RAEng Enterprise Fellowship for Hypervision Surgical

  • Wednesday, Jun 17, 2020

Dr Michael Ebner, CEO of Hypervision Surgical and Scientist at the Department of Surgical & Interventional Engineering at the School of Biomedical Engineering & Imaging Sciences, King’s College London, has been awarded a prestigious Enterprise Fellowship from the Royal Academy of Engineering (RAEng) to support the development of an intraoperative system for improved surgical guidance as part of the RAEng Enterprise Hub.

The Enterprise Fellowship is a prize awarded to support outstanding entrepreneurial engineering researchers, working at a UK University, to enable them to develop the skills to spin-out a business around their technological idea, and to act as role models to promote a culture of creativity, entrepreneurship and innovation in engineering.

With the support of the RAEng, Dr Ebner, Dr Tom Vercauteren, Professor of Interventional Image Computing at King’s and Medtronic / RAEng Research Chair in Machine Learning for Computer-Assisted Neurosurgery, Mr Jonathan Shapey, Clinical Senior Lecturer in Neurosurgery at King’s College Hospital, and Dr Sebastien Ourselin, Professor of Healthcare Engineering and Head of School, School of Biomedical Engineering & Imaging Sciences, King’s College London, have co-founded a university spin-out, Hypervision Surgical Ltd, to refine the prototype and develop the technology into a commercial device.

“With Hypervision Surgical, a King’s spin-out, we have the opportunity to fast track the application of our research in the real word and eventually commercialise a device that will equip clinicians with advanced computer-assisted tissue analysis that can provide real-time surgical guidance,” said Dr Ebner.

The goal is to develop a device that will provide surgeons with objective real-time information to increase precision during procedures, with the potential to improve outcomes for patients.

The AI-powered technology uses hyperspectral imaging, which splits light into multiple narrow spectral bands far beyond what the naked eye can see and provides information for safe and rich tissue differentiation without the need for contrast agents traditionally used in fluorescence-based imaging, the current standard procedure.

Our proposed hyperspectral imaging system provides an opportunity to improve upon the existing clinical standard and address several of its limitations with innovative system design and bespoke computer-assisted analysis.

Dr Michael Ebner, CEO of Hypervision Surgical, Scientist at King’s College London

The technology is also capable of capturing functional imaging information, such as blood oxygenation levels, which can be made readily available to the surgeon to help reduce the risk of injury during procedures.

The technology provides a promising opportunity to improve outcomes in neuro-oncology, where surgery is often the primary treatment for brain cancer.

Over 70,000 people are diagnosed with brain tumours in the UK each year with a particular burden on children and young adults. Brain tumours are the biggest cancer killer of children and young adults under 40 years which costs the UK economy an estimated £580M per year.

Hypervision Surgical will next seek to further develop and evaluate this technology to ensure its safety and performance in clinical studies to achieve commercial readiness.

This technology holds potential for multiple clinical applications and, in addition to neurosurgery, can assist the surgical team in a number of specialties including gastrointestinal and vascular surgery, to help reduce patient morbidity and healthcare costs.

Professor Tom Vercauteren, CSO of Hypervision Surgical, Professor of Interventional Image Computing at King’s College Hospital

Hypervision Surgical Ltd is the result of a wider research and team effort at King’s College London and King’s Health Partners. It is embedded within the King’s and St Thomas’ MedTech Hub, which seeks to translate research into health and economic impact and fosters cross-sector collaboration.

The story was initially published by King’s College London, School of Biomedical Engineering & Imaging Sciences, 2020 here.