30 October 2020 3.00pm-5.00pm - MS Teams

Joseph Hardwicke, Dr. Jerome Charmet and Professor Shervanthi Homer-Vanniasinkam invite you to the 11th Clinical Challenges Forum. These quarterly meetings bring clinicians and scientist together around clinical challenges requiring interdisciplinary interventions/research.

• Cross-specialty research
• Pre-clinical and clinical studies
• Quick-fire research updates
• Colleagues from UoW, WMS, UHCW and beyond

Please sign up to this event if you are interested.

Multiscale, flow rate independent liquid biopsy

Dr Jerome Charmet - WMG, University of Warwick

Immunoaffinity based liquid biopsies typically suffer from low throughput, relative complexity and limitations for post-processing the captured cells. Here we address these issues simultaneously by decoupling and independently optimising the nano-, micro- and macro- length scales of our device. The integration of a nanofunctionalised microscale mesh into a macroscale channel, whose diameters can be scaled, enables high capture efficiency maintained constant at any flow rate. Using nanobranched polymer functionalised with antibodies against specific cell surface proteins, we demonstrate capture efficiency above 80% at flow rates up to ~12mL/h, which is up to an order of magnitude higher than typically used in affinity-based microfluidic devices. We also demonstrate the isolation of CTC in 4 ml blood samples from 72 cancer patients (n=72, 100%). Furthermore, our simple design enables easy post-processing of the cells. To demonstrate this, we evaluate the expression of PD-L1 in CTC from 36 patients undergoing therapy, using immunofluorescence double-labelling technology. Our multiscale approach, which overcomes major limitations in affinity-based liquid biopsies, could provide a simple alternative to facilitate cancer management. 

Modelling Brain Injury Severity in a Traumatic Fall

Dr Christophe Bastien and Dr Huw Davies - Coventry University, Institute for Future Transport and Cities

Professor Clive Neal-Sturgess - University of Birmingham

In the real world, the severity of traumatic injuries are measured using the Abbreviated Injury Scale (AIS). However, the AIS scale cannot currently be computed by using the output from finite element human computer models, which currently rely on maximum principal strains (MPS) to capture serious and fatal injuries. In order to overcome these limitations, a unique Organ Trauma Model (OTM) able to calculate the threat to life of a brain model at all AIS levels is introduced. The OTM uses a power method, named Peak Virtual Power (PVP), and defines brain white and grey matter trauma responses as a function of impact location and impact speed. This research has considered ageing in the injury severity computation by including soft tissue material degradation, as well as brain volume changes due to ageing. Further, to account for the limitations of the Lagrangian formulation of the brain model in representing hemorrhage, an approach to include the effects of subdural hematoma is proposed and included as part of the OTM predictions in this study. The OTM model was tested against two real-life falls and has proven to correctly predict the Postmortem (PM) outcomes. Pending more testing, the OTM could support forensic studies.

Computer simulation of lower limb pedestrian injuries

Dr Thomas Cloake - University Hospitals Coventry and Warwickshire

Open fractures of the tibia are the most common open long bone fractures, frequently occurring in young adults as a result of road traffic accidents or falls from a great height. The management of these injuries is challenging and often results in multiple, complex surgeries with a long postoperative rehabilitation period. Classification systems exist for open fractures to aid clinicians in decision making and counselling of patients however these are often limited by inter-observer variability and are inaccurate predictors of outcome. Advances in computational engineering have led to the development of models that aim to accurately predict both injury patterns based on accident data. The Organ Trauma Model (OTM) has been shown to be an accurate predictor of head injury patterns as well as outcome following pedestrian versus car accidents and has the potential to be used to model extremity trauma. This project explores the application of computer simulation to open fractures of the lower limb with the aim to create a predictive model that aids classification and informs management decisions about these devastating injuries.