Augmented Neurosurgical Navigation Software Using Resting State MRI

使用静息态 MRI 的增强神经外科导航软件

• 批准号: 10066314
• 负责人: Eric CLAUDE Leuthardt
• 金额: $ 69.85万
• 依托单位: WASHINGTON UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2017
• 资助国家: 美国
• 起止时间: 2017-01-17 至 2022-07-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10066314
• 关键词: 3-Dimensional; Address; Algorithmic Software; Algorithms; Anatomy; Brain; Brain Mapping; Brain Neoplasms; Brain imaging; Child; Classification; Clinical; Cognitive; Collaborations; Computer Interface; Computer software; Data; Data Set; Development; Ensure; Environment; Excision; Failure; Functional Magnetic Resonance Imaging; Goals; Gold; Healthcare; Heart; Image; Image Analysis; Image-Guided Surgery; Imaging Techniques; Imaging technology; Individual; Industry; Intuition; Language; Lesion; Magnetic Resonance Imaging; Malignant Glioma; Maps; Methodology; Methods; Mind; Navigation System; Neuronavigation; Neurosurgeon; Neurosurgical Procedures; Operative Surgical Procedures; Outcome; Output; Patients; Performance; Picture Archiving and Communication System; Population; Privatization; Public Health; Quality Control; Quality of life; Research; Rest; Science; Site; Standardization; Stress Tests; Supervision; Surface; Surgeon; System; Techniques; Technology; Testing; Time; Translating; Translations; Universities; Washington; Work; base; brain tumor resection; clinical application; clinical infrastructure; design; experience; flexibility; functional outcomes; functional status; improved; improved outcome; industry partner; innovation; multilayer perceptron; patient population; personalized approach; preservation; prevent; statistics; tool; translational approach; tumor

Project Summary/Abstract By providing real-time anatomic information to the neurosurgeon, stereotactic neuro-navigation has been shown to improve the extent of tumor resection and, as a result, improve survival statistics. That said, it is not routine during resections to make use of similar neuronavigation displays that reflect the functional organization of the brain. Task-based fMRI has been employed as a means of pre-operatively localizing function. However, task- based fMRI depends on the patient's ability to comply with the task paradigm, which frequently is lacking. This problem can be overcome by using the recently developed method of resting state functional magnetic resonance imaging (rsfMRI) to localize function. Moreover, rsfMRI is highly efficient, as multiple resting state networks (RSNs) associated with multiple cognitive domains can be mapped at the same time. With this in mind, the long-term goal of our research is to improve survival and quality of life after surgical resection of brain tumors by improving the identification and preservation of eloquent cortex. The current barrier that prevents the widespread use of rsfMRI is the high degree of advanced imaging expertise currently necessary to create and interpret the images. To address this shortcoming, we propose to create a turnkey system for functional mapping within the brain. At the heart of our methodology is a multi-layer perceptron (MLP) algorithm that assigns RSN membership to each locus within the brain using supervised classification of rsfMRI data. Current data demonstrate that MLP-based RSN mapping is more reliable than conventional taskbased fMRI and is extremely sensitive to sites identified by cortical stimulation, which currently is the standard in pre-surgical planning and intraoperative mapping. Translation of the science and techniques created at Washington University will be accomplished by a deep collaboration with Medtronic Corporation, the creator of the most widely used neuro- navigation system[s]. Towards this end, the overall objective of the proposed project is to create an imaging technology package that will integrate rsfMRI analysis with extant anatomical surgical stereotactic navigation. The Specific Goals of this proposal are to 1) Integrate the MLP analytic methodology into the Medtronic StealthStation Navigation System, 2) Ensure the software is stable and the output is reliable, 3) Optimize the user interface for clinical applications. The expected outcome of this translation strategy will be an integrated navigation technology using rsfMRI with clearly defined performance capabilities, well-delineated localization outputs, an intraoperatively efficient user experience, and a technical flexibility that can scale to different health care environments. Thus, this proposal is innovative because there currently does not exist any comparable system that integrates cutting edge image analysis tools with existing industry supplied clinical infrastructure. This work is significant because it will disseminate technology that fundamentally enhances the surgeon's understanding of the functional implications of their surgical strategy, thereby enabling safer and more tailored approaches to improving outcomes.

项目总结/摘要 通过向神经外科医生提供实时解剖信息，立体定向神经导航已被证明是可行的。 以提高肿瘤切除的范围，并因此提高存活率统计。也就是说， 在切除术期间，利用类似的神经导航显示，反映了功能组织的 个脑袋基于任务的功能磁共振成像已被用作术前定位功能的一种手段。但是，任务- 基于功能磁共振成像取决于病人的能力，以遵守任务范式，这往往是缺乏的。这 这个问题可以通过使用最近开发的静息态功能磁方法来克服。 共振成像（rsfMRI）定位功能。此外，rsfMRI是高效的，因为多个静息状态 可以同时映射与多个认知域相关联的RSN。考虑到这一点， 我们研究的长期目标是提高脑肿瘤手术切除后的生存率和生活质量 通过改进功能皮层的识别和保存。目前的障碍，防止 rsfMRI的广泛使用是目前创建和 解读图像。为了解决这个缺点，我们建议创建一个交钥匙系统的功能映射 在大脑中。在我们的方法的核心是一个多层感知器（MLP）算法，分配RSN 使用rsfMRI数据的监督分类来确定大脑内每个位点的成员资格。当前数据 证明了基于MLP的RSN映射比传统的基于任务的fMRI更可靠，并且 对皮质刺激识别的部位敏感，这是目前手术前计划的标准， 术中标测。在华盛顿大学创造的科学和技术的翻译将是 通过与美敦力公司的深入合作，美敦力公司是最广泛使用的神经系统的创造者， 导航系统[S]。为此，拟议项目的总体目标是建立一个成像系统， 技术包，将整合rsfMRI分析与现有的解剖外科立体定位导航。 本提案的具体目标是：1）将MLP分析方法集成到Medtronic中 StealthStation导航系统，2）确保软件稳定，输出可靠，3）优化 用于临床应用的用户界面。这一翻译战略的预期成果将是一个综合的 使用rsfMRI的导航技术，具有明确定义的性能能力， 输出，术中高效的用户体验，以及可扩展到不同健康状况的技术灵活性 护理环境。因此，这一建议是创新的，因为目前不存在任何可比的 该系统将尖端的图像分析工具与现有的行业提供的临床基础设施相集成。 这项工作意义重大，因为它将传播技术，从根本上提高外科医生的 了解其手术策略的功能影响，从而实现更安全和更定制的 改善结果的方法。