Robot-Assisted Ocular Surgery

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.

The critical mass of scientists and engineers that i4health will produce will ensure the UK's continued standing as a world-leader in medical imaging and healthcare technology research. In addition to continued academic excellence, they will further support a future culture of industry and entrepreneurship in healthcare technologies driven by highly trained engineers with deep understanding of the key factors involved in delivering effective translatable and marketable technology. They will achieve this through high quality engineering and imaging science, a broad view of other relevant technological areas, the ability to pinpoint clinical gaps and needs, consideration of clinical user requirements, and patient considerations. Our graduates will provide the drive, determination and enthusiasm to build future UK industry in this vital area via start-ups and spin-outs adding to the burgeoning community of healthcare-related SMEs in London and the rest of the UK. The training in entrepreneurship, coupled with the vibrant environment we are developing for this topic via unique linkage of Engineering and Medicine at UCL, is specifically designed to foster such outcomes. These same innovative leaders will bolster the UK's presence in medical multinationals - pharmaceutical companies, scanner manufacturers, etc. - and ensure the UK's competitiveness as a location for future R&D and medical engineering. They will also provide an invaluable source of expertise for the future NHS and other healthcare-delivery services enabling rapid translation and uptake of the latest imaging and healthcare technologies at the clinical front line. The ultimate impact will be on people and patients, both in the UK and internationally, who will benefit from the increased knowledge of health and disease, as well as better treatment and healthcare management provided by the future technologies our trainees will produce.

In addition to impact in healthcare research, development, and capability, the CDT will have major impact on the students we will attract and train. We will provide our talented cohorts of students with the skills required to lead academic research in this area, to lead industrial development and to make a significant impact as advocates of the science and engineering of their discipline. The i4health CDT's combination of the highest academic standards of research with excellent in-depth training in core skills will mean that our cohorts of students will be in great demand placing them in a powerful position to sculpt their own careers, have major impact within our discipline, while influencing the international mindset and direction. Strong evidence demonstrates this in our existing cohorts of students through high levels of conference podium talks in the most prestigious venues in our field, conference prizes, high impact publications in both engineering, clinical, and general science journals, as well as post-PhD fellowships and career progression. The content and training innovations we propose in i4health will ensure this continues and expands over the next decade.