Dr Wahbi El-Bouri from the Department of Cardiovascular and Metabolic Medicine, Institute of Life Course and Medical Sciences has recently been awarded a Royal Society Research Grant to investigate the use of computational models for differential diagnosis.
The project (Detecting Intracranial Pressure Changes with Transcranial Doppler: In silico models towards differential diagnosis) will combine the use of transcranial doppler to measure blood flow in the brain, along with in silico (or computational) models of the fluid dynamics in the brain to detect intracranial pressure changes non-invasively.
Dr El-Bouri is head of the Virtual Vascular Human group within the Liverpool Centre for Cardiovascular Science. His research involves the development of in silico models of the cardiovascular system in health and disease with the aim of translating these models into the clinic to improve patient outcomes.
He previously worked on developing computational models of blood flow in the brain for the purpose of stroke simulation at University of Oxford (2013 – 2020) as well as on non-invasive intracranial pressure measurement with traumatic head injuries at Southampton General Hospital (2017 – 2018).
The models his group develops are also used to simulate interventions, whether through devices or drugs, with the eventual aim of running in silico clinical trials.
“Digital twins of humans can improve differential diagnosis in conditions where the cause is not clear. Similar to how we are able to predict the weather using a combination of measurements and computational modelling, this project seeks to predict an individual’s health through a combination of measurements and computational modelling.
The cause of raised intracranial pressure (ICP) is often not clear with differential diagnosis difficult due to the complex regulatory mechanisms that keep the brain healthy. ‘Digital twins’ of the cerebrovasculature and intracranial space, along with measurements of cerebral blood flow and blood pressure, provide an ideal environment in which to simulate different disease mechanisms that then allow us to make a probabilistic judgement on what is the likely cause of raised ICP. This will provide a differential diagnosis on likely mechanistic pathology, and eventually aid clinicians in diagnosis and treatment of raised ICP.”