Forecasting brain injury in the virtual patient; a future extension for Doppler embolus detection?

A leading cause of stroke comes from emboli (particles and gas bubbles) that travel through the bloodstream to become lodged in the brain. Emboli can be non-invasively detected using Doppler ultrasound, but there is currently no model relating embolus properties to the severity and duration of brain injury. Here we examine some of the mechanisms underlying embolic stroke through computer simulation of embolisation in a 'virtual patient'. Our model predicts the severity of microvascular blockages by simulating fundamental interactions between emboli and the fractal arterial tree through which they travel.

In agreement with clinical observations, we find that cerebral injury can be caused either by large emboli or the steady accumulation of embolic debris. Feedback processes produce a sharp transition between free-flowing and severely obstructed arteries at specific combinations of embolus size and embolisation rate. Particles and gas bubbles were found to produce different patterns of brain injury; diffuse and transient for small emboli with short clearance times, and focal and persistent for large solid emboli. Arterial blockages were extremely sensitive to embolus size, indicating that pharmacological interventions, therapeutic ultrasound, and modifications of surgical procedure could all be useful in preventing brain injury during surgery.

Extension of Doppler embolus detection using computer simulations has potential to become a versatile tool for forecasting responses to embolisation during clinical monitoring. By combining our simulations with ultrasound embolus detection, we aim to create an advanced clinical aid for predicting the pattern and severity of arterial blockages in patients at risk of stroke.

Fig. 1: Forecasting brain injury in the ‘virtual patient’