Quasi-diffusion magnetic resonance imaging (QDI): A fast, high b-value diffusion imaging technique.

To enable application of non-Gaussian diffusion magnetic resonance imaging (dMRI) techniques in large-scale clinical trials and facilitate translation to clinical practice there is a requirement for fast, high contrast, techniques that are sensitive to changes in tissue structure which provide diagnostic signatures at the early stages of disease. Here we describe a new way to compress the acquisition of multi-shell b-value diffusion data, Quasi-Diffusion MRI (QDI), which provides a probe of subvoxel tissue complexity using short acquisition times (1-4 min). We also describe a coherent framework for multi-directional diffusion gradient acquisition and data processing that allows computation of rotationally invariant quasi-diffusion tensor imaging (QDTI) maps. QDI is a quantitative technique that is based on a special case of the Continuous Time Random Walk model of diffusion dynamics and assumes the presence of non-Gaussian diffusion properties within tissue microstructure. QDI parameterises the diffusion signal attenuation according to the rate of decay (i.e. diffusion coefficient, D in mm2 s-1) and the shape of the power law tail (i.e. the fractional exponent, α). QDI provides analogous tissue contrast to Diffusional Kurtosis Imaging (DKI) by calculation of normalised entropy of the parameterised diffusion signal decay curve, Hn, but does so without the limitations of a maximum b-value. We show that QDI generates images with superior tissue contrast to conventional diffusion imaging within clinically acceptable acquisition times of between 84 and 228 s. We show that QDI provides clinically meaningful images in cerebral small vessel disease and brain tumour case studies. Our initial findings suggest that QDI may be added to routine conventional dMRI acquisitions allowing simple application in clinical trials and translation to the clinical arena

Empirical comparison of diffusion kurtosis imaging and diffusion basis spectrum imaging using the same acquisition in healthy young adults

As diffusion tensor imaging gains widespread use, many researchers have been motivated to go beyond the tensor model and fit more complex diffusion models, to gain a more complete description of white matter microstructure and associated pathology. Two such models are diffusion kurtosis imaging (DKI) and diffusion basis spectrum imaging (DBSI). It is not clear which DKI parameters are most closely related to DBSI parameters, so in the interest of enabling comparisons between DKI and DBSI studies, we conducted an empirical survey of the interrelation of these models in 12 healthy volunteers using the same diffusion acquisition. We found that mean kurtosis is positively associated with the DBSI fiber ratio and negatively associated with the hindered ratio. This was primarily driven by the radial component of kurtosis. The axial component of kurtosis was strongly and specifically correlated with the restricted ratio. The joint spatial distributions of DBSI and DKI parameters are tissue-dependent and stable across healthy individuals. Our contribution is a better understanding of the biological interpretability of the parameters generated by the two models in healthy individuals

Feasibility of in vivo multi-parametric quantitative magnetic resonance imaging of the healthy sciatic nerve with a unified signal readout protocol

Magnetic resonance neurography (MRN) has been used successfully over the years to investigate the peripheral nervous system (PNS) because it allows early detection and precise localisation of neural tissue damage. However, studies demonstrating the feasibility of combining MRN with multi-parametric quantitative magnetic resonance imaging (qMRI) methods, which provide more specific information related to nerve tissue composition and microstructural organisation, can be invaluable. The translation of emerging qMRI methods previously validated in the central nervous system to the PNS offers real potential to characterise in patients in vivo the underlying pathophysiological mechanisms involved in a plethora of conditions of the PNS. The aim of this study was to assess the feasibility of combining MRN with qMRI to measure diffusion, magnetisation transfer and relaxation properties of the healthy sciatic nerve in vivo using a unified signal readout protocol. The reproducibility of the multi-parametric qMRI protocol as well as normative qMRI measures in the healthy sciatic nerve are reported. The findings presented herein pave the way to the practical implementation of joint MRN-qMRI in future studies of pathological conditions affecting the PNS

Diffusion Kurtosis Magnetic Resonance Imaging and Its Application to Traumatic Brain Injury

Diffusion tensor imaging (DTI) is a popular magnetic resonance imaging technique that provides in vivo information about tissue microstructure, based on the local water diffusion environment. DTI models the diffusion displacement of water molecules in tissue as a Gaussian distribution. In this dissertation, to mimic the complex nature of water diffusion in brain tissues, a diffusion kurtosis model is used, to incorporate important non-Gaussian diffusion properties. This diffusion kurtosis imaging (DKI) is applied in an experimental traumatic brain injury in a rat model, to study whether it provides more information on microstructural changes than standard DTI. Our results indicate changes in ordinary DTI parameters, in various brain regions following injury, normalize to the baseline by the sub-acute stage. However, DKI parameters continue to show abnormalities at this sub-acute stage, as confirmed by immunohistochemical examination. Specifically, increased mean kurtosis (MK) was found to associate with increased reactive astrogliosis, a hallmark for inflammation, even in regions far removed from the injury foci. Findings suggest that monitoring changes in MK enhances the investigation of molecular and morphological changes in vivo. Extending DKI to clinical usage, however, poses several challenges: (a) long image acquisition time (~20 min) due to the augmented measurements required to fit the more complex model, (b) slow image reconstruction (~90 min) due to required nonlinear fitting and, (c) errors associated with fitting the inherently low signal-to-noise ratio (SNR) images from higher diffusion weighting. The second portion of this dissertation is devoted to developing imaging schemes and image reconstruction methods that facilitate clinical DKI applications. A fast and efficient DKI reconstruction method is developed with a reconstruction time of 2-3 seconds, with improved accuracy and reduced variability in DKI estimation over conventional methods. Further analysis of diffusion weighted imaging schemes and their affect on DKI estimation leads to the identification of two clinically practical optimal imaging schemes (needing 7-10 min) that perform comparably to traditional schemes. The effect of SNR and reconstruction methods on DKI estimation is also studied, to provide a foundation for interpreting DKI results and optimizing DKI protocols

Diffusion kurtosis imaging with tract-based spatial statistics reveals white matter alterations in preschool children

Diffusion kurtosis imaging (DKI), an extension of diffusion tensor imaging (DTI), provides a practical method to describe non-Gaussian water diffusion in neural tissues. The sensitivity of DKI to detect the subtle changes in several chosen brain structures has been studied. However, intuitive and holistic methods to validate the merits of DKI remain to be explored. In this paper, tract-based spatial statistics (TBSS) was used to demonstrate white matter alterations in both DKI and DTI parameters in preschool children (1-6 years; n=10). Correlation analysis was also performed in multiple regions of interest (ROIs). Fractional anisotropy, mean kurtosis, axial kurtosis and radial kurtosis increased with age, while mean diffusivity and radial diffusivity decreased significantly with age. Fractional anisotropy of kurtosis and axial diffusivity were found to be less sensitive to the changes with age. These preliminary findings indicated that TBSS could be used to detect subtle changes of DKI parameters on the white matter tract. Kurtosis parameters, except fractional anisotropy of kurtosis, demonstrated higher sensitivity than DTI parameters. TBSS may be a convenient method to yield higher sensitivity of DKI.published_or_final_versio