经外科医生。 我们的目标是显著增加手术期间神经外科医生可获得的术前和术中数据的精确对齐融合可视化的时间。我们将应用我们最近开发的用于术中数据融合的新的非刚性配准算法，以及其他小组发表的最好的可用技术，以便利用术前数据重建精确的导航。我们将通过评估肿瘤切除的体积和百分比，以及评估手术后的神经学结果来评估增强导航的效果。 本研究的具体目的是：1)评估非刚性配准算法在儿童脑肿瘤手术中的目标配准误差；2)显著提高儿童脑肿瘤手术中精确配准和数据融合的时间；3)通过评估术后肿瘤切除体积来评估增强导航的效果。 这项提案将通过评估在儿童脑肿瘤手术期间增强术中导航的关键技术，使公众健康受益。在整个手术过程中可视化肿瘤和肿瘤边缘的能力，以及功能显著的皮质灰质区和白质纤维束，将更好地使神经外科医生在不造成神经功能缺陷的情况下实现更彻底的肿瘤切除。手术切除的评估将导致在儿童脑肿瘤手术中增强导航的有效性的定量确定。

DESCRIPTION (provided by applicant):. This research proposal is a new R01 application in response to the Program Announcement "Innovations in Biomedical Computational Science and Technology" for five years of funding to apply and evaluate novel surgical navigation technology to improve outcomes in pediatric brain tumor surgery. Commercially available surgical navigation systems can align multi-modality data at the start of surgery, and provide real-time tracking of surgical instruments. However, existing systems are unable to align data following soft tissue deformation such as occurs during resection of pediatric brain tumors. As a consequence, the precise alignment established at the start of surgery is lost, and the accuracy of preoperative to intraoperative data fusion is progressively worsened as the neurosurgery continues. At the critical periods of final resection of the tumor margin, the accuracy of alignment is worst, and the preoperative data does not provide a direct guide to the neurosurgeon. It is our objective to significantly increasing the amount of time during the surgery for which precisely aligned fused visualization of preoperative and intraoperative data will be available to the neurosurgeon. We will apply a novel nonrigid registration algorithm that we have recently developed for intraoperative data fusion, as well as the best available techniques published by other groups, in order to re-establish precise navigation with preoperative data. We will assess the efficacy of the enhanced navigation by assessing the volume and percentage of tumor resected, and by assessing neurological outcomes following the surgery. The specific aims of this research are to 1) Evaluate target registration error of nonrigid registration algorithms for pediatric brain tumor surgery, 2) Significantly improve the duration of precise alignment and data fusion during pediatric brain tumor surgery, and to 3) Evaluate the efficacy of enhanced navigation by assessing post-operative tumor resection volume. This proposal will benefit public health by evaluating key technologies to enable enhanced intraoperative navigation during pediatric brain tumor surgery. The capacity to visualize the tumor and tumor margin throughout the surgery, together with functionally significant cortical gray matter regions and white matter fiber tracts, will better enable the neurosurgeon to achieve more complete tumor resection without creating neurological deficits. The assessment of surgical resection will lead to a quantitative determination of the efficacy of enhanced navigation during pediatric brain tumor surgery.