Imaging, Guidance, and QA for Emerging High-Precision Neurosurgical Techniques

新兴高精度神经外科技术的成像、指导和质量保证

• 批准号: 10015355
• 负责人: JEFFREY H SIEWERDSEN
• 金额: $ 67.44万
• 依托单位: JOHNS HOPKINS UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2019
• 资助国家: 美国
• 起止时间: 2019-09-15 至 2024-07-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10015355
• 关键词: 3-Dimensional; Acceleration; Affect; Alzheimer' s Disease; Amygdaloid structure; Anatomy; Brain; Cadaver; Cell Nucleus; Cerebrospinal Fluid; Clinical Research; Complication; Data; Deep Brain Stimulation; Dementia; Development; Diagnostic radiologic examination; Dose; Electrodes; Endoscopy; Future; Generations; Gilles de la Tourette syndrome; Hippocampus (Brain); Hypothalamic structure; Image; Image-Guided Surgery; Individual; Intracranial Hemorrhages; Magnetic Resonance Imaging; Mental Depression; Metals; Methods; Modality; Modeling; Morphologic artifacts; Motion; Movement Disorders; Neurologic; Neuronavigation; Obesity; Operative Surgical Procedures; Parkinson Disease; Patients; Performance; Quantitative Evaluations; Research; Resolution; Robotics; Spinal; Structure; Surface; System; Systems Integration; Techniques; Technology; Thalamic Nuclei; Three-Dimensional Image; Time; Transcend; Translating; Translations; Uncertainty; Ventricular; Visualization; Work; autism spectrum disorder; base; bone; brain parenchyma; clinical translation; cone-beam computed tomography; deep brain stimulator; design; image guided; image reconstruction; image registration; imaging system; improved; industry partner; interest; multimodality; neurophysiology; neurosurgery; next generation; novel; novel therapeutics; prototype; reconstruction; research clinical testing; robot assistance; safety outcomes; simulation; skull base; soft tissue; success

PROJECT SUMMARY / ABSTRACT Emerging neurosurgical techniques offer potential breakthroughs in treatment of a growing spectrum of movement disorders and dementia (including Alzheimer’s disease, Tourette’s syndrome, autism, depression, and even obesity). These emerging surgical approaches extend the established success of deep-brain stimulation (DBS) in Parkinson’s disease by using novel electrode stimulators delivered trans-ventricularly to targets about the hypothalamus. While endoscopic approach provides reliable access to the ventricles, such access imparts a loss of cerebrospinal fluid (CSF) and brain shift up to ~10 mm in the very regions of interest for these novel DBS therapies. Therefore, realizing the benefit of such promising techniques requires advances beyond the state of the art in neuro-navigation. Moreover, the use of novel, directional electrodes in such techniques requires a means to guide and confirm stimulator placement. Especially in the early stages of development of such novel therapies, it is important to resolve uncertainties related to geometric precision in order to differentiate from underlying neurophysiology and other factors that may affect safety and outcome. We propose to develop and evaluate the following advances in intraoperative imaging, registration, and guidance to realize a platform for robot-assisted ventriculoscopic approach to deep-brain targets in a manner that overcomes conventional limitations of neuro-navigation and supports the emerging generation of novel DBS therapies: (Aim 1) Develop high-quality intraoperative cone-beam CT (CBCT) using 3D image reconstruction methods that propel image quality beyond conventional limits of CBCT, providing image quality sufficient to drive deformable registration with preop MRI, precisely localize stimulator placement, and provide a check against complication / intracranial hemorrhage. (Aim 2) Develop 3D-2D image registration methods to relate low-dose intraoperative radiographs with: (a) preop MRI for automatic patient registration; and (b) parametric models of DBS electrodes (including novel directional stimulators) for guidance and confirmation of stimulator placement with precision and accuracy beyond that of conventional tracking. (Aim 3) Develop multi-modality deformable image registration (MR-CBCT) to resolve alignment between preop MRI and intraoperative CBCT – particularly peri-ventricular deep-brain deformation following CSF egress – using a fast, modality- insensitive, diffeomorphic Demons method for accurate transformation of MRI / planning data to CBCT and endoscopy. (Aim 4) Develop endoscopic video registration to render 3D image and planning information directly in the endoscopic scene, providing accurate visualization of target and critical structures during ventriculoscopic approach. (Aim 5) Translate the methods from Aims 1-4 to clinical studies for quantitative evaluation of performance under realistic conditions, and combine within an integrated system for robot-assisted ventriculoscopy (RAV) approach to DBS targets. The proposal advances previous work in skull base and spinal neurosurgery, offering a high likelihood of success in enabling next-generation DBS, and creates an integrated system for image-guided surgical robotics beyond the state of the art – a valuable testbed for development and translation of clinical systems under future academic-industry partnership.

项目总结/摘要 新兴的神经外科技术为治疗不断增长的运动范围提供了潜在的突破 疾病和痴呆症（包括阿尔茨海默氏病，图雷特综合征，自闭症，抑郁症，甚至肥胖症）。这些 新兴的手术方法通过以下方式扩展了脑深部电刺激（DBS）在帕金森病中的既定成功： 使用新颖的电极刺激器经心室传递到下丘脑周围的目标。虽然内窥镜 入路提供了进入脑室的可靠通路，这种通路导致脑脊液（CSF）丢失和脑移位 对于这些新型DBS治疗，在感兴趣的区域中最多可达~10 mm。因此，实现这样的利益， 有前途的技术需要超越神经导航领域的现有技术的进步。此外，使用小说， 这种技术中的定向电极需要一种引导和确认刺激器放置的装置。特别是在 在这种新疗法开发的早期阶段，解决与几何精度相关的不确定性是很重要的 以便与潜在的神经生理学和其他可能影响安全性和结果的因素区分开来。 我们建议开发和评估以下术中成像、配准和引导方面的进展， 实现机器人辅助脑室镜方法的平台，以克服 神经导航的传统局限性，并支持新一代的新型DBS疗法： (Aim 1）开发高质量的术中锥形束CT（CBCT），使用3D图像重建方法， 图像质量超出CBCT的常规限制，提供足以驱动变形配准的图像质量， 术前MRI，精确定位刺激器放置，并检查并发症/颅内出血。 (Aim 2）开发3D-2D图像配准方法，以将低剂量术中X线照片与以下内容相关联：（a）术前MRI， 自动患者配准;以及（B）DBS电极（包括新型定向刺激器）的参数模型， 以超出常规跟踪的精确度和准确度指导和确认刺激器放置。 (Aim 3）开发多模态可变形图像配准（MR-CBCT），以解决术前MRI和 术中CBCT -特别是脑脊液排出后脑室周围深部脑变形-使用快速模式- 用于将MRI /计划数据准确转换为CBCT和内窥镜检查的不敏感、同构Demons方法。 (Aim 4）开发内窥镜视频配准，以直接在内窥镜中呈现3D图像和规划信息 场景，在脑室镜手术过程中提供目标和关键结构的准确可视化。 (Aim 5）将目标1-4的方法转化为临床研究，以便在现实条件下定量评价性能。 条件下，并结合联合收割机内的集成系统的机器人辅助脑室镜检查（RAV）的方法DBS的目标。 该提案推进了以前在颅底和脊髓神经外科的工作，提供了成功的可能性很高， 下一代DBS，并创建了一个超越最先进水平的图像引导手术机器人集成系统- 在未来的学术界和工业界的合作下，临床系统的开发和翻译的一个有价值的试验平台。