Optimisation of statistical methodologies for a better diagnosis of neurological and psychiatric disorders by means of SPECT

In the last years there has been a wide consensus on the importance of brain imaging in assessing neurodegenerative and psychiatric disorders. Different techniques for functional and anatomical examination are currently clinically implemented in neurology and psychiatry to improve sensitivity, specificity and accuracy of the diagnosis of various diseases. In addition, the increasing life expectancy in the Western world raises the social importance and the economical impact of age-related neurodegenerative disorders since the incidence of Alzheimer disease and Parkinson disease is higher in the elderly. An early diagnosis of neuro-psychiatric diseases and the assessment of "natural" changes of regional cerebral blood flow (rCBF) distribution during normal aging are hence of utmost importance. In the recent past brain disorders have extensively been investigated by means of optimised nuclear medicine techniques, instruments and algorithms. Diagnosis can be better achieved by identifying those structures in which CBF or metabolism deviate from normality resulting in significant changes as compared to a reference database. In the present paper we present some studies investigating, by means of recently implemented diagnostic tools, patients bearer of various neuro-psychiatric disorders. The improved nuclear medicine techniques and instrumentation, the state-of-the-art software for brain imaging standardisation and the use of sophisticated multivariate data analysis are extensively reviewed

Optimisation of statistical methodologies for a better diagnosis of neurological and psychiatric disorders by means of SPECT

Abstract In the last years there has been a wide consensus on the importance of brain imaging in assessing neurodegenerative and psychiatric disorders. Different techniques for functional and anatomical examination are currently clinically implemented in neurology and psychiatry to improve sensitivity, specificity and accuracy of the diagnosis of various diseases. In addition, the increasing life expectancy in the Western world raises the social importance and the economical impact of age-related neurodegenerative disorders since the incidence of Alzheimer disease and Parkinson disease is higher in the elderly. An early diagnosis of neuro-psychiatric diseases and the assessment of "natural" changes of regional cerebral blood flow (rCBF) distribution during normal aging are hence of utmost importance. In the recent past brain disorders have extensively been investigated by means of optimised nuclear medicine techniques, instruments and algorithms. Diagnosis can be better achieved by identifying those structures in which CBF or metabolism deviate from normality resulting in significant changes as compared to a reference database. In the present paper we present some studies investigating, by means of recently implemented diagnostic tools, patients bearer of various neuro-psychiatric disorders. The improved nuclear medicine techniques and instrumentation, the state-of-the-art software for brain imaging standardisation and the use of sophisticated multivariate data analysis are extensively reviewed

Evaluating Spatial Normalization Methods for the Human Brain

Cortical stimulation mapping (CSM) studies have shown cortical locations for language function are highly variable from one subject to the next. Because no two cortical surfaces are alike and language is a higher order cognitive function, observed variability is attributable to a combination of functional and anatomical variation. If individual variation can be normalized, patterns of language organization may emerge that were heretofore hidden. In order to discover whether or not such patterns exist, computer-aided spatial normalization is required. Because CSM data has been collected on the cortical surface, we believe that a surface-based normalization method will provide more accurate results than will a volume-based method. To investigate this hypothesis, we evaluate a surface-based (Caret) and volume-based method (SPM2). For our application, the "ideal" method would i) minimize variation as measured by spread reduction between cortical language sites across subjects while also ii) preserving anatomical localization of sites. Evaluation technique: Eleven MR image volumes and corresponding CSM site coordinates were selected. Images were segmented to create left hemisphere surface reconstruction for each patient. Individual surfaces were registered to the colin27 human brain atlas using each method. Deformation parameters from each method were applied to CSM coordinates to obtain post-normalization coordinates in 2D space and 3D ICBM152 space. Accuracy metrics were calculated i) as mean distance between language sites across subjects in both 2D and 3D space and ii) by visual inspection of post-normalization site locations on a 2D map. Results: Globally, we found no statistically significant difference between CARET (surface-based method) and SPM2 (volume-based method) as measured by both spread reduction and anatomical localization. Local analysis showed that more than twenty percent of total mapping errors were mapped incorrectly by both methods. There was a statistically significant difference between Caret and SPM2 mapping of type 2 errors

Caudate responses to reward and punishment are preserved in healthy older adults

An fMRI task developed in our laboratory has consistently identified the head of the caudate nucleus as a region with distinct responses to positive and negative outcomes (Delgado et al., 2000, Delgado et al., 2003, Tricomi et al., 2004). Subjects are engaged in a guessing game in which they receive monetary gain for correct guesses and monetary loss for incorrect guesses. Following a rewarding outcome, the caudate exhibits a relatively sustained hemodynamic response, while punishment responses are characterized by an early, high-amplitude peak response followed by a below-baseline dip in the caudate signal. This response pattern has been replicated across multiple studies in young adults; however, no published evidence has yet established the nature of reward and punishment signals in the striatum of healthy older adults. Therefore, the purpose of the current study was to establish a valid method for measuring reward- and punishment-related activity in healthy aging, and to describe any age-related effects on the hemodynamic responses found in the striatum. Twenty older adults (51-68 y) and thirteen young adults (18-28 y) were scanned as they completed the card-guessing task. Older adults exhibited robust, outcome-specific responses in the anterior caudate with bilateral foci of activation that overlapped with the activation found in the young adults. Furthermore, older adults retained key features of the typical caudate response profile, with a sustained increase in the signal following reward outcomes and a decrease in the signal following punishments. However, older adults did not demonstrate an early, high-amplitude peak in the punishment response, which has been reported for earlier studies and was observed in the current young-adult sample. Finally, voxel-wise analyses identified two small clusters at or near the anterior caudate where older adults' signal appeared somewhat blunted relative to that of the young adults; similar blunting effects were found in a number of other regions throughout the brain. Overall, these findings validate the use of the card-guessing paradigm to assess outcome-specific responses in the striatum of older adults, and they point to some possible age-related effects that may be worthwhile to investigate in future studies

Brains of verbal memory specialists show anatomical differences in language, memory and visual systems

Abstract We studied a group of verbal memory specialists to determine whether intensive oral text memory is associated with structural features of hippocampal and lateral-temporal regions implicated in language processing. Professional Vedic Sanskrit Pandits in India train from childhood for around 10 years in an ancient, formalized tradition of oral Sanskrit text memorization and recitation, mastering the exact pronunciation and invariant content of multiple 40,000–100,000 word oral texts. We conducted structural analysis of gray matter density, cortical thickness, local gyrification, and white matter structure, relative to matched controls. We found massive gray matter density and cortical thickness increases in Pandit brains in language, memory and visual systems, including i ) bilateral lateral temporal cortices and ii ) the anterior cingulate cortex and the hippocampus, regions associated with long and short-term memory. Differences in hippocampal morphometry matched those previously documented for expert spatial navigators and individuals with good verbal working memory. The findings provide unique insight into the brain organization implementing formalized oral knowledge systems

Neuroinformatics in Functional Neuroimaging

This Ph.D. thesis proposes methods for information retrieval in functional neuroimaging through automatic computerized authority identification, and searching and cleaning in a neuroscience database. Authorities are found through cocitation analysis of the citation pattern among scientific articles. Based on data from a single scientific journal it is shown that multivariate analyses are able to determine group structure that is interpretable as particular “known ” subgroups in functional neuroimaging. Methods for text analysis are suggested that use a combination of content and links, in the form of the terms in scientific documents and scientific citations, respectively. These included context sensitive author ranking and automatic labeling of axes and groups in connection with multivariate analyses of link data. Talairach foci from the BrainMap ™ database are modeled with conditional probability density models useful for exploratory functional volumes modeling. A further application is shown with conditional outlier detection where abnormal entries in the BrainMap ™ database are spotted using kernel density modeling and the redundancy between anatomical labels and spatial Talairach coordinates. This represents a combination of simple term and spatial modeling. The specific outliers that were found in the BrainMap ™ database constituted among others: Entry errors, errors in the article and unusual terminology

Optimization of the diffusion-weighted MRI processing pipeline for the longitudinal assessment of the brain microstructure in a rat model of Alzheimer’s disease

Tese de mestrado integrado, Engenharia Biomédica e Biofísica (Radiações em Diagnóstico e Terapia) Universidade de Lisboa, Faculdade de Ciências, 2019The mechanism that triggers Alzheimer’s disease (AD) is not well-established, with amyloid plaques, neurofibrillary tangles of tau protein, microgliosis and glucose hypometabolism all likely involved in the early cascade. One main advantage of animal models is the possibility to tease out the impact of each insult on the neurodegeneration. Following an intracerebroventricular (icv) injection of streptozotocin (STZ), rats and monkeys develop impaired brain glucose metabolism, i.e. “diabetes of the brain”. Nu-merous studies have reported AD-like features in icv-STZ animals, but this model has never been char-acterized in terms of Magnetic Resonance Imaging (MRI)-derived biomarkers beyond structural brain atrophy. White matter degeneration has been proposed as a promising biomarker for AD that well pre-cedes cortical atrophy and correlates strongly with disease severity. Therefore, this project proposes a longitudinal study of white matter degeneration in icv-STZ rats using diffusion MRI. An existing image processing pipeline was primarily used to obtain preliminary results and propose an optimization strat-egy to improve it in terms of data quality and reliability. These strategies were tested and implemented in the pipeline when confirmed to be valuable, in order to achieve results as reproducible as possible and find the spatio-temporal pattern of brain degeneration in this animal model. All experiments were approved by the local Service for Veterinary Affairs. Male Wistar rats (N=18) (236±11 g) underwent a bilateral icv-injection of either streptozotocin (3 mg/kg, STZ group, N=10) or buffer (control group, CTL, N=8). Rats were scanned at four timepoints following surgery on a 14 T Varian system. Diffusion data were acquired using a semi-adiabatic SE-EPI PGSE sequence as follows: 4 (b=0 ms/μm2), 12 (b=0.8 ms/μm2), 16 (b=1.3 ms/μm2) and 30 (b=2 ms/μm2) directions; TE/TR=48/2500 ms, 9 coronal 1 mm slices, δ/Δ=4/27 ms, FOV=23x17 mm2, matrix=128x64 and 4 shots. The existing image processing pipeline included image denoising and eddy-correction. Moreover, diffusion and kurtosis tensors were calculated for each voxel, producing parametric maps of fractional anisotropy (FA), mean, axial and radial diffusivity (MD, AxD and RD) and mean, axial and radial kur-tosis (MK, AK and RK). Additionally, the two-compartment WMTI-Watson model was further esti-mated to provide specificity to the microstructure assessment. The following metrics were derived from the model: volume water fraction , parallel intra-axonal diffusivity , parallel ,║ and perpendicular extra-axonal diffusivities ,ꓕ and dispersion of fiber orientations 2. Since the model allows for two mathematical solutions, the >,║ solution was retained based on recent evidence. Considering pre-vious findings, the corpus callosum, cingulum, fornix and fimbria were chosen as white matter regions of interest (ROIs) and automatically segmented using anatomical atlas-based registration. Mean diffu-sion metrics were calculated in each ROI for each dataset. CTL and STZ groups were compared using two-sided t-tests at each timepoint. Within-group longitudinal changes were assessed using one-way ANOVA. Because of the small cohort, statistical analysis excluded the last time point. In the course of this project, strategies to optimize the existing pipeline were developed and tested. The existing brain atlas template was supplemented with white matter labels, rat brain extraction was semi-automated, and bias field correction of anatomical data was added before registration. Ventricle enlargement is typically reported in icv-STZ animals and normally constitutes an issue of misalignment in registration. In order to better match the label ROIs with the respective underlying tissue, several registration procedures were tested with different FA and color-coded FA template images. Color-coded FA-based registration dramatically improved the segmentation of the corpus callosum and the fimbria and reliability of diffusion metrics extracted from these regions. Moreover, additional fiber metrics were extracted from a newly developed tractography pipeline to compare with tensors metrics and finally, tensors metrics were evaluated in the gray matter for a more comprehensive spatio-temporal character-ization of brain degeneration. Results from statistical analysis were obtained after implementing the successful optimization strat-egies into the pipeline. There were few significant differences within groups over time. However, be-tween-group differences at each time point were more pronounced. White matter microstructure altera-tions were consistent with previous studies of histology and cognitive performance of the icv-STZ model. Changes in tensors metrics indicate early axonal injury in the fimbria and fornix at 2 weeks after injection, a period of potential recovery at 6 weeks after injection and late axonal injury at 13 weeks in all ROIs. The WMTI-Watson biophysical model provided specificity to the underlying microstructure, by showing intra-axonal damage in the fimbria and corpus callosum as early as 2 weeks, followed by a recover period and definite axonal loss at 13 weeks after injection. Results from tensors metrics and the WMTI-Watson model are not only complementary, they are consistent with each other and with previously-established trends for structural thickness, memory per-formance, amyloid deposition and inflammation. The icv-STZ model displays white matter changes in tracts reportedly affected by AD, while the degeneration is induced primarily by impaired brain glucose metabolism. The icv-STZ constitutes an excellent model to reproduce sporadic AD and should allow to further explore the hypothesis of AD being “type III diabetes”. The combination of diffusion information extracted from tensor imaging and biophysical modelling is a promising set of tools to assess white matter in the AD brain and might be the upcoming strategy to assess the human brain. Regarding future work, it will focus on estimating the correlation between microstructural alterations and functional con-nectivity (from resting-state functional MRI), glucose hypometabolism (from FDG-PET), and patholog-ical features (from histological stainings) – all currently under processing at CIBM. Tractography is a cutting-edge methodology to assess brain connectivity and the pipeline created could be further devel-oped to improve understanding and support diffusion metrics. The relationship between white and gray matter will also improve the understanding of spatio-temporal degeneration and the progression nature of the disease.O mecanismo que desencadeia a doença de Alzheimer (DA) não é bem conhecido, contudo sabe-se que a presença de placas amilóides e de emaranhados neurofibrilares da proteína tau, microgliose e ainda hipometabolismo de glucose estão envolvidos na fase inicial da cascata de desenvolvimento da doença. A principal vantagem dos modelos animais é justamente a possibilidade de estudar individualmente o impacto de cada um destes mecanismos no processo de neurodegeneração. Após uma injeção intracere-broventricular (icv) de estreptozotocina (STZ), várias espécies de animais mostraram um metabolismo anormal de glucose no cérebro, processo que foi referido como “diabetes do cérebro”. Vários estudos demonstraram que animais icv-STZ são portadores de características típicas de DA, mas este modelo animal nunca foi estudado em termos de biomarcadores derivados de técnicas de imagem por ressonân-cia magnética (IRM), exceto atrofia estrutural do cérebro. Um biomarcador promissor de DA que se acredita preceder a atrofia do córtex cerebral é a degeneração da matéria branca do cérebro, uma vez que foi fortemente correlacionado com a progressão e gravidade da doença. Logo, este projeto propõe um estudo longitudinal da degeneração da matéria branca em ratazanas icv-STZ utilizando IRM de di-fusão. O plano de processamento de imagem existente foi utilizado primeiramente para obter resultados preliminares e viabilizar a proposta de estratégias de otimização da mesma, em termos de melhoramento da qualidade de imagem e credibilidade das variáveis extraídas das imagens resultantes. Estas estratégias foram testadas e implementadas no plano de processamento quando a sua performance confirmou ser de valor, para que os resultados fossem o mais reproduzíveis possível em caracterizar a distribuição espácio-temporal da degeneração do cérebro neste modelo animal. Todos os procedimentos aqui descritos foram aprovados pelo serviço local dos assuntos veterinários. Ratazanas macho Wistar (N=18, 236±11 g) foram submetidas a uma injeção icv de STZ (3 mg/kg) no caso do grupo infetado (N=10) ou de um buffer no caso do grupo de controlo (N=8). As ratazanas foram examinadas no scanner de IRM do tipo Varian de 14 T em quatro momentos no tempo: 2, 6, 13 e 21 semanas após a injeção. As imagens por difusão foram adquiridas com uma sequência semi-adiabática spin-echo EPI PGSE com os seguintes parâmetros: 4 (b=0), 12 (b=0.8 ms/μm2), 16 (b=1.3 ms/μm2) and 30 (b=2 ms/μm2) direções; TE/TR=48/2500 ms, 9 secções coronais de 1 mm, δ/Δ=4/27 ms, FOV=23x17 mm2, matriz=128x64 e 4 shots. O plano existente de processamento de imagem incluía a correção das imagens ao nível de ruído e correntes-eddy. Posteriormente, os tensores de difusão e curtose foram estimados para cada voxel e os mapas paramétricos de anisotropia fracional (FA), difusão média, axial e radial (MD, AD e RD) e cur-tose média, axial e radial (MK, AK e RK) foram calculados. Adicionalmente, um modelo de difusão de água nas fibras da matéria branca foi utilizado para providenciar maior especificidade ao estudo da microestrutura do cérebro. Como tal, o modelo de dois compartimentos denominado WMTI-Watson foi também estimado e as seguintes variáveis foram derivadas do mesmo: a fração do volume de água , a difusividade paralela intra-axonal , as difusividades paralela ,║ e perpendicular ,ꓕ extra-axonais e, finalmente, a orientação da dispersão axonal 2. Este modelo matemático tem duas soluções possíveis dada a sua natureza quadrática, pelo que a solução >,║ foi imposta com base em evidências re-centes. Considerando estudos anteriores, as regiões de interesse (RDIs) da matéria branca escolhidas para analisar a microestrutura cerebral foram o corpo caloso, o cíngulo, a fimbria e a fórnix. Estes foram automaticamente segmentados através de registo de imagem de um atlas das regiões do cérebro da rata-zana e as médias das medidas extraídas dos tensores de difusão e curtose e ainda do modelo biofísico neuronal foram calculadas em cada RDI para cada conjunto de imagens obtidas. Os dois grupos de teste e controlo foram comparados usando testes t de Student bilaterais em cada momento do tempo, e a comparação das alterações longitudinais em cada grupo foi feita usando uma ANOVA. Devido ao baixo número de amostras, o último momento no tempo às 21 semanas foi excluído da análise. No decorrer deste projeto, várias estratégias para otimizar o processamento de imagem ou comple-mentar a análise da informação disponível foram testadas. Nomeadamente, o atlas cerebral da ratazana foi aperfeiçoado relativamente às regiões de matéria branca, a segmentação do cérebro foi testada com algoritmos automáticos e a correção do bias field em imagens estruturais de IRM foi adicionada ao plano antes do registo de imagem. O aumento dos ventrículos cerebrais é uma característica frequente em animais icv-STZ, constituindo um problema de alinhamento nos métodos de registo de imagem. No sentido de otimizar a correspondência entre as regiões do atlas e as respetivas regiões na imagem estru-tural e por difusão, vários procedimentos de registo de imagem foram testados. O co-registo de imagem convencional utiliza imagens estruturais para normalizar o espaço das imagens por difusão, no entanto os mapas paramétricos de FA têm vindo a substituir este conceito dado o excelente contraste que provi-denciam entre a matéria branca e cinzenta do cérebro. Mapas de FA com diferentes direções predomi-nantes mostraram uma melhoria significante da segmentação do corpo caloso e da fimbria e também do poder estatístico das variáveis extraídas destas RDIs. Adicionalmente, um novo plano de processamento de tratografia foi construído de raiz no âmbito deste projeto para extrair variáveis adicionais das fibras de interesse e compará-las com as variáveis de difusão obtidas por análise voxel-a-voxel. Por último, as variáveis calculadas através dos tensores de difusão e curtose foram avaliadas na matéria cinzenta do cérebro para uma caracterização espácio-temporal da degeneração cerebral na DA. Os resultados da análise estatística foram obtidos após integrar no plano de processamento as estra-tégias que mostraram valorizar o projeto em termos de qualidade de imagem ou credibilidade das vari-áveis. Houve poucas diferenças significativas ao longo do tempo em cada grupo, no entanto as diferen-ças entre grupos foram bastante acentuadas. As alterações ao nível da microestrutura da matéria branca foram consistentes com estudos prévios em animais icv-STZ usando métodos histológicos e avaliações das suas capacidades cognitivas. Alterações nas variáveis extraídas dos tensores indicaram deficiência axonal inicial na fimbria e no fórnix 2 semanas após injeção no grupo de teste, um potencial período de recuperação às 6 semanas e novamente deficiência axonal às 13 semanas, sendo que neste período tardio todas as RDIs foram afetadas. O modelo biofísico WMTI-Watson confirmou aumentar especificidade ao estudo da microestrutura, visto que demostrou danos intra-axonais na fimbria e no corpo caloso 2 semanas após injeção, seguidos de um período de recuperação e de perda de estrutura axonal definitiva às 13 semanas em todas as RDIs. Não só estes dois métodos de análise de IRM de difusão se complementam, como são também con-sistentes entre eles e com as tendências de alterações ao longo do tempo descritas noutros estudos. Além disso, o animal icv-STZ mostrou alterações características da DA, mesmo tendo a degeneração cerebral sido induzida pela disrupção do metabolismo de glucose no cérebro. Como tal, este modelo animal é excelente para reproduzir a doença e deverá continuar a ser avaliado nas diferentes áreas multidiscipli-nares para explorar a hipótese de a DA ser desencadeada pela falha do sistema insulina/glucose. A com-binação da informação de difusão obtida dos tensores e da modelação da difusão neuronal provou ser uma ferramenta promissora no estudo das fibras da matéria branca do cérebro e poderá vir a ser o desafio futuro no que toca a investigação clínica da DA. Este estudo focar-se-á em correlacionar as alterações microestruturais aqui descritas com dados de conectividade funcional (obtida por IRM funcional em repouso), hipometabolismo de glucose (por FDG-PET) e outras características patológicas (por colora-ção histológica) – todos já em curso no CIBM. Tratografia é a metodologia topo de gama para aceder à conetividade cerebral e o plano de processamento gerado neste projeto poderá continuar a ser desenvol-vido no futuro para informação adicional, assim como a relação entre a matéria branca e cinzenta poderá suplementar a compreensão da progressão da doença no espaço e no tempo

Development of an MRI Template and Analysis Pipeline for the Spinal Cord and Application in Patients with Spinal Cord Injury

La moelle épinière est un organe fondamental du corps humain. Étant le lien entre le cerveau et le système nerveux périphérique, endommager la moelle épinière, que ce soit suite à un trauma ou une maladie neurodégénérative, a des conséquences graves sur la qualité de vie des patients. En effet, les maladies et traumatismes touchant la moelle épinière peuvent affecter l’intégrité des neurones et provoquer des troubles neurologiques et/ou des handicaps fonctionnels. Bien que de nombreuses voies thérapeutiques pour traiter les lésions de la moelle épinière existent, la connaissance de l’étendue des dégâts causés par ces lésions est primordiale pour améliorer l’efficacité de leur traitement et les décisions cliniques associées. L’imagerie par résonance magnétique (IRM) a démontré un grand potentiel pour le diagnostic et pronostic des maladies neurodégénératives et traumas de la moelle épinière. Plus particulièrement, l’analyse par template de données IRM du cerveau, couplée à des outils de traitement d’images automatisés, a permis une meilleure compréhension des mécanismes sous-jacents de maladies comme l’Alzheimer et la Sclérose en Plaques. Extraire automatiquement des informations pertinentes d’images IRM au sein de régions spécifiques de la moelle épinière présente toutefois de plus grands défis que dans le cerveau. Il n’existe en effet qu’un nombre limité de template de la moelle épinière dans la littérature, et aucun ne couvre toute la moelle épinière ou n’est lié à un template existant du cerveau. Ce manque de template et d’outils automatisés rend difficile la tenue de larges études d’analyse de la moelle épinière sur des populations variées. L’objectif de ce projet est donc de proposer un nouveau template IRM couvrant toute la moelle épinière, recalé avec un template existant du cerveau, et intégrant des atlas de la structure interne de la moelle épinière (e.g., matière blanche et grise, tracts de la matière blanche). Ce template doit venir avec une série d’outils automatisés permettant l’extraction d’information IRM au sein de régions spécifiques de la moelle épinière. La question générale de recherche de ce projet est donc « Comment créer un template générique de la moelle épinière, qui permettrait l’analyse non biaisée et reproductible de données IRM de la moelle épinière ? ». Plusieurs contributions originales ont été proposées pour répondre à cette question et vont être décrites dans les prochains paragraphes. La première contribution de ce projet est le développement du logiciel Spinal Cord Toolbox (SCT). SCT est un logiciel open-source de traitement d’images IRM multi-parametrique de la moelle épinière (De Leener, Lévy, et al., 2016). Ce logiciel intègre notamment des outils pour la détection et la segmentation automatique de la moelle épinière et de sa structure interne (i.e., matière blanche et matière grise), l’identification et la labellisation des niveaux vertébraux, le recalage d’images IRM multimodales sur un template générique de la moelle épinière (précédemment le template MNI-Poly-AMU, maintenant le template PAM50, proposé içi). En se basant sur un atlas de la moelle, SCT intègre également des outils pour extraire des données IRM de régions spécifiques de la moelle épinière, comme la matière blanche et grise et les tracts de la matière blanche, ainsi que sur des niveaux vertébraux spécifiques. D’autres outils additionnels ont aussi été proposés, comme des outils de correction de mouvement et de traitement basiques d’images appliqués le long de la moelle épinière. Chaque outil intégré à SCT a été validé sur un jeu de données multimodales. La deuxième contribution de ce projet est le développement d’une nouvelle méthode de recalage d’images IRM de la moelle épinière (De Leener, Mangeat, et al., 2017). Cette méthode a été développée pour un usage particulier : le redressement d’images IRM de la moelle épinière, mais peut également être utilisé pour recaler plusieurs images de la moelle épinière entre elles, tout en tenant compte de la distribution vertébrale de chaque sujet. La méthode proposée se base sur une approximation globale de la courbure de la moelle épinière dans l’espace et sur la résolution analytique des champs de déformation entre les deux images. La validation de cette nouvelle méthode a été réalisée sur une population de sujets sains et de patients touchés par une compression de la moelle épinière. La contribution majeure de ce projet est le développement d’un système de création de template IRM de la moelle épinière et la proposition du template PAM50 comme template de référence pour les études d’analyse par template de données IRM de la moelle épinière. Le template PAM50 a été créé à partir d’images IRM tiré de 50 sujets sains, et a été généré en utilisant le redressement d’images présenté ci-dessus et une méthode de recalage d’images itératif non linéaire, après plusieurs étapes de prétraitement d’images. Ces étapes de prétraitement incluent la segmentation automatique de la moelle épinière, l’extraction manuelle du bord antérieur du tronc cérébral, la détection et l’identification des disques intervertébraux, et la normalisation d’intensité le long de la moelle. Suite au prétraitement, la ligne centrale moyenne de la moelle et la distribution vertébrale ont été calculées sur la population entière de sujets et une image initiale de template a été générée. Après avoir recalé toutes les images sur ce template initial, le template PAM50 a été créé en utilisant un processus itératif de recalage d’image, utilisé pour générer des templates de cerveau. Le PAM50 couvre le tronc cérébral et la moelle épinière en entier, est disponible pour les contrastes IRM pondérés en T1, T2 et T2*, et intègre des cartes probabilistes et atlas de la structure interne de la moelle épinière. De plus, le PAM50 a été recalé sur le template ICBM152 du cerveau, permettant ainsi la tenue d’analyse par template simultanément dans le cerveau et dans la moelle épinière. Finalement, plusieurs résultats complémentaires ont été présentés dans cette dissertation. Premièrement, une étude de validation de la répétabilité et reproductibilité de mesures de l’aire de section de la moelle épinière a été menée sur une population de patients touchés par la sclérose en plaques. Les résultats démontrent une haute fiabilité des mesures ainsi que la possibilité de détecter des changements très subtiles de l’aire de section transverse de la moelle, importants pour mesurer l’atrophie de la moelle épinière précoce due à des maladies neurodégénératives comme la sclérose en plaques. Deuxièmement, un nouveau biomarqueur IRM des lésions de la moelle épinière a été proposé, en collaboration avec Allan Martin, de l’Université de Toronto. Ce biomarqueur, calculé à partir du ratio d’intensité entre la matière blanche et grise sur des images IRM pondérées en T2*, utilise directement les développements proposés dans ce projet, notamment en utilisant le recalage du template de la moelle épinière et les méthodes de segmentation de la moelle. La faisabilité d’extraire des mesures de données IRM multiparamétrique dans des régions spécifiques de la moelle épinière a également été démontrée, permettant d’améliorer le diagnostic et pronostic de lésions et compression de la moelle épinière. Finalement, une nouvelle méthode d’extraction de la morphométrie de la moelle épinière a été proposée et utilisée sur une population de patients touchés par une compression asymptomatique de la moelle épinière, démontrant de grandes capacités de diagnostic (> 99%). Le développement du template PAM50 comble le manque de template de la moelle épinière dans la littérature mais présente cependant plusieurs limitations. En effet, le template proposé se base sur une population de 50 sujets sains et jeunes (âge moyen = 27 +- 6.5) et est donc biaisée vers cette population particulière. Adapter les analyses par template pour un autre type de population (âge, race ou maladie différente) peut être réalisé directement sur les méthodes d’analyse mais aussi sur le template en lui-même. Tous le code pour générer le template a en effet été mis en ligne (https://github.com/neuropoly/template) pour permettre à tout groupe de recherche de développer son propre template. Une autre limitation de ce projet est le choix d’un système de coordonnées basé sur la position des vertèbres. En effet, les vertèbres ne représentent pas complètement le caractère fonctionnel de la moelle épinière, à cause de la différence entre les niveaux vertébraux et spinaux. Le développement d’un système de coordonnées spinal, bien que difficile à caractériser dans des images IRM, serait plus approprié pour l’analyse fonctionnelle de la moelle épinière. Finalement, il existe encore de nombreux défis pour automatiser l’ensemble des outils développés dans ce projet et les rendre robuste pour la majorité des contrastes et champs de vue utilisés en IRM conventionnel et clinique. Ce projet a présenté plusieurs développements importants pour l’analyse de données IRM de la moelle épinière. De nombreuses améliorations du travail présenté sont cependant requises pour amener ces outils dans un contexte clinique et pour permettre d’améliorer notre compréhension des maladies affectant la moelle épinière. Les applications cliniques requièrent notamment l’amélioration de la robustesse et de l’automatisation des méthodes d’analyse d’images proposées. La caractérisation de la structure interne de la moelle épinière, incluant la matière blanche et la matière grise, présente en effet de grands défis, compte tenu de la qualité et la résolution des images IRM standard acquises en clinique. Les outils développés et validés au cours de ce projet ont un grand potentiel pour la compréhension et la caractérisation des maladies affectant la moelle épinière et aura un impact significatif sur la communauté de la neuroimagerie.----------ABSTRACT The spinal cord plays a fundamental role in the human body, as part of the central nervous system and being the vector between the brain and the peripheral nervous system. Damaging the spinal cord, through traumatic injuries or neurodegenerative diseases, can significantly affect the quality of life of patients. Indeed, spinal cord injuries and diseases can affect the integrity of neurons, and induce neurological impairments and/or functional disabilities. While various treatment procedures exist, assessing the extent of damages and understanding the underlying mechanisms of diseases would improve treatment efficiency and clinical decisions. Over the last decades, magnetic resonance imaging (MRI) has demonstrated a high potential for the diagnosis and prognosis of spinal cord injury and neurodegenerative diseases. Particularly, template-based analysis of brain MRI data has been very helpful for the understanding of neurological diseases, using automated analysis of large groups of patients. However, extracting MRI information within specific regions of the spinal cord with minimum bias and using automated tools is still a challenge. Indeed, only a limited number of MRI template of the spinal cord exists, and none covers the full spinal cord, thereby preventing large multi-centric template-based analysis of the spinal cord. Moreover, no template integrates both the spinal cord and the brain region, thereby preventing simultaneous cerebrospinal studies. The objective of this project was to propose a new MRI template of the full spinal cord, which allows simultaneous brain and spinal cord studies, that integrates atlases of the spinal cord internal structures (e.g., white and gray matter, white matter pathways) and that comes with tools for extracting information within these subregions. More particularly, the general research question of the project was “How to create generic MRI templates of the spinal cord that would enable unbiased and reproducible template-based analysis of spinal cord MRI data?”. Several original contributions have been made to answer this question and to enable template-based analysis of spinal cord MRI data. The first contribution was the development of the Spinal Cord Toolbox (SCT), a comprehensive and open-source software for processing multi-parametric MRI data of the spinal cord (De Leener, Lévy, et al., 2016). SCT includes tools for the automatic segmentation of the spinal cord and its internal structure (white and gray matter), vertebral labeling, registration of multimodal MRI data (structural and non-structural) on a spinal cord MRI template (initially the MNI-Poly-AMU template, later the PAM50 template), co-registration of spinal cord MRI images, as well as the robust extraction of MRI metric within specific regions of the spinal cord (i.e., white and gray matter, white matter tracts, gray matter subregions) and specific vertebral levels using a spinal cord atlas (Lévy et al., 2015). Additional tools include robust motion correction and image processing along the spinal cord. Each tool included in SCT has been validated on a multimodal dataset. The second contribution of this project was the development of a novel registration method dedicated to spinal cord images, with an interest in the straightening of the spinal cord, while preserving its topology (De Leener, Mangeat et al., 2017). This method is based on the global approximation of the spinal cord and the analytical computation of deformation fields perpendicular to the centerline. Validation included calculation of distance measurements after straightening on a population of healthy subjects and patients with spinal cord compression. The major contribution of this project was the development of a framework for generating MRI template of the spinal cord and the PAM50 template, an unbiased and symmetrical MRI template of the brainstem and full spinal cord. Based on 50 healthy subjects, the PAM50 template was generated using an iterative nonlinear registration process, after applying normalization and straightening of all images. Pre-processing included segmentation of the spinal cord, manual delineation of the brainstem anterior edge, detection and identification of intervertebral disks, and normalization of intensity along the spinal cord. Next, the average centerline and vertebral distribution was computed to create an initial straight template space. Then, all images were registered to the initial template space and an iterative nonlinear registration framework was applied to create the final symmetrical template. The PAM50 covers the brainstem and the full spinal cord, from C1 to L2, is available for T1-, T2- and T2*-weighted contrasts, and includes probabilistic maps of the white and the gray matter and atlases of the white matter pathways and gray matter subregions. Additionally, the PAM50 template has been merged with the ICBM152 brain template, thereby allowing for simultaneous cerebrospinal template-based analysis. Finally, several complementary results, focused on clinical validation and applications, are presented. First, a reproducibility and repeatability study of cross-sectional area measurements using SCT (De Leener, Granberg, Fink, Stikov, & Cohen-Adad, 2017) was performed on a Multiple Sclerosis population (n=9). The results demonstrated the high reproducibility and repeatability of SCT and its ability to detect very subtle atrophy of the spinal cord. Second, a novel biomarker of spinal cord injury has been proposed. Based on the T2*-weighted intensity ratio between the white and the gray matter, this new biomarker is computed by registering MRI images with the PAM50 template and extracting metrics using probabilistic atlases. Additionally, the feasibility of extracting multiparametric MRI metrics from subregions of the spinal cord has been demonstrated and the diagnostic potential of this approach has been assessed on a degenerative cervical myelopathy (DCM) population. Finally, a method for extracting shape morphometrics along the spinal cord has been proposed, including spinal cord flattening, indentation and torsion. These metrics demonstrated high capabilities for the diagnostic of asymptomatic spinal cord compression (AUC=99.8% for flattening, 99.3% for indentation, and 98.4% for torsion). The development of the PAM50 template enables unbiased template-based analysis of the spinal cord. However, the PAM50 template has several limitations. Indeed, the proposed template has been generated with multimodal MRI images from 50 healthy and young individuals (age = 27+/- 6.5 y.o.). Therefore, the template is specific to this particular population and could not be directly usable for age- or disease-specific populations. One solution is to open-source the templategeneration code so that research groups can generate and use their own spinal cord MRI template. The code is available on https://github.com/neuropoly/template. While this project introduced a generic referential coordinate system, based on vertebral levels and the pontomedullary junction as origin, one limitation is the choice of this coordinate system. Another coordinate system, based spinal segments would be more suitable for functional analysis. However, the acquisition of MRI images with high enough resolution to delineate the spinal roots is still challenging. Finally, several challenges in the automation of spinal cord MRI processing remains, including the robust detection and identification of vertebral levels, particularly in case of small fields-of-view. This project introduced key developments for the analysis of spinal cord MRI data. Many more developments are still required to bring them into clinics and to improve our understanding of diseases affecting the spinal cord. Indeed, clinical applications require the improvement of the robustness and the automation of the proposed processing and analysis tools. Particularly, the detection and segmentation of spinal cord structures, including vertebral labeling and white/gray matter segmentation, is still challenging, given the lowest quality and resolution of standard clinical MRI acquisition. The tools developed and validated here have the potential to improve our understanding and the characterization of diseases affecting the spinal cord and will have a significant impact on the neuroimaging community