In this thesis, we introduce a novel method of reconstructing fibre directions from diffusion images. By modelling the Principal Diffusion Direction PDD (the fibre direction) directly, we are able to apply regularization to the fibre direction explicitly, which was not possible before. Diffusion Tensor Imaging (DTI) is a technique which extracts information from multiple Magnetic Resonance Images about the amount and orientation of diffusion within the body. It is commonly used for brain connectivity studies, providing information about the white matter structure. Many methods have been represented in the literature for estimating diffusion tensors with and without regularization. Previous methods of regularization applied to the source images or diffusion tensors. The process of extracting PDDs therefore required two or three numerical procedures, in which regularization (including filtering) is applied in earlier steps before the PDD is extracted. Such methods require and/or impose smoothness on all components of the signal, which is inherently less efficient than using regularizing terms that penalize non-smoothness in the principal diffusion direction directly. Our model can be interpreted as a restriction of the diffusion tensor model, in which the principal eigenvalue of the diffusion tensor is a model variable and not a derived quantity. We test the model using a numerical phantom designed to test many fibre orientations in parallel, and process a set of thigh muscle diffusion-weighted images. / Thesis / Master of Science (MSc)

Diploma thesis Errors in MRI methods for measuring diffusion coefficients a study of measurement of diffusion NMR methods, specifies the location, causes, origination diffusion coefficients. The main function of the program is to simulate changes parameters measurement of diffusion coefficients and allows for example only one gradient or runs down gradient pulses.

Diffusion MRI (dMRI) measurements allow us to infer the microstructural properties of white matter and to reconstruct fiber pathways in-vivo. High angular diffusion imaging (HARDI) allows for the creation of more and more complex local models connecting the microstructure to the measured signal. One of the challenges is the derivation of meaningful metrics describing the underlying structure from the local models. The aim hereby is to increase the specificity of the widely used metric fractional anisotropy (FA) by using the additional information contained within the HARDI data. A local model which is connected directly to the underlying microstructure through the model of a single fiber population is spherical deconvolution. It produces a fiber orientation density function (fODF), which can often be interpreted as superposition of multiple peaks, each associated to one relatively coherent fiber population (bundle). Parameterizing these peaks one is able to disentangle and characterize these bundles. In this work, the fODF peaks are approximated by Bingham distributions, capturing first and second order statistics of the fiber orientations, from which metrics for the parametric quantification of fiber bundles are derived. Meaningful relationships between these measures and the underlying microstructural properties are proposed. The focus lies on metrics derived directly from properties of the Bingham distribution, such as peak length, peak direction, peak spread, integral over the peak, as well as a metric derived from the comparison of the largest peaks, which probes the complexity of the underlying microstructure. These metrics are compared to the conventionally used fractional anisotropy (FA) and it is shown how they may help to increase the specificity of the characterization of microstructural properties. Visualization of the micro-structural arrangement is another application of dMRI. This is done by using tractography to propagate the fiber layout, extracted from the local model, in each voxel. In practice most tractography algorithms use little of the additional information gained from HARDI based local models aside from the reconstructed fiber bundle directions. In this work an approach to tractography based on the Bingham parameterization of the fODF is introduced. For each of the fiber populations present in a voxel the diffusion signal and tensor are computed. Then tensor deflection tractography is performed. This allows incorporating the complete bundle information, performing local interpolation as well as using multiple directions per voxel for generating tracts. Another aspect of this work is the investigation of the spherical harmonic representation which is used most commonly for the fODF by means of the parameters derived from the Bingham distribution fit. Here a strong connection between the approximation errors in the spherical representation of the Dirac delta function and the distribution of crossing angles recovered from the fODF was discovered. The final aspect of this work is the application of the metrics derived from the Bingham fit to a number of fetal datasets for quantifying the brain’s development. This is done by introducing the Gini-coefficient as a metric describing the brain’s age.

This is a brief summary of the Fourteenth International Bologna Conference on Magnetic Resonance in Porous Media (MRPM14).

Diffusion-weighted magnetic resonance imaging can be used to estimate microstructural parameters of white matter in the brain. Two complementary techniques are investigated: the use of the temporal diffusion spectrum to explore small length scales and the STEAM technique to probe larger features. The diffusion spectrum has the potential to be more sensitive to small pores compared to conventional time-dependent diffusion. However, analytical expressions for the diffusion spectrum of particles only exist for simple geometries such as cylinders, which are often used as a model for intra-axonal diffusion. We propose a mathematical model for the extra-axonal space with parameters that are related to the microstructural properties of pore size, tortuosity, and surface-to-volume ratio. Measurements were made with an extra-axonal space phantom to validate the model. Fitted values for the phantom pore size match those from simulation. We extend the model to include the intra-axonal signal contribution. However, the parameters used to describe the intra- and extra-axonal spaces are related and it is important to remove redundant parameters to avoid overparameterization, which would make the model less robust. We propose analytical expressions to simplify the model. The model was then applied to measurements on fixed corpus callosum, which is a model system consisting of parallel axons. The estimated values of the axon volume fraction and mean and standard deviation of the axon radius distribution are comparable to those found in literature. Temporal diffusion spectra are useful for measuring the geometric properties of small spaces such as axon radii. However, longer diffusion times accessible using the STEAM sequence are necessary to probe structures with longer diffusion distances such as those parallel to the direction of axons. We used a model from the literature originally developed for use with animal magnetic resonance scanners and simplified it to quantify axial hindrance from data acquired on healthy volunteers in a clinical scanner. The interpretation of axial hindrance, which is a largely unexplored area of research, is discussed.

Diffusion of water molecules in biological tissues depends on several microstructural properties. Therefore, diffusion Magnetic Resonance Imaging (dMRI) is a useful tool to infer and study microstructural brain changes in the context of human development, ageing and neuropathology. In this thesis, the state-of-the-art of advanced dMRI techniques is explored and strategies to overcome or reduce its pitfalls are developed and validated. Firstly, it is shown that PCA denoising and Gibbs artefact suppression algorithms provide an optimal compromise between increased precision of diffusion measures and the loss of tissue's diffusion non-Gaussian information. Secondly, the spatial information provided by the diffusion kurtosis imaging (DKI) technique is explored and used to resolve crossing fibres and generalize diffusion measures to cases not limited to well-aligned white matter fibres. Thirdly, as an alternative to diffusion microstructural modelling techniques such as the neurite orientation dispersion and density imaging (NODDI), it is shown that spherical deconvolution techniques can be used to characterize fibre crossing and dispersion simultaneously. Fourthly, free water volume fraction estimates provided by the free water diffusion tensor imaging (fwDTI) are shown to be useful to detect and remove voxels corrupted by cerebrospinal fluid (CSF) partial volume effects. Finally, dMRI techniques are applied to the diffusion data from the large collaborative Cambridge Centre for Ageing and Neuroscience (CamCAN) study. From these data, the inference provided by diffusion anisotropy measures on maturation and degeneration processes is shown to be biased by age-related changes of fibre organization. Inconsistencies of previous NODDI ageing studies are also revealed to be associated with the different age ranges covered. The CamCAN data is also processed using a novel non-Gaussian diffusion characterization technique which is invariant to different fibre configurations. Results show that this technique can provide indices specific to axonal water fraction which can be linked to age-related fibre density changes.

Introduction Optimal nutrition is vital in the management of infants born preterm. Dietary fat in infancy is fundamental for the provision of energy for growth and development. Essential fatty acids, specifically Long Chain Polyunsaturated Fatty Acids (LC-PUFAs) such as docosahexaenoic acid (DHA), have been under investigation by several international research groups in the past decade. Essential fatty acids are critical in neurodevelopment as DHA is found in high proportions in structural lipids of cell membranes, particularly in the central nervous system (CNS). The accumulation of essential fatty acids and particularly DHA in the brain and retina occurs most rapidly during the perinatal period, therefore preterm infants are of particular concern (Singer, 2001). Current scientific consensus is that the optimum growth rate for preterm infants is equal to the in utero growth rate throughout the last trimester, however, failure to achieve the optimum intrauterine growth rate is common in preterm infants (Olhager and Forsum, 2003). Preterm infants require large amounts of energy and nutrients with which many infants are not provided or are not able to absorb, due to immature gastrointestinal and metabolic systems and other medical complications (Olhager and Forsum, 2003). There are a number of unresolved issues regarding optimal growth rate and total energy requirements (ER) for preterm infants. Hypotheses/Objectives This study is a “side study” to a double blind randomised controlled trial (RCT) of DHA supplementation in preterm infants. The hypothesis of this “side study” is that increased DHA during the neonatal period would increase total energy expenditure (TEE) and improve neurodevelopmental outcome. Specifically, at term postconceptual age (PCA) it was hypothesised that preterm infants receiving higher intake of DHA would have higher TEE’s due to the acceleration in brain maturation. Also, it was hypothesised that preterm infants receiving high levels of DHA would have TEE’s equivalent to term born infants due to their same brain maturation status. Other hypothesised effects of DHA supplementation include an accelerated maturation of the visual cortical pathways, and accelerated white matter (WM) tract development aiding in brain maturation. The first objective of this study was to measure TEE and ER in very preterm infants when they reached an age of 31-33 weeks post conceptional age (PCA). The effects of DHA supplementation on TEE, at simulated in utero levels, in very preterm infants (born < 33 weeks PCA), when assessed at term equivalent (40 weeks PCA) were studied. Another objective was to compare WM brain tissue volume at term PCA between two preterm groups and then with the term born infants. Visual latency was also compared between the two preterm infant groups and then with the term born infants. Methods TEE was measured using the doubly labelled water (DLW) method which is based on the differential elimination of 2H (deuterium) and 18O from the body subsequent to a loading dose of these isotopes. TEE was measured at the preterm age between 31-33 weeks PCA and again at term PCA. TEE measurements are made at term PCA in a term born control group. Brain assessment was by Magnetic Resonance Imaging and (MRI) and Visual Evoked Potential (VEP). Magnetic resonance imaging quantitatively measured brain volumes and WM. Visual evoked potential would provide information on visual latency and amplitude. Results The cohort consisted of 38 infants. The TEE of the very preterm infant group was measured at 31-33 weeks PCA. The mean (±standard deviation) (SD) TEE was calculated at 80(±27) kcal/kg/d, and using data in the literature for foetal energy accretion of 28kcal/kg/d, the mean ER was calculated to be 108(±27) kcal/kg/d. At term PCA TEE was calculated for the preterm DHA supplemented group to be 56(±19) kcal/kg/d and for the non-DHA supplemented group 70(±39) kcal/kg/d. These measurements were not statistically different. Flash VEP conducted on preterm given different amounts of DHA tested at term PCA found no statistically different measurements. When combining these results and comparing them to measurements of term born infants at term PCA, the right eye measurements showed that preterm infants had statistically greater latencies than term infants. When combining the left and right eye measurements the latencies no statistical significance was found. Amplitude was also not statistically significant between the groups. MRI measures at term PCA were not statistically different DHA supplemented and the non-DHA supplemented preterm infant group. When the preterm infant cohort was combined and compared to the term born infant group, the results showed that preterm infants imaged at term PCA had reduced WM development in a number of frontal lobe projections, and anterior and posterior commissarial pathways of the corpus callosum and corona radiata. Discussion The TEE and ER measurements in this study represent the largest preterm infant cohort to date. The ER values reported here are of value in allowing the calculation of appropriate feeding and nutritional strategies for preterm infants. Although no differences in TEE between the DHA and non DHA supplemented groups were found this may have been due to the small sample size. With regard to the latency outcomes, it can be speculated that if measurements were conducted at a later PCA the correlations may have been stronger and significant. Several other factors may have also affected the results, including alertness of the infant at the time of testing, thickness of the cranium, and other health factors could not be controlled for. This study contains the youngest cohort to be compared via Flash VEP. The MRI data did not find significant differences in brain volume and WM between the DHA supplemented and the non-DHA supplemented groups. The infant CNS is rapidly developing and there are multiple environmental factors which may have affected outcomes. The data did however find differences in WM development between the preterm and term infants. The reduced WM development found in the preterm infants compared to term born infants may provide some explanation for the correlation between preterm birth and poorer cognitive and functional outcomes. Larger studies which extend beyond the first months of life are recommended in order to investigate the long-term relationships between DHA supplementation, TEE and brain maturation.

Background To investigate vascular-related pathophysiological characteristics of two human lung cancers with modifiable vascularisation using MRI and CT. Methods Tumour xenografts with modifiable vascularisation were established in 71 rats (approval by the Animal Care Committee was obtained) by subcutaneous transplantation of two human non-small-cell lung cancer (NSCLC) cells (A549, H1299) either alone or co-transplanted with vascular growth promoters. The vascularity of the tumours was assessed noninvasively by MRI diffusion-weighted-imaging (DWI), T2-weighted, and time-of-flight (TOF) sequences) as well as contrast-enhanced CT (CE-CT), using clinical scanners. As a reference standard, histological examinations (CD-31, fluorescent beads) were done after explantation. Results Microvessel density (MVD) was higher in co-transplanted tumours (171 ± 19 number/mm2) than in non-co-transplanted tumours (111 ± 11 number/mm2; p = 0.002). Co-transplanted tumours showed higher growth rates and larger tumour vessels at TOF-MRI as well as larger necrotic areas at CE-CT. In co-transplanted tumours, DWI revealed higher cellularity (lower minimal ADCdiff 166 ± 15 versus 346 ± 27 mm2/s × 10−6; p < 0.001), highly necrotic areas (higher maximal ADCdiff 1695 ± 65 versus 1320 ± 59 mm2/s × 10−6; p < 0.001), and better-perfused tumour stroma (higher ADCperf 723 ± 36 versus 636 ± 51 mm2/s × 10−6; p = 0.005). Significant correlations were found using qualitative and quantitative parameters: maximal ADCperf and MVD (r = 0.326); maximal ADCdiff and relative necrotic volume on CE-CT (r = 0.551); minimal ADCdiff and MVD (r = −0.395). Conclusions Pathophysiological differences related to vascular supply in two human lung cancer cell lines with modifiable vascularity are quantifiable with clinical imaging techniques. Imaging parameters of vascularisation correlated with the results of histology. DWI was able to characterise both the extent of necrosis and the level of perfusion.

Background To investigate vascular-related pathophysiological characteristics of two human lung cancers with modifiable vascularisation using MRI and CT. Methods Tumour xenografts with modifiable vascularisation were established in 71 rats (approval by the Animal Care Committee was obtained) by subcutaneous transplantation of two human non-small-cell lung cancer (NSCLC) cells (A549, H1299) either alone or co-transplanted with vascular growth promoters. The vascularity of the tumours was assessed noninvasively by MRI diffusion-weighted-imaging (DWI), T2-weighted, and time-of-flight (TOF) sequences) as well as contrast-enhanced CT (CE-CT), using clinical scanners. As a reference standard, histological examinations (CD-31, fluorescent beads) were done after explantation. Results Microvessel density (MVD) was higher in co-transplanted tumours (171 ± 19 number/mm2) than in non-co-transplanted tumours (111 ± 11 number/mm2; p = 0.002). Co-transplanted tumours showed higher growth rates and larger tumour vessels at TOF-MRI as well as larger necrotic areas at CE-CT. In co-transplanted tumours, DWI revealed higher cellularity (lower minimal ADCdiff 166 ± 15 versus 346 ± 27 mm2/s × 10−6; p < 0.001), highly necrotic areas (higher maximal ADCdiff 1695 ± 65 versus 1320 ± 59 mm2/s × 10−6; p < 0.001), and better-perfused tumour stroma (higher ADCperf 723 ± 36 versus 636 ± 51 mm2/s × 10−6; p = 0.005). Significant correlations were found using qualitative and quantitative parameters: maximal ADCperf and MVD (r = 0.326); maximal ADCdiff and relative necrotic volume on CE-CT (r = 0.551); minimal ADCdiff and MVD (r = −0.395). Conclusions Pathophysiological differences related to vascular supply in two human lung cancer cell lines with modifiable vascularity are quantifiable with clinical imaging techniques. Imaging parameters of vascularisation correlated with the results of histology. DWI was able to characterise both the extent of necrosis and the level of perfusion.

The aim of this work was to establish a comprehensive processing pipeline of cervical spinal cord HARDI dMRI data and T2-weighted anatomical MRI images in high-resolution. In the research part we provide description of anatomical data processing, theoretical background of dMRI, description of current approaches to 3D anisotropic diffusion estimation as well as current imaging methods of spinal cord axonal bundles. As one of the first in the world, we are investigating multiple-direction diffusion models for human in-vivo spinal cord white matter minority bundles imaging. We designed our own processing pipeline utilizing Spinal Cord Toolbox (SCT), FSL, in-house developer scripts and TORQUE-based batch system for grid computation, tested on real data from cervical spinal cord area between segments C4-C6 from 26 healthy volunteers. Designed processing pipeline with one non-automatic step, works from pre-processing to parcelation of selected spinal cord structures based on co-registration with anatomical spinal cord template for 25 subjects. One person data includes motion artifacts for which the proces failed. There are visible waves in sagittal images of some subjects caused probably by blood-vessel pulsing. Local quantification metrics of spinal cord anatomy (fractional anisotropy – FA, fractional volumes of first – f1 and second – f2 direction of anisotropic diffusion) from different parts (white matter, gray matter, cortico-spinal tract) and from different population groups (men vs. women), were extracted from dMRI data. As we expected, FA maps show visible decreases in areas of gray matter. We also detected second diffusion dirrection in slices, where the spinal roots come out. In some areas, fractional volume of second diffusion direction reaches up to 40% of the total component of the dMRI signal. All mentioned parameters probability density functions for all mentioned groups are non-normal distributions. Between male and female groups there were no significant distribution differences for f1 and f2 volumes. The distribution of FA values between men and women is statistically different. Unfortunatelly, there is a significant inter-subject variability in results, which has much higher dispersion than differences between different group distributions. Despite the inter-subject variability, this work significantly extends the knowledge about data acquisiton capabilities and MRI and dMRI data from cervical spinal cord image processing. This work also lays down foundations for utilization of the imaging method in future and planned clinical research, where it will be possible to test the alteration of the spinal cord anatomy on the minor secondary bundles separately.