Trendalyze and UCL get a C2N award to develop advanced analytic solutions for computer assisted surgery

By March 16, 2017Blog

MedCity @MedCityHQ is a collaboration between the Mayor of London and London’s three Academic Health Science Centres – Imperial College Academic Health Science Centre, King’s Health Partners, and UCL Partners. Launched in April 2014 to promote and grow the world-leading life sciences cluster of England’s greater south east, it is promoting life sciences investment, entrepreneurship and industry in the region.

Collaborate to Innovate @C2N_ERDF is an exciting MedCity project in the broad life sciences domain which launched in 2016, part-funded by the European Regional Development Fund. The project aims to promote knowledge transfer and commercialisation of innovations. C2N targets London based SMEs that have ambitions to embark on innovative projects in the applied research/clinical domain, or wish to bring new products and services to market.

Trendalyze and UCL have been successful in a C2N award to develop analytics solutions based on advanced data science and deep learning for computer assisted surgery.

Image-guided surgery (IGS) has the potential to enhance the localisation and navigation capabilities of the surgeon during Minimal Access Surgery (MAS). To address the significant challenge of deploying such a system in clinical practice it is important to understand its use in training scenarios with two key research goals:

  • To test the computing algorithms for IGS in a manageable training environment and understand the workflow needs and trend changes in motion patterns for robotic radical prostatectomy;
  • To understand how guidance information influences surgical performance and if it can potentially be used for developing advanced instrument-tissue motion modelling and skill evaluation.

This project will have potential for several potential exploitation opportunities in the IGS and broader computer assisted surgery (CAS) markets:

  • Added value to surgical robotics companies who can use the analytical platform and research to guide their system by Trendalyze;
  • Added value to medical device manufacturers by demonstrating skills changes with new devices in a new analytics product by Trendalyze, designed for bespoke analysis and deep learning on instrument motion data gathered from different sources (robots, optical trackers, sensors);
  • New products can come from IGS work (and the broader CAS) as well as from the time series analysis and deep learning that exploit the workflow information to highlight parameters automatically at the right point of care. Such new analytics products can accelerate clinical innovation time to market and improve quality.