Real-time Digital Twin Assisted Surgery
Lead Research Organisation:
University of Strathclyde
Department Name: Biomedical Engineering
Abstract
Surgery is a critical treatment delivered by NHS. Pre-COVID19 data (2004-2014) suggest a 27% increase in surgeries in England (>10 million operations performed). Despite >1.5 million cancelled or postponed surgeries in 2020 due to COVID19 (~33.6% reduction in England and Wales) and rocketed waiting lists for cancer surgery likely resulting in more deaths, tumour resection surgeries have recently resumed and remain high (e.g. ~51% of diagnoses received a kidney tumour resection in 2021). The total UK economic burden of surgery was ~£54.6 billion between 2009-2014 (£10.9 bn pa), amounting to 9.4% of the total NHS budget (£117 billion, 2013-2014). There is a clear clinical need for minimising surgical operations, healthcare costs, patient waiting lists, and associated patient complications.
To address this need, we aim to digitally transform future surgery, particularly for cancer, by creating a ground-breaking real-time digital twin assisted surgery (DTAS) technology. The patient is at the core of this technology, with significant and measurable benefits for their quality of life and healthcare. DTAS can be applied to several types of surgery (open, minimally invasive, or robotic surgery), for high precision tumour removal even in a partial organ resection. A parallel goal is to revolutionise surgical training, offering a new paradigm of patient-centred personalised surgical rehearsal. This project is timely and will be delivered by an internationally competitive, highly experienced multidisciplinary team, capable of delivering our vision. Our team covers several disciplines, including the lived experience from patients; health technologies; bioengineering; digital twin (DT) technology; artificial intelligence (AI); mathematical science; numerical simulation.
To address this need, we aim to digitally transform future surgery, particularly for cancer, by creating a ground-breaking real-time digital twin assisted surgery (DTAS) technology. The patient is at the core of this technology, with significant and measurable benefits for their quality of life and healthcare. DTAS can be applied to several types of surgery (open, minimally invasive, or robotic surgery), for high precision tumour removal even in a partial organ resection. A parallel goal is to revolutionise surgical training, offering a new paradigm of patient-centred personalised surgical rehearsal. This project is timely and will be delivered by an internationally competitive, highly experienced multidisciplinary team, capable of delivering our vision. Our team covers several disciplines, including the lived experience from patients; health technologies; bioengineering; digital twin (DT) technology; artificial intelligence (AI); mathematical science; numerical simulation.
Organisations
- University of Strathclyde (Lead Research Organisation)
- Medical Research Council (Co-funder)
- Kidney Cancer UK (Project Partner)
- National Manufacturing Institute Scotland (Project Partner)
- Organlike Ltd (Project Partner)
- NHS Golden Jubilee (Project Partner)
- Olympus Surgical Technologies Europe (Project Partner)
- Prometheus Regeneration Holdings Ltd (Project Partner)
Publications
Asciak L
(2025)
Digital twin assisted surgery, concept, opportunities, and challenges
in npj Digital Medicine
Black S
(2023)
Calibration of patient-specific boundary conditions for coupled CFD models of the aorta derived from 4D Flow-MRI
in Frontiers in Bioengineering and Biotechnology
Black SM
(2023)
Reconstruction and Validation of Arterial Geometries for Computational Fluid Dynamics Using Multiple Temporal Frames of 4D Flow-MRI Magnitude Images.
in Cardiovascular engineering and technology
Cowley J
(2024)
Near Real-Time Estimation of Blood Loss and Flow-Pressure Redistribution during Unilateral Nephrectomy
in Fluids
Cowley J
(2023)
A Mathematical Model of Blood Loss during Renal Resection
in Fluids
Denton O
(2024)
Understanding the Role of Biofilms in Acute Recurrent Tonsillitis through 3D Bioprinting of a Novel Gelatin-PEGDA Hydrogel.
in Bioengineering (Basel, Switzerland)
Holland I
(2023)
Stratified tissue biofabrication by rotational internal flow layer engineering
in Biofabrication
Murphy JF
(2024)
Biofabrication and biomanufacturing in Ireland and the UK.
in Bio-design and manufacturing
Shen A
(2024)
Dynamic healing-assembly for biocompatible, biodegradable, stretchable and self-healing triboelectric nanogenerators
in Chemical Engineering Journal
