Development of New, Robust, Approaches for Continuous Monitoring of Vascular and Brain Tissue Physical Properties in Traumatic Brain Injury Patients

Summary

Dynamic, pathological, biochemical processes triggered by a severe traumatic brain injury lead to brain swelling, often with devastating, persistent consequences to the brain tissue, frequently culminating in the patient’s death. Various physical properties of the brain vasculature and cerebral tissue controlling the cerebral blood flow naturally reflect those processes but they are impossible to monitor directly using currently available technology.

Instead, one must rely on surrogate measurements, like pressures and flows in the brain, and analysis of patterns carried by the temporal changes in those measurements at various time scales. Many metrics have been proposed, with some more successful then others, each of them carrying certain assumptions and gross simplifications.

Project aims

The purpose of this project is to use mathematical (system) modelling as well as statistical learning approaches to build on previous discoveries but ultimately aiming to provide a simplified, robust, and readily interpretable set of complemental metrics reflecting the physical properties of the cerebral vasculature along with the accuracy indicators.

The project will take advantage of a large number (1300+) of data sets (at full, waveform level, temporal resolution) collected by the group from the neuro ICU in Cambridge over the last decades. The new metrics will be ultimately implemented for real time use at the bedside using tools included in the brain monitoring software written by the group ICM+ (https://icmplus.neurosurg.cam.ac.uk), and by extending its battery via Python plugins. Appropriate visualisation methods for presentation of those metrics to the clinician at the bed-side will also be developed.

Contact details

Dr Peter Smielewski - ps10011@cam.ac.uk

Opportunities

This project is open to applicants who want to do a:

• PhD
• MPhil

This project would suit graduates in Biomedical Engineering, Physics, Mathematics, Signal Processing, Electrical Engineering, and Computer Science.