Optimisation and application of diffusion MRI in neonates
There have been many advances in the field of diffusion MRI (dMRI) since the introduction of diffusion tensor imaging. Of note, many different models have been proposed to make use of high angular resolution diffusion imaging (HARDI) data, and more recently multi-shell HARDI data. This makes it difficult to identify data acquisition strategies that can provide optimal results with most current and future models of dMRI. This problem is compounded in neonatal imaging since their diffusion characteristics differ from adults, and vary considerably with age and location in the brain. Here, we propose a strategy to identify optimal imaging parameters for neonatal dMRI, as used in the developing human connectome project (dHCP), and demonstrate the use of the resulting data for investigations into brain development.
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Discussion points of the webinar:
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Dr J-Donald Tournier (PhD)
King's College London
My work is focused on the development and application of diffusion MRI methods, particularly those that relate to the characterisation of white matter and its connectivity. I have worked particularly on: the design of acquisition schemes for high angular resolution diffusion imaging (HARDI); estimating fibre orientations in a crossing fibre context via spherical deconvolution; probabilistic tractography methods and related applications such as Track Density Imaging (TDI), Anatomically Constrained Tractography (ACT), and spherical deconvolution informed filtering of tracks (SIFT); Apparent Fibre Density (AFD) methods for group-wise fixel-based analysis (FBA) of whole brain diffusion MRI data; advocating the use of higher-order models for clinical applications, particularly neurosurgery. Much of my research output is available for use in the open-source software package MRtrix (www.mrtrix.org).
