Deep Learning for Semi-Automated Brain Claustrum Segmentation on Magnetic Resonance (MR) Images

Title from PDF of title page viewed June 18, 2018Thesis advisor: Yugyung LeeVitaIncludes bibliographical references (pages 73-78)Thesis (M.S.)--School of Computing and Engineering. University of Missouri--Kansas City, 2018In recent years, Deep Learning (DL) has shown promising results with regard to conducting AI tasks such as computer vision and speech recognition. Specifically, DL demonstrated the state-of-the-art in computer vision tasks including image classification, segmentation, localization, and annotation. Convolutional Neural Network (CNN) models in DL have been applied to prevention, detection, and diagnosis in predictive medicine. Image segmentation plays a significant role in predictive medicine. However, there are huge challenges when performing DL-based automatic segmentation due to the nature of medical images such as heterogeneous modalities and formats, the very limited labeled training data, and the high-class imbalance in the labeled data. Furthermore, automatic segmentation becomes a challenging task, especially for Magnetic Resonance Images (MRI). In reality, it is a time- consuming procedure that requires trained biomedical experts to manually segment or annotate such MRI datasets. The need for automated segmentation or annotation is what motivates our work. In this thesis, we propose a semi-automated approach that aims to segment the claustrum in brain MRI images. We recognize that the claustrum is an information hub of human brains and can be used to find significant patterns from the segmentations. We applied a 2-Dimensional CNN model called U-net to segment the human brain dataset comprising 30 manually annotated subjects provided to us by the Department of Psychiatry at the University of Missouri-Kansas City. Our approach consisted of the following steps: (1) preprocessing, including converting, the data into Digital Imaging and Communications in Medicine (DICOM), re-sampling and selecting the claustrum slices, and applying an ROI selection; (2) building the claustrum model; (3) automatic segmentation; and (4) evaluation and validation. For the model validation, we used the cross-validation technique with n = 5. We administered the Dice coefficient index to evaluate the results and we achieved a Dice score of approximately 70%. A domain expert also evaluated the results.Introduction -- Background -- Related work -- Proposed solutions -- Proposed model application -- Conclusion and future wor

The nonhuman primate neuroimaging and neuroanatomy project

Multi-modal neuroimaging projects such as the Human Connectome Project (HCP) and UK Biobank are advancing our understanding of human brain architecture, function, connectivity, and their variability across individuals using high-quality non-invasive data from many subjects. Such efforts depend upon the accuracy of non-invasive brain imaging measures. However, ‘ground truth’ validation of connectivity using invasive tracers is not feasible in humans. Studies using nonhuman primates (NHPs) enable comparisons between invasive and non-invasive measures, including exploration of how “functional connectivity” from fMRI and “tractographic connectivity” from diffusion MRI compare with long-distance connections measured using tract tracing. Our NonHuman Primate Neuroimaging & Neuroanatomy Project (NHP_NNP) is an international effort (6 laboratories in 5 countries) to: (i) acquire and analyze high-quality multi-modal brain imaging data of macaque and marmoset monkeys using protocols and methods adapted from the HCP; (ii) acquire quantitative invasive tract-tracing data for cortical and subcortical projections to cortical areas; and (iii) map the distributions of different brain cell types with immunocytochemical stains to better define brain areal boundaries. We are acquiring high-resolution structural, functional, and diffusion MRI data together with behavioral measures from over 100 individual macaques and marmosets in order to generate non-invasive measures of brain architecture such as myelin and cortical thickness maps, as well as functional and diffusion tractography-based connectomes. We are using classical and next-generation anatomical tracers to generate quantitative connectivity maps based on brain-wide counting of labeled cortical and subcortical neurons, providing ground truth measures of connectivity. Advanced statistical modeling techniques address the consistency of both kinds of data across individuals, allowing comparison of tracer-based and non-invasive MRI-based connectivity measures. We aim to develop improved cortical and subcortical areal atlases by combining histological and imaging methods. Finally, we are collecting genetic and sociality-associated behavioral data in all animals in an effort to understand how genetic variation shapes the connectome and behavior

Dopaminergic dysfunction in neurodevelopmental disorders: recent advances and synergistic technologies to aid basic research

Neurodevelopmental disorders (NDDs) represent a diverse group of syndromes characterized by abnormal development of the central nervous system and whose symptomatology includes cognitive, emotional, sensory, and motor impairments. The identification of causative genetic defects has allowed for creation of transgenic NDD mouse models that have revealed pathophysiological mechanisms of disease phenotypes in a neural circuit- and cell type-specific manner. Mouse models of several syndromes, including Rett syndrome, Fragile X syndrome, Angelman syndrome, Neurofibromatosis type 1, etc., exhibit abnormalities in the structure and function of dopaminergic circuitry, which regulates motivation, motor behavior, sociability, attention, and executive function. Recent advances in technologies for functional circuit mapping, including tissue clearing, viral vector-based tracing methods, and optical readouts of neural activity, have refined our knowledge of dopaminergic circuits in unperturbed states, yet these tools have not been widely applied to NDD research. Here, we will review recent findings exploring dopaminergic function in NDD models and discuss the promise of new tools to probe NDD pathophysiology in these circuits

Dopaminergic dysfunction in neurodevelopmental disorders: recent advances and synergistic technologies to aid basic research

Neurodevelopmental disorders (NDDs) represent a diverse group of syndromes characterized by abnormal development of the central nervous system and whose symptomatology includes cognitive, emotional, sensory, and motor impairments. The identification of causative genetic defects has allowed for creation of transgenic NDD mouse models that have revealed pathophysiological mechanisms of disease phenotypes in a neural circuit- and cell type-specific manner. Mouse models of several syndromes, including Rett syndrome, Fragile X syndrome, Angelman syndrome, Neurofibromatosis type 1, etc., exhibit abnormalities in the structure and function of dopaminergic circuitry, which regulates motivation, motor behavior, sociability, attention, and executive function. Recent advances in technologies for functional circuit mapping, including tissue clearing, viral vector-based tracing methods, and optical readouts of neural activity, have refined our knowledge of dopaminergic circuits in unperturbed states, yet these tools have not been widely applied to NDD research. Here, we will review recent findings exploring dopaminergic function in NDD models and discuss the promise of new tools to probe NDD pathophysiology in these circuits

Joint registration and synthesis using a probabilistic model for alignment of MRI and histological sections

Nonlinear registration of 2D histological sections with corresponding slices of MRI data is a critical step of 3D histology reconstruction. This task is difficult due to the large differences in image contrast and resolution, as well as the complex nonrigid distortions produced when sectioning the sample and mounting it on the glass slide. It has been shown in brain MRI registration that better spatial alignment across modalities can be obtained by synthesizing one modality from the other and then using intra-modality registration metrics, rather than by using mutual information (MI) as metric. However, such an approach typically requires a database of aligned images from the two modalities, which is very difficult to obtain for histology/MRI. Here, we overcome this limitation with a probabilistic method that simultaneously solves for registration and synthesis directly on the target images, without any training data. In our model, the MRI slice is assumed to be a contrast-warped, spatially deformed version of the histological section. We use approximate Bayesian inference to iteratively refine the probabilistic estimate of the synthesis and the registration, while accounting for each other's uncertainty. Moreover, manually placed landmarks can be seamlessly integrated in the framework for increased performance. Experiments on a synthetic dataset show that, compared with MI, the proposed method makes it possible to use a much more flexible deformation model in the registration to improve its accuracy, without compromising robustness. Moreover, our framework also exploits information in manually placed landmarks more efficiently than MI, since landmarks inform both synthesis and registration - as opposed to registration alone. Finally, we show qualitative results on the public Allen atlas, in which the proposed method provides a clear improvement over MI based registration

GAMMA KNIFE RADIOSURGERY OF THE VIM: FROM THE LESIONAL EFFECT TOWARDS NEUROMODULATION

Gamma Knife radiosurgery (GKR) is a neurosurgical stereotactic procedure, combining image guidance, with high-precision convergence of multiple gamma rays, currently emitted by 192 sources of Cobalt-60 (Leksell Gamma Knife ICON®, Elekta Instruments, AB, Sweden). The intimate mechanisms of action are not all very well understood and vary according to the treated pathological condition. In functional disorders, GKR is used either to target a specific anatomical point [e.g. thalamus- ventro-intermediate nucleus (Vim) for tremor] or to target a larger zone, such as an epileptic focus. The present thesis focuses on Vim GKR for drug-resistant essential tremor (ET). Essential tremor is the most common movement disorder, with the predominant clinical finding being kinetic tremor of the arms. Radiosurgery (RS) has several limitations in this indication: (1) indirect targeting (Vim is not visible on current MR acquisitions), with (2) no intraoperative confirmation of the target, (3) delayed clinical effect, (4) inability to predict the radiological response and a (5) lack of understanding of its radiobiological effect. Moreover, despite a standard radiosurgical procedure, there is a variability of clinical effect, with a lower efficacy rate as compared to standard deep-brain stimulation, the reference technique. Gamma Knife radiosurgery has no access to tissue analysis, and targeting and follow-up evaluation are based only on neuroimaging. We addressed the limitation of the indirect targeting by using high-field 7 Tesla (T) MRI, and combining multimodal imaging for Vim definition, at both 3 and 7 T. The central core of this thesis was the understanding of radiobiology of RS for tremor, using both structural [e.g. T1 weighted (T1-w), voxel-based morphometry (VBM)] and functional resting- state functional MRI (rs-fMRI). We aimed for a direct Vim visualization using ultra-high field 7 T. The former allows an increased signal to noise ratio, an improved spatial resolution, as well as a superior sensitivity to magnetic susceptibility engendered contrast. Susceptibility-weighted images (SWI) might be an important step to allow a direct visualization of thalamic subparts (including the Vim). We explored 7T SWI advantages, which were done in a qualitative manner. We combined several different methodologies for Vim definition (in healthy subjects of different ages): manual delineation on 7T, quadrilatere of Guiot used in common clinical practice and automated segmentation based on diffusion weighted imaging and atlases (last two performed by and in collaboration with Dr Najdenovska). We concluded that although 7T SWI, alone or in combination with other neuroimaging modalities, is useful, several limitations need to be overcome yet, precluding a standardization of a direct Vim visualization, with the current state-of- the art. The T1-w and rs-fMRI based studies analyzed the radiobiology effects of Vim GKR for intractable tremor and led to several important contributions. The most relevant and novel was the presence of a visually-sensitive structural and functional network, involved in tremor generation and further arrest after Vim GKR. The patients with this network more integrated pretherapeutically benefited more from RS. The candidate had shaped the term “cerebello- thalamo-cortical” into the “cerebello-thalamo-visuo-motor” network, as a step forward in the understanding of essential tremor’s pathophysiology. Two structures were proposed as main calibrators of this network, in the light of the present thesis: the cerebellum (as the most probable) versus the thalamus itself. Moreover, a more classical basal ganglia network, interconnected with a salience one, as well as a cerebellar, interconnected with the motor and visual one, were reported. Other longitudinal changes involved dorsal attention, insular or supplementary motor area circuitries. Particular phenotypes of ET, including patients with head tremor, were analyzed and discussed. As a perspective and future work, in progress, the dynamics of the extrastriate cortex was further analyzed, using co-activation patterns. -- La radio-neurochirurgie par Gamma Knife (GK) est une procédure de neurochirurgie stéréotaxique, combinant l’utilisation d’une imagerie multimodale, avec la convergence de multiples rayons Gamma émis par 192 sources of Cobalt-60 (Leksell Gamma Knife ICON®, Elekta Instruments, AB, Suède). Ses mécanismes pathophysiologiques ne sont pas complètement élucidés et varient selon la condition traitée. Lors des procédures fonctionnelles, le GK est utilisé pour irradier avec une haute précision, soit un point précis (par exemple, le noyau ventro- intermediare, Vim, du thalamus pour le tremblement), soit une zone plus large, comme un foyer d’épilepsie. La présente thèse a comme sujet principal la radiochirugie du Vim (RC du Vim) pour le tremblement essentiel (TE). Le TE est un des mouvements anormaux le plus commun, manifesté principalement avec un tremblement d’action de la main. Toutefois, la RC du Vim a plusieurs limitations: (1) le ciblage est indirect (le Vim n’est pas visible sur les séquences IRM classiques), (2) elle ne permet pas la confirmation électrophysiologique de la cible, (3) l’effet clinique est délayé dans le temps, (4) la réponse radiologique est difficile à prédire et, (5) il manque une compréhension claire de son effet radiobiologique. De plus, malgré le fait que la procédure soit standardisée, il y a une variabilité de son effet clinique. La RC ne permet pas d’analyser le tissu et, le ciblage ainsi que le suivi, sont réalisés uniquement sur la base de la neuroimagerie. Nous avons analysé la limitation du ciblage indirect en utilisant l’IRM à haut champs [7 Tesla (T)] et en la combinant avec une imagerie multimodale, incluant des séquences 3T et 7T, pour la définition du Vim. La partie centrale de la thèse se focalise sur la compréhension de l’effet radiobiologique de la RC du Vim dans le TE. Cette partie se base tant de l’analyse de l’imagerie structurelle (séquence classique T1) que sur l’imagerie fonctionnelle (IRM de repos). Le but de la première partie de la thèse est la visualisation directe du Vim en utilisant l’IRM 7T, qui a plusieurs avantages par rapport à l’IRM 3T, y compris une meilleure résolution spatiale. Notamment, la séquence SWI a un intérêt particulier, mais elle n’avait encore jamais été explorée que de manière quantitative au niveau du thalamus (qui contient le Vim). Nous avons combinée plusieurs modalités pour définir le Vim (chez des sujets sains de différents âges): visualisation directe sur la 7T, quadrilatère de Guiot tel qu’utilisé en pratique clinique courante, ainsi que segmentation automatique en imagerie de diffusion ou par des atlas (ces dernières deux approches ont été réalisées par, et en collaboration avec, Dr Najdenovska). Nous avons conclu que la séquence 7T SWI, malgré certains avantages, et utilisée seule ou combinée avec d’autres modalités, présente certaines limitations qui ne permettent pas, à l’heure actuelle, de l’utiliser d’une manière standardisée, tant chez les sujets sains que chez les patients atteints de TE. Dans la deuxième partie, l’étude de la radiobiologie de la radiochirugie pour le TE a permis d’apporter plusieurs contributions. La plus importante est la mise en évidence d’un « réseau visuel » structurel et fonctionnel, impliqué dans la genèse du tremblement et dans son amélioration après une RC du Vim. Les patients dont ce réseau est mieux intégré avant la procédure ont de meilleures chances d’amélioration clinique du TE. Dans ce contexte, nous avons proposé d’adapter le terme classique d’ «axe cérébello-thalamo-moteur» en le modifiant en « axe cérébello-thalamo-visuo-moteur», ce qui pourrait aider à une meilleure compréhension de la pathophysiologie du TE. Nous proposons également que deux structures puissent jouer le rôle de neuromodulateur de ce réseau, le cervelet et le thalamus. Une autre contribution est la description de l’interconnexion entre le réseau classique impliquant les noyaux de la base et celui l’attention, ainsi que de l’interconnexion entre le réseau cérébelleux et celui des cortex moteur primaire et visuel associatif. Des phénotypes particuliers du tremblement ont été analysés, incluant par exemple des tremblements du chef. Des travaux en cours incluent l’étude de la dynamique du cortex extra-strié en utilisant de nouvelles approches, comme les patterns de co-activation

Investigation of Memory Related Cortical Thalamic Circuitry in the Human Brain

This dissertation examined the role of medial prefrontal cortex (mPFC) and the hippocampus (HC) in episodic memory, and provides a novel approach to identify the midline thalamus mediating mPFC-HC interactions in humans. The mPFC and HC are critical to the temporal organization of episodic memory, and these interactions are disrupted in several mental health and neurological disorders. In the first study, I provide evidence that the mPFC is involved in ordinal retrieval, and the HC is active in temporal context retrieval in remembering the order of when events happen. In the second study, I focus on the anatomical basis of the mPFC-HC interactions which is reliant on the midline thalamus. I review in detail the anatomy of the midline thalamus both in location, and connectivity profile with the rest of the brain comparing the extensive anatomical evidence in rodents with the available evidence in monkeys and humans. This section also elaborates on the role of the midline thalamus in memory, stress regulation, wakefulness, and feeding behavior, and how pathological markers along the midline thalamus are a vanguard of several neurological disorders including Alzheimer’s Disease, schizophrenia, depression, and drug addiction. Lastly, I devised a new approach to identify the midline thalamus in humans in vivo using diffusion weighted imaging, capitalizing on known fiber connections gleaned from non-human animals, focusing on connections between the midline thalamus and the mPFC, medial temporal lobe and the nucleus accumbens. The success of this approach is promising for translational imaging. Overall, this dissertation provides new evidence on 1) complementary functional roles of the mPFC and HC in sequence memory, 2) a cross-species anatomical framework for understanding the midline thalamus in humans and neurological disorders, and 3) a new method for non-invasive identification of the midline thalamus in humans in vivo. Thus, this dissertation provides a new fundamental understanding of mPFC-midline thalamic-HC circuit in humans and tools for its non-invasive study in human disease

Sex-specific association between infant caudate volumes and a polygenic risk score for major depressive disorder

Polygenic risk scores for major depressive disorder (PRS-MDD) have been identified in large genome-wide association studies, and recent findings suggest that PRS-MDD might interact with environmental risk factors to shape human limbic brain development as early as in the prenatal period. Striatal structures are crucially involved in depression; however, the association of PRS-MDD with infant striatal volumes is yet unknown. In this study, 105 Finnish mother-infant dyads (44 female, 11-54 days old) were investigated to reveal how infant PRS-MDD is associated with infant dorsal striatal volumes (caudate, putamen) and whether PRS-MDD interacts with prenatal maternal depressive symptoms (Edinburgh Postnatal Depression Scale, gestational weeks 14, 24, 34) on infant striatal volumes. A robust sex-specific main effect of PRS-MDD on bilateral infant caudate volumes was observed. PRS-MDD were more positively associated with caudate volumes in boys compared to girls. No significant interaction effects of genotype PRS-MDD with the environmental risk factor "prenatal maternal depressive symptoms" (genotype-by-environment interaction) nor significant interaction effects of genotype with prenatal maternal depressive symptoms and sex (genotype-by-environment-by-sex interaction) were found for infant dorsal striatal volumes. Our study showed that a higher PRS-MDD irrespective of prenatal exposure to maternal depressive symptoms is associated with smaller bilateral caudate volumes, an indicator of greater susceptibility to major depressive disorder, in female compared to male infants. This sex-specific polygenic effect might lay the ground for the higher prevalence of depression in women compared to men.Peer reviewe