A data-driven approach to optimising the encoding for multi-shell diffusion MRI with application to neonatal imaging

Diffusion MRI has the potential to provide important information about the connectivity and microstructure of the human brain during normal and abnormal development, non-invasively and in vivo. Recent developments in MRI hardware and reconstruction methods now permit the acquisition of large amounts of data within relatively short scan times. This makes it possible to acquire more informative multi-shell data, with diffusion-sensitisation applied along many directions over multiple b-value shells. Such schemes are characterised by the number of shells acquired, and the specific b-value and number of directions sampled for each shell. However, there is currently no clear consensus as to how to optimise these parameters. In this work, we propose a means of optimising multi-shell acquisition schemes by estimating the information content of the diffusion MRI signal, and optimising the acquisition parameters for sensitivity to the observed effects, in a manner agnostic to any particular diffusion analysis method that might subsequently be applied to the data. This method was used to design the acquisition scheme for the neonatal diffusion MRI sequence used in the developing Human Connectome Project, which aims to acquire high quality data and make it freely available to the research community. The final protocol selected by the algorithm, and currently in use within the dHCP, consists of 20 b = 0 images and DW images at b = 400, 1000, 2600 s/mm2 with 64, 88, and 128 directions per shell respectively

Axon diameter mapping using diffusion MRI

Axon diameter plays a key role in the function and performance of nerve pathways of the central and peripheral nervous system. Therefore, there is a growing interest in imaging axon diameter non-invasively. One such technique is using diffusion MRI. The purpose of this thesis is to test the feasibility of axon diameter imaging using diffusion MRI. This thesis provides for the first time a thorough experimental framework for evaluation and comparison of diffusion MR sequences, specifically two promising sequences: SDE and OGSE. The thesis involves designing a phantom to determine intrinsic sensitivity of the diffusion sequences to axon diameters. Additional experiments involving an ex vivo monkey brain and a viable rat sciatic nerve are carried out. The comparison of OGSE and SDE sequences across all different experiments demonstrate that OGSE is better than SDE. Diameter estimates of the optimal sequences are compared to the ground truth and the accuracy are found to depend on the gradient strength and SNR. For clinical scanners (G=62 mT/m and SNR>20), diameters of 5 μm are below the resolution limit. At G=300 mT/m and SNR=20, the resolution limit is 2.5 μm within an ex vivo monkey brain, causing overestimated diameters; however, an excellent prediction of the low-high-low diameter trend across the corpus callosum is observed. For G=800 mT/m and SNR=10, the resolution limit is at 2.5-3 μm for a viable rat sciatic nerve and excellent histology match is obtained. This thesis demonstrates that axon diameter imaging using diffusion MRI is possible in the nervous system. The small axons of the central nervous system require strong gradients, which are increasingly becoming more available, and peripheral nervous system have axons that are large enough to be imaged at clinical gradient strengths. This, therefore, opens up possibilities of using axon diameters as biomarkers for neurodegenerative diseases and peripheral nerve regeneration studies