NRI: Advanced Biophotonics for Image-guided Robotic Surgery

NRI：用于图像引导机器人手术的先进生物光子学

• 批准号: 8458644
• 负责人: Eric J Seibel
• 金额: $ 32.91万
• 依托单位: UNIVERSITY OF WASHINGTON
• 依托单位国家: 美国
• 财政年份: 2012
• 资助国家: 美国
• 起止时间: 2012-09-01 至 2016-08-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8458644
• 关键词: Ablation; Affect; Algorithms; Anatomy; Area; Biological; Biological Markers; Biological Models; Biophotonics; Brain; Brain Neoplasms; Cancerous; Complex; Computer software; Devices; Diagnostic Imaging; Dyes; Endoscopes; Engineering; Environment; Excision; Fiber; Fluorescence; Future; Goals; Health; Human; Image; Imaging Techniques; Laser Surgery; Lasers; Lead; Left; Life; Lighting; Location; Malignant Neoplasms; Marketing; Medical; Modeling; Monitor; Motion; Neurologic; Neurosurgeon; Noise; Operative Surgical Procedures; Patients; Performance; Procedures; Research; Research Project Grants; Resected; Residual Tumors; Resolution; Robot; Robotics; Safety; Scanning; Signal Transduction; Site; Spectrum Analysis; Stream; Surgeon; Surgical Instruments; System; Techniques; Technology; Testing; Therapeutic; Time; Tissues; Tumor Tissue; Visible Radiation; Vision; Work; arm; base; bioimaging; brain surgery; brain tissue; cancer imaging; cancer therapy; clinically relevant; cranium; fluorescence imaging; improved; minimally invasive; multidisciplinary; neoplastic; novel; operation; photonics; robot assistance; software systems; three-dimensional modeling; tool; tumor

DESCRIPTION (provided by applicant): Complete resection of tumor tissue remains one of the most important factors for survival in patients with cancer. Surgical removal is the most common front-line cancer therapy. Tumor resection in the brain is exceptionally difficult because leaving residual tumor tissue leads to decreased survival and removing normal healthy brain tissue leads to life-long neurological deficits. Brain surgery requires a very high degree of dexterity, accurate navigation, and niicro-precision cutting over long durations; thus it is an idel candidate for robotically assisted surgery. However, tumor resection is compounded by the need to make a small opening (keyhole) in the skull, and the difficulty of distinguishing normal from diseased tissue in an intraoperative setting. A minimally-invasive robotic system that allows surgeons to directly visualize and accurately discriminate neoplastic (cancer) from non-neoplastic tissue in a real-time intra-operative setting is currently not available, but an ideal gal for NRI. We propose to overcome two major limitations affecting robotically-assisted surgery in a team approach: inability to (1) automatically and (2) optically guide treatments in a miriimally-invasive intraoperative environment with advanced photonics and new cancer biomarkers. Dr. Hannaford will lead the integration of the RAVEN II open hardware and softvvare robotic system with laser-based endoscopic imaging. A single robot arm will hold a standard surgical tool for resecting/removing tumor, and a novel scanning fluorescence and reflectance imaging system to provide the advanced photonics in an ultra-small size. A team of three research neurosurgeons (Drs. Olson, Ellenbogen, Sekhar) will help develop clinically relevant phantoms and biological models of future image-guided brain surgery. PI, Dr. Seibel will provide a new multi-modal scanning fiber endoscope (mmSFE) technology that allows advanced laser imaging, diagnostic, and therapeutic biophotonics approaches to intra-operative keyhole surgery for improved performance and safety.

描述（由申请人提供）：肿瘤组织的完全切除仍然是癌症患者生存的最重要因素之一。手术切除是最常见的一线癌症治疗方法。大脑中的肿瘤切除术异常困难，因为留下残留的肿瘤组织会导致生存率下降，而去除正常的健康脑组织会导致终生神经功能缺陷。脑部手术需要非常高的灵活性、精确的导航以及长时间的微精密切割；因此它是机器人辅助手术的理想候选者。然而，由于需要在颅骨上开一个小开口（锁孔），并且在术中很难区分正常组织和患病组织，因此肿瘤切除变得更加复杂。目前还没有一种微创机器人系统可以让外科医生在实时术中环境中直接可视化并准确区分肿瘤（癌症）和非肿瘤组织，但它是 NRI 的理想选择。我们建议通过团队方法克服影响机器人辅助手术的两个主要限制：无法（1）自动和（2）在微创术中环境中利用先进的光子学和新的癌症生物标志物光学引导治疗。 Hannaford 博士将领导 RAVEN II 开放硬件和软件机器人系统与基于激光的内窥镜成像的集成。单个机械臂将容纳用于切除/切除肿瘤的标准手术工具，以及新颖的扫描荧光和反射成像系统，以提供超小尺寸的先进光子学。由三名研究神经外科医生（Olson、Ellenbogen、Sekhar 博士）组成的团队将帮助开发未来图像引导脑部手术的临床相关模型和生物模型。 PI Seibel 博士将提供一种新型多模态扫描光纤内窥镜 (mmSFE) 技术，该技术允许在术中锁孔手术中采用先进的激光成像、诊断和治疗生物光子学方法，从而提高性能和安全性。