European training network for developing smart neuromonitoring solutions to support precision medicine in acute central nervous injury
Lead Research Organisation:
St George's, University of London
Department Name: Molecular & Clinical Sci Research Inst
Abstract
In traumatic brain/spinal cord injury and stroke - major causes of death and disability -, progress has come from monitored intensive care and swift action upon detection of secondary insults. Although it is possible to monitor intracranial pressure, the brain & spinal cord still behave as a black box. Current measurable signals only roughly represent ongoing pathophysiological processes, and dynamic insults (eg impaired autoregulation and neurovascular unit dysfunction) cannot be reliably monitored. As a result, no therapeutic action has been shown to be beneficial in randomised patient trials.
The project goal is to prepare novel dynamic insult monitoring technologies and to develop improved decision support by integrating disease models and insult/treatment ontologies into smart multimodality monitor software.
A parallel goal is to unite high level expertise in clinical, biomedical, statistical and engineering sciences into one network to boost the next generation of researchers to substantially advance the field of neuromonitoring.
The network includes 3 relevant animal models and access to large (multi)center patient databases with injury, treatment & outcome data (eg Center-TBI).
Direct autoregulation visualization in the cranial window piglet model will be elaborated to improve circulation models and relations
with measurable high resolution signals to develop a real-time autoregulation monitor. These metrics will be associated with spreading depolarizations, vasospasm, ischemia and brain function in the rodent stroke models. The models and monitor technology are highly transferrable to patient care. Patient data will be used to build multidimensional statistical disease models. Insult and treatment ontologies will be developed in parallel with insult prediction and insult burden visualization concepts. Smart monitor platforms that aid precision medicine in acute central nervous system injury close to trials and future innovation leaders are expected results.
The project goal is to prepare novel dynamic insult monitoring technologies and to develop improved decision support by integrating disease models and insult/treatment ontologies into smart multimodality monitor software.
A parallel goal is to unite high level expertise in clinical, biomedical, statistical and engineering sciences into one network to boost the next generation of researchers to substantially advance the field of neuromonitoring.
The network includes 3 relevant animal models and access to large (multi)center patient databases with injury, treatment & outcome data (eg Center-TBI).
Direct autoregulation visualization in the cranial window piglet model will be elaborated to improve circulation models and relations
with measurable high resolution signals to develop a real-time autoregulation monitor. These metrics will be associated with spreading depolarizations, vasospasm, ischemia and brain function in the rodent stroke models. The models and monitor technology are highly transferrable to patient care. Patient data will be used to build multidimensional statistical disease models. Insult and treatment ontologies will be developed in parallel with insult prediction and insult burden visualization concepts. Smart monitor platforms that aid precision medicine in acute central nervous system injury close to trials and future innovation leaders are expected results.
