Self-guided Microrobotics for Automated Brain Dissection

Neural precursor cells (NPCs) are neural stem cells and their progeny, which are multipotent, self-renewing cells that are responsible for building the fundamental components of the vertebrate central nervous system during embryonic development. Notably, NPCs persist into the mature brain as very rare cells that continue to generate new neurons throughout the lifetime of the organism. Intensive study of these precious cells could lead to a watershed moment in the field of neurobiology and the development of regenerative therapies to treat Alzheimer's disease, dementia, and traumatic brain injury. However, our ability to harness the therapeutic potential of NPCs is limited by the practical difficulty of identifying and collecting them for analysis. Current methods require painstaking manual microdissection of neural tissue followed by cell sorting methods which, in addition to requiring large samples sizes (and thus large quantities of tissue) also often fail to distinguish between NPCs and other cells expressing the same biomarkers.

This highly interdisciplinary project brings together researchers with expertise in artificial intelligence (AI), robotics, engineering and neuroscience to create a new automated microsurgical platform which will be applied to identify and collect NPCs from brain tissues. By exploiting the capacity of deep learning approaches to detect features in complex data sets we will develop two new image-guided microsurgery tools: a microrobotic resector capable of carefully excising the small region of brain tissue (the SVZ) within which NPCs are found and microrobotic cell collector, capable of efficiently harvesting individual cells for further study and analysis using a coordinated array of optoelectronic microrobots. When then aim to integrate these two systems into a single, unique robotic microsurgery platform.

The new system will be applied to collect and analyse NPCs from different brain tissues. In particular, we propose to analyse the sex-dependent differences in NPCs phenotypes, which have been reported in previous research. As well as transforming our capacity for collection of NPCs and likewise supporting the development of new regenerative therapies, we believe this approach will provide a powerful new method for a wide range of microsurgery applications. Altogether, we will use these results to simulate debate among the related engineering, scientific and wider public communities to shape a new international multi-disciplinary network focusing on challenges with regenerative medicine i.e. providing new case studies for govt. policy and further investment for AI-driven healthcare applications.

This project addresses the need for improved microsurgical tools in neurobiology through development of a new autonomous micro-robotic concept powered by Artificial Intelligence (AI). The work brings together a diverse range of world leading research expertise across both Canadian and UK institutions in nerobiology, computer science, robotics and engineering. Given the broad range of connected sciences that also include, optics, machine vision, neuroscience, healthcare engineering etc. we expect the results generated to have a wide reach. Importantly, UCL is well placed to support these activities by providing access to aligned investments to facilitate clinical applications and translation through our flagship Wellcome / EPSRC Centre in Interventional and Surgical Sciences (WEISS) and its links to institutionally backed units like the Translational Research Office, the NIHR UCLH BRC Joint Research Office and the UCL Institute for Healthcare Engineering. As such, we believe this consortium has the potential for significant impact opportunities for novel technical development and knowledge exchange that aims to change healthcare communities to adopt new ways of working.

Examples of planned activities for industrial, academic and societal impact include:

- Publication of peer-reviewed journal articles describing the techniques and results from the project, presentations at major scientific conferences (such as FoM, MICCAI and ICRA) and dissemination of results more widely to the life science research and clinical healthcare research community at national meetings.

- UK-Canada community building workshop: We will host a workshop in Canada to demonstrate the application of new automated microscopy and microsurgery techniques, involving a range of stakeholders from academics, industry and clinicians to discuss the implications for AI and automation technologies cell and neurobiology and regenerative medicine. Specifically this will lead to generation of case studies and policy work to help align and grow a common roadmap for the community.

- Supported by experienced communication officers, we will develop thought provoking images and movies. Acting as a tool to inspire the next generation of researchers and engage the wider public in scientific research, we anticipate that the new AI-driven imaging capability developed under this project will generate extremely rich media content and world-wide visibility of multidisciplinary Canada-UK research. We plan to exploit existing relationships with media outlets including the BBC, The Guardian and Wired Magazine to raise wider awareness of the research.

- In all teaching, we engage students with our latest cutting edge research which both enhances the learning experience, aids dissemination of our ideas and long-term research agenda ensuring impact. We intend to offer student research projects associated with microscopy, AI-driven automation and computer vision, bioimage analysis and biology to students enrolled in UCL CDTs focusing on AI-fundamentals and applied challenges

- Following on from previous events, outputs of the project will contribute to a yearly demonstrator showcase as part of UCL Robotics Week to promote wider engagement end-user stakeholders within the life sciences, AI and Robotics. Other planned events include Science Rendezvous events

- The project will establish a clear exploitation plan at the start of the project. This includes guidance from expertise from UCLB, UoT and assoicated industry advisory boards to ensure we achieve maximum impact from the generated results.