BU’s Institute of Medical Imaging and Visualisation (IMIV) will be part of a project awarded funding by the National Institute for Health Research (NIHR) to test a new Alzheimer’s diagnostic tool in the NHS.
The three-year multi-centre study, led by Oxford Brain Diagnostics (OBD), aims to assess the use of Cortical Disarray Measurement (CDM®) as a tool to identify and predict disease progression amongst patients presenting with mild cognitive impairment due to Alzheimer’s disease.
As part of the project, a total of 300 MRI scans from NHS patients in the early stages of the disease will be examined using CDM to distinguish patient cohorts and measure changes in brain structure over time.
This will enable the project team to assess how improved diagnosis will impact on current treatment pathways and patient outcomes, and to assess future economic impact across primary, secondary, and social care.
IMIV will be one of the centres carrying out imaging for this study using its state-of-the-art Siemens Lumina 3T MRI scanner. IMIV MRI Operations Manager John Totman said: “Our Siemens scanner has the capacity and capabilities to perform complex neuroimaging research studies, and we look forward to working with OBD in delivering this project.”
The project also involves the University of Oxford Health Economics Research Centre, University Hospital Southampton NHS Foundation Trust, NIHR Community Healthcare MedTech and IVD Cooperative, Cardiff and the Vale University Health Board, the University of Southampton, and Cardiff University.
It has been awarded funding of £1.4m from the NIHR Invention for Innovation (i4i) programme.
Dr Jamie Franklin, Head of the Institute of Imaging and Visualisation, said, “We are excited to be using Bournemouth University’s fantastic imaging facilities to contribute to this innovative and collaborative project.”
The Institute of Medical Imaging and Visualisation (IMIV): getting involved with this SIA enabled initiative
Academic Targeted Research Scheme (Data Science for Medical Imaging and Visualisation): Medical Image Analysis










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