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Stær K, Iranzo A, Terkelsen MH, Stokholm MG, Danielsen EH, Østergaard K, Serradell M, Otto M, Svendsen KB, Garrido A, Vilas D, Santamaria J, Møller A, Gaig C, Brooks DJ, Borghammer P, Tolosa E, Pavese N. Progression of brain cholinergic dysfunction in patients with isolated rapid eye movement sleep behavior disorder. Eur J Neurol 2024; 31:e16101. [PMID: 37847229 PMCID: PMC11236023 DOI: 10.1111/ene.16101] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/19/2023] [Revised: 09/25/2023] [Accepted: 09/27/2023] [Indexed: 10/18/2023]
Abstract
BACKGROUND Reduced cortical acetylcholinesterase activity, as measured by 11 C-donepezil positron emission tomography (PET), has been reported in patients with isolated rapid eye movement (REM) sleep behavior disorder (iRBD). However, its progression and clinical implications have not been fully investigated. Here, we explored the relationship between longitudinal changes in brain acetylcholinesterase activity and cognitive function in iRBD. METHODS Twelve iRBD patients underwent 11 C-donepezil PET at baseline and after 3 years. PET images were interrogated with statistical parametric mapping (SPM) and a regions of interest (ROI) approach. Clinical progression was assessed with the Movement Disorder Society-Unified Parkinson's Disease Rating Scale-Part III (MDS-UPDRS-III). Cognitive function was rated using the Mini-Mental State Examination (MMSE) and the Montreal Cognitive Assessment (MoCA). RESULTS From baseline to follow-up, the mean 11 C-donepezil distribution volume ratio (DVR) decreased in the cortex (p = 0.006), thalamus (p = 0.013), and caudate (p = 0.013) ROI. Despite no significant changes in the group mean MMSE or MoCA scores being observed, individually, seven patients showed a decline in their scores on these cognitive tests. Subgroup analysis showed that only the subgroup of patients with a decline in cognitive scores had a significant reduction in mean cortical 11 C-donepezil DVR. CONCLUSIONS Our results show that severity of brain cholinergic dysfunction in iRBD patients increases significantly over 3 years, and those changes are more severe in those with a decline in cognitive test scores.
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Affiliation(s)
- Kristian Stær
- Department of Nuclear Medicine & PET, Institute of Clinical MedicineAarhus UniversityAarhus NDenmark
| | - Alex Iranzo
- Department of NeurologyHospital Clínic de BarcelonaBarcelonaSpain
- Centro de Investigación Biomédica en Red sobre Enfermedades Neurodegenerativas (CIBERNED), Hospital Clínic, IDIBAPSUniversitat de BarcelonaCataloniaSpain
- Sleep Disorders CenterHospital ClinicBarcelonaSpain
| | - Miriam Højholt Terkelsen
- Department of Nuclear Medicine & PET, Institute of Clinical MedicineAarhus UniversityAarhus NDenmark
- Department of NeurologyAarhus University HospitalAarhus NDenmark
| | - Morten Gersel Stokholm
- Department of Nuclear Medicine & PET, Institute of Clinical MedicineAarhus UniversityAarhus NDenmark
| | | | - Karen Østergaard
- Department of NeurologyAarhus University HospitalAarhus NDenmark
| | - Mónica Serradell
- Department of NeurologyHospital Clínic de BarcelonaBarcelonaSpain
- Sleep Disorders CenterHospital ClinicBarcelonaSpain
| | - Marit Otto
- Department of NeurologyAarhus University HospitalAarhus NDenmark
- Department of Clinical NeurophysiologyAarhus University HospitalAarhus NDenmark
| | | | - Alicia Garrido
- Centro de Investigación Biomédica en Red sobre Enfermedades Neurodegenerativas (CIBERNED), Hospital Clínic, IDIBAPSUniversitat de BarcelonaCataloniaSpain
- Movement Disorders Unit, Neurology ServiceHospital Clínic de BarcelonaCataloniaSpain
| | - Dolores Vilas
- Centro de Investigación Biomédica en Red sobre Enfermedades Neurodegenerativas (CIBERNED), Hospital Clínic, IDIBAPSUniversitat de BarcelonaCataloniaSpain
- Movement Disorders Unit, Neurology ServiceHospital Clínic de BarcelonaCataloniaSpain
| | - Joan Santamaria
- Department of NeurologyHospital Clínic de BarcelonaBarcelonaSpain
- Centro de Investigación Biomédica en Red sobre Enfermedades Neurodegenerativas (CIBERNED), Hospital Clínic, IDIBAPSUniversitat de BarcelonaCataloniaSpain
- Sleep Disorders CenterHospital ClinicBarcelonaSpain
| | - Arne Møller
- Department of Nuclear Medicine & PET, Institute of Clinical MedicineAarhus UniversityAarhus NDenmark
| | - Carles Gaig
- Department of NeurologyHospital Clínic de BarcelonaBarcelonaSpain
- Centro de Investigación Biomédica en Red sobre Enfermedades Neurodegenerativas (CIBERNED), Hospital Clínic, IDIBAPSUniversitat de BarcelonaCataloniaSpain
- Sleep Disorders CenterHospital ClinicBarcelonaSpain
| | - David J. Brooks
- Department of Nuclear Medicine & PET, Institute of Clinical MedicineAarhus UniversityAarhus NDenmark
- Translational and Clinical Research InstituteNewcastle UniversityNewcastle upon TyneUK
| | - Per Borghammer
- Department of Nuclear Medicine & PET, Institute of Clinical MedicineAarhus UniversityAarhus NDenmark
| | - Eduardo Tolosa
- Centro de Investigación Biomédica en Red sobre Enfermedades Neurodegenerativas (CIBERNED), Hospital Clínic, IDIBAPSUniversitat de BarcelonaCataloniaSpain
- Movement Disorders Unit, Neurology ServiceHospital Clínic de BarcelonaCataloniaSpain
| | - Nicola Pavese
- Department of Nuclear Medicine & PET, Institute of Clinical MedicineAarhus UniversityAarhus NDenmark
- Translational and Clinical Research InstituteNewcastle UniversityNewcastle upon TyneUK
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102
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Mohammadi MS, Planty-Bonjour A, Poupon F, Uszynski I, Poupon C, Destrieux C, Andersson F. ProbaStem, a pipeline towards the first high-resolution probabilistic atlas of the whole human brainstem. Brain Struct Funct 2024; 229:115-132. [PMID: 37924354 DOI: 10.1007/s00429-023-02726-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/26/2022] [Accepted: 10/16/2023] [Indexed: 11/06/2023]
Abstract
The brainstem plays an essential role in many vital functions, such as autonomic control, consciousness and sleep, motricity, somatic afferent function, and cognition. Its involvement in several neurological diseases and the definition of brainstem targets for deep brain stimulation (DBS) explain the need for brainstem atlases describing its structural organization and connectivity from several modalities, from histology to ultrahigh field ex vivo MRI. Nonetheless, these atlases are often limited to a subpart of the brainstem or only include a single subject, the brainstem variability being considered low. This paper proposes a pipeline to create a high-resolution multisubject probabilistic atlas of the whole human brainstem based on four ultrahigh field ex vivo MRI datasets. The variability of the brainstem structures appears higher than usually considered, both for the volume and position of the central gray matter structures of the brainstem. This justifies the creation of atlases that capture the anatomical variability across subjects. The one we present here only included four specimens, but can easily be incremented due to its highly flexible design.
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Affiliation(s)
| | - Alexia Planty-Bonjour
- UMR 1253, Inserm, iBrain, Université de Tours, Tours, France
- CHRU de Tours, Tours, France
| | - Fabrice Poupon
- CEA, CNRS, BAOBAB, Paris-Saclay University, Gif-sur-Yvette, France
| | - Ivy Uszynski
- CEA, CNRS, BAOBAB, Paris-Saclay University, Gif-sur-Yvette, France
| | - Cyril Poupon
- CEA, CNRS, BAOBAB, Paris-Saclay University, Gif-sur-Yvette, France
| | - Christophe Destrieux
- UMR 1253, Inserm, iBrain, Université de Tours, Tours, France.
- CHRU de Tours, Tours, France.
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103
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Sebök M, van der Wouden F, Mader C, Pangalu A, Treyer V, Fisher JA, Mikulis DJ, Hüllner M, Regli L, Fierstra J, van Niftrik CHB. Hemodynamic Failure Staging With Blood Oxygenation Level-Dependent Cerebrovascular Reactivity and Acetazolamide-Challenged ( 15O-)H 2O-Positron Emission Tomography Across Individual Cerebrovascular Territories. J Am Heart Assoc 2023; 12:e029491. [PMID: 38084716 PMCID: PMC10863778 DOI: 10.1161/jaha.123.029491] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/10/2023] [Accepted: 09/11/2023] [Indexed: 12/20/2023]
Abstract
BACKGROUND Staging of hemodynamic failure (HF) in symptomatic patients with cerebrovascular steno-occlusive disease is required to assess the risk of ischemic stroke. Since the gold standard positron emission tomography-based perfusion reserve is unsuitable as a routine clinical imaging tool, blood oxygenation level-dependent cerebrovascular reactivity (BOLD-CVR) with CO2 is a promising surrogate imaging approach. We investigated the accuracy of standardized BOLD-CVR to classify the extent of HF. METHODS AND RESULTS Patients with symptomatic unilateral cerebrovascular steno-occlusive disease, who underwent both an acetazolamide challenge (15O-)H2O-positron emission tomography and BOLD-CVR examination, were included. HF staging of vascular territories was assessed using qualitative inspection of the positron emission tomography perfusion reserve images. The optimum BOLD-CVR cutoff points between HF stages 0-1-2 were determined by comparing the quantitative BOLD-CVR data to the qualitative (15O-)H2O-positron emission tomography classification using the 3-dimensional accuracy index to the randomly assigned training and test data sets with the following determination of a single cutoff for clinical application. In the 2-case scenario, classifying data points as HF 0 or 1-2 and HF 0-1 or 2, BOLD-CVR showed an accuracy of >0.7 for all vascular territories for HF 1 and HF 2 cutoff points. In particular, the middle cerebral artery territory had an accuracy of 0.79 for HF 1 and 0.83 for HF 2, whereas the anterior cerebral artery had an accuracy of 0.78 for HF 1 and 0.82 for HF 2. CONCLUSIONS Standardized and clinically accessible BOLD-CVR examinations harbor sufficient data to provide specific cerebrovascular reactivity cutoff points for HF staging across individual vascular territories in symptomatic patients with unilateral cerebrovascular steno-occlusive disease.
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Affiliation(s)
- Martina Sebök
- Department of NeurosurgeryUniversity Hospital Zurich, University of ZurichSwitzerland
- Clinical Neuroscience CenterUniversity Hospital Zurich, University of ZurichSwitzerland
| | | | - Cäcilia Mader
- Department of Nuclear MedicineUniversity Hospital Zurich, University of ZurichSwitzerland
| | - Athina Pangalu
- Clinical Neuroscience CenterUniversity Hospital Zurich, University of ZurichSwitzerland
- Department of NeuroradiologyUniversity Hospital Zurich, University of ZurichSwitzerland
| | - Valerie Treyer
- Department of Nuclear MedicineUniversity Hospital Zurich, University of ZurichSwitzerland
| | - Joseph Arnold Fisher
- Department of Anesthesia and Pain ManagementUniversity Health NetworkTorontoOntarioCanada
- Institute of Medical ScienceUniversity of TorontoTorontoOntarioCanada
| | - David John Mikulis
- Institute of Medical ScienceUniversity of TorontoTorontoOntarioCanada
- Joint Department of Medical Imaging and the Functional Neuroimaging LaboratoryUniversity Health NetworkTorontoOntarioCanada
| | - Martin Hüllner
- Department of Nuclear MedicineUniversity Hospital Zurich, University of ZurichSwitzerland
| | - Luca Regli
- Department of NeurosurgeryUniversity Hospital Zurich, University of ZurichSwitzerland
- Clinical Neuroscience CenterUniversity Hospital Zurich, University of ZurichSwitzerland
| | - Jorn Fierstra
- Department of NeurosurgeryUniversity Hospital Zurich, University of ZurichSwitzerland
- Clinical Neuroscience CenterUniversity Hospital Zurich, University of ZurichSwitzerland
| | - Christiaan Hendrik Bas van Niftrik
- Department of NeurosurgeryUniversity Hospital Zurich, University of ZurichSwitzerland
- Clinical Neuroscience CenterUniversity Hospital Zurich, University of ZurichSwitzerland
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He Z, Zheng Y, Ni J, Huang J, Pang Q, Chen T, Muhlert N, Elliott R. Loneliness is related to smaller gray matter volumes in ACC and right VLPFC in people with major depression: a UK biobank study. Cereb Cortex 2023; 33:11656-11667. [PMID: 37874025 DOI: 10.1093/cercor/bhad399] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/01/2023] [Revised: 10/08/2023] [Accepted: 10/09/2023] [Indexed: 10/25/2023] Open
Abstract
The anterior cingulate cortex (ACC) and right ventrolateral prefrontal cortex (VLPFC) are thought to have important roles in loneliness (feeling of social isolation/exclusion) experience or regulation and in the pathophysiology of their disturbance in major depressive disorder (MDD). However, the structural abnormalities of these regions and the correlates with loneliness in MDD across the healthy population have not fully been clarified. The study analyzed the link between loneliness and gray matter volumes (GMVs) in the ACC and right VLPFC among 1,005 patients with MDD and 7,247 healthy controls (HCs) using UK Biobank data. Significant reductions in GMV in the right VLPFC were found in MDD males compared to HCs. MDD males also showed a higher association between loneliness and reduced GMVs in the right VLPFC and bilateral ACC than HCs. No such associations were found in MDD females. The findings suggest that loneliness may influence brain structures crucial for emotion experience and regulation, particularly in middle-older aged men with MDD. This highlights the potential adverse effects of loneliness on brain structure in MDD and suggests that social engagement could have a positive impact.
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Affiliation(s)
- Zhenhong He
- School of Psychology, Shenzhen University, Shenzhen 518060, China
- Division of Neuroscience and Experimental Psychology, School of Biological Science, University of Manchester, Manchester M13 9PL, United Kingdom
| | - Youcun Zheng
- School of Science and Engineering, Chinese University of Hong Kong, Shenzhen 518172, China
| | - Jingxuan Ni
- School of Psychology, Shenzhen University, Shenzhen 518060, China
| | - Jin Huang
- School of Mathematical Sciences, Shenzhen University, Shenzhen 518060, China
| | - Qingqing Pang
- School of Psychology, Shenzhen University, Shenzhen 518060, China
| | - Tongtong Chen
- School of Humanities, Shenzhen University, Shenzhen 518060, China
| | - Nils Muhlert
- Division of Neuroscience and Experimental Psychology, School of Biological Science, University of Manchester, Manchester M13 9PL, United Kingdom
| | - Rebecca Elliott
- Division of Neuroscience and Experimental Psychology, School of Biological Science, University of Manchester, Manchester M13 9PL, United Kingdom
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105
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Cruz-Cortes Á, Avendaño-Estrada A, Alcauter S, Núñez-Enríquez JC, Rivera-Bravo B, Olarte-Casas MÁ, Ávila-Rodríguez MÁ. Semiquantitative analysis of cerebral [ 18F]FDG-PET uptake in pediatric patients. Pediatr Radiol 2023; 53:2574-2585. [PMID: 37910188 PMCID: PMC10698097 DOI: 10.1007/s00247-023-05794-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/01/2023] [Revised: 10/11/2023] [Accepted: 10/16/2023] [Indexed: 11/03/2023]
Abstract
BACKGROUND Glycolytic metabolism in the brain of pediatric patients, imaged with [18F] fluorodeoxyglucose-positron emission tomography (FDG-PET) is incompletely characterized. OBJECTIVE The purpose of the current study was to characterize [18F]FDG-PET brain uptake in a large sample of pediatric patients with non-central nervous system diseases as an alternative to healthy subjects to evaluate changes at different pediatric ages. MATERIALS AND METHODS Seven hundred ninety-five [18F]FDG-PET examinations from children < 18 years of age without central nervous system diseases were included. Each brain image was spatially normalized, and the standardized uptake value (SUV) was obtained. The SUV and the SUV relative to different pseudo-references were explored as a function of age. RESULTS At all evaluated ages, the occipital lobe showed the highest [18F]FDG uptake (0.27 ± 0.04 SUV/year), while the parietal lobe and brainstem had the lowest uptake (0.17 ± 0.02 SUV/year, for both regions). An increase [18F]FDG uptake was found for all brain regions until 12 years old, while no significant uptake differences were found between ages 13 (SUV = 5.39) to 17 years old (SUV = 5.52) (P < 0.0001 for the whole brain). A sex dependence was found in the SUVmean for the whole brain during adolescence (SUV 5.04-5.25 for males, 5.68-5.74 for females, P = 0.0264). Asymmetries in [18F]FDG uptake were found in the temporal and central regions during infancy. CONCLUSIONS Brain glycolytic metabolism of [18F]FDG, measured through the SUVmean, increased with age until early adolescence (< 13 years old), showing differences across brain regions. Age, sex, and brain region influence [18F]FDG uptake, with significant hemispheric asymmetries for temporal and central regions.
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Affiliation(s)
- Álvaro Cruz-Cortes
- Unidad de Radiofarmacia-Ciclotrón, División de Investigación, Facultad de Medicina, Universidad Nacional Autónoma de México, Ciudad de Mexico, Mexico
| | - Arturo Avendaño-Estrada
- Unidad de Radiofarmacia-Ciclotrón, División de Investigación, Facultad de Medicina, Universidad Nacional Autónoma de México, Ciudad de Mexico, Mexico.
| | - Sarael Alcauter
- Instituto de Neurobiología, Universidad Nacional Autónoma de México, Querétaro City, Mexico
| | - Juan Carlos Núñez-Enríquez
- Unidad de Investigación Médica en Epidemiología Clínica, UMAE Hospital de Pediatría, Centro Médico Nacional Siglo XXI, Instituto Mexicano del Seguro Social, Ciudad de Mexico, Mexico
| | - Belen Rivera-Bravo
- División de Investigación Facultad de Medicina Universidad Nacional Autónoma de México, Unidad PET/CT, Ciudad de Mexico, Mexico
| | - Miguel Ángel Olarte-Casas
- División de Investigación Facultad de Medicina Universidad Nacional Autónoma de México, Unidad PET/CT, Ciudad de Mexico, Mexico
| | - Miguel Ángel Ávila-Rodríguez
- Unidad de Radiofarmacia-Ciclotrón, División de Investigación, Facultad de Medicina, Universidad Nacional Autónoma de México, Ciudad de Mexico, Mexico
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106
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Constantinescu CC, Brown T, Wang S, Yin W, Barret O, Jennings D, Tauscher J. Clinical Characterization of [ 18F]T-008, a Cholesterol 24-Hydroxylase PET Ligand: Dosimetry, Kinetic Modeling, Variability, and Soticlestat Occupancy. J Nucl Med 2023; 64:1972-1979. [PMID: 37770111 PMCID: PMC10690114 DOI: 10.2967/jnumed.123.265912] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/20/2023] [Revised: 08/18/2023] [Indexed: 10/03/2023] Open
Abstract
This series of studies characterized [18F]T-008, a PET radiotracer for imaging cholesterol 24-hydroxylase (CH24H), in healthy volunteers (ClinicalTrials.gov identifier NCT02497235). Assessments included radiation dosimetry, kinetic modeling, test-retest variability (TRT) evaluation, and a dose occupancy evaluation using soticlestat, a selective CH24H inhibitor. Soticlestat is currently in phase 3 development for the treatment of seizures in Dravet syndrome and Lennox-Gastaut syndrome. Methods: In the dosimetry study, 5 participants (3 men) underwent serial whole-body scans to estimate organ-absorbed doses and effective doses of [18F]T-008 using OLINDA/EXM 1.1. For the kinetic modeling and TRT study, 6 participants (all men) underwent two 210-min dynamic [18F]T-008 PET scans with arterial blood sampling. The regional total volume of distribution was estimated using a 1-tissue-compartment model, a 2-tissue-compartment model, and Logan graphic analysis. In the dose occupancy study, 11 participants (all men) underwent 120-min scans at baseline and 2 time points (peak and trough) after receiving single oral doses of soticlestat (50-600 mg). The relationship between effect-site soticlestat concentration and brain occupancy was evaluated with a specially developed pharmacokinetic model and a saturable maximal occupancy model. Results: The estimated mean whole-body effective dose was 0.0292 mSv/MBq (SD, 0.00147 mSv/MBq). [18F]T-008 entered the brain rapidly, with a distribution consistent with known CH24H distribution densities. The 2-tissue-compartment model and Logan graphic analysis best described the tracer kinetics. The mean TRT for estimating total volume of distribution was 7%-15%. Single doses of soticlestat in the range 50-600 mg resulted in occupancies of 64%-96% at 2 h and 11%-79% at 24 h. The estimated half-maximal effect-site concentration of soticlestat was 5.52 ng/mL. Conclusion: [18F]T-008 is a suitable PET radiotracer for quantitatively analyzing CH24H in the human brain. Using [18F]T-008 and PET, we demonstrated that soticlestat was brain-penetrant and established target engagement by displacing [18F]T-008 in a dose-dependent manner in the brain.
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Affiliation(s)
| | - Terry Brown
- Takeda Pharmaceutical Co. Ltd., Cambridge, Massachusetts
| | - Shining Wang
- Takeda Pharmaceutical Co. Ltd., Cambridge, Massachusetts
| | - Wei Yin
- Takeda Pharmaceutical Co. Ltd., Cambridge, Massachusetts
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107
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Jin SO, Mérida I, Stavropoulos I, Elwes RDC, Lam T, Guedj E, Girard N, Costes N, Hammers A. Characterisation of a novel [ 18F]FDG brain PET database and combination with a second database for optimising detection of focal abnormalities, using focal cortical dysplasia as an example. EJNMMI Res 2023; 13:98. [PMID: 37964137 PMCID: PMC10645721 DOI: 10.1186/s13550-023-01023-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/10/2023] [Accepted: 07/26/2023] [Indexed: 11/16/2023] Open
Abstract
BACKGROUND Brain [18F]FDG PET is used clinically mainly in the presurgical evaluation for epilepsy surgery and in the differential diagnosis of neurodegenerative disorders. While scans are usually interpreted visually on an individual basis, comparison against normative cohorts allows statistical assessment of abnormalities and potentially higher sensitivity for detecting abnormalities. Little work has been done on out-of-sample databases (acquired differently to the patient data). Combination of different databases would potentially allow better power and discrimination. We fully characterised an unpublished healthy control brain [18F]FDG PET database (Marseille, n = 60, ages 21-78 years) and compared it to another publicly available database (MRXFDG, n = 37, ages 23-65 years). We measured and then harmonised spatial resolution and global values. A collection of patient scans (n = 34, 13-48 years) with histologically confirmed focal cortical dysplasias (FCDs) obtained on three generations of scanners was used to estimate abnormality detection rates using standard software (statistical parametric mapping, SPM12). RESULTS Regional SUVs showed similar patterns, but global values and resolutions were different as expected. Detection rates for the FCDs were 50% for comparison with the Marseille database and 53% for MRXFDG. Simply combining both databases worsened the detection rate to 41%. After harmonisation of spatial resolution, using a full factorial design matrix to accommodate global differences, and leaving out controls older than 60 years, we achieved detection rates of up to 71% for both databases combined. Detection rates were similar across the three scanner types used for patients, and high for patients whose MRI had been normal (n = 10/11). CONCLUSIONS As expected, global and regional data characteristics are database specific. However, our work shows the value of increasing database size and suggests ways in which database differences can be overcome. This may inform analysis via traditional statistics or machine learning, and clinical implementation.
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Affiliation(s)
- Sameer Omer Jin
- Faculty of Life Sciences and Medicine, School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK
- King's College London & Guy's and St Thomas' PET Centre, London, UK
| | - Inés Mérida
- Centre d'Etude et de Recherche Multimodale et Pluridisciplinaire en Imagerie du Vivant (CERMEP), Lyon, France
| | - Ioannis Stavropoulos
- Department of Clinical Neurophysiology, King's College Hospital, London, UK
- Department of Basic and Clinical Neuroscience, Institute of Psychiatry, Psychology, and Neuroscience, King's College London, London, UK
| | - Robert D C Elwes
- Department of Clinical Neurophysiology, King's College Hospital, London, UK
| | - Tanya Lam
- Children's Neuroscience Centre, Evelina London Children's Hospital, Guy's and St Thomas' NHS Trust, London, UK
| | - Eric Guedj
- Nuclear Medicine Department, APHM, CNRS, Centrale Marseille, Institut Fresnel, Timone Hospital, CERIMED, Aix Marseille University, Marseille, France
| | - Nadine Girard
- Department of Neuroradiology, APHM, CRMBM, UMR CNRS 7339, Timone Hospital, Aix Marseille University, Marseille, France
| | - Nicolas Costes
- Centre d'Etude et de Recherche Multimodale et Pluridisciplinaire en Imagerie du Vivant (CERMEP), Lyon, France
| | - Alexander Hammers
- Faculty of Life Sciences and Medicine, School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK.
- King's College London & Guy's and St Thomas' PET Centre, London, UK.
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108
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Cheval M, Rodrigo S, Taussig D, Caillé F, Petrescu AM, Bottlaender M, Tournier N, Besson FL, Leroy C, Bouilleret V. [ 18F]DPA-714 PET Imaging in the Presurgical Evaluation of Patients With Drug-Resistant Focal Epilepsy. Neurology 2023; 101:e1893-e1904. [PMID: 37748889 PMCID: PMC10663012 DOI: 10.1212/wnl.0000000000207811] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/07/2023] [Accepted: 07/17/2023] [Indexed: 09/27/2023] Open
Abstract
BACKGROUND AND OBJECTIVES Translocator protein 18 kDa (TSPO) PET imaging is used to monitor glial activation. Recent studies have proposed TSPO PET as a marker of the epileptogenic zone (EZ) in drug-resistant focal epilepsy (DRFE). This study aims to assess the contributions of TSPO imaging using [18F]DPA-714 PET and [18F]FDG PET for localizing the EZ during presurgical assessment of DRFE, when phase 1 presurgical assessment does not provide enough information. METHODS We compared [18F]FDG and [18F]DPA-714 PET images of 23 patients who had undergone a phase 1 presurgical assessment, using qualitative visual analysis and quantitative analysis, at both the voxel and the regional levels. PET abnormalities (increase in binding for [18F]DPA-714 vs decrease in binding for [18F]FDG) were compared with clinical hypotheses concerning the localization of the EZ based on phase 1 presurgical assessment. The additional value of [18F]DPA-714 PET imaging to [18F]FDG for refining the localization of the EZ was assessed. To strengthen the visual analysis, [18F]DPA-714 PET imaging was also reviewed by 2 experienced clinicians blind to the EZ location. RESULTS The study included 23 patients. Visual analysis of [18F]DPA-714 PET was significantly more accurate than [18F]FDG PET to both, show anomalies (95.7% vs 56.5%, p = 0.022), and provide additional information to refine the EZ localization (65.2% vs 17.4%, p = 0.019). All 10 patients with normal [18F]FDG PET had anomalies when using [18F]DPA-714 PET. The additional value of [18F]DPA-714 PET seemed to be greater in patients with normal brain MRI or with neocortical EZ (especially if insula is involved). Regional analysis of [18F]DPA-714 and [18F]FDG PET provided similar results. However, using voxel-wise analysis, [18F]DPA-714 was more effective than [18F]FDG for unveiling clusters whose localization was more often consistent with the EZ hypothesis (87.0% vs 39.1%, p = 0.019). Nonrelevant bindings were seen in 14 of 23 patients in visual analysis and 9 patients of 23 patients in voxel-wise analysis. DISCUSSION [18F]DPA-714 PET imaging provides valuable information for presurgical assessments of patients with DRFE. TSPO PET could become an additional tool to help to the localization of the EZ, especially in patients with negative [18F]FDG PET. TRIAL REGISTRATION INFORMATION Eudract 2017-003381-27. Inclusion of the first patient: September 24, 2018. CLASSIFICATION OF EVIDENCE This study provides Class IV evidence on the utility of [18F]DPA-714 PET compared with [18F]FDG PET in identifying the epileptic zone in patients undergoing phase 1 presurgical evaluation for intractable epilepsy.
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Affiliation(s)
- Margaux Cheval
- From the Université Paris-Saclay (M.C., C.L., M.B., N.T.); BioMAPS (S.R., F.C., F.L.B.); Bicetre University Hospital (D.T., A.M.P.), Paris; and Imagerie Moléculaire In Vivo (V.B.), SHFJ, CEA, Orsay, France.
| | - Sebastian Rodrigo
- From the Université Paris-Saclay (M.C., C.L., M.B., N.T.); BioMAPS (S.R., F.C., F.L.B.); Bicetre University Hospital (D.T., A.M.P.), Paris; and Imagerie Moléculaire In Vivo (V.B.), SHFJ, CEA, Orsay, France
| | - Delphine Taussig
- From the Université Paris-Saclay (M.C., C.L., M.B., N.T.); BioMAPS (S.R., F.C., F.L.B.); Bicetre University Hospital (D.T., A.M.P.), Paris; and Imagerie Moléculaire In Vivo (V.B.), SHFJ, CEA, Orsay, France
| | - Fabien Caillé
- From the Université Paris-Saclay (M.C., C.L., M.B., N.T.); BioMAPS (S.R., F.C., F.L.B.); Bicetre University Hospital (D.T., A.M.P.), Paris; and Imagerie Moléculaire In Vivo (V.B.), SHFJ, CEA, Orsay, France
| | - Ana Maria Petrescu
- From the Université Paris-Saclay (M.C., C.L., M.B., N.T.); BioMAPS (S.R., F.C., F.L.B.); Bicetre University Hospital (D.T., A.M.P.), Paris; and Imagerie Moléculaire In Vivo (V.B.), SHFJ, CEA, Orsay, France
| | - Michel Bottlaender
- From the Université Paris-Saclay (M.C., C.L., M.B., N.T.); BioMAPS (S.R., F.C., F.L.B.); Bicetre University Hospital (D.T., A.M.P.), Paris; and Imagerie Moléculaire In Vivo (V.B.), SHFJ, CEA, Orsay, France
| | - Nicolas Tournier
- From the Université Paris-Saclay (M.C., C.L., M.B., N.T.); BioMAPS (S.R., F.C., F.L.B.); Bicetre University Hospital (D.T., A.M.P.), Paris; and Imagerie Moléculaire In Vivo (V.B.), SHFJ, CEA, Orsay, France
| | - Florent L Besson
- From the Université Paris-Saclay (M.C., C.L., M.B., N.T.); BioMAPS (S.R., F.C., F.L.B.); Bicetre University Hospital (D.T., A.M.P.), Paris; and Imagerie Moléculaire In Vivo (V.B.), SHFJ, CEA, Orsay, France
| | - Claire Leroy
- From the Université Paris-Saclay (M.C., C.L., M.B., N.T.); BioMAPS (S.R., F.C., F.L.B.); Bicetre University Hospital (D.T., A.M.P.), Paris; and Imagerie Moléculaire In Vivo (V.B.), SHFJ, CEA, Orsay, France
| | - Viviane Bouilleret
- From the Université Paris-Saclay (M.C., C.L., M.B., N.T.); BioMAPS (S.R., F.C., F.L.B.); Bicetre University Hospital (D.T., A.M.P.), Paris; and Imagerie Moléculaire In Vivo (V.B.), SHFJ, CEA, Orsay, France
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109
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Clementi L, Arnone E, Santambrogio MD, Franceschetti S, Panzica F, Sangalli LM. Anatomically compliant modes of variations: New tools for brain connectivity. PLoS One 2023; 18:e0292450. [PMID: 37934760 PMCID: PMC10629624 DOI: 10.1371/journal.pone.0292450] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/17/2023] [Accepted: 09/20/2023] [Indexed: 11/09/2023] Open
Abstract
Anatomical complexity and data dimensionality present major issues when analysing brain connectivity data. The functional and anatomical aspects of the connections taking place in the brain are in fact equally relevant and strongly intertwined. However, due to theoretical challenges and computational issues, their relationship is often overlooked in neuroscience and clinical research. In this work, we propose to tackle this problem through Smooth Functional Principal Component Analysis, which enables to perform dimensional reduction and exploration of the variability in functional connectivity maps, complying with the formidably complicated anatomy of the grey matter volume. In particular, we analyse a population that includes controls and subjects affected by schizophrenia, starting from fMRI data acquired at rest and during a task-switching paradigm. For both sessions, we first identify the common modes of variation in the entire population. We hence explore whether the subjects' expressions along these common modes of variation differ between controls and pathological subjects. In each session, we find principal components that are significantly differently expressed in the healthy vs pathological subjects (with p-values < 0.001), highlighting clearly interpretable differences in the connectivity in the two subpopulations. For instance, the second and third principal components for the rest session capture the imbalance between the Default Mode and Executive Networks characterizing schizophrenia patients.
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Affiliation(s)
- Letizia Clementi
- MOX - Department of Mathematics, Politecnico di Milano, Milan, Italy
- Department of Electronics, Information and Bioengineering, Politecnico di Milano, Milan, Italy
- CHDS, Center for Health Data Science, Human Technopole, Milan, Italy
| | | | - Marco D. Santambrogio
- Department of Electronics, Information and Bioengineering, Politecnico di Milano, Milan, Italy
| | | | | | - Laura M. Sangalli
- MOX - Department of Mathematics, Politecnico di Milano, Milan, Italy
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110
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Coomans EM, de Koning LA, Rikken RM, Verfaillie SCJ, Visser D, den Braber A, Tomassen J, van de Beek M, Collij LE, Lemstra AW, Windhorst AD, Barkhof F, Golla SSV, Visser PJ, Scheltens P, van der Flier WM, Ossenkoppele R, van Berckel BNM, van de Giessen E. Performance of a [ 18F]Flortaucipir PET Visual Read Method Across the Alzheimer Disease Continuum and in Dementia With Lewy Bodies. Neurology 2023; 101:e1850-e1862. [PMID: 37748892 PMCID: PMC10663007 DOI: 10.1212/wnl.0000000000207794] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/30/2023] [Accepted: 07/24/2023] [Indexed: 09/27/2023] Open
Abstract
BACKGROUND AND OBJECTIVES Recently, the US Food and Drug Administration approved the tau-binding radiotracer [18F]flortaucipir and an accompanying visual read method to support the diagnostic process in cognitively impaired patients assessed for Alzheimer disease (AD). Studies evaluating this visual read method are limited. In this study, we evaluated the performance of the visual read method in participants along the AD continuum and dementia with Lewy bodies (DLB) by determining its reliability, accordance with semiquantitative analyses, and associations with clinically relevant variables. METHODS We included participants who underwent tau-PET at Amsterdam University Medical Center. A subset underwent follow-up tau-PET. Two trained nuclear medicine physicians visually assessed all scans. Inter-reader agreement was calculated using Cohen κ. To examine the concordance of visual read tau positivity with semiquantification, we defined standardized uptake value ratio (SUVr) positivity using different threshold approaches. To evaluate the prognostic value of tau-PET visual read, we performed linear mixed models with longitudinal Mini-Mental State Examination (MMSE). RESULTS We included 263 participants (mean age 68.5 years, 45.6% female), including 147 cognitively unimpaired (CU) participants, 97 amyloid-positive participants with mild cognitive impairment or AD dementia (AD), and 19 participants with DLB. The visual read inter-reader agreement was excellent (κ = 0.95, CI 0.91-0.99). None of the amyloid-negative CU participants (0/92 [0%]) and 1 amyloid-negative participant with DLB (1/12 [8.3%]) were tau-positive. Among amyloid-positive participants, 13 CU participants (13/52 [25.0%]), 85 with AD (85/97 [87.6%]), and 3 with DLB (3/7 [42.9%]) were tau-positive. Two-year follow-up visual read status was identical to baseline. Tau-PET visual read corresponded strongly to SUVr status, with up to 90.4% concordance. Visual read tau positivity was associated with a decline on the MMSE in CU participants (β = -0.52, CI -0.74 to -0.30, p < 0.001) and participants with AD (β = -0.30, CI -0.58 to -0.02, p = 0.04). DISCUSSION The excellent inter-reader agreement, strong correspondence with SUVr, and longitudinal stability indicate that the visual read method is reliable and robust, supporting clinical application. Furthermore, visual read tau positivity was associated with prospective cognitive decline, highlighting its additional prognostic potential. Future studies in unselected cohorts are needed for a better generalizability to the clinical population. CLASSIFICATION OF EVIDENCE This study provides Class II evidence that [18F]flortaucipir visual read accurately distinguishes patients with low tau-tracer binding from those with high tau-tracer binding and is associated with amyloid positivity and cognitive decline.
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Affiliation(s)
- Emma M Coomans
- From the Radiology & Nuclear Medicine (E.M.C., L.A.d.K., R.M.R., S.C.J.V., D.V., L.E.C., A.D.W., F.B., S.S.V.G., B.N.M.v.B., E.v.d.G.), Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc; Brain Imaging (E.M.C., L.A.d.K., R.M.R., S.C.J.V., D.V., L.E.C., A.D.W., F.B., S.S.V.G., B.N.M.v.B., E.v.d.G.), Amsterdam Neuroscience; Medical Psychology (S.C.J.V.), Amsterdam UMC location University of Amsterdam; Alzheimer Center Amsterdam (A.d.B., J.T., M.v.d.B., A.W.L., P.J.V., P.S., W.M.v.d.F., R.O.), Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc; Neurodegeneration (A.d.B., J.T., M.v.d.B., A.W.L., P.J.V., P.S., W.M.v.d.F., R.O.), Amsterdam Neuroscience; Department of Biological Psychology (A.d.B.), Vrije Universiteit Amsterdam, the Netherlands; Queen Square Institute of Neurology and Centre for Medical Image Computing (F.B.), University College London, United Kingdom; Alzheimer Center Limburg (P.J.V.), School for Mental Health and Neuroscience, Maastricht University, the Netherlands; Division of Neurogeriatrics (P.J.V.), Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden; Department of Epidemiology & Data Science (W.M.v.d.F.), Vrije Universiteit Amsterdam, Amsterdam UMC, the Netherlands; and Clinical Memory Research Unit (R.O.), Lund University, Sweden.
| | - Lotte A de Koning
- From the Radiology & Nuclear Medicine (E.M.C., L.A.d.K., R.M.R., S.C.J.V., D.V., L.E.C., A.D.W., F.B., S.S.V.G., B.N.M.v.B., E.v.d.G.), Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc; Brain Imaging (E.M.C., L.A.d.K., R.M.R., S.C.J.V., D.V., L.E.C., A.D.W., F.B., S.S.V.G., B.N.M.v.B., E.v.d.G.), Amsterdam Neuroscience; Medical Psychology (S.C.J.V.), Amsterdam UMC location University of Amsterdam; Alzheimer Center Amsterdam (A.d.B., J.T., M.v.d.B., A.W.L., P.J.V., P.S., W.M.v.d.F., R.O.), Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc; Neurodegeneration (A.d.B., J.T., M.v.d.B., A.W.L., P.J.V., P.S., W.M.v.d.F., R.O.), Amsterdam Neuroscience; Department of Biological Psychology (A.d.B.), Vrije Universiteit Amsterdam, the Netherlands; Queen Square Institute of Neurology and Centre for Medical Image Computing (F.B.), University College London, United Kingdom; Alzheimer Center Limburg (P.J.V.), School for Mental Health and Neuroscience, Maastricht University, the Netherlands; Division of Neurogeriatrics (P.J.V.), Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden; Department of Epidemiology & Data Science (W.M.v.d.F.), Vrije Universiteit Amsterdam, Amsterdam UMC, the Netherlands; and Clinical Memory Research Unit (R.O.), Lund University, Sweden
| | - Roos M Rikken
- From the Radiology & Nuclear Medicine (E.M.C., L.A.d.K., R.M.R., S.C.J.V., D.V., L.E.C., A.D.W., F.B., S.S.V.G., B.N.M.v.B., E.v.d.G.), Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc; Brain Imaging (E.M.C., L.A.d.K., R.M.R., S.C.J.V., D.V., L.E.C., A.D.W., F.B., S.S.V.G., B.N.M.v.B., E.v.d.G.), Amsterdam Neuroscience; Medical Psychology (S.C.J.V.), Amsterdam UMC location University of Amsterdam; Alzheimer Center Amsterdam (A.d.B., J.T., M.v.d.B., A.W.L., P.J.V., P.S., W.M.v.d.F., R.O.), Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc; Neurodegeneration (A.d.B., J.T., M.v.d.B., A.W.L., P.J.V., P.S., W.M.v.d.F., R.O.), Amsterdam Neuroscience; Department of Biological Psychology (A.d.B.), Vrije Universiteit Amsterdam, the Netherlands; Queen Square Institute of Neurology and Centre for Medical Image Computing (F.B.), University College London, United Kingdom; Alzheimer Center Limburg (P.J.V.), School for Mental Health and Neuroscience, Maastricht University, the Netherlands; Division of Neurogeriatrics (P.J.V.), Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden; Department of Epidemiology & Data Science (W.M.v.d.F.), Vrije Universiteit Amsterdam, Amsterdam UMC, the Netherlands; and Clinical Memory Research Unit (R.O.), Lund University, Sweden
| | - Sander C J Verfaillie
- From the Radiology & Nuclear Medicine (E.M.C., L.A.d.K., R.M.R., S.C.J.V., D.V., L.E.C., A.D.W., F.B., S.S.V.G., B.N.M.v.B., E.v.d.G.), Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc; Brain Imaging (E.M.C., L.A.d.K., R.M.R., S.C.J.V., D.V., L.E.C., A.D.W., F.B., S.S.V.G., B.N.M.v.B., E.v.d.G.), Amsterdam Neuroscience; Medical Psychology (S.C.J.V.), Amsterdam UMC location University of Amsterdam; Alzheimer Center Amsterdam (A.d.B., J.T., M.v.d.B., A.W.L., P.J.V., P.S., W.M.v.d.F., R.O.), Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc; Neurodegeneration (A.d.B., J.T., M.v.d.B., A.W.L., P.J.V., P.S., W.M.v.d.F., R.O.), Amsterdam Neuroscience; Department of Biological Psychology (A.d.B.), Vrije Universiteit Amsterdam, the Netherlands; Queen Square Institute of Neurology and Centre for Medical Image Computing (F.B.), University College London, United Kingdom; Alzheimer Center Limburg (P.J.V.), School for Mental Health and Neuroscience, Maastricht University, the Netherlands; Division of Neurogeriatrics (P.J.V.), Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden; Department of Epidemiology & Data Science (W.M.v.d.F.), Vrije Universiteit Amsterdam, Amsterdam UMC, the Netherlands; and Clinical Memory Research Unit (R.O.), Lund University, Sweden
| | - Denise Visser
- From the Radiology & Nuclear Medicine (E.M.C., L.A.d.K., R.M.R., S.C.J.V., D.V., L.E.C., A.D.W., F.B., S.S.V.G., B.N.M.v.B., E.v.d.G.), Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc; Brain Imaging (E.M.C., L.A.d.K., R.M.R., S.C.J.V., D.V., L.E.C., A.D.W., F.B., S.S.V.G., B.N.M.v.B., E.v.d.G.), Amsterdam Neuroscience; Medical Psychology (S.C.J.V.), Amsterdam UMC location University of Amsterdam; Alzheimer Center Amsterdam (A.d.B., J.T., M.v.d.B., A.W.L., P.J.V., P.S., W.M.v.d.F., R.O.), Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc; Neurodegeneration (A.d.B., J.T., M.v.d.B., A.W.L., P.J.V., P.S., W.M.v.d.F., R.O.), Amsterdam Neuroscience; Department of Biological Psychology (A.d.B.), Vrije Universiteit Amsterdam, the Netherlands; Queen Square Institute of Neurology and Centre for Medical Image Computing (F.B.), University College London, United Kingdom; Alzheimer Center Limburg (P.J.V.), School for Mental Health and Neuroscience, Maastricht University, the Netherlands; Division of Neurogeriatrics (P.J.V.), Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden; Department of Epidemiology & Data Science (W.M.v.d.F.), Vrije Universiteit Amsterdam, Amsterdam UMC, the Netherlands; and Clinical Memory Research Unit (R.O.), Lund University, Sweden
| | - Anouk den Braber
- From the Radiology & Nuclear Medicine (E.M.C., L.A.d.K., R.M.R., S.C.J.V., D.V., L.E.C., A.D.W., F.B., S.S.V.G., B.N.M.v.B., E.v.d.G.), Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc; Brain Imaging (E.M.C., L.A.d.K., R.M.R., S.C.J.V., D.V., L.E.C., A.D.W., F.B., S.S.V.G., B.N.M.v.B., E.v.d.G.), Amsterdam Neuroscience; Medical Psychology (S.C.J.V.), Amsterdam UMC location University of Amsterdam; Alzheimer Center Amsterdam (A.d.B., J.T., M.v.d.B., A.W.L., P.J.V., P.S., W.M.v.d.F., R.O.), Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc; Neurodegeneration (A.d.B., J.T., M.v.d.B., A.W.L., P.J.V., P.S., W.M.v.d.F., R.O.), Amsterdam Neuroscience; Department of Biological Psychology (A.d.B.), Vrije Universiteit Amsterdam, the Netherlands; Queen Square Institute of Neurology and Centre for Medical Image Computing (F.B.), University College London, United Kingdom; Alzheimer Center Limburg (P.J.V.), School for Mental Health and Neuroscience, Maastricht University, the Netherlands; Division of Neurogeriatrics (P.J.V.), Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden; Department of Epidemiology & Data Science (W.M.v.d.F.), Vrije Universiteit Amsterdam, Amsterdam UMC, the Netherlands; and Clinical Memory Research Unit (R.O.), Lund University, Sweden
| | - Jori Tomassen
- From the Radiology & Nuclear Medicine (E.M.C., L.A.d.K., R.M.R., S.C.J.V., D.V., L.E.C., A.D.W., F.B., S.S.V.G., B.N.M.v.B., E.v.d.G.), Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc; Brain Imaging (E.M.C., L.A.d.K., R.M.R., S.C.J.V., D.V., L.E.C., A.D.W., F.B., S.S.V.G., B.N.M.v.B., E.v.d.G.), Amsterdam Neuroscience; Medical Psychology (S.C.J.V.), Amsterdam UMC location University of Amsterdam; Alzheimer Center Amsterdam (A.d.B., J.T., M.v.d.B., A.W.L., P.J.V., P.S., W.M.v.d.F., R.O.), Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc; Neurodegeneration (A.d.B., J.T., M.v.d.B., A.W.L., P.J.V., P.S., W.M.v.d.F., R.O.), Amsterdam Neuroscience; Department of Biological Psychology (A.d.B.), Vrije Universiteit Amsterdam, the Netherlands; Queen Square Institute of Neurology and Centre for Medical Image Computing (F.B.), University College London, United Kingdom; Alzheimer Center Limburg (P.J.V.), School for Mental Health and Neuroscience, Maastricht University, the Netherlands; Division of Neurogeriatrics (P.J.V.), Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden; Department of Epidemiology & Data Science (W.M.v.d.F.), Vrije Universiteit Amsterdam, Amsterdam UMC, the Netherlands; and Clinical Memory Research Unit (R.O.), Lund University, Sweden
| | - Marleen van de Beek
- From the Radiology & Nuclear Medicine (E.M.C., L.A.d.K., R.M.R., S.C.J.V., D.V., L.E.C., A.D.W., F.B., S.S.V.G., B.N.M.v.B., E.v.d.G.), Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc; Brain Imaging (E.M.C., L.A.d.K., R.M.R., S.C.J.V., D.V., L.E.C., A.D.W., F.B., S.S.V.G., B.N.M.v.B., E.v.d.G.), Amsterdam Neuroscience; Medical Psychology (S.C.J.V.), Amsterdam UMC location University of Amsterdam; Alzheimer Center Amsterdam (A.d.B., J.T., M.v.d.B., A.W.L., P.J.V., P.S., W.M.v.d.F., R.O.), Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc; Neurodegeneration (A.d.B., J.T., M.v.d.B., A.W.L., P.J.V., P.S., W.M.v.d.F., R.O.), Amsterdam Neuroscience; Department of Biological Psychology (A.d.B.), Vrije Universiteit Amsterdam, the Netherlands; Queen Square Institute of Neurology and Centre for Medical Image Computing (F.B.), University College London, United Kingdom; Alzheimer Center Limburg (P.J.V.), School for Mental Health and Neuroscience, Maastricht University, the Netherlands; Division of Neurogeriatrics (P.J.V.), Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden; Department of Epidemiology & Data Science (W.M.v.d.F.), Vrije Universiteit Amsterdam, Amsterdam UMC, the Netherlands; and Clinical Memory Research Unit (R.O.), Lund University, Sweden
| | - Lyduine E Collij
- From the Radiology & Nuclear Medicine (E.M.C., L.A.d.K., R.M.R., S.C.J.V., D.V., L.E.C., A.D.W., F.B., S.S.V.G., B.N.M.v.B., E.v.d.G.), Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc; Brain Imaging (E.M.C., L.A.d.K., R.M.R., S.C.J.V., D.V., L.E.C., A.D.W., F.B., S.S.V.G., B.N.M.v.B., E.v.d.G.), Amsterdam Neuroscience; Medical Psychology (S.C.J.V.), Amsterdam UMC location University of Amsterdam; Alzheimer Center Amsterdam (A.d.B., J.T., M.v.d.B., A.W.L., P.J.V., P.S., W.M.v.d.F., R.O.), Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc; Neurodegeneration (A.d.B., J.T., M.v.d.B., A.W.L., P.J.V., P.S., W.M.v.d.F., R.O.), Amsterdam Neuroscience; Department of Biological Psychology (A.d.B.), Vrije Universiteit Amsterdam, the Netherlands; Queen Square Institute of Neurology and Centre for Medical Image Computing (F.B.), University College London, United Kingdom; Alzheimer Center Limburg (P.J.V.), School for Mental Health and Neuroscience, Maastricht University, the Netherlands; Division of Neurogeriatrics (P.J.V.), Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden; Department of Epidemiology & Data Science (W.M.v.d.F.), Vrije Universiteit Amsterdam, Amsterdam UMC, the Netherlands; and Clinical Memory Research Unit (R.O.), Lund University, Sweden
| | - Afina W Lemstra
- From the Radiology & Nuclear Medicine (E.M.C., L.A.d.K., R.M.R., S.C.J.V., D.V., L.E.C., A.D.W., F.B., S.S.V.G., B.N.M.v.B., E.v.d.G.), Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc; Brain Imaging (E.M.C., L.A.d.K., R.M.R., S.C.J.V., D.V., L.E.C., A.D.W., F.B., S.S.V.G., B.N.M.v.B., E.v.d.G.), Amsterdam Neuroscience; Medical Psychology (S.C.J.V.), Amsterdam UMC location University of Amsterdam; Alzheimer Center Amsterdam (A.d.B., J.T., M.v.d.B., A.W.L., P.J.V., P.S., W.M.v.d.F., R.O.), Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc; Neurodegeneration (A.d.B., J.T., M.v.d.B., A.W.L., P.J.V., P.S., W.M.v.d.F., R.O.), Amsterdam Neuroscience; Department of Biological Psychology (A.d.B.), Vrije Universiteit Amsterdam, the Netherlands; Queen Square Institute of Neurology and Centre for Medical Image Computing (F.B.), University College London, United Kingdom; Alzheimer Center Limburg (P.J.V.), School for Mental Health and Neuroscience, Maastricht University, the Netherlands; Division of Neurogeriatrics (P.J.V.), Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden; Department of Epidemiology & Data Science (W.M.v.d.F.), Vrije Universiteit Amsterdam, Amsterdam UMC, the Netherlands; and Clinical Memory Research Unit (R.O.), Lund University, Sweden
| | - Albert D Windhorst
- From the Radiology & Nuclear Medicine (E.M.C., L.A.d.K., R.M.R., S.C.J.V., D.V., L.E.C., A.D.W., F.B., S.S.V.G., B.N.M.v.B., E.v.d.G.), Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc; Brain Imaging (E.M.C., L.A.d.K., R.M.R., S.C.J.V., D.V., L.E.C., A.D.W., F.B., S.S.V.G., B.N.M.v.B., E.v.d.G.), Amsterdam Neuroscience; Medical Psychology (S.C.J.V.), Amsterdam UMC location University of Amsterdam; Alzheimer Center Amsterdam (A.d.B., J.T., M.v.d.B., A.W.L., P.J.V., P.S., W.M.v.d.F., R.O.), Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc; Neurodegeneration (A.d.B., J.T., M.v.d.B., A.W.L., P.J.V., P.S., W.M.v.d.F., R.O.), Amsterdam Neuroscience; Department of Biological Psychology (A.d.B.), Vrije Universiteit Amsterdam, the Netherlands; Queen Square Institute of Neurology and Centre for Medical Image Computing (F.B.), University College London, United Kingdom; Alzheimer Center Limburg (P.J.V.), School for Mental Health and Neuroscience, Maastricht University, the Netherlands; Division of Neurogeriatrics (P.J.V.), Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden; Department of Epidemiology & Data Science (W.M.v.d.F.), Vrije Universiteit Amsterdam, Amsterdam UMC, the Netherlands; and Clinical Memory Research Unit (R.O.), Lund University, Sweden
| | - Frederik Barkhof
- From the Radiology & Nuclear Medicine (E.M.C., L.A.d.K., R.M.R., S.C.J.V., D.V., L.E.C., A.D.W., F.B., S.S.V.G., B.N.M.v.B., E.v.d.G.), Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc; Brain Imaging (E.M.C., L.A.d.K., R.M.R., S.C.J.V., D.V., L.E.C., A.D.W., F.B., S.S.V.G., B.N.M.v.B., E.v.d.G.), Amsterdam Neuroscience; Medical Psychology (S.C.J.V.), Amsterdam UMC location University of Amsterdam; Alzheimer Center Amsterdam (A.d.B., J.T., M.v.d.B., A.W.L., P.J.V., P.S., W.M.v.d.F., R.O.), Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc; Neurodegeneration (A.d.B., J.T., M.v.d.B., A.W.L., P.J.V., P.S., W.M.v.d.F., R.O.), Amsterdam Neuroscience; Department of Biological Psychology (A.d.B.), Vrije Universiteit Amsterdam, the Netherlands; Queen Square Institute of Neurology and Centre for Medical Image Computing (F.B.), University College London, United Kingdom; Alzheimer Center Limburg (P.J.V.), School for Mental Health and Neuroscience, Maastricht University, the Netherlands; Division of Neurogeriatrics (P.J.V.), Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden; Department of Epidemiology & Data Science (W.M.v.d.F.), Vrije Universiteit Amsterdam, Amsterdam UMC, the Netherlands; and Clinical Memory Research Unit (R.O.), Lund University, Sweden
| | - Sandeep S V Golla
- From the Radiology & Nuclear Medicine (E.M.C., L.A.d.K., R.M.R., S.C.J.V., D.V., L.E.C., A.D.W., F.B., S.S.V.G., B.N.M.v.B., E.v.d.G.), Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc; Brain Imaging (E.M.C., L.A.d.K., R.M.R., S.C.J.V., D.V., L.E.C., A.D.W., F.B., S.S.V.G., B.N.M.v.B., E.v.d.G.), Amsterdam Neuroscience; Medical Psychology (S.C.J.V.), Amsterdam UMC location University of Amsterdam; Alzheimer Center Amsterdam (A.d.B., J.T., M.v.d.B., A.W.L., P.J.V., P.S., W.M.v.d.F., R.O.), Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc; Neurodegeneration (A.d.B., J.T., M.v.d.B., A.W.L., P.J.V., P.S., W.M.v.d.F., R.O.), Amsterdam Neuroscience; Department of Biological Psychology (A.d.B.), Vrije Universiteit Amsterdam, the Netherlands; Queen Square Institute of Neurology and Centre for Medical Image Computing (F.B.), University College London, United Kingdom; Alzheimer Center Limburg (P.J.V.), School for Mental Health and Neuroscience, Maastricht University, the Netherlands; Division of Neurogeriatrics (P.J.V.), Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden; Department of Epidemiology & Data Science (W.M.v.d.F.), Vrije Universiteit Amsterdam, Amsterdam UMC, the Netherlands; and Clinical Memory Research Unit (R.O.), Lund University, Sweden
| | - Pieter Jelle Visser
- From the Radiology & Nuclear Medicine (E.M.C., L.A.d.K., R.M.R., S.C.J.V., D.V., L.E.C., A.D.W., F.B., S.S.V.G., B.N.M.v.B., E.v.d.G.), Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc; Brain Imaging (E.M.C., L.A.d.K., R.M.R., S.C.J.V., D.V., L.E.C., A.D.W., F.B., S.S.V.G., B.N.M.v.B., E.v.d.G.), Amsterdam Neuroscience; Medical Psychology (S.C.J.V.), Amsterdam UMC location University of Amsterdam; Alzheimer Center Amsterdam (A.d.B., J.T., M.v.d.B., A.W.L., P.J.V., P.S., W.M.v.d.F., R.O.), Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc; Neurodegeneration (A.d.B., J.T., M.v.d.B., A.W.L., P.J.V., P.S., W.M.v.d.F., R.O.), Amsterdam Neuroscience; Department of Biological Psychology (A.d.B.), Vrije Universiteit Amsterdam, the Netherlands; Queen Square Institute of Neurology and Centre for Medical Image Computing (F.B.), University College London, United Kingdom; Alzheimer Center Limburg (P.J.V.), School for Mental Health and Neuroscience, Maastricht University, the Netherlands; Division of Neurogeriatrics (P.J.V.), Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden; Department of Epidemiology & Data Science (W.M.v.d.F.), Vrije Universiteit Amsterdam, Amsterdam UMC, the Netherlands; and Clinical Memory Research Unit (R.O.), Lund University, Sweden
| | - Philip Scheltens
- From the Radiology & Nuclear Medicine (E.M.C., L.A.d.K., R.M.R., S.C.J.V., D.V., L.E.C., A.D.W., F.B., S.S.V.G., B.N.M.v.B., E.v.d.G.), Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc; Brain Imaging (E.M.C., L.A.d.K., R.M.R., S.C.J.V., D.V., L.E.C., A.D.W., F.B., S.S.V.G., B.N.M.v.B., E.v.d.G.), Amsterdam Neuroscience; Medical Psychology (S.C.J.V.), Amsterdam UMC location University of Amsterdam; Alzheimer Center Amsterdam (A.d.B., J.T., M.v.d.B., A.W.L., P.J.V., P.S., W.M.v.d.F., R.O.), Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc; Neurodegeneration (A.d.B., J.T., M.v.d.B., A.W.L., P.J.V., P.S., W.M.v.d.F., R.O.), Amsterdam Neuroscience; Department of Biological Psychology (A.d.B.), Vrije Universiteit Amsterdam, the Netherlands; Queen Square Institute of Neurology and Centre for Medical Image Computing (F.B.), University College London, United Kingdom; Alzheimer Center Limburg (P.J.V.), School for Mental Health and Neuroscience, Maastricht University, the Netherlands; Division of Neurogeriatrics (P.J.V.), Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden; Department of Epidemiology & Data Science (W.M.v.d.F.), Vrije Universiteit Amsterdam, Amsterdam UMC, the Netherlands; and Clinical Memory Research Unit (R.O.), Lund University, Sweden
| | - Wiesje M van der Flier
- From the Radiology & Nuclear Medicine (E.M.C., L.A.d.K., R.M.R., S.C.J.V., D.V., L.E.C., A.D.W., F.B., S.S.V.G., B.N.M.v.B., E.v.d.G.), Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc; Brain Imaging (E.M.C., L.A.d.K., R.M.R., S.C.J.V., D.V., L.E.C., A.D.W., F.B., S.S.V.G., B.N.M.v.B., E.v.d.G.), Amsterdam Neuroscience; Medical Psychology (S.C.J.V.), Amsterdam UMC location University of Amsterdam; Alzheimer Center Amsterdam (A.d.B., J.T., M.v.d.B., A.W.L., P.J.V., P.S., W.M.v.d.F., R.O.), Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc; Neurodegeneration (A.d.B., J.T., M.v.d.B., A.W.L., P.J.V., P.S., W.M.v.d.F., R.O.), Amsterdam Neuroscience; Department of Biological Psychology (A.d.B.), Vrije Universiteit Amsterdam, the Netherlands; Queen Square Institute of Neurology and Centre for Medical Image Computing (F.B.), University College London, United Kingdom; Alzheimer Center Limburg (P.J.V.), School for Mental Health and Neuroscience, Maastricht University, the Netherlands; Division of Neurogeriatrics (P.J.V.), Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden; Department of Epidemiology & Data Science (W.M.v.d.F.), Vrije Universiteit Amsterdam, Amsterdam UMC, the Netherlands; and Clinical Memory Research Unit (R.O.), Lund University, Sweden
| | - Rik Ossenkoppele
- From the Radiology & Nuclear Medicine (E.M.C., L.A.d.K., R.M.R., S.C.J.V., D.V., L.E.C., A.D.W., F.B., S.S.V.G., B.N.M.v.B., E.v.d.G.), Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc; Brain Imaging (E.M.C., L.A.d.K., R.M.R., S.C.J.V., D.V., L.E.C., A.D.W., F.B., S.S.V.G., B.N.M.v.B., E.v.d.G.), Amsterdam Neuroscience; Medical Psychology (S.C.J.V.), Amsterdam UMC location University of Amsterdam; Alzheimer Center Amsterdam (A.d.B., J.T., M.v.d.B., A.W.L., P.J.V., P.S., W.M.v.d.F., R.O.), Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc; Neurodegeneration (A.d.B., J.T., M.v.d.B., A.W.L., P.J.V., P.S., W.M.v.d.F., R.O.), Amsterdam Neuroscience; Department of Biological Psychology (A.d.B.), Vrije Universiteit Amsterdam, the Netherlands; Queen Square Institute of Neurology and Centre for Medical Image Computing (F.B.), University College London, United Kingdom; Alzheimer Center Limburg (P.J.V.), School for Mental Health and Neuroscience, Maastricht University, the Netherlands; Division of Neurogeriatrics (P.J.V.), Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden; Department of Epidemiology & Data Science (W.M.v.d.F.), Vrije Universiteit Amsterdam, Amsterdam UMC, the Netherlands; and Clinical Memory Research Unit (R.O.), Lund University, Sweden
| | - Bart N M van Berckel
- From the Radiology & Nuclear Medicine (E.M.C., L.A.d.K., R.M.R., S.C.J.V., D.V., L.E.C., A.D.W., F.B., S.S.V.G., B.N.M.v.B., E.v.d.G.), Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc; Brain Imaging (E.M.C., L.A.d.K., R.M.R., S.C.J.V., D.V., L.E.C., A.D.W., F.B., S.S.V.G., B.N.M.v.B., E.v.d.G.), Amsterdam Neuroscience; Medical Psychology (S.C.J.V.), Amsterdam UMC location University of Amsterdam; Alzheimer Center Amsterdam (A.d.B., J.T., M.v.d.B., A.W.L., P.J.V., P.S., W.M.v.d.F., R.O.), Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc; Neurodegeneration (A.d.B., J.T., M.v.d.B., A.W.L., P.J.V., P.S., W.M.v.d.F., R.O.), Amsterdam Neuroscience; Department of Biological Psychology (A.d.B.), Vrije Universiteit Amsterdam, the Netherlands; Queen Square Institute of Neurology and Centre for Medical Image Computing (F.B.), University College London, United Kingdom; Alzheimer Center Limburg (P.J.V.), School for Mental Health and Neuroscience, Maastricht University, the Netherlands; Division of Neurogeriatrics (P.J.V.), Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden; Department of Epidemiology & Data Science (W.M.v.d.F.), Vrije Universiteit Amsterdam, Amsterdam UMC, the Netherlands; and Clinical Memory Research Unit (R.O.), Lund University, Sweden
| | - Elsmarieke van de Giessen
- From the Radiology & Nuclear Medicine (E.M.C., L.A.d.K., R.M.R., S.C.J.V., D.V., L.E.C., A.D.W., F.B., S.S.V.G., B.N.M.v.B., E.v.d.G.), Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc; Brain Imaging (E.M.C., L.A.d.K., R.M.R., S.C.J.V., D.V., L.E.C., A.D.W., F.B., S.S.V.G., B.N.M.v.B., E.v.d.G.), Amsterdam Neuroscience; Medical Psychology (S.C.J.V.), Amsterdam UMC location University of Amsterdam; Alzheimer Center Amsterdam (A.d.B., J.T., M.v.d.B., A.W.L., P.J.V., P.S., W.M.v.d.F., R.O.), Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc; Neurodegeneration (A.d.B., J.T., M.v.d.B., A.W.L., P.J.V., P.S., W.M.v.d.F., R.O.), Amsterdam Neuroscience; Department of Biological Psychology (A.d.B.), Vrije Universiteit Amsterdam, the Netherlands; Queen Square Institute of Neurology and Centre for Medical Image Computing (F.B.), University College London, United Kingdom; Alzheimer Center Limburg (P.J.V.), School for Mental Health and Neuroscience, Maastricht University, the Netherlands; Division of Neurogeriatrics (P.J.V.), Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden; Department of Epidemiology & Data Science (W.M.v.d.F.), Vrije Universiteit Amsterdam, Amsterdam UMC, the Netherlands; and Clinical Memory Research Unit (R.O.), Lund University, Sweden
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111
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Jonker I, Doorduin J, Knegtering H, van't Hag E, Dierckx RA, de Vries EFJ, Schoevers RA, Klein HC. Antiviral treatment in schizophrenia: a randomized pilot PET study on the effects of valaciclovir on neuroinflammation. Psychol Med 2023; 53:7087-7095. [PMID: 37016791 PMCID: PMC10719624 DOI: 10.1017/s0033291723000430] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/11/2022] [Revised: 01/22/2023] [Accepted: 02/03/2023] [Indexed: 04/06/2023]
Abstract
BACKGROUND Patients with schizophrenia experience cognitive impairment, which could be related to neuroinflammation in the hippocampus. The cause for such hippocampal inflammation is still unknown, but it has been suggested that herpes virus infection is involved. This study therefore aimed to determine whether add-on treatment of schizophrenic patients with the anti- viral drug valaciclovir would reduce hippocampal neuroinflammation and consequently improve cognitive symptoms. METHODS We performed a double-blind monocenter study in 24 male and female patients with schizophrenia, experiencing active psychotic symptoms. Patients were orally treated with the anti-viral drug valaciclovir for seven consecutive days (8 g/day). Neuroinflammation was measured with Positron Emission Tomography using the translocator protein ligand [11C]-PK11195, pre-treatment and at seven days post-treatment, as were psychotic symptoms and cognition. RESULTS Valaciclovir treatment resulted in reduced TSPO binding (39%) in the hippocampus, as well as in the brainstem, frontal lobe, temporal lobe, parahippocampal gyrus, amygdala, parietal lobe, occipital lobe, insula and cingulate gyri, nucleus accumbens and thalamus (31-40%) when using binding potential (BPND) as an outcome. With total distribution volume (VT) as outcome we found essentially the same results, but associations only approached statistical significance (p = 0.050 for hippocampus). Placebo treatment did not affect neuroinflammation. No effects of valaciclovir on psychotic symptoms or cognitive functioning were found. CONCLUSION We found a decreased TSPO binding following antiviral treatment, which could suggest a viral underpinning of neuroinflammation in psychotic patients. Whether this reduced neuroinflammation by treatment with valaciclovir has clinical implications and is specific for schizophrenia warrants further research.
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Affiliation(s)
- Iris Jonker
- Department of Psychiatry, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands
| | - Janine Doorduin
- Department of Nuclear Medicine and Molecular Imaging, University of Groningen, University Medical Center Groningen, Groningen, the Netherlands
| | - Henderikus Knegtering
- Department of Psychiatry, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands
- Lentis Mental Health Institution, Groningen, The Netherlands
| | - Erna van't Hag
- Department of Psychiatry, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands
| | - Rudi A. Dierckx
- Department of Nuclear Medicine and Molecular Imaging, University of Groningen, University Medical Center Groningen, Groningen, the Netherlands
| | - Erik F. J. de Vries
- Department of Nuclear Medicine and Molecular Imaging, University of Groningen, University Medical Center Groningen, Groningen, the Netherlands
| | - Robert A. Schoevers
- Department of Psychiatry, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands
| | - Hans C. Klein
- Department of Nuclear Medicine and Molecular Imaging, University of Groningen, University Medical Center Groningen, Groningen, the Netherlands
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112
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Volpi T, Vallini G, Silvestri E, Francisci MD, Durbin T, Corbetta M, Lee JJ, Vlassenko AG, Goyal MS, Bertoldo A. A new framework for metabolic connectivity mapping using bolus [ 18F]FDG PET and kinetic modeling. J Cereb Blood Flow Metab 2023; 43:1905-1918. [PMID: 37377103 PMCID: PMC10676136 DOI: 10.1177/0271678x231184365] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/02/2023] [Revised: 04/11/2023] [Accepted: 06/03/2023] [Indexed: 06/29/2023]
Abstract
Metabolic connectivity (MC) has been previously proposed as the covariation of static [18F]FDG PET images across participants, i.e., across-individual MC (ai-MC). In few cases, MC has been inferred from dynamic [18F]FDG signals, i.e., within-individual MC (wi-MC), as for resting-state fMRI functional connectivity (FC). The validity and interpretability of both approaches is an important open issue. Here we reassess this topic, aiming to 1) develop a novel wi-MC methodology; 2) compare ai-MC maps from standardized uptake value ratio (SUVR) vs. [18F]FDG kinetic parameters fully describing the tracer behavior (i.e., Ki, K1, k3); 3) assess MC interpretability in comparison to structural connectivity and FC. We developed a new approach based on Euclidean distance to calculate wi-MC from PET time-activity curves. The across-individual correlation of SUVR, Ki, K1, k3 produced different networks depending on the chosen [18F]FDG parameter (k3 MC vs. SUVR MC, r = 0.44). We found that wi-MC and ai-MC matrices are dissimilar (maximum r = 0.37), and that the match with FC is higher for wi-MC (Dice similarity: 0.47-0.63) than for ai-MC (0.24-0.39). Our analyses demonstrate that calculating individual-level MC from dynamic PET is feasible and yields interpretable matrices that bear similarity to fMRI FC measures.
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Affiliation(s)
- Tommaso Volpi
- Department of Radiology and Biomedical Imaging, Yale University, New Haven, CT, USA
- Padova Neuroscience Center, University of Padova, Padova, Italy
| | - Giulia Vallini
- Department of Information Engineering, University of Padova, Padova, Italy
| | - Erica Silvestri
- Department of Information Engineering, University of Padova, Padova, Italy
| | | | - Tony Durbin
- Neuroimaging Laboratories at the Mallinckrodt Institute of Radiology, Washington University School of Medicine, St Louis, MO, USA
| | - Maurizio Corbetta
- Padova Neuroscience Center, University of Padova, Padova, Italy
- Department of Neuroscience, University of Padova, Padova, Italy
| | - John J Lee
- Neuroimaging Laboratories at the Mallinckrodt Institute of Radiology, Washington University School of Medicine, St Louis, MO, USA
| | - Andrei G Vlassenko
- Neuroimaging Laboratories at the Mallinckrodt Institute of Radiology, Washington University School of Medicine, St Louis, MO, USA
| | - Manu S Goyal
- Neuroimaging Laboratories at the Mallinckrodt Institute of Radiology, Washington University School of Medicine, St Louis, MO, USA
| | - Alessandra Bertoldo
- Padova Neuroscience Center, University of Padova, Padova, Italy
- Department of Information Engineering, University of Padova, Padova, Italy
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113
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Yoshida Y, Yokoi T, Hara K, Watanabe H, Yamaguchi H, Bagarinao E, Masuda M, Kato T, Ogura A, Ohdake R, Kawabata K, Katsuno M, Kato K, Naganawa S, Okamura N, Yanai K, Sobue G. <Editors' Choice> Pattern of THK 5351 retention in normal aging involves core regions of resting state networks associated with higher cognitive function. NAGOYA JOURNAL OF MEDICAL SCIENCE 2023; 85:758-771. [PMID: 38155624 PMCID: PMC10751491 DOI: 10.18999/nagjms.85.4.758] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 06/21/2022] [Accepted: 12/22/2022] [Indexed: 12/30/2023]
Abstract
We aimed to elucidate the distribution pattern of the positron emission tomography probe [18F]THK 5351, a marker for astrogliosis and tau accumulation, in healthy aging. We also assessed the relationship between THK5351 retention and resting state networks. We enrolled 62 healthy participants in this study. All participants underwent magnetic resonance imaging/positron emission tomography scanning consisting of T1-weighted images, resting state functional magnetic resonance imaging, Pittsburgh Compound-B and THK positron emission tomography. The preprocessed THK images were entered into a scaled subprofile modeling/principal component analysis to extract THK distribution patterns. Using the most significant THK pattern, we generated regions of interest, and performed seed-based functional connectivity analyses. We also evaluated the functional connectivity overlap ratio to identify regions with high between-network connectivity. The most significant THK distributions were observed in the medial prefrontal cortex and bilateral putamen. The seed regions of interest in the medial prefrontal cortex had a functional connectivity map that significantly overlapped with regions of the dorsal default mode network. The seed regions of interest in the putamen showed strong overlap with the basal ganglia and anterior salience networks. The functional connectivity overlap ratio also showed that three peak regions had the characteristics of connector hubs. We have identified an age-related spatial distribution of THK in the medial prefrontal cortex and basal ganglia in normal aging. Interestingly, the distribution's peaks are located in regions of connector hubs that are strongly connected to large-scale resting state networks associated with higher cognitive function.
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Affiliation(s)
- Yusuke Yoshida
- Department of Neurology, Nagoya University Graduate School of Medicine, Nagoya, Japan
| | - Takamasa Yokoi
- Department of Neurology, Toyohashi Municipal Hospital, Toyohashi, Japan
| | - Kazuhiro Hara
- Department of Neurology, Nagoya University Graduate School of Medicine, Nagoya, Japan
| | - Hirohisa Watanabe
- Brain and Mind Research Center, Nagoya University, Nagoya, Japan
- Department of Neurology, School of Medicine, Fujita Health University, Toyoake, Japan
| | - Hiroshi Yamaguchi
- Department of Radiological and Medical Laboratory Sciences, Nagoya University Graduate School of Medicine, Nagoya, Japan
| | | | - Michihito Masuda
- Department of Neurology, Nagoya University Graduate School of Medicine, Nagoya, Japan
| | - Toshiyasu Kato
- Department of Neurology, Nagoya University Graduate School of Medicine, Nagoya, Japan
| | - Aya Ogura
- Department of Neurology, Nagoya University Graduate School of Medicine, Nagoya, Japan
| | - Reiko Ohdake
- Brain and Mind Research Center, Nagoya University, Nagoya, Japan
| | - Kazuya Kawabata
- Department of Neurology, Nagoya University Graduate School of Medicine, Nagoya, Japan
| | - Masahisa Katsuno
- Department of Neurology, Nagoya University Graduate School of Medicine, Nagoya, Japan
| | - Katsuhiko Kato
- Department of Radiological and Medical Laboratory Sciences, Nagoya University Graduate School of Medicine, Nagoya, Japan
| | - Shinji Naganawa
- Department of Radiology, Nagoya University Graduate School of Medicine, Nagoya, Japan
| | - Nobuyuki Okamura
- Division of Pharmacology, Faculty of Medicine, Tohoku Medical and Pharmaceutical University, Sendai, Japan
| | - Kazuhiko Yanai
- Department of Pharmacology, Tohoku University School of Medicine, Sendai, Japan
| | - Gen Sobue
- Brain and Mind Research Center, Nagoya University, Nagoya, Japan
- Aichi Medical University, Nagakute, Japan
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114
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Bollack A, Pemberton HG, Collij LE, Markiewicz P, Cash DM, Farrar G, Barkhof F. Longitudinal amyloid and tau PET imaging in Alzheimer's disease: A systematic review of methodologies and factors affecting quantification. Alzheimers Dement 2023; 19:5232-5252. [PMID: 37303269 DOI: 10.1002/alz.13158] [Citation(s) in RCA: 14] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/21/2022] [Revised: 04/21/2023] [Accepted: 04/25/2023] [Indexed: 06/13/2023]
Abstract
Deposition of amyloid and tau pathology can be quantified in vivo using positron emission tomography (PET). Accurate longitudinal measurements of accumulation from these images are critical for characterizing the start and spread of the disease. However, these measurements are challenging; precision and accuracy can be affected substantially by various sources of errors and variability. This review, supported by a systematic search of the literature, summarizes the current design and methodologies of longitudinal PET studies. Intrinsic, biological causes of variability of the Alzheimer's disease (AD) protein load over time are then detailed. Technical factors contributing to longitudinal PET measurement uncertainty are highlighted, followed by suggestions for mitigating these factors, including possible techniques that leverage shared information between serial scans. Controlling for intrinsic variability and reducing measurement uncertainty in longitudinal PET pipelines will provide more accurate and precise markers of disease evolution, improve clinical trial design, and aid therapy response monitoring.
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Affiliation(s)
- Ariane Bollack
- Department of Medical Physics and Biomedical Engineering, Centre for Medical Image Computing (CMIC), University College London, London, UK
| | - Hugh G Pemberton
- Department of Medical Physics and Biomedical Engineering, Centre for Medical Image Computing (CMIC), University College London, London, UK
- GE Healthcare, Amersham, UK
- UCL Queen Square Institute of Neurology, London, UK
| | - Lyduine E Collij
- Department of Radiology and Nuclear Medicine, Amsterdam UMC, location VUmc, Amsterdam, The Netherlands
- Clinical Memory Research Unit, Department of Clinical Sciences, Lund University, Malmö, Sweden
| | - Pawel Markiewicz
- Department of Medical Physics and Biomedical Engineering, Centre for Medical Image Computing (CMIC), University College London, London, UK
| | - David M Cash
- UCL Queen Square Institute of Neurology, London, UK
- UK Dementia Research Institute at University College London, London, UK
| | | | - Frederik Barkhof
- Department of Medical Physics and Biomedical Engineering, Centre for Medical Image Computing (CMIC), University College London, London, UK
- UCL Queen Square Institute of Neurology, London, UK
- Department of Radiology and Nuclear Medicine, Amsterdam UMC, location VUmc, Amsterdam, The Netherlands
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115
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Karl V, Rohe T. Structural brain changes in emotion recognition across the adult lifespan. Soc Cogn Affect Neurosci 2023; 18:nsad052. [PMID: 37769357 PMCID: PMC10627307 DOI: 10.1093/scan/nsad052] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/13/2022] [Revised: 06/22/2023] [Accepted: 09/19/2023] [Indexed: 09/30/2023] Open
Abstract
Emotion recognition (ER) declines with increasing age, yet little is known whether this observation is based on structural brain changes conveyed by differential atrophy. To investigate whether age-related ER decline correlates with reduced grey matter (GM) volume in emotion-related brain regions, we conducted a voxel-based morphometry analysis using data of the Human Connectome Project-Aging (N = 238, aged 36-87) in which facial ER was tested. We expected to find brain regions that show an additive or super-additive age-related change in GM volume indicating atrophic processes that reduce ER in older adults. The data did not support our hypotheses after correction for multiple comparisons. Exploratory analyses with a threshold of P < 0.001 (uncorrected), however, suggested that relationships between GM volume and age-related general ER may be widely distributed across the cortex. Yet, small effect sizes imply that only a small fraction of the decline of ER in older adults can be attributed to local GM volume changes in single voxels or their multivariate patterns.
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Affiliation(s)
- Valerie Karl
- Institute of Psychology, Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen 91054, Germany
- NORMENT, Division of Mental Health and Addiction, Oslo University Hospital & Institute of Clinical Medicine, University of Oslo, Oslo 0424, Norway
- PROMENTA Research Center, Department of Psychology, University of Oslo, Oslo 0373, Norway
| | - Tim Rohe
- Institute of Psychology, Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen 91054, Germany
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116
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Tuncel H, Visser D, Timmers T, Wolters EE, Ossenkoppele R, van der Flier WM, van Berckel BNM, Boellaard R, Golla SSV. Head-to-head comparison of relative cerebral blood flow derived from dynamic [ 18F]florbetapir and [ 18F]flortaucipir PET in subjects with subjective cognitive decline. EJNMMI Res 2023; 13:93. [PMID: 37889456 PMCID: PMC10611685 DOI: 10.1186/s13550-023-01041-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/21/2023] [Accepted: 10/11/2023] [Indexed: 10/28/2023] Open
Abstract
BACKGROUND Dynamic PET imaging studies provide accurate estimates of specific binding, but also measure the relative tracer delivery (R1), which is a proxy for relative cerebral blood flow (rCBF). Recently, studies suggested that R1 obtained from different tracers could be used interchangeably and is irrespective of target tissue. However, the similarities or differences of R1 obtained from different PET tracers still require validation. Therefore, the goal of the current study was to compare R1 estimates, derived from dynamic [18F]florbetapir (amyloid) and [18F]flortaucipir (tau) PET, in the same subjects with subjective cognitive decline (SCD). RESULTS Voxel-wise analysis presented a small cluster (1.6% of the whole brain) with higher R1 values for [18F]flortaucipir compared to [18F]florbetapir in the Aβ-negative group. These voxels were part of the hippocampus and the left middle occipital gyrus. In part of the thalamus, midbrain and cerebellum, voxels (2.5% of the whole brain) with higher R1 values for [18F]florbetapir were observed. In the Aβ-positive group, a cluster (0.2% of the whole brain) of higher R1 values was observed in part of the hippocampus, right parahippocampal gyrus and in the left sagittal stratum for [18F]flortaucipir compared to [18F]florbetapir. Furthermore, in part of the thalamus, left amygdala, midbrain and right parahippocampal gyrus voxels (0.4% of the whole brain) with higher R1 values for [18F]florbetapir were observed. Despite these differences, [18F]florbetapir R1 had high correspondence with [18F]flortaucipir R1 across all regions of interest (ROIs) and subjects (Aβ-:r2 = 0.79, slope = 0.85, ICC = 0.76; Aβ+: r2 = 0.87, slope = 0.93, ICC = 0.77). CONCLUSION [18F]flortaucipir and [18F]florbetapir showed similar R1 estimates in cortical regions. This finding, put together with previous studies, indicates that R1 could be considered a surrogate for relative cerebral blood flow (rCBF) in the cortex and may be used interchangeably, but with caution, regardless of the choice of these two tracers.
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Affiliation(s)
- Hayel Tuncel
- Department of Radiology and Nuclear Medicine, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, De Boelelaan 1117, 1081 HV, Amsterdam, The Netherlands
| | - Denise Visser
- Department of Radiology and Nuclear Medicine, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, De Boelelaan 1117, 1081 HV, Amsterdam, The Netherlands
| | - Tessa Timmers
- Department of Radiology and Nuclear Medicine, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, De Boelelaan 1117, 1081 HV, Amsterdam, The Netherlands
- Department of Neurology, Alzheimer Center Amsterdam, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands
| | - Emma E Wolters
- Department of Radiology and Nuclear Medicine, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, De Boelelaan 1117, 1081 HV, Amsterdam, The Netherlands
- Department of Neurology, Alzheimer Center Amsterdam, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands
| | - Rik Ossenkoppele
- Department of Neurology, Alzheimer Center Amsterdam, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands
- Clinical Memory Research Unit, Lund University, Lund, Sweden
| | - Wiesje M van der Flier
- Department of Neurology, Alzheimer Center Amsterdam, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands
- Department of Epidemiology and Biostatistics, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands
| | - Bart N M van Berckel
- Department of Radiology and Nuclear Medicine, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, De Boelelaan 1117, 1081 HV, Amsterdam, The Netherlands
| | - Ronald Boellaard
- Department of Radiology and Nuclear Medicine, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, De Boelelaan 1117, 1081 HV, Amsterdam, The Netherlands
| | - Sandeep S V Golla
- Department of Radiology and Nuclear Medicine, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, De Boelelaan 1117, 1081 HV, Amsterdam, The Netherlands.
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117
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Parent O, Bussy A, Devenyi GA, Dai A, Costantino M, Tullo S, Salaciak A, Bedford S, Farzin S, Béland ML, Valiquette V, Villeneuve S, Poirier J, Tardif CL, Dadar M, Chakravarty MM. Assessment of white matter hyperintensity severity using multimodal magnetic resonance imaging. Brain Commun 2023; 5:fcad279. [PMID: 37953840 PMCID: PMC10636521 DOI: 10.1093/braincomms/fcad279] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/04/2023] [Revised: 09/05/2023] [Accepted: 10/17/2023] [Indexed: 11/14/2023] Open
Abstract
White matter hyperintensities are radiological abnormalities reflecting cerebrovascular dysfunction detectable using MRI. White matter hyperintensities are often present in individuals at the later stages of the lifespan and in prodromal stages in the Alzheimer's disease spectrum. Tissue alterations underlying white matter hyperintensities may include demyelination, inflammation and oedema, but these are highly variable by neuroanatomical location and between individuals. There is a crucial need to characterize these white matter hyperintensity tissue alterations in vivo to improve prognosis and, potentially, treatment outcomes. How different MRI measure(s) of tissue microstructure capture clinically-relevant white matter hyperintensity tissue damage is currently unknown. Here, we compared six MRI signal measures sampled within white matter hyperintensities and their associations with multiple clinically-relevant outcomes, consisting of global and cortical brain morphometry, cognitive function, diagnostic and demographic differences and cardiovascular risk factors. We used cross-sectional data from 118 participants: healthy controls (n = 30), individuals at high risk for Alzheimer's disease due to familial history (n = 47), mild cognitive impairment (n = 32) and clinical Alzheimer's disease dementia (n = 9). We sampled the median signal within white matter hyperintensities on weighted MRI images [T1-weighted (T1w), T2-weighted (T2w), T1w/T2w ratio, fluid-attenuated inversion recovery (FLAIR)] as well as the relaxation times from quantitative T1 (qT1) and T2* (qT2*) images. qT2* and fluid-attenuated inversion recovery signals within white matter hyperintensities displayed different age- and disease-related trends compared to normal-appearing white matter signals, suggesting sensitivity to white matter hyperintensity-specific tissue deterioration. Further, white matter hyperintensity qT2*, particularly in periventricular and occipital white matter regions, was consistently associated with all types of clinically-relevant outcomes in both univariate and multivariate analyses and across two parcellation schemes. qT1 and fluid-attenuated inversion recovery measures showed consistent clinical relationships in multivariate but not univariate analyses, while T1w, T2w and T1w/T2w ratio measures were not consistently associated with clinical variables. We observed that the qT2* signal was sensitive to clinically-relevant microstructural tissue alterations specific to white matter hyperintensities. Our results suggest that combining volumetric and signal measures of white matter hyperintensity should be considered to fully characterize the severity of white matter hyperintensities in vivo. These findings may have implications in determining the reversibility of white matter hyperintensities and the potential efficacy of cardio- and cerebrovascular treatments.
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Affiliation(s)
- Olivier Parent
- Cerebral Imaging Centre, Douglas Mental Health University Institute, Montreal, Quebec H4H 1R3, Canada
- Integrated Program in Neuroscience, McGill University, Montreal, Quebec H3A 1A1, Canada
| | - Aurélie Bussy
- Cerebral Imaging Centre, Douglas Mental Health University Institute, Montreal, Quebec H4H 1R3, Canada
- Integrated Program in Neuroscience, McGill University, Montreal, Quebec H3A 1A1, Canada
| | - Gabriel Allan Devenyi
- Cerebral Imaging Centre, Douglas Mental Health University Institute, Montreal, Quebec H4H 1R3, Canada
- Department of Psychiatry, McGill University, Montreal, Quebec H3A 1A1, Canada
| | - Alyssa Dai
- Cerebral Imaging Centre, Douglas Mental Health University Institute, Montreal, Quebec H4H 1R3, Canada
- Integrated Program in Neuroscience, McGill University, Montreal, Quebec H3A 1A1, Canada
- McConnell Brain Imaging Centre, Montreal Neurological Institute, Montreal, Quebec H3A 2B4, Canada
| | - Manuela Costantino
- Cerebral Imaging Centre, Douglas Mental Health University Institute, Montreal, Quebec H4H 1R3, Canada
| | - Stephanie Tullo
- Cerebral Imaging Centre, Douglas Mental Health University Institute, Montreal, Quebec H4H 1R3, Canada
- Integrated Program in Neuroscience, McGill University, Montreal, Quebec H3A 1A1, Canada
| | - Alyssa Salaciak
- Cerebral Imaging Centre, Douglas Mental Health University Institute, Montreal, Quebec H4H 1R3, Canada
| | - Saashi Bedford
- Cerebral Imaging Centre, Douglas Mental Health University Institute, Montreal, Quebec H4H 1R3, Canada
- Department of Psychiatry, McGill University, Montreal, Quebec H3A 1A1, Canada
| | - Sarah Farzin
- Cerebral Imaging Centre, Douglas Mental Health University Institute, Montreal, Quebec H4H 1R3, Canada
| | - Marie-Lise Béland
- Cerebral Imaging Centre, Douglas Mental Health University Institute, Montreal, Quebec H4H 1R3, Canada
| | - Vanessa Valiquette
- Cerebral Imaging Centre, Douglas Mental Health University Institute, Montreal, Quebec H4H 1R3, Canada
- Integrated Program in Neuroscience, McGill University, Montreal, Quebec H3A 1A1, Canada
| | - Sylvia Villeneuve
- Cerebral Imaging Centre, Douglas Mental Health University Institute, Montreal, Quebec H4H 1R3, Canada
- Department of Psychiatry, McGill University, Montreal, Quebec H3A 1A1, Canada
- Center for the Studies in the Prevention of Alzheimer's Disease, Douglas Mental Health University Institute, Montreal, Quebec H4H 1R3, Canada
- McConnell Brain Imaging Centre, Montreal Neurological Institute, Montreal, Quebec H3A 2B4, Canada
| | - Judes Poirier
- Department of Psychiatry, McGill University, Montreal, Quebec H3A 1A1, Canada
- Center for the Studies in the Prevention of Alzheimer's Disease, Douglas Mental Health University Institute, Montreal, Quebec H4H 1R3, Canada
- Molecular Neurobiology Unit, Douglas Mental Health University Institute, Montreal, Quebec H4H 1R3, Canada
- Department of Medicine, McGill University, Montreal, Quebec H4A 3J1, Canada
| | - Christine Lucas Tardif
- McConnell Brain Imaging Centre, Montreal Neurological Institute, Montreal, Quebec H3A 2B4, Canada
- Department of Biomedical Engineering, McGill University, Montreal, Quebec H3A 2B4, Canada
- Department of Neurology and Neurosurgery, McGill University, Montreal, Quebec H3A 1A1, Canada
| | - Mahsa Dadar
- Department of Psychiatry, McGill University, Montreal, Quebec H3A 1A1, Canada
| | - M Mallar Chakravarty
- Cerebral Imaging Centre, Douglas Mental Health University Institute, Montreal, Quebec H4H 1R3, Canada
- Integrated Program in Neuroscience, McGill University, Montreal, Quebec H3A 1A1, Canada
- Department of Psychiatry, McGill University, Montreal, Quebec H3A 1A1, Canada
- Department of Biomedical Engineering, McGill University, Montreal, Quebec H3A 2B4, Canada
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118
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Kitazaki Y, Ikawa M, Hamano T, Sasaki H, Yamaguchi T, Enomoto S, Shirafuji N, Hayashi K, Yamamura O, Tsujikawa T, Okazawa H, Kimura H, Nakamoto Y. Magnetic resonance imaging arterial spin labeling hypoperfusion with diffusion-weighted image hyperintensity is useful for diagnostic imaging of Creutzfeldt-Jakob disease. Front Neurol 2023; 14:1242615. [PMID: 37885479 PMCID: PMC10598551 DOI: 10.3389/fneur.2023.1242615] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/20/2023] [Accepted: 09/14/2023] [Indexed: 10/28/2023] Open
Abstract
Background and objectives Magnetic resonance imaging with arterial spin labeling (ASL) perfusion imaging is a noninvasive method for quantifying cerebral blood flow (CBF). We aimed to evaluate the clinical utility of ASL perfusion imaging to aid in the diagnosis of Creutzfeldt-Jakob disease (CJD). Methods This retrospective study enrolled 10 clinically diagnosed with probable sporadic CJD (sCJD) based on the National CJD Research & Surveillance Unit and EuroCJD criteria and 18 healthy controls (HCs). Diffusion-weighted images (DWIs), CBF images obtained from ASL, N-isopropyl-(123I)-p-iodoamphetamine (123IMP)-single-photon emission computed tomography (SPECT) images, and 18F-fluorodeoxyglucose (18FDG)-positron emission tomography (PET) images were analyzed. First, the cortical values obtained using volume-of-interest (VOI) analysis were normalized using the global mean in each modality. The cortical regions were classified into DWI-High (≥ +1 SD) and DWI-Normal (< +1 SD) regions according to the DWI-intensity values. The normalized cortical values were compared between the two regions for each modality. Second, each modality value was defined as ASL hypoperfusion (< -1 SD), SPECT hypoperfusion (< -1 SD), and PET low accumulation (< -1 SD). The overall agreement rate of DWIs with ASL-CBF, SPECT, and PET was calculated. Third, regression analyses between the normalized ASL-CBF values and normalized SPECT or PET values derived from the VOIs were performed using a scatter plot. Results The mean values of ASL-CBF (N = 10), 123IMP-SPECT (N = 8), and 18FDG-PET (N = 3) in DWI-High regions were significantly lower than those in the DWI-Normal regions (p < 0.001 for all); however, HCs (N = 18) showed no significant differences in ASL-CBF between the two regions. The overall agreement rate of DWI (high or normal) with ASL-CBF (hypoperfusion or normal) (81.8%) was similar to that of SPECT (85.2%) and PET (78.5%) in CJD. The regression analysis showed that the normalized ASL-CBF values significantly correlated with the normalized SPECT (r = 0.44, p < 0.001) and PET values (r = 0.46, p < 0.001) in CJD. Discussion Patients with CJD showed ASL hypoperfusion in lesions with DWI hyperintensity, suggesting that ASL-CBF could be beneficial for the diagnostic aid of CJD.
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Affiliation(s)
- Yuki Kitazaki
- Second Department of Internal Medicine, Faculty of Medical Sciences, University of Fukui, Fukui, Japan
| | - Masamichi Ikawa
- Second Department of Internal Medicine, Faculty of Medical Sciences, University of Fukui, Fukui, Japan
- Biomedical Imaging Research Center, University of Fukui, Fukui, Japan
- Department of Advanced Medicine for Community Healthcare, Faculty of Medical Sciences, University of Fukui, Fukui, Japan
| | - Tadanori Hamano
- Second Department of Internal Medicine, Faculty of Medical Sciences, University of Fukui, Fukui, Japan
- Department of Aging and Dementia (DAD), University of Fukui, Fukui, Japan
- Life Science Innovation Center, University of Fukui, Fukui, Japan
| | - Hirohito Sasaki
- Second Department of Internal Medicine, Faculty of Medical Sciences, University of Fukui, Fukui, Japan
| | - Tomohisa Yamaguchi
- Second Department of Internal Medicine, Faculty of Medical Sciences, University of Fukui, Fukui, Japan
| | - Soichi Enomoto
- Second Department of Internal Medicine, Faculty of Medical Sciences, University of Fukui, Fukui, Japan
| | - Norimichi Shirafuji
- Second Department of Internal Medicine, Faculty of Medical Sciences, University of Fukui, Fukui, Japan
| | - Kouji Hayashi
- Second Department of Internal Medicine, Faculty of Medical Sciences, University of Fukui, Fukui, Japan
- Department of Rehabilitation, Faculty of Health Science, Fukui Health Science University, Fukui, Japan
| | - Osamu Yamamura
- Second Department of Internal Medicine, Faculty of Medical Sciences, University of Fukui, Fukui, Japan
| | - Tetsuya Tsujikawa
- Biomedical Imaging Research Center, University of Fukui, Fukui, Japan
| | - Hidehiko Okazawa
- Biomedical Imaging Research Center, University of Fukui, Fukui, Japan
| | - Hirohiko Kimura
- Department of Radiology, Faculty of Medical Sciences, University of Fukui, Fukui, Japan
| | - Yasunari Nakamoto
- Second Department of Internal Medicine, Faculty of Medical Sciences, University of Fukui, Fukui, Japan
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119
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Schoonhoven DN, Coomans EM, Millán AP, van Nifterick AM, Visser D, Ossenkoppele R, Tuncel H, van der Flier WM, Golla SSV, Scheltens P, Hillebrand A, van Berckel BNM, Stam CJ, Gouw AA. Tau protein spreads through functionally connected neurons in Alzheimer's disease: a combined MEG/PET study. Brain 2023; 146:4040-4054. [PMID: 37279597 PMCID: PMC10545627 DOI: 10.1093/brain/awad189] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/23/2022] [Revised: 03/03/2023] [Accepted: 04/10/2023] [Indexed: 06/08/2023] Open
Abstract
Recent studies on Alzheimer's disease (AD) suggest that tau proteins spread through the brain following neuronal connections. Several mechanisms could be involved in this process: spreading between brain regions that interact strongly (functional connectivity); through the pattern of anatomical connections (structural connectivity); or simple diffusion. Using magnetoencephalography (MEG), we investigated which spreading pathways influence tau protein spreading by modelling the tau propagation process using an epidemic spreading model. We compared the modelled tau depositions with 18F-flortaucipir PET binding potentials at several stages of the AD continuum. In this cross-sectional study, we analysed source-reconstructed MEG data and dynamic 100-min 18F-flortaucipir PET from 57 subjects positive for amyloid-β pathology [preclinical AD (n = 16), mild cognitive impairment (MCI) due to AD (n = 16) and AD dementia (n = 25)]. Cognitively healthy subjects without amyloid-β pathology were included as controls (n = 25). Tau propagation was modelled as an epidemic process (susceptible-infected model) on MEG-based functional networks [in alpha (8-13 Hz) and beta (13-30 Hz) bands], a structural or diffusion network, starting from the middle and inferior temporal lobe. The group-level network of the control group was used as input for the model to predict tau deposition in three stages of the AD continuum. To assess performance, model output was compared to the group-specific tau deposition patterns as measured with 18F-flortaucipir PET. We repeated the analysis by using networks of the preceding disease stage and/or using regions with most observed tau deposition during the preceding stage as seeds. In the preclinical AD stage, the functional networks predicted most of the modelled tau-PET binding potential, with best correlations between model and tau-PET [corrected amplitude envelope correlation (AEC-c) alpha C = 0.584; AEC-c beta C = 0.569], followed by the structural network (C = 0.451) and simple diffusion (C = 0.451). Prediction accuracy declined for the MCI and AD dementia stages, although the correlation between modelled tau and tau-PET binding remained highest for the functional networks (C = 0.384; C = 0.376). Replacing the control-network with the network from the preceding disease stage and/or alternative seeds improved prediction accuracy in MCI but not in the dementia stage. These results suggest that in addition to structural connections, functional connections play an important role in tau spread, and highlight that neuronal dynamics play a key role in promoting this pathological process. Aberrant neuronal communication patterns should be taken into account when identifying targets for future therapy. Our results also suggest that this process is more important in earlier disease stages (preclinical AD/MCI); possibly, in later stages, other processes may be influential.
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Affiliation(s)
- Deborah N Schoonhoven
- Department of Clinical Neurophysiology and MEG Center, Neurology, Amsterdam UMC location Vrije Universiteit Amsterdam, 1081 HZ Amsterdam, The Netherlands
- Alzheimer Center Amsterdam, Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc, 1081 HZ Amsterdam, The Netherlands
- Amsterdam Neuroscience, Neurodegeneration, 1081 HV Amsterdam, The Netherlands
| | - Emma M Coomans
- Alzheimer Center Amsterdam, Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc, 1081 HZ Amsterdam, The Netherlands
- Amsterdam Neuroscience, Neurodegeneration, 1081 HV Amsterdam, The Netherlands
- Radiology and Nuclear Medicine, Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc, 1081 HZ Amsterdam, The Netherlands
- Amsterdam Neuroscience, Brain Imaging, 1081 HV Amsterdam, The Netherlands
| | - Ana P Millán
- Department of Clinical Neurophysiology and MEG Center, Neurology, Amsterdam UMC location Vrije Universiteit Amsterdam, 1081 HZ Amsterdam, The Netherlands
- Amsterdam Neuroscience, Brain Imaging, 1081 HV Amsterdam, The Netherlands
| | - Anne M van Nifterick
- Department of Clinical Neurophysiology and MEG Center, Neurology, Amsterdam UMC location Vrije Universiteit Amsterdam, 1081 HZ Amsterdam, The Netherlands
- Alzheimer Center Amsterdam, Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc, 1081 HZ Amsterdam, The Netherlands
- Amsterdam Neuroscience, Neurodegeneration, 1081 HV Amsterdam, The Netherlands
| | - Denise Visser
- Alzheimer Center Amsterdam, Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc, 1081 HZ Amsterdam, The Netherlands
- Amsterdam Neuroscience, Neurodegeneration, 1081 HV Amsterdam, The Netherlands
- Radiology and Nuclear Medicine, Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc, 1081 HZ Amsterdam, The Netherlands
- Amsterdam Neuroscience, Brain Imaging, 1081 HV Amsterdam, The Netherlands
| | - Rik Ossenkoppele
- Alzheimer Center Amsterdam, Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc, 1081 HZ Amsterdam, The Netherlands
- Amsterdam Neuroscience, Neurodegeneration, 1081 HV Amsterdam, The Netherlands
- Radiology and Nuclear Medicine, Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc, 1081 HZ Amsterdam, The Netherlands
- Amsterdam Neuroscience, Brain Imaging, 1081 HV Amsterdam, The Netherlands
- Clinical Memory Research Unit, Lund University, 221 00 Lund, Sweden
| | - Hayel Tuncel
- Amsterdam Neuroscience, Neurodegeneration, 1081 HV Amsterdam, The Netherlands
- Radiology and Nuclear Medicine, Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc, 1081 HZ Amsterdam, The Netherlands
- Amsterdam Neuroscience, Brain Imaging, 1081 HV Amsterdam, The Netherlands
| | - Wiesje M van der Flier
- Alzheimer Center Amsterdam, Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc, 1081 HZ Amsterdam, The Netherlands
- Amsterdam Neuroscience, Neurodegeneration, 1081 HV Amsterdam, The Netherlands
| | - Sandeep S V Golla
- Amsterdam Neuroscience, Neurodegeneration, 1081 HV Amsterdam, The Netherlands
- Radiology and Nuclear Medicine, Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc, 1081 HZ Amsterdam, The Netherlands
- Amsterdam Neuroscience, Brain Imaging, 1081 HV Amsterdam, The Netherlands
| | - Philip Scheltens
- Alzheimer Center Amsterdam, Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc, 1081 HZ Amsterdam, The Netherlands
- Amsterdam Neuroscience, Neurodegeneration, 1081 HV Amsterdam, The Netherlands
| | - Arjan Hillebrand
- Department of Clinical Neurophysiology and MEG Center, Neurology, Amsterdam UMC location Vrije Universiteit Amsterdam, 1081 HZ Amsterdam, The Netherlands
- Amsterdam Neuroscience, Brain Imaging, 1081 HV Amsterdam, The Netherlands
- Amsterdam Neuroscience, Systems and Network Neuroscience, 1081 HV Amsterdam, The Netherlands
| | - Bart N M van Berckel
- Amsterdam Neuroscience, Neurodegeneration, 1081 HV Amsterdam, The Netherlands
- Radiology and Nuclear Medicine, Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc, 1081 HZ Amsterdam, The Netherlands
- Amsterdam Neuroscience, Brain Imaging, 1081 HV Amsterdam, The Netherlands
| | - Cornelis J Stam
- Department of Clinical Neurophysiology and MEG Center, Neurology, Amsterdam UMC location Vrije Universiteit Amsterdam, 1081 HZ Amsterdam, The Netherlands
- Amsterdam Neuroscience, Neurodegeneration, 1081 HV Amsterdam, The Netherlands
| | - Alida A Gouw
- Department of Clinical Neurophysiology and MEG Center, Neurology, Amsterdam UMC location Vrije Universiteit Amsterdam, 1081 HZ Amsterdam, The Netherlands
- Alzheimer Center Amsterdam, Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc, 1081 HZ Amsterdam, The Netherlands
- Amsterdam Neuroscience, Neurodegeneration, 1081 HV Amsterdam, The Netherlands
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Albayrak B, Dathe AK, Heuser-Spura KM, Felderhoff-Mueser U, Timmann D, Huening BM. Ataxia Rating Scales Reveal Increased Scores in Very Preterm Born 5-6-Year-Old Preschool Children and Young Adults. CEREBELLUM (LONDON, ENGLAND) 2023; 22:877-887. [PMID: 36018542 PMCID: PMC10485085 DOI: 10.1007/s12311-022-01463-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Accepted: 08/18/2022] [Indexed: 06/15/2023]
Abstract
The aim of this study is to investigate whether scores in ataxia rating scales (ARS) are different in very preterm (VP) preschool and adult participants compared to term controls. This is a case-control study. Sixty VP children (years: 5.5-6.5; gestational age: 23.9-31.7 weeks) and 56 VP adults (years: 17.8-27.9; gestational age: 23.3-32.0 weeks) without major cerebral lesions participated in the study; 60-age and sex-matched term children and 64 term adults for comparison were used in the study intervened with the assessment with International Cooperative Ataxia Rating Scale (ICARS) and Scale for Assessment and Rating of Ataxia (SARA). Main outcome measures are primary outcome: total icars and sara scores in preterm (vp) participants versus controls. Results showed that VP children showed significantly higher total ICARS (M 15.98, SD 6.29, range 4.0-32.0; p < .001) and SARA scores (M 6.5, SD 2.53, range 1.0-15.0; p < .001) than controls (ICARS: M 9.17, SD 3.88, range 2.0-20.0; SARA: M 3.51, SD 1.54, range 1.0-8.0). VP adults also showed significantly higher total ICARS (M 1.0, SD 1.99, range 0.0-11.0; p < .001) and SARA scores (M 0.54, SD 1.08, range 0.0-6.0; p < .001) than controls (ICARS: M 0.11, SD 0.44, range 0.0-2.0; SARA: M 0.04, SD 0.18, range 0.0-1.0). In conclusion, VP children showed significantly higher scores in ARS than controls. These differences were also present in VP adults, suggesting that deficits likely prevail until adulthood. ARS are a time and cost-effective method to screen for difficulties in coordination and balance in a patient group at risk.
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Affiliation(s)
- Bilge Albayrak
- Department of Pediatrics I, Neonatology, Pediatric Intensive Care and Pediatric Neurology, University Hospital Essen, University of Duisburg-Essen, Essen, Germany.
- Center for Translational Neuro- and Behavioral Sciences, University Hospital Essen, University of Duisburg-Essen, Hufelandstraße 55, 45147, Essen, Germany.
| | - Anne-Kathrin Dathe
- Department of Pediatrics I, Neonatology, Pediatric Intensive Care and Pediatric Neurology, University Hospital Essen, University of Duisburg-Essen, Essen, Germany
- Center for Translational Neuro- and Behavioral Sciences, University Hospital Essen, University of Duisburg-Essen, Hufelandstraße 55, 45147, Essen, Germany
| | - Katharina Maria Heuser-Spura
- Department of Pediatrics I, Neonatology, Pediatric Intensive Care and Pediatric Neurology, University Hospital Essen, University of Duisburg-Essen, Essen, Germany
- Center for Translational Neuro- and Behavioral Sciences, University Hospital Essen, University of Duisburg-Essen, Hufelandstraße 55, 45147, Essen, Germany
| | - Ursula Felderhoff-Mueser
- Department of Pediatrics I, Neonatology, Pediatric Intensive Care and Pediatric Neurology, University Hospital Essen, University of Duisburg-Essen, Essen, Germany
- Center for Translational Neuro- and Behavioral Sciences, University Hospital Essen, University of Duisburg-Essen, Hufelandstraße 55, 45147, Essen, Germany
| | - Dagmar Timmann
- Center for Translational Neuro- and Behavioral Sciences, University Hospital Essen, University of Duisburg-Essen, Hufelandstraße 55, 45147, Essen, Germany
- Department of Neurology, University Hospital Essen, University of Duisburg-Essen, Essen, Germany
| | - Britta Maria Huening
- Department of Pediatrics I, Neonatology, Pediatric Intensive Care and Pediatric Neurology, University Hospital Essen, University of Duisburg-Essen, Essen, Germany
- Center for Translational Neuro- and Behavioral Sciences, University Hospital Essen, University of Duisburg-Essen, Hufelandstraße 55, 45147, Essen, Germany
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Rowland GE, Roeckner A, Ely TD, Lebois LAM, van Rooij SJH, Bruce SE, Jovanovic T, House SL, Beaudoin FL, An X, Neylan TC, Clifford GD, Linnstaedt SD, Germine LT, Rauch SL, Haran JP, Storrow AB, Lewandowski C, Musey PI, Hendry PL, Sheikh S, Jones CW, Punches BE, Kurz MC, Gentile NT, Hudak LA, Pascual JL, Seamon MJ, Harris E, Pearson C, Merchant RC, Domeier RM, Rathlev NK, Sergot P, Sanchez LD, Miller MW, Pietrzak RH, Joormann J, Pizzagalli DA, Sheridan JF, Smoller JW, Harte SE, Elliott JM, Kessler RC, Koenen KC, McLean SA, Ressler KJ, Stevens JS, Harnett NG. Prior Sexual Trauma Exposure Impacts Posttraumatic Dysfunction and Neural Circuitry Following a Recent Traumatic Event in the AURORA Study. BIOLOGICAL PSYCHIATRY GLOBAL OPEN SCIENCE 2023; 3:705-715. [PMID: 37881578 PMCID: PMC10593890 DOI: 10.1016/j.bpsgos.2023.02.004] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/06/2023] [Revised: 02/02/2023] [Accepted: 02/06/2023] [Indexed: 02/17/2023] Open
Abstract
Background Prior sexual trauma (ST) is associated with greater risk for posttraumatic stress disorder after a subsequent traumatic event; however, the underlying neurobiological mechanisms remain opaque. We investigated longitudinal posttraumatic dysfunction and amygdala functional dynamics following admission to an emergency department for new primarily nonsexual trauma in participants with and without previous ST. Methods Participants (N = 2178) were recruited following acute trauma exposure (primarily motor vehicle collision). A subset (n = 242) completed magnetic resonance imaging that included a fearful faces task and a resting-state scan 2 weeks after the trauma. We investigated associations between prior ST and several dimensions of posttraumatic symptoms over 6 months. We further assessed amygdala activation and connectivity differences between groups with or without prior ST. Results Prior ST was associated with greater posttraumatic depression (F1,1120 = 28.35, p = 1.22 × 10-7, ηp2 = 0.06), anxiety (F1,1113 = 17.43, p = 3.21 × 10-5, ηp2 = 0.05), and posttraumatic stress disorder (F1,1027 = 11.34, p = 7.85 × 10-4, ηp2 = 0.04) severity and more maladaptive beliefs about pain (F1,1113 = 8.51, p = .004, ηp2 = 0.02) but was not related to amygdala reactivity to fearful versus neutral faces (all ps > .05). A secondary analysis revealed an interaction between ST and lifetime trauma load on the left amygdala to visual cortex connectivity (peak Z value: -4.41, corrected p < .02). Conclusions Findings suggest that prior ST is associated with heightened posttraumatic dysfunction following a new trauma exposure but not increased amygdala activity. In addition, ST may interact with lifetime trauma load to alter neural circuitry in visual processing regions following acute trauma exposure. Further research should probe the relationship between trauma type and visual circuitry in the acute aftermath of trauma.
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Affiliation(s)
- Grace E Rowland
- Division of Depression and Anxiety, McLean Hospital, Belmont, Massachusetts
| | - Alyssa Roeckner
- Department of Psychiatry and Behavioral Sciences, Emory University School of Medicine, Atlanta, Georgia
| | - Timothy D Ely
- Department of Psychiatry and Behavioral Sciences, Emory University School of Medicine, Atlanta, Georgia
| | - Lauren A M Lebois
- Division of Depression and Anxiety, McLean Hospital, Belmont, Massachusetts
- Department of Psychiatry, Harvard Medical School, Boston, Massachusetts
| | - Sanne J H van Rooij
- Department of Psychiatry and Behavioral Sciences, Emory University School of Medicine, Atlanta, Georgia
| | - Steven E Bruce
- Department of Psychological Sciences, University of Missouri - St. Louis, St. Louis, Missouri
| | - Tanja Jovanovic
- Department of Psychiatry and Behavioral Neurosciences, Wayne State University, Detroit, Michigan
| | - Stacey L House
- Department of Emergency Medicine, Washington University School of Medicine, St. Louis, Missouri
| | - Francesca L Beaudoin
- Department of Epidemiology, Brown University, Providence, Rhode Island
- Department of Emergency Medicine, Brown University, Providence, Rhode Island
| | - Xinming An
- Institute for Trauma Recovery, Department of Anesthesiology, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina
| | - Thomas C Neylan
- Department of Psychiatry, University of California, San Francisco, San Francisco, California
- Department of Neurology, University of California, San Francisco, San Francisco, California
| | - Gari D Clifford
- Department of Biomedical Informatics, Emory University School of Medicine, Atlanta, Georgia
- Department of Biomedical Engineering, Georgia Institute of Technology and Emory University, Atlanta, Georgia
| | - Sarah D Linnstaedt
- Institute for Trauma Recovery, Department of Anesthesiology, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina
| | - Laura T Germine
- Department of Psychiatry, Harvard Medical School, Boston, Massachusetts
- Institute for Technology in Psychiatry, McLean Hospital, Belmont, Massachusetts
- TheMany Brains Project, Belmont, Massachusetts
| | - Scott L Rauch
- Department of Psychiatry, Harvard Medical School, Boston, Massachusetts
- Institute for Technology in Psychiatry, McLean Hospital, Belmont, Massachusetts
- Department of Psychiatry, McLean Hospital, Belmont, Massachusetts
| | - John P Haran
- Department of Emergency Medicine, University of Massachusetts Chan Medical School, Worcester, Massachusetts
| | - Alan B Storrow
- Department of Emergency Medicine, Vanderbilt University Medical Center, Nashville, Tennessee
| | | | - Paul I Musey
- Department of Emergency Medicine, Indiana University School of Medicine, Indianapolis, Indiana
| | - Phyllis L Hendry
- Department of Emergency Medicine, University of Florida College of Medicine-Jacksonville, Jacksonville, Florida
| | - Sophia Sheikh
- Department of Emergency Medicine, University of Florida College of Medicine-Jacksonville, Jacksonville, Florida
| | - Christopher W Jones
- Department of Emergency Medicine, Cooper Medical School of Rowan University, Camden, New Jersey
| | - Brittany E Punches
- Department of Emergency Medicine, Ohio State University College of Medicine, Columbus, Ohio
- Ohio State University College of Nursing, Columbus, Ohio
| | - Michael C Kurz
- Department of Emergency Medicine, University of Alabama School of Medicine, Birmingham, Alabama
- Division of Acute Care Surgery, Department of Surgery, University of Alabama School of Medicine, Birmingham, Alabama
- Center for Injury Science, University of Alabama at Birmingham, Birmingham, Alabama
| | - Nina T Gentile
- Department of Emergency Medicine, Lewis Katz School of Medicine, Temple University, Philadelphia, Pennsylvania
| | - Lauren A Hudak
- Department of Emergency Medicine, Emory University School of Medicine, Atlanta, Georgia
| | - Jose L Pascual
- Department of Surgery, University of Pennsylvania, Philadelphia, Pennsylvania
- Department of Neurosurgery, University of Pennsylvania, Philadelphia, Pennsylvania
- Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania
| | - Mark J Seamon
- Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania
- Division of Traumatology, Department of Surgery, Surgical Critical Care and Emergency Surgery, University of Pennsylvania, Philadelphia, Pennsylvania
| | - Erica Harris
- Einstein Medical Center, Philadelphia, Pennsylvania
| | - Claire Pearson
- Department of Emergency Medicine, Wayne State University, Ascension St. John Hospital, Detroit, Michigan
| | - Roland C Merchant
- Department of Emergency Medicine, Brigham and Women's Hospital, Boston, Massachusetts
| | - Robert M Domeier
- Department of Emergency Medicine, Saint Joseph Mercy Hospital, Ypsilanti, Michigan
| | - Niels K Rathlev
- Department of Emergency Medicine, University of Massachusetts Medical School-Baystate, Springfield, Massachusetts
| | - Paulina Sergot
- Department of Emergency Medicine, McGovern Medical School at UTHealth, Houston, Texas
| | - Leon D Sanchez
- Department of Emergency Medicine, Brigham and Women's Hospital, Boston, Massachusetts
- Department of Emergency Medicine, Harvard Medical School, Boston, Massachusetts
| | - Mark W Miller
- National Center for PTSD, Behavioral Science Division, VA Boston Healthcare System, Boston, Massachusetts
- Department of Psychiatry, Boston University School of Medicine, Boston, Massachusetts
| | - Robert H Pietrzak
- National Center for PTSD, Clinical Neurosciences Division, VA Connecticut Healthcare System, West Haven, Connecticut
- Department of Psychiatry, Yale School of Medicine, New Haven, Connecticut
| | - Jutta Joormann
- Department of Psychology, Yale University, New Haven, Connecticut
| | - Diego A Pizzagalli
- Department of Psychiatry, Harvard Medical School, Boston, Massachusetts
- Division of Depression and Anxiety, McLean Hospital, Belmont, Massachusetts
| | - John F Sheridan
- Division of Biosciences, Ohio State University College of Dentistry, Columbus, Ohio
- Institute for Behavioral Medicine Research, OSU Wexner Medical Center, Columbus, Ohio
| | - Jordan W Smoller
- Department of Psychiatry, Psychiatric and Neurodevelopmental Genetics Unit, Massachusetts General Hospital, Boston, Massachusetts
- Stanley Center for Psychiatric Research, Broad Institute, Cambridge, Massachusetts
| | - Steven E Harte
- Department of Anesthesiology, University of Michigan Medical School, Ann Arbor, Michigan
- Department of Internal Medicine-Rheumatology, University of Michigan Medical School, Ann Arbor, Michigan
| | - James M Elliott
- Kolling Institute, University of Sydney, St. Leonards, New South Wales, Sydney, Australia
- Faculty of Medicine and Health, University of Sydney, Northern Sydney Local Health District, New South Wales, Sydney, Australia
- Physical Therapy & Human Movement Sciences, Feinberg School of Medicine, Northwestern University, Chicago, Illinois
| | - Ronald C Kessler
- Department of Health Care Policy, Harvard Medical School, Boston, Massachusetts
| | - Karestan C Koenen
- Department of Epidemiology, Harvard TH Chan School of Public Health, Harvard University, Boston, Massachusetts
| | - Samuel A McLean
- Department of Emergency Medicine, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina
- Department of Psychiatry, Institute for Trauma Recovery, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina
| | - Kerry J Ressler
- Department of Psychiatry, Harvard Medical School, Boston, Massachusetts
- Division of Depression and Anxiety, McLean Hospital, Belmont, Massachusetts
| | - Jennifer S Stevens
- Department of Psychiatry and Behavioral Sciences, Emory University School of Medicine, Atlanta, Georgia
| | - Nathaniel G Harnett
- Division of Depression and Anxiety, McLean Hospital, Belmont, Massachusetts
- Department of Psychiatry, Harvard Medical School, Boston, Massachusetts
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122
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Giannini LAA, Seelaar H, van der Ende EL, Poos JM, Jiskoot LC, Dopper EGP, Pijnenburg YAL, Willemse EAJ, Vermunt L, Teunissen CE, van Swieten JC, Meeter LH. Clinical Value of Longitudinal Serum Neurofilament Light Chain in Prodromal Genetic Frontotemporal Dementia. Neurology 2023; 101:e1069-e1082. [PMID: 37491327 PMCID: PMC10491440 DOI: 10.1212/wnl.0000000000207581] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/19/2023] [Accepted: 05/10/2023] [Indexed: 07/27/2023] Open
Abstract
BACKGROUND AND OBJECTIVES Elevated serum neurofilament light chain (NfL) is used to identify carriers of genetic frontotemporal dementia (FTD) pathogenic variants approaching prodromal conversion. Yet, the magnitude and timeline of NfL increase are still unclear. Here, we investigated the predictive and early diagnostic value of longitudinal serum NfL for the prodromal conversion in genetic FTD. METHODS In a longitudinal observational cohort study of genetic FTD pathogenic variant carriers, we examined the diagnostic accuracy and conversion risk associated with cross-sectional and longitudinal NfL. Time periods relative to prodromal conversion (>3, 3-1.5, 1.5-0 years before; 0-1.5 years after) were compared with values of participants who did not convert. Next, we modeled longitudinal NfL and MRI volume trajectories to determine their timeline. RESULTS We included 21 participants who converted (5 chromosome 9 open-reading frame 72 [C9orf72], 10 progranulin [GRN], 5 microtubule-associated protein tau [MAPT], and 1 TAR DNA-binding protein [TARDBP]) and 61 who did not (20 C9orf72, 30 GRN, and 11 MAPT). Participants who converted had higher NfL levels at all examined periods before prodromal conversion (median values 14.0-18.2 pg/mL; betas = 0.4-0.7, standard error [SE] = 0.1, p < 0.046) than those who did not (6.5 pg/mL) and showed further increase 0-1.5 years after conversion (28.4 pg/mL; beta = 1.0, SE = 0.1, p < 0.001). Annualized longitudinal NfL change was only significantly higher in participants who converted (vs. participants who did not) 0-1.5 years after conversion (beta = 1.2, SE = 0.3, p = 0.001). Diagnostic accuracy of cross-sectional NfL for prodromal conversion (vs. nonconversion) was good-to-excellent at time periods before conversion (area under the curve range: 0.72-0.92), improved 0-1.5 years after conversion (0.94-0.97), and outperformed annualized longitudinal change (0.76-0.84). NfL increase in participants who converted occurred earlier than frontotemporal MRI volume change and differed by genetic group and clinical phenotypes. Higher NfL corresponded to increased conversion risk (hazard ratio: cross-sectional = 6.7 [95% CI 3.3-13.7]; longitudinal = 13.0 [95% CI 4.0-42.8]; p < 0.001), but conversion-free follow-up time varied greatly across participants. DISCUSSION NfL increase discriminates individuals who convert to prodromal FTD from those who do not, preceding significant frontotemporal MRI volume loss. However, NfL alone is limited in predicting the exact timing of prodromal conversion. NfL levels also vary depending on underlying variant-carrying genes and clinical phenotypes. These findings help to guide participant recruitment for clinical trials targeting prodromal genetic FTD.
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Affiliation(s)
- Lucia A A Giannini
- From the Department of Neurology (L.A.A.G., H.S., J.M.P., L.C.J., E.G.P.D., J.C.S., L.H.M.), Alzheimer Center Erasmus MC, Erasmus University Medical Center, Rotterdam; Amsterdam Neuroscience (E.L.E., Y.A.L.P., E.A.J.W., L.V., C.E.T.), Neurodegeneration; Neurochemistry Laboratory (E.L.E., E.A.J.W., L.V., C.E.T.), Department of Clinical Chemistry, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit; and Alzheimer Center Amsterdam (Y.A.L.P.), Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC Location VUmc, The Netherlands
| | - Harro Seelaar
- From the Department of Neurology (L.A.A.G., H.S., J.M.P., L.C.J., E.G.P.D., J.C.S., L.H.M.), Alzheimer Center Erasmus MC, Erasmus University Medical Center, Rotterdam; Amsterdam Neuroscience (E.L.E., Y.A.L.P., E.A.J.W., L.V., C.E.T.), Neurodegeneration; Neurochemistry Laboratory (E.L.E., E.A.J.W., L.V., C.E.T.), Department of Clinical Chemistry, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit; and Alzheimer Center Amsterdam (Y.A.L.P.), Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC Location VUmc, The Netherlands
| | - Emma L van der Ende
- From the Department of Neurology (L.A.A.G., H.S., J.M.P., L.C.J., E.G.P.D., J.C.S., L.H.M.), Alzheimer Center Erasmus MC, Erasmus University Medical Center, Rotterdam; Amsterdam Neuroscience (E.L.E., Y.A.L.P., E.A.J.W., L.V., C.E.T.), Neurodegeneration; Neurochemistry Laboratory (E.L.E., E.A.J.W., L.V., C.E.T.), Department of Clinical Chemistry, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit; and Alzheimer Center Amsterdam (Y.A.L.P.), Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC Location VUmc, The Netherlands
| | - Jackie M Poos
- From the Department of Neurology (L.A.A.G., H.S., J.M.P., L.C.J., E.G.P.D., J.C.S., L.H.M.), Alzheimer Center Erasmus MC, Erasmus University Medical Center, Rotterdam; Amsterdam Neuroscience (E.L.E., Y.A.L.P., E.A.J.W., L.V., C.E.T.), Neurodegeneration; Neurochemistry Laboratory (E.L.E., E.A.J.W., L.V., C.E.T.), Department of Clinical Chemistry, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit; and Alzheimer Center Amsterdam (Y.A.L.P.), Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC Location VUmc, The Netherlands
| | - Lize C Jiskoot
- From the Department of Neurology (L.A.A.G., H.S., J.M.P., L.C.J., E.G.P.D., J.C.S., L.H.M.), Alzheimer Center Erasmus MC, Erasmus University Medical Center, Rotterdam; Amsterdam Neuroscience (E.L.E., Y.A.L.P., E.A.J.W., L.V., C.E.T.), Neurodegeneration; Neurochemistry Laboratory (E.L.E., E.A.J.W., L.V., C.E.T.), Department of Clinical Chemistry, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit; and Alzheimer Center Amsterdam (Y.A.L.P.), Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC Location VUmc, The Netherlands
| | - Elise G P Dopper
- From the Department of Neurology (L.A.A.G., H.S., J.M.P., L.C.J., E.G.P.D., J.C.S., L.H.M.), Alzheimer Center Erasmus MC, Erasmus University Medical Center, Rotterdam; Amsterdam Neuroscience (E.L.E., Y.A.L.P., E.A.J.W., L.V., C.E.T.), Neurodegeneration; Neurochemistry Laboratory (E.L.E., E.A.J.W., L.V., C.E.T.), Department of Clinical Chemistry, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit; and Alzheimer Center Amsterdam (Y.A.L.P.), Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC Location VUmc, The Netherlands
| | - Yolande A L Pijnenburg
- From the Department of Neurology (L.A.A.G., H.S., J.M.P., L.C.J., E.G.P.D., J.C.S., L.H.M.), Alzheimer Center Erasmus MC, Erasmus University Medical Center, Rotterdam; Amsterdam Neuroscience (E.L.E., Y.A.L.P., E.A.J.W., L.V., C.E.T.), Neurodegeneration; Neurochemistry Laboratory (E.L.E., E.A.J.W., L.V., C.E.T.), Department of Clinical Chemistry, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit; and Alzheimer Center Amsterdam (Y.A.L.P.), Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC Location VUmc, The Netherlands
| | - Eline A J Willemse
- From the Department of Neurology (L.A.A.G., H.S., J.M.P., L.C.J., E.G.P.D., J.C.S., L.H.M.), Alzheimer Center Erasmus MC, Erasmus University Medical Center, Rotterdam; Amsterdam Neuroscience (E.L.E., Y.A.L.P., E.A.J.W., L.V., C.E.T.), Neurodegeneration; Neurochemistry Laboratory (E.L.E., E.A.J.W., L.V., C.E.T.), Department of Clinical Chemistry, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit; and Alzheimer Center Amsterdam (Y.A.L.P.), Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC Location VUmc, The Netherlands
| | - Lisa Vermunt
- From the Department of Neurology (L.A.A.G., H.S., J.M.P., L.C.J., E.G.P.D., J.C.S., L.H.M.), Alzheimer Center Erasmus MC, Erasmus University Medical Center, Rotterdam; Amsterdam Neuroscience (E.L.E., Y.A.L.P., E.A.J.W., L.V., C.E.T.), Neurodegeneration; Neurochemistry Laboratory (E.L.E., E.A.J.W., L.V., C.E.T.), Department of Clinical Chemistry, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit; and Alzheimer Center Amsterdam (Y.A.L.P.), Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC Location VUmc, The Netherlands
| | - Charlotte E Teunissen
- From the Department of Neurology (L.A.A.G., H.S., J.M.P., L.C.J., E.G.P.D., J.C.S., L.H.M.), Alzheimer Center Erasmus MC, Erasmus University Medical Center, Rotterdam; Amsterdam Neuroscience (E.L.E., Y.A.L.P., E.A.J.W., L.V., C.E.T.), Neurodegeneration; Neurochemistry Laboratory (E.L.E., E.A.J.W., L.V., C.E.T.), Department of Clinical Chemistry, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit; and Alzheimer Center Amsterdam (Y.A.L.P.), Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC Location VUmc, The Netherlands
| | - John C van Swieten
- From the Department of Neurology (L.A.A.G., H.S., J.M.P., L.C.J., E.G.P.D., J.C.S., L.H.M.), Alzheimer Center Erasmus MC, Erasmus University Medical Center, Rotterdam; Amsterdam Neuroscience (E.L.E., Y.A.L.P., E.A.J.W., L.V., C.E.T.), Neurodegeneration; Neurochemistry Laboratory (E.L.E., E.A.J.W., L.V., C.E.T.), Department of Clinical Chemistry, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit; and Alzheimer Center Amsterdam (Y.A.L.P.), Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC Location VUmc, The Netherlands
| | - Lieke H Meeter
- From the Department of Neurology (L.A.A.G., H.S., J.M.P., L.C.J., E.G.P.D., J.C.S., L.H.M.), Alzheimer Center Erasmus MC, Erasmus University Medical Center, Rotterdam; Amsterdam Neuroscience (E.L.E., Y.A.L.P., E.A.J.W., L.V., C.E.T.), Neurodegeneration; Neurochemistry Laboratory (E.L.E., E.A.J.W., L.V., C.E.T.), Department of Clinical Chemistry, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit; and Alzheimer Center Amsterdam (Y.A.L.P.), Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC Location VUmc, The Netherlands.
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Okkels N, Horsager J, Labrador-Espinosa M, Kjeldsen PL, Damholdt MF, Mortensen J, Vestergård K, Knudsen K, Andersen KB, Fedorova TD, Skjærbæk C, Gottrup H, Hansen AK, Grothe MJ, Borghammer P. Severe cholinergic terminal loss in newly diagnosed dementia with Lewy bodies. Brain 2023; 146:3690-3704. [PMID: 37279796 DOI: 10.1093/brain/awad192] [Citation(s) in RCA: 13] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/23/2023] [Revised: 05/03/2023] [Accepted: 05/23/2023] [Indexed: 06/08/2023] Open
Abstract
Cholinergic changes play a fundamental role in the natural history of dementia with Lewy bodies and Lewy body disease in general. Despite important achievements in the field of cholinergic research, significant challenges remain. We conducted a study with four main objectives: (i) to examine the integrity of cholinergic terminals in newly diagnosed dementia with Lewy bodies; (ii) to disentangle the cholinergic contribution to dementia by comparing cholinergic changes in Lewy body patients with and without dementia; (iii) to investigate the in vivo relationship between cholinergic terminal loss and atrophy of cholinergic cell clusters in the basal forebrain at different stages of Lewy body disease; and (iv) to test whether any asymmetrical degeneration in cholinergic terminals would correlate with motor dysfunction and hypometabolism. To achieve these objectives, we conducted a comparative cross-sectional study of 25 newly diagnosed dementia with Lewy bodies patients (age 74 ± 5 years, 84% male), 15 healthy control subjects (age 75 ± 6 years, 67% male) and 15 Parkinson's disease patients without dementia (age 70 ± 7 years, 60% male). All participants underwent 18F-fluoroetoxybenzovesamicol PET and high-resolution structural MRI. In addition, we collected clinical 18F-fluorodeoxyglucose PET images. Brain images were normalized to standard space and regional tracer uptake and volumetric indices of basal forebrain degeneration were extracted. Patients with dementia showed spatially distinct reductions in cholinergic terminals across the cerebral cortex, limbic system, thalamus and brainstem. Also, cholinergic terminal binding in cortical and limbic regions correlated quantitatively and spatially with atrophy of the basal forebrain. In contrast, patients without dementia showed decreased cholinergic terminal binding in the cerebral cortex despite preserved basal forebrain volumes. In patients with dementia, cholinergic terminal reductions were most severe in limbic regions and least severe in occipital regions compared to those without dementia. Interhemispheric asymmetry of cholinergic terminals correlated with asymmetry of brain metabolism and lateralized motor function. In conclusion, this study provides robust evidence for severe cholinergic terminal loss in newly diagnosed dementia with Lewy bodies, which correlates with structural imaging measures of cholinergic basal forebrain degeneration. In patients without dementia, our findings suggest that loss of cholinergic terminal function occurs 'before' neuronal cell degeneration. Moreover, the study supports that degeneration of the cholinergic system is important for brain metabolism and may be linked with degeneration in other transmitter systems. Our findings have implications for understanding how cholinergic system pathology contributes to the clinical features of Lewy body disease, changes in brain metabolism and disease progression patterns.
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Affiliation(s)
- Niels Okkels
- Department of Nuclear Medicine and PET, Aarhus University Hospital, 8200 Aarhus N, Denmark
- Department of Clinical Medicine, Aarhus University, 8000 Aarhus C, Denmark
- Department of Neurology, Aarhus University Hospital, 8200 Aarhus N, Denmark
| | - Jacob Horsager
- Department of Nuclear Medicine and PET, Aarhus University Hospital, 8200 Aarhus N, Denmark
- Department of Clinical Medicine, Aarhus University, 8000 Aarhus C, Denmark
| | - Miguel Labrador-Espinosa
- Unidad de Trastornos del Movimiento, Servicio de Neurología y Neurofisiología Clínica, Instituto de Biomedicina de Sevilla (IBiS), Hospital Universitario Virgen del Rocío/CSIC/Universidad de Sevilla, 41013 Seville, Spain
- Centro de Investigación Biomédica en Red Sobre Enfermedades Neurodegenerativas (CIBERNED), Instituto de Salud Carlos III, 28029 Madrid, Spain
| | - Pernille L Kjeldsen
- Department of Nuclear Medicine and PET, Aarhus University Hospital, 8200 Aarhus N, Denmark
- Department of Clinical Medicine, Aarhus University, 8000 Aarhus C, Denmark
- Department of Neurology, Aalborg University Hospital, 9000 Aalborg, Denmark
| | - Malene F Damholdt
- Department of Clinical Medicine, Aarhus University, 8000 Aarhus C, Denmark
| | - Janne Mortensen
- Department of Neurology, Aarhus University Hospital, 8200 Aarhus N, Denmark
| | - Karsten Vestergård
- Department of Neurology, Aalborg University Hospital, 9000 Aalborg, Denmark
| | - Karoline Knudsen
- Department of Nuclear Medicine and PET, Aarhus University Hospital, 8200 Aarhus N, Denmark
- Department of Clinical Medicine, Aarhus University, 8000 Aarhus C, Denmark
| | - Katrine B Andersen
- Department of Nuclear Medicine and PET, Aarhus University Hospital, 8200 Aarhus N, Denmark
- Department of Clinical Medicine, Aarhus University, 8000 Aarhus C, Denmark
| | - Tatyana D Fedorova
- Department of Nuclear Medicine and PET, Aarhus University Hospital, 8200 Aarhus N, Denmark
- Department of Clinical Medicine, Aarhus University, 8000 Aarhus C, Denmark
| | - Casper Skjærbæk
- Department of Nuclear Medicine and PET, Aarhus University Hospital, 8200 Aarhus N, Denmark
- Department of Clinical Medicine, Aarhus University, 8000 Aarhus C, Denmark
| | - Hanne Gottrup
- Department of Neurology, Aarhus University Hospital, 8200 Aarhus N, Denmark
| | - Allan K Hansen
- Department of Nuclear Medicine and PET, Aarhus University Hospital, 8200 Aarhus N, Denmark
- Department of Nuclear Medicine, Aalborg University Hospital, 9000 Aalborg, Denmark
| | - Michel J Grothe
- Unidad de Trastornos del Movimiento, Servicio de Neurología y Neurofisiología Clínica, Instituto de Biomedicina de Sevilla (IBiS), Hospital Universitario Virgen del Rocío/CSIC/Universidad de Sevilla, 41013 Seville, Spain
- Centro de Investigación Biomédica en Red Sobre Enfermedades Neurodegenerativas (CIBERNED), Instituto de Salud Carlos III, 28029 Madrid, Spain
| | - Per Borghammer
- Department of Nuclear Medicine and PET, Aarhus University Hospital, 8200 Aarhus N, Denmark
- Department of Clinical Medicine, Aarhus University, 8000 Aarhus C, Denmark
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Bierbrier J, Eskandari M, Giovanni DAD, Collins DL. Toward Estimating MRI-Ultrasound Registration Error in Image-Guided Neurosurgery. IEEE TRANSACTIONS ON ULTRASONICS, FERROELECTRICS, AND FREQUENCY CONTROL 2023; 70:999-1015. [PMID: 37022005 DOI: 10.1109/tuffc.2023.3239320] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/19/2023]
Abstract
Image-guided neurosurgery allows surgeons to view their tools in relation to preoperatively acquired patient images and models. To continue using neuronavigation systems throughout operations, image registration between preoperative images [typically magnetic resonance imaging (MRI)] and intraoperative images (e.g., ultrasound) is common to account for brain shift (deformations of the brain during surgery). We implemented a method to estimate MRI-ultrasound registration errors, with the goal of enabling surgeons to quantitatively assess the performance of linear or nonlinear registrations. To the best of our knowledge, this is the first dense error estimating algorithm applied to multimodal image registrations. The algorithm is based on a previously proposed sliding-window convolutional neural network that operates on a voxelwise basis. To create training data where the true registration error is known, simulated ultrasound images were created from preoperative MRI images and artificially deformed. The model was evaluated on artificially deformed simulated ultrasound data and real ultrasound data with manually annotated landmark points. The model achieved a mean absolute error (MAE) of 0.977 ± 0.988 mm and a correlation of 0.8 ± 0.062 on the simulated ultrasound data, and an MAE of 2.24 ± 1.89 mm and a correlation of 0.246 on the real ultrasound data. We discuss concrete areas to improve the results on real ultrasound data. Our progress lays the foundation for future developments and ultimately implementation of clinical neuronavigation systems.
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125
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Coomans EM, Tomassen J, Ossenkoppele R, Tijms BM, Lorenzini L, ten Kate M, Collij LE, Heeman F, Rikken RM, van der Landen SM, den Hollander ME, Golla SSV, Yaqub M, Windhorst AD, Barkhof F, Scheltens P, de Geus EJC, Visser PJ, van Berckel BNM, den Braber A. Genetically identical twin-pair difference models support the amyloid cascade hypothesis. Brain 2023; 146:3735-3746. [PMID: 36892415 PMCID: PMC10473566 DOI: 10.1093/brain/awad077] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/14/2022] [Revised: 02/03/2023] [Accepted: 02/23/2023] [Indexed: 03/10/2023] Open
Abstract
The amyloid cascade hypothesis has strongly impacted the Alzheimer's disease research agenda and clinical trial designs over the past decades, but precisely how amyloid-β pathology initiates the aggregation of neocortical tau remains unclear. We cannot exclude the possibility of a shared upstream process driving both amyloid-β and tau in an independent manner instead of there being a causal relationship between amyloid-β and tau. Here, we tested the premise that if a causal relationship exists, then exposure should be associated with outcome both at the individual level as well as within identical twin-pairs, who are strongly matched on genetic, demographic and shared environmental background. Specifically, we tested associations between longitudinal amyloid-β PET and cross-sectional tau PET, neurodegeneration and cognitive decline using genetically identical twin-pair difference models, which provide the unique opportunity of ruling out genetic and shared environmental effects as potential confounders in an association. We included 78 cognitively unimpaired identical twins with [18F]flutemetamol (amyloid-β)-PET, [18F]flortaucipir (tau)-PET, MRI (hippocampal volume) and cognitive data (composite memory). Associations between each modality were tested at the individual level using generalized estimating equation models, and within identical twin-pairs using within-pair difference models. Mediation analyses were performed to test for directionality in the associations as suggested by the amyloid cascade hypothesis. At the individual level, we observed moderate-to-strong associations between amyloid-β, tau, neurodegeneration and cognition. The within-pair difference models replicated results observed at the individual level with comparably strong effect sizes. Within-pair differences in amyloid-β were strongly associated with within-pair differences in tau (β = 0.68, P < 0.001), and moderately associated with within-pair differences in hippocampal volume (β = -0.37, P = 0.03) and memory functioning (β = -0.57, P < 0.001). Within-pair differences in tau were moderately associated with within-pair differences in hippocampal volume (β = -0.53, P < 0.001) and strongly associated with within-pair differences in memory functioning (β = -0.68, P < 0.001). Mediation analyses showed that of the total twin-difference effect of amyloid-β on memory functioning, the proportion mediated through pathways including tau and hippocampal volume was 69.9%, which was largely attributable to the pathway leading from amyloid-β to tau to memory functioning (proportion mediated, 51.6%). Our results indicate that associations between amyloid-β, tau, neurodegeneration and cognition are unbiased by (genetic) confounding. Furthermore, effects of amyloid-β on neurodegeneration and cognitive decline were fully mediated by tau. These novel findings in this unique sample of identical twins are compatible with the amyloid cascade hypothesis and thereby provide important new knowledge for clinical trial designs.
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Affiliation(s)
- Emma M Coomans
- Department of Radiology and Nuclear Medicine, Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc, 1081 HV Amsterdam, The Netherlands
- Amsterdam Neuroscience, Brain Imaging, 1081 HV Amsterdam, The Netherlands
| | - Jori Tomassen
- Alzheimer Center Amsterdam, Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc, 1081 HV Amsterdam, The Netherlands
- Amsterdam Neuroscience, Neurodegeneration, 1081 HV Amsterdam, The Netherlands
| | - Rik Ossenkoppele
- Alzheimer Center Amsterdam, Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc, 1081 HV Amsterdam, The Netherlands
- Amsterdam Neuroscience, Neurodegeneration, 1081 HV Amsterdam, The Netherlands
- Clinical Memory Research Unit, Lund University, 205 02 Lund, Sweden
| | - Betty M Tijms
- Alzheimer Center Amsterdam, Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc, 1081 HV Amsterdam, The Netherlands
- Amsterdam Neuroscience, Neurodegeneration, 1081 HV Amsterdam, The Netherlands
| | - Luigi Lorenzini
- Department of Radiology and Nuclear Medicine, Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc, 1081 HV Amsterdam, The Netherlands
- Amsterdam Neuroscience, Brain Imaging, 1081 HV Amsterdam, The Netherlands
| | - Mara ten Kate
- Department of Radiology and Nuclear Medicine, Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc, 1081 HV Amsterdam, The Netherlands
- Amsterdam Neuroscience, Brain Imaging, 1081 HV Amsterdam, The Netherlands
| | - Lyduine E Collij
- Department of Radiology and Nuclear Medicine, Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc, 1081 HV Amsterdam, The Netherlands
- Amsterdam Neuroscience, Brain Imaging, 1081 HV Amsterdam, The Netherlands
| | - Fiona Heeman
- Department of Radiology and Nuclear Medicine, Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc, 1081 HV Amsterdam, The Netherlands
- Amsterdam Neuroscience, Brain Imaging, 1081 HV Amsterdam, The Netherlands
- Wallenberg Centre for Molecular and Translational Medicine, University of Gothenburg, 405 30 Gothenburg, Sweden
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, The Sahlgrenska Academy, University of Gothenburg, 405 30 Gothenburg, Sweden
| | - Roos M Rikken
- Department of Radiology and Nuclear Medicine, Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc, 1081 HV Amsterdam, The Netherlands
- Amsterdam Neuroscience, Brain Imaging, 1081 HV Amsterdam, The Netherlands
| | - Sophie M van der Landen
- Alzheimer Center Amsterdam, Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc, 1081 HV Amsterdam, The Netherlands
- Amsterdam Neuroscience, Neurodegeneration, 1081 HV Amsterdam, The Netherlands
| | - Marijke E den Hollander
- Department of Radiology and Nuclear Medicine, Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc, 1081 HV Amsterdam, The Netherlands
- Amsterdam Neuroscience, Brain Imaging, 1081 HV Amsterdam, The Netherlands
| | - Sandeep S V Golla
- Department of Radiology and Nuclear Medicine, Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc, 1081 HV Amsterdam, The Netherlands
- Amsterdam Neuroscience, Brain Imaging, 1081 HV Amsterdam, The Netherlands
| | - Maqsood Yaqub
- Department of Radiology and Nuclear Medicine, Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc, 1081 HV Amsterdam, The Netherlands
- Amsterdam Neuroscience, Brain Imaging, 1081 HV Amsterdam, The Netherlands
| | - Albert D Windhorst
- Department of Radiology and Nuclear Medicine, Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc, 1081 HV Amsterdam, The Netherlands
- Amsterdam Neuroscience, Brain Imaging, 1081 HV Amsterdam, The Netherlands
| | - Frederik Barkhof
- Department of Radiology and Nuclear Medicine, Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc, 1081 HV Amsterdam, The Netherlands
- Amsterdam Neuroscience, Brain Imaging, 1081 HV Amsterdam, The Netherlands
- Queen Square Institute of Neurology and Centre for Medical Image Computing, University College London, London WC1N 3BG, UK
| | - Philip Scheltens
- Alzheimer Center Amsterdam, Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc, 1081 HV Amsterdam, The Netherlands
- Amsterdam Neuroscience, Neurodegeneration, 1081 HV Amsterdam, The Netherlands
| | - Eco J C de Geus
- Department of Biological Psychology, Vrije Universiteit Amsterdam, 1081 HV Amsterdam, The Netherlands
| | - Pieter Jelle Visser
- Alzheimer Center Amsterdam, Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc, 1081 HV Amsterdam, The Netherlands
- Amsterdam Neuroscience, Neurodegeneration, 1081 HV Amsterdam, The Netherlands
- Alzheimer Center Limburg, School for Mental Health and Neuroscience, Maastricht University, 6200 MD Maastricht, The Netherlands
- Department of Neurobiology, Care Sciences and Society, Division of Neurogeriatrics, Karolinska Institutet, 171 77 Stockholm, Sweden
| | - Bart N M van Berckel
- Department of Radiology and Nuclear Medicine, Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc, 1081 HV Amsterdam, The Netherlands
- Amsterdam Neuroscience, Brain Imaging, 1081 HV Amsterdam, The Netherlands
| | - Anouk den Braber
- Alzheimer Center Amsterdam, Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc, 1081 HV Amsterdam, The Netherlands
- Amsterdam Neuroscience, Neurodegeneration, 1081 HV Amsterdam, The Netherlands
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, The Sahlgrenska Academy, University of Gothenburg, 405 30 Gothenburg, Sweden
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Perszyk EE, Davis XS, Djordjevic J, Jones-Gotman M, Trinh J, Hutelin Z, Veldhuizen MG, Koban L, Wager TD, Kober H, Small DM. Odour-imagery ability is linked to food craving, intake, and adiposity change in humans. Nat Metab 2023; 5:1483-1493. [PMID: 37640944 DOI: 10.1038/s42255-023-00874-z] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/06/2023] [Accepted: 07/25/2023] [Indexed: 08/31/2023]
Abstract
It is well-known that food-cue reactivity (FCR) is positively associated with body mass index (BMI)1 and weight change2, but the mechanisms underlying these relationships are incompletely understood. One prominent theory of craving posits that the elaboration of a desired substance through sensory imagery intensifies cravings, thereby promoting consumption3. Olfaction is integral to food perception, yet the ability to imagine odours varies widely4. Here we test in a basic observational study whether this large variation in olfactory imagery drives FCR strength to promote adiposity in 45 adults (23 male). We define odour-imagery ability as the extent to which imagining an odour interferes with the detection of a weak incongruent odour (the 'interference effect'5). As predicted in our preregistration, the interference effect correlates with the neural decoding of imagined, but not real, odours. These perceptual and neural measures of odour imagery are in turn associated with FCR, defined by the rated craving intensity of liked foods and cue-potentiated intake. Finally, odour imagery exerts positive indirect effects on changes in BMI and body-fat percentage over one year via its influences on FCR. These findings establish odour imagery as a driver of FCR that in turn confers risk for weight gain.
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Affiliation(s)
- Emily E Perszyk
- Modern Diet and Physiology Research Center, New Haven, CT, USA.
- Department of Psychiatry, Yale University School of Medicine, New Haven, CT, USA.
| | - Xue S Davis
- Modern Diet and Physiology Research Center, New Haven, CT, USA
- Department of Psychiatry, Yale University School of Medicine, New Haven, CT, USA
| | - Jelena Djordjevic
- Department of Neurology and Neurosurgery, Montreal Neurological Institute and Hospital, McGill University, Montreal, Quebec, Canada
| | - Marilyn Jones-Gotman
- Department of Neurology and Neurosurgery, Montreal Neurological Institute and Hospital, McGill University, Montreal, Quebec, Canada
| | - Jessica Trinh
- Modern Diet and Physiology Research Center, New Haven, CT, USA
- Department of Psychiatry, Yale University School of Medicine, New Haven, CT, USA
| | - Zach Hutelin
- Modern Diet and Physiology Research Center, New Haven, CT, USA
- Department of Psychiatry, Yale University School of Medicine, New Haven, CT, USA
| | - Maria G Veldhuizen
- Department of Anatomy, Faculty of Medicine, Mersin University, Ciftlikkoy Campus, Mersin, Turkey
| | - Leonie Koban
- Lyon Neuroscience Research Center (CRNL), CNRS, INSERM, University Claude Bernard Lyon 1, Bron, France
| | - Tor D Wager
- Department of Psychological and Brain Sciences, Dartmouth College, Hanover, NH, USA
| | - Hedy Kober
- Department of Psychiatry, Yale University School of Medicine, New Haven, CT, USA
- Department of Psychology, Yale University, New Haven, CT, USA
| | - Dana M Small
- Modern Diet and Physiology Research Center, New Haven, CT, USA.
- Department of Psychiatry, Yale University School of Medicine, New Haven, CT, USA.
- Department of Neurology and Neurosurgery, Montreal Neurological Institute and Hospital, McGill University, Montreal, Quebec, Canada.
- Department of Psychology, Yale University, New Haven, CT, USA.
- Department of Medicine, McGill University Health Center, Montreal, Quebec, Canada.
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127
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Jiang D, Liu L, Kong Y, Chen Z, Rosa‑Neto P, Chen K, Ren L, Chu M, Wu L. Regional Glymphatic Abnormality in Behavioral Variant Frontotemporal Dementia. Ann Neurol 2023; 94:442-456. [PMID: 37243334 PMCID: PMC10657235 DOI: 10.1002/ana.26710] [Citation(s) in RCA: 34] [Impact Index Per Article: 17.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/11/2023] [Revised: 04/24/2023] [Accepted: 05/22/2023] [Indexed: 05/28/2023]
Abstract
OBJECTIVES Glymphatic function has not yet been explored in behavioral variant frontotemporal dementia (bvFTD). The spatial correlation between regional glymphatic function and bvFTD remains unknown. METHOD A total of 74 patients with bvFTD and 67 age- and sex-matched healthy controls (HCs) were selected from discovery dataset and replication dataset. All participants underwent neuropsychological assessment. Glymphatic measures including choroid plexus (CP) volume, diffusion tensor imaging along the perivascular (DTI-ALPS) index, and coupling between blood-oxygen-level-dependent signals and cerebrospinal fluid signals (BOLD-CSF coupling), were compared between the two groups. Regional glymphatic function was evaluated by dividing DTI-ALPS and BOLD-CSF coupling into anterior, middle, and posterior regions. The bvFTD-related metabolic pattern was identified using spatial covariance analysis based on l8 F-FDG-PET. RESULTS Patients with bvFTD showed higher CP volume (p < 0.001); anterior and middle DTI-ALPS (p < 0.001); and weaker anterior BOLD-CSF coupling (p < 0.05) than HCs after controlling for cortical gray matter volume in both datasets. In bvFTD from the discovery dataset, the anterior DTI-ALPS was negatively associated with the expression of the bvFTD-related metabolic pattern (r = -0.52, p = 0.034) and positively related with regional standardized uptake value ratios of l8 F-FDG-PET in bvFTD-related brain regions (r range: 0.49 to 0.62, p range: 0.017 to 0.047). Anterior and middle glymphatic functions were related to global cognition and disease severity. INTERPRETATION Our findings reveal abnormal glymphatic function, especially in the anterior and middle regions of brain in bvFTD. Regional glymphatic dysfunction may contribute to the pathogenesis of bvFTD. ANN NEUROL 2023;94:442-456.
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Affiliation(s)
- Deming Jiang
- Department of Neurology, Xuanwu Hospital, Capital Medical University, Changchun Street 45, Beijing, China
| | - Li Liu
- Department of Neurology, Xuanwu Hospital, Capital Medical University, Changchun Street 45, Beijing, China
| | - Yu Kong
- Department of Neurology, Xuanwu Hospital, Capital Medical University, Changchun Street 45, Beijing, China
| | - Zhongyun Chen
- Department of Neurology, Xuanwu Hospital, Capital Medical University, Changchun Street 45, Beijing, China
| | - Pedro Rosa‑Neto
- Alzheimer’s Disease Research Unit, McGill Centre for Studies in Aging, Montreal H4H 1R3, Canada
| | - Kewei Chen
- Banner Alzheimer’s Institute, University of Arizona, School of Mathematics and Statistics, Arizona Alzheimer’s Consortium, Arizona State University, Tempe, USA
| | - Liankun Ren
- Department of Neurology, Xuanwu Hospital, Capital Medical University, Changchun Street 45, Beijing, China
| | - Min Chu
- Department of Neurology, Xuanwu Hospital, Capital Medical University, Changchun Street 45, Beijing, China
| | - Liyong Wu
- Department of Neurology, Xuanwu Hospital, Capital Medical University, Changchun Street 45, Beijing, China
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128
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Gandia-Ferrero MT, Torres-Espallardo I, Martínez-Sanchis B, Morera-Ballester C, Muñoz E, Sopena-Novales P, González-Pavón G, Martí-Bonmatí L. Objective Image Quality Comparison Between Brain-Dedicated PET and PET/CT Scanners. J Med Syst 2023; 47:88. [PMID: 37589893 DOI: 10.1007/s10916-023-01984-7] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/09/2023] [Accepted: 08/02/2023] [Indexed: 08/18/2023]
Abstract
As part of a clinical validation of a new brain-dedicated PET system (CMB), image quality of this scanner has been compared to that of a whole-body PET/CT scanner. To that goal, Hoffman phantom and patient data were obtined with both devices. Since CMB does not use a CT for attenuation correction (AC) which is crucial for PET images quality, this study includes the evaluation of CMB PET images using emission-based or CT-based attenuation maps. PET images were compared using 34 image quality metrics. Moreover, a neural network was used to evaluate the degree of agreement between both devices on the patients diagnosis prediction. Overall, results showed that CMB images have higher contrast and recovery coefficient but higher noise than PET/CT images. Although SUVr values presented statistically significant differences in many brain regions, relative differences were low. An asymmetry between left and right hemispheres, however, was identified. Even so, the variations between the two devices were minor. Finally, there is a greater similarity between PET/CT and CMB CT-based AC PET images than between PET/CT and the CMB emission-based AC PET images.
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Affiliation(s)
- Maria Teresa Gandia-Ferrero
- Biomedical Imaging Research Group (GIBI230), La Fe Health Research Institute (IIS La Fe), Avenida Fernando Abril Martorell, València, 46026, Spain.
| | - Irene Torres-Espallardo
- Biomedical Imaging Research Group (GIBI230), La Fe Health Research Institute (IIS La Fe), Avenida Fernando Abril Martorell, València, 46026, Spain
- Nuclear Medicine Department, La Fe University and Polytechnic Hospital, Avenida Fernando Abril Martorell, València, 46026, Spain
| | - Begoña Martínez-Sanchis
- Nuclear Medicine Department, La Fe University and Polytechnic Hospital, Avenida Fernando Abril Martorell, València, 46026, Spain
| | | | - Enrique Muñoz
- Oncovision, Carrer de Jeroni de Montsoriu, 92, València, 46022, Spain
| | - Pablo Sopena-Novales
- Nuclear Medicine Department, La Fe University and Polytechnic Hospital, Avenida Fernando Abril Martorell, València, 46026, Spain
| | | | - Luis Martí-Bonmatí
- Biomedical Imaging Research Group (GIBI230), La Fe Health Research Institute (IIS La Fe), Avenida Fernando Abril Martorell, València, 46026, Spain
- Radiology Department, La Fe University and Polytechnic Hospital, Avenida Fernando Abril Martorell, València, 46026, Spain
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129
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Kolabas ZI, Kuemmerle LB, Perneczky R, Förstera B, Ulukaya S, Ali M, Kapoor S, Bartos LM, Büttner M, Caliskan OS, Rong Z, Mai H, Höher L, Jeridi D, Molbay M, Khalin I, Deligiannis IK, Negwer M, Roberts K, Simats A, Carofiglio O, Todorov MI, Horvath I, Ozturk F, Hummel S, Biechele G, Zatcepin A, Unterrainer M, Gnörich J, Roodselaar J, Shrouder J, Khosravani P, Tast B, Richter L, Díaz-Marugán L, Kaltenecker D, Lux L, Chen Y, Zhao S, Rauchmann BS, Sterr M, Kunze I, Stanic K, Kan VWY, Besson-Girard S, Katzdobler S, Palleis C, Schädler J, Paetzold JC, Liebscher S, Hauser AE, Gokce O, Lickert H, Steinke H, Benakis C, Braun C, Martinez-Jimenez CP, Buerger K, Albert NL, Höglinger G, Levin J, Haass C, Kopczak A, Dichgans M, Havla J, Kümpfel T, Kerschensteiner M, Schifferer M, Simons M, Liesz A, Krahmer N, Bayraktar OA, Franzmeier N, Plesnila N, Erener S, Puelles VG, Delbridge C, Bhatia HS, Hellal F, Elsner M, Bechmann I, Ondruschka B, Brendel M, Theis FJ, Erturk A. Distinct molecular profiles of skull bone marrow in health and neurological disorders. Cell 2023; 186:3706-3725.e29. [PMID: 37562402 PMCID: PMC10443631 DOI: 10.1016/j.cell.2023.07.009] [Citation(s) in RCA: 61] [Impact Index Per Article: 30.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/06/2021] [Revised: 04/24/2023] [Accepted: 07/07/2023] [Indexed: 08/12/2023]
Abstract
The bone marrow in the skull is important for shaping immune responses in the brain and meninges, but its molecular makeup among bones and relevance in human diseases remain unclear. Here, we show that the mouse skull has the most distinct transcriptomic profile compared with other bones in states of health and injury, characterized by a late-stage neutrophil phenotype. In humans, proteome analysis reveals that the skull marrow is the most distinct, with differentially expressed neutrophil-related pathways and a unique synaptic protein signature. 3D imaging demonstrates the structural and cellular details of human skull-meninges connections (SMCs) compared with veins. Last, using translocator protein positron emission tomography (TSPO-PET) imaging, we show that the skull bone marrow reflects inflammatory brain responses with a disease-specific spatial distribution in patients with various neurological disorders. The unique molecular profile and anatomical and functional connections of the skull show its potential as a site for diagnosing, monitoring, and treating brain diseases.
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Affiliation(s)
- Zeynep Ilgin Kolabas
- Institute for Tissue Engineering and Regenerative Medicine (iTERM), Helmholtz Center, Neuherberg, Munich, Germany; Institute for Stroke and Dementia Research, LMU University Hospital, Ludwig-Maximilians University Munich, Munich, Germany; Graduate School of Systemic Neurosciences (GSN), Munich, Germany
| | - Louis B Kuemmerle
- Institute for Tissue Engineering and Regenerative Medicine (iTERM), Helmholtz Center, Neuherberg, Munich, Germany; Institute of Computational Biology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
| | - Robert Perneczky
- Division of Mental Health in Older Adults and Alzheimer Therapy and Research Center, Department of Psychiatry and Psychotherapy, University Hospital, Ludwig Maximilian University Munich, 80336 Munich, Germany; German Center for Neurodegenerative Diseases (DZNE) Munich, Munich, Germany; Ageing Epidemiology (AGE) Research Unit, School of Public Health, Imperial College London, London, UK; Munich Cluster for Systems Neurology (SyNergy), Munich, Germany; Sheffield Institute for Translational Neuroscience, University of Sheffield, Sheffield, UK
| | - Benjamin Förstera
- Institute for Tissue Engineering and Regenerative Medicine (iTERM), Helmholtz Center, Neuherberg, Munich, Germany; Institute for Stroke and Dementia Research, LMU University Hospital, Ludwig-Maximilians University Munich, Munich, Germany
| | - Selin Ulukaya
- Institute for Tissue Engineering and Regenerative Medicine (iTERM), Helmholtz Center, Neuherberg, Munich, Germany
| | - Mayar Ali
- Institute for Tissue Engineering and Regenerative Medicine (iTERM), Helmholtz Center, Neuherberg, Munich, Germany; Graduate School of Systemic Neurosciences (GSN), Munich, Germany; Institute of Computational Biology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
| | - Saketh Kapoor
- Institute for Tissue Engineering and Regenerative Medicine (iTERM), Helmholtz Center, Neuherberg, Munich, Germany
| | - Laura M Bartos
- Department of Nuclear Medicine, University Hospital, Ludwig-Maximilians-Universität München, Munich, Germany
| | - Maren Büttner
- Institute of Computational Biology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
| | - Ozum Sehnaz Caliskan
- Institute for Diabetes and Obesity, Helmholtz Center Munich and German Center for Diabetes Research (DZD), 85764 Neuherberg, Germany
| | - Zhouyi Rong
- Institute for Tissue Engineering and Regenerative Medicine (iTERM), Helmholtz Center, Neuherberg, Munich, Germany; Institute for Stroke and Dementia Research, LMU University Hospital, Ludwig-Maximilians University Munich, Munich, Germany; Munich Medical Research School (MMRS), 80336 Munich, Germany
| | - Hongcheng Mai
- Institute for Tissue Engineering and Regenerative Medicine (iTERM), Helmholtz Center, Neuherberg, Munich, Germany; Institute for Stroke and Dementia Research, LMU University Hospital, Ludwig-Maximilians University Munich, Munich, Germany; Munich Medical Research School (MMRS), 80336 Munich, Germany
| | - Luciano Höher
- Institute for Tissue Engineering and Regenerative Medicine (iTERM), Helmholtz Center, Neuherberg, Munich, Germany
| | - Denise Jeridi
- Institute for Tissue Engineering and Regenerative Medicine (iTERM), Helmholtz Center, Neuherberg, Munich, Germany
| | - Muge Molbay
- Institute for Tissue Engineering and Regenerative Medicine (iTERM), Helmholtz Center, Neuherberg, Munich, Germany
| | - Igor Khalin
- Institute for Stroke and Dementia Research, LMU University Hospital, Ludwig-Maximilians University Munich, Munich, Germany
| | | | - Moritz Negwer
- Institute for Tissue Engineering and Regenerative Medicine (iTERM), Helmholtz Center, Neuherberg, Munich, Germany
| | | | - Alba Simats
- Institute for Stroke and Dementia Research, LMU University Hospital, Ludwig-Maximilians University Munich, Munich, Germany
| | - Olga Carofiglio
- Institute for Stroke and Dementia Research, LMU University Hospital, Ludwig-Maximilians University Munich, Munich, Germany
| | - Mihail I Todorov
- Institute for Tissue Engineering and Regenerative Medicine (iTERM), Helmholtz Center, Neuherberg, Munich, Germany; Institute for Stroke and Dementia Research, LMU University Hospital, Ludwig-Maximilians University Munich, Munich, Germany
| | - Izabela Horvath
- Institute for Tissue Engineering and Regenerative Medicine (iTERM), Helmholtz Center, Neuherberg, Munich, Germany; School of Computation, Information and Technology (CIT), TUM, Boltzmannstr. 3, 85748 Garching, Germany
| | - Furkan Ozturk
- Institute for Tissue Engineering and Regenerative Medicine (iTERM), Helmholtz Center, Neuherberg, Munich, Germany
| | - Selina Hummel
- German Center for Neurodegenerative Diseases (DZNE) Munich, Munich, Germany; Department of Nuclear Medicine, University Hospital, Ludwig-Maximilians-Universität München, Munich, Germany
| | - Gloria Biechele
- Department of Nuclear Medicine, University Hospital, Ludwig-Maximilians-Universität München, Munich, Germany
| | - Artem Zatcepin
- German Center for Neurodegenerative Diseases (DZNE) Munich, Munich, Germany; Department of Nuclear Medicine, University Hospital, Ludwig-Maximilians-Universität München, Munich, Germany
| | - Marcus Unterrainer
- Department of Nuclear Medicine, University Hospital, Ludwig-Maximilians-Universität München, Munich, Germany; Department of Radiology, University Hospital, LMU Munich, Munich, Germany
| | - Johannes Gnörich
- Department of Nuclear Medicine, University Hospital, Ludwig-Maximilians-Universität München, Munich, Germany
| | - Jay Roodselaar
- Charité - Universitätsmedizin Berlin, Department of Rheumatology and Clinical Immunology, Berlin, Germany; Immune Dynamics, Deutsches Rheuma-Forschungszentrum (DRFZ), a Leibniz Institute, Berlin, Germany
| | - Joshua Shrouder
- Institute for Stroke and Dementia Research, LMU University Hospital, Ludwig-Maximilians University Munich, Munich, Germany
| | - Pardis Khosravani
- Biomedical Center (BMC), Core Facility Flow Cytometry, Faculty of Medicine, LMU Munich, Munich, Germany
| | - Benjamin Tast
- Biomedical Center (BMC), Core Facility Flow Cytometry, Faculty of Medicine, LMU Munich, Munich, Germany
| | - Lisa Richter
- Biomedical Center (BMC), Core Facility Flow Cytometry, Faculty of Medicine, LMU Munich, Munich, Germany
| | - Laura Díaz-Marugán
- Institute for Stroke and Dementia Research, LMU University Hospital, Ludwig-Maximilians University Munich, Munich, Germany
| | - Doris Kaltenecker
- Institute for Tissue Engineering and Regenerative Medicine (iTERM), Helmholtz Center, Neuherberg, Munich, Germany; Institute for Diabetes and Cancer, Helmholtz Munich, Munich, Germany
| | - Laurin Lux
- Institute for Tissue Engineering and Regenerative Medicine (iTERM), Helmholtz Center, Neuherberg, Munich, Germany
| | - Ying Chen
- Institute for Stroke and Dementia Research, LMU University Hospital, Ludwig-Maximilians University Munich, Munich, Germany
| | - Shan Zhao
- Institute for Tissue Engineering and Regenerative Medicine (iTERM), Helmholtz Center, Neuherberg, Munich, Germany; Institute for Stroke and Dementia Research, LMU University Hospital, Ludwig-Maximilians University Munich, Munich, Germany
| | - Boris-Stephan Rauchmann
- Division of Mental Health in Older Adults and Alzheimer Therapy and Research Center, Department of Psychiatry and Psychotherapy, University Hospital, Ludwig Maximilian University Munich, 80336 Munich, Germany; Sheffield Institute for Translational Neuroscience, University of Sheffield, Sheffield, UK; Institute of Neuroradiology, University Hospital LMU, Munich, Germany
| | - Michael Sterr
- Institute of Diabetes and Regeneration Research, Helmholtz Diabetes Center, Helmholtz Zentrum München, Neuherberg, Germany; Institute of Stem Cell Research, Helmholtz Zentrum München, Neuherberg, Germany
| | - Ines Kunze
- Institute of Diabetes and Regeneration Research, Helmholtz Diabetes Center, Helmholtz Zentrum München, Neuherberg, Germany; Institute of Stem Cell Research, Helmholtz Zentrum München, Neuherberg, Germany
| | - Karen Stanic
- Institute for Tissue Engineering and Regenerative Medicine (iTERM), Helmholtz Center, Neuherberg, Munich, Germany; Institute for Stroke and Dementia Research, LMU University Hospital, Ludwig-Maximilians University Munich, Munich, Germany
| | - Vanessa W Y Kan
- Institute of Clinical Neuroimmunology, University Hospital Munich, Ludwig-Maximilians University Munich, Munich, Germany
| | - Simon Besson-Girard
- Institute for Stroke and Dementia Research, LMU University Hospital, Ludwig-Maximilians University Munich, Munich, Germany; Graduate School of Systemic Neurosciences (GSN), Munich, Germany
| | - Sabrina Katzdobler
- German Center for Neurodegenerative Diseases (DZNE) Munich, Munich, Germany; Department of Neurology, Ludwig-Maximilians-Universität München, Munich, Germany
| | - Carla Palleis
- German Center for Neurodegenerative Diseases (DZNE) Munich, Munich, Germany; Department of Neurology, Ludwig-Maximilians-Universität München, Munich, Germany
| | - Julia Schädler
- Institute of Legal Medicine, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Johannes C Paetzold
- Institute for Tissue Engineering and Regenerative Medicine (iTERM), Helmholtz Center, Neuherberg, Munich, Germany; Department of Computing, Imperial College London, London, UK
| | - Sabine Liebscher
- Munich Cluster for Systems Neurology (SyNergy), Munich, Germany; Institute of Clinical Neuroimmunology, University Hospital Munich, Ludwig-Maximilians University Munich, Munich, Germany; Biomedical Center (BMC), Medical Faculty, Ludwig-Maximilians Universität Munich, Munich, Germany
| | - Anja E Hauser
- Charité - Universitätsmedizin Berlin, Department of Rheumatology and Clinical Immunology, Berlin, Germany; Immune Dynamics, Deutsches Rheuma-Forschungszentrum (DRFZ), a Leibniz Institute, Berlin, Germany
| | - Ozgun Gokce
- Institute for Stroke and Dementia Research, LMU University Hospital, Ludwig-Maximilians University Munich, Munich, Germany; Munich Cluster for Systems Neurology (SyNergy), Munich, Germany
| | - Heiko Lickert
- Institute of Diabetes and Regeneration Research, Helmholtz Diabetes Center, Helmholtz Zentrum München, Neuherberg, Germany; Institute of Stem Cell Research, Helmholtz Zentrum München, Neuherberg, Germany; TUM School of Medicine, Technical University of Munich, Munich, Germany
| | - Hanno Steinke
- Institute of Anatomy, University of Leipzig, 04109 Leipzig, Germany
| | - Corinne Benakis
- Institute for Stroke and Dementia Research, LMU University Hospital, Ludwig-Maximilians University Munich, Munich, Germany
| | - Christian Braun
- Institute of Legal Medicine, Faculty of Medicine, LMU Munich, Germany
| | - Celia P Martinez-Jimenez
- Helmholtz Pioneer Campus (HPC), Helmholtz Munich, Neuherberg, Germany; TUM School of Medicine, Technical University of Munich, Munich, Germany
| | - Katharina Buerger
- Institute for Stroke and Dementia Research, LMU University Hospital, Ludwig-Maximilians University Munich, Munich, Germany; German Center for Neurodegenerative Diseases (DZNE) Munich, Munich, Germany
| | - Nathalie L Albert
- Department of Nuclear Medicine, University Hospital, Ludwig-Maximilians-Universität München, Munich, Germany
| | - Günter Höglinger
- German Center for Neurodegenerative Diseases (DZNE) Munich, Munich, Germany; Department of Neurology, Ludwig-Maximilians-Universität München, Munich, Germany
| | - Johannes Levin
- German Center for Neurodegenerative Diseases (DZNE) Munich, Munich, Germany; Munich Cluster for Systems Neurology (SyNergy), Munich, Germany; Department of Neurology, Ludwig-Maximilians-Universität München, Munich, Germany
| | - Christian Haass
- German Center for Neurodegenerative Diseases (DZNE) Munich, Munich, Germany; Munich Cluster for Systems Neurology (SyNergy), Munich, Germany; Metabolic Biochemistry, Biomedical Center (BMC), Faculty of Medicine, Ludwig-Maximilians-Universität München, Munich, Germany
| | - Anna Kopczak
- Institute for Stroke and Dementia Research, LMU University Hospital, Ludwig-Maximilians University Munich, Munich, Germany
| | - Martin Dichgans
- Institute for Stroke and Dementia Research, LMU University Hospital, Ludwig-Maximilians University Munich, Munich, Germany; German Center for Neurodegenerative Diseases (DZNE) Munich, Munich, Germany; Munich Cluster for Systems Neurology (SyNergy), Munich, Germany
| | - Joachim Havla
- Institute of Clinical Neuroimmunology, University Hospital Munich, Ludwig-Maximilians University Munich, Munich, Germany; Biomedical Center (BMC), Medical Faculty, Ludwig-Maximilians Universität Munich, Munich, Germany
| | - Tania Kümpfel
- Institute of Clinical Neuroimmunology, University Hospital Munich, Ludwig-Maximilians University Munich, Munich, Germany; Biomedical Center (BMC), Medical Faculty, Ludwig-Maximilians Universität Munich, Munich, Germany
| | - Martin Kerschensteiner
- Munich Cluster for Systems Neurology (SyNergy), Munich, Germany; Institute of Clinical Neuroimmunology, University Hospital Munich, Ludwig-Maximilians University Munich, Munich, Germany; Biomedical Center (BMC), Medical Faculty, Ludwig-Maximilians Universität Munich, Munich, Germany
| | - Martina Schifferer
- German Center for Neurodegenerative Diseases (DZNE) Munich, Munich, Germany; Munich Cluster for Systems Neurology (SyNergy), Munich, Germany
| | - Mikael Simons
- German Center for Neurodegenerative Diseases (DZNE) Munich, Munich, Germany; Munich Cluster for Systems Neurology (SyNergy), Munich, Germany
| | - Arthur Liesz
- Institute for Stroke and Dementia Research, LMU University Hospital, Ludwig-Maximilians University Munich, Munich, Germany; Graduate School of Systemic Neurosciences (GSN), Munich, Germany; Munich Cluster for Systems Neurology (SyNergy), Munich, Germany
| | - Natalie Krahmer
- Institute for Diabetes and Obesity, Helmholtz Center Munich and German Center for Diabetes Research (DZD), 85764 Neuherberg, Germany
| | | | - Nicolai Franzmeier
- Institute for Stroke and Dementia Research, LMU University Hospital, Ludwig-Maximilians University Munich, Munich, Germany
| | - Nikolaus Plesnila
- Institute for Stroke and Dementia Research, LMU University Hospital, Ludwig-Maximilians University Munich, Munich, Germany; Munich Cluster for Systems Neurology (SyNergy), Munich, Germany
| | - Suheda Erener
- Institute for Tissue Engineering and Regenerative Medicine (iTERM), Helmholtz Center, Neuherberg, Munich, Germany
| | - Victor G Puelles
- III. Department of Medicine, University Medical Center Hamburg-Eppendorf, Hamburg, Germany; Hamburg Center for Kidney Health (HCKH), University Medical Center Hamburg-Eppendorf, Hamburg, Germany; Department of Clinical Medicine, Aarhus University, Aarhus, Denmark; Department of Pathology, Aarhus University Hospital, Aarhus, Denmark
| | - Claire Delbridge
- Institute of Pathology, Department of Neuropathology, Technical University Munich, TUM School of Medicine, Munich, Germany
| | - Harsharan Singh Bhatia
- Institute for Tissue Engineering and Regenerative Medicine (iTERM), Helmholtz Center, Neuherberg, Munich, Germany; Institute for Stroke and Dementia Research, LMU University Hospital, Ludwig-Maximilians University Munich, Munich, Germany
| | - Farida Hellal
- Institute for Tissue Engineering and Regenerative Medicine (iTERM), Helmholtz Center, Neuherberg, Munich, Germany; Institute for Stroke and Dementia Research, LMU University Hospital, Ludwig-Maximilians University Munich, Munich, Germany; Munich Cluster for Systems Neurology (SyNergy), Munich, Germany
| | - Markus Elsner
- Institute for Tissue Engineering and Regenerative Medicine (iTERM), Helmholtz Center, Neuherberg, Munich, Germany
| | - Ingo Bechmann
- Institute of Anatomy, University of Leipzig, 04109 Leipzig, Germany
| | - Benjamin Ondruschka
- Institute of Legal Medicine, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Matthias Brendel
- German Center for Neurodegenerative Diseases (DZNE) Munich, Munich, Germany; Munich Cluster for Systems Neurology (SyNergy), Munich, Germany; Department of Nuclear Medicine, University Hospital, Ludwig-Maximilians-Universität München, Munich, Germany
| | - Fabian J Theis
- Institute of Computational Biology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany; Department of Mathematics, Technische Universität München, Garching bei München, Germany
| | - Ali Erturk
- Institute for Tissue Engineering and Regenerative Medicine (iTERM), Helmholtz Center, Neuherberg, Munich, Germany; Institute for Stroke and Dementia Research, LMU University Hospital, Ludwig-Maximilians University Munich, Munich, Germany; Graduate School of Systemic Neurosciences (GSN), Munich, Germany; Munich Cluster for Systems Neurology (SyNergy), Munich, Germany.
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Smart K, Uribe C, Desmond KL, Martin SL, Vasdev N, Strafella AP. Preliminary Assessment of Reference Region Quantification and Reduced Scanning Times for [ 18F]SynVesT-1 PET in Parkinson's Disease. Mol Imaging 2023; 2023:1855985. [PMID: 37622164 PMCID: PMC10445483 DOI: 10.1155/2023/1855985] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/30/2023] [Revised: 06/02/2023] [Accepted: 07/26/2023] [Indexed: 08/26/2023] Open
Abstract
Synaptic density in the central nervous system can be measured in vivo using PET with [18F]SynVesT-1. While [18F]SynVesT-1 has been proven to be a powerful radiopharmaceutical for PET imaging of neurodegenerative disorders such as Parkinson's disease (PD), its currently validated acquisition and quantification protocols are invasive and technically challenging in these populations due to the arterial sampling and relatively long scanning times. The objectives of this work were to evaluate a noninvasive (reference tissue) quantification method for [18F]SynVesT-1 in PD patients and to determine the minimum scan time necessary for accurate quantification. [18F]SynVesT-1 PET scans were acquired in 5 patients with PD and 3 healthy control subjects for 120 min with arterial blood sampling. Quantification was performed using the one-tissue compartment model (1TCM) with arterial input function, as well as with the simplified reference tissue model (SRTM) to estimate binding potential (BPND) using centrum semiovale (CS) as a reference region. The SRTM2 method was used with k2' fixed to either a sample average value (0.037 min-1) or a value estimated first through coupled fitting across regions for each participant. Direct SRTM estimation and the Logan reference region graphical method were also evaluated. There were no significant group differences in CS volume, radiotracer uptake, or efflux (ps > 0.47). Each fitting method produced BPND estimates in close agreement with those derived from the 1TCM (subject R2s > 0.98, bias < 10%), with no difference in bias between the control and PD groups. With SRTM2, BPND estimates from truncated scan data as short as 80 min produced values in excellent agreement with the data from the full 120 min scans (bias < 6%). While these are preliminary results from a small sample of patients with PD (n = 5), this work suggests that accurate synaptic density quantification may be performed without blood sampling and with scan time under 90 minutes. If further validated, these simplified procedures for [18F]SynVesT-1 PET quantification can facilitate its application as a clinical research imaging technology and allow for larger study samples and include a broader scope of patients including those with neurodegenerative diseases.
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Affiliation(s)
- Kelly Smart
- Brain Health Imaging Centre, Centre for Addiction and Mental Health, 250 College St., Toronto, ON, Canada M5T 1R8
- Department of Psychiatry, University of Toronto, 250 College St., Toronto, ON, Canada M5T 1R8
| | - Carme Uribe
- Brain Health Imaging Centre, Centre for Addiction and Mental Health, 250 College St., Toronto, ON, Canada M5T 1R8
- Unitat de Psicologia Medica, Departament de Medicina, Institute of Neuroscience, Universitat de Barcelona, Barcelona, Spain
| | - Kimberly L. Desmond
- Brain Health Imaging Centre, Centre for Addiction and Mental Health, 250 College St., Toronto, ON, Canada M5T 1R8
- Department of Psychiatry, University of Toronto, 250 College St., Toronto, ON, Canada M5T 1R8
| | - Sarah L. Martin
- Brain Health Imaging Centre, Centre for Addiction and Mental Health, 250 College St., Toronto, ON, Canada M5T 1R8
| | - Neil Vasdev
- Brain Health Imaging Centre, Centre for Addiction and Mental Health, 250 College St., Toronto, ON, Canada M5T 1R8
- Department of Psychiatry, University of Toronto, 250 College St., Toronto, ON, Canada M5T 1R8
| | - Antonio P. Strafella
- Brain Health Imaging Centre, Centre for Addiction and Mental Health, 250 College St., Toronto, ON, Canada M5T 1R8
- Edmond J. Safra Parkinson Disease Program, Neurology Division, Toronto Western Hospital & Krembil Brain Institute, University Health Network, University of Toronto, 399 Bathurst Street, Toronto, ON, Canada M5T 2S8
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131
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Nordio G, Easmin R, Giacomel A, Dipasquale O, Martins D, Williams S, Turkheimer F, Howes O, Veronese M, Jauhar S, Rogdaki M, McCutcheon R, Kaar S, Vano L, Rutigliano G, Angelescu I, Borgan F, D’Ambrosio E, Dahoun T, Kim E, Kim S, Bloomfield M, Egerton A, Demjaha A, Bonoldi I, Nosarti C, Maccabe J, McGuire P, Matthews J, Talbot PS. An automatic analysis framework for FDOPA PET neuroimaging. J Cereb Blood Flow Metab 2023; 43:1285-1300. [PMID: 37026455 PMCID: PMC10369152 DOI: 10.1177/0271678x231168687] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/13/2022] [Revised: 01/23/2023] [Accepted: 02/05/2023] [Indexed: 04/08/2023]
Abstract
In this study we evaluate the performance of a fully automated analytical framework for FDOPA PET neuroimaging data, and its sensitivity to demographic and experimental variables and processing parameters. An instance of XNAT imaging platform was used to store the King's College London institutional brain FDOPA PET imaging archive, alongside individual demographics and clinical information. By re-engineering the historical Matlab-based scripts for FDOPA PET analysis, a fully automated analysis pipeline for imaging processing and data quantification was implemented in Python and integrated in XNAT. The final data repository includes 892 FDOPA PET scans organized from 23 different studies. We found good reproducibility of the data analysis by the automated pipeline (in the striatum for the Kicer: for the controls ICC = 0.71, for the psychotic patients ICC = 0.88). From the demographic and experimental variables assessed, gender was found to most influence striatal dopamine synthesis capacity (F = 10.7, p < 0.001), with women showing greater dopamine synthesis capacity than men. Our automated analysis pipeline represents a valid resourse for standardised and robust quantification of dopamine synthesis capacity using FDOPA PET data. Combining information from different neuroimaging studies has allowed us to test it comprehensively and to validate its replicability and reproducibility performances on a large sample size.
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Affiliation(s)
- Giovanna Nordio
- Department of Neuroimaging, Institute of Psychiatry, Psychology & Neuroscience, King’s College London, London, UK
| | - Rubaida Easmin
- Department of Neuroimaging, Institute of Psychiatry, Psychology & Neuroscience, King’s College London, London, UK
| | - Alessio Giacomel
- Department of Neuroimaging, Institute of Psychiatry, Psychology & Neuroscience, King’s College London, London, UK
| | - Ottavia Dipasquale
- Department of Neuroimaging, Institute of Psychiatry, Psychology & Neuroscience, King’s College London, London, UK
| | - Daniel Martins
- Department of Neuroimaging, Institute of Psychiatry, Psychology & Neuroscience, King’s College London, London, UK
| | - Steven Williams
- Department of Neuroimaging, Institute of Psychiatry, Psychology & Neuroscience, King’s College London, London, UK
| | - Federico Turkheimer
- Department of Neuroimaging, Institute of Psychiatry, Psychology & Neuroscience, King’s College London, London, UK
| | - Oliver Howes
- Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, King’s College London, London, UK
- MRC London Institute of Medical Sciences, Hammersmith Hospital, London, UK
- Institute of Clinical Sciences (ICS), Faculty of Medicine, Imperial College London, UK
| | - Mattia Veronese
- Department of Neuroimaging, Institute of Psychiatry, Psychology & Neuroscience, King’s College London, London, UK
- Department of Information Engineering (DEI), University of Padua, Padua, Italy
| | - and the FDOPA PET imaging working group:
- Department of Neuroimaging, Institute of Psychiatry, Psychology & Neuroscience, King’s College London, London, UK
- Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, King’s College London, London, UK
- MRC London Institute of Medical Sciences, Hammersmith Hospital, London, UK
- Institute of Clinical Sciences (ICS), Faculty of Medicine, Imperial College London, UK
- Department of Information Engineering (DEI), University of Padua, Padua, Italy
- Psychiatric Imaging Group, MRC London Institute of Medical Sciences, Hammersmith Hospital, Imperial College London, London, UK
- Institute of Clinical Sciences, Faculty of Medicine, Imperial College, Imperial College London, London, UK
- South London and Maudsley NHS Foundation Trust, London, UK
- COMPASS Pathways plc, London, UK
- Psychiatric Neuroscience Group, Department of Basic Medical Sciences, Neuroscience and Sense Organs, University of Bari "Aldo Moro", Bari, Italy
- Department of Psychiatry, Warneford Hospital, University of Oxford, Oxford, UK
- Department of Psychiatry, Seoul National University Bundang Hospital, Gyeonggi-do, Republic of Korea
- Department of Psychiatry, College of Medicine, Seoul National University, Seoul, Republic of Korea
- Department of Brain & Cognitive Sciences, College of Natural Sciences, Seoul National University, Seoul, Republic of Korea
- Division of Psychiatry, Faculty of Brain Sciences, University College of London, London, UK
- Department of Child and Adolescent Psychiatry, Institute of Psychiatry, Psychology & Neurosicences, King’s College London, London, UK
- Centre for the Developing Brain, Division of Imaging Sciences & Biomedical Engineering, King's College London, London, UK
- Early Intervention Psychosis Clinical Academic Group, South London & Maudsley NHS Trust, London, UK
- Division of Neuroscience and Experimental Psychology, School of Biological Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester, UK
| | - Sameer Jauhar
- Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, King’s College London, London, UK
- Psychiatric Imaging Group, MRC London Institute of Medical Sciences, Hammersmith Hospital, Imperial College London, London, UK
- Institute of Clinical Sciences, Faculty of Medicine, Imperial College, Imperial College London, London, UK
| | - Maria Rogdaki
- Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, King’s College London, London, UK
| | - Robert McCutcheon
- Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, King’s College London, London, UK
- Psychiatric Imaging Group, MRC London Institute of Medical Sciences, Hammersmith Hospital, Imperial College London, London, UK
- Institute of Clinical Sciences, Faculty of Medicine, Imperial College, Imperial College London, London, UK
- South London and Maudsley NHS Foundation Trust, London, UK
| | - Stephen Kaar
- Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, King’s College London, London, UK
- Institute of Clinical Sciences (ICS), Faculty of Medicine, Imperial College London, UK
- Psychiatric Imaging Group, MRC London Institute of Medical Sciences, Hammersmith Hospital, Imperial College London, London, UK
- South London and Maudsley NHS Foundation Trust, London, UK
| | - Luke Vano
- Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, King’s College London, London, UK
- Psychiatric Imaging Group, MRC London Institute of Medical Sciences, Hammersmith Hospital, Imperial College London, London, UK
| | - Grazia Rutigliano
- Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, King’s College London, London, UK
- Psychiatric Imaging Group, MRC London Institute of Medical Sciences, Hammersmith Hospital, Imperial College London, London, UK
| | - Ilinca Angelescu
- Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, King’s College London, London, UK
| | - Faith Borgan
- Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, King’s College London, London, UK
- COMPASS Pathways plc, London, UK
| | - Enrico D’Ambrosio
- Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, King’s College London, London, UK
- Psychiatric Neuroscience Group, Department of Basic Medical Sciences, Neuroscience and Sense Organs, University of Bari "Aldo Moro", Bari, Italy
| | - Tarik Dahoun
- Psychiatric Imaging Group, MRC London Institute of Medical Sciences, Hammersmith Hospital, Imperial College London, London, UK
- Institute of Clinical Sciences, Faculty of Medicine, Imperial College, Imperial College London, London, UK
- Department of Psychiatry, Warneford Hospital, University of Oxford, Oxford, UK
| | - Euitae Kim
- Department of Psychiatry, Seoul National University Bundang Hospital, Gyeonggi-do, Republic of Korea
- Department of Psychiatry, College of Medicine, Seoul National University, Seoul, Republic of Korea
- Department of Brain & Cognitive Sciences, College of Natural Sciences, Seoul National University, Seoul, Republic of Korea
| | - Seoyoung Kim
- Department of Psychiatry, College of Medicine, Seoul National University, Seoul, Republic of Korea
| | - Micheal Bloomfield
- Division of Psychiatry, Faculty of Brain Sciences, University College of London, London, UK
| | - Alice Egerton
- Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, King’s College London, London, UK
| | - Arsime Demjaha
- Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, King’s College London, London, UK
| | - Ilaria Bonoldi
- Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, King’s College London, London, UK
| | - Chiara Nosarti
- Department of Child and Adolescent Psychiatry, Institute of Psychiatry, Psychology & Neurosicences, King’s College London, London, UK
- Centre for the Developing Brain, Division of Imaging Sciences & Biomedical Engineering, King's College London, London, UK
| | - James Maccabe
- Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, King’s College London, London, UK
| | - Philip McGuire
- Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, King’s College London, London, UK
- Early Intervention Psychosis Clinical Academic Group, South London & Maudsley NHS Trust, London, UK
| | - Julian Matthews
- Division of Neuroscience and Experimental Psychology, School of Biological Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester, UK
| | - Peter S Talbot
- Division of Neuroscience and Experimental Psychology, School of Biological Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester, UK
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132
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Tian M, Zuo C, Civelek AC, Carrio I, Watanabe Y, Kang KW, Murakami K, Garibotto V, Prior JO, Barthel H, Guan Y, Lu J, Zhou R, Jin C, Wu S, Zhang X, Zhong Y, Zhang H. International Nuclear Medicine Consensus on the Clinical Use of Amyloid Positron Emission Tomography in Alzheimer's Disease. PHENOMICS (CHAM, SWITZERLAND) 2023; 3:375-389. [PMID: 37589025 PMCID: PMC10425321 DOI: 10.1007/s43657-022-00068-9] [Citation(s) in RCA: 23] [Impact Index Per Article: 11.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 02/21/2022] [Revised: 07/19/2022] [Accepted: 07/22/2022] [Indexed: 08/18/2023]
Abstract
Alzheimer's disease (AD) is the main cause of dementia, with its diagnosis and management remaining challenging. Amyloid positron emission tomography (PET) has become increasingly important in medical practice for patients with AD. To integrate and update previous guidelines in the field, a task group of experts of several disciplines from multiple countries was assembled, and they revised and approved the content related to the application of amyloid PET in the medical settings of cognitively impaired individuals, focusing on clinical scenarios, patient preparation, administered activities, as well as image acquisition, processing, interpretation and reporting. In addition, expert opinions, practices, and protocols of prominent research institutions performing research on amyloid PET of dementia are integrated. With the increasing availability of amyloid PET imaging, a complete and standard pipeline for the entire examination process is essential for clinical practice. This international consensus and practice guideline will help to promote proper clinical use of amyloid PET imaging in patients with AD.
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Affiliation(s)
- Mei Tian
- PET Center, Huashan Hospital, Fudan University, Shanghai, 200235 China
- Human Phenome Institute, Fudan University, Shanghai, 201203 China
- Department of Nuclear Medicine and PET Center, The Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, 310009 China
| | - Chuantao Zuo
- PET Center, Huashan Hospital, Fudan University, Shanghai, 200235 China
- National Center for Neurological Disorders and National Clinical Research Center for Aging and Medicine, Huashan Hospital, Fudan University, Shanghai, 200040 China
| | - Ali Cahid Civelek
- Department of Radiology and Radiological Science, Division of Nuclear Medicine and Molecular Imaging, Johns Hopkins Medicine, Baltimore, 21287 USA
| | - Ignasi Carrio
- Department of Nuclear Medicine, Hospital Sant Pau, Autonomous University of Barcelona, Barcelona, 08025 Spain
| | - Yasuyoshi Watanabe
- Laboratory for Pathophysiological and Health Science, RIKEN Center for Biosystems Dynamics Research, Kobe, Hyogo 650-0047 Japan
| | - Keon Wook Kang
- Department of Nuclear Medicine, Seoul National University College of Medicine, Seoul, 03080 Korea
| | - Koji Murakami
- Department of Radiology, Juntendo University Hospital, Tokyo, 113-8431 Japan
| | - Valentina Garibotto
- Diagnostic Department, University Hospitals of Geneva and NIMTlab, University of Geneva, Geneva, 1205 Switzerland
| | - John O. Prior
- Department of Nuclear Medicine and Molecular Imaging, Lausanne University Hospital, Lausanne, 1011 Switzerland
| | - Henryk Barthel
- Department of Nuclear Medicine, Leipzig University Medical Center, Leipzig, 04103 Germany
| | - Yihui Guan
- PET Center, Huashan Hospital, Fudan University, Shanghai, 200235 China
| | - Jiaying Lu
- PET Center, Huashan Hospital, Fudan University, Shanghai, 200235 China
| | - Rui Zhou
- Department of Nuclear Medicine and PET Center, The Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, 310009 China
| | - Chentao Jin
- Department of Nuclear Medicine and PET Center, The Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, 310009 China
| | - Shuang Wu
- Department of Nuclear Medicine and PET Center, The Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, 310009 China
| | - Xiaohui Zhang
- Department of Nuclear Medicine and PET Center, The Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, 310009 China
| | - Yan Zhong
- Department of Nuclear Medicine and PET Center, The Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, 310009 China
| | - Hong Zhang
- Department of Nuclear Medicine and PET Center, The Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, 310009 China
- Key Laboratory of Medical Molecular Imaging of Zhejiang Province, Hangzhou, 310009 China
- The College of Biomedical Engineering and Instrument Science of Zhejiang University, Hangzhou, 310007 China
- Key Laboratory for Biomedical Engineering of Ministry of Education, Zhejiang University, Hangzhou, 310007 China
| | - Molecular Imaging-Based Precision Medicine Task Group of A3 (China-Japan-Korea) Foresight Program
- PET Center, Huashan Hospital, Fudan University, Shanghai, 200235 China
- Human Phenome Institute, Fudan University, Shanghai, 201203 China
- Department of Nuclear Medicine and PET Center, The Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, 310009 China
- National Center for Neurological Disorders and National Clinical Research Center for Aging and Medicine, Huashan Hospital, Fudan University, Shanghai, 200040 China
- Department of Radiology and Radiological Science, Division of Nuclear Medicine and Molecular Imaging, Johns Hopkins Medicine, Baltimore, 21287 USA
- Department of Nuclear Medicine, Hospital Sant Pau, Autonomous University of Barcelona, Barcelona, 08025 Spain
- Laboratory for Pathophysiological and Health Science, RIKEN Center for Biosystems Dynamics Research, Kobe, Hyogo 650-0047 Japan
- Department of Nuclear Medicine, Seoul National University College of Medicine, Seoul, 03080 Korea
- Department of Radiology, Juntendo University Hospital, Tokyo, 113-8431 Japan
- Diagnostic Department, University Hospitals of Geneva and NIMTlab, University of Geneva, Geneva, 1205 Switzerland
- Department of Nuclear Medicine and Molecular Imaging, Lausanne University Hospital, Lausanne, 1011 Switzerland
- Department of Nuclear Medicine, Leipzig University Medical Center, Leipzig, 04103 Germany
- Key Laboratory of Medical Molecular Imaging of Zhejiang Province, Hangzhou, 310009 China
- The College of Biomedical Engineering and Instrument Science of Zhejiang University, Hangzhou, 310007 China
- Key Laboratory for Biomedical Engineering of Ministry of Education, Zhejiang University, Hangzhou, 310007 China
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Yu HJ, Dickson SP, Wang PN, Chiu MJ, Huang CC, Chang CC, Liu H, Hendrix SB, Dodart JC, Verma A, Wang CY, Cummings J. Safety, tolerability, immunogenicity, and efficacy of UB-311 in participants with mild Alzheimer's disease: a randomised, double-blind, placebo-controlled, phase 2a study. EBioMedicine 2023; 94:104665. [PMID: 37392597 PMCID: PMC10338203 DOI: 10.1016/j.ebiom.2023.104665] [Citation(s) in RCA: 21] [Impact Index Per Article: 10.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/05/2023] [Revised: 06/01/2023] [Accepted: 06/05/2023] [Indexed: 07/03/2023] Open
Abstract
BACKGROUND Anti-amyloid vaccines may offer a convenient, affordable, and accessible means of preventing and treating Alzheimer's disease. UB-311 is an anti-amyloid-β active immunotherapeutic vaccine shown to be well-tolerated and to have a durable antibody response in a phase 1 trial. This phase 2a study assessed the safety, immunogenicity, and preliminary efficacy of UB-311 in participants with mild Alzheimer's disease. METHODS A 78-week, randomised, double-blind, placebo-controlled, parallel-group, multicentre, phase 2a study was conducted in Taiwan. Participants were randomised in a 1:1:1 ratio to receive seven intramuscular injections of UB-311 (Q3M arm), or five doses of U311 with two doses of placebo (Q6M arm), or seven doses of placebo (placebo arm). The primary endpoints were safety, tolerability, and immunogenicity of UB-311. Safety was assessed in all participants who received at least one dose of investigational product. This study was registered at ClinicalTrials.gov (NCT02551809). FINDINGS Between 7 December 2015 and 28 August 2018, 43 participants were randomised. UB-311 was safe, well-tolerated, and generated a robust immune response. The three treatment-emergent adverse events (TEAEs) with the highest incidence were injection-site pain (14 TEAEs in seven [16%] participants), amyloid-related imaging abnormality with microhaemorrhages and haemosiderin deposits (12 TEAEs in six [14%] participants), and diarrhoea (five TEAEs in five [12%] participants). A 97% antibody response rate was observed and maintained at 93% by the end of the study across both UB-311 arms. INTERPRETATION These results support the continued development of UB-311. FUNDING Vaxxinity, Inc. (Formerly United Neuroscience Ltd.).
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Affiliation(s)
- Hui Jing Yu
- Vaxxinity, Inc. (Formerly United Neuroscience Ltd.), Exploration Park, FL, USA.
| | | | - Pei-Ning Wang
- Division of General Neurology, Department of Neurological Institute, Taipei Veterans General Hospital & Brain Research Center, National Yang Ming Chiao Tung University, Taipei, Taiwan
| | | | | | - Chiung-Chih Chang
- Department of Neurology, Cognition and Aging Center, Institute for Translational Research in Biomedicine, Kaohsiung Chang Gung Memorial Hospital, Chang Gung University College of Medicine, Kaohsiung, Taiwan
| | - Hope Liu
- United Biomedical, Inc. Asia, Zhubei City, Hsinchu, Taiwan
| | | | - Jean-Cosme Dodart
- Vaxxinity, Inc. (Formerly United Neuroscience Ltd.), Exploration Park, FL, USA
| | - Ajay Verma
- Vaxxinity, Inc. (Formerly United Neuroscience Ltd.), Exploration Park, FL, USA
| | - Chang Yi Wang
- United Biomedical, Inc. Asia, Zhubei City, Hsinchu, Taiwan; United Biomedical, Inc., Hauppauge, NY, USA
| | - Jeffrey Cummings
- Chambers-Grundy Center for Transformative Neuroscience, Pam Quirk Brain Health and Biomarker Laboratory, Department of Brain Health, School of Integrated Health Sciences, University of Nevada Las Vegas, Las Vegas, NV, USA
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Visser D, Verfaillie SCJ, Bosch I, Brouwer I, Tuncel H, Coomans EM, Rikken RM, Mastenbroek SE, Golla SSV, Barkhof F, van de Giessen E, van Berckel BNM, van der Flier WM, Ossenkoppele R. Tau pathology as determinant of changes in atrophy and cerebral blood flow: a multi-modal longitudinal imaging study. Eur J Nucl Med Mol Imaging 2023; 50:2409-2419. [PMID: 36976303 PMCID: PMC10250461 DOI: 10.1007/s00259-023-06196-2] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/20/2023] [Accepted: 03/13/2023] [Indexed: 03/29/2023]
Abstract
PURPOSE Tau pathology is associated with concurrent atrophy and decreased cerebral blood flow (CBF) in Alzheimer's disease (AD), but less is known about their temporal relationships. Our aim was therefore to investigate the association of concurrent and longitudinal tau PET with longitudinal changes in atrophy and relative CBF. METHODS We included 61 individuals from the Amsterdam Dementia Cohort (mean age 65.1 ± 7.5 years, 44% female, 57% amyloid-β positive [Aβ +], 26 cognitively impaired [CI]) who underwent dynamic [18F]flortaucipir PET and structural MRI at baseline and 25 ± 5 months follow-up. In addition, we included 86 individuals (68 CI) who only underwent baseline dynamic [18F]flortaucipir PET and MRI scans to increase power in our statistical models. We obtained [18F]flortaucipir PET binding potential (BPND) and R1 values reflecting tau load and relative CBF, respectively, and computed cortical thickness from the structural MRI scans using FreeSurfer. We assessed the regional associations between i) baseline and ii) annual change in tau PET BPND in Braak I, III/IV, and V/VI regions and cortical thickness or R1 in cortical gray matter regions (spanning the whole brain) over time using linear mixed models with random intercepts adjusted for age, sex, time between baseline and follow-up assessments, and baseline BPND in case of analyses with annual change as determinant. All analyses were performed in Aβ- cognitively normal (CN) individuals and Aβ+ (CN and CI) individuals separately. RESULTS In Aβ+ individuals, greater baseline Braak III/IV and V/VI tau PET binding was associated with faster cortical thinning in primarily frontotemporal regions. Annual changes in tau PET were not associated with cortical thinning over time in either Aβ+ or Aβ- individuals. Baseline tau PET was not associated with longitudinal changes in relative CBF, but increases in Braak III/IV tau PET over time were associated with increases in parietal relative CBF over time in Aβ + individuals. CONCLUSION We showed that higher tau load was related to accelerated cortical thinning, but not to decreases in relative CBF. Moreover, tau PET load at baseline was a stronger predictor of cortical thinning than change of tau PET signal.
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Affiliation(s)
- Denise Visser
- Department of Radiology & Nuclear Medicine, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, P.O. Box 7057, 1007 MB, Amsterdam, The Netherlands.
- Amsterdam Neuroscience, Neurodegeneration, Amsterdam, The Netherlands.
- Amsterdam Neuroscience, Brain Imaging, Amsterdam, The Netherlands.
| | - Sander C J Verfaillie
- Department of Radiology & Nuclear Medicine, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, P.O. Box 7057, 1007 MB, Amsterdam, The Netherlands
- Amsterdam Neuroscience, Neurodegeneration, Amsterdam, The Netherlands
- Amsterdam Neuroscience, Brain Imaging, Amsterdam, The Netherlands
- Medical Psychology, Amsterdam UMC Location University of Amsterdam, Meibergdreef 9, Amsterdam, the Netherlands
| | - Iris Bosch
- Department of Radiology & Nuclear Medicine, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, P.O. Box 7057, 1007 MB, Amsterdam, The Netherlands
- Amsterdam Neuroscience, Brain Imaging, Amsterdam, The Netherlands
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, The Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden
- Wallenberg Centre for Molecular and Translational Medicine, University of Gothenburg, Gothenburg, Sweden
| | - Iman Brouwer
- Department of Radiology & Nuclear Medicine, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, P.O. Box 7057, 1007 MB, Amsterdam, The Netherlands
- Amsterdam Neuroscience, Neurodegeneration, Amsterdam, The Netherlands
- Amsterdam Neuroscience, Brain Imaging, Amsterdam, The Netherlands
| | - Hayel Tuncel
- Department of Radiology & Nuclear Medicine, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, P.O. Box 7057, 1007 MB, Amsterdam, The Netherlands
- Amsterdam Neuroscience, Neurodegeneration, Amsterdam, The Netherlands
- Amsterdam Neuroscience, Brain Imaging, Amsterdam, The Netherlands
| | - Emma M Coomans
- Department of Radiology & Nuclear Medicine, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, P.O. Box 7057, 1007 MB, Amsterdam, The Netherlands
- Amsterdam Neuroscience, Neurodegeneration, Amsterdam, The Netherlands
- Amsterdam Neuroscience, Brain Imaging, Amsterdam, The Netherlands
| | - Roos M Rikken
- Department of Radiology & Nuclear Medicine, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, P.O. Box 7057, 1007 MB, Amsterdam, The Netherlands
- Amsterdam Neuroscience, Neurodegeneration, Amsterdam, The Netherlands
- Amsterdam Neuroscience, Brain Imaging, Amsterdam, The Netherlands
| | - Sophie E Mastenbroek
- Department of Radiology & Nuclear Medicine, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, P.O. Box 7057, 1007 MB, Amsterdam, The Netherlands
- Amsterdam Neuroscience, Neurodegeneration, Amsterdam, The Netherlands
- Amsterdam Neuroscience, Brain Imaging, Amsterdam, The Netherlands
- Clinical Memory Research Unit, Lund University, Lund, Sweden
| | - Sandeep S V Golla
- Department of Radiology & Nuclear Medicine, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, P.O. Box 7057, 1007 MB, Amsterdam, The Netherlands
- Amsterdam Neuroscience, Neurodegeneration, Amsterdam, The Netherlands
- Amsterdam Neuroscience, Brain Imaging, Amsterdam, The Netherlands
| | - Frederik Barkhof
- Department of Radiology & Nuclear Medicine, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, P.O. Box 7057, 1007 MB, Amsterdam, The Netherlands
- Amsterdam Neuroscience, Neurodegeneration, Amsterdam, The Netherlands
- Amsterdam Neuroscience, Brain Imaging, Amsterdam, The Netherlands
- Institutes of Neurology and Healthcare Engineering, University College London, London, UK
| | - Elsmarieke van de Giessen
- Department of Radiology & Nuclear Medicine, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, P.O. Box 7057, 1007 MB, Amsterdam, The Netherlands
- Amsterdam Neuroscience, Neurodegeneration, Amsterdam, The Netherlands
- Amsterdam Neuroscience, Brain Imaging, Amsterdam, The Netherlands
| | - Bart N M van Berckel
- Department of Radiology & Nuclear Medicine, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, P.O. Box 7057, 1007 MB, Amsterdam, The Netherlands
- Amsterdam Neuroscience, Neurodegeneration, Amsterdam, The Netherlands
- Amsterdam Neuroscience, Brain Imaging, Amsterdam, The Netherlands
| | - Wiesje M van der Flier
- Amsterdam Neuroscience, Neurodegeneration, Amsterdam, The Netherlands
- Alzheimer Center Amsterdam, Department of Neurology, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc, Amsterdam, The Netherlands
- Department of Epidemiology and Data Science, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands
| | - Rik Ossenkoppele
- Amsterdam Neuroscience, Neurodegeneration, Amsterdam, The Netherlands.
- Clinical Memory Research Unit, Lund University, Lund, Sweden.
- Alzheimer Center Amsterdam, Department of Neurology, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc, Amsterdam, The Netherlands.
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135
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Yoo JH, Chong B, Barber PA, Stinear C, Wang A. Predicting Motor Outcomes Using Atlas-Based Voxel Features of Post-Stroke Neuroimaging: A Scoping Review. Neurorehabil Neural Repair 2023; 37:475-487. [PMID: 37191349 PMCID: PMC10350710 DOI: 10.1177/15459683231173668] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/17/2023]
Abstract
BACKGROUND Atlas-based voxel features have the potential to aid motor outcome prognostication after stroke, but are seldom used in clinically feasible prediction models. This could be because neuroimaging feature development is a non-standardized, complex, multistep process. This is a barrier to entry for researchers and poses issues for reproducibility and validation in a field of research where sample sizes are typically small. OBJECTIVES The primary aim of this review is to describe the methodologies currently used in motor outcome prediction studies using atlas-based voxel neuroimaging features. Another aim is to identify neuroanatomical regions commonly used for motor outcome prediction. METHODS A Preferred Reporting Items for Systematic Reviews and Meta-Analyses protocol was constructed and OVID Medline and Scopus databases were searched for relevant studies. The studies were then screened and details about imaging modality, image acquisition, image normalization, lesion segmentation, region of interest determination, and imaging measures were extracted. RESULTS Seventeen studies were included and examined. Common limitations were a lack of detailed reporting on image acquisition and the specific brain templates used for normalization and a lack of clear reasoning behind the atlas or imaging measure selection. A wide variety of sensorimotor regions relate to motor outcomes and there is no consensus use of one single sensorimotor atlas for motor outcome prediction. CONCLUSION There is an ongoing need to validate imaging predictors and further improve methodological techniques and reporting standards in neuroimaging feature development for motor outcome prediction post-stroke.
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Affiliation(s)
- Ji-Hun Yoo
- Auckland Bioengineering Institute, The University of Auckland, Auckland, New Zealand
| | - Benjamin Chong
- Auckland Bioengineering Institute, The University of Auckland, Auckland, New Zealand
- Department of Medicine, The University of Auckland, Auckland, New Zealand
- Centre for Brain Research, The University of Auckland, Auckland, New Zealand
| | - Peter Alan Barber
- Department of Medicine, The University of Auckland, Auckland, New Zealand
- Centre for Brain Research, The University of Auckland, Auckland, New Zealand
| | - Cathy Stinear
- Department of Medicine, The University of Auckland, Auckland, New Zealand
| | - Alan Wang
- Auckland Bioengineering Institute, The University of Auckland, Auckland, New Zealand
- Department of Medicine, The University of Auckland, Auckland, New Zealand
- Centre for Brain Research, The University of Auckland, Auckland, New Zealand
- Centre for Medical Imaging, The University of Auckland, Auckland, New Zealand
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Tsagkaris S, Yau EKC, McClelland V, Papandreou A, Siddiqui A, Lumsden DE, Kaminska M, Guedj E, Hammers A, Lin JP. Metabolic patterns in brain 18F-fluorodeoxyglucose PET relate to aetiology in paediatric dystonia. Brain 2023; 146:2512-2523. [PMID: 36445406 PMCID: PMC10232264 DOI: 10.1093/brain/awac439] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/25/2022] [Revised: 10/24/2022] [Accepted: 11/08/2022] [Indexed: 12/09/2023] Open
Abstract
There is a lack of imaging markers revealing the functional characteristics of different brain regions in paediatric dystonia. In this observational study, we assessed the utility of [18F]2-fluoro-2-deoxy-D-glucose (FDG)-PET in understanding dystonia pathophysiology by revealing specific resting awake brain glucose metabolism patterns in different childhood dystonia subgroups. PET scans from 267 children with dystonia being evaluated for possible deep brain stimulation surgery between September 2007 and February 2018 at Evelina London Children's Hospital (ELCH), UK, were examined. Scans without gross anatomical abnormality (e.g. large cysts, significant ventriculomegaly; n = 240) were analysed with Statistical Parametric Mapping (SPM12). Glucose metabolism patterns were examined in the 144/240 (60%) cases with the 10 commonest childhood-onset dystonias, focusing on nine anatomical regions. A group of 39 adult controls was used for comparisons. The genetic dystonias were associated with the following genes: TOR1A, THAP1, SGCE, KMT2B, HPRT1 (Lesch Nyhan disease), PANK2 and GCDH (Glutaric Aciduria type 1). The acquired cerebral palsy (CP) cases were divided into those related to prematurity (CP-Preterm), neonatal jaundice/kernicterus (CP-Kernicterus) and hypoxic-ischaemic encephalopathy (CP-Term). Each dystonia subgroup had distinct patterns of altered FDG-PET uptake. Focal glucose hypometabolism of the pallidi, putamina or both, was the commonest finding, except in PANK2, where basal ganglia metabolism appeared normal. HPRT1 uniquely showed glucose hypometabolism across all nine cerebral regions. Temporal lobe glucose hypometabolism was found in KMT2B, HPRT1 and CP-Kernicterus. Frontal lobe hypometabolism was found in SGCE, HPRT1 and PANK2. Thalamic and brainstem hypometabolism were seen only in HPRT1, CP-Preterm and CP-term dystonia cases. The combination of frontal and parietal lobe hypermetabolism was uniquely found in CP-term cases. PANK2 cases showed a distinct combination of parietal hypermetabolism with cerebellar hypometabolism but intact putaminal-pallidal glucose metabolism. HPRT1, PANK2, CP-kernicterus and CP-preterm cases had cerebellar and insula glucose hypometabolism as well as parietal glucose hypermetabolism. The study findings offer insights into the pathophysiology of dystonia and support the network theory for dystonia pathogenesis. 'Signature' patterns for each dystonia subgroup could be a useful biomarker to guide differential diagnosis and inform personalized management strategies.
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Affiliation(s)
- Stavros Tsagkaris
- Children’s Neurosciences, Complex Motor Disorders Service (CMDS), Evelina London Children's Hospital, Guy's and St Thomas’ NHS Foundation Trust (GSTT), London SE1 7EH, UK
- King’s College London & Guy’s and St Thomas’ PET Centre, Division of Biomedical Engineering and Imaging Sciences, King’s College London, London SE1 7EH, UK
| | - Eric K C Yau
- Department of Paediatrics & Adolescent Medicine, Princess Margaret Hospital, Kowloon, Hong Kong
| | - Verity McClelland
- Children’s Neurosciences, Complex Motor Disorders Service (CMDS), Evelina London Children's Hospital, Guy's and St Thomas’ NHS Foundation Trust (GSTT), London SE1 7EH, UK
- Department of Basic and Clinical Neuroscience, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London SE5 8AF, UK
| | - Apostolos Papandreou
- Children’s Neurosciences, Complex Motor Disorders Service (CMDS), Evelina London Children's Hospital, Guy's and St Thomas’ NHS Foundation Trust (GSTT), London SE1 7EH, UK
- Developmental Neurosciences, Zayed Centre for Research into Rare Disease in Children, University College London Great Ormond Street Institute of Child Health, London WC1N 1DZ, UK
| | - Ata Siddiqui
- Neuroradiology Department, Evelina London Children's Hospital, Guy's and St Thomas’ NHS Foundation Trust (GSTT), London SE1 7EH, UK
| | - Daniel E Lumsden
- Children’s Neurosciences, Complex Motor Disorders Service (CMDS), Evelina London Children's Hospital, Guy's and St Thomas’ NHS Foundation Trust (GSTT), London SE1 7EH, UK
- Perinatal Imaging, Division of Biomedical Engineering and Imaging Sciences, King’s College London, London SE1 7EH, UK
| | - Margaret Kaminska
- Children’s Neurosciences, Complex Motor Disorders Service (CMDS), Evelina London Children's Hospital, Guy's and St Thomas’ NHS Foundation Trust (GSTT), London SE1 7EH, UK
| | - Eric Guedj
- CERIMED, Nuclear Medicine Department, Aix Marseille Universite, APHM, CNRS, Centrale Marseille, Institut Fresnel, Timone Hospital, 13397 Marseille, France
| | - Alexander Hammers
- King’s College London & Guy’s and St Thomas’ PET Centre, Division of Biomedical Engineering and Imaging Sciences, King’s College London, London SE1 7EH, UK
| | - Jean-Pierre Lin
- Children’s Neurosciences, Complex Motor Disorders Service (CMDS), Evelina London Children's Hospital, Guy's and St Thomas’ NHS Foundation Trust (GSTT), London SE1 7EH, UK
- Women and Children’s Health Institute Faculty of Life Sciences & Medicine, Kings Health Partners, King’s College London, London SE1 7EH, UK
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137
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Sanaat A, Shooli H, Böhringer AS, Sadeghi M, Shiri I, Salimi Y, Ginovart N, Garibotto V, Arabi H, Zaidi H. A cycle-consistent adversarial network for brain PET partial volume correction without prior anatomical information. Eur J Nucl Med Mol Imaging 2023; 50:1881-1896. [PMID: 36808000 PMCID: PMC10199868 DOI: 10.1007/s00259-023-06152-0] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/25/2022] [Accepted: 02/12/2023] [Indexed: 02/23/2023]
Abstract
PURPOSE Partial volume effect (PVE) is a consequence of the limited spatial resolution of PET scanners. PVE can cause the intensity values of a particular voxel to be underestimated or overestimated due to the effect of surrounding tracer uptake. We propose a novel partial volume correction (PVC) technique to overcome the adverse effects of PVE on PET images. METHODS Two hundred and twelve clinical brain PET scans, including 50 18F-Fluorodeoxyglucose (18F-FDG), 50 18F-Flortaucipir, 36 18F-Flutemetamol, and 76 18F-FluoroDOPA, and their corresponding T1-weighted MR images were enrolled in this study. The Iterative Yang technique was used for PVC as a reference or surrogate of the ground truth for evaluation. A cycle-consistent adversarial network (CycleGAN) was trained to directly map non-PVC PET images to PVC PET images. Quantitative analysis using various metrics, including structural similarity index (SSIM), root mean squared error (RMSE), and peak signal-to-noise ratio (PSNR), was performed. Furthermore, voxel-wise and region-wise-based correlations of activity concentration between the predicted and reference images were evaluated through joint histogram and Bland and Altman analysis. In addition, radiomic analysis was performed by calculating 20 radiomic features within 83 brain regions. Finally, a voxel-wise two-sample t-test was used to compare the predicted PVC PET images with reference PVC images for each radiotracer. RESULTS The Bland and Altman analysis showed the largest and smallest variance for 18F-FDG (95% CI: - 0.29, + 0.33 SUV, mean = 0.02 SUV) and 18F-Flutemetamol (95% CI: - 0.26, + 0.24 SUV, mean = - 0.01 SUV), respectively. The PSNR was lowest (29.64 ± 1.13 dB) for 18F-FDG and highest (36.01 ± 3.26 dB) for 18F-Flutemetamol. The smallest and largest SSIM were achieved for 18F-FDG (0.93 ± 0.01) and 18F-Flutemetamol (0.97 ± 0.01), respectively. The average relative error for the kurtosis radiomic feature was 3.32%, 9.39%, 4.17%, and 4.55%, while it was 4.74%, 8.80%, 7.27%, and 6.81% for NGLDM_contrast feature for 18F-Flutemetamol, 18F-FluoroDOPA, 18F-FDG, and 18F-Flortaucipir, respectively. CONCLUSION An end-to-end CycleGAN PVC method was developed and evaluated. Our model generates PVC images from the original non-PVC PET images without requiring additional anatomical information, such as MRI or CT. Our model eliminates the need for accurate registration or segmentation or PET scanner system response characterization. In addition, no assumptions regarding anatomical structure size, homogeneity, boundary, or background level are required.
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Affiliation(s)
- Amirhossein Sanaat
- Division of Nuclear Medicine and Molecular Imaging, Geneva University Hospital, CH-1211, Geneva, Switzerland
| | - Hossein Shooli
- Persian Gulf Nuclear Medicine Research Center, Department of Molecular Imaging and Radionuclide Therapy (MIRT), Bushehr Medical University Hospital, Faculty of Medicine, Bushehr University of Medical Sciences, Bushehr, Iran
| | - Andrew Stephen Böhringer
- Division of Nuclear Medicine and Molecular Imaging, Geneva University Hospital, CH-1211, Geneva, Switzerland
| | - Maryam Sadeghi
- Department of Medical Statistics, Informatics and Health Economics, Medical University of Innsbruck, Schoepfstr. 41, Innsbruck, Austria
| | - Isaac Shiri
- Division of Nuclear Medicine and Molecular Imaging, Geneva University Hospital, CH-1211, Geneva, Switzerland
| | - Yazdan Salimi
- Division of Nuclear Medicine and Molecular Imaging, Geneva University Hospital, CH-1211, Geneva, Switzerland
| | - Nathalie Ginovart
- Geneva University Neurocenter, University of Geneva, Geneva, Switzerland
- Department of Psychiatry, Geneva University, Geneva, Switzerland
- Department of Basic Neuroscience, Geneva University, Geneva, Switzerland
| | - Valentina Garibotto
- Division of Nuclear Medicine and Molecular Imaging, Geneva University Hospital, CH-1211, Geneva, Switzerland
- Geneva University Neurocenter, University of Geneva, Geneva, Switzerland
| | - Hossein Arabi
- Division of Nuclear Medicine and Molecular Imaging, Geneva University Hospital, CH-1211, Geneva, Switzerland
| | - Habib Zaidi
- Division of Nuclear Medicine and Molecular Imaging, Geneva University Hospital, CH-1211, Geneva, Switzerland.
- Geneva University Neurocenter, University of Geneva, Geneva, Switzerland.
- Department of Nuclear Medicine and Molecular Imaging, University of Groningen, Groningen, Netherlands.
- Department of Nuclear Medicine, University of Southern Denmark, Odense, Denmark.
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Green MA, Crawford JL, Kuhnen CM, Samanez-Larkin GR, Seaman KL. Multivariate associations between dopamine receptor availability and risky investment decision-making across adulthood. Cereb Cortex Commun 2023; 4:tgad008. [PMID: 37255569 PMCID: PMC10225308 DOI: 10.1093/texcom/tgad008] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/08/2023] [Revised: 05/08/2023] [Accepted: 05/10/2023] [Indexed: 06/01/2023] Open
Abstract
Enhancing dopamine increases financial risk taking across adulthood but it is unclear whether baseline individual differences in dopamine function are related to risky financial decisions. Here, thirty-five healthy adults completed an incentive-compatible risky investment decision task and a PET scan at rest using [11C]FLB457 to assess dopamine D2-like receptor availability. Participants made choices between a safe asset (bond) and a risky asset (stock) with either an expected value less than the bond ("bad stock") or expected value greater than the bond ("good stock"). Five measures of behavior (choice inflexibility, risk seeking, suboptimal investment) and beliefs (absolute error, optimism) were computed and D2-like binding potential was extracted from four brain regions of interest (midbrain, amygdala, anterior cingulate, insula). We used canonical correlation analysis to evaluate multivariate associations between decision-making and dopamine function controlling for age. Decomposition of the first dimension (r = 0.76) revealed that the strongest associations were between measures of choice inflexibility, incorrect choice, optimism, amygdala binding potential, and age. Follow-up univariate analyses revealed that amygdala binding potential and age were both independently associated with choice inflexibility. The findings suggest that individual differences in dopamine function may be associated with financial risk taking in healthy adults.
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Affiliation(s)
- Mikella A Green
- Department of Psychology & Neuroscience, 417 Chapel Dr, Durham, NC 27708, Center for Cognitive Neuroscience, Duke University, 308 Research Drive, Durham, NC 27708
| | - Jennifer L Crawford
- Department of Psychology, Brandeis University, 415 South Street, Waltham, MA 02453
| | - Camelia M Kuhnen
- UNC Kenan-Flagler Business School, 300 Kenan Center Drive, Chapel Hill, NC 27599, National Bureau of Economic Research, 1050 Massachusetts Avenue, Cambridge, MA 02138
| | - Gregory R Samanez-Larkin
- Department of Psychology & Neuroscience, 417 Chapel Dr, Durham, NC 27708, Center for Cognitive Neuroscience, Duke University, 308 Research Drive, Durham, NC 27708
| | - Kendra L Seaman
- Department of Psychology, University of Texas at Dallas, 800 W Campbell Road, Richardson, TX 75080-3021, Center for Vital Longevity, University of Texas at Dallas, 1600 Viceroy Drive, Suite 800, Dallas, TX 75235
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139
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Laurencin C, Lancelot S, Merida I, Costes N, Redouté J, Le Bars D, Boulinguez P, Ballanger B. Distribution of α 2-Adrenergic Receptors in the Living Human Brain Using [ 11C]yohimbine PET. Biomolecules 2023; 13:biom13050843. [PMID: 37238713 DOI: 10.3390/biom13050843] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/27/2023] [Revised: 05/12/2023] [Accepted: 05/12/2023] [Indexed: 05/28/2023] Open
Abstract
The neurofunctional basis of the noradrenergic (NA) system and its associated disorders is still very incomplete because in vivo imaging tools in humans have been missing up to now. Here, for the first time, we use [11C]yohimbine in a large sample of subjects (46 healthy volunteers, 23 females, 23 males; aged 20-50) to perform direct quantification of regional alpha 2 adrenergic receptors' (α2-ARs) availability in the living human brain. The global map shows the highest [11C]yohimbine binding in the hippocampus, the occipital lobe, the cingulate gyrus, and the frontal lobe. Moderate binding was found in the parietal lobe, thalamus, parahippocampus, insula, and temporal lobe. Low levels of binding were found in the basal ganglia, the amygdala, the cerebellum, and the raphe nucleus. Parcellation of the brain into anatomical subregions revealed important variations in [11C]yohimbine binding within most structures. Strong heterogeneity was found in the occipital lobe, the frontal lobe, and the basal ganglia, with substantial gender effects. Mapping the distribution of α2-ARs in the living human brain may prove useful not only for understanding the role of the NA system in many brain functions, but also for understanding neurodegenerative diseases in which altered NA transmission with specific loss of α2-ARs is suspected.
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Affiliation(s)
- Chloé Laurencin
- Université de Lyon, 69622 Lyon, France
- Université Claude Bernard Lyon 1, 69100 Villeurbanne, France
- INSERM U1028, Lyon Neuroscience Research Center (CRNL), 69000 Lyon, France
- CNRS UMR5292, Lyon Neuroscience Research Center (CRNL), 69000 Lyon, France
- Hôpital Neurologique Pierre Wertheimer, Service de Neurologie C, Centre Expert Parkinson, Hospices Civils de Lyon, 69677 Bron, France
| | - Sophie Lancelot
- Université de Lyon, 69622 Lyon, France
- Université Claude Bernard Lyon 1, 69100 Villeurbanne, France
- INSERM U1028, Lyon Neuroscience Research Center (CRNL), 69000 Lyon, France
- CNRS UMR5292, Lyon Neuroscience Research Center (CRNL), 69000 Lyon, France
- CERMEP-Imagerie du Vivant, 69500 Bron, France
- Hospices Civils de Lyon, 69677 Bron, France
| | - Inès Merida
- CERMEP-Imagerie du Vivant, 69500 Bron, France
| | | | | | - Didier Le Bars
- CERMEP-Imagerie du Vivant, 69500 Bron, France
- Hospices Civils de Lyon, 69677 Bron, France
| | - Philippe Boulinguez
- Université de Lyon, 69622 Lyon, France
- Université Claude Bernard Lyon 1, 69100 Villeurbanne, France
- INSERM U1028, Lyon Neuroscience Research Center (CRNL), 69000 Lyon, France
- CNRS UMR5292, Lyon Neuroscience Research Center (CRNL), 69000 Lyon, France
| | - Bénédicte Ballanger
- Université de Lyon, 69622 Lyon, France
- Université Claude Bernard Lyon 1, 69100 Villeurbanne, France
- INSERM U1028, Lyon Neuroscience Research Center (CRNL), 69000 Lyon, France
- CNRS UMR5292, Lyon Neuroscience Research Center (CRNL), 69000 Lyon, France
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140
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Tada T, Hara K, Fujita N, Ito Y, Yamaguchi H, Ohdake R, Kawabata K, Ogura A, Kato T, Yokoi T, Masuda M, Abe S, Miyao S, Naganawa S, Katsuno M, Watanabe H, Sobue G, Kato K. Comparative examination of the pons and corpus callosum as reference regions for quantitative evaluation in positron emission tomography imaging for Alzheimer's disease using 11C-Pittsburgh Compound-B. Ann Nucl Med 2023:10.1007/s12149-023-01843-y. [PMID: 37160863 DOI: 10.1007/s12149-023-01843-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/18/2022] [Accepted: 04/24/2023] [Indexed: 05/11/2023]
Abstract
OBJECTIVES Standardised uptake value ratio (SUVR) is usually obtained by dividing the SUV of the region of interest (ROI) by that of the cerebellar cortex. Cerebellar cortex is not a valid reference in cases where amyloid β deposition or lesions are present. Only few studies have evaluated the use of other regions as references. We compared the validity of the pons and corpus callosum as reference regions for the quantitative evaluation of brain positron emission tomography (PET) using 11C-PiB compared to the cerebellar cortex. METHODS We retrospectively evaluated data from 86 subjects with or without Alzheimer's disease (AD). All subjects underwent magnetic resonance imaging, PET imaging, and cognitive function testing. For the quantitative analysis, three-dimensional ROIs were automatically placed, and SUV and SUVR were obtained. We compared these values between AD and healthy control (HC) groups. RESULTS SUVR data obtained using the pons and corpus callosum as reference regions strongly correlated with that using the cerebellar cortex. The sensitivity and specificity were high when either the pons or corpus callosum was used as the reference region. However, the SUV values of the corpus callosum were different between AD and HC (p < 0.01). CONCLUSIONS Our data suggest that the pons and corpus callosum might be valid reference regions.
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Affiliation(s)
- Tomohiro Tada
- Department of Radiological Technology, Nagoya University Hospital, 65 Tsurumai-Cho, Showa-Ku, Nagoya, 466-8560, Japan
| | - Kazuhiro Hara
- Department of Neurology, Nagoya University Graduate School of Medicine, 65 Tsurumai-Cho, Showa-Ku, Nagoya, 466-8550, Japan
| | - Naotoshi Fujita
- Department of Radiological Technology, Nagoya University Hospital, 65 Tsurumai-Cho, Showa-Ku, Nagoya, 466-8560, Japan
| | - Yoshinori Ito
- Department of Radiological and Medical Laboratory Sciences, Nagoya University Graduate School of Medicine, 1-1-20 Daiko-Minami, Higashi-Ku, Nagoya, 461-8673, Japan
| | - Hiroshi Yamaguchi
- Nagoya University Radioisotope Research Center Medical Branch, 65 Tsurumai-Cho, Showa-Ku, Nagoya, 466-8550, Japan
| | - Reiko Ohdake
- Department of Neurology, Fujita Health University School of Medicine, 1-98 Dengakugakubo, Kutsukake-Cho, Toyoake, Aichi, 470-1192, Japan
| | - Kazuya Kawabata
- Department of Neurology, Nagoya University Graduate School of Medicine, 65 Tsurumai-Cho, Showa-Ku, Nagoya, 466-8550, Japan
- Department of Neurology, Medical University of Innsbruck, Innrain 52, 6020, Innsbruck, Austria
| | - Aya Ogura
- Department of Neurology, Nagoya University Graduate School of Medicine, 65 Tsurumai-Cho, Showa-Ku, Nagoya, 466-8550, Japan
| | - Toshiyasu Kato
- Department of Neurology, Nagoya University Graduate School of Medicine, 65 Tsurumai-Cho, Showa-Ku, Nagoya, 466-8550, Japan
- Department of Neurology, Anjo Kosei Hospital, 28 Higashihirokute Anjo-Cho, Anjo, 446-8602, Japan
| | - Takamasa Yokoi
- Department of Neurology, Toyohashi Municipal Hospital, 50 Hachikennishi, Aotake-Cho, Toyohashi, 441-8570, Japan
| | - Michihito Masuda
- Department of Neurology, Nagoya University Graduate School of Medicine, 65 Tsurumai-Cho, Showa-Ku, Nagoya, 466-8550, Japan
- Department of Neurology, Okazaki City Hospital, 1-3 Gosyoai, Kouryuji-Cho, Okazaki, 444-8553, Japan
| | - Shinji Abe
- Department of Radiological Technology, Nagoya University Hospital, 65 Tsurumai-Cho, Showa-Ku, Nagoya, 466-8560, Japan
| | - Shinichi Miyao
- Department of Neurology, Meitetsu Hospital, 2-26-11 Sakou, Nishiku, Nagoya, Japan
| | - Shinji Naganawa
- Department of Radiology, Nagoya University Graduate School of Medicine, 65 Tsurumai-Cho, Showa-Ku, Nagoya, 466-8560, Japan
| | - Masahisa Katsuno
- Department of Neurology, Nagoya University Graduate School of Medicine, 65 Tsurumai-Cho, Showa-Ku, Nagoya, 466-8550, Japan
- Department of Clinical Research Education, Nagoya University Graduate School of Medicine, 65 Tsurumai-Cho, Showa-Ku, Nagoya, 466-8560, Japan
| | - Hirohisa Watanabe
- Department of Neurology, Fujita Health University School of Medicine, 1-98 Dengakugakubo, Kutsukake-Cho, Toyoake, Aichi, 470-1192, Japan
| | - Gen Sobue
- Aichi Medical University, 1-1 Yazakokarimata, Nagakute, Japan
| | - Katsuhiko Kato
- Functional Medical Imaging, Biomedical Imaging Sciences, Division of Advanced Information Health Sciences, Department of Integrated Health Sciences, Nagoya University Graduate School of Medicine, 1-1-20 Daiko-Minami, Higashi-Ku, Nagoya, 461-8673, Japan.
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Teipel S, Grothe MJ. MRI-based basal forebrain atrophy and volumetric signatures associated with limbic TDP-43 compared to Alzheimer's disease pathology. Neurobiol Dis 2023; 180:106070. [PMID: 36898615 DOI: 10.1016/j.nbd.2023.106070] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/04/2023] [Revised: 02/23/2023] [Accepted: 03/05/2023] [Indexed: 03/11/2023] Open
Abstract
BACKGROUND It is not clear to which degree limbic TDP-43 pathology associates with a cholinergic deficit in the absence of Alzheimer's disease (AD) pathology. OBJECTIVE Replicate and extend recent evidence on cholinergic basal forebrain atrophy in limbic TDP-43 and evaluate MRI based patterns of atrophy as a surrogate marker for TDP-43. METHODS We studied ante-mortem MRI data of 11 autopsy cases with limbic TDP-43 pathology, 47 cases with AD pathology, and 26 mixed AD/TDP-43 cases from the ADNI autopsy sample, and 17 TDP-43, 170 AD, and 58 mixed AD/TDP-43 cases from the NACC autopsy sample. Group differences in basal forebrain and other brain volumes of interest were assessed using Bayesian ANCOVA. We assessed the diagnostic utility of MRI based patterns of brain atrophy using voxel-based receiver operating characteristics and random forest analyses. RESULTS In the NACC sample, we found moderate evidence for the absence of a difference in basal forebrain volumes between AD, TDP-43, and mixed pathologies (Bayes factor(BF)10 = 0.324), and very strong evidence for lower hippocampus volume in TDP-43 and mixed cases compared with AD cases (BF10 = 156.1). The ratio of temporal to hippocampus volume reached an AUC of 75% for separating pure TDP-43 from pure AD cases. Random-forest analysis between TDP-43, AD, and mixed pathology reached only a multiclass AUC of 0.63 based on hippocampus, middle-inferior temporal gyrus, and amygdala volumes. Findings in the ADNI sample were consistent with these results. CONCLUSION A comparable degree of basal forebrain atrophy in pure TDP-43 cases compared to AD cases encourages studies on the effect of cholinergic treatment in amnestic dementia due to TDP-43. A distinct pattern of temporo-limbic brain atrophy may serve as a surrogate marker to enrich samples in clinical trials for the presence of TDP-43 pathology.
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Affiliation(s)
- Stefan Teipel
- Deutsches Zentrum für Neurodegenerative Erkrankungen (DZNE) Rostock/Greifswald, Rostock, Germany; Department of Psychosomatic Medicine, Rostock University Medical Center, Rostock, Germany.
| | - Michel J Grothe
- Unidad de Trastornos del Movimiento, Servicio de Neurología y Neurofisiología Clínica, Instituto de Biomedicina de Sevilla, Hospital Universitario Virgen del Rocío/CSIC/Universidad de Sevilla, Seville, Spain
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142
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Matsumoto Y, Nakae R, Sekine T, Kodani E, Warnock G, Igarashi Y, Tagami T, Murai Y, Suzuki K, Yokobori S. Rapidly progressive cerebral atrophy following a posterior cranial fossa stroke: Assessment with semiautomatic CT volumetry. Acta Neurochir (Wien) 2023; 165:1575-1584. [PMID: 37119319 DOI: 10.1007/s00701-023-05609-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/31/2023] [Accepted: 04/25/2023] [Indexed: 05/01/2023]
Abstract
BACKGROUND The effect of posterior cranial fossa stroke on changes in cerebral volume is not known. We assessed cerebral volume changes in patients with acute posterior fossa stroke using CT scans, and looked for risk factors for cerebral atrophy. METHODS Patients with cerebellar or brainstem hemorrhage/infarction admitted to the ICU, and who underwent at least two subsequent inpatient head CT scans during hospitalization were included (n = 60). The cerebral volume was estimated using an automatic segmentation method. Patients with cerebral volume reduction > 0% from the first to the last scan were defined as the "cerebral atrophy group (n = 47)," and those with ≤ 0% were defined as the "no cerebral atrophy group (n = 13)." RESULTS The cerebral atrophy group showed a significant decrease in cerebral volume (first CT scan: 0.974 ± 0.109 L vs. last CT scan: 0.927 ± 0.104 L, P < 0.001). The mean percentage change in cerebral volume between CT scans in the cerebral atrophy group was -4.7%, equivalent to a cerebral volume of 46.8 cm3, over a median of 17 days. The proportions of cases with a history of hypertension, diabetes mellitus, and median time on mechanical ventilation were significantly higher in the cerebral atrophy group than in the no cerebral atrophy group. CONCLUSIONS Many ICU patients with posterior cranial fossa stroke showed signs of cerebral atrophy. Those with rapidly progressive cerebral atrophy were more likely to have a history of hypertension or diabetes mellitus and required prolonged ventilation.
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Affiliation(s)
- Yoshiyuki Matsumoto
- Department of Emergency and Critical Care Medicine, Nippon Medical School Hospital, 1-1-5, Sendagi, Bunkyo-Ku, Tokyo, 113-8603, Japan
| | - Ryuta Nakae
- Department of Emergency and Critical Care Medicine, Nippon Medical School Hospital, 1-1-5, Sendagi, Bunkyo-Ku, Tokyo, 113-8603, Japan.
| | - Tetsuro Sekine
- Department of Radiology, Nippon Medical School Musashi Kosugi Hospital, Kanagawa, Japan
| | - Eigo Kodani
- Department of Radiology, Nippon Medical School Musashi Kosugi Hospital, Kanagawa, Japan
| | | | - Yutaka Igarashi
- Department of Emergency and Critical Care Medicine, Nippon Medical School Hospital, 1-1-5, Sendagi, Bunkyo-Ku, Tokyo, 113-8603, Japan
| | - Takashi Tagami
- Department of Emergency and Critical Care Medicine, Nippon Medical School Musashi Kosugi Hospital, Kanagawa, Japan
| | - Yasuo Murai
- Department of Neurological Surgery, Nippon Medical School Hospital, Tokyo, Japan
| | - Kensuke Suzuki
- Department of Neurosurgery, Dokkyo Medical University Saitama Medical Center, Saitama, Japan
| | - Shoji Yokobori
- Department of Emergency and Critical Care Medicine, Nippon Medical School Hospital, 1-1-5, Sendagi, Bunkyo-Ku, Tokyo, 113-8603, Japan
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143
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Segobin S, Ambler M, Laniepce A, Platel H, Chételat G, Groussard M, Pitel AL. Korsakoff's Syndrome and Alzheimer's Disease-Commonalities and Specificities of Volumetric Brain Alterations within Papez Circuit. J Clin Med 2023; 12:jcm12093147. [PMID: 37176588 PMCID: PMC10179200 DOI: 10.3390/jcm12093147] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/10/2023] [Revised: 04/11/2023] [Accepted: 04/18/2023] [Indexed: 05/15/2023] Open
Abstract
Background: Alzheimer's disease (AD) and Korsakoff's syndrome (KS) are two major neurocognitive disorders characterized by amnesia but AD is degenerative while KS is not. The objective is to compare regional volume deficits within the Papez circuit in AD and KS, considering AD progression. Methods: 18 KS patients, 40 AD patients (20 with Moderate AD (MAD) matched on global cognitive deficits with KS patients and 20 with Severe AD (SAD)), and 70 healthy controls underwent structural MRI. Volumes of the hippocampi, thalami, cingulate gyri, mammillary bodies (MB) and mammillothalamic tracts (MTT) were extracted. Results: For the cingulate gyri, and anterior thalamic nuclei, all patient groups were affected compared to controls but did not differ between each other. Smaller volumes were observed in all patient groups compared to controls in the mediodorsal thalamic nuclei and MB, but these regions were more severely damaged in KS than AD. MTT volumes were damaged in KS only. Hippocampi were affected in all patient groups but more severely in the SAD than in the KS and MAD. Conclusions: There are commonalities in the pattern of volume deficits in KS and AD within the Papez circuit with the anterior thalamic nuclei, cingulate cortex and hippocampus (in MAD only) being damaged to the same extent. The specificity of KS relies on the alteration of the MTT and the severity of the MB shrinkage. Further comparative studies including other imaging modalities and a neuropsychological assessment are required.
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Affiliation(s)
- Shailendra Segobin
- Normandie Univ, UNICAEN, PSL Université Paris, EPHE, INSERM, U1077, CHU de Caen, Cyceron, Neuropsychologie et Imagerie de la Mémoire Humaine (NIMH), 14000 Caen, France
| | - Melanie Ambler
- Normandie Univ, UNICAEN, PSL Université Paris, EPHE, INSERM, U1077, CHU de Caen, Cyceron, Neuropsychologie et Imagerie de la Mémoire Humaine (NIMH), 14000 Caen, France
| | - Alice Laniepce
- Normandie Univ, UNICAEN, PSL Université Paris, EPHE, INSERM, U1077, CHU de Caen, Cyceron, Neuropsychologie et Imagerie de la Mémoire Humaine (NIMH), 14000 Caen, France
- Normandie Univ, UNIROUEN, CRFDP (EA 7475), 76821 Rouen, France
- Normandie Univ, UNICAEN, INSERM, PhIND "Physiopathology and Imaging of Neurological Disorders", Institut Blood and Brain @ Caen-Normandie, Cyceron, 14000 Caen, France
| | - Hervé Platel
- Normandie Univ, UNICAEN, PSL Université Paris, EPHE, INSERM, U1077, CHU de Caen, Cyceron, Neuropsychologie et Imagerie de la Mémoire Humaine (NIMH), 14000 Caen, France
| | - Gael Chételat
- Normandie Univ, UNICAEN, INSERM, PhIND "Physiopathology and Imaging of Neurological Disorders", Institut Blood and Brain @ Caen-Normandie, Cyceron, 14000 Caen, France
| | - Mathilde Groussard
- Normandie Univ, UNICAEN, PSL Université Paris, EPHE, INSERM, U1077, CHU de Caen, Cyceron, Neuropsychologie et Imagerie de la Mémoire Humaine (NIMH), 14000 Caen, France
| | - Anne-Lise Pitel
- Normandie Univ, UNICAEN, INSERM, PhIND "Physiopathology and Imaging of Neurological Disorders", Institut Blood and Brain @ Caen-Normandie, Cyceron, 14000 Caen, France
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Morrison C, Dadar M, Kamal F, Collins DL. Differences in AD-related pathology profiles across APOE groups. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2023:2023.04.25.23289108. [PMID: 37162910 PMCID: PMC10168520 DOI: 10.1101/2023.04.25.23289108] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/11/2023]
Abstract
BACKGROUND The apolipoprotein (APOE) e4 allele is a known risk factor for Alzheimer's disease (AD), while the e2 allele is thought to be protective against AD. Few studies have examined the relationship between brain pathologies, atrophy, and white matter hyperintensities (WMHs) and APOE status in those with the e2e4 genotype and results are inconsistent for those with an e2 allele. METHODS We analyzed Alzheimer's Disease Neuroimaging participants that had APOE genotyping and at least one of the following metrics: regional WMH load, ventricle size, hippocampal (HC) and entorhinal cortex (EC) volume, amyloid level (i.e., AV-45), and phosphorylated tau (pTau). Participants were divided into one of four APOE allele profiles (E4=e4e4 or e3e4; E2=e2e2 or e2e3; E3=e3e3; or E24=e2e4, Fig.1). Linear mixed models examined the relationship between APOE profiles and each pathology (i.e., regional WMHs, ventricle size, hippocampal and entorhinal cortex volume, amyloid level, and phosphorylated tau measures). while controlling for age, sex, education, and diagnostic status at baseline and over time. RESULTS APOE ε4 is associated with increased pathology while ε2 positivity is associated with reduced baseline and lower accumulation of pathologies and rates of neurodegeneration. APOE ε2ε4 is similar to ε4 (increased neurodegeneration) but with a slower rate of change. CONCLUSIONS The strong associations observed between APOE and pathology in this study show the importance of how genetic factors influence structural brain changes. These findings suggest that ε2ε4 genotype is related to increased declines associated with the ε4 as opposed to the protective effects of the ε2. These findings have important implications for initiating treatments and interventions. Given that people who have the ε2ε4 genotype can expect to have increased atrophy, they must be included (alongside those with an ε4 profile) in targeted interventions to reduce brain changes that occur with AD.
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145
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Park S, Hong CH, Lee DG, Park K, Shin H. Prospective classification of Alzheimer's disease conversion from mild cognitive impairment. Neural Netw 2023; 164:335-344. [PMID: 37163849 DOI: 10.1016/j.neunet.2023.04.018] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/03/2022] [Revised: 02/26/2023] [Accepted: 04/12/2023] [Indexed: 05/12/2023]
Abstract
Alzheimer's disease (AD) is emerging as a serious problem with the rapid aging of the population, but due to the unclear cause of the disease and the absence of therapy, appropriate preventive measures are the next best thing. For this reason, it is important to early detect whether the disease converts from mild cognitive impairment (MCI) which is a prodromal phase of AD. With the advance in brain imaging techniques, various machine learning algorithms have become able to predict the conversion from MCI to AD by learning brain atrophy patterns. However, at the time of diagnosis, it is difficult to distinguish between the conversion group and the non-conversion group of subjects because the difference between groups is small, but the within-group variability is large in brain images. After a certain period of time, the subjects of conversion group show significant brain atrophy, whereas subjects of non-conversion group show only subtle changes due to the normal aging effect. This difference on brain atrophy makes the brain images more discriminative for learning. Motivated by this, we propose a method to perform classification by projecting brain images into the future, namely prospective classification. The experiments on the Alzheimer's Disease Neuroimaging Initiative dataset show that the prospective classification outperforms ordinary classification. Moreover, the features of prospective classification indicate the brain regions that significantly influence the conversion from MCI to AD.
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Affiliation(s)
- Sunghong Park
- Department of Psychiatry, Ajou University School of Medicine, Suwon, 16499, Republic of Korea
| | - Chang Hyung Hong
- Department of Psychiatry, Ajou University School of Medicine, Suwon, 16499, Republic of Korea
| | - Dong-Gi Lee
- Department of Biostatistics, Epidemiology & Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA
| | - Kanghee Park
- Korea Institute of Science and Technology Information, Seoul, 02456, Republic of Korea
| | - Hyunjung Shin
- Department of Artificial Intelligence, Ajou University, Suwon, 16499, Republic of Korea; Department of Industrial Engineering, Ajou University, Suwon, 16499, Republic of Korea.
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146
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Deters JR, Fietsam AC, Gander PE, Boles Ponto LL, Rudroff T. Effect of Post-COVID-19 on Brain Volume and Glucose Metabolism: Influence of Time Since Infection and Fatigue Status. Brain Sci 2023; 13:brainsci13040675. [PMID: 37190640 DOI: 10.3390/brainsci13040675] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/09/2023] [Revised: 03/23/2023] [Accepted: 04/15/2023] [Indexed: 05/17/2023] Open
Abstract
Post-COVID-19 syndrome (PCS) fatigue is typically most severe <6 months post-infection. Combining magnetic resonance imaging (MRI) and positron emission tomography (PET) imaging with the glucose analog [18F]-Fluorodeoxyglucose (FDG) provides a comprehensive overview of the effects of PCS on regional brain volumes and metabolism, respectively. The primary purpose of this exploratory study was to investigate differences in MRI/PET outcomes between people < 6 months (N = 18, 11 female) and > 6 months (N = 15, 6 female) after COVID-19. The secondary purpose was to assess if any differences in MRI/PET outcomes were associated with fatigue symptoms. Subjects > 6 months showed smaller volumes in the putamen, pallidum, and thalamus compared to subjects < 6 months. In subjects > 6 months, fatigued subjects had smaller volumes in frontal areas compared to non-fatigued subjects. Moreover, worse fatigue was associated with smaller volumes in several frontal areas in subjects > 6 months. The results revealed no brain metabolism differences between subjects > 6 and < 6 months. However, both groups exhibited both regional hypo- and hypermetabolism compared to a normative database. These results suggest that PCS may alter regional brain volumes but not metabolism in people > 6 months, particularly those experiencing fatigue symptoms.
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Affiliation(s)
- Justin R Deters
- Department of Health and Human Physiology, University of Iowa, Iowa City, IA 52242, USA
| | - Alexandra C Fietsam
- Department of Health and Human Physiology, University of Iowa, Iowa City, IA 52242, USA
| | - Phillip E Gander
- Department of Radiology, University of Iowa Hospitals and Clinics, Iowa City, IA 52242, USA
| | - Laura L Boles Ponto
- Department of Radiology, University of Iowa Hospitals and Clinics, Iowa City, IA 52242, USA
| | - Thorsten Rudroff
- Department of Health and Human Physiology, University of Iowa, Iowa City, IA 52242, USA
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147
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Weaver NA, Mamdani MH, Lim JS, Biesbroek JM, Biessels GJ, Huenges Wajer IMC, Kang Y, Kim BJ, Lee BC, Lee KJ, Yu KH, Bae HJ, Bzdok D, Kuijf HJ. Disentangling poststroke cognitive deficits and their neuroanatomical correlates through combined multivariable and multioutcome lesion-symptom mapping. Hum Brain Mapp 2023; 44:2266-2278. [PMID: 36661231 PMCID: PMC10028652 DOI: 10.1002/hbm.26208] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/13/2022] [Revised: 12/21/2022] [Accepted: 01/04/2023] [Indexed: 01/21/2023] Open
Abstract
Studies in patients with brain lesions play a fundamental role in unraveling the brain's functional anatomy. Lesion-symptom mapping (LSM) techniques can relate lesion location to cognitive performance. However, a limitation of current LSM approaches is that they can only evaluate one cognitive outcome at a time, without considering interdependencies between different cognitive tests. To overcome this challenge, we implemented canonical correlation analysis (CCA) as combined multivariable and multioutcome LSM approach. We performed a proof-of-concept study on 1075 patients with acute ischemic stroke to explore whether addition of CCA to a multivariable single-outcome LSM approach (support vector regression) could identify infarct locations associated with deficits in three well-defined verbal memory functions (encoding, consolidation, retrieval) based on four verbal memory subscores derived from the Seoul Verbal Learning Test (immediate recall, delayed recall, recognition, learning ability). We evaluated whether CCA could extract cognitive score patterns that matched prior knowledge of these verbal memory functions, and if these patterns could be linked to more specific infarct locations than through single-outcome LSM alone. Two of the canonical modes identified with CCA showed distinct cognitive patterns that matched prior knowledge on encoding and consolidation. In addition, CCA revealed that each canonical mode was linked to a distinct infarct pattern, while with multivariable single-outcome LSM individual verbal memory subscores were associated with largely overlapping patterns. In conclusion, our findings demonstrate that CCA can complement single-outcome LSM techniques to help disentangle cognitive functions and their neuroanatomical correlates.
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Affiliation(s)
- Nick A Weaver
- Department of Neurology and Neurosurgery, UMC Utrecht Brain Center, Utrecht, The Netherlands
| | - Muhammad Hasnain Mamdani
- Department of Biomedical Engineering, Faculty of Medicine, McConnell Brain Imaging Centre, School of Computer Science, Montreal Neurological Institute (MNI), McGill University, Montreal, Canada
| | - Jae-Sung Lim
- Department of Neurology, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Republic of Korea
| | | | - Geert Jan Biessels
- Department of Neurology and Neurosurgery, UMC Utrecht Brain Center, Utrecht, The Netherlands
| | - Irene M C Huenges Wajer
- Department of Neurology and Neurosurgery, UMC Utrecht Brain Center, Utrecht, The Netherlands
- Experimental Psychology, Helmholtz Institute, Utrecht University, Utrecht, The Netherlands
| | - Yeonwook Kang
- Department of Neurology, Hallym University Sacred Heart Hospital, Hallym Neurological Institute, Hallym University College of Medicine, Anyang, Republic of Korea
- Department of Psychology, Hallym University, Chuncheon, Republic of Korea
| | - Beom Joon Kim
- Department of Neurology, Seoul National University Bundang Hospital, Seoul National University College of Medicine, Seongnam, Republic of Korea
| | - Byung-Chul Lee
- Department of Neurology, Hallym University Sacred Heart Hospital, Hallym Neurological Institute, Hallym University College of Medicine, Anyang, Republic of Korea
| | - Keon-Joo Lee
- Department of Neurology, Korea University Guro Hospital, Seoul, Republic of Korea
| | - Kyung-Ho Yu
- Department of Neurology, Hallym University Sacred Heart Hospital, Hallym Neurological Institute, Hallym University College of Medicine, Anyang, Republic of Korea
| | - Hee-Joon Bae
- Department of Neurology, Seoul National University Bundang Hospital, Seoul National University College of Medicine, Seongnam, Republic of Korea
| | - Danilo Bzdok
- Department of Biomedical Engineering, Faculty of Medicine, McConnell Brain Imaging Centre, School of Computer Science, Montreal Neurological Institute (MNI), McGill University, Montreal, Canada
- Mila-Quebec Artificial Intelligence Institute, Montreal, Canada
| | - Hugo J Kuijf
- Image Sciences Institute, University Medical Center Utrecht, Utrecht, The Netherlands
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Steinbart D, Yaakub SN, Steinbrenner M, Guldin LS, Holtkamp M, Keller SS, Weber B, Rüber T, Heckemann RA, Ilyas-Feldmann M, Hammers A. Automatic and manual segmentation of the piriform cortex: Method development and validation in patients with temporal lobe epilepsy and Alzheimer's disease. Hum Brain Mapp 2023; 44:3196-3209. [PMID: 37052063 PMCID: PMC10171523 DOI: 10.1002/hbm.26274] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/16/2022] [Revised: 02/10/2023] [Accepted: 02/24/2023] [Indexed: 04/14/2023] Open
Abstract
The piriform cortex (PC) is located at the junction of the temporal and frontal lobes. It is involved physiologically in olfaction as well as memory and plays an important role in epilepsy. Its study at scale is held back by the absence of automatic segmentation methods on MRI. We devised a manual segmentation protocol for PC volumes, integrated those manually derived images into the Hammers Atlas Database (n = 30) and used an extensively validated method (multi-atlas propagation with enhanced registration, MAPER) for automatic PC segmentation. We applied automated PC volumetry to patients with unilateral temporal lobe epilepsy with hippocampal sclerosis (TLE; n = 174 including n = 58 controls) and to the Alzheimer's Disease Neuroimaging Initiative cohort (ADNI; n = 151, of whom with mild cognitive impairment (MCI), n = 71; Alzheimer's disease (AD), n = 33; controls, n = 47). In controls, mean PC volume was 485 mm3 on the right and 461 mm3 on the left. Automatic and manual segmentations overlapped with a Jaccard coefficient (intersection/union) of ~0.5 and a mean absolute volume difference of ~22 mm3 in healthy controls, ~0.40/ ~28 mm3 in patients with TLE, and ~ 0.34/~29 mm3 in patients with AD. In patients with TLE, PC atrophy lateralised to the side of hippocampal sclerosis (p < .001). In patients with MCI and AD, PC volumes were lower than those of controls bilaterally (p < .001). Overall, we have validated automatic PC volumetry in healthy controls and two types of pathology. The novel finding of early atrophy of PC at the stage of MCI possibly adds a novel biomarker. PC volumetry can now be applied at scale.
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Affiliation(s)
- David Steinbart
- Charité - Universitätsmedizin Berlin, Freie Universität and Humboldt-Universität zu Berlin, Department of Neurology, Epilepsy-Center Berlin-Brandenburg, Berlin, Germany
- King's College London & Guy's and St Thomas' PET Centre, School of Biomedical Engineering and Imaging Sciences, St Thomas' Hospital, London, UK
| | - Siti N Yaakub
- King's College London & Guy's and St Thomas' PET Centre, School of Biomedical Engineering and Imaging Sciences, St Thomas' Hospital, London, UK
- School of Psychology, Faculty of Health, University of Plymouth, Plymouth, UK
| | - Mirja Steinbrenner
- Charité - Universitätsmedizin Berlin, Freie Universität and Humboldt-Universität zu Berlin, Department of Neurology, Epilepsy-Center Berlin-Brandenburg, Berlin, Germany
| | - Lynn S Guldin
- King's College London & Guy's and St Thomas' PET Centre, School of Biomedical Engineering and Imaging Sciences, St Thomas' Hospital, London, UK
| | - Martin Holtkamp
- Charité - Universitätsmedizin Berlin, Freie Universität and Humboldt-Universität zu Berlin, Department of Neurology, Epilepsy-Center Berlin-Brandenburg, Berlin, Germany
| | - Simon S Keller
- Department of Pharmacology and Therapeutics, Institute of Systems, Molecular and Integrative Biology, University of Liverpool, Liverpool, UK
- Department of Neuroradiology, The Walton Centre NHS Foundation Trust, Liverpool, UK
| | - Bernd Weber
- Center for Economics and Neuroscience, University of Bonn, Bonn, Germany
- Institute of Experimental Epileptology and Cognition Research, University Hospital Bonn, Bonn, Germany
| | - Theodor Rüber
- Institute of Experimental Epileptology and Cognition Research, University Hospital Bonn, Bonn, Germany
| | - Rolf A Heckemann
- Department of Medical Radiation Sciences, University of Gothenburg, Gothenburg, Sweden
| | - Maria Ilyas-Feldmann
- Charité - Universitätsmedizin Berlin, Freie Universität and Humboldt-Universität zu Berlin, Department of Neurology, Epilepsy-Center Berlin-Brandenburg, Berlin, Germany
| | - Alexander Hammers
- King's College London & Guy's and St Thomas' PET Centre, School of Biomedical Engineering and Imaging Sciences, St Thomas' Hospital, London, UK
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149
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Okkels N, Horsager J, Labrador-Espinosa MA, Hansen FO, Andersen KB, Just MK, Fedorova TD, Skjærbæk C, Munk OL, Hansen KV, Gottrup H, Hansen AK, Grothe MJ, Borghammer P. Distribution of cholinergic nerve terminals in the aged human brain measured with [ 18F]FEOBV PET and its correlation with histological data. Neuroimage 2023; 269:119908. [PMID: 36720436 DOI: 10.1016/j.neuroimage.2023.119908] [Citation(s) in RCA: 14] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/02/2022] [Revised: 01/10/2023] [Accepted: 01/27/2023] [Indexed: 01/30/2023] Open
Abstract
INTRODUCTION [18F]fluoroetoxybenzovesamicol ([18F]FEOBV) is a positron emission topography (PET) tracer for the vesicular acetylcholine transporter (VAChT), a protein located predominantly in synaptic vesicles in cholinergic nerve terminals. We aimed to use [18F]FEOBV PET to study the cholinergic topography of the healthy human brain. MATERIALS AND METHODS [18F]FEOBV PET brain data volumes of healthy elderly humans were normalized to standard space and intensity-normalized to the white matter. Stereotactic atlases of regions of interest were superimposed to describe and quantify tracer distribution. The spatial distribution of [18F]FEOBV PET uptake was compared with histological and gene expression data. RESULTS Twenty participants of both sexes and a mean age of 73.9 ± 6.0 years, age-range [64; 86], were recruited. Highest tracer binding was present in the striatum, some thalamic nuclei, and the basal forebrain. Intermediate binding was found in most nuclei of the brainstem, thalamus, and hypothalamus; the vermis and flocculonodular lobe; and the hippocampus, amygdala, insula, cingulate, olfactory cortex, and Heschl's gyrus. Lowest binding was present in most areas of the cerebral cortex, and in the cerebellar nuclei and hemispheres. The spatial distribution of tracer correlated with immunohistochemical post-mortem data, as well as with regional expression levels of SLC18A3, the VAChT coding gene. DISCUSSION Our in vivo findings confirm the regional cholinergic distribution in specific brain structures as described post-mortem. A positive spatial correlation between tracer distribution and regional gene expression levels further corroborates [18F]FEOBV PET as a validated tool for in vivo cholinergic imaging. The study represents an advancement in the continued efforts to delineate the spatial topography of the human cholinergic system in vivo.
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Affiliation(s)
- Niels Okkels
- Department of Nuclear Medicine and PET, Aarhus University Hospital, Aarhus, Denmark; Department of Clinical Medicine, Aarhus University, Aarhus, Denmark; Department of Neurology, Aarhus University Hospital, Aarhus, Denmark.
| | - Jacob Horsager
- Department of Nuclear Medicine and PET, Aarhus University Hospital, Aarhus, Denmark
| | - Miguel A Labrador-Espinosa
- Unidad de Trastornos del Movimiento, Servicio de Neurología y Neurofisiología Clínica, Instituto de Biomedicina de Sevilla (IBiS), Hospital Universitario Virgen del Rocío/CSIC/Universidad de Sevilla, Seville, Spain; Centro de Investigación Biomédica en Red Sobre Enfermedades Neurodegenerativas (CIBERNED), Instituto de Salud Carlos III, Madrid, Spain
| | - Frederik O Hansen
- Department of Nuclear Medicine and PET, Aarhus University Hospital, Aarhus, Denmark; Department of Clinical Medicine, Aarhus University, Aarhus, Denmark
| | - Katrine B Andersen
- Department of Nuclear Medicine and PET, Aarhus University Hospital, Aarhus, Denmark; Department of Clinical Medicine, Aarhus University, Aarhus, Denmark
| | - Mie Kristine Just
- Department of Nuclear Medicine and PET, Aarhus University Hospital, Aarhus, Denmark; Department of Clinical Medicine, Aarhus University, Aarhus, Denmark
| | - Tatyana D Fedorova
- Department of Nuclear Medicine and PET, Aarhus University Hospital, Aarhus, Denmark; Department of Clinical Medicine, Aarhus University, Aarhus, Denmark
| | - Casper Skjærbæk
- Department of Nuclear Medicine and PET, Aarhus University Hospital, Aarhus, Denmark; Department of Clinical Medicine, Aarhus University, Aarhus, Denmark
| | - Ole L Munk
- Department of Nuclear Medicine and PET, Aarhus University Hospital, Aarhus, Denmark; Department of Clinical Medicine, Aarhus University, Aarhus, Denmark
| | - Kim V Hansen
- Department of Nuclear Medicine and PET, Aarhus University Hospital, Aarhus, Denmark
| | - Hanne Gottrup
- Department of Neurology, Aarhus University Hospital, Aarhus, Denmark
| | - Allan K Hansen
- Department of Nuclear Medicine and PET, Aarhus University Hospital, Aarhus, Denmark; Department of Nuclear Medicine, Aalborg University Hospital, Aalborg, Denmark
| | - Michel J Grothe
- Unidad de Trastornos del Movimiento, Servicio de Neurología y Neurofisiología Clínica, Instituto de Biomedicina de Sevilla (IBiS), Hospital Universitario Virgen del Rocío/CSIC/Universidad de Sevilla, Seville, Spain; Centro de Investigación Biomédica en Red Sobre Enfermedades Neurodegenerativas (CIBERNED), Instituto de Salud Carlos III, Madrid, Spain
| | - Per Borghammer
- Department of Nuclear Medicine and PET, Aarhus University Hospital, Aarhus, Denmark
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150
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van 't Hooft JJ, Pelkmans W, Tomassen J, Smits C, Legdeur N, den Braber A, Barkhof F, van Berckel B, Yaqub M, Scheltens P, Pijnenburg YA, Visser PJ, Tijms BM. Distinct disease mechanisms may underlie cognitive decline related to hearing loss in different age groups. J Neurol Neurosurg Psychiatry 2023; 94:314-320. [PMID: 36639225 DOI: 10.1136/jnnp-2022-329726] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/03/2022] [Accepted: 11/21/2022] [Indexed: 01/15/2023]
Abstract
BACKGROUND Hearing loss in older adults is associated with increased dementia risk. Underlying mechanisms that connect hearing loss with dementia remain largely unclear. METHODS We studied the association of hearing loss and biomarkers for dementia risk in two age groups with normal cognition: 65 participants from the European Medical Information Framework (EMIF)-Alzheimer's disease (AD) 90+ study (oldest-old; mean age 92.7 years, 56.9% female) and 60 participants from the EMIF-AD PreclinAD study (younger-old; mean age 74.4, 43.3% female). Hearing function was tested by the 'digits-in-noise test' and cognition by repeated neuropsychological evaluation. Regressions and generalised estimating equations were used to test the association of hearing function and PET-derived amyloid burden, and linear mixed models were used to test the association of hearing function and cognitive decline. In the oldest-old group, mediation analyses were performed to study whether cognitive decline is mediated through regional brain atrophy. RESULTS In oldest-old individuals, hearing function was not associated with amyloid pathology (p=0.7), whereas in the younger-old individuals hearing loss was associated with higher amyloid burden (p=0.0034). In oldest-old individuals, poorer hearing was associated with a steeper decline in memory, global cognition and language, and in the younger-old with steeper decline in language only. The hippocampus and nucleus accumbens mediated the effects of hearing loss on memory and global cognition in the oldest-old individuals. CONCLUSIONS Hearing loss was associated with amyloid binding in younger-old individuals only, and with cognitive decline in both age groups. These results suggest that mechanisms linking hearing loss with risk for dementia depends on age.
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Affiliation(s)
- Jochum J van 't Hooft
- Alzheimer Center Amsterdam, Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC Location VUmc, Amsterdam, The Netherlands .,Amsterdam Neuroscience, Neurodegeneration, Amsterdam, The Netherlands
| | - Wiesje Pelkmans
- Alzheimer Center Amsterdam, Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC Location VUmc, Amsterdam, The Netherlands.,Amsterdam Neuroscience, Neurodegeneration, Amsterdam, The Netherlands
| | - Jori Tomassen
- Alzheimer Center Amsterdam, Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC Location VUmc, Amsterdam, The Netherlands.,Amsterdam Neuroscience, Neurodegeneration, Amsterdam, The Netherlands
| | - Cas Smits
- Otolaryngology - Head and Neck Surgery, Ear and Hearing, Amsterdam Public Health Research Institute, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Nienke Legdeur
- Alzheimer Center Amsterdam, Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC Location VUmc, Amsterdam, The Netherlands.,Amsterdam Neuroscience, Neurodegeneration, Amsterdam, The Netherlands
| | - Anouk den Braber
- Alzheimer Center Amsterdam, Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC Location VUmc, Amsterdam, The Netherlands.,Amsterdam Neuroscience, Neurodegeneration, Amsterdam, The Netherlands
| | - Frederik Barkhof
- Department of Radiology and Nuclear Medicine, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands.,UCL Institutes of Neurology and Healthcare Engineering, University College London, London, UK
| | - Bart van Berckel
- Department of Radiology and Nuclear Medicine, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands
| | - Maqsood Yaqub
- Department of Radiology and Nuclear Medicine, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands
| | - Philip Scheltens
- Alzheimer Center Amsterdam, Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC Location VUmc, Amsterdam, The Netherlands.,Amsterdam Neuroscience, Neurodegeneration, Amsterdam, The Netherlands
| | - Yolande Al Pijnenburg
- Alzheimer Center Amsterdam, Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC Location VUmc, Amsterdam, The Netherlands.,Amsterdam Neuroscience, Neurodegeneration, Amsterdam, The Netherlands
| | - Pieter Jelle Visser
- Alzheimer Center Amsterdam, Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC Location VUmc, Amsterdam, The Netherlands.,Amsterdam Neuroscience, Neurodegeneration, Amsterdam, The Netherlands.,Department of Psychiatry and Neuropsychology, School for Mental Health and Neuroscience, Alzheimer Center Limburg, Maastricht University, Maastricht, The Netherlands
| | - Betty M Tijms
- Alzheimer Center Amsterdam, Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC Location VUmc, Amsterdam, The Netherlands.,Amsterdam Neuroscience, Neurodegeneration, Amsterdam, The Netherlands
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