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Abstract #4136

Longitudinal progression of white matter deficits in Young Onset Alzheimer's Disease and Its Syndromic Variants using NODDI

Jiaying Zhang1, Catherine F Slattery2, Ross W Paterson2, Alexander JM Foulkes2, Laura Mancini3,4, David L Thomas3,4, Marc Modat1, Nicolas Toussaint1, David M Cash1,2, John S Thornton5, Daniel C Alexander1, Sebastien Ourselin1, Nick C Fox2, Jonathan M Schott2, and Hui Zhang1

1Department of Computer Science and Centre for medical image computing, University College London, London, United Kingdom, 2Department of Neurodegenerative disease, Institute of Neurology, University College London, London, United Kingdom, 3Neuroradiological Academic Unit, Department of Brain Repair and Rehabilitation, UCL Institute of Neurology, London, UK, University College London, London, United Kingdom, 4Lysholm Department of Neuroradiology, National Hospital for Neurology and Neurosurgery, UCLH NHS Foundation Trust, London, UK, University College London, 5Lysholm Department of Neuroradiology, National Hospital for Neurology and Neurosurgery, UCLH NHS Foundation Trust, London, UK, University College London, London, United Kingdom

Young Onset Alzheimer's disease (YOAD) is characterised by its syndromic diversity, which may be underpinned by different patterns of white matter (WM) network breakdown. This prompts considerable interest in studying WM. We have previously shown that NODDI, a multi-shell diffusion MRI technique, is more sensitive at detecting WM changes in YOAD than standard DTI and demonstrated unique profiles of WM deficits in its syndromic variants. Here we investigated longitudinal WM changes in YOAD patients using NODDI, and explored the patterns of longitudinal WM changes associated with syndromic variants using tract-based spatial statistics (TBSS).

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