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Abstract #0494

Identifying microstructural changes in diffusion MRI models; How to break parameter degeneracies

Hossein Rafipoor1, Saad Jbabdi1, Ludovica Griffanti1,2, and Michiel Cottaar1
1Wellcome Centre for Integrative Neuroimaging (WIN), Nuffield Department of Clinical Neurosciences (NDCN), University of Oxford, Oxford, United Kingdom, 2Wellcome Centre for Integrative Neuroimaging (WIN), Department of Psychiatry, University of Oxford, Oxford, United Kingdom

We present a novel Bayesian framework to relate changes in data to changes in model parameters even in models that cannot be directly inverted. We do so by training probabilistic models that characterise how the measurements change as a result of a change in the parameters. While the approach is general, in this work we used the framework to study microstructural parameter changes that are associated with the appearance of areas of white matter hyperintensities. We found a dichotomy between periventricular and deep white matter hyperintensities, where the latter are associated with increased extracellular signal.

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