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）：肿瘤组织的完整切除仍然是癌症患者生存的最重要因素之一。手术清除是最常见的前线癌症治疗。大脑中的肿瘤切除非常困难，因为留下残留的肿瘤组织会导致生存降低并去除正常的健康脑组织会导致终身神经缺陷。脑部手术需要很高的敏捷性，准确的导航和长时间的尼克罗过度切割。因此，它是机器人辅助手术的IDEL候选人。然而，肿瘤切除是由于需要在颅骨中进行较小的开口（钥匙孔）的需要，以及在术中环境中将正常与患病组织区分开的困难。当前尚无实时术中环境中的非侵入性机器人系统，允许外科医生直接可视化并准确地将肿瘤（癌）与非肿瘤组织区分开，但目前尚不可用，但对于NRI来说是理想的GAL。我们建议在团队方法中克服影响机器人辅助手术的两个主要局限性：无法（1）自动自动以及（2）在具有晚期光子学和新癌症生物标志物的术中环境中光学指导治疗。 Hannaford博士将领导Raven II开放硬件和SoftVare机器人系统与基于激光的内窥镜成像的整合。单个机器人臂将拥有一个标准的外科手术工具，用于切除/去除肿瘤，并具有新颖的扫描荧光和反射成像系统，以提供超小尺寸的高级光子学。由三个研究神经外科医生组成的团队（Olson博士，Ellenbogen，Sekhar）将有助于开发与未来图像引导的脑外科手术的临床相关幻影和生物学模型。 PI，Seibel博士将提供一种新的多模式扫描纤维内窥镜（MMSFE）技术，该技术允许高级激光成像，诊断和治疗性生物探测方法，用于术中钥匙孔手术，以改善性能和安全性。