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MRI-informed computational model for non-invasive detection of brain pressure

Year:
2023
Duration:
36 months
Approved budget:
$1,191,990.00
Researchers:
Dr Samantha Holdsworth
,
Dr Gonzalo Maso Talou
,
Dr Sarah-Jane Guild
,
Dr Soroush Safaei
,
Associate Professor Miriam Scadeng
,
Dr Matthew McDonald
,
Professor Helen Danesh-Meyer
,
Dr David Dubowitz
,
Associate Professor Graham Wilson
,
Dr Eryn Kwon
,
Mrs Leigh Potter
Host:
Mātai Medical Research Institute
Health issue:
Neurological (CNS)
Proposal type:
Project
Lay summary
Management of several conditions, characterized by high intracranial pressure (ICP), is hampered by the lack of a reliable, non-invasive technique to confidently determine if ICP is elevated. Raised ICP can severely compromise brain perfusion. Currently, the only way to definitively determine ICP is to measure it directly, requiring a highly invasive skull burr hole. What if there was a way to determine the ICP with a non-invasive MRI scan? We have developed a method called amplified MRI (aMRI), which can detect changes in brain motion with changes in ICP. We will acquire MRI data in Idiopathic Intracranial Hypertension patients to test the ability of an MRI-informed computational model to provide a diagnostic index of ICP. Our approach is ambitious and unique in its methods and application of scientific, computational modelling and bioengineering tools, with the potential to revolutionise patient management.