Multimodal Registration of the Brain's Cortical Surface

大脑皮质表面的多模态配准

• 批准号: 7999248
• 负责人: Michael Ian Miga
• 金额: $ 57.02万
• 依托单位: VANDERBILT UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2005
• 资助国家: 美国
• 起止时间: 2005-04-01 至 2012-12-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/7999248
• 关键词: Accounting; Adoption; Anatomy; Award; Biomechanics; Brain; Brain Neoplasms; Cephalic; Cessation of life; Clinical; Clinical Research; Collection; Computational algorithm; Computer Simulation; Computing Methodologies; Conflict (Psychology); Country; Custom; Data; Development; Diagnosis; Diffusion Magnetic Resonance Imaging; Enrollment; Environment; Evolution; Excision; Feedback; Financial compensation; Goals; Health; Image; Image-Guided Surgery; Intervention; Investigation; Lasers; Life; Light; Magnetic Resonance Imaging; Malignant neoplasm of central nervous system; Maps; Measures; Medical center; Methodology; Methods; Mission; National Cancer Institute; National Institute of Neurological Disorders and Stroke; Nervous System Physiology; Nomenclature; Operating Rooms; Operative Surgical Procedures; Organ; Pathology; Patients; Positioning Attribute; Process; Progress Reports; Qualitative Evaluations; Quality of life; Quantitative Evaluations; Reader; Resolution; Resources; Scanning; Series; Shapes; Sterility; Surface; Surgeon; Surgical Error; Survival Rate; System; Techniques; Technology; Testing; Time; Tissues; Translating; Ultrasonography; Uncertainty; Update; Validation; Visual; Work; animation; base; bone; brain tissue; brain tumor resection; charge coupled device camera; computerized data processing; data acquisition; design; digital imaging; functional restoration; imaging modality; improved; innovation; interest; nervous system disorder; novel; simulation; soft tissue; validation studies

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.

描述（由申请人提供）：在20,500人中，今年诊断出的20,500人以及中枢神经系统癌症死亡的12,740人死亡，这些患者中约有85-90％患有脑肿瘤。尽管过去20年增长了20％，但5年生存率约为34-37％。根据国家癌症研究所的外科手术去除是针对大多数脑肿瘤的推荐治疗方法，其目标是最完整的切除，同时保留神经系统功能。关于国家神经系统疾病和中风研究所的使命，更完整的切除可以通过恢复功能，延长生命和改善生活质量来减轻神经疾病的负担。关于手术疗法，将患者在手术室内暴露的大脑（OR）与术前获得的神经解剖学图像相关的视觉显示的部署已变得很普遍。更具体地说，外科医生可以使用笔状的手写笔指向患者脑组织的特定部分，并查看该组织驻留在神经解剖图像上的位置，以促进交互式显示。这过程的损害是，由于常见的手术操纵，患者的大脑变形时。结果，图像与患者的身体大脑之间的比对变得妥协，并且可能会出现手术错误。在最近的工作中，已经证明激光范围扫描（LRS）技术既可以改善皮质表面的比对，又可以在手术过程中测量脑变形。在此应用中，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诱导的错位。要测试的假设是，可以合并计算机模型，术中环境的激光范围数据以及跟踪的手写笔数字化技术，以有效地补偿图像引导的脑肿瘤手术期间的变形。研究该假设的具体目的涉及：（1）一个可以定位在无菌领域中的综合数字化平台，（2）计算机算法，以根据使用数字化平台收集的数据来补偿变形，（3）或计算可以处理数据并在视觉上呈现数据的节点以寻求反馈，以及（4）一系列临床研究以验证该方法。该应用程序中的工作将是第一个用于图像引导手术的完全实现的校正系统。该策略尤其是通过使用预发行和直接模拟来产生强大，准确且快速的补偿方法来创新的。鉴于验证的困难，我们还生成了一种3组分的验证方法，当验证在一起时，它将对技术进行良好的评估。关于这项工作的重要性，在很大程度上，在软组织器官中使用图像引导的手术用于手术切除，主要局限于颅骨环境。随着本文提出的变形的分辨率，将图像引导的手术转换为其他软组织器官的能力变得可能是可能的。此外，与术中成像方法（例如MR）相比，此处的方法也很便宜，并且可扩展，即能够广泛采用。该应用程序的重点是产生图像指导中的下一个演变。公共卫生相关性：在被诊断出的20,500人中，今年中枢神经系统癌症死亡的12,740人死亡，这些患者中约有85-90％患有脑肿瘤。根据国家癌症研究所的外科手术去除是针对大多数脑肿瘤的推荐治疗方法，其目标是最完整的切除，同时保留神经系统功能。更完整的切除可以恢复功能，延长生命并改善这种生活的质量。该项目的目的是帮助外科医生对脑肿瘤进行更完整的切除。另一个重要方面是我们正在引入的技术相对便宜，并且可以接受全国各地的医疗中心广泛采用。