Robot-Assisted Ocular Surgery

机器人辅助眼科手术

• 批准号: 2784667
• 金额: --
• 依托单位: University College London
• 依托单位国家: 英国
• 项目类别: Studentship
• 财政年份: 2023
• 资助国家: 英国
• 起止时间: 2023 至 无数据
• 项目状态: 未结题
• 来源: https://gtr.ukri.org/projects?ref=studentship-2784667
• 关键词: Robot; Assisted; Ocular; Surgery

1) Brief description of the context of the research including potential impactSubretinal injections have gained popularity in recent years in a context of retinal gene therapy for conditions like inherited retinal dystrophies, age-related degenerations, and other retinopathies. Subretinal injections are deemed one of the most difficult clinical procedures to perform correctly. The reason for that is the drug needs to be delivered exactly to subretinal space which is only a few microns deep. Given the nature of the targeted space, innate tremor of human hands, difference in skill level across the medical professionals, duration of the injection in a stable position, and potential side effect of incorrect delivery site, robotic surgery can offer stabilisation of the system and precise measurement of both the delivery site and delivery volume based on imaging technology currently used in theatres. Creating a precise robotic system for the injections and would accommodate for human error and greatly improve safety and quality of post-operative patients. Additional applications for this technology would include cannulation of retinal vessels in vision robbing diseases such as vein occlusion. 2) Aims and ObjectivesThe aim of this project is to construct and test an autonomous subretinal injection and cannulation system. This would be done by integrating patient data collected from the Royal Free Hospital, medical imaging and image processing systems developed at Institute of Ophthalmology, Deep Neural Network (DNN) development and training for AI which will be a basis for the robot operations, and construction and redesign of the robot model constructed in the UCL WEISS lab.The development would be divided into the following objectives:a) Development of the AI algorithm for precise calculation of volume and position of surgical instruments and injected drugs (blebs) for use in VR surgery; b) Testing the working prototype of the surgical robot made by UCL WEISS lab on artificial eye modelsc) Developing a working prototype for testing on inanimate eye models for precise delivery of drugs calculated by algorithms developed in the previous stepd) Ethical approval for animal testing 3) Novelty of Research MethodologyThe research will integrate newly tested and developed technology and create new solutions for the problems which will arise along the way. The research will aim at creating a novel tracking system for surgical instruments based on intraoperative Optical Coherence Tomography (iOCT). The DNN development will automate tracking for focusing the iOCT in real-time, complement a surgical binocular augmented reality (AR) system for comfortable working environment with visualisation of the iOCT on top of the surgical field. 4) Alignment to EPSRC's strategies and research areasThis project is aligned with UKRI Healthcare Technology area of interest. We aim to develop a novel system that will be adaptable and compatible with already existing surgical and imaging technologies with no need to replace existing systems, but rather as a complimentary tool that will assure safety and success of delicate surgical interventions.5) Any companies or collaborators involvedThe research group ARISE is part of the UCL WEISS lab. Data collected from Royal Free NHS Trust will be used in the study. The ARISE team aims to apply for research grants from both BMA UK and Roche Holding AG.

1)研究背景的简要描述，包括潜在的影响视网膜下注射近年来在视网膜基因治疗的背景下越来越受欢迎，如遗传性视网膜营养不良，年龄相关性变性和其他视网膜病变。视网膜下注射被认为是最难正确执行的临床程序之一。原因是药物需要精确地输送到视网膜下空间，只有几微米深。考虑到目标空间的性质、人手的先天震颤、医疗专业人员的技能水平差异、稳定位置注射的持续时间以及不正确输送部位的潜在副作用，机器人手术可以提供系统的稳定性以及基于目前在手术室中使用的成像技术的输送部位和输送体积的精确测量。为注射创建精确的机器人系统，将适应人为错误，并大大提高术后患者的安全性和质量。该技术的其他应用将包括视网膜血管插管，用于视觉障碍疾病，如静脉阻塞。2)目的和目标本项目的目的是构建和测试一个自主的视网膜下注射和插管系统。这将通过整合从皇家自由医院收集的患者数据，眼科研究所开发的医学成像和图像处理系统，深度神经网络（DNN）开发和人工智能训练（这将是机器人操作的基础），以及在UCL韦斯实验室构建的机器人模型的构建和重新设计来完成。开发将分为以下目标：a）开发AI算法，用于精确计算VR手术中使用的手术器械和注射药物（水泡）的体积和位置; B）在义眼模型上测试UCL韦斯实验室制造的手术机器人的工作原型c）开发一个工作原型，用于在无生命的眼睛模型上进行测试，以通过上一步骤中开发的算法计算药物的精确递送d）动物测试的伦理批准3）研究方法的新奇研究将整合新测试和开发的技术，并为沿着出现的问题创造新的解决方案。该研究旨在创建一种基于术中光学相干断层扫描（iOCT）的新型手术器械跟踪系统。DNN的开发将自动跟踪，以实时聚焦iOCT，补充手术双目增强现实（AR）系统，以实现舒适的工作环境，并在手术野顶部可视化iOCT。4)与EPSRC的战略和研究领域保持一致该项目与UKRI感兴趣的医疗技术领域保持一致。我们的目标是开发一种新的系统，它将适应和兼容现有的手术和成像技术，不需要更换现有的系统，而是作为一种补充工具，将确保安全和成功的微妙的手术干预。5）任何公司或合作者参与研究小组ARISE是伦敦大学学院韦斯实验室的一部分。本研究将使用从皇家免费NHS信托收集的数据。ARISE团队的目标是申请英国BMA和罗氏控股公司的研究赠款。