Holly E Holmes1, Nick Powell2, James M O'Callaghan1, Jack A Wells1, Ian F Harrison1, Da Ma2, Ozama Ismail1, Victor LJ Tybulewicz3, Frances Wiseman4, Sebastian Ourselin2, Elizabeth M Fisher4, and Mark F Lythgoe1
1Centre for Advanced Biomedical Imaging, University College London, London, United Kingdom, 2Centre for Medical Image Computing, University College London, London, United Kingdom, 3National Institite for Medical Research, London, United Kingdom, 4Institute of Neurology, University College London, London, United Kingdom
Magnetic resonance angiography
(MRA) is an established MRI technique for visualising the cerebral vasculature.
Interpretation of MR angiograms is often reliant on visual inspection of the
data;1 however, it is possible to
misinterpret flow artefacts (e.g. signal
voids) as vascular alterations.2
In this work, we have used a
novel combination of MRA and advanced registration as well as statistical
algorithms to explore vascular alterations in the Tc1 mouse model of Down’s
syndrome. We identified operator-independent local disturbances in the vascular
architecture, which supports previous work in this mouse model as well as observations
in the wider DS population.