Meeting Banner
Abstract #2043

USING MACHINE LEARNING TO CLASSIFY EARLY STAGES OF COGNITIVE DECLINE FROM TYPICAL AGEING - THE CEREBELLUM MORE THAN JUST A BYSTANDER

Muriel Marisa Katharina Bruchhage1,2, Stephen Correla3, Paul Malloy4, Stephen Salloway5, and Sean Deoni2,6

1Centre for Neuroimaging Sciences, King's College London, London, United Kingdom, 2Advanced Baby Imaging Lab, Memorial Hospital of Rhode Island, Providence, RI, United States, 3Veterans Affairs Medical Center, Providence, RI, United States, 4Neurology, Butler Hospital, Providence, RI, United States, 5Human Behavior and Psychiatry, Warren Alpert Medical School at Brown University, Providence, RI, United States, 6Warren Alpert Medical School at Brown University, Providence, RI, United States

Alzheimer’s disease (AD) is one of the most common forms of dementia, marked by progressively degrading cognitive function. The cerebellum plays a role in AD development, but its predictive contribution to early stages of AD remains unclear. We used MRI machine learning based classification within myelin and grey matter of the whole, anterior and posterior cerebellum and the whole brain, between individuals within the first two early stages of dementia and typically ageing controls. Our findings suggest myelin and grey matter loss in early stages of AD, with distinct patterns of anterior and posterior cerebellar atrophy for each tissue property.

How to access this content:

For one year after publication, abstracts and videos are only open to registrants of this annual meeting. Registrants should use their existing login information. Non-registrant access can be purchased via the ISMRM E-Library.

After one year, current ISMRM & ISMRT members get free access to both the abstracts and videos. Non-members and non-registrants must purchase access via the ISMRM E-Library.

After two years, the meeting proceedings (abstracts) are opened to the public and require no login information. Videos remain behind password for access by members, registrants and E-Library customers.

Click here for more information on becoming a member.

Keywords