Caractérisation par imagerie TEP 18F-FDG de la maladie d’Alzheimer à début précoce

Alzheimer’s disease (AD) is the most common form of neurodegenerative dementia, characterized at 95% by late-onset forms (LOAD) which present episodic memory impairments and progress slowly. However, 5% of AD patients have an early-onset form (EOAD) of the disease whose onset begins before 65. Although the lesion substratum is similar between EOAD and LOAD, EOAD has more severe neuritic plaque deposits, neurofibrillary tangles and brain atrophy. Moreover, EOAD is more heterogeneous than LOAD, because even if most of the impairments are about episodic memory there is a high proportion of atypical forms impaired in language, visuospatial or executive functions. Although many 18F-FDG PET studies allowed to metabolically characterize EOAD compared to LOAD or healthy controls group, very few differentiated typical from atypical forms. In this thesis, we examined 18F-FDG PET data, complemented by structural MRI, in order to improve characterization and comprehension of typical and atypical forms of EOAD. Following a first harmonization work between 18F-FDG PET reconstructions from both GE and Siemens scanners used for the acquisition of patient data, our second aim was to study at baseline on the whole brain hypometabolic patterns characterizing the clinical forms of EOAD and their correlations with neuropsychological performance. This work showed that each clinical form of EOAD was characterized by specific hypometabolic patterns highly correlated with clinical symptoms and neuropsychological performance of the associated cognitive domain. Then, we focused on the 3-year hypometabolism progression on the cortical surface according typical or atypical forms of EOAD. Although similar patterns of hypometabolism evolution between typical and atypical forms were observed in parietal cortices, atypical only showed a more severe reduction of metabolism in lateral orbitofrontal cortices associated with more severe cognitive declines. Temporally, the results suggest that hypometabolism in typical forms would progress according to an anterior-to-posterior axis coherently with Braak and Braak stages, whereas in atypical forms hypometabolism would progress according a posterior-to-anterior axis. Taken together, results consolidate the hypothesis of a different tau distribution in terms of burden and temporal evolution between both forms of EOAD. Our last goal was to determine the discriminative power of 18F-FDG PET data, alone or combined to structural MRI data, in order to automatically classify in a supervised manner EOAD patients into typical or atypical form. We applied machine learning algorithms combined to cross-validation methods to assess influence of some components on classification performances. Maximum balanced accuracies equal to 80.8% in monomodal 18F-FDG PET and 92.4% in multimodal 18F-FDG PET/T1 MRI were obtained, validating 18F-FDG PET as a sensible biomarker of EOAD and highlighting the incontestable contribution of multimodality. In conclusion, our works allowed a better characterization and comprehension of clinical forms of EOAD, paving the way to personalized patient management and more effective treatments for these distinct clinical forms.La maladie d’Alzheimer (AD) est la principale cause de démence neurodégénérative, caractérisée à 95% par des formes tardives (LOAD) qui présentent des troubles mnésiques et progressent lentement. Cependant, environ 5% des patients atteints d’AD présentent une forme précoce de la maladie (EOAD) débutant avant 65 ans. Bien que le substratum lésionnel soit identique à la LOAD, l’EOAD est caractérisée par une plus grande sévérité des dépôts de plaques amyloïdes, des enchevêtrements neurofibrillaires et de l’atrophie cérébrale. De plus, l’EOAD est plus hétérogène que la LOAD, car même si la majorité des troubles sont mnésiques il existe une proportion importante de formes atypiques affectées par des troubles du langage, visuospatiaux ou exécutifs. Bien que de nombreuses études en imagerie TEP 18F-FDG aient permis de caractériser métaboliquement l’EOAD par rapport à la LOAD ou à un groupe de contrôles sains, très peu différentiaient pas les formes typiques (mnésiques) des formes atypiques. Dans ce travail de thèse, nous avons examiné les données d’imagerie TEP 18F-FDG, complémentées par l’IRM structurelle, afin d’améliorer la caractérisation et la compréhension des formes typiques et atypiques d’EOAD. Suite à un premier travail d’harmonisation des reconstructions TEP 18F-FDG entre deux machines GE et Siemens ayant toutes deux servies à l’acquisition des données patients, notre second objectif a été d’étudier à l’inclusion sur le cerveau entier les patterns hypométaboliques caractéristiques des différentes formes d’EOAD et leurs corrélations potentielles avec la performance neuropsychologique. Cette étude a montré que chaque forme clinique d’EOAD était caractérisée par des patterns hypométaboliques spécifiques fortement corrélés aux symptômes cliniques et aux scores neuropsychologiques du domaine cognitif associé. Par la suite, nous nous sommes intéressés à la progression sur 3 ans de l’hypométabolisme sur la surface corticale en fonction des formes typiques ou atypiques d’EOAD. Bien que des patterns similaires d’évolution de l’hypométabolisme entre les formes typiques et atypiques aient été observés au niveau du cortex pariétal, seules les formes atypiques ont présenté une réduction du métabolisme bilatérale plus importante au niveau du cortex orbito-frontal latéral associée à des déclins cognitifs plus sévères. Temporellement, les résultats suggèrent que l’hypométabolisme chez les formes typiques progresserait selon un axe antérieur-vers-postérieur en cohérence avec les stades de Braak et Braak, alors que l’hypométabolisme chez les formes atypiques progresserait selon un axe postérieur-vers-antérieur. Pris ensemble, ces résultats confortent l’hypothèse d’une distribution différente de la pathologie tau en termes de charge et d’évolution temporelle entre ces deux formes d’EOAD. Notre dernier objectif a été de déterminer les capacités discriminatives des données TEP 18F-FDG, seules ou combinées aux données de l’IRM structurelle, afin de classifier de manière automatique et supervisée des patients atteints d’EOAD en forme typique ou atypique. Nous avons mis en application des algorithmes de machine learning combinés à des méthodes de validation croisée afin d’évaluer les influences de diverses composantes sur les performances de classification. Des précisions équilibrées maximales égales à 80,8% en imagerie monomodale TEP 18F-FDG et 92,4% en imagerie multimodale TEP 18F-FDG/IRM T1 ont été obtenues, validant ainsi la TEP 18F-FDG comme un biomarqueur sensible de l’EOAD et soulignant l’apport incontestable de la multimodalité. En conclusion, nos travaux ont permis une meilleure caractérisation et compréhension des formes cliniques d’EOAD, ouvrant la voie à un management personnalisé du patient et des traitements plus efficaces pour ces formes distinctes

Characterization by 18F-FDG PET imaging of the Early-Onset Alzheimer's disease

La maladie d’Alzheimer (AD) est la principale cause de démence neurodégénérative, caractérisée à 95% par des formes tardives (LOAD) qui présentent des troubles mnésiques et progressent lentement. Cependant, environ 5% des patients atteints d’AD présentent une forme précoce de la maladie (EOAD) débutant avant 65 ans. Bien que le substratum lésionnel soit identique à la LOAD, l’EOAD est caractérisée par une plus grande sévérité des dépôts de plaques amyloïdes, des enchevêtrements neurofibrillaires et de l’atrophie cérébrale. De plus, l’EOAD est plus hétérogène que la LOAD, car même si la majorité des troubles sont mnésiques il existe une proportion importante de formes atypiques affectées par des troubles du langage, visuospatiaux ou exécutifs. Bien que de nombreuses études en imagerie TEP 18F-FDG aient permis de caractériser métaboliquement l’EOAD par rapport à la LOAD ou à un groupe de contrôles sains, très peu différentiaient pas les formes typiques (mnésiques) des formes atypiques. Dans ce travail de thèse, nous avons examiné les données d’imagerie TEP 18F-FDG, complémentées par l’IRM structurelle, afin d’améliorer la caractérisation et la compréhension des formes typiques et atypiques d’EOAD. Suite à un premier travail d’harmonisation des reconstructions TEP 18F-FDG entre deux machines GE et Siemens ayant toutes deux servies à l’acquisition des données patients, notre second objectif a été d’étudier à l’inclusion sur le cerveau entier les patterns hypométaboliques caractéristiques des différentes formes d’EOAD et leurs corrélations potentielles avec la performance neuropsychologique. Cette étude a montré que chaque forme clinique d’EOAD était caractérisée par des patterns hypométaboliques spécifiques fortement corrélés aux symptômes cliniques et aux scores neuropsychologiques du domaine cognitif associé. Par la suite, nous nous sommes intéressés à la progression sur 3 ans de l’hypométabolisme sur la surface corticale en fonction des formes typiques ou atypiques d’EOAD. Bien que des patterns similaires d’évolution de l’hypométabolisme entre les formes typiques et atypiques aient été observés au niveau du cortex pariétal, seules les formes atypiques ont présenté une réduction du métabolisme bilatérale plus importante au niveau du cortex orbito-frontal latéral associée à des déclins cognitifs plus sévères. Temporellement, les résultats suggèrent que l’hypométabolisme chez les formes typiques progresserait selon un axe antérieur-vers-postérieur en cohérence avec les stades de Braak et Braak, alors que l’hypométabolisme chez les formes atypiques progresserait selon un axe postérieur-vers-antérieur. Pris ensemble, ces résultats confortent l’hypothèse d’une distribution différente de la pathologie tau en termes de charge et d’évolution temporelle entre ces deux formes d’EOAD. Notre dernier objectif a été de déterminer les capacités discriminatives des données TEP 18F-FDG, seules ou combinées aux données de l’IRM structurelle, afin de classifier de manière automatique et supervisée des patients atteints d’EOAD en forme typique ou atypique. Nous avons mis en application des algorithmes de machine learning combinés à des méthodes de validation croisée afin d’évaluer les influences de diverses composantes sur les performances de classification. Des précisions équilibrées maximales égales à 80,8% en imagerie monomodale TEP 18F-FDG et 92,4% en imagerie multimodale TEP 18F-FDG/IRM T1 ont été obtenues, validant ainsi la TEP 18F-FDG comme un biomarqueur sensible de l’EOAD et soulignant l’apport incontestable de la multimodalité. En conclusion, nos travaux ont permis une meilleure caractérisation et compréhension des formes cliniques d’EOAD, ouvrant la voie à un management personnalisé du patient et des traitements plus efficaces pour ces formes distinctes.Alzheimer’s disease (AD) is the most common form of neurodegenerative dementia, characterized at 95% by late-onset forms (LOAD) which present episodic memory impairments and progress slowly. However, 5% of AD patients have an early-onset form (EOAD) of the disease whose onset begins before 65. Although the lesion substratum is similar between EOAD and LOAD, EOAD has more severe neuritic plaque deposits, neurofibrillary tangles and brain atrophy. Moreover, EOAD is more heterogeneous than LOAD, because even if most of the impairments are about episodic memory there is a high proportion of atypical forms impaired in language, visuospatial or executive functions. Although many 18F-FDG PET studies allowed to metabolically characterize EOAD compared to LOAD or healthy controls group, very few differentiated typical from atypical forms. In this thesis, we examined 18F-FDG PET data, complemented by structural MRI, in order to improve characterization and comprehension of typical and atypical forms of EOAD. Following a first harmonization work between 18F-FDG PET reconstructions from both GE and Siemens scanners used for the acquisition of patient data, our second aim was to study at baseline on the whole brain hypometabolic patterns characterizing the clinical forms of EOAD and their correlations with neuropsychological performance. This work showed that each clinical form of EOAD was characterized by specific hypometabolic patterns highly correlated with clinical symptoms and neuropsychological performance of the associated cognitive domain. Then, we focused on the 3-year hypometabolism progression on the cortical surface according typical or atypical forms of EOAD. Although similar patterns of hypometabolism evolution between typical and atypical forms were observed in parietal cortices, atypical only showed a more severe reduction of metabolism in lateral orbitofrontal cortices associated with more severe cognitive declines. Temporally, the results suggest that hypometabolism in typical forms would progress according to an anterior-to-posterior axis coherently with Braak and Braak stages, whereas in atypical forms hypometabolism would progress according a posterior-to-anterior axis. Taken together, results consolidate the hypothesis of a different tau distribution in terms of burden and temporal evolution between both forms of EOAD. Our last goal was to determine the discriminative power of 18F-FDG PET data, alone or combined to structural MRI data, in order to automatically classify in a supervised manner EOAD patients into typical or atypical form. We applied machine learning algorithms combined to cross-validation methods to assess influence of some components on classification performances. Maximum balanced accuracies equal to 80.8% in monomodal 18F-FDG PET and 92.4% in multimodal 18F-FDG PET/T1 MRI were obtained, validating 18F-FDG PET as a sensible biomarker of EOAD and highlighting the incontestable contribution of multimodality. In conclusion, our works allowed a better characterization and comprehension of clinical forms of EOAD, paving the way to personalized patient management and more effective treatments for these distinct clinical forms

Crash gun device for many dynamic and damage behaviour analysis

This work deals with fust results of crash tests provided by a new compressed air gun device. This installation has been built and instrumented in collaboration between BOMBARDIER Transport and the University of Technology of Compiègne. Complementary rapid data acquisition systems have been optimised to measure impact tests parameters. Thus, dynamic behaviour and damage tolerance of shapes can be investigated by both clamping fixtures for testing structures and specific apparatus for dynamic tensile loading of materials. About present study, crash strength of corrugated composite sandwich panels for railway application is analysed through 15 to 40 m/s impact velocities. Both influence of velocity level and projectile size is emphasised and placed in a context of particular sandwich structure characteristics. Next, damage and mechanical behaviour chronology during the crash event is partially described with interconnected observations coming fiom impact parameters measurements, appropriate strain gauges disposition and ultra speed acquisition camera. Finally, these first crash test results reveal wide perspectives about dynamic and damage investigation of-structures and materials

Association of the informant-reported memory decline with cognitive and brain deterioration through the Alzheimer's clinical continuum

International audienceBackground and objectives: Studies are sparse regarding the association between the informant-reported subjective memory decline (informant-report) and Alzheimer's disease (AD) biomarkers. This study thus aimed at determining the clinical relevance of the informant-report throughout the AD clinical continuum, by assessing its specific relationships with amyloid deposition, cognition and neurodegeneration.Methods: Participants from the Imagerie Multimodale de la maladie d'Alzheimer à un stade Précoce (IMAP+) primary cohort and from the Alzheimer's Disease Neuroimaging Initiative (ADNI) replication cohort were included; all underwent multimodal neuroimaging and neuropsychological assessments. Follow-up data of IMAP+ participants over up to 36 months were also used for longitudinal analyses. The informant-report was measured respectively with the Cognitive Difficulties Scale (IMAP+) and Everyday Cognition (ADNI). General linear models were used to assess the cross-sectional associations between the informant-report and amyloid-PET, cognitive performances, and neurodegeneration (atrophy and hypometabolism) in Alzheimer's-signature areas; while longitudinal links were assessed in IMAP+ with linear mixed-effects models.Results: 110 IMAP+ participants were included, including 32 cognitively unimpaired elders (controls, age: 70.91±6.57, female:50%), 25 patients with subjective cognitive decline (SCD, 65.88±6.64, 40%), 35 with mild cognitive impairment (MCI, 72.49±7.5, 34%) and 18 with Alzheimer's-type dementia (AD dementia, 68.17±8.59, 28%). 731 ADNI participants were included, including 157 controls (74.21±5.95, 55%), 84 SCD (72.00±5.41, 63%), 369 MCI (71.84±7.4, 44%) and 121 AD dementia (74.29±7.75, 40%). In IMAP+, higher informant-report strongly correlated to greater amyloid-PET specifically in MCI patients (β=0.48, p=.003), and to lower cognitive performance in SCD (global cognition, β=-0.41, p=.04) and MCI patients (memory, β=-0.37, p=.03). Findings in MCI patients were replicated in ADNI (amyloid-PET, β=0.25, p<.001; memory, β=-0.22, p<.001), and extended to neurodegeneration in AD signature areas (β=-0.2, p<.001). Longitudinal analyses in IMAP+ showed links with global cognitive decline over time in MCI (est. -0.74, SE 0.26, p=.005) and in SCD (est. -0.36, SE 0.26, p=.02) patients where higher baseline informant-report also predicted increased amyloid-PET over time (est. 0.008, SE 0.003, p=.02).Discussion: Altogether, our findings suggest that the informant-report is particularly relevant in MCI patients where it strongly relates to higher amyloid-PET, indicative of impairment due-to-AD.Trial registration information: ClinicalTrials.gov Identifier: NCT01638949

Optimization of early-phase Florbetapir as a surrogate of FDG-PET in ageing and Alzheimer’s clinical syndrome

peer reviewe

Longitudinal Changes in Hippocampal Network Connectivity in Alzheimer's Disease

International audienceObjective The hippocampus is connected to 2 distinct cortical brain networks, the posterior–medial and the anterior–temporal networks, involving different medial temporal lobe (MTL) subregions. The aim of this study was to assess the functional alterations of these 2 networks, their changes over time, and links to cognition in Alzheimer's disease. Methods We assessed MTL connectivity in 53 amyloid‐β–positive patients with mild cognitive impairment and AD dementia and 68 healthy elderly controls, using resting‐state functional magnetic resonance imaging, cross‐sectionally and longitudinally. First, we compared the functional connectivity of the posterior–medial and anterior–temporal networks within the control group to highlight their specificities. Second, we compared the connectivity of these networks between groups, and between baseline and 18‐month follow‐up in patients. Third, we assessed the association in the connectivity changes between the 2 networks, and with cognitive performance. Results We found decreased connectivity in patients specifically between the hippocampus and the posterior–medial network, together with increased connectivity between several MTL subregions and the anterior–temporal network. Moreover, changes in the posterior–medial and anterior–temporal networks were interrelated such that decreased MTL–posterior–medial connectivity was associated with increased MTL–anterior–temporal connectivity. Finally, both MTL–posterior–medial decrease and MTL–anterior–temporal increase predicted cognitive decline. Interpretation Our findings demonstrate that longitudinal connectivity changes in the posterior–medial and anterior–temporal hippocampal networks are linked together and that they both contribute to cognitive decline in Alzheimer's disease. These results shed light on the critical role of the posterior–medial and anterior–temporal networks in Alzheimer's disease pathophysiology and clinical symptoms. ANN NEUROL 2021;90:391–40

Optimization of early-phase florbetapir as a surrogate of FDG-PET in ageing and Alzheimer’s clinical syndrome: Neuroimaging/New imaging methods

peer reviewe

Hypothalamic structural and functional imbalances in anorexia nervosa

International audienceThe hypothalamus contains integrative systems that support life, including physiological processes such as food intake, energy expenditure and reproduction. Here, we show that anorexia nervosa patients, contrary to normal weight and constitutionally lean individuals, respond with a paradoxical reduction in hypothalamic levels of glutamate/glutamine (Glx) upon feeding. This reversal of the Glx response is associated with decreased wiring in the arcuate nucleus and increased connectivity in the lateral hypothalamic area, which are involved in the regulation on a variety of physiological and behavioral functions including the control of food intake and energy balance. The identification of distinct hypothalamic neurochemical dysfunctions and associated structural variations in anorexia nervosa paves the way for the development of new diagnostic and treatment strategies in conditions associated with abnormal body mass index and a maladaptive response to negative energy balance