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| Funder | Engineering and Physical Sciences Research Council |
|---|---|
| Recipient Organization | University College London |
| Country | United Kingdom |
| Start Date | Jan 01, 2023 |
| End Date | Jan 31, 2026 |
| Duration | 1,126 days |
| Number of Grantees | 2 |
| Roles | Student; Supervisor |
| Data Source | UKRI Gateway to Research |
| Grant ID | 2784667 |
1) Brief description of the context of the research including potential impact
Subretinal 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 Objectives The 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 models
c) Developing a working prototype for testing on inanimate eye models for precise delivery of drugs calculated by algorithms developed in the previous step d) Ethical approval for animal testing 3) Novelty of Research Methodology
The 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 areas
This 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 involved
The 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.
University College London
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