Multimodal Registration of the Brain's Cortical Surface

描述（申请人提供）：在今年诊断的20，500人中，有12，740人死于中枢神经系统癌症，其中约85-90%的患者患有脑肿瘤。5年生存率约为34-37%，尽管在过去20年中增加了20%。根据国家癌症研究所的建议，手术切除是大多数脑肿瘤的推荐治疗方法，其目标是尽可能完整地切除，同时保留神经功能。关于国家神经疾病和中风研究所的使命，更完整的切除通过恢复功能、延长生命和提高生活质量来减轻神经疾病的负担。关于手术治疗，将手术室（OR）内的患者暴露的大脑与手术前获取的神经解剖图像相关联的视觉显示器的部署已经变得司空见惯。更具体地，外科医生可以使用笔状触针来指向患者脑组织的特定块，并通过交互式显示器来查看该组织在神经解剖图像上的位置。对这个过程的一个损害是当患者的大脑由于常见的外科手术操作而变形时。结果，图像和患者的物理大脑之间的对准变得受损，并且可能发生手术错误。在最近的工作中，激光范围扫描（LRS）技术已被证明可以改善皮质表面的对齐，并在手术过程中测量大脑变形。在该应用中，LRS技术的使用将与计算机模型一起扩展，以纠正手术期间变形引起的未对准。要测试的假设是，计算机模型，术中环境的激光范围数据，和跟踪针数字化技术可以结合起来，以有效地补偿在图像引导的脑肿瘤手术中的变形。调查这一假设的具体目标涉及以下方面的发展：（1）可以定位在无菌区域中的综合数字化平台，（2）基于用数字化平台收集的数据补偿变形的计算机算法，（3）可以处理数据并将数据可视地呈现给外科医生以供反馈的OR计算节点，以及（4）一系列临床研究来验证该方法。这项应用的工作将是第一个完全实现的图像引导手术校正系统。该策略通过使用预先计算和直接模拟来生成鲁棒、准确和快速的补偿方法，特别具有创新性。考虑到验证的困难，我们还生成了一个3组件验证方法，当它们结合在一起时，将提供对技术的良好评估。关于这项工作的重要性，在很大程度上，使用图像引导手术切除软组织器官主要局限于颅环境。利用如本文所提出的变形的分辨率，将图像引导的外科手术转换到其他软组织器官的能力变得可能。此外，当与术中成像方法（例如，MR）相比时，本文中的方法也是廉价的，并且是可扩展的，即能够被广泛采用。该应用程序的重点是产生图像引导的下一个演变。公共卫生相关性：在今年确诊的20，500人和12，740名死于中枢神经系统癌症的患者中，大约85-90%的患者患有脑肿瘤。根据国家癌症研究所的建议，手术切除是大多数脑肿瘤的推荐治疗方法，其目标是尽可能完整地切除，同时保留神经功能。更完整的切除可以恢复功能，延长生命，提高生活质量。该项目的目标是帮助外科医生更完整地切除脑肿瘤。另一个重要的方面是，我们引入的技术相对便宜，并且适合全国各地的医疗中心广泛采用。

DESCRIPTION (provided by applicant): Of the 20,500 people diagnosed, and the 12,740 deaths from cancer of the central nervous system this year, approximately 85-90% of these patients are afflicted with brain tumors. The 5-year survival rate is approximately 34-37% despite an increase by 20% over the past 20 years. According to the National Cancer Institute surgical removal is the recommended treatment for most brain tumors with the goal of the most complete resection possible while preserving neurological function. With respect to the mission of the National Institute for Neurological Disorders and Stroke, more complete resection reduces the burden of neurological disease by restoring function, extending life, and improving the quality of that life. With respect to surgical therapy, the deployment of visual displays that relate the patient's exposed brain within the operating room (OR) to the pre-operatively acquired neuroanatomical images has become commonplace. More specifically, surgeon's can use a pen-like stylus to point at a specific piece of the patient's brain tissue and see where that tissue resides on the neuroanatomical images as facilitated by an interactive display. One detriment to this process is when the patient's brain deforms due to common surgical manipulations. As a result, the alignment between images and the patient's physical brain becomes compromised and surgical error could ensue. In recent work, laser range scanning (LRS) technology has been demonstrated to both improve the alignment of the cortical surface and measure brain deformations during surgery. In this application, the use of LRS technology will be extended in conjunction with computer models to correct the deformation-induced misalignment during surgery. The hypothesis to be tested is that computer models, laser range data of the intra-operative environment, and tracked stylus digitization technology can be combined to effectively compensate for deformation during image-guided brain tumor surgery. The specific aims to investigate this hypothesis involve the development of: (1) a comprehensive digitization platform that can be positioned in the sterile field, (2) a computer algorithm to compensate for deformations based on data collected with digitization platform, (3) an OR compute node that can process data and present the data visually to the surgeon for feedback, and (4) a series of clinical studies to validate the approach. The work in this application will be the first fully realized correction system for image-guided surgery. The strategy is particularly innovative by using both pre-computation and direct simulation to generate a robust, accurate, and fast approach to compensation. Given the difficulty in validation, we have also generated a 3-component approach to validation, which when take together, will provide a good assessment of the techniques. With respect to the importance of this work, in large part, the use of image-guided surgery for surgical resection in soft-tissue organs has been confined primarily to the cranial environment. With the resolution of deformations as proposed herein, the ability to translate image-guided surgery to other soft-tissue organs becomes possible. Furthermore, the approaches herein are also inexpensive when compared to intra-operative imaging methods (e.g. MR), and scalable, i.e. capable of widespread adoption. This application is focused at producing the next evolution in image guidance. PUBLIC HEALTH RELEVANCE: Of the 20,500 people diagnosed, and the 12,740 deaths from cancer of the central nervous system this year, approximately 85-90% of these patients are afflicted with brain tumors. According to the National Cancer Institute surgical removal is the recommended treatment for most brain tumors with the goal of the most complete resection possible while preserving neurological function. More complete resection restores function, extends life, and improves the quality of that life. The goal of this project is to assist the surgeon in producing a more complete resection of brain tumors. The other important aspect is the technology we are introducing is relatively inexpensive and is amenable to widespread adoption by medical centers all across the country.