OBJECTIFS : de précédentes études ont déjà démontré le potentiel de l’imagerie en tenseur de diffusion (DTI) pour détecter des anomalies médullaires dans la sclérose en plaques (SEP). L’objectif de ce travail était d’appliquer les techniques de DTI à des patients atteints de SEP et présentant une lésion médullaire symptomatique, afin de mettre en évidence une corrélation entre les variations des paramètres DTI et l’évolution clinique, et d’identifier des facteurs pronostiques prédictifs en DTI. METHODE : réalisation d’une étude prospective monocentrique chez des patients ayant une poussée médullaire de SEP traitée par corticoïdes intraveineux. Les patients étaient évalués cliniquement ainsi qu’en IRM (conventionnelle et DTI), à l’inclusion et à 3 mois. RESULTATS : seize patients ont été inclus. Lors du suivi à 3 mois, 12 patients étaient cliniquement améliorés. Tous sauf un avaient des valeurs de Fraction d’Anisotropie (FA) plus basses que les sujets normaux, au sein des lésions inflammatoires et dans la moelle apparemment normale, à l’inclusion ou lors du suivi à 3 mois. Les patients améliorés à 3 mois avaient une réduction significative de la Diffusivité Radiale (DR) (p=0,02) dans les lésions au cours du suivi. Ils avaient également une réduction significative du Coefficient de Diffusion Apparent moyen (p=0,002), de la Diffusivité Axiale (p=0,02) et de la DR (p=0,02) et une augmentation significative des valeurs de FA (p=0,02) dans la moelle apparemment normale. Les huit patients améliorés sur leur score ASIA (American Spinal Injury Association) sensitif à 3 mois avaient une FA initiale au sein des lésions inflammatoires significativement plus élevée (p=0,009) et une DR significativement plus basse (p=0,04) que les patients non améliorés. CONCLUSION : dans la SEP, l’IRM médullaire avec séquences en DTI détecte plus d’anomalies que l’IRM conventionnelle T2. Ces anomalies sont évolutives et corrélées au pronostic clinique, notamment celles observées dans la moelle épinière apparemment normale. Une diminution moins marquée des valeurs de FA initiales et plus marquée de la DR au sein des lésions inflammatoires est associée à un meilleur pronostic fonctionnel. / PURPOSE: the potential of Diffusion Tensor Imaging (DTI) to detect spinal cord abnormalities in patients with multiple sclerosis has already been demonstrated. The objective of this study was to apply DTI techniques to Multiple Sclerosis patients with a recently diagnosed spinal cord lesion, in order to demonstrate a correlation between variations of DTI parameters and clinical outcome, and to try to identify DTI parameters predictive of outcome. METHODS: a prospective single-centre study of patients with spinal cord relapse treated by intravenous steroid therapy. Patients were assessed clinically and by conventional MRI with DTI sequences at baseline and at 3 months. RESULTS: Sixteen patients were recruited. At 3 months, 12 patients were clinically improved. All but one patient had lower Fractional Anisotropy (FA) and Apparent Diffusion Coefficient (ADC) values than normal subjects in either inflammatory lesions or normal-appearing spinal cord. Patients who improved at 3 months presented a significant reduction in the Radial Diffusivity (p=0.05) in lesions during the follow-up period. They also had a significant reduction in the mean ADC (p=0.002), Axial Diffusivity (p=0.02), Radial Diffusivity (p=0.02) and a significant increase in FA values (p=0.02) in normal-appearing spinal cord. Patients in whom the American Spinal Injury Association sensory score improved at 3 months showed a significantly higher FA (p=0.009) and lower Radial Diffusivity (p=0.04) in inflammatory lesion at baseline compared to patients with no improvement. CONCLUSION: DTI MRI detects more extensive abnormalities than conventional T2 MRI. A less marked decrease in FA value and more marked decrease in Radial Diffusivity inside the inflammatory lesion were associated with better outcome.

L’IRM de diffusion est une modalité d’imagerie médicale qui suscite un intérêt croissant dans larecherche en neuro-imagerie. Elle permet de caractériser in vivo l’organisation neuronale et apportepar conséquent de nouvelles informations sur les fibres de la matière blanche. En outre, il a étémontré que chaque région corticale a une signature spécifique pouvant être décrite par des mesuresde connectivité. Notre travail de recherche a ainsi porté sur la conception d’une méthode deparcellisation du cortex entier à partir de ces métriques. En se basant sur de précédents travaux dudomaine (thèse de P. Roca 2011), ce travail propose une nouvelle analyse de groupe permettantl’obtention d’une segmentation individuelle ou moyennée sur la population d'étude. Il s’agit d’unproblème difficile en raison de la variabilité interindividuelle présente dans les données. Laméthode a été testée et évaluée sur les 80 sujets de la base ARCHI. Des aspects multimodaux ontété abordés pour comparer nos parcellisations structurelles avec d’autres parcellisations ou descaractéristiques morphologiques calculées à partir des modalités présentes dans la base de données.Une correspondance avec la variabilité de l’anatomie corticale, ainsi qu’avec des parcellisations dedonnées d’IRM fonctionnelle, a pu être montrée, apportant une première validationneuroscientifique. / Résumé anglais :Diffusion MRI is a medical imaging modality of great interest in neuroimaging research. Thismodality enables the characterization in vivo of neuronal organization and thus providinginformation on the white matter fibers. In addition, each cortical region has been shown to have aspecific signature, which can be described by connectivity measures. Our research has focused onthe design of a whole cortex parcellation method driven by these metrics. Based on the previouswork of P. Roca 2011, a new group analysis is proposed to achieve an individual or populationaveraged segmentation. This is a difficult problem due to the interindividual variability present inthe data. The method was tested and evaluated on the 80 subjects of the ARCHI database.Multimodal aspects were investigated to compare the proposed structural parcelliations with otherparcellations or morphological characteristics derived from the modalities present in the database. Aconnection between the variability of cortical anatomy and parcellations of the functional MRI datawas demonstrated, providing a first neuroscientist validation.

Objective: Following a sport related concussion (SRC) visible symptoms generally dissipate in 7-10 days post-injury. However, little is known about the cumulative effects of SRCs both in terms of structural damage to the white matter of the brain and neurocognitive performance. To address this issue, the relationship between the number of SRCs (frequency), axonal white matter (WM) damage and neurocognitive performance was examined. There were three predictions. First, increases in SRC frequency will be associated with decreases in performance on neurocognitive tests. Second, the frequency of SRC will be associated with axonal injury measured three WM tracts: the corpus callosum, the fronto-occipital fasciculus and the inferior longitudinal fasciculus. Third, less accurate and slower performance on a response inhibition task (STOP-IT) will be associated with greater axonal injury. Methods: A cross-sectional correlational design was utilised. Participants were rugby players with a history of SRC, rugby players with no history of SRC and control athletes (N=40) who completed a neurocognitive test battery and had a DTI brain scan. The neurocognitive battery consisted of the following standardised tests: Speed and Capacity of Language Processing Test, CogState Electronic Battery, Stroop Colour and Word Test, Controlled Oral Word Association Test, the Trail Making Test and the experimental test STOP-IT Electronic Test. White matter axonal injury was measured by DTI using fractional anisotropy (FA) and mean diffusivity (MD) metrics. The DTI data was processed using FSL to extract FA and MD DTI metrics in three a-priori regions of interest. Results: Spearman’s correlation analyses did not find significant associations between SRC frequency and neurocognitive performance on the FAS (rs=0.053, 95% CI [-0.27, 0.36]), TMT-A (rs=0.058, 95% CI [-0.26, 0.37]), TMT-B (rs= -0.046, 95% CI [-0.27, 0.36]) and the Stroop Interference (rs= -0.25, 95% CI [-0.07, 0.52]). Similarly, no significant Spearman’s correlations were found between SRC frequency and the computerised neurocognitive tests STOP-IT-SSRT (rs= -0.04, 95% CI [-0.28, 0.35])), STOP-IT–Accuracy (rs= -0.05, 95% CI [-0.27, 0.36]), CogState Detection subtest (rs= -0.15, 95% CI [-0.17, 0.44]), CogState Identification subtest (rs= -0.065, 95% CI [-0.26, 0.37]), CogState One card learning subtest (rs= 0.24, 95% CI [-0.08, 0.52]) or the CogState One back task subtest (rs= 0.06, 95% CI [-0.26, 0.37]). In terms of the DTI data there were no significant associations between SRC frequency and axonal injury measured by FA values in the CC (rs= 0.005, 95% CI [-0.31, 0.32]), ILF (rs= 0.028, 95% CI [-0.29, 0.34]) or FOF (rs= -0.022, 95% CI [-0.30, 0.33]). The same was pattern was found for MD values in the CC (rs= 0.081, 95% CI [-0.24, 0.39]), ILF (rs= -0.16, 95% CI [-0.16, 0.45]) or FOF (rs= -0.15, 95% CI [-0.17, 0.44]) Finally, there were no significant Spearman’s correlations between axonal injury FA values and the STOP-IT SSRT in any of the ROIs: CC (rs= 0.005, 95% CI [-0.31, 0.32]), ILF (rs= 0.028, 95% CI [-0.29, 0.34]) or FOF (rs= -0.022, 95% CI [-0.30, 0.33]). Equally, there were no significant correlations between MD values STOP-IT SSRT in the CC (rs= -0.028, 95% CI [-0.29, 0.34]), ILF (rs= -0.16, 95% CI [-0.16, 0.45]) or FOF (rs= -0.15, 95% CI [-0.17, 0.44]). Likewise, there were no significant Spearman’s correlations between accuracy on the STOP-IT and FA values and in any of the ROIs: CC (rs= 0.19, 95% CI [-0.13, 0.48]), ILF (rs= -0.045, 95% CI [-0.27, 0.35]) and FOF (rs= -0.032, 95% CI [-0.29, 0.34]), or MD values in the CC (rs= -0.11, 95% CI [-0.21, 0.41]), ILF (rs= 0.017, 95% CI [-0.30, 0.33]) or FOF (rs= 0.082, 95% CI [-0.24, 0.39]). This study did not find support for the hypothesis that cumulative SRCs are associated with poorer performance on neurocognitive tests or with axonal injury as measured by FA and MD DTI metrics. Conclusion: The null findings suggest that there are no cumulative effects of SRCs. The current findings are inconsistent with previous cross-sectional research that indicates that there are long-term changes to diffusivity measures present after single SRCs as well as cumulative effects in contact sport athletes. Likewise they are at odds with evidence suggesting that after three SRCs neurocognitive performance can be affected. The study needs to be extended to include a larger sample to ensure the results are not due to low statistical power.

The logistical complexities of performing multi-site longitudinal diffusion-weighted imaging (DWI) studies requires careful construction of analysis tools and procedures. Proposed clinical trials for therapies in neurodegenerative disease are known to re- quire several hundred subjects, thus mandating multiple site participation to obtain sufficient sample sizes. DWI is an important tool for monitoring diffusivity properties of white matter (WM) in disease progression. The multi-site nature of clinical trials requires new strategies in DWI processing and analysis to reliably measure longitudi- nal WM changes. This work describes the process of developing and validating robust analysis methodologies to process multi-site DWI data in a rare, neurodegenerative disease. Key processing components to accomplish a robust DWI processing system include: DICOM conversion, automated quality control, unbiased atlas construction, fiber tracking, and statistical analysis. Extensive validation studies were performed to characterize methodological results within and across the common confounds inherent in multi-site clinical trials. The conversion and automated quality control tools optimized for this work both enhanced the ability to reliably obtain repeat diffusion tensor image (DTI) scalar measurements in a reliability analysis of healthy controls scanned at multiple sites using multiple scanner vendors. A DTI scalar analysis performed on focused WM regions showed it was possible to detect significant mean differences of DTI scalars among separate groups of a neurodegenerative disease population. The DTI scalar analysis paved the way for an atlas-based cross-sectional fiber tracking analysis. In the cross-sectional fiber tracking analysis, multi-site data was brought into the same space, making major fiber tracts terminating in the focused WM regions of the scalar analysis from all participants comparable. Significant differences in diffusivity were found throughout each tract among separate groups of the neurodegenerative disease population. In addition, multiple neuropsychological cognitive variables that have a documented ability to track disease progression of the neurodegenerative disease, strongly correlated with many of the DTI scalars in each tract. The findings of the cross-sectional fiber tracking analysis were reinforced by similar findings produced by a longitudinal fiber tracking analysis. Collectively, these findings suggest that cogni- tive deficits seen in the neurodegenerative disease population could be explained by changes in diffusivity of the tracts explored in this work. In addition to the longi- tudinal fiber tracking analysis examining diffusivity, methods for a WM morphology analysis using parallel transport to apply longitudinal volume changes to a template was explored.

The current study investigates the effects of vascular disease on white matter health by comparing participants with atherosclerotic vascular disease (AVD) to healthy control participants (HC). The comparison between groups will help elucidate the differences between early-stage mild vascular disease and normal aging processes in terms of their effects on white matter health as measured by diffusion tensor imaging (DTI). Relationships between white matter health and depression, attention, and processing speed are studied by the application of a variety of DTI neuroimaging techniques, which will allow investigation of these relationships at the levels of global, lobe-wise, and subregional analysis. The specific subregion of interest in the depression study is Brodmann Area 25, which has shown significant relationships with depressive symptomatology in patients with treatment refractory depression, but has not been studied in the context of aging, vascular disease, or subthreshold depressive symptoms. Results indicate that there are significant differences between AVD and HC participants in global and regional FA measures. Within the AVD group, significant relationships of FA with depressive symptoms and attentional function have been observed in the current study. Several unexpected findings emerged, most important of which was the observation that there is a significant relationship between FA in Brodmann Area 25 and depressive symptoms in AVD participants which is specific to the right hemisphere. These findings have implications for the treatment of depressive symptoms in older adults and participants with vascular disease.

<p>Neuroimaging and neurophysiology techniques were used to study some aspects of cortical sensory and motor system reorganisation in patients in the chronic phase after stroke. Using Diffusion Tensor Imaging, we found that the degree of white matter integrity of the corticofugal tracts (CFT) was positively related to grip strength. Structural changes of the CFT were also associated with functional changes in the corticospinal pathways, measured using Transcranial Magnetic Stimulation. This suggests that structural and functional integrity of the CFT is essential for upper limb function after stroke.</p><p>Using functional magnetic resonance imaging (fMRI), to measure brain activity during slow and fast passive hand movements, we found that velocity-dependent brain activity correlated positively with neural contribution to passive movement resistance in the hand in ipsilateral primary sensory (S1) and motor (M1) cortex in both patients and controls. This suggests a cortical involvement in the hyperactive reflex response of flexor muscles upon fast passive stretch.</p><p>Effects of a four week passive-active movement training programme were evaluated in chronic stroke patients. The group improved in range of motion and upper limb function after the training. The patients also reported improvements in a variety of daily tasks requiring the use of the affected upper limb. </p><p>Finally, we used fMRI to explore if brain activity during passive hand movement is related to time after stroke, and if such activity can be affected with intense training. In patients, reduced activity over time was found in supplementary motor area (SMA), contralateral M1 and prefrontal and parietal association areas along with ipsilateral cerebellum. After training, brain activity increased in SMA, ipsilateral S1 and intraparietal sulcus, and contralateral cerebellum in parallel with functional improvements of the upper limb. The findings suggest a use-dependent modification of cortical activation patterns in the affected hand after stroke. </p>

Functional brain images are extraordinarily rich data sets that reveal distributed brain networks engaged in a wide variety of cognitive operations. It is a substantial challenge both to create models of cognition that mimic behavior and underlying cognitive processes and to choose a suitable analytic method to identify underlying brain networks. Most of the contemporary techniques used in analyses of functional neuroimaging data are based on univariate approaches in which single image elements (i.e. voxels) are considered to be computationally independent measures. Beyond univariate methods (e.g. statistical parametric mapping), multivariate approaches, which identify a network across all regions of the brain rather than a tessellation of regions, are potentially well suited for analyses of brain imaging data. A multivariate method (e.g. partial least squares) is a computational strategy that determines time-varying distributed patterns of the brain (as a function of a cognitive task). Compared to its univariate counterparts, a multivariate approach provides greater levels of sensitivity and reflects cooperative interactions among brain regions. Thus, by considering information across more than one measuring point, additional information on brain function can be revealed. Similarly, by considering information across more than one measuring technique, the nature of underlying cognitive processes become well-understood. Cognitive processes have been investigated in conjunction with multiple neuroimaging modalities (e.g. fMRI, sMRI, EEG, DTI), whereas the typical method has been to analyze each modality separately. Accordingly, little work has been carried out to examine the relation between different modalities. Indeed, due to the interconnected nature of brain processing, it is plausible that changes in one modality locally or distally modulate changes in another modality. This thesis focuses on multivariate and multimodal methods of image analysis applied to various cognitive questions. These methods are used in order to extract features that are inaccessible using univariate / unimodal analytic approaches. To this end, I implemented multivariate partial least squares analysis in study I and II in order to identify neural commonalities and differences between the available and accessible information in memory (study I), and also between episodic encoding and episodic retrieval (study II). Study I provided evidence of a qualitative differences between availability and accessibility signals in memory by linking memory access to modality-independent brain regions, and availability in memory to elevated activity in modality-specific brain regions. Study II provided evidence in support of general and specific memory operations during encoding and retrieval by linking general processes to the joint demands on attentional, executive, and strategic processing, and a process-specific network to core episodic memory function. In study II, III, and IV, I explored whether the age-related changes/differences in one modality were driven by age-related changes/differences in another modality. To this end, study II investigated whether age-related functional differences in hippocampus during an episodic memory task could be accounted for by age-related structural differences. I found that age-related local structural deterioration could partially but not entirely account for age-related diminished hippocampal activation. In study III, I sought to explore whether age-related changes in the prefrontal and occipital cortex during a semantic memory task were driven by local and/or distal gray matter loss. I found that age-related diminished prefrontal activation was driven, at least in part, by local gray matter atrophy, whereas the age-related decline in occipital cortex was accounted for by distal gray matter atrophy. Finally, in study IV, I investigated whether white matter (WM) microstructural differences mediated age-related decline in different cognitive domains. The findings implicated WM as one source of age-related decline on tasks measuring processing speed, but they did not support the view that age-related differences in episodic memory, visuospatial ability, or fluency were strongly driven by age-related differences in white-matter pathways. Taken together, the architecture of different aspects of episodic memory (e.g. encoding vs. retrieval; availability vs. accessibility) was characterized using a multivariate partial least squares. This finding highlights usefulness of multivariate techniques in guiding cognitive theories of episodic memory. Additionally, competing theories of cognitive aging were investigated by multimodal integration of age-related changes in brain structure, function, and behavior. The structure-function relationships were specific to brain regions and cognitive domains. Finally, we urged that contemporary theories on cognitive aging need to be extended to longitudinal measures to be further validated.

Neuroimaging and neurophysiology techniques were used to study some aspects of cortical sensory and motor system reorganisation in patients in the chronic phase after stroke. Using Diffusion Tensor Imaging, we found that the degree of white matter integrity of the corticofugal tracts (CFT) was positively related to grip strength. Structural changes of the CFT were also associated with functional changes in the corticospinal pathways, measured using Transcranial Magnetic Stimulation. This suggests that structural and functional integrity of the CFT is essential for upper limb function after stroke. Using functional magnetic resonance imaging (fMRI), to measure brain activity during slow and fast passive hand movements, we found that velocity-dependent brain activity correlated positively with neural contribution to passive movement resistance in the hand in ipsilateral primary sensory (S1) and motor (M1) cortex in both patients and controls. This suggests a cortical involvement in the hyperactive reflex response of flexor muscles upon fast passive stretch. Effects of a four week passive-active movement training programme were evaluated in chronic stroke patients. The group improved in range of motion and upper limb function after the training. The patients also reported improvements in a variety of daily tasks requiring the use of the affected upper limb. Finally, we used fMRI to explore if brain activity during passive hand movement is related to time after stroke, and if such activity can be affected with intense training. In patients, reduced activity over time was found in supplementary motor area (SMA), contralateral M1 and prefrontal and parietal association areas along with ipsilateral cerebellum. After training, brain activity increased in SMA, ipsilateral S1 and intraparietal sulcus, and contralateral cerebellum in parallel with functional improvements of the upper limb. The findings suggest a use-dependent modification of cortical activation patterns in the affected hand after stroke.

In two separate studies, we used diffusion tensor imaging (DTI)to examine white matter changes secondary to traumatic brain injury (TBI) and spinal cord injury (SCI). The first study examined the utility of DTI for a single case diagnosis of mild TBI (mTBI) and demonstrated that the anterior limb of the internal capsule and the genu of the corpus callosum were sensitive and specific to mTBI. The second study examined the sub-acute effects of SCI on white matter tissue in the brain and demonstrated that SCI patients have a significantly greater degree of FA asymmetry than control subjects in the superior and posterior corona radiata. The first study has provided preliminary proof of principal evidence that DTI can be used to diagnose mTBI in individual cases. The second study suggests that the degree of asymmetry may be a useful biomarker for detecting subtle white matter changes.

Diffusion Tensor Imaging (DTI) can quantify tissue integrity in normal-appearing white matter (NAWM). NAWM abnormalities present at the earliest time point implicate neurodegeneration operative from the outset of multiple sclerosis (MS). DTI scans were obtained at first attacks from 6 children later diagnosed with MS and 6 children with monophasic demyelination, and from 6 controls, matched for age. DTI scans were also obtained from 22 children with established MS with clinical onset before age 12 years and compared to age-matched controls. Atlas- and tractography-based image processing methods were utilized. DTI metrics distinguished MS patients from patients with monophasic demyelination and from controls at the first attack. Differences in NAWM between children with established early-onset MS and controls were only notable when DTI was obtained in adolescence. DTI provides valuable insights into NAWM in children with MS, although in the youngest patients such changes may require time to develop.