An Integrated CT-based Image-Guided Neurosurgical System

基于 CT 的集成图像引导神经外科系统

• 批准号: 10017876
• 负责人: William Charles VanKampen
• 金额: $ 127.96万
• 依托单位: XORAN TECHNOLOGIES, LLC
• 依托单位国家: 美国
• 财政年份: 2005
• 资助国家: 美国
• 起止时间: 2005-05-01 至 2022-08-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10017876
• 关键词: 3-Dimensional; Address; Agreement; American; Anatomy; Animals; Area; Benefits and Risks; Brain; Brain Neoplasms; Brain imaging; Businesses; Caliber; Cancer Etiology; Canis familiaris; Capital; Central Nervous System Neoplasms; Cephalic; Cessation of life; Clinic; Clinical; Computed Tomography Scanners; Consensus; Consult; Consumption; Data; Devices; Diagnosis; Dose; Electromagnetics; Environment; Evaluation; Excision; Feedback; Fluoroscopy; Funding; Goals; Head; Image; Image-Guided Surgery; Institutional Review Boards; Investments; Licensing; Machine Learning; Malignant neoplasm of brain; Mediation; Medical; Medical Imaging; Metals; Metastatic Neoplasm to the Bone; Michigan; Minimally Invasive Surgical Procedures; Monitor; Navigation System; Neoplasm Metastasis; Neurosurgeon; Neurosurgical Procedures; Normal tissue morphology; Operative Surgical Procedures; Outcome; Pathologic; Patients; Pennsylvania; Phase; Physicians; Pituitary Neoplasms; Positioning Attribute; Procedures; Public Health; Radiation; Radiation Dose Unit; Resolution; Risk; Roentgen Rays; Safety; Scanning; Series; Small Business Innovation Research Grant; Speed; Spinal; Spine surgery; Structure; Surgeon; Survival Rate; System; Systems Development; Technology; Time; Tissues; United States National Institutes of Health; Universities; Update; Vertebral column; Veterinary Medicine; Veterinary Schools; Work; X-Ray Computed Tomography; base; cancer site; cancer surgery; commercial application; cost; cranium; deep neural network; human subject; image guided; image reconstruction; imaging capabilities; imaging modality; imaging system; improved; instrument; interest; meetings; minimally invasive; neurosurgery; next generation; operation; point of care; portability; real-time images; research clinical testing; soft tissue; spine bone structure; tool; tumor; validation studies

An Integrated CT-based Image-Guided Neurosurgical System In this SBIR Phase IIb proposal Xoran intends to commercialize a compact and affordable, yet highly- functional, system to provide real time image updates and navigation guidance in support of minimally invasive cranial and spinal neurosurgical procedures. The effort builds on previously developed compact and portable flat-panel Computed Tomography (CT) technology which has been commercialized for hard tissue applications, and incorporates work done in earlier phases of this project to generate viable high- quality images of the soft tissue structures in the brain. Intraoperatively obtained images tightly integrated into an onboard surgical navigation will provide updated instrument localization using next generation electromagnetic tool tip guidance. Workflow optimizations become possible when the imaging and guidance are one device, including fast local image updates, automatic image-to-world registration, as well as speed and simplicity of use. The project includes expansion of the system capabilities to facilitate precise minimally-invasive surgical removal of tumors in both the head and spine. It incorporates a machine-learning based deep neural network method for image finalization to allow high quality, low radiation image updates. The three-year project involves meeting technical milestones of system development including imaging capability, registration, navigation accuracy, speed, workflow, radiation dose considerations and cost. Clinical evaluations will take place at University of Michigan, and a team of consulting physicians has been assembled for oversight, input and feedback.

一种集成化的CT图像引导神经外科手术系统 在SBIR第IIb阶段的提案中，Xoran打算将一种紧凑、经济实惠、但高度- 功能，系统提供真实的时间图像更新和导航指导，以支持最低限度的 侵入性颅和脊髓神经外科手术。这项工作建立在以前制定的契约基础上， 和便携式平板计算机断层扫描（CT）技术，该技术已经商业化， 组织的应用，并结合在这个项目的早期阶段所做的工作，以产生可行的高， 大脑中软组织结构的高质量图像。 术中获得的图像紧密集成到机载手术导航中， 使用下一代电磁工具尖端引导更新了工具定位。工作流 当成像和引导是一个设备时，优化成为可能，包括快速本地 图像更新、自动图像与世界配准以及使用的速度和简单性。的 该项目包括扩展系统功能，以促进精确的微创手术 切除头部和脊柱的肿瘤它结合了基于机器学习的深度神经网络， 用于图像最终化的网络方法，以允许高质量、低辐射的图像更新。 这个为期三年的项目涉及满足系统开发的技术里程碑，包括成像 能力、配准、导航精度、速度、工作流程、辐射剂量考虑因素和成本。 临床评估将在密歇根大学进行，一个咨询医生小组已经 进行监督、投入和反馈。