Assisted Diagnosis of Parkinsonism Based on the Striatal Morphology

Parkinsonism is a clinical syndrome characterized by the progressive loss of striatal dopamine. Its diagnosis is usually corroborated by neuroimaging data such as DaTSCAN neuroimages that allow visualizing the possible dopamine deficiency. During the last decade, a number of computer systems have been proposed to automatically analyze DaTSCAN neuroimages, eliminating the subjectivity inherent to the visual examination of the data. In this work, we propose a computer system based on machine learning to separate Parkinsonian patients and control subjects using the size and shape of the striatal region, modeled from DaTSCAN data. First, an algorithm based on adaptative thresholding is used to parcel the striatum. This region is then divided into two according to the brain hemisphere division and characterized with 152 measures, extracted from the volume and its three possible 2-dimensional projections. Afterwards, the Bhattacharyya distance is used to discard the least discriminative measures and, finally, the neuroimage category is estimated by means of a Support Vector Machine classifier. This method was evaluated using a dataset with 189 DaTSCAN neuroimages, obtaining an accuracy rate over 94%. This rate outperforms those obtained by previous approaches that use the intensity of each striatal voxel as a feature.This work was supported by the MINECO/ FEDER under the TEC2015-64718-R project, the Ministry of Economy, Innovation, Science and Employment of the Junta de Andaluc´ıa under the P11-TIC-7103 Excellence Project and the Vicerectorate of Research and Knowledge Transfer of the University of Granada

Tissue microstructural changes in dementia with Lewy bodies revealed by quantitative MRI.

We aimed to characterize dementia with Lewy bodies (DLB) by the quantitative MRI parameters of longitudinal relaxation time (qT1) and transverse relaxation time (qT2). These parameters reflect potential pathological changes in tissue microstructures, which may be detectable noninvasively in brain areas without evident atrophy, so may have potential value in revealing the early neuropathological changes in DLB. We conducted a cross-sectional study of subjects with DLB (N = 35) and similarly aged control participants (N = 35). All subjects underwent a detailed clinical and neuropsychological assessment and structural and quantitative 3T MRI. Quantitative MRI maps were obtained using relaxation time mapping methods. Statistical analysis was performed on gray matter qT1 and qT2 values. We found significant alterations of quantitative parameters in DLB compared to controls. In particular, qT1 decreases in bilateral temporal lobes, right parietal lobes, basal ganglia including left putamen, left caudate nucleus and left amygdala, and left hippocampus/parahippocampus; qT2 decreases in left putamen and increases in left precuneus. These regions showed only partial overlap with areas where grey matter loss was found, making atrophy an unlikely explanation for our results. Our findings support that DLB is predominantly associated with changes in posterior regions, such as visual association areas, and subcortical structures, and that qT1 and qT2 measurement can detect subtle changes not seen on structural volumetric imaging. Hence, quantitative MRI may compliment other imaging techniques in detecting early changes in DLB and in understanding neurobiological changes associated with the disorder.This is the author accepted manuscript. The final version is available from Springer via http://dx.doi.org/10.1007/s00415-014-7541-

Morphometric analysis of subcortical structures in progressive supranuclear palsy: In vivo evidence of neostriatal and mesencephalic atrophy

Progressive supranuclear palsy (PSP) is a neurodegenerative disease characterized by gait and postural disturbance, gaze palsy, apathy, decreased verbal fluency and dysexecutive symptoms, with some of these clinical features potentially having origins in degeneration of frontostriatal circuits and the mesencephalon. This hypothesis was investigated by manual segmentation of the caudate and putamen on MRI scans, using previously published protocols, in 15 subjects with PSP and 15 healthy age-matched controls. Midbrain atrophy was assessed by measurement of mid-sagittal area of the midbrain and pons. Shape analysis of the caudate and putamen was performed using spherical harmonics (SPHARM-PDM, University of North Carolina). The sagittal pons area/midbrain area ratio (P/M ratio) was significantly higher in the PSP group, consistent with previous findings. Significantly smaller striatal volumes were found in the PSP group - putamina were 10% smaller and caudate volumes were 17% smaller than in controls after controlling for age and intracranial volume. Shape analysis revealed significant shape deflation in PSP in the striatum, compared to controls; with regionally significant change relevant to frontostriatal and corticostriatal circuits in the caudate. Thus, in a clinically diagnosed and biomarker-confirmed cohort with early PSP, we demonstrate that neostriatal volume and shape are significantly reduced in vivo. The findings suggest a neostriatal and mesencephalic structural basis for the clinical features of PSP leading to frontostriatal and mesocortical-striatal circuit disruption. (C) 2011 Elsevier Ireland Ltd. All rights reserved

Theoretical and experimental considerations of selective vulnerability In Parkinson's disease

Les maladies neurodégénératives sont typiquement caractérisées en fonction de leurs symptômes et des observations pathologiques effectuées après le décès. Les symptômes spécifiques à la maladie sont également normalement associés aux dysfonctionnements et à la dégénérescence de certaines sous- populations spécifiques de neurones dans le système nerveux. La maladie de Parkinson (MP) est une maladie neurodégénérative principalement caractérisée par des symptômes moteurs dus à la dégénérescence spécifique des neurones dopaminergiques (DA) de la substantia nigra pars compacta (SNpc/SNc). Il semble cependant que les neurones DA de la SNc ne soient pas la seule population de neurones qui dégénère dans la MP. L'analyse post-mortem, l'imagerie in vivo et les symptômes cliniques démontrent que le dysfonctionnement et la dégénérescence se produisent dans plusieurs autres régions du système nerveux, incluant par exemple des neurones noradrénergiques (NA) du locus coeruleus (LC), des neurones sérotoninergiques des noyaux du raphé et des neurones cholinergiques du noyau moteur dorsal du nerf vague (DMV) et du noyau pédonculopontin. Comme d'autres maladies neurodégénératives, la MP est causée par plusieurs facteurs, tant génétiques qu'environnementaux. De nombreuses observations suggèrent que ces facteurs soient associés au dysfonctionnement de plusieurs systèmes ou fonctions cellulaires incluant la production d’énergie par la mitochondrie, l’élimination de protéines dysfonctionnelles par le protéasome et le lysosome, la régulation de l’équilibre entre la production d'espèces oxydatives réactives et les mécanismes antioxydants, la régulation des niveaux de calcium intracellulaire et l’inflammation. Il semble donc que le dysfonctionnement de ces facteurs converge pour provoquer la dégénérescence neuronale dans le contexte du vieillissement. Ce qui rend les neurones de certaines régions du système nerveux intrinsèquement plus vulnérables aux facteurs associés à la MP est une question fondamentale qui n’est pas résolue pour le moment. Les travaux de cette thèse sont basés sur l’hypothèse proposant que cette vulnérabilité sélective découle de propriétés communes retrouvées chez les neurones vulnérables. En particulier, les neurones vulnérables auraient en commun d’être des neurones de projections dotés d’un axone complexe qui projette sur de longues distances, formant un nombre très élevé de terminaisons axonales sur de vastes territoires du système nerveux. De plus, ces neurones présenteraient des propriétés physiologiques distinctives, incluant notamment une décharge autonome (pacemaker). Ensemble, ces caractéristiques pourraient contribuer à placer ces neurones dans des conditions de fonctionnement aux limites de leur capacités bioénergétiques et homéostatiques, rendant difficile toute adaptation aux dysfonctionnements cellulaires associés au vieillissement et causés par les facteurs de risques de la MP. Dans cette thèse, je présenterai une revue systématique de la littérature sur la perte de neurones dans le cerveau des personnes atteintes de la maladie de Parkinson, montrant que l'identité neurochimique précise des neurones qui dégénèrent dans la maladie de Parkinson, et l'ordre temporel dans lequel cela se produit, n’est pas clair. Cependant, en analysant les points de vue présentés dans les publications citant cette revue, nous avons remarqué que la majorité de ceux-ci ne reflètent pas le message central de notre publication. Puisque l’identification de l’identité des neurones vulnérables et non vulnérables à la MP est fondamentale pour le développement de théories et hypothèses sur les causes de la MP, nous suivons cette première publication avec une lettre réaffirmant l'importance de faire face aux problèmes identifiés dans notre revue. Nous présentons ensuite des données in vitro montrant que les neurones vulnérables à la MP, comparés à ceux qui sont moins vulnérables, ont une capacité intrinsèque à développer des champs axonaux plus importants et plus complexes, avec un nombre plus élevé de sites actifs de libération de neurotransmetteurs. De plus, nous constatons que ces observations sont corrélées à une vulnérabilité plus élevée face à un stress oxydatif pertinent pour la MP. Ces données sont en accord avec l'hypothèse selon laquelle le domaine axonal, et en particulier le nombre de sites de libération de neurotransmetteurs par neurone, est un facteur important qui contribue à rendre un neurone sélectivement vulnérable dans le contexte de la MP. Enfin, nous présentons une méthode d’analyse d’image open-source visant à aider les biologistes et les neuroscientifiques à automatiser la quantification du nombre de neurones dans des cultures primaires de neurones, telle qu’utilisée dans les travaux de cette thèse. Nous proposons que cet algorithme simple — mais robuste — permettra aux biologistes d'automatiser le comptage des neurones avec une grande précision, quelque chose de difficile à effectuer avec les autres approches open-source disponibles présentement. Nous espérons que les travaux présentés dans cette thèse permettront de contribuer à raffiner les théories visant à expliquer l’origine de la MP et à terme, de développer de nouvelles approches thérapeutiques.Neurodegenerative diseases are typically characterized based on their symptoms, and pathological factors identified after death. The disease-specific symptoms are due to the dysfunction and degeneration of specific subpopulations of neurons, which cause dysfunction in particular brain functions. Parkinson's disease (PD) is a neurodegenerative disease primarily characterized by motor symptoms due to the specific degeneration of dopamine (DA) neurons of the substantia nigra pars compacta (SNpc/SNc): a population of neurons essential for motor control. SNc DA neurons are, however, not the only population of neurons that degenerate in PD. Post-mortem analysis, in vivo imaging, and clinical symptoms demonstrate that dysfunction and degeneration occur in several other neuronal nuclei. These include, but are not limited to, noradrenergic (NA) locus coeruleus (LC) neurons, serotonin neurons of the raphe nuclei, and cholinergic neurons of the dorsal motor nucleus of the vagus (DMV) and pedunculopontine nucleus. Like other neurodegenerative diseases, PD is linked to several risk factors, both genetic and environmental. The evidence suggests that these risk factors are associated with the dysfunction in systems of cellular bioenergetics (including mitochondrial function); proteostatic homeostasis; endolysosomal function; an imbalance between the production of reactive oxidative species (ROS), and antioxidant mechanisms; calcium homeostasis; alpha-synuclein misfolding; and neuroinflammation. Consequently, together with aging, these risk factors converge on causing the selective degeneration of "PD-vulnerable" nuclei. What makes these neurons intrinsically vulnerable to PD-associated risk factors is a fundamental question — and understanding these neurons will reveal biological mechanisms that we can target to protect these cells from degeneration. Our best hypotheses to explain why these neurons are based on the observations that most PD- vulnerable neurons are long-range projection neuromodulatory neurons sharing common characteristics: projecting to voluminous territories, having very long and highly branched unmyelinated axonal domains with vast numbers of neurotransmitter release sites, and exhibiting a unique physiology such as pacemaker firing. Taken together, this suggests that these neurons function at the tail-end of their bioenergetic and homeostatic capacity, unable to tolerate any further demands, such as those incurred in the presence of risk factors associated with PD. In this thesis, I will present a systematic review on the literature on purported cell loss in PD brains, showing that — given the actual primary evidence — the precise neurochemical identity of neurons that degenerate in PD, and the temporal order of this degeneration, is far less clear than described by most publications. This review — at the time of writing — has gone on to be highly cited. However, analyzing the claims made in publications citing this review, we discover that the majority of claims do not reflect the core message of our publication. Since the identity of PD-vulnerable and non-PD-vulnerable neurons is fundamental to theory and hypotheses when trying to understand PD, we follow this first publication with a letter restating the importance to address our observations. We then present in vitro data showing that classically PD-vulnerable neurons, when compared to non-PD vulnerable neurons, have an intrinsic capacity to develop larger and more complex axonal domains, with higher numbers of active neurotransmitter release sites. Moreover, we find that these observations correlate to elevated vulnerability to PD-relevant stress assays. These data provide additional support for the hypothesis that the axonal domain — and in particular — the number of active neurotransmitter sites per neuron, is a cell-autonomous factor rendering a neuron selectively vulnerable in the context of PD. Finally, we present an open-source tool to support biologists and neuroscientists in automating the quantification of neuron numbers in medium-throughput primary cell cultures. Where the application of other open-source solutions is either too simplistic for the use-case or technically challenging to implement, this simple — yet robust algorithm — allows biologists with limited computational nous to automate neuron counting with high precision. We hope that the work presented in this thesis will contribute to the refinement of theories aimed at explaining the origin of PD and, ultimately, to the development of new therapeutic approaches

The Locus coeruleus in Parkinson’s disease - from basic research to new translational perspectives -

This cumulative dissertation summarizes three peer-reviewed publications addressing different aspects of the prodromal and manifest phase of Parkinson’s disease with special emphasis on the vulnerability of the noradrenergic locus coeruleus. The first publication represents an original article describing the establishment and characterization of the first ever α-synuclein overexpression mouse model for the locus coeruleus. Narrative articles two and three discuss the importance of the locus coeruleus in context of prodromal Parkinson’s disease, and the heterogeneity of the affected mesencephalic and extramesencephalic dopaminergic systems in manifest Parkinson’s disease. The first publication entitled “A53T-α-synuclein overexpression in murine locus coeruleus induces Parkinson’s disease-like pathology in neurons and glia” describes the establishment of the first locus coeruleus α-synucleinopathy mouse model. The data show that viral vector mediated focal overexpression of human A53T-α-synuclein triggered time-dependent neurodegeneration of noradrenergic locus coeruleus neurons, accompanied by progressive α-synuclein phosphorylation, formation of proteinase K-resistant α-synuclein-aggregates, accumulation of Ubi-1- and p62-positive inclusions in microglial cells and induction of progressive micro- and astrogliosis. Apart from this local pathology, we observed abundant α-synuclein positive axons in LC output regions, indicating rapid anterograde axonal transport of A53T-α-synuclein. The second publication entitled “The locus coeruleus – another vulnerability target in Parkinson’s disease” addresses the role of the locus coeruleus noradrenergic system in prodromal and manifest Parkinson’s disease. Within this review we provide a comprehensive description of the neuroanatomical basis of the locus coeruleus system and its implication in Parkinson’s disease, summarize highly relevant vulnerability factors, and list all animal studies conducted so far investigating locus coeruleus pathology in experimental research. Further, we provide a therapeutic outlook on how noradrenergic replacement therapy has already been successfully tested in manifest Parkinson’s disease patients and how locus coeruleus dysfunction can be of use for the development of disease modifying therapy approaches and disease progression biomarkers. Within the third publication entitled “Mesencephalic and extramesencephalic dopaminergic systems in Parkinson’s disease”, we provide a historical overview over the key milestones of Parkinson’s disease pathogenesis and therapy, dissect the dopaminergic basis of the cardinal parkinsonian motor symptomatology, summarize the anatomical features of the ten dopaminergic systems of the mammalian central nervous system and their involvement in Parkinson’s disease, illustrate how the advanced dopaminergic imaging techniques contribute to optimized differential diagnosis and pathogenetic knowledge, and explain how dopaminergic replacement therapy improves the cardinal motor symptomatology while simultaneously inducing a new set of symptoms based on a hyperdopaminergic status

Looking beneath the surface: the importance of subcortical structures in frontotemporal dementia.

Funder: National Institute for Health Research (NIHR) Queen Square Dementia Biomedical Research UnitFunder: Alzheimer's Research UK, Brain Research Trust and The Wolfson FoundationFunder: Medical Research CouncilFunder: Alzheimer’s Society and Alzheimer’s Research UKFunder: NIHR UCL/H Biomedical Research Centre and the Leonard Wolfson Experimental Neurology Centre (LWENC) Clinical Research FacilityFunder: DRI LtdWhilst initial anatomical studies of frontotemporal dementia focussed on cortical involvement, the relevance of subcortical structures to the pathophysiology of frontotemporal dementia has been increasingly recognized over recent years. Key structures affected include the caudate, putamen, nucleus accumbens, and globus pallidus within the basal ganglia, the hippocampus and amygdala within the medial temporal lobe, the basal forebrain, and the diencephalon structures of the thalamus, hypothalamus and habenula. At the most posterior aspect of the brain, focal involvement of brainstem and cerebellum has recently also been shown in certain subtypes of frontotemporal dementia. Many of the neuroimaging studies on subcortical structures in frontotemporal dementia have been performed in clinically defined sporadic cases. However, investigations of genetically- and pathologically-confirmed forms of frontotemporal dementia are increasingly common and provide molecular specificity to the changes observed. Furthermore, detailed analyses of sub-nuclei and subregions within each subcortical structure are being added to the literature, allowing refinement of the patterns of subcortical involvement. This review focuses on the existing literature on structural imaging and neuropathological studies of subcortical anatomy across the spectrum of frontotemporal dementia, along with investigations of brain-behaviour correlates that examine the cognitive sequelae of specific subcortical involvement: it aims to 'look beneath the surface' and summarize the patterns of subcortical involvement have been described in frontotemporal dementia

Improving nuclear medicine with deep learning and explainability: two real-world use cases in parkinsonian syndrome and safety dosimetry

Computer vision in the area of medical imaging has rapidly improved during recent years as a consequence of developments in deep learning and explainability algorithms. In addition, imaging in nuclear medicine is becoming increasingly sophisticated, with the emergence of targeted radiotherapies that enable treatment and imaging on a molecular level (“theranostics”) where radiolabeled targeted molecules are directly injected into the bloodstream. Based on our recent work, we present two use-cases in nuclear medicine as follows: first, the impact of automated organ segmentation required for personalized dosimetry in patients with neuroendocrine tumors and second, purely data-driven identification and verification of brain regions for diagnosis of Parkinson’s disease. Convolutional neural network was used for automated organ segmentation on computed tomography images. The segmented organs were used for calculation of the energy deposited into the organ-at-risk for patients treated with a radiopharmaceutical. Our method resulted in faster and cheaper dosimetry and only differed by 7% from dosimetry performed by two medical physicists. The identification of brain regions, however was analyzed on dopamine-transporter single positron emission tomography images using convolutional neural network and explainability, i.e., layer-wise relevance propagation algorithm. Our findings confirm that the extra-striatal brain regions, i.e., insula, amygdala, ventromedial prefrontal cortex, thalamus, anterior temporal cortex, superior frontal lobe, and pons contribute to the interpretation of images beyond the striatal regions. In current common diagnostic practice, however, only the striatum is the reference region, while extra-striatal regions are neglected. We further demonstrate that deep learning-based diagnosis combined with explainability algorithm can be recommended to support interpretation of this image modality in clinical routine for parkinsonian syndromes, with a total computation time of three seconds which is compatible with busy clinical workflow. Overall, this thesis shows for the first time that deep learning with explainability can achieve results competitive with human performance and generate novel hypotheses, thus paving the way towards improved diagnosis and treatment in nuclear medicine

Anatomical, Biological, and Surgical Features of Basal Ganglia

Basal ganglia refers to the deep gray matter masses on the deeply telencephalon and encompasses a group of nuclei and it influence the information in the extrapyramidal system. In human they are related with numerous significant functions controlled by the nervous system. Gross anatomically, it is comprised of different parts as the dorsal striatum that are consisted of the caudate nucleus and putamen and ventral striatum which includes the nucleus accumbens, olfactory tubercle, globus pallidus, substantia nigra, and subthalamic nucleus. Nucleus accumbens, is also associated with reward circuits and has two parts; the nucleus accumbens core and the nucleus accumbens shell. Neurological diseases are characterized through the obvious pathology of the basal ganglia, and there are important findings explaining striatal neurodegeneration on human brain. Some of these diseases are induced by bacterial and/or viral infections. Surgical interference can be one alternative for neuronal disease treatment like Parkinson’s Disease or Thiamine Responsive Basal Ganglia Disease or Wilson’s Disease, respectively in addition to the vascular or tumor surgery within this area. Extensive knowledge on the morphological basis of diseases of the basal ganglia along with motor, behavioral and cognitive symptoms can contribute significantly to the optimization of the diagnosis and later patient’s treatment

In vivo assessment of non-dopaminergic systems in Parkinson’s disease with Positron Emission Tomography

Parkinson's disease (PD) is characterized by a progressive loss of nigrostriatal dopaminergic neurons. Non-dopaminergic neurotransmission is also impaired. Intraneuronal Lewy bodies, the pathological hallmark of PD, have been observed in serotoninergic, noradrenergic, and cholinergic neurons. Dysfunction of these systems could play a role in the occurrence of non-motor symptoms including fatigue. However, the extent of non-dopaminergic degeneration in PD, rates of its progression, and its contribution to the development of non-motor symptoms is unclear. First, I used 18F-dopa Positron Emission Tomography (PET), a marker of monoaminergic terminal function, to assess the involvement of dopaminergic, noradrenergic, and serotoninergic pathways in PD and in parkin-linked parkinsonism, a genetic form of PD. I found that parkin patients and PD patients have distinct patterns of monoaminergic involvement, with more widespread dysfunction in PD. In a second study, I used serial 18F-dopa PET to assess longitudinal changes in tracer uptake in brain monoaminergic structures over a 3-year period in a group of PD patients. I also assessed the relationship between striatal function decline and dysfunction in extra-striatal areas in the same patients. I found that the degeneration in extrastriatal monoaminergic structures in PD occurs independently from nigrostriatal degeneration and at a slower rate. Brain compensatory mechanisms disappear within the first years of disease. I then used 18F-dopa and 11C-DASB PET to investigate whether fatigue in PD is associated with dysfunction of dopaminergic/serotoninergic innervation. I found that PD patients with fatigue show severe loss of serotoninergic innervation in basal ganglia and limbic areas. Finally, I assessed the relationship between 18F-dopa uptake and measurements of serotonin transporter availability by 11C-DASB PET within brain serotoninergic structures and I provided evidence for the hypothesis that 18F-dopa PET can be used to evaluate the distribution and the function of serotoninergic systems in the brain of PD patients

Microarray analysis of GFP-expressing mouse Dopamine neurons isolated by laser capture microdissection

The Central Nervous System (CNS) contains an enormous variety of cell types which organize in complex networks. The lack of adequate markers to discern unequivocally among this cellular heterogeneity make the task of dissecting out such neural networks and the cells that comprise them very challenging. The present study represents a \u201cbottom-up\u201d approach that entails a description of A9 and A10 nuclei, which are components of the mesencephalic dopaminergic system, and the identification of their molecular make-up through microarray analysis of their gene expression profiles. These mesencephalic dopaminergic nuclei give rise to the mesocortical and mesostriatal projections and are well known for their roles in initiation of movement, reward behaviour and neurobiology of addiction. Moreover, in post mortem brains of Parkinson Disease patients a specific topographic pattern of degeneration of these neurons, also recapitulated in experimental animal models, is noted, with A9 neurons presenting with a higher vulnerability to degeneration with respect to A10 cells among which, neuron loss is almost negligible. Molecular differences may be at the basis of this different susceptibility. In this study we have optimized a protocol for laser-assisted microdissection of fluorescent-expressing cells and have taken advantage of a line of transgenic mice TH-GFP/21-31, which express GFP under the TH promoter in all CA cells, to guide laser capture microdissection of A9 and A10 mDA neurons for differential informative cDNA microarray profiling. Results show that our optimized method retains the GFP-fluorescence of DA cells and achieves good tissue morphology visualization. Moreover, RNA of high quality and good reproducibility of hybridizations support the validity of the protocol. Many of the genes that resulted differentially expressed from this analysis were found to be genes previously known to specifically define the different identities of the two DA neuronal nuclei. Transcripts were verified for expression, in DA neurons, using the collection of in situ hybridization in the Allen Brain Atlas. We have identified 592 differentially expressed transcripts (less than 8%) of which 242 showing higher expression in A9 and 350 showing higher expression in A10. Categorical analysis showed that transcripts associated with mitochondria and energy production were enriched in A9, while transcripts involved in redox homeostasis and stress response resulted enriched in A10. Of all the differentially expressed genes, eight transcripts (Mif, Hnt, Ndufa10, Aurka, Cs, enriched in A9 neurons and Pdia5, Whrn, and Gpx3 enriched in A10 neurons), verified with the Allen Brain Atlas and not noted or confirmed as differentially expressed before, emerged from this analysis. These and other selected genes are discussed