Introdução: Os processos degenerativos vêm sendo considerados determinantes da progressão do déficit neurológico na esclerose múltipla (EM) e são associados sobretudo à perda neuronal e axonal. A patologia na substância branca (SB) manifesta-se pela quebra de membranas e perda da complexidade microestrutural dos tratos cerebrais, o que pode ser estudado indiretamente pelas alterações nos índices de fração de anisotropia (FA) e difusividade média (DM), obtidos por meio das análises das imagens por tensores de difusão (diffusion tensor imaging - DTI). Essa técnica oferece outros dois índices mais específicos, a difusividade axial () e difusividade radial (), que são associados aos processos de perda axonal e desmielinização, respectivamente. A perda neuronal na substância cinzenta (SC) pode ser avaliada pelo grau de atrofia do córtex cerebral. Este estudo tem como objetivos mensurar os índices de DTI na maior comissura cerebral, o corpo caloso (CC), e o grau e distribuição da atrofia cortical em indivíduos com EM remitente-recorrente (EMRR) e baixos escores de incapacidade funcional, correlacionando essas alterações com o volume de lesões macroscópicas e os principais parâmetros clínicos. Método: 31 indivíduos (22 mulheres, idade média 30,5 anos ± 8,7) com EMRR e um grupo controle (GC) composto por 34 indivíduos saudáveis (27 mulheres, idade média 32,3 anos ± 7,8) realizaram exames de crânio em aparelho de ressonância magnética de 3 Tesla (3T), sendo adquiridas imagens de DTI com 32 direções de gradiente, obtendo-se os índices de FA, DM, e de cinco segmentos na secção sagital do corpo caloso (CC). Através da segmentação de imagens volumétricas ponderadas em T1 foram obtidas as espessuras corticais regionais nos grupos. Esses resultados foram correlacionados com os volumes lesionais de imagens ponderadas em T1 e T2/FLAIR e os escores da escala expandida do estado de incapacidade (Expanded Disability Status Scale - EDSS), considerando-se significativos resultados com p< 0,05. Resultados: Os índices de FA, DM e do CC estavam difusamente alterados no grupo EMRR e a , alterada significativamente no esplênio, tronco médio anterior e tronco médio posterior do CC. Observou-se atrofia cortical significativa no terço anterior dos lobos temporais, bilateralmente, e nas regiões parietal inferior, insular e fronto-orbitária direitas, com uma tendência à atrofia no giro frontal superior esquerdo. As FA, DM e correlacionaram-se com os volumes lesionais T1 e, mais significativamente, com os volumes lesionais T2/FLAIR, porém não houve correlação entre os volumes lesionais e a . A espessura cortical no grupo EMRR apresentou correlações com ambos os volumes lesionais, mais significativamente com as lesões em T1. O escore médio da EDSS era 1,1 ± 0,9 (variando de 0-3), apresentando correlações com a DM e a no esplênio, tronco médio anterior e posterior do CC, com uma correlação com a no tronco médio posterior. O EDSS correlacionou-se com a espessura cortical na topografia do giro frontal superior esquerdo. Discussão e conclusão: Houve alteração difusa nos índices de FA, DM e nos segmentos do CC, com acometimento mais localizado, predominantemente médio posterior, da , o que pode sugerir desmielinização difusa do CC, porém axonopatia ou degeneração mais acentuada em algumas regiões da SB. A atrofia cortical também apresentou uma distribuição regional característica, afetando sobretudo as regiões temporais, bilateralmente, parietal inferior, insular e fronto-orbitária direitas. As correlações encontradas entre os índices de DTI e a espessura cortical e os volumes lesionais demonstraram que, ao menos em parte, as degenerações das SB e SC podem ser relacionadas à degeneração Walleriana, secundária ao acúmulo de placas lesionais. As correlações entre a DM, de alguns segmentos do CC e a espessura cortical do giro frontal superior com os escores da EDSS favoreceram à hipótese de que a degeneração tecidual na EM foi um fator preponderante na progressão do déficit neurológico na EMRR / Introduction: The degenerative processes are gaining attention as predictors of the neurological deficit in multiple sclerosis (MS), being reflected by the degree of axon loss and central nervous system atrophy. The white matter pathology (WM) is characterized by cellular membranes disruption and loss of the microstructural complexity, which can be accessed by the diffusion tensor imaging (DTI) indices of fractional anisotropy (FA) and mean diffusivity (MD). This imaging technique also offers two more specific indices: the axial diffusivity () and radial diffusivity (), which are useful to differentiate between axon loss and demyelination, respectively. The gray matter (GM) neuronal loss can be accessed by the degree of cortical atrophy. The aim of this study is to measure the DTI indices in the greatest WM commisure, the corpus callosum (CC), and the degree and distribution of cortical atrophy in patients with relapsing remitting MS (RRMS) and low disability scores, correlating them to the macroscopic lesion load and the main clinical scores. Method: 31 RRMS patients (22 women, mean age 30.5 years ± 8.7) and 34 healthy control (HC) subjects (27 women, mean age 32.3 years ± 7.8) were submitted to brain examinations in a 3T magnetic resonance image scanner. From DTI with 32 gradient encoding directions were extracted the indices of FA, MD, and , which were measured in 5 segments of the mid-sagital section of the corpus callosum (CC). The cortical thickness was obtained from the segmentation of volumetric T1 images. These results were correlated with the macroscopic lesion loads in the T1 and T2/FLAIR images and the scores in the Expanded Disability Status Scale EDSS, considering significant the results with p< 0.05. Results: The FA, MD and were diffusively abnormal in all 5 segments of the CC in the RRMS group and the was abnormal only in the splenium, anterior midbody and posterior mid-body. The anterior area of the both temporal lobes and right inferior parietal, some orbital-frontal and insular regions showed significant atrophy, with a tendency of atrophy in the superior frontal gyrus. The FA, MD and correlated with the T1 lesion load and, more significantly, with the T2/FLAIR lesion load. The cortical thickness correlated with T1 and T2/FLAIR lesion loads, more significantly with the T1 lesion load. The mean EDSS in the RRMS group was 1.1 ± 0.9 (range 0-3), correlating with the MD and of the splenium, anterior and posterior mid-body of the CC. The EDSS correlated to cortical thickness in the topography of the superior frontal gyrus. Discussion and conclusion: The FA, MD and are diffusively abnormal in the CC, with abnormalities in the , restricted to the medial and posterior segments. These results can be interpreted as signs of diffuse demyelination in the CC and a predominance of axonopathy or more advanced degeneration in some segments. The cortical atrophy also followed a characteristic regional distribution, affecting predominantly the bilateral temporal lobes, and inferior parietal, orbital-frontal and insular regions, in the right hemisphere. The correlations found between the DTI indices and the cortical thickness and the macroscopic lesion loads show that, at least partially, the WM and GM degeneration can be related to Wallerian degeneration secondary to macroscopic lesion accumulation. The correlations between the DM, , in some of the CC segments, and cortical thickness, in the superior frontal gyrus, and the EDSS scores reinforces the hypothesis that the degenerative processes in MS can play a role in the disability status of the patients

Extracting structure from initially incomprehensible streams of events is fundamental to a range of human abilities: from navigating in a new environment to learning a language. These skills rely on our ability to extract spatial and temporal regularities, often with minimal explicit feedback, that is known as statistical learning. Despite the importance of statistical learning for making perceptual decisions, we know surprisingly little about the brain circuits and how they change when learning temporal regularities. In my thesis, I combine behavioural measurements, Diffusion Tensor Imaging (DTI) and resting-state fMRI (rs-fMRI) to investigate the structural and functional circuits that are involved in statistical learning of temporal structures. In particular, I compare structural connectivity as measured by DTI and functional connectivity as measured by rs-fMRI before vs. after training to investigate learning-dependent changes in human brain pathways. Further, I combine the two imaging modalities using graph theory and regression analyses to identify key predictors of individual learning performance. Using a prediction task in the context of sequence learning without explicit feedback, I demonstrate that individuals adapt to the environment’s statistics as they change over time from simple repetition to probabilistic combinations. Importantly, I show that learning of temporal structures relates to decision strategy that varies among individuals between two prototypical distributions: matching the exact sequence statistics or selecting the most probable outcome in a given context (i.e. maximising). Further, combining DTI and rs-fMRI, I show that learning-dependent plasticity in dissociable cortico-striatal circuits relates to decision strategy. In particular, matching relates to connectivity between visual cortex, hippocampus and caudate, while maximisation relates to connectivity between frontal and motor cortices and striatum. These findings have potential translational applications, as alternate brain routes may be re-trained to support learning ability when specific pathways (e.g. memory-related circuits) are compromised by age or disease.

Functional magnetic resonance imaging (fMRI) is a widely used, noninvasive technique to map brain activation, and has provided considerable insight into human brain function over the past two decades. Until recently, fMRI studies have focused on gray matter; however, reports of fMRI activation in white matter are mounting. White matter fMRI activation has the potential to greatly expand the breadth of brain connectivity research, as well as improve the assessment and diagnosis of white matter and connectivity disorders. Despite these potential benefits, white matter fMRI activation remains controversial. The controversy is partially due to the existence of incompletely understood facets of fMRI signals in white matter. This thesis describes three experiments that aim to refine what is currently known about white matter fMRI activation. In the first experiment, one of the main concerns about fMRI activation in white matter was addressed; namely, whether white matter has sufficient cerebrovascular reactivity to support hemodynamic changes that can be measured with fMRI. It was demonstrated that white matter has the capacity to support detectable hemodynamic changes in the absence of partial volume effects. In the second experiment, the effect of static magnetic field strength on sensitivity to white matter fMRI activation was explored as a possible cause of the relative paucity of reports of white matter fMRI activation. The results showed greater sensitivity to white matter fMRI activation at 4 T relative to 1.5 T MRI. In the third experiment, the relationship between white matter activation and the activated network of gray matter regions was explored. This was accomplished using fMRI-guided tractography in which structural connections between activated clusters are evaluated. Structural connectivity between white matter fMRI activation and regions of gray matter activation was demonstrated, providing evidence of the functional significance of fMRI activation in white matter. These experiments provide important insights, which will allow for improved investigations of white matter fMRI activation in the future. In addition, it is posited that experimenter bias, via selective reporting of activation clusters, has contributed to the slow acceptance of fMRI activation in white matter.

Healthy white matter in the brain and spinal cord is composed primarily of myelinated axons and glial cells. Myelinated axons transfer information between the peripheral nervous system and the central nervous system (CNS) as well as between centres within the CNS. Demyelination, a hallmark of neurodegenerative autoimmune diseases such as multiple sclerosis (MS), can cause nerve damage and degrade signal propagation. Magnetic resonance imaging (MRI) methods thought to assess myelin integrity and the structural integrity of axons are improving both the diagnosis and understanding of white matter diseases such as MS. Current methods, however, are sensitive to many different pathologies, making the interpretation of individual MRI results difficult. For this dissertation, several quantitative MRI methods were developed and compared, including single component T1 and T2 relaxometry, multicomponent T2 relaxometry, diffusion tensor imaging (DTI), and quantitative magnetization transfer imaging (qMTI). These methods were tested on agarose gels, fixed rat spinal cords, healthy control mice, and the cuprizone mouse model of demyelination. Quantitative MRI measurements were correlated to ultrastructural measurements of white matter to determine the influence myelin content and axonal structure have on different MRI methods. Cellular distributions measured in electron micrographs of the corpus callosum correlated strongly to several different quantitative MRI metrics. The largest Spearman correlation coefficient varied depending on cellular type: longitudinal relaxation rates (RA/T1) vs. the myelinated axon fraction ( r = 0.90/-0.90), the qMTI-derived bound pool fraction (f) vs. the myelin sheath fraction ( r = 0.93), and the DTI-derived axial diffusivity vs. the non-myelinated cell fraction (r = 0.92). Using Pearson’s correlation coefficient, f was strongly correlated to the myelin sheath fraction (r = 0.98) with a linear equation predicting myelin content (5.37f −0.25). Of the calculated MRI metrics, f was the strongest indicator of myelin content while longitudinal relaxation rates and diffusivity measurements were the strongest indicators of changes in tissue structure. Multiparametric MRI measurements of relaxation, diffusion, and magnetization transfer give a more complete picture of white matter integrity.

Parkinson’s disease patients present with the highest risk of dementia development. The thalamus, integral to several functions and behaviours is involved in the pathophysiology of Parkinson’s disease. The aim of this thesis was to determine if anatomical abnormalities in the thalamus are associated with the development of dementia in Parkinson’s disease. We examined the thalamus using macro and microstructural techniques and the white matter pathways that connect the thalamus with areas of the surrounding cortex using diffusion tensor imaging (DTI) based tractography. T1-weighted magnetic resonance and DT images were collected in 56 Parkinson’s disease patients with no cognitive impairment, 19 patients with mild cognitive impairment, 17 patients with dementia and 25 healthy individuals who acted as control subjects. An established automated segmentation procedure (FIRST FSL) was used to delineate the thalamus and a modified k-means clustering algorithm applied to segment the thalamus into clusters assumed to represent thalamic nuclei. Fibre tracts were determined using DTI probabilistic tracking methods available in FIRST. Microstructural integrity was quantified by fractional anisotropy and mean diffusivity (MD) DTI measures. Results show that microstructural measures of thalamic integrity are more sensitive to cognitive dysfunction in PD than macrostructural measures. For the first time we showed a progressive worsening of cellular integrity (MD) in the groups who had greater levels of cognitive dysfunction. Thalamic degeneration was regionally specific and most advanced in the limbic thalamic nuclei which influenced executive function and attention, areas of cognition that are known to be affected in the earliest stages of PD. The integrity of the fibre tracts corresponding to these thalamic regions was also compromised. Degeneration of fibre tracts was most evident in the dementia group, indicating that they may be more protected against Lewy pathology than the nuclei of the thalamus. Our findings confirm previous histological, animal and lesion studies and provide a reliable estimate of cortical degeneration in PD that can be applied non-invasively and in vivo. A longitudinal study is needed to monitor the progression of cognitive decline in PD but we have provided the basis for further investigation into the predictive validity of thalamic degeneration for cognitive dysfunction. In the future, the microstructural changes of the thalamus could be used as biomarkers for the identification of individuals with a higher risk for dementia development and for the longitudinal monitoring of any interventions into cognitive decline.

Mild cognitive impairment (MCI) is a transition phase between normal aging and Alzheimer’s disease. Individuals with MCI show impairment in cognition as well as corresponding damage to areas of their brain. Performance on tasks such as discriminating objects with ambiguous features has been associated with damage to the perirhinal cortex, while scenes with structural (spatial) elements have been associated with damage to the hippocampus. In addition, attention is regarded as one of the first non-memory domains to decline in MCI. A relatively new MRI technique called diffusion tensor imaging (DTI) is sensitive to white matter microstructural integrity and has been associated with changes due to cognitive decline. 18 MCI (14 amnesic, 4 vascular) and 12 healthy matched controls were assessed in feature ambiguity, attention and structural learning to assess associated deficits in MCI. Associations with white matter microstructural integrity were then investigated. The MCI groups were discovered to perform worse than controls on the test of structural learning. In addition, altered attention networks were found in MCI and were associated with white matter microstructural integrity. No significant differences were found for feature ambiguity. These findings suggest there may be specific damage to the hippocampus while the perirhinal cortex may be preserved in MCI. Furthermore, dysfunction in attention was found to be associated with white matter microstructural integrity. These experimental tests may be useful in assessing dysfunction in MCI and identifying degeneration in white matter microstructural integrity. Further studies with larger sample sizes are needed to validate these findings.

The objective of this thesis is to provide a complete pipeline that achieves an accurate reconstruction of the white matter fascicles using clinical diffusion images characterized by a low angular resolution. This involves (i) a diffusion model inferred in each voxel from the diffusion images and (ii) a tractography algorithm fed with these local models to perform the actual reconstruction of fascicles. Our contribution in diffusion modeling is a new statistical distribution, the properties of which are extensively studied. We model the diffusion as a mixture of such distributions, for which we design a model selection tool that estimates the number of mixture components. We show that the model can be accurately estimated from single shell low angular resolution diffusion images and that it provides specific biomarkers for studying tumors. Our contribution in tractography is an algorithm that approximates the distribution of fascicles emanating from a seed voxel. We achieve that by means of a particle filter better adapted to multi-modal distributions than the traditional filters. To demonstrate the clinical applicability of our tools, we participated to all three editions of the MICCAI DTI Tractography challenge aiming at reconstructing the cortico-spinal tract from single-shell low angular and low spatial resolution diffusion images. Results show that our pipeline provides a reconstruction of the full extent of the CST.

Healthy white matter in the brain and spinal cord is composed primarily of myelinated axons and glial cells. Myelinated axons transfer information between the peripheral nervous system and the central nervous system (CNS) as well as between centres within the CNS. Demyelination, a hallmark of neurodegenerative autoimmune diseases such as multiple sclerosis (MS), can cause nerve damage and degrade signal propagation. Magnetic resonance imaging (MRI) methods thought to assess myelin integrity and the structural integrity of axons are improving both the diagnosis and understanding of white matter diseases such as MS. Current methods, however, are sensitive to many different pathologies, making the interpretation of individual MRI results difficult. For this dissertation, several quantitative MRI methods were developed and compared, including single component T1 and T2 relaxometry, multicomponent T2 relaxometry, diffusion tensor imaging (DTI), and quantitative magnetization transfer imaging (qMTI). These methods were tested on agarose gels, fixed rat spinal cords, healthy control mice, and the cuprizone mouse model of demyelination. Quantitative MRI measurements were correlated to ultrastructural measurements of white matter to determine the influence myelin content and axonal structure have on different MRI methods. Cellular distributions measured in electron micrographs of the corpus callosum correlated strongly to several different quantitative MRI metrics. The largest Spearman correlation coefficient varied depending on cellular type: longitudinal relaxation rates (RA/T1) vs. the myelinated axon fraction ( r = 0.90/-0.90), the qMTI-derived bound pool fraction (f) vs. the myelin sheath fraction ( r = 0.93), and the DTI-derived axial diffusivity vs. the non-myelinated cell fraction (r = 0.92). Using Pearson’s correlation coefficient, f was strongly correlated to the myelin sheath fraction (r = 0.98) with a linear equation predicting myelin content (5.37f −0.25). Of the calculated MRI metrics, f was the strongest indicator of myelin content while longitudinal relaxation rates and diffusivity measurements were the strongest indicators of changes in tissue structure. Multiparametric MRI measurements of relaxation, diffusion, and magnetization transfer give a more complete picture of white matter integrity.

<p>In recent years, the emergence of diffusion tensor imaging (DTI) has provided a unique means via water diffusional characteristics to investigate the white matter integrity in the human brain, and its impact on neuronal functions. However, since the characterization of white matter integrity using DTI often lacks tissue specificity, most research studies report changes in anisotropy that are not explicitly correlated with particular cellular origins. To improve the utility of DTI in translational neuroimaging, it is critical to develop DTI acquisition techniques that are quantitative and tissue specific.</p><p>There are, nevertheless, existing methods for tissue specificity. For example, myelin water images can be generated using multiple echo time (TE) or magnetization transfer techniques. These techniques can detect changes in the concentration of myelin associated markers, but not in their spatial organization. Most white matter pathologies however start with early microstructural changes in the myelin sheaths during which the tissue contents remain similar and are thus not differentiable on a conventional MR image. Thus, the ability to construct a diffusion tensor that is myelin specific can have an immediate impact on our better understanding myelin physiology and pathophysiology during brain development. </p><p>Unfortunately, the myelin water signal decays rapidly because of its short transverse relaxation time constant (T2 < 50 ms), especially in DTI experiments where the echo time (TE) can be as large as 100ms. Even in special cases where the TE is shorter, the lack of myelin selectivity in conventional DTI techniques makes assessment of myelin microstructure extremely challenging. Thus we need to develop a DTI methodology that will greatly shorten the TE and allow myelin selectivity.</p><p>To address these challenges we have developed innovative DTI acquisition methodologies that can specifically assess myelin microstructural changes in white matter. To preserve more signal from myelin water we used a stimulated echo DTI implementation. In our initial approach we integrated this sequence with a magnetization transfer preparation to achieve additional differentiating sensitization to myelin water and derive a myelin water weighted (MWW) diffusion tensor. Our results indicate that, compared to the conventional DTI, myelin water diffuses along the axis of the fiber, but has the same has larger fractional anisotropy (FA) due to significantly smaller radial diffusivity. The limited specificity of MT and high radio frequency power deposition of MT-DTI restrict its applicability in clinical studies. </p><p>To obtain increased myelin specificity we implemented a robust stimulated echo DTI sequence with segmented spiral-out readout trajectory for achieving minimal TE on clinical MRI scanners. To ensure high spatial accuracy throughout the DTI scan we further develop a methodology for inherently and dynamically correcting both motion induced phase errors and off-resonance effects due to magnetic field inhomogeneities (including eddy currents) in the reconstructed image. We the used this technique to conduct an unprecedented experiment in which we collected DTI images at multiple echo times (as short as 18ms) and characterized the dependence of anisotropy on the T2 components including myelin water. The results confirmed the anisotropy characteristics of myelin water found with our initial previous approach. </p><p>Building on this new information, we designed a MWW-DTI method based on the simultaneous acquisition of DTI images at two different echo times within clinical practical durations. It is hoped that this new DTI technique sensitized myelin microanatomy will find wide applications in monitoring healthy brain development in pediatric populations, as many developmental brain disorders start with microstructural changes in white matter.</p> / Dissertation

Diffusion tensor imaging (DTI) is a specialist MRI modality that can identify microstructural changes or abnormalities in the brain. It can also be used to show fibre tract pathways. Both of these features were used in this thesis. Firstly, standard imaging analysis techniques were used to study the effects of mild, repetitive closed head injury on a group of professional boxers. Such data is extremely rare, so the findings of regions of brain abnormalities in the boxers are important, adding to the body of knowledge about more severe traumatic brain injury. The author developed a novel multivariate analysis technique which was used on the same data. This new technique proved to be more sensitive than the standard univariate methods commonly used. An important part of diagnosing and monitoring brain damage involves the use of biomarkers. A novel investigation of whether diffusion parameters obtained from DTI data could serve as bio-markers of cognitive impairment in Parkinson's disease was conducted. This also involved developing a multivariate approach, which displayed increased sensitivity compared with any of the component parameters used singly, and suggested these diffusion measures could be robust bio-markers of cognitive impairment. Fibre tract connectivity between regions of the brain is also a potentially valuable measure for diagnosis and monitoring brain integrity. The feasibility of this was investigated in a multi-modal MRI study. Functional MRI (fMRI) identifies regions of activation associated with a particular task. DTI can then find the pathway of the fibre bundles connecting these regions. The feasibility of using regional connectivity to interrogate brain integrity was investigated using a single healthy volunteer. Fibre pathways between regions activated and deactivated by a working memory paradigm were determined. Though the results are only preliminary, they suggest that this line of research should be continued.