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）对研究的背景的简要描述包括潜在的贝型注射量，近年来，在视网膜基因治疗的背景下，遗传性视网膜营养不良，与年龄相关的退化和其他视网膜病变等疾病。视网膜下注射是正确执行的最困难的临床程序之一。原因是该药物需要精确地输送到视网膜下空间，而后空间只有几微米深。鉴于有针对性的空间的性质，人类手的先天震颤，在医疗专业人员的技能水平上的差异，在稳定位置处注射的持续时间以及不正确的递送现场的潜在副作用，机器人手术可以稳定系统，并基于目前在TheAters中使用的成像技术的交付现场和交付现场的精确度量。为注射创建精确的机器人系统，并将适应人为错误，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在视觉抢劫疾病（例如静脉闭塞）中插管视网膜船。 2）该项目的目的和目标是构建和测试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，医学成像和图像处理系统中收集的患者数据，在眼科研究所开发的，深度神经网络（DNN）的AI开发和培训，这将是机器人操作的基础，以及在UCL Weiss Lab中构建的机器人模型的构建和重新设计的ucl Weiss Lab。用于VR手术的手术仪器和注射药物（BLEB）； b）测试由UCL Weiss Lab在人造眼模型上制作的手术机器人的工作原型）开发一个工作原型，用于测试无生命的眼模模型，以精确输送由上一个Stepd中开发的算法计算出的药物计算的药物）伦理学批准）用于动物测试的动物测试3）研究方法将融合了新的技术，并将新的技术融为一体，以融合新的技术，以解决新的解决方案。该研究将旨在建立基于术中光学相干断层扫描（IOCT）的外科手术仪器的新型跟踪系统。 DNN开发将自动化跟踪，以实时聚焦IOCT，并补充外科双目增强现实（AR）系统，以舒适的工作环境，并在外科手术领域的顶部可视化IOCT。 4）与EPSRC的策略和研究领域保持一致，该项目与乌克里医疗保健技术领域一致。我们的目标是开发一种新型系统，该系统将与已经存在的手术和成像技术兼容，而无需替代现有系统，而是作为一种免费的工具，可以确保精致外科手术干预的安全性和成功。从皇家免费NHS信托收集的数据将用于研究。 ARISE团队旨在申请BMA UK和Roche Holding AG的研究赠款。