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Toribio-Fernandez R, Ceron C, Tristão-Pereira C, Fernandez-Nueda I, Perez-Castillo A, Fernandez-Ferro J, Moro MA, Ibañez B, Fuster V, Cortes-Canteli M. Oral anticoagulants: A plausible new treatment for Alzheimer's disease? Br J Pharmacol 2024; 181:760-776. [PMID: 36633908 DOI: 10.1111/bph.16032] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/19/2022] [Revised: 01/02/2023] [Accepted: 01/06/2023] [Indexed: 01/13/2023] Open
Abstract
Alzheimer's disease (AD) and cardiovascular disease (CVD) are strongly associated. Both are multifactorial disorders with long asymptomatic phases and similar risk factors. Indeed, CVD signatures such as cerebral microbleeds, micro-infarcts, atherosclerosis, cerebral amyloid angiopathy and a procoagulant state are highly associated with AD. However, AD and CVD co-development and the molecular mechanisms underlying such associations are not understood. Here, we review the evidence regarding the vascular component of AD and clinical studies using anticoagulants that specifically evaluated the development of AD and other dementias. Most studies reported a markedly decreased incidence of composite dementia in anticoagulated patients with atrial fibrillation, with the highest benefit for direct oral anticoagulants. However, sub-analyses by differential dementia diagnosis were scarce and inconclusive. We finally discuss whether anticoagulation could be a plausible preventive/therapeutic approach for AD and, if so, which would be the best drug and strategy to maximize clinical benefit and minimize potential risks. LINKED ARTICLES: This article is part of a themed issue From Alzheimer's Disease to Vascular Dementia: Different Roads Leading to Cognitive Decline. To view the other articles in this section visit http://onlinelibrary.wiley.com/doi/10.1111/bph.v181.6/issuetoc.
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Affiliation(s)
- Raquel Toribio-Fernandez
- Instituto de Investigación Sanitaria Fundación Jiménez Díaz (IIS-FJD), Madrid, Spain
- Centro Nacional de Investigaciones Cardiovasculares Carlos III (CNIC), Madrid, Spain
| | - Carlos Ceron
- Centro Nacional de Investigaciones Cardiovasculares Carlos III (CNIC), Madrid, Spain
| | | | - Irene Fernandez-Nueda
- Centro Nacional de Investigaciones Cardiovasculares Carlos III (CNIC), Madrid, Spain
| | - Ana Perez-Castillo
- Centro de Investigación Biomédica en Red en Enfermedades Neurodegenerativas (CIBERNED), Instituto de Salud Carlos III (ISCIII), Madrid, Spain
- Instituto de Investigaciones Biomédicas "Alberto Sols" (CSIC-UAM), Madrid, Spain
| | - Jose Fernandez-Ferro
- Instituto de Investigación Sanitaria Fundación Jiménez Díaz (IIS-FJD), Madrid, Spain
- Centro Nacional de Investigaciones Cardiovasculares Carlos III (CNIC), Madrid, Spain
- Stroke Unit, Neurology Service, Hospital Universitario Rey Juan Carlos (HURJC), Madrid, Spain
| | - Maria Angeles Moro
- Centro Nacional de Investigaciones Cardiovasculares Carlos III (CNIC), Madrid, Spain
| | - Borja Ibañez
- Instituto de Investigación Sanitaria Fundación Jiménez Díaz (IIS-FJD), Madrid, Spain
- Centro Nacional de Investigaciones Cardiovasculares Carlos III (CNIC), Madrid, Spain
- CIBER de enfermedades cardiovasculares (CIBERCV), ISCIII, Madrid, Spain
| | - Valentin Fuster
- Centro Nacional de Investigaciones Cardiovasculares Carlos III (CNIC), Madrid, Spain
- Icahn School of Medicine at Mount Sinai, New York, New York, USA
| | - Marta Cortes-Canteli
- Instituto de Investigación Sanitaria Fundación Jiménez Díaz (IIS-FJD), Madrid, Spain
- Centro Nacional de Investigaciones Cardiovasculares Carlos III (CNIC), Madrid, Spain
- Centro de Investigación Biomédica en Red en Enfermedades Neurodegenerativas (CIBERNED), Instituto de Salud Carlos III (ISCIII), Madrid, Spain
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2
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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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3
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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: 1.0] [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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Guehl NJ, Dhaynaut M, Hanseeuw BJ, Moon SH, Lois C, Thibault E, Fu JF, Price JC, Johnson KA, El Fakhri G, Normandin MD. Measurement of Cerebral Perfusion Indices from the Early Phase of [ 18F]MK6240 Dynamic Tau PET Imaging. J Nucl Med 2023; 64:968-975. [PMID: 36997330 PMCID: PMC10241011 DOI: 10.2967/jnumed.122.265072] [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: 10/21/2022] [Revised: 01/26/2023] [Accepted: 01/26/2023] [Indexed: 04/01/2023] Open
Abstract
6-(fluoro-18F)-3-(1H-pyrrolo[2,3-c]pyridin-1-yl)isoquinolin-5-amine ([18F]MK6240) has high affinity and selectivity for hyperphosphorylated tau and readily crosses the blood-brain barrier. This study investigated whether the early phase of [18F]MK6240 can be used to provide a surrogate index of cerebral perfusion. Methods: Forty-nine subjects who were cognitively normal (CN), had mild cognitive impairment (MCI), or had Alzheimer's disease (AD) underwent paired dynamic [18F]MK6240 and [11C]Pittsburgh compound B (PiB) PET, as well as structural MRI to obtain anatomic information. Arterial blood samples were collected in a subset of 24 subjects for [18F]MK6240 scans to derive metabolite-corrected arterial input functions. Regional time-activity curves were extracted using atlases available in the Montreal Neurologic Institute template space and using FreeSurfer. The early phase of brain time-activity curves was analyzed using a 1-tissue-compartment model to obtain a robust estimate of the rate of transfer from plasma to brain tissue, K 1 (mL⋅cm-3⋅min-1), and the simplified reference tissue model 2 was investigated for noninvasive estimation of the relative delivery rate, R 1 (unitless). A head-to-head comparison with R 1 derived from [11C]PiB scans was performed. Grouped differences in R 1 were evaluated among CN, MCI, and AD subjects. Results: Regional K 1 values suggested a relatively high extraction fraction. R 1 estimated noninvasively from simplified reference tissue model 2 agreed well with R 1 calculated indirectly from the blood-based compartment modeling (r = 0.99; mean difference, 0.024 ± 0.027), suggesting that robust estimates were obtained. R 1 measurements obtained with [18F]MK6240 correlated strongly and overall agreed well with those obtained from [11C]PiB (r = 0.93; mean difference, -0.001 ± 0.068). Statistically significant differences were observed in regional R 1 measurements among CN, MCI, and AD subjects, notably in the temporal and parietal cortices. Conclusion: Our results provide evidence that the early phase of [18F]MK6240 images may be used to derive a useful index of cerebral perfusion. The early and late phases of a [18F]MK6240 dynamic acquisition may thus offer complementary information about the pathophysiologic mechanisms of the disease.
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Affiliation(s)
- Nicolas J Guehl
- Gordon Center for Medical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts;
| | - Maeva Dhaynaut
- Gordon Center for Medical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts
| | - Bernard J Hanseeuw
- Gordon Center for Medical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts
- Department of Neurology, Cliniques Universitaires Saint-Luc, Université Catholique de Louvain, Brussels, Belgium; and
| | - Sung-Hyun Moon
- Gordon Center for Medical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts
| | - Cristina Lois
- Gordon Center for Medical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts
| | - Emma Thibault
- Gordon Center for Medical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts
| | - Jessie Fanglu Fu
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts
| | - Julie C Price
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts
| | - Keith A Johnson
- Gordon Center for Medical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts
| | - Georges El Fakhri
- Gordon Center for Medical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts
| | - Marc D Normandin
- Gordon Center for Medical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts
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5
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Carneiro CDG, Faria DDP, Coutinho AM, Ono CR, Duran FLDS, da Costa NA, Garcez AT, da Silveira PS, Forlenza OV, Brucki SMD, Nitrini R, Busatto G, Buchpiguel CA. Evaluation of 10-minute post-injection 11C-PiB PET and its correlation with 18F-FDG PET in older adults who are cognitively healthy, mildly impaired, or with probable Alzheimer's disease. REVISTA BRASILEIRA DE PSIQUIATRIA (SAO PAULO, BRAZIL : 1999) 2022; 44:495-506. [PMID: 36420910 PMCID: PMC9561831 DOI: 10.47626/1516-4446-2021-2374] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 11/22/2022] [Accepted: 03/14/2022] [Indexed: 11/17/2022]
Abstract
OBJECTIVE Positron emission tomography (PET) allows in vivo evaluation of molecular targets in neurodegenerative diseases, such as Alzheimer's disease. Mild cognitive impairment is an intermediate stage between normal cognition and Alzheimer-type dementia. In vivo fibrillar amyloid-beta can be detected in PET using [11C]-labeled Pittsburgh compound B (11C-PiB). In contrast, [18F]fluoro-2-deoxy-d-glucose (18F-FDG) is a neurodegeneration biomarker used to evaluate cerebral glucose metabolism, indicating neuronal injury and synaptic dysfunction. In addition, early cerebral uptake of amyloid-PET tracers can determine regional cerebral blood flow. The present study compared early-phase 11C-PiB and 18F-FDG in older adults without cognitive impairment, amnestic mild cognitive impairment, and clinical diagnosis of probable Alzheimer's disease. METHODS We selected 90 older adults, clinically classified as healthy controls, with amnestic mild cognitive impairment, or with probable Alzheimer's disease, who underwent an 18F-FDG PET, early-phase 11C-PiB PET and magnetic resonance imaging. All participants were also classified as amyloid-positive or -negative in late-phase 11C-PiB. The data were analyzed using statistical parametric mapping. RESULTS We found that the probable Alzheimer's disease and amnestic mild cognitive impairment group had lower early-phase 11C-PiB uptake in limbic structures than 18F-FDG uptake. The images showed significant interactions between amyloid-beta status (negative or positive). However, early-phase 11C-PiB appears to provide different information from 18F-FDG about neurodegeneration. CONCLUSIONS Our study suggests that early-phase 11C-PiB uptake correlates with 18F-FDG, irrespective of the particular amyloid-beta status. In addition, we observed distinct regional distribution patterns between both biomarkers, reinforcing the need for more robust studies to investigate the real clinical value of early-phase amyloid-PET imaging.
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Affiliation(s)
- Camila de Godoi Carneiro
- Laboratório de Medicina Nuclear (LIM 43), Departamento de Radiologia e Oncologia, Hospital das Clínicas, Faculdade de Medicina, Universidade de São Paulo (USP), São Paulo, SP, Brazil,Centro de Investigação Translacional em Oncologia, Departamento de Radiologia e Oncologia, Hospital das Clínicas, Faculdade de Medicina, Universidade de São Paulo (USP), São Paulo, SP, Brazil
| | - Daniele de Paula Faria
- Laboratório de Medicina Nuclear (LIM 43), Departamento de Radiologia e Oncologia, Hospital das Clínicas, Faculdade de Medicina, Universidade de São Paulo (USP), São Paulo, SP, Brazil,Centro de Investigação Translacional em Oncologia, Departamento de Radiologia e Oncologia, Hospital das Clínicas, Faculdade de Medicina, Universidade de São Paulo (USP), São Paulo, SP, Brazil
| | - Artur Martins Coutinho
- Laboratório de Medicina Nuclear (LIM 43), Departamento de Radiologia e Oncologia, Hospital das Clínicas, Faculdade de Medicina, Universidade de São Paulo (USP), São Paulo, SP, Brazil
| | - Carla Rachel Ono
- Laboratório de Medicina Nuclear (LIM 43), Departamento de Radiologia e Oncologia, Hospital das Clínicas, Faculdade de Medicina, Universidade de São Paulo (USP), São Paulo, SP, Brazil
| | - Fábio Luís de Souza Duran
- Laboratório Neuro-Imagem em Psiquiatria (LIM 21), Departamento de Psiquiatria, Hospital das Clínicas, Faculdade de Medicina, USP, São Paulo, SP, Brazil
| | - Naomi Antunes da Costa
- Laboratório Neuro-Imagem em Psiquiatria (LIM 21), Departamento de Psiquiatria, Hospital das Clínicas, Faculdade de Medicina, USP, São Paulo, SP, Brazil
| | - Alexandre Teles Garcez
- Laboratório de Medicina Nuclear (LIM 43), Departamento de Radiologia e Oncologia, Hospital das Clínicas, Faculdade de Medicina, Universidade de São Paulo (USP), São Paulo, SP, Brazil
| | - Paula Squarzoni da Silveira
- Laboratório Neuro-Imagem em Psiquiatria (LIM 21), Departamento de Psiquiatria, Hospital das Clínicas, Faculdade de Medicina, USP, São Paulo, SP, Brazil
| | - Orestes Vicente Forlenza
- Laboratório de Neurociências (LIM 27), Departamento de Psiquiatria, Hospital das Clínicas, Faculdade de Medicina, USP, São Paulo, SP, Brazil
| | - Sonia Maria Dozzi Brucki
- Departamento de Neurologia, Hospital das Clínicas, Faculdade de Medicina, USP, São Paulo, SP, Brazil
| | - Ricardo Nitrini
- Departamento de Neurologia, Hospital das Clínicas, Faculdade de Medicina, USP, São Paulo, SP, Brazil
| | - Geraldo Busatto
- Laboratório Neuro-Imagem em Psiquiatria (LIM 21), Departamento de Psiquiatria, Hospital das Clínicas, Faculdade de Medicina, USP, São Paulo, SP, Brazil
| | - Carlos Alberto Buchpiguel
- Laboratório de Medicina Nuclear (LIM 43), Departamento de Radiologia e Oncologia, Hospital das Clínicas, Faculdade de Medicina, Universidade de São Paulo (USP), São Paulo, SP, Brazil,Correspondence: Carlos Alberto Buchpiguel, Universidade de São Paulo, Faculdade de Medicina da Universidade de São Paulo, Av. Dr. Arnaldo, 455, CEP 01255-090, São Paulo, SP, Brazil. E-mail:
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Boccalini C, Peretti DE, Ribaldi F, Scheffler M, Stampacchia S, Tomczyk S, Rodriguez C, Montandon ML, Haller S, Giannakopoulos P, Frisoni GB, Perani D, Garibotto V. Early-phase 18F-Florbetapir and 18F-Flutemetamol images as proxies of brain metabolism in a memory clinic setting. J Nucl Med 2022; 64:jnumed.122.264256. [PMID: 35863896 PMCID: PMC9902851 DOI: 10.2967/jnumed.122.264256] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/08/2022] [Revised: 07/15/2022] [Accepted: 07/15/2022] [Indexed: 11/16/2022] Open
Abstract
Background: Alzheimer's disease (AD) neuropathologic changes are β-amyloid (Aβ) deposition, pathologic tau, and neurodegeneration. Dual-phase amyloid-PET might be able to evaluate Aβ deposition and neurodegeneration with a single tracer injection. Early-phase amyloid-PET scans provide a proxy for cerebral perfusion, which has shown good correlations with neural dysfunction measured through metabolic consumption, while the late frames depict amyloid distribution. Our study aims to assess the comparability between early-phase amyloid-PET scans and 18F-fluorodeoxyglucose (18F-FDG)-PET brain topography at the individual level, and their ability to discriminate patients. Methods: 166 subjects evaluated at the Geneva Memory Center, ranging from cognitively unimpaired to Mild Cognitive Impairment (MCI) and dementia, underwent early-phase amyloid-PET - using either 18F-florbetapir (eFBP) (n = 94) or 18F-flutemetamol (eFMM) (n = 72) - and 18F-FDG-PET. Aβ status was assessed. Standardized uptake value ratios (SUVR) were extracted to evaluate the correlation of eFBP/eFMM and their respective 18F-FDG-PET scans. The single-subject procedure was applied to investigate hypometabolism and hypoperfusion maps and their spatial overlap by Dice coefficient. Receiver operating characteristic analyses were performed to compare the discriminative power of eFBP/eFMM, and 18F-FDG-PET SUVR in AD-related metaROI between Aβ-negative healthy controls and cases in the AD continuum. Results: Positive correlations were found between eFBP/eFMM and 18F-FDG-PET SUVR independently of Aβ status and Aβ radiotracer (R>0.72, p<0.001). eFBP/eFMM single-subject analysis revealed clusters of significant hypoperfusion with good correspondence to hypometabolism topographies, independently of the underlying neurodegenerative patterns. Both eFBP/eFMM and 18F-FDG-PET SUVR significantly discriminated AD patients from controls in the AD-related metaROIs (AUCFBP = 0.888; AUCFMM=0.801), with 18F-FDG-PET performing slightly better, however not significantly (all p-value higher than 0.05), than others (AUCFDG=0.915 and 0.832 for subjects evaluated with 18F-FBP and 18F-FMM, respectively). Conclusion: The distribution of perfusion was comparable to that of metabolism at the single-subject level by parametric analysis, particularly in the presence of a high neurodegeneration burden. Our findings indicate that eFBP/eFMM imaging can replace 18F-FDG-PET imaging, as they reveal typical neurodegenerative patterns, or allow to exclude the presence of neurodegeneration. The finding shows cost-saving capacities of amyloid-PET and supports the routine use of the modality for individual classification in clinical practice.
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Affiliation(s)
- Cecilia Boccalini
- Laboratory of Neuroimaging and Innovative Molecular Tracers (NIMTlab), Geneva University Neurocenter and Faculty of Medicine, University of Geneva, Geneva, Switzerland
- Vita-Salute San Raffaele University, Milan, Italy
- In Vivo Human Molecular and Structural Neuroimaging Unit, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Débora Elisa Peretti
- Laboratory of Neuroimaging and Innovative Molecular Tracers (NIMTlab), Geneva University Neurocenter and Faculty of Medicine, University of Geneva, Geneva, Switzerland
| | - Federica Ribaldi
- Laboratory of Neuroimaging of Aging (LANVIE), University of Geneva, Geneva, Switzerland
- Memory Clinic, Geneva University Hospitals, Geneva, Switzerland
| | - Max Scheffler
- Division of Radiology, Diagnostic Department, Geneva University Hospitals, Geneva, Switzerland
| | - Sara Stampacchia
- Laboratory of Neuroimaging and Innovative Molecular Tracers (NIMTlab), Geneva University Neurocenter and Faculty of Medicine, University of Geneva, Geneva, Switzerland
| | - Szymon Tomczyk
- Laboratory of Neuroimaging of Aging (LANVIE), University of Geneva, Geneva, Switzerland
| | - Cristelle Rodriguez
- Division of Institutional Measures, Medical Direction, University Hospitals of Geneva, Geneva, Switzerland
- Department of Psychiatry, Faculty of Medicine, University of Geneva, Geneva, Switzerland
| | - Marie-Louise Montandon
- Department of Psychiatry, Faculty of Medicine, University of Geneva, Geneva, Switzerland
- Department of Rehabilitation and Geriatrics, Geneva University Hospitals and University of Geneva, Geneva, Switzerland
| | - Sven Haller
- CIMC–Centre d’Imagerie Médicale de Cornavin, Geneva, Switzerland
- Faculty of Medicine of University of Geneva, Geneva, Switzerland
- Division of Radiology, Department of Surgical Sciences, Uppsala University, Uppsala, Sweden
- Department of Radiology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Panteleimon Giannakopoulos
- Division of Institutional Measures, Medical Direction, University Hospitals of Geneva, Geneva, Switzerland
- Department of Psychiatry, Faculty of Medicine, University of Geneva, Geneva, Switzerland
| | - Giovanni B. Frisoni
- Laboratory of Neuroimaging of Aging (LANVIE), University of Geneva, Geneva, Switzerland
- Memory Clinic, Geneva University Hospitals, Geneva, Switzerland
| | - Daniela Perani
- Vita-Salute San Raffaele University, Milan, Italy
- In Vivo Human Molecular and Structural Neuroimaging Unit, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy
- Nuclear Medicine Unit, San Raffaele Hospital, Milan, Italy
| | - Valentina Garibotto
- Laboratory of Neuroimaging and Innovative Molecular Tracers (NIMTlab), Geneva University Neurocenter and Faculty of Medicine, University of Geneva, Geneva, Switzerland
- Division of Nuclear Medicine and Molecular Imaging, Geneva University Hospitals, Geneva, Switzerland; and
- CIBM Center for Biomedical Imaging, Geneva, Switzerland
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7
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Peretti DE, Vállez García D, Renken RJ, Reesink FE, Doorduin J, de Jong BM, De Deyn PP, Dierckx RAJO, Boellaard R. Alzheimer's disease pattern derived from relative cerebral flow as an alternative for the metabolic pattern using SSM/PCA. EJNMMI Res 2022; 12:37. [PMID: 35737201 PMCID: PMC9226207 DOI: 10.1186/s13550-022-00909-8] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/12/2022] [Accepted: 06/15/2022] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND 2-Deoxy-2-[18F]fluoroglucose (FDG) PET is an important tool for the identification of Alzheimer's disease (AD) patients through the characteristic neurodegeneration pattern that these patients present. Regional cerebral blood flow (rCBF) images derived from dynamic 11C-labelled Pittsburgh Compound B (PIB) have been shown to present a similar pattern as FDG. Moreover, multivariate analysis techniques, such as scaled subprofile modelling using principal component analysis (SSM/PCA), can be used to generate disease-specific patterns (DP) that may aid in the classification of subjects. Therefore, the aim of this study was to compare rCBF AD-DPs with FDG AD-DP and their respective performances. Therefore, 52 subjects were included in this study. Fifteen AD and 16 healthy control subjects were used to generate four AD-DP: one based on relative cerebral trace blood (R1), two based on time-weighted average of initial frame intervals (ePIB), and one based on FDG images. Furthermore, 21 subjects diagnosed with mild cognitive impairment were tested against these AD-DPs. RESULTS In general, the rCBF and FDG AD-DPs were characterized by a reduction in cortical frontal, temporal, and parietal lobes. FDG and rCBF methods presented similar score distribution. CONCLUSION rCBF images may provide an alternative for FDG PET scans for the identification of AD patients through SSM/PCA.
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Affiliation(s)
- Débora E Peretti
- Department of Nuclear Medicine and Molecular Imaging, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands
| | - David Vállez García
- Department of Nuclear Medicine and Molecular Imaging, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands
| | - Remco J Renken
- Department of Biomedical Sciences of Cells and Systems, Cognitive Neuroscience Center, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands
| | - Fransje E Reesink
- Department of Neurology, Alzheimer Centre, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands
| | - Janine Doorduin
- Department of Nuclear Medicine and Molecular Imaging, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands
| | - Bauke M de Jong
- Department of Neurology, Alzheimer Centre, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands
| | - Peter P De Deyn
- Department of Neurology, Alzheimer Centre, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands.,Laboratory of Neurochemistry and Behaviour, Institute Born-Bunge, University of Antwerp, Antwerp, Belgium
| | - Rudi A J O Dierckx
- Department of Nuclear Medicine and Molecular Imaging, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands
| | - Ronald Boellaard
- Department of Nuclear Medicine and Molecular Imaging, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands. .,Department of Radiology and Nuclear Medicine, Location VU Medical Center, Amsterdam University Medical Center, De Boelelaan 1117, 1081 HV, Amsterdam, The Netherlands.
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8
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Taubel J, Nelson NR, Bansal A, Curran GL, Wang L, Wang Z, Berg HM, Vernon CJ, Min HK, Larson NB, DeGrado TR, Kandimalla KK, Lowe VJ, Pandey MK. Design, Synthesis, and Preliminary Evaluation of [ 68Ga]Ga-NOTA-Insulin as a PET Probe in an Alzheimer's Disease Mouse Model. Bioconjug Chem 2022; 33:892-906. [PMID: 35420782 PMCID: PMC9121347 DOI: 10.1021/acs.bioconjchem.2c00126] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/11/2023]
Abstract
Aberrant insulin signaling has been considered one of the risk factors for the development of Alzheimer's disease (AD) and has drawn considerable attention from the research community to further study its role in AD pathophysiology. Herein, we describe the development of an insulin-based novel positron emission tomography (PET) probe, [68Ga]Ga-NOTA-insulin, to noninvasively study the role of insulin in AD. The developed PET probe [68Ga]Ga-NOTA-insulin showed a significantly higher uptake (0.396 ± 0.055 SUV) in the AD mouse brain compared to the normal (0.140 ± 0.027 SUV) mouse brain at 5 min post injection and also showed a similar trend at 10, 15, and 20 min post injection. In addition, [68Ga]Ga-NOTA-insulin was found to have a differential uptake in various brain regions at 30 min post injection. Among the brain regions, the cortex, thalamus, brain stem, and cerebellum showed a significantly higher standard uptake value (SUV) of [68Ga]Ga-NOTA-insulin in AD mice as compared to normal mice. The inhibition of the insulin receptor (IR) with an insulin receptor antagonist peptide (S961) in normal mice showed a similar brain uptake profile of [68Ga]Ga-NOTA-insulin as it was observed in the AD case, suggesting nonfunctional IR in AD and the presence of an alternative insulin uptake route in the absence of a functional IR. The Gjedde-Patlak graphical analysis was also performed to predict the input rate of [68Ga]Ga-NOTA-insulin into the brain using MicroPET imaging data and supported the in vivo results. The [68Ga]Ga-NOTA-insulin PET probe was successfully synthesized and evaluated in a mouse model of AD in comparison with [18F]AV1451 and [11C]PIB to noninvasively study the role of insulin in AD pathophysiology.
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Affiliation(s)
- Jillissa
C. Taubel
- Division
of Nuclear Medicine, Department of Radiology, Mayo Clinic Rochester, Minnesota 55905, United States
| | - Nicholas R. Nelson
- Division
of Nuclear Medicine, Department of Radiology, Mayo Clinic Rochester, Minnesota 55905, United States
| | - Aditya Bansal
- Division
of Nuclear Medicine, Department of Radiology, Mayo Clinic Rochester, Minnesota 55905, United States
| | - Geoffrey L. Curran
- Division
of Nuclear Medicine, Department of Radiology, Mayo Clinic Rochester, Minnesota 55905, United States
| | - Lushan Wang
- Department
of Pharmaceutics, College of Pharmacy, University
of Minnesota, Minneapolis, Minnesota 55455, United States
| | - Zengtao Wang
- Department
of Pharmaceutics, College of Pharmacy, University
of Minnesota, Minneapolis, Minnesota 55455, United States
| | - Heather M. Berg
- Division
of Nuclear Medicine, Department of Radiology, Mayo Clinic Rochester, Minnesota 55905, United States
| | - Cynthia J. Vernon
- Division
of Nuclear Medicine, Department of Radiology, Mayo Clinic Rochester, Minnesota 55905, United States
| | - Hoon-Ki Min
- Division
of Nuclear Medicine, Department of Radiology, Mayo Clinic Rochester, Minnesota 55905, United States
| | - Nicholas B. Larson
- Department
of Quantitative Health Sciences, Mayo Clinic, Rochester, Minnesota 55905, United States
| | - Timothy R. DeGrado
- Department
of Radiology, University of Colorado Anschutz
Medical Campus, Aurora, Colorado 80045, United States
| | - Karunya K. Kandimalla
- Department
of Pharmaceutics, College of Pharmacy, University
of Minnesota, Minneapolis, Minnesota 55455, United States,
| | - Val J. Lowe
- Division
of Nuclear Medicine, Department of Radiology, Mayo Clinic Rochester, Minnesota 55905, United States,
| | - Mukesh K. Pandey
- Division
of Nuclear Medicine, Department of Radiology, Mayo Clinic Rochester, Minnesota 55905, United States,
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Shen C, Wang Z, Chen H, Bai Y, Li X, Liang D, Liu X, Zheng H, Wang M, Yang Y, Wang H, Sun T. Identifying Mild Alzheimer's Disease With First 30-Min 11C-PiB PET Scan. Front Aging Neurosci 2022; 14:785495. [PMID: 35450057 PMCID: PMC9016824 DOI: 10.3389/fnagi.2022.785495] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/29/2021] [Accepted: 02/23/2022] [Indexed: 11/13/2022] Open
Abstract
Introduction 11C-labeled Pittsburgh compound B (11C-PiB) PET imaging can provide information for the diagnosis of Alzheimer's disease (AD) by quantifying the binding of PiB to β-amyloid deposition in the brain. Quantification index, such as standardized uptake value ratio (SUVR) and distribution volume ratio (DVR), has been exploited to effectively distinguish between healthy and subjects with AD. However, these measures require a long wait/scan time, as well as the selection of an optimal reference region. In this study, we propose an alternate measure named amyloid quantification index (AQI), which can be obtained with the first 30-min scan without the selection of the reference region. Methods 11C-labeled Pittsburgh compound B PET scan data were obtained from the public dataset "OASIS-3". A total of 60 mild subjects with AD and 60 healthy controls were included, with 50 used for training and 10 used for testing in each group. The proposed measure AQI combines information of clearance rate and mid-phase PIB retention in featured brain regions from the first 30-min scan. For each subject in the training set, AQI, SUVR, and DVR were calculated and used for classification by the logistic regression classifier. The receiver operating characteristic (ROC) analysis was performed to evaluate the performance of these measures. Accuracy, sensitivity, and specificity were reported. The Kruskal-Wallis test and effect size were also performed and evaluated for all measures. Then, the performance of three measures was further validated on the testing set using the same method. The correlations between these measures and clinical MMSE and CDR-SOB scores were analyzed. Results The Kruskal-Wallis test suggested that AQI, SUVR, and DVR can all differentiate between the healthy and subjects with mild AD (p < 0.001). For the training set, ROC analysis showed that AQI achieved the best classification performance with an accuracy rate of 0.93, higher than 0.88 for SUVR and 0.89 for DVR. The effect size of AQI, SUVR, and DVR were 2.35, 2.12, and 2.06, respectively, indicating that AQI was the most effective among these measures. For the testing set, all three measures achieved less superior performance, while AQI still performed the best with the highest accuracy of 0.85. Some false-negative cases with below-threshold SUVR and DVR values were correctly identified using AQI. All three measures showed significant and comparable correlations with clinical scores (p < 0.01). Conclusion Amyloid quantification index combines early-phase kinetic information and a certain degree of β-amyloid deposition, and can provide a better differentiating performance using the data from the first 30-min dynamic scan. Moreover, it was shown that clinically indistinguishable AD cases regarding PiB retention potentially can be correctly identified.
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Affiliation(s)
- Chushu Shen
- Paul C. Lauterbur Research Center for Biomedical Imaging, Shenzhen Institute of Advanced Technology, Chinese Academy of Science, Shenzhen, China
| | - Zhenguo Wang
- Paul C. Lauterbur Research Center for Biomedical Imaging, Shenzhen Institute of Advanced Technology, Chinese Academy of Science, Shenzhen, China
| | - Hongzhao Chen
- Paul C. Lauterbur Research Center for Biomedical Imaging, Shenzhen Institute of Advanced Technology, Chinese Academy of Science, Shenzhen, China
| | - Yan Bai
- Henan Provincial People's Hospital and the People's Hospital of Zhengzhou, University of Zhengzhou, Zhengzhou, China
| | - Xiaochen Li
- Henan Provincial People's Hospital and the People's Hospital of Zhengzhou, University of Zhengzhou, Zhengzhou, China
| | - Dong Liang
- Paul C. Lauterbur Research Center for Biomedical Imaging, Shenzhen Institute of Advanced Technology, Chinese Academy of Science, Shenzhen, China
| | - Xin Liu
- Paul C. Lauterbur Research Center for Biomedical Imaging, Shenzhen Institute of Advanced Technology, Chinese Academy of Science, Shenzhen, China
| | - Hairong Zheng
- Paul C. Lauterbur Research Center for Biomedical Imaging, Shenzhen Institute of Advanced Technology, Chinese Academy of Science, Shenzhen, China
| | - Meiyun Wang
- Henan Provincial People's Hospital and the People's Hospital of Zhengzhou, University of Zhengzhou, Zhengzhou, China
| | - Yongfeng Yang
- Paul C. Lauterbur Research Center for Biomedical Imaging, Shenzhen Institute of Advanced Technology, Chinese Academy of Science, Shenzhen, China
| | - Haifeng Wang
- Paul C. Lauterbur Research Center for Biomedical Imaging, Shenzhen Institute of Advanced Technology, Chinese Academy of Science, Shenzhen, China
| | - Tao Sun
- Paul C. Lauterbur Research Center for Biomedical Imaging, Shenzhen Institute of Advanced Technology, Chinese Academy of Science, Shenzhen, China,*Correspondence: Tao Sun
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10
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Huang Z, Wu Y, Fu F, Meng N, Gu F, Wu Q, Zhou Y, Yang Y, Liu X, Zheng H, Liang D, Wang M, Hu Z. Parametric image generation with the uEXPLORER total-body PET/CT system through deep learning. Eur J Nucl Med Mol Imaging 2022; 49:2482-2492. [DOI: 10.1007/s00259-022-05731-x] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/22/2021] [Accepted: 02/13/2022] [Indexed: 11/25/2022]
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11
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Raman F, Fang YHD, Grandhi S, Murchison CF, Kennedy RE, Morris JC, Massoumzadeh P, Benzinger T, Roberson ED, McConathy J. Dynamic Amyloid PET: Relationships to 18F-Flortaucipir Tau PET Measures. J Nucl Med 2022; 63:287-293. [PMID: 34049986 PMCID: PMC8805772 DOI: 10.2967/jnumed.120.254490] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/27/2020] [Revised: 04/23/2021] [Indexed: 11/16/2022] Open
Abstract
Measuring amyloid and predicting tau status using a single amyloid PET study would be valuable for assessing brain AD pathophysiology. We hypothesized that early-frame amyloid PET (efAP) correlates with the presence of tau pathology because the initial regional brain concentrations of radioactivity are determined primarily by blood flow, which is expected to be decreased in the setting of tau pathology. Methods: The study included 120 participants (63 amyloid-positive and 57 amyloid-negative) with dynamic 18F-florbetapir PET and static 18F-flortaucipir PET scans obtained within 6 mo of each other. These subjects were predominantly cognitively intact in both the amyloid-positive (63%) and the amyloid-negative (93%) groups. Parameters for efAP quantification were optimized for stratification of tau PET positivity, assessed by either a tauopathy score or Braak regions. The ability of efAP to stratify tau positivity was measured using receiver-operating-characteristic analysis of area under the curve (AUC). Pearson r and Spearman ρ were used for parametric and nonparametric comparisons between efAP and tau PET, respectively. Standardized net benefit was used to evaluate improvement in using efAP as an additional copredictor over hippocampal volume in predicting tau PET positivity. Results: Measuring efAP within the hippocampus and summing the first 3 min of brain activity after injection showed the strongest discriminative ability to stratify for tau positivity (AUC, 0.67-0.89 across tau PET Braak regions) in amyloid-positive individuals. Hippocampal efAP correlated significantly with a global tau PET tauopathy score in amyloid-positive participants (r = -0.57, P < 0.0001). Compared with hippocampal volume, hippocampal efAP showed a stronger association with tau PET Braak stage (ρ = -0.58 vs. -0.37) and superior stratification of tau PET tauopathy score (AUC, 0.86 vs. 0.66; P = 0.002). Conclusion: Hippocampal efAP can provide additional information to conventional amyloid PET, including estimation of the likelihood of tau positivity in amyloid-positive individuals.
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Affiliation(s)
- Fabio Raman
- Department of Radiology, University of Alabama at Birmingham, Birmingham, Alabama
- Alzheimer's Disease Center, University of Alabama at Birmingham, Birmingham, Alabama
- Department of Neurology, University of Alabama at Birmingham, Birmingham, Alabama
- Center for Neurodegeneration and Experimental Therapeutics, University of Alabama at Birmingham, Birmingham, Alabama
| | - Yu-Hua Dean Fang
- Department of Radiology, University of Alabama at Birmingham, Birmingham, Alabama
| | - Sameera Grandhi
- Department of Radiology, University of Alabama at Birmingham, Birmingham, Alabama
- Alzheimer's Disease Center, University of Alabama at Birmingham, Birmingham, Alabama
| | - Charles F Murchison
- Alzheimer's Disease Center, University of Alabama at Birmingham, Birmingham, Alabama
- Department of Medicine, University of Alabama at Birmingham, Birmingham, Alabama
| | - Richard E Kennedy
- Alzheimer's Disease Center, University of Alabama at Birmingham, Birmingham, Alabama
- Department of Neurology, University of Alabama at Birmingham, Birmingham, Alabama
| | - John C Morris
- Department of Neurology, Washington University in St. Louis School of Medicine, St. Louis, Missouri; and
| | - Parinaz Massoumzadeh
- Mallinckrodt Institute of Radiology, Washington University in St. Louis School of Medicine, St. Louis, Missouri
| | - Tammie Benzinger
- Mallinckrodt Institute of Radiology, Washington University in St. Louis School of Medicine, St. Louis, Missouri
| | - Erik D Roberson
- Alzheimer's Disease Center, University of Alabama at Birmingham, Birmingham, Alabama
- Department of Neurology, University of Alabama at Birmingham, Birmingham, Alabama
- Center for Neurodegeneration and Experimental Therapeutics, University of Alabama at Birmingham, Birmingham, Alabama
| | - Jonathan McConathy
- Department of Radiology, University of Alabama at Birmingham, Birmingham, Alabama;
- Alzheimer's Disease Center, University of Alabama at Birmingham, Birmingham, Alabama
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Differential associations between neocortical tau pathology and blood flow with cognitive deficits in early-onset vs late-onset Alzheimer's disease. Eur J Nucl Med Mol Imaging 2022; 49:1951-1963. [PMID: 34997294 PMCID: PMC9016024 DOI: 10.1007/s00259-021-05669-6] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/17/2021] [Accepted: 12/20/2021] [Indexed: 12/23/2022]
Abstract
Purpose Early-onset Alzheimer’s disease (EOAD) and late-onset Alzheimer’s disease (LOAD) differ in neuropathological burden and type of cognitive deficits. Assessing tau pathology and relative cerebral blood flow (rCBF) measured with [18F]flortaucipir PET in relation to cognition may help explain these differences between EOAD and LOAD. Methods Seventy-nine amyloid-positive individuals with a clinical diagnosis of AD (EOAD: n = 35, age-at-PET = 59 ± 5, MMSE = 23 ± 4; LOAD: n = 44, age-at-PET = 71 ± 5, MMSE = 23 ± 4) underwent a 130-min dynamic [18F]flortaucipir PET scan and extensive neuropsychological assessment. We extracted binding potentials (BPND) and R1 (proxy of rCBF) from parametric images using receptor parametric mapping, in medial and lateral temporal, parietal, occipital, and frontal regions-of-interest and used nine neuropsychological tests covering memory, attention, language, and executive functioning. We first examined differences between EOAD and LOAD in BPND or R1 using ANOVA (region-of-interest analysis) and voxel-wise contrasts. Next, we performed linear regression models to test for potential interaction effects between age-at-onset and BPND/R1 on cognition. Results Both region-of-interest and voxel-wise contrasts showed higher [18F]flortaucipir BPND values across all neocortical regions in EOAD. By contrast, LOAD patients had lower R1 values (indicative of more reduced rCBF) in medial temporal regions. For both tau and flow in lateral temporal, and occipitoparietal regions, associations with cognitive impairment were stronger in EOAD than in LOAD (EOAD BPND − 0.76 ≤ stβ ≤ − 0.48 vs LOAD − 0.18 ≤ stβ ≤ − 0.02; EOAD R1 0.37 ≤ stβ ≤ 0.84 vs LOAD − 0.25 ≤ stβ ≤ 0.16). Conclusions Compared to LOAD, the degree of lateral temporal and occipitoparietal tau pathology and relative cerebral blood-flow is more strongly associated with cognition in EOAD. Supplementary Information The online version contains supplementary material available at 10.1007/s00259-021-05669-6.
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Wolters EE, Papma JM, Verfaillie SCJ, Visser D, Weltings E, Groot C, van der Ende EL, Giannini LAA, Tuncel H, Timmers T, Boellaard R, Yaqub M, van Assema DME, Kuijper DA, Segbers M, Rozemuller AJM, Barkhof F, Windhorst AD, van der Flier WM, Pijnenburg YAL, Scheltens P, van Berckel BNM, van Swieten JC, Ossenkoppele R, Seelaar H. [ 18F]Flortaucipir PET Across Various MAPT Mutations in Presymptomatic and Symptomatic Carriers. Neurology 2021; 97:e1017-e1030. [PMID: 34210823 PMCID: PMC8448551 DOI: 10.1212/wnl.0000000000012448] [Citation(s) in RCA: 17] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/17/2021] [Accepted: 06/07/2021] [Indexed: 11/15/2022] Open
Abstract
OBJECTIVE To assess the [18F]flortaucipir binding distribution across MAPT mutations in presymptomatic and symptomatic carriers. METHODS We compared regional [18F]flortaucipir binding potential (BPND) derived from a 130-minute dynamic [18F]flortaucipir PET scan in 9 (pre)symptomatic MAPT mutation carriers (4 with P301L [1 symptomatic], 2 with R406W [1 symptomatic], 1 presymptomatic L315R, 1 presymptomatic S320F, and 1 symptomatic G272V carrier) with 30 cognitively normal controls and 52 patients with Alzheimer disease. RESULTS [18F]Flortaucipir BPND images showed overall highest binding in the symptomatic carriers. This was most pronounced in the symptomatic R406W carrier in whom tau binding exceeded the normal control range in the anterior cingulate cortex, insula, amygdala, temporal, parietal, and frontal lobe. Elevated medial temporal lobe BPND was observed in a presymptomatic R406W carrier. The single symptomatic carrier and 1 of the 3 presymptomatic P301L carriers showed elevated [18F]flortaucipir BPND in the insula, parietal, and frontal lobe compared to controls. The symptomatic G272V carrier exhibited a widespread elevated cortical BPND, with at neuropathologic examination a combination of 3R pathology and encephalitis. The L315R presymptomatic mutation carrier showed higher frontal BPND compared to controls. The BPND values of the S320F presymptomatic mutation carrier fell within the range of controls. CONCLUSION Presymptomatic MAPT mutation carriers already showed subtle elevated tau binding, whereas symptomatic MAPT mutation carriers showed a more marked increase in [18F]flortaucipir BPND. Tau deposition was most pronounced in R406W MAPT (pre)symptomatic mutation carriers, which is associated with both 3R and 4R tau accumulation. Thus, [18F]flortaucipir may serve as an early biomarker for MAPT mutation carriers in mutations that cause 3R/4R tauopathies.
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Affiliation(s)
- Emma E Wolters
- From the Department of Radiology & Nuclear Medicine (E.E.W., S.C.J.V., D.V., E.W., H.T., T.T., R.B., M.Y., F.B., A.D.W., B.N.M.v.B.) and Alzheimer Center Amsterdam, Department of Neurology (E.E.W., C.G., W.M.v.d.F., Y.A.L.P., P.S., R.O.), Amsterdam Neuroscience, and Department of Epidemiology and Biostatistics (W.M.v.d.F.), Vrije Universiteit Amsterdam, Amsterdam UMC; Department of Neurology, Alzheimer Center (J.M.P., E.L.v.d.E., L.A.A.G., J.C.v.S., H.S.), and Department of Radiology & Nuclear Medicine (D.M.E.v.A., D.A.K., M.S.), Erasmus MC University Medical Center, Rotterdam; Department of Pathology (A.J.M.R.), Amsterdam Neuroscience, Amsterdam UMC, location VUmc, the Netherlands; Institutes of Neurology & Healthcare Engineering (F.B.), UCL, London, UK; and Clinical Memory Research Unit (R.O.), Lund University, Sweden.
| | - Janne M Papma
- From the Department of Radiology & Nuclear Medicine (E.E.W., S.C.J.V., D.V., E.W., H.T., T.T., R.B., M.Y., F.B., A.D.W., B.N.M.v.B.) and Alzheimer Center Amsterdam, Department of Neurology (E.E.W., C.G., W.M.v.d.F., Y.A.L.P., P.S., R.O.), Amsterdam Neuroscience, and Department of Epidemiology and Biostatistics (W.M.v.d.F.), Vrije Universiteit Amsterdam, Amsterdam UMC; Department of Neurology, Alzheimer Center (J.M.P., E.L.v.d.E., L.A.A.G., J.C.v.S., H.S.), and Department of Radiology & Nuclear Medicine (D.M.E.v.A., D.A.K., M.S.), Erasmus MC University Medical Center, Rotterdam; Department of Pathology (A.J.M.R.), Amsterdam Neuroscience, Amsterdam UMC, location VUmc, the Netherlands; Institutes of Neurology & Healthcare Engineering (F.B.), UCL, London, UK; and Clinical Memory Research Unit (R.O.), Lund University, Sweden
| | - Sander C J Verfaillie
- From the Department of Radiology & Nuclear Medicine (E.E.W., S.C.J.V., D.V., E.W., H.T., T.T., R.B., M.Y., F.B., A.D.W., B.N.M.v.B.) and Alzheimer Center Amsterdam, Department of Neurology (E.E.W., C.G., W.M.v.d.F., Y.A.L.P., P.S., R.O.), Amsterdam Neuroscience, and Department of Epidemiology and Biostatistics (W.M.v.d.F.), Vrije Universiteit Amsterdam, Amsterdam UMC; Department of Neurology, Alzheimer Center (J.M.P., E.L.v.d.E., L.A.A.G., J.C.v.S., H.S.), and Department of Radiology & Nuclear Medicine (D.M.E.v.A., D.A.K., M.S.), Erasmus MC University Medical Center, Rotterdam; Department of Pathology (A.J.M.R.), Amsterdam Neuroscience, Amsterdam UMC, location VUmc, the Netherlands; Institutes of Neurology & Healthcare Engineering (F.B.), UCL, London, UK; and Clinical Memory Research Unit (R.O.), Lund University, Sweden
| | - Denise Visser
- From the Department of Radiology & Nuclear Medicine (E.E.W., S.C.J.V., D.V., E.W., H.T., T.T., R.B., M.Y., F.B., A.D.W., B.N.M.v.B.) and Alzheimer Center Amsterdam, Department of Neurology (E.E.W., C.G., W.M.v.d.F., Y.A.L.P., P.S., R.O.), Amsterdam Neuroscience, and Department of Epidemiology and Biostatistics (W.M.v.d.F.), Vrije Universiteit Amsterdam, Amsterdam UMC; Department of Neurology, Alzheimer Center (J.M.P., E.L.v.d.E., L.A.A.G., J.C.v.S., H.S.), and Department of Radiology & Nuclear Medicine (D.M.E.v.A., D.A.K., M.S.), Erasmus MC University Medical Center, Rotterdam; Department of Pathology (A.J.M.R.), Amsterdam Neuroscience, Amsterdam UMC, location VUmc, the Netherlands; Institutes of Neurology & Healthcare Engineering (F.B.), UCL, London, UK; and Clinical Memory Research Unit (R.O.), Lund University, Sweden
| | - Emma Weltings
- From the Department of Radiology & Nuclear Medicine (E.E.W., S.C.J.V., D.V., E.W., H.T., T.T., R.B., M.Y., F.B., A.D.W., B.N.M.v.B.) and Alzheimer Center Amsterdam, Department of Neurology (E.E.W., C.G., W.M.v.d.F., Y.A.L.P., P.S., R.O.), Amsterdam Neuroscience, and Department of Epidemiology and Biostatistics (W.M.v.d.F.), Vrije Universiteit Amsterdam, Amsterdam UMC; Department of Neurology, Alzheimer Center (J.M.P., E.L.v.d.E., L.A.A.G., J.C.v.S., H.S.), and Department of Radiology & Nuclear Medicine (D.M.E.v.A., D.A.K., M.S.), Erasmus MC University Medical Center, Rotterdam; Department of Pathology (A.J.M.R.), Amsterdam Neuroscience, Amsterdam UMC, location VUmc, the Netherlands; Institutes of Neurology & Healthcare Engineering (F.B.), UCL, London, UK; and Clinical Memory Research Unit (R.O.), Lund University, Sweden
| | - Colin Groot
- From the Department of Radiology & Nuclear Medicine (E.E.W., S.C.J.V., D.V., E.W., H.T., T.T., R.B., M.Y., F.B., A.D.W., B.N.M.v.B.) and Alzheimer Center Amsterdam, Department of Neurology (E.E.W., C.G., W.M.v.d.F., Y.A.L.P., P.S., R.O.), Amsterdam Neuroscience, and Department of Epidemiology and Biostatistics (W.M.v.d.F.), Vrije Universiteit Amsterdam, Amsterdam UMC; Department of Neurology, Alzheimer Center (J.M.P., E.L.v.d.E., L.A.A.G., J.C.v.S., H.S.), and Department of Radiology & Nuclear Medicine (D.M.E.v.A., D.A.K., M.S.), Erasmus MC University Medical Center, Rotterdam; Department of Pathology (A.J.M.R.), Amsterdam Neuroscience, Amsterdam UMC, location VUmc, the Netherlands; Institutes of Neurology & Healthcare Engineering (F.B.), UCL, London, UK; and Clinical Memory Research Unit (R.O.), Lund University, Sweden
| | - Emma L van der Ende
- From the Department of Radiology & Nuclear Medicine (E.E.W., S.C.J.V., D.V., E.W., H.T., T.T., R.B., M.Y., F.B., A.D.W., B.N.M.v.B.) and Alzheimer Center Amsterdam, Department of Neurology (E.E.W., C.G., W.M.v.d.F., Y.A.L.P., P.S., R.O.), Amsterdam Neuroscience, and Department of Epidemiology and Biostatistics (W.M.v.d.F.), Vrije Universiteit Amsterdam, Amsterdam UMC; Department of Neurology, Alzheimer Center (J.M.P., E.L.v.d.E., L.A.A.G., J.C.v.S., H.S.), and Department of Radiology & Nuclear Medicine (D.M.E.v.A., D.A.K., M.S.), Erasmus MC University Medical Center, Rotterdam; Department of Pathology (A.J.M.R.), Amsterdam Neuroscience, Amsterdam UMC, location VUmc, the Netherlands; Institutes of Neurology & Healthcare Engineering (F.B.), UCL, London, UK; and Clinical Memory Research Unit (R.O.), Lund University, Sweden
| | - Lucia A A Giannini
- From the Department of Radiology & Nuclear Medicine (E.E.W., S.C.J.V., D.V., E.W., H.T., T.T., R.B., M.Y., F.B., A.D.W., B.N.M.v.B.) and Alzheimer Center Amsterdam, Department of Neurology (E.E.W., C.G., W.M.v.d.F., Y.A.L.P., P.S., R.O.), Amsterdam Neuroscience, and Department of Epidemiology and Biostatistics (W.M.v.d.F.), Vrije Universiteit Amsterdam, Amsterdam UMC; Department of Neurology, Alzheimer Center (J.M.P., E.L.v.d.E., L.A.A.G., J.C.v.S., H.S.), and Department of Radiology & Nuclear Medicine (D.M.E.v.A., D.A.K., M.S.), Erasmus MC University Medical Center, Rotterdam; Department of Pathology (A.J.M.R.), Amsterdam Neuroscience, Amsterdam UMC, location VUmc, the Netherlands; Institutes of Neurology & Healthcare Engineering (F.B.), UCL, London, UK; and Clinical Memory Research Unit (R.O.), Lund University, Sweden
| | - Hayel Tuncel
- From the Department of Radiology & Nuclear Medicine (E.E.W., S.C.J.V., D.V., E.W., H.T., T.T., R.B., M.Y., F.B., A.D.W., B.N.M.v.B.) and Alzheimer Center Amsterdam, Department of Neurology (E.E.W., C.G., W.M.v.d.F., Y.A.L.P., P.S., R.O.), Amsterdam Neuroscience, and Department of Epidemiology and Biostatistics (W.M.v.d.F.), Vrije Universiteit Amsterdam, Amsterdam UMC; Department of Neurology, Alzheimer Center (J.M.P., E.L.v.d.E., L.A.A.G., J.C.v.S., H.S.), and Department of Radiology & Nuclear Medicine (D.M.E.v.A., D.A.K., M.S.), Erasmus MC University Medical Center, Rotterdam; Department of Pathology (A.J.M.R.), Amsterdam Neuroscience, Amsterdam UMC, location VUmc, the Netherlands; Institutes of Neurology & Healthcare Engineering (F.B.), UCL, London, UK; and Clinical Memory Research Unit (R.O.), Lund University, Sweden
| | - Tessa Timmers
- From the Department of Radiology & Nuclear Medicine (E.E.W., S.C.J.V., D.V., E.W., H.T., T.T., R.B., M.Y., F.B., A.D.W., B.N.M.v.B.) and Alzheimer Center Amsterdam, Department of Neurology (E.E.W., C.G., W.M.v.d.F., Y.A.L.P., P.S., R.O.), Amsterdam Neuroscience, and Department of Epidemiology and Biostatistics (W.M.v.d.F.), Vrije Universiteit Amsterdam, Amsterdam UMC; Department of Neurology, Alzheimer Center (J.M.P., E.L.v.d.E., L.A.A.G., J.C.v.S., H.S.), and Department of Radiology & Nuclear Medicine (D.M.E.v.A., D.A.K., M.S.), Erasmus MC University Medical Center, Rotterdam; Department of Pathology (A.J.M.R.), Amsterdam Neuroscience, Amsterdam UMC, location VUmc, the Netherlands; Institutes of Neurology & Healthcare Engineering (F.B.), UCL, London, UK; and Clinical Memory Research Unit (R.O.), Lund University, Sweden
| | - Ronald Boellaard
- From the Department of Radiology & Nuclear Medicine (E.E.W., S.C.J.V., D.V., E.W., H.T., T.T., R.B., M.Y., F.B., A.D.W., B.N.M.v.B.) and Alzheimer Center Amsterdam, Department of Neurology (E.E.W., C.G., W.M.v.d.F., Y.A.L.P., P.S., R.O.), Amsterdam Neuroscience, and Department of Epidemiology and Biostatistics (W.M.v.d.F.), Vrije Universiteit Amsterdam, Amsterdam UMC; Department of Neurology, Alzheimer Center (J.M.P., E.L.v.d.E., L.A.A.G., J.C.v.S., H.S.), and Department of Radiology & Nuclear Medicine (D.M.E.v.A., D.A.K., M.S.), Erasmus MC University Medical Center, Rotterdam; Department of Pathology (A.J.M.R.), Amsterdam Neuroscience, Amsterdam UMC, location VUmc, the Netherlands; Institutes of Neurology & Healthcare Engineering (F.B.), UCL, London, UK; and Clinical Memory Research Unit (R.O.), Lund University, Sweden
| | - Maqsood Yaqub
- From the Department of Radiology & Nuclear Medicine (E.E.W., S.C.J.V., D.V., E.W., H.T., T.T., R.B., M.Y., F.B., A.D.W., B.N.M.v.B.) and Alzheimer Center Amsterdam, Department of Neurology (E.E.W., C.G., W.M.v.d.F., Y.A.L.P., P.S., R.O.), Amsterdam Neuroscience, and Department of Epidemiology and Biostatistics (W.M.v.d.F.), Vrije Universiteit Amsterdam, Amsterdam UMC; Department of Neurology, Alzheimer Center (J.M.P., E.L.v.d.E., L.A.A.G., J.C.v.S., H.S.), and Department of Radiology & Nuclear Medicine (D.M.E.v.A., D.A.K., M.S.), Erasmus MC University Medical Center, Rotterdam; Department of Pathology (A.J.M.R.), Amsterdam Neuroscience, Amsterdam UMC, location VUmc, the Netherlands; Institutes of Neurology & Healthcare Engineering (F.B.), UCL, London, UK; and Clinical Memory Research Unit (R.O.), Lund University, Sweden
| | - Danielle M E van Assema
- From the Department of Radiology & Nuclear Medicine (E.E.W., S.C.J.V., D.V., E.W., H.T., T.T., R.B., M.Y., F.B., A.D.W., B.N.M.v.B.) and Alzheimer Center Amsterdam, Department of Neurology (E.E.W., C.G., W.M.v.d.F., Y.A.L.P., P.S., R.O.), Amsterdam Neuroscience, and Department of Epidemiology and Biostatistics (W.M.v.d.F.), Vrije Universiteit Amsterdam, Amsterdam UMC; Department of Neurology, Alzheimer Center (J.M.P., E.L.v.d.E., L.A.A.G., J.C.v.S., H.S.), and Department of Radiology & Nuclear Medicine (D.M.E.v.A., D.A.K., M.S.), Erasmus MC University Medical Center, Rotterdam; Department of Pathology (A.J.M.R.), Amsterdam Neuroscience, Amsterdam UMC, location VUmc, the Netherlands; Institutes of Neurology & Healthcare Engineering (F.B.), UCL, London, UK; and Clinical Memory Research Unit (R.O.), Lund University, Sweden
| | - Dennis A Kuijper
- From the Department of Radiology & Nuclear Medicine (E.E.W., S.C.J.V., D.V., E.W., H.T., T.T., R.B., M.Y., F.B., A.D.W., B.N.M.v.B.) and Alzheimer Center Amsterdam, Department of Neurology (E.E.W., C.G., W.M.v.d.F., Y.A.L.P., P.S., R.O.), Amsterdam Neuroscience, and Department of Epidemiology and Biostatistics (W.M.v.d.F.), Vrije Universiteit Amsterdam, Amsterdam UMC; Department of Neurology, Alzheimer Center (J.M.P., E.L.v.d.E., L.A.A.G., J.C.v.S., H.S.), and Department of Radiology & Nuclear Medicine (D.M.E.v.A., D.A.K., M.S.), Erasmus MC University Medical Center, Rotterdam; Department of Pathology (A.J.M.R.), Amsterdam Neuroscience, Amsterdam UMC, location VUmc, the Netherlands; Institutes of Neurology & Healthcare Engineering (F.B.), UCL, London, UK; and Clinical Memory Research Unit (R.O.), Lund University, Sweden
| | - Marcel Segbers
- From the Department of Radiology & Nuclear Medicine (E.E.W., S.C.J.V., D.V., E.W., H.T., T.T., R.B., M.Y., F.B., A.D.W., B.N.M.v.B.) and Alzheimer Center Amsterdam, Department of Neurology (E.E.W., C.G., W.M.v.d.F., Y.A.L.P., P.S., R.O.), Amsterdam Neuroscience, and Department of Epidemiology and Biostatistics (W.M.v.d.F.), Vrije Universiteit Amsterdam, Amsterdam UMC; Department of Neurology, Alzheimer Center (J.M.P., E.L.v.d.E., L.A.A.G., J.C.v.S., H.S.), and Department of Radiology & Nuclear Medicine (D.M.E.v.A., D.A.K., M.S.), Erasmus MC University Medical Center, Rotterdam; Department of Pathology (A.J.M.R.), Amsterdam Neuroscience, Amsterdam UMC, location VUmc, the Netherlands; Institutes of Neurology & Healthcare Engineering (F.B.), UCL, London, UK; and Clinical Memory Research Unit (R.O.), Lund University, Sweden
| | - Annemieke J M Rozemuller
- From the Department of Radiology & Nuclear Medicine (E.E.W., S.C.J.V., D.V., E.W., H.T., T.T., R.B., M.Y., F.B., A.D.W., B.N.M.v.B.) and Alzheimer Center Amsterdam, Department of Neurology (E.E.W., C.G., W.M.v.d.F., Y.A.L.P., P.S., R.O.), Amsterdam Neuroscience, and Department of Epidemiology and Biostatistics (W.M.v.d.F.), Vrije Universiteit Amsterdam, Amsterdam UMC; Department of Neurology, Alzheimer Center (J.M.P., E.L.v.d.E., L.A.A.G., J.C.v.S., H.S.), and Department of Radiology & Nuclear Medicine (D.M.E.v.A., D.A.K., M.S.), Erasmus MC University Medical Center, Rotterdam; Department of Pathology (A.J.M.R.), Amsterdam Neuroscience, Amsterdam UMC, location VUmc, the Netherlands; Institutes of Neurology & Healthcare Engineering (F.B.), UCL, London, UK; and Clinical Memory Research Unit (R.O.), Lund University, Sweden
| | - Frederik Barkhof
- From the Department of Radiology & Nuclear Medicine (E.E.W., S.C.J.V., D.V., E.W., H.T., T.T., R.B., M.Y., F.B., A.D.W., B.N.M.v.B.) and Alzheimer Center Amsterdam, Department of Neurology (E.E.W., C.G., W.M.v.d.F., Y.A.L.P., P.S., R.O.), Amsterdam Neuroscience, and Department of Epidemiology and Biostatistics (W.M.v.d.F.), Vrije Universiteit Amsterdam, Amsterdam UMC; Department of Neurology, Alzheimer Center (J.M.P., E.L.v.d.E., L.A.A.G., J.C.v.S., H.S.), and Department of Radiology & Nuclear Medicine (D.M.E.v.A., D.A.K., M.S.), Erasmus MC University Medical Center, Rotterdam; Department of Pathology (A.J.M.R.), Amsterdam Neuroscience, Amsterdam UMC, location VUmc, the Netherlands; Institutes of Neurology & Healthcare Engineering (F.B.), UCL, London, UK; and Clinical Memory Research Unit (R.O.), Lund University, Sweden
| | - Albert D Windhorst
- From the Department of Radiology & Nuclear Medicine (E.E.W., S.C.J.V., D.V., E.W., H.T., T.T., R.B., M.Y., F.B., A.D.W., B.N.M.v.B.) and Alzheimer Center Amsterdam, Department of Neurology (E.E.W., C.G., W.M.v.d.F., Y.A.L.P., P.S., R.O.), Amsterdam Neuroscience, and Department of Epidemiology and Biostatistics (W.M.v.d.F.), Vrije Universiteit Amsterdam, Amsterdam UMC; Department of Neurology, Alzheimer Center (J.M.P., E.L.v.d.E., L.A.A.G., J.C.v.S., H.S.), and Department of Radiology & Nuclear Medicine (D.M.E.v.A., D.A.K., M.S.), Erasmus MC University Medical Center, Rotterdam; Department of Pathology (A.J.M.R.), Amsterdam Neuroscience, Amsterdam UMC, location VUmc, the Netherlands; Institutes of Neurology & Healthcare Engineering (F.B.), UCL, London, UK; and Clinical Memory Research Unit (R.O.), Lund University, Sweden
| | - Wiesje M van der Flier
- From the Department of Radiology & Nuclear Medicine (E.E.W., S.C.J.V., D.V., E.W., H.T., T.T., R.B., M.Y., F.B., A.D.W., B.N.M.v.B.) and Alzheimer Center Amsterdam, Department of Neurology (E.E.W., C.G., W.M.v.d.F., Y.A.L.P., P.S., R.O.), Amsterdam Neuroscience, and Department of Epidemiology and Biostatistics (W.M.v.d.F.), Vrije Universiteit Amsterdam, Amsterdam UMC; Department of Neurology, Alzheimer Center (J.M.P., E.L.v.d.E., L.A.A.G., J.C.v.S., H.S.), and Department of Radiology & Nuclear Medicine (D.M.E.v.A., D.A.K., M.S.), Erasmus MC University Medical Center, Rotterdam; Department of Pathology (A.J.M.R.), Amsterdam Neuroscience, Amsterdam UMC, location VUmc, the Netherlands; Institutes of Neurology & Healthcare Engineering (F.B.), UCL, London, UK; and Clinical Memory Research Unit (R.O.), Lund University, Sweden
| | - Yolande A L Pijnenburg
- From the Department of Radiology & Nuclear Medicine (E.E.W., S.C.J.V., D.V., E.W., H.T., T.T., R.B., M.Y., F.B., A.D.W., B.N.M.v.B.) and Alzheimer Center Amsterdam, Department of Neurology (E.E.W., C.G., W.M.v.d.F., Y.A.L.P., P.S., R.O.), Amsterdam Neuroscience, and Department of Epidemiology and Biostatistics (W.M.v.d.F.), Vrije Universiteit Amsterdam, Amsterdam UMC; Department of Neurology, Alzheimer Center (J.M.P., E.L.v.d.E., L.A.A.G., J.C.v.S., H.S.), and Department of Radiology & Nuclear Medicine (D.M.E.v.A., D.A.K., M.S.), Erasmus MC University Medical Center, Rotterdam; Department of Pathology (A.J.M.R.), Amsterdam Neuroscience, Amsterdam UMC, location VUmc, the Netherlands; Institutes of Neurology & Healthcare Engineering (F.B.), UCL, London, UK; and Clinical Memory Research Unit (R.O.), Lund University, Sweden
| | - Philip Scheltens
- From the Department of Radiology & Nuclear Medicine (E.E.W., S.C.J.V., D.V., E.W., H.T., T.T., R.B., M.Y., F.B., A.D.W., B.N.M.v.B.) and Alzheimer Center Amsterdam, Department of Neurology (E.E.W., C.G., W.M.v.d.F., Y.A.L.P., P.S., R.O.), Amsterdam Neuroscience, and Department of Epidemiology and Biostatistics (W.M.v.d.F.), Vrije Universiteit Amsterdam, Amsterdam UMC; Department of Neurology, Alzheimer Center (J.M.P., E.L.v.d.E., L.A.A.G., J.C.v.S., H.S.), and Department of Radiology & Nuclear Medicine (D.M.E.v.A., D.A.K., M.S.), Erasmus MC University Medical Center, Rotterdam; Department of Pathology (A.J.M.R.), Amsterdam Neuroscience, Amsterdam UMC, location VUmc, the Netherlands; Institutes of Neurology & Healthcare Engineering (F.B.), UCL, London, UK; and Clinical Memory Research Unit (R.O.), Lund University, Sweden
| | - Bart N M van Berckel
- From the Department of Radiology & Nuclear Medicine (E.E.W., S.C.J.V., D.V., E.W., H.T., T.T., R.B., M.Y., F.B., A.D.W., B.N.M.v.B.) and Alzheimer Center Amsterdam, Department of Neurology (E.E.W., C.G., W.M.v.d.F., Y.A.L.P., P.S., R.O.), Amsterdam Neuroscience, and Department of Epidemiology and Biostatistics (W.M.v.d.F.), Vrije Universiteit Amsterdam, Amsterdam UMC; Department of Neurology, Alzheimer Center (J.M.P., E.L.v.d.E., L.A.A.G., J.C.v.S., H.S.), and Department of Radiology & Nuclear Medicine (D.M.E.v.A., D.A.K., M.S.), Erasmus MC University Medical Center, Rotterdam; Department of Pathology (A.J.M.R.), Amsterdam Neuroscience, Amsterdam UMC, location VUmc, the Netherlands; Institutes of Neurology & Healthcare Engineering (F.B.), UCL, London, UK; and Clinical Memory Research Unit (R.O.), Lund University, Sweden
| | - John C van Swieten
- From the Department of Radiology & Nuclear Medicine (E.E.W., S.C.J.V., D.V., E.W., H.T., T.T., R.B., M.Y., F.B., A.D.W., B.N.M.v.B.) and Alzheimer Center Amsterdam, Department of Neurology (E.E.W., C.G., W.M.v.d.F., Y.A.L.P., P.S., R.O.), Amsterdam Neuroscience, and Department of Epidemiology and Biostatistics (W.M.v.d.F.), Vrije Universiteit Amsterdam, Amsterdam UMC; Department of Neurology, Alzheimer Center (J.M.P., E.L.v.d.E., L.A.A.G., J.C.v.S., H.S.), and Department of Radiology & Nuclear Medicine (D.M.E.v.A., D.A.K., M.S.), Erasmus MC University Medical Center, Rotterdam; Department of Pathology (A.J.M.R.), Amsterdam Neuroscience, Amsterdam UMC, location VUmc, the Netherlands; Institutes of Neurology & Healthcare Engineering (F.B.), UCL, London, UK; and Clinical Memory Research Unit (R.O.), Lund University, Sweden
| | - Rik Ossenkoppele
- From the Department of Radiology & Nuclear Medicine (E.E.W., S.C.J.V., D.V., E.W., H.T., T.T., R.B., M.Y., F.B., A.D.W., B.N.M.v.B.) and Alzheimer Center Amsterdam, Department of Neurology (E.E.W., C.G., W.M.v.d.F., Y.A.L.P., P.S., R.O.), Amsterdam Neuroscience, and Department of Epidemiology and Biostatistics (W.M.v.d.F.), Vrije Universiteit Amsterdam, Amsterdam UMC; Department of Neurology, Alzheimer Center (J.M.P., E.L.v.d.E., L.A.A.G., J.C.v.S., H.S.), and Department of Radiology & Nuclear Medicine (D.M.E.v.A., D.A.K., M.S.), Erasmus MC University Medical Center, Rotterdam; Department of Pathology (A.J.M.R.), Amsterdam Neuroscience, Amsterdam UMC, location VUmc, the Netherlands; Institutes of Neurology & Healthcare Engineering (F.B.), UCL, London, UK; and Clinical Memory Research Unit (R.O.), Lund University, Sweden
| | - Harro Seelaar
- From the Department of Radiology & Nuclear Medicine (E.E.W., S.C.J.V., D.V., E.W., H.T., T.T., R.B., M.Y., F.B., A.D.W., B.N.M.v.B.) and Alzheimer Center Amsterdam, Department of Neurology (E.E.W., C.G., W.M.v.d.F., Y.A.L.P., P.S., R.O.), Amsterdam Neuroscience, and Department of Epidemiology and Biostatistics (W.M.v.d.F.), Vrije Universiteit Amsterdam, Amsterdam UMC; Department of Neurology, Alzheimer Center (J.M.P., E.L.v.d.E., L.A.A.G., J.C.v.S., H.S.), and Department of Radiology & Nuclear Medicine (D.M.E.v.A., D.A.K., M.S.), Erasmus MC University Medical Center, Rotterdam; Department of Pathology (A.J.M.R.), Amsterdam Neuroscience, Amsterdam UMC, location VUmc, the Netherlands; Institutes of Neurology & Healthcare Engineering (F.B.), UCL, London, UK; and Clinical Memory Research Unit (R.O.), Lund University, Sweden
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Kwon SJ, Ha S, Yoo SW, Shin NY, O JH, Yoo IR, Kim JS. Comparison of early F-18 Florbetaben PET/CT to Tc-99m ECD SPECT using voxel, regional, and network analysis. Sci Rep 2021; 11:16738. [PMID: 34408171 PMCID: PMC8373880 DOI: 10.1038/s41598-021-95808-8] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/07/2021] [Accepted: 07/30/2021] [Indexed: 11/09/2022] Open
Abstract
This study aimed to validate early-phase F-18 Florbetaben positron emission tomography (eFBB PET) as a brain perfusion test and determine the optimal reference region. A total of 27 patients with early Parkinson's disease with Tc-99m ethyl cysteinate dimer single photon emission tomography (ECD SPECT) and FBB PET were included. Six reference regions, including whole brain (GN), pons, central white matter (CWM), whole cerebellum (WC), WC with brain stem (WC + B), and cerebellar grey matter (CG), were applied to obtain SUVR using cortex volume-of-interest (VOI). Reference regions of WC (r 0.886), WC + B (r 0.897), and CG (r 0.904) had highest correlation values of cortex-VOI SUVR between both perfusion images (all p < 0.001). Early-phase FBB PET had a significant linear correlation of CG-normalized SUVR of the cortex, basal ganglia, thalamus, and midbrain with ECD SPECT in voxel-wise analysis (FDR adjusted-p < 0.05). Early-phase FBB PET extracts more ICNS than ECD SPECT, as 9 ICNS and 4 ICNs, respectively. Both eFBB PET and ECD SPECT well discriminated PD from DLB (Area-under-curve of receiver-operating-characteristics, 0.911 for eFBB PET, 0.922 for ECD SPECT). Our findings suggest that eFBB PET is a reliable perfusion test based on a high correlation with ECD SPECT using cerebellum-based normalization methods.
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Affiliation(s)
- Soo Jin Kwon
- Division of Nuclear Medicine, Department of Radiology, Seoul St. Mary's Hospital, College of Medicine, The Catholic University of Korea, 222, Banpo-daero, Seocho-gu, Seoul, 06591, Republic of Korea
| | - Seunggyun Ha
- Division of Nuclear Medicine, Department of Radiology, Seoul St. Mary's Hospital, College of Medicine, The Catholic University of Korea, 222, Banpo-daero, Seocho-gu, Seoul, 06591, Republic of Korea.
| | - Sang-Won Yoo
- Department of Neurology, College of Medicine, The Catholic University of Korea, Seoul, Republic of Korea
| | - Na-Young Shin
- Department of Radiology, College of Medicine, The Catholic University of Korea, Seoul, Republic of Korea
| | - Joo Hyun O
- Division of Nuclear Medicine, Department of Radiology, Seoul St. Mary's Hospital, College of Medicine, The Catholic University of Korea, 222, Banpo-daero, Seocho-gu, Seoul, 06591, Republic of Korea
| | - Ie Ryung Yoo
- Division of Nuclear Medicine, Department of Radiology, Seoul St. Mary's Hospital, College of Medicine, The Catholic University of Korea, 222, Banpo-daero, Seocho-gu, Seoul, 06591, Republic of Korea
| | - Joong-Seok Kim
- Department of Neurology, College of Medicine, The Catholic University of Korea, Seoul, Republic of Korea
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15
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Seiffert AP, Gómez-Grande A, Villarejo-Galende A, González-Sánchez M, Bueno H, Gómez EJ, Sánchez-González P. High Correlation of Static First-Minute-Frame (FMF) PET Imaging after 18F-Labeled Amyloid Tracer Injection with [ 18F]FDG PET Imaging. SENSORS (BASEL, SWITZERLAND) 2021; 21:5182. [PMID: 34372416 PMCID: PMC8348394 DOI: 10.3390/s21155182] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 06/08/2021] [Revised: 07/26/2021] [Accepted: 07/28/2021] [Indexed: 01/17/2023]
Abstract
Dynamic early-phase PET images acquired with radiotracers binding to fibrillar amyloid-beta (Aβ) have shown to correlate with [18F]fluorodeoxyglucose (FDG) PET images and provide perfusion-like information. Perfusion information of static PET scans acquired during the first minute after radiotracer injection (FMF, first-minute-frame) is compared to [18F]FDG PET images. FMFs of 60 patients acquired with [18F]florbetapir (FBP), [18F]flutemetamol (FMM), and [18F]florbetaben (FBB) are compared to [18F]FDG PET images. Regional standardized uptake value ratios (SUVR) are directly compared and intrapatient Pearson's correlation coefficients are calculated to evaluate the correlation of FMFs to their corresponding [18F]FDG PET images. Additionally, regional interpatient correlations are calculated. The intensity profiles of mean SUVRs among the study cohort (r = 0.98, p < 0.001) and intrapatient analyses show strong correlations between FMFs and [18F]FDG PET images (r = 0.93 ± 0.05). Regional VOI-based analyses also result in high correlation coefficients. The FMF shows similar information to the cerebral metabolic patterns obtained by [18F]FDG PET imaging. Therefore, it could be an alternative to the dynamic imaging of early phase amyloid PET and be used as an additional neurodegeneration biomarker in amyloid PET studies in routine clinical practice while being acquired at the same time as amyloid PET images.
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Affiliation(s)
- Alexander P. Seiffert
- Biomedical Engineering and Telemedicine Centre, ETSI Telecomunicación, Center for Biomedical Technology, Universidad Politécnica de Madrid, 28040 Madrid, Spain;
| | - Adolfo Gómez-Grande
- Department of Nuclear Medicine, Hospital Universitario 12 de Octubre, 28041 Madrid, Spain;
- Facultad de Medicina, Universidad Complutense de Madrid, 28040 Madrid, Spain; (A.V.-G.); (H.B.)
| | - Alberto Villarejo-Galende
- Facultad de Medicina, Universidad Complutense de Madrid, 28040 Madrid, Spain; (A.V.-G.); (H.B.)
- Department of Neurology, Hospital Universitario 12 de Octubre, 28041 Madrid, Spain;
- Group of Neurodegenerative Diseases, Hospital 12 de Octubre Research Institute (imas12), 28041 Madrid, Spain
- Biomedical Research Networking Center in Neurodegenerative Diseases (CIBERNED), 28029 Madrid, Spain
| | - Marta González-Sánchez
- Department of Neurology, Hospital Universitario 12 de Octubre, 28041 Madrid, Spain;
- Group of Neurodegenerative Diseases, Hospital 12 de Octubre Research Institute (imas12), 28041 Madrid, Spain
- Biomedical Research Networking Center in Neurodegenerative Diseases (CIBERNED), 28029 Madrid, Spain
| | - Héctor Bueno
- Facultad de Medicina, Universidad Complutense de Madrid, 28040 Madrid, Spain; (A.V.-G.); (H.B.)
- Department of Cardiology and Instituto de Investigación Sanitaria (imas12), Hospital Universitario 12 de Octubre, 28041 Madrid, Spain
- Centro Nacional de Investigaciones Cardiovasculares (CNIC), 28029 Madrid, Spain
- Centro de Investigación Biomédica en Red de Enfermedades Cardiovasculares (CIBERCV), 28029 Madrid, Spain
| | - Enrique J. Gómez
- Biomedical Engineering and Telemedicine Centre, ETSI Telecomunicación, Center for Biomedical Technology, Universidad Politécnica de Madrid, 28040 Madrid, Spain;
- Centro de Investigación Biomédica en Red de Bioingeniería, Biomateriales y Nanomedicina (CIBER-BBN), 28029 Madrid, Spain
| | - Patricia Sánchez-González
- Biomedical Engineering and Telemedicine Centre, ETSI Telecomunicación, Center for Biomedical Technology, Universidad Politécnica de Madrid, 28040 Madrid, Spain;
- Centro de Investigación Biomédica en Red de Bioingeniería, Biomateriales y Nanomedicina (CIBER-BBN), 28029 Madrid, Spain
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16
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Early-phase 18F-FP-CIT and 18F-flutemetamol PET were significantly correlated. Sci Rep 2021; 11:12297. [PMID: 34112926 PMCID: PMC8192502 DOI: 10.1038/s41598-021-91891-z] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/29/2021] [Accepted: 06/02/2021] [Indexed: 02/02/2023] Open
Abstract
Little is known about whether early-phase PET images of 18F-FP-CIT match those of amyloid PET. Here, we compared early-phase 18F-FP-CIT and 18F-flutemetamol PET images in patients who underwent both within a 1-month interval. The SUVR on early-phase 18F-FP-CIT PET (median, 0.86) was significantly lower than that of 18F-flutemetamol PET (median, 0.91, p < 0.001) for total brain regions including all cerebral lobes and central structures. This significant difference persisted for each brain region except central structures (p = 0.232). The SUVR of total brain regions obtained from early 18F-FP-CIT PET showed a very strong correlation with that of 18F-flutemetamol PET (rho = 0.80, p < 0.001). Among the kinetic parameters, only R1 showed a statistically significant correlation between the two techniques for all brain regions (rho = 0.89, p < 0.001). R1 from 18F-FP-CIT (median, 0.77) was significantly lower in all areas of the brain compared to R1 from 18F-flutemetamol PET (median, 0.81, p < 0.001).18F-FP-CIT demonstrated lower uptake in cortical brain regions than 18F-flutemetamol on early-phase PET. However, both early-phase PETs demonstrated significant correlation of uptake.
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17
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Schmitt J, Palleis C, Sauerbeck J, Unterrainer M, Harris S, Prix C, Weidinger E, Katzdobler S, Wagemann O, Danek A, Beyer L, Rauchmann BS, Rominger A, Simons M, Bartenstein P, Perneczky R, Haass C, Levin J, Höglinger GU, Brendel M. Dual-Phase β-Amyloid PET Captures Neuronal Injury and Amyloidosis in Corticobasal Syndrome. Front Aging Neurosci 2021; 13:661284. [PMID: 34054506 PMCID: PMC8155727 DOI: 10.3389/fnagi.2021.661284] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/30/2021] [Accepted: 04/06/2021] [Indexed: 11/13/2022] Open
Abstract
Objectives: In recent years several 18F-labeled amyloid PET (Aβ-PET) tracers have been developed and have obtained clinical approval. There is evidence that Aβ-PET perfusion can provide surrogate information about neuronal injury in neurodegenerative diseases when compared to conventional blood flow and glucose metabolism assessment. However, this paradigm has not yet been tested in neurodegenerative disorders with cortical and subcortical affection. Therefore, we investigated the performance of early acquisition 18F-flutemetamol Aβ-PET in comparison to 18F-fluorodeoxyglucose (FDG)-PET in corticobasal syndrome (CBS). Methods: Subjects with clinically possible or probable CBS were recruited within the prospective Activity of Cerebral Networks, Amyloid and Microglia in Aging and Alzheimer's Disease (ActiGliA) observational study and all CBS cases with an available FDG-PET prior to Aβ-PET were selected. Aβ-PET was acquired 0-10 min p.i. (early-phase) and 90-110 min p.i. (late-phase) whereas FDG-PET was recorded statically from 30 to 50 min p.i. Semiquantitative regional values and asymmetry indices (AI) were compared between early-phase Aβ-PET and FDG-PET. Visual assessments of hypoperfusion and hypometabolism were compared between both methods. Late-phase Aβ-PET was evaluated visually for assessment of Aβ-positivity. Results: Among 20 evaluated patients with CBS, 5 were Aβ-positive. Early-phase Aβ-PET and FDG-PET SUVr correlated highly in cortical (mean R = 0.86, range 0.77-0.92) and subcortical brain regions (mean R = 0.84, range 0.79-0.90). Strong asymmetry was observed in FDG-PET for the motor cortex (mean |AI| = 2.9%), the parietal cortex (mean |AI| = 2.9%), and the thalamus (mean |AI| = 5.5%), correlating well with AI of early-phase Aβ-PET (mean R = 0.87, range 0.62-0.98). Visual assessments of hypoperfusion and hypometabolism were highly congruent. Conclusion: Early-phase Aβ-PET facilitates assessment of neuronal injury in CBS for cortical and subcortical areas. Known asymmetries in CBS are captured by this method, enabling assessment of Aβ-status and neuronal injury with a single radiation exposure at a single visit.
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Affiliation(s)
- Julia Schmitt
- Department of Nuclear Medicine, University Hospital of Munich, LMU Munich, Munich, Germany
| | - Carla Palleis
- Department of Neurology, University Hospital of Munich, LMU Munich, Munich, Germany
| | - Julia Sauerbeck
- Department of Nuclear Medicine, University Hospital of Munich, LMU Munich, Munich, Germany
| | - Marcus Unterrainer
- Department of Nuclear Medicine, University Hospital of Munich, LMU Munich, Munich, Germany
| | - Stefanie Harris
- Department of Nuclear Medicine, University Hospital of Munich, LMU Munich, Munich, Germany
| | - Catharina Prix
- Department of Neurology, University Hospital of Munich, LMU Munich, Munich, Germany
| | - Endy Weidinger
- Department of Neurology, University Hospital of Munich, LMU Munich, Munich, Germany
| | - Sabrina Katzdobler
- Department of Neurology, University Hospital of Munich, LMU Munich, Munich, Germany
| | - Olivia Wagemann
- Department of Neurology, University Hospital of Munich, LMU Munich, Munich, Germany
| | - Adrian Danek
- Department of Neurology, University Hospital of Munich, LMU Munich, Munich, Germany
| | - Leonie Beyer
- Department of Nuclear Medicine, University Hospital of Munich, LMU Munich, Munich, Germany
| | - Boris-Stephan Rauchmann
- Department of Psychiatry and Psychotherapy, University Hospital, LMU Munich, Munich, Germany.,Department of Radiology, University Hospital of Munich, LMU Munich, Munich, Germany
| | - Axel Rominger
- Department of Nuclear Medicine, University Hospital of Munich, LMU Munich, Munich, Germany.,Department of Nuclear Medicine, University of Bern, Inselspital, Bern, Switzerland.,Munich Cluster for Systems Neurology (SyNergy), Munich, Germany
| | - Mikael Simons
- Munich Cluster for Systems Neurology (SyNergy), Munich, Germany.,German Center for Neurodegenerative Diseases (DZNE), Munich, Germany.,Institute of Neuronal Cell Biology, Technical University Munich, Munich, Germany
| | - Peter Bartenstein
- Department of Nuclear Medicine, University Hospital of Munich, LMU Munich, Munich, Germany.,Munich Cluster for Systems Neurology (SyNergy), Munich, Germany
| | - Robert Perneczky
- Department of Psychiatry and Psychotherapy, University Hospital, LMU Munich, Munich, Germany.,Munich Cluster for Systems Neurology (SyNergy), Munich, Germany.,German Center for Neurodegenerative Diseases (DZNE), Munich, Germany.,Ageing Epidemiology Research Unit (AGE), School of Public Health, Imperial College London, London, United Kingdom
| | - Christian Haass
- Munich Cluster for Systems Neurology (SyNergy), Munich, Germany.,German Center for Neurodegenerative Diseases (DZNE), Munich, Germany.,Faculty of Medicine, Chair of Metabolic Biochemistry, Biomedical Center (BMC), Ludwig-Maximilians-Universtität München, Munich, Germany
| | - Johannes Levin
- Department of Neurology, University Hospital of Munich, LMU Munich, Munich, Germany.,Munich Cluster for Systems Neurology (SyNergy), Munich, Germany.,German Center for Neurodegenerative Diseases (DZNE), Munich, Germany
| | - Günter U Höglinger
- German Center for Neurodegenerative Diseases (DZNE), Munich, Germany.,Department of Neurology, Medizinische Hochschule Hannover, Hanover, Germany.,Department of Neurology, Technical University Munich, Munich, Germany
| | - Matthias Brendel
- Department of Nuclear Medicine, University Hospital of Munich, LMU Munich, Munich, Germany.,Munich Cluster for Systems Neurology (SyNergy), Munich, Germany
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18
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Heeman F, Hendriks J, Lopes Alves I, Tolboom N, van Berckel BNM, Yaqub M, Lammertsma AA. Test-Retest Variability of Relative Tracer Delivery Rate as Measured by [ 11C]PiB. Mol Imaging Biol 2021; 23:335-339. [PMID: 33884565 PMCID: PMC8099850 DOI: 10.1007/s11307-021-01606-z] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/15/2020] [Revised: 02/23/2021] [Accepted: 04/06/2021] [Indexed: 11/30/2022]
Abstract
Purpose Moderate-to-high correlations have been reported between the [11C]PiB PET-derived relative tracer delivery rate R1 and relative CBF as measured using [15O]H2O PET, supporting its use as a proxy of relative CBF. As longitudinal PET studies become more common for measuring treatment efficacy or disease progression, it is important to know the intrinsic variability of R1. The purpose of the present study was to determine this through a retrospective data analysis. Procedures Test-retest data belonging to twelve participants, who underwent two 90 min [11C]PiB PET scans, were retrospectively included. The voxel-based implementation of the two-step simplified reference tissue model with cerebellar grey matter as reference tissue was used to compute R1 images. Next, test-retest variability was calculated, and test and retest R1 measures were compared using linear mixed effect models and a Bland-Altman analysis. Results Test-retest variability was low across regions (max. 5.8 %), and test and retest measures showed high, significant correlations (R2=0.92, slope=0.98) and a negligible bias (0.69±3.07 %). Conclusions In conclusion, the high precision of [11C]PiB R1 suggests suitable applicability for cross-sectional and longitudinal studies.
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Affiliation(s)
- Fiona Heeman
- Amsterdam UMC, Vrije Universiteit Amsterdam, Radiology and Nuclear Medicine, Amsterdam Neuroscience, De Boelelaan 1117, Amsterdam, The Netherlands.
| | - Janine Hendriks
- Amsterdam UMC, Vrije Universiteit Amsterdam, Radiology and Nuclear Medicine, Amsterdam Neuroscience, De Boelelaan 1117, Amsterdam, The Netherlands
| | - Isadora Lopes Alves
- Amsterdam UMC, Vrije Universiteit Amsterdam, Radiology and Nuclear Medicine, Amsterdam Neuroscience, De Boelelaan 1117, Amsterdam, The Netherlands
| | - Nelleke Tolboom
- Imaging Division, Department of Radiology, University Medical Center Utrecht, Utrecht, Netherlands
| | - Bart N M van Berckel
- Amsterdam UMC, Vrije Universiteit Amsterdam, Radiology and Nuclear Medicine, Amsterdam Neuroscience, De Boelelaan 1117, Amsterdam, The Netherlands
| | - Maqsood Yaqub
- Amsterdam UMC, Vrije Universiteit Amsterdam, Radiology and Nuclear Medicine, Amsterdam Neuroscience, De Boelelaan 1117, Amsterdam, The Netherlands
| | - Adriaan A Lammertsma
- Amsterdam UMC, Vrije Universiteit Amsterdam, Radiology and Nuclear Medicine, Amsterdam Neuroscience, De Boelelaan 1117, Amsterdam, The Netherlands
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19
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Peretti DE, Renken RJ, Reesink FE, de Jong BM, De Deyn PP, Dierckx RAJO, Doorduin J, Boellaard R, Vállez García D. Feasibility of pharmacokinetic parametric PET images in scaled subprofile modelling using principal component analysis. NEUROIMAGE-CLINICAL 2021; 30:102625. [PMID: 33756179 PMCID: PMC8020472 DOI: 10.1016/j.nicl.2021.102625] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 01/28/2021] [Accepted: 03/05/2021] [Indexed: 11/30/2022]
Abstract
Scaled subprofile model using principal component analysis (SSM/PCA) is a multivariate analysis technique used, mainly in [18F]-2-fluoro-2-deoxy-d-glucose (FDG) PET studies, for the generation of disease-specific metabolic patterns (DP) that may aid with the classification of subjects with neurological disorders, like Alzheimer’s disease (AD). The aim of this study was to explore the feasibility of using quantitative parametric images for this type of analysis, with dynamic [11C]-labelled Pittsburgh Compound B (PIB) PET data as an example. Therefore, 15 AD patients and 15 healthy control subjects were included in an SSM/PCA analysis to generate four AD-DPs using relative cerebral blood flow (R1), binding potential (BPND) and SUVR images derived from dynamic PIB and static FDG-PET studies. Furthermore, 49 new subjects with a variety of neurodegenerative cognitive disorders were tested against these DPs. The AD-DP was characterized by a reduction in the frontal, parietal, and temporal lobes voxel values for R1 and SUVR-FDG DPs; and by a general increase of values in cortical areas for BPND and SUVR-PIB DPs. In conclusion, the results suggest that the combination of parametric images derived from a single dynamic scan might be a good alternative for subject classification instead of using 2 independent PET studies.
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Affiliation(s)
- Débora E Peretti
- University of Groningen, University Medical Center Groningen, Department of Nuclear Medicine and Molecular Imaging, The Netherlands.
| | - Remco J Renken
- University of Groningen, University Medical Center Groningen, Cognitive Neuroscience Centre, Department of Biomedical Sciences of Cell & Systems, The Netherlands
| | - Fransje E Reesink
- University of Groningen, University Medical Center Groningen, Department of Neurology, Alzheimer Research Centre, The Netherlands
| | - Bauke M de Jong
- University of Groningen, University Medical Center Groningen, Department of Neurology, Alzheimer Research Centre, The Netherlands
| | - Peter P De Deyn
- University of Groningen, University Medical Center Groningen, Department of Neurology, Alzheimer Research Centre, The Netherlands; University of Antwerp, Institute Born-Bunge, Laboratory of Neurochemistry and Behaviour, Belgium
| | - Rudi A J O Dierckx
- University of Groningen, University Medical Center Groningen, Department of Nuclear Medicine and Molecular Imaging, The Netherlands
| | - Janine Doorduin
- University of Groningen, University Medical Center Groningen, Department of Nuclear Medicine and Molecular Imaging, The Netherlands
| | - Ronald Boellaard
- University of Groningen, University Medical Center Groningen, Department of Nuclear Medicine and Molecular Imaging, The Netherlands
| | - David Vállez García
- University of Groningen, University Medical Center Groningen, Department of Nuclear Medicine and Molecular Imaging, The Netherlands
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20
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Kolinger GD, Vállez García D, Willemsen ATM, Reesink FE, de Jong BM, Dierckx RAJO, De Deyn PP, Boellaard R. Amyloid burden quantification depends on PET and MR image processing methodology. PLoS One 2021; 16:e0248122. [PMID: 33667281 PMCID: PMC7935288 DOI: 10.1371/journal.pone.0248122] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/18/2020] [Accepted: 02/19/2021] [Indexed: 11/19/2022] Open
Abstract
Quantification of amyloid load with positron emission tomography can be useful to assess Alzheimer's Disease in-vivo. However, quantification can be affected by the image processing methodology applied. This study's goal was to address how amyloid quantification is influenced by different semi-automatic image processing pipelines. Images were analysed in their Native Space and Standard Space; non-rigid spatial transformation methods based on maximum a posteriori approaches and tissue probability maps (TPM) for regularisation were explored. Furthermore, grey matter tissue segmentations were defined before and after spatial normalisation, and also using a population-based template. Five quantification metrics were analysed: two intensity-based, two volumetric-based, and one multi-parametric feature. Intensity-related metrics were not substantially affected by spatial normalisation and did not significantly depend on the grey matter segmentation method, with an impact similar to that expected from test-retest studies (≤10%). Yet, volumetric and multi-parametric features were sensitive to the image processing methodology, with an overall variability up to 45%. Therefore, the analysis should be carried out in Native Space avoiding non-rigid spatial transformations. For analyses in Standard Space, spatial normalisation regularised by TPM is preferred. Volumetric-based measurements should be done in Native Space, while intensity-based metrics are more robust against differences in image processing pipelines.
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Affiliation(s)
- Guilherme D. Kolinger
- Medical Imaging Center, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands
| | - David Vállez García
- Medical Imaging Center, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands
| | - Antoon T. M. Willemsen
- Medical Imaging Center, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands
| | - Fransje E. Reesink
- Department of Neurology, Alzheimer Research Centre, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands
| | - Bauke M. de Jong
- Department of Neurology, Alzheimer Research Centre, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands
| | - Rudi A. J. O. Dierckx
- Medical Imaging Center, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands
| | - Peter P. De Deyn
- Department of Neurology, Alzheimer Research Centre, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands
- Laboratory of Neurochemistry and Behaviour, Institute Born-Bunge, University of Antwerp, Antwerp, Belgium
| | - Ronald Boellaard
- Medical Imaging Center, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands
- Department of Radiology and Nuclear Medicine, Amsterdam University Medical Center, VU Medical Center, Amsterdam, The Netherlands
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21
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Validation of Parametric Methods for [ 11C]UCB-J PET Imaging Using Subcortical White Matter as Reference Tissue. Mol Imaging Biol 2021; 22:444-452. [PMID: 31209780 DOI: 10.1007/s11307-019-01387-6] [Citation(s) in RCA: 24] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/26/2022]
Abstract
PURPOSE The aim of this study was to evaluate different non-invasive methods for generating (R)-1-((3-([11C]methyl)pyridin-4-yl)methyl)-4-(3,4,5-trifluorophenyl)pyrrolidin-2-one) ([11C]UCB-J) parametric maps using white matter (centrum semi-ovale-SO) as reference tissue. PROCEDURES Ten healthy volunteers (8 M/2F; age 27.6 ± 10.0 years) underwent a 90-min dynamic [11C]UCB-J positron emission tomography (PET) scan with full arterial blood sampling and metabolite analysis before and after administration of a novel chemical entity with high affinity for presynaptic synaptic vesicle glycoprotein 2A (SV2A). A simplified reference tissue model (SRTM2), multilinear reference tissue model (MRTM2), and reference Logan graphical analysis (rLGA) were used to generate binding potential maps using SO as reference tissue (BPSO). Shorter dynamic acquisitions down to 50 min were also considered. In addition, standard uptake value ratios (SUVR) relative to SO were evaluated for three post-injection intervals (SUVRSO,40-70min, SUVRSO,50-80min, and SUVRSO,60-90min respectively). Regional parametric BPSO + 1 and SUVRSO were compared with regional distribution volume ratios of a 1-tissue compartment model (1TCM DVRSO) using Spearman correlation and Bland-Altman analysis. RESULTS For all methods, highly significant correlations were found between regional, parametric BPSO + 1 (r = [0.63;0.96]) or SUVRSO (r = [0.90;0.91]) estimates and regional 1TCM DVRSO. For a 90-min dynamic scan, parametric SRTM2 and MRTM2 values presented similar small bias and variability (- 3.0 ± 2.9 % for baseline SRTM2) and outperformed rLGA (- 10.0 ± 5.3 % for baseline rLGA). Reducing the dynamic acquisition to 60 min had limited impact on the bias and variability of parametric SRTM2 BPSO estimates (- 1.0 ± 9.9 % for baseline SRTM2) while a higher variability (- 1.83 ± 10.8 %) for baseline MRTM2 was observed for shorter acquisition times. Both SUVRSO,60-90min and SUVRSO,50-80min showed similar small bias and variability (- 2.8 ± 4.6 % bias for baseline SUVRSO,60-90min). CONCLUSION SRTM2 is the preferred method for a voxelwise analysis of dynamic [11C]UCB-J PET using SO as reference tissue, while reducing the dynamic acquisition to 60 min has limited impact on [11C]UCB-J BPSO parametric maps. For a static PET protocol, both SUVRSO,60-90min and SUVRSO,50-80min images are an excellent proxy for [11C]UCB-J BPSO parametric maps.
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22
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Wang G, Rahmim A, Gunn RN. PET Parametric Imaging: Past, Present, and Future. IEEE TRANSACTIONS ON RADIATION AND PLASMA MEDICAL SCIENCES 2020; 4:663-675. [PMID: 33763624 PMCID: PMC7983029 DOI: 10.1109/trpms.2020.3025086] [Citation(s) in RCA: 35] [Impact Index Per Article: 8.8] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/11/2022]
Abstract
Positron emission tomography (PET) is actively used in a diverse range of applications in oncology, cardiology, and neurology. The use of PET in the clinical setting focuses on static (single time frame) imaging at a specific time-point post radiotracer injection and is typically considered as semi-quantitative; e.g. standardized uptake value (SUV) measures. In contrast, dynamic PET imaging requires increased acquisition times but has the advantage that it measures the full spatiotemporal distribution of a radiotracer and, in combination with tracer kinetic modeling, enables the generation of multiparametric images that more directly quantify underlying biological parameters of interest, such as blood flow, glucose metabolism, and receptor binding. Parametric images have the potential for improved detection and for more accurate and earlier therapeutic response assessment. Parametric imaging with dynamic PET has witnessed extensive research in the past four decades. In this paper, we provide an overview of past and present activities and discuss emerging opportunities in the field of parametric imaging for the future.
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Affiliation(s)
- Guobao Wang
- Department of Radiology, University of California Davis Health, Sacramento, CA 95817, USA
| | - Arman Rahmim
- University of British Columbia, Vancouver, BC, Canada
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Visser D, Wolters EE, Verfaillie SCJ, Coomans EM, Timmers T, Tuncel H, Reimand J, Boellaard R, Windhorst AD, Scheltens P, van der Flier WM, Ossenkoppele R, van Berckel BNM. Tau pathology and relative cerebral blood flow are independently associated with cognition in Alzheimer's disease. Eur J Nucl Med Mol Imaging 2020; 47:3165-3175. [PMID: 32462397 PMCID: PMC7680306 DOI: 10.1007/s00259-020-04831-w] [Citation(s) in RCA: 22] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/23/2019] [Accepted: 04/16/2020] [Indexed: 12/18/2022]
Abstract
Purpose We aimed to investigate associations between tau pathology and relative cerebral blood flow (rCBF), and their relationship with cognition in Alzheimer’s disease (AD), by using a single dynamic [18F]flortaucipir positron emission tomography (PET) scan. Methods Seventy-one subjects with AD (66 ± 8 years, mini-mental state examination (MMSE) 23 ± 4) underwent a dynamic 130-min [18F]flortaucipir PET scan. Cognitive assessment consisted of composite scores of four cognitive domains. For tau pathology and rCBF, receptor parametric mapping (cerebellar gray matter reference region) was used to create uncorrected and partial volume-corrected parametric images of non-displaceable binding potential (BPND) and R1, respectively. (Voxel-wise) linear regressions were used to investigate associations between BPND and/or R1 and cognition. Results Higher [18F]flortaucipir BPND was associated with lower R1 in the lateral temporal, parietal and occipital regions. Higher medial temporal BPND was associated with worse memory, and higher lateral temporal BPND with worse executive functioning and language. Higher parietal BPND was associated with worse executive functioning, language and attention, and higher occipital BPND with lower cognitive scores across all domains. Higher frontal BPND was associated with worse executive function and attention. For [18F]flortaucipir R1, lower values in the lateral temporal and parietal ROIs were associated with worse executive functioning, language and attention, and lower occipital R1 with lower language and attention scores. When [18F]flortaucipir BPND and R1 were modelled simultaneously, associations between lower R1 in the lateral temporal ROI and worse attention remained, as well as for lower parietal R1 and worse executive functioning and attention. Conclusion Tau pathology was associated with locally reduced rCBF. Tau pathology and low rCBF were both independently associated with worse cognitive performance. For tau pathology, these associations spanned widespread neocortex, while for rCBF, independent associations were restricted to lateral temporal and parietal regions and the executive functioning and attention domains. These findings indicate that each biomarker may independently contribute to cognitive impairment in AD. Electronic supplementary material The online version of this article (10.1007/s00259-020-04831-w) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- Denise Visser
- Department of Radiology & Nuclear Medicine, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands.
| | - Emma E Wolters
- Department of Radiology & Nuclear Medicine, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands
- Alzheimer Center Amsterdam, Department of Neurology, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands
| | - Sander C J Verfaillie
- Department of Radiology & Nuclear Medicine, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands
| | - Emma M Coomans
- Department of Radiology & Nuclear Medicine, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands
| | - Tessa Timmers
- Department of Radiology & Nuclear Medicine, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands
- Alzheimer Center Amsterdam, Department of Neurology, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands
| | - Hayel Tuncel
- Department of Radiology & Nuclear Medicine, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands
| | - Juhan Reimand
- Alzheimer Center Amsterdam, Department of Neurology, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands
| | - Ronald Boellaard
- Department of Radiology & Nuclear Medicine, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands
| | - Albert D Windhorst
- Department of Radiology & Nuclear Medicine, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands
| | - Philip Scheltens
- Alzheimer Center Amsterdam, Department of Neurology, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands
| | - Wiesje M van der Flier
- Alzheimer Center Amsterdam, Department of Neurology, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands
- Department of Epidemiology and Biostatistics, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands
| | - Rik Ossenkoppele
- Alzheimer Center Amsterdam, Department of Neurology, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands
- Clinical Memory Research Unit, Lund University, Lund, Sweden
| | - Bart N M van Berckel
- Department of Radiology & Nuclear Medicine, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands
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Correlation of Early-Phase F-18 Florapronal PET with F-18 FDG PET in Alzheimer's Disease and Normal Brain. Nucl Med Mol Imaging 2019; 53:328-333. [PMID: 31723362 DOI: 10.1007/s13139-019-00612-y] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/27/2019] [Revised: 08/26/2019] [Accepted: 09/04/2019] [Indexed: 10/26/2022] Open
Abstract
Purpose F-18 florapronol (FPN) is the commercially recognized beta-amyloid positron emission tomography (PET) radiotracer in Korea. This study compared the early F-18 florapronol PET with F-18 fluorodeoxyglucose (FDG) PET between healthy controls (HC) and Alzheimer's dementia (AD) patients. Methods A total of 29 subjects (15 HC and 14 AD subjects) underwent F-18 FPN PET and F-18 FDG PET. F-18 FDG PET image was acquired from 30 to 60 min and F-18 FPN PET for 0 to 10 min. F-18 FPN and F-18 FDG images were spatially normalized with transformation matrices obtained from individual CT images and standardized uptake value ration (SUVR) from cerebellum area, and the global mean was calculated using PMOD 3.6. Pearson's correlation coefficients between F-18 FDG and early F-18 FPN for predefined cortical brain regions were calculated. Results We compared the F-18 FDG and F-18 FPN for SUVR of a specific region in global mean normalization and cerebellum normalization, and most of the correlation coefficient was higher in global mean normalization. In global mean normalization, the correlation coefficient for SUVR of HC was higher than that of AD in all brain regions. Conclusions Early F-18 FPN study can be used as a proxy marker for the F-18 FDG PET.
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Brown EE, Rashidi-Ranjbar N, Caravaggio F, Gerretsen P, Pollock BG, Mulsant BH, Rajji TK, Fischer CE, Flint A, Mah L, Herrmann N, Bowie CR, Voineskos AN, Graff-Guerrero A. Brain Amyloid PET Tracer Delivery is Related to White Matter Integrity in Patients with Mild Cognitive Impairment. J Neuroimaging 2019; 29:721-729. [PMID: 31270885 DOI: 10.1111/jon.12646] [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: 04/30/2019] [Revised: 05/31/2019] [Accepted: 06/14/2019] [Indexed: 11/28/2022] Open
Abstract
BACKGROUND AND PURPOSE Amyloid deposition, tau neurofibrillary tangles, and cerebrovascular dysfunction are important pathophysiologic features in Alzheimer's disease. Pittsburgh compound B ([11 C]-PIB) is a positron emission tomography (PET) radiotracer used to quantify amyloid deposition in vivo. In addition, certain models of [11 C]-PIB delivery reflect cerebral blood flow rather than amyloid plaques. As cerebral blood flow and perfusion deficits are associated with white matter pathology, we hypothesized that [11 C]-PIB delivery in white matter regions may reflect white matter integrity. METHODS We obtained [11 C]-PIB-PET scans and quantified white matter hyperintensities and global fractional anisotropy on magnetic resonance images as biomarkers of white matter pathology in 34 older participants with mild cognitive impairment with or without a history of major depressive disorder. We analyzed the [11 C]-PIB time-activity curve data with models associated with cerebral blood flow: the early maximum standard uptake value and the relative delivery parameter R1. We used a global white matter region of interest. RESULTS Both of the partial-volume corrected PET parameters were correlated with white matter hyperintensities and fractional anisotropy. CONCLUSION Future studies are warranted to explore whether [11 C]-PIB PET is a "triple biomarker" that may provide information about amyloid deposition, cerebral blood flow, and white matter pathology.
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Affiliation(s)
- Eric E Brown
- Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, Ontario, Canada.,Adult Neurodevelopment and Geriatric Psychiatry Division, Centre for Addiction and Mental Health, Toronto, Ontario, Canada.,Department of Psychiatry, University of Toronto, Toronto, Ontario, Canada.,Institute of Medical Science, University of Toronto, Toronto, Ontario, Canada
| | - Neda Rashidi-Ranjbar
- Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, Ontario, Canada.,Adult Neurodevelopment and Geriatric Psychiatry Division, Centre for Addiction and Mental Health, Toronto, Ontario, Canada.,Department of Psychiatry, University of Toronto, Toronto, Ontario, Canada.,Institute of Medical Science, University of Toronto, Toronto, Ontario, Canada
| | - Fernando Caravaggio
- Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, Ontario, Canada.,Adult Neurodevelopment and Geriatric Psychiatry Division, Centre for Addiction and Mental Health, Toronto, Ontario, Canada
| | - Philip Gerretsen
- Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, Ontario, Canada.,Adult Neurodevelopment and Geriatric Psychiatry Division, Centre for Addiction and Mental Health, Toronto, Ontario, Canada.,Department of Psychiatry, University of Toronto, Toronto, Ontario, Canada.,Institute of Medical Science, University of Toronto, Toronto, Ontario, Canada
| | - Bruce G Pollock
- Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, Ontario, Canada.,Adult Neurodevelopment and Geriatric Psychiatry Division, Centre for Addiction and Mental Health, Toronto, Ontario, Canada.,Department of Psychiatry, University of Toronto, Toronto, Ontario, Canada.,Institute of Medical Science, University of Toronto, Toronto, Ontario, Canada
| | - Benoit H Mulsant
- Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, Ontario, Canada.,Adult Neurodevelopment and Geriatric Psychiatry Division, Centre for Addiction and Mental Health, Toronto, Ontario, Canada.,Department of Psychiatry, University of Toronto, Toronto, Ontario, Canada.,Institute of Medical Science, University of Toronto, Toronto, Ontario, Canada
| | - Tarek K Rajji
- Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, Ontario, Canada.,Adult Neurodevelopment and Geriatric Psychiatry Division, Centre for Addiction and Mental Health, Toronto, Ontario, Canada.,Department of Psychiatry, University of Toronto, Toronto, Ontario, Canada.,Institute of Medical Science, University of Toronto, Toronto, Ontario, Canada.,Temerty Centre for Therapeutic Brain Intervention, Centre for Addiction and Mental Health, Toronto, Ontario, Canada
| | - Corinne E Fischer
- Department of Psychiatry, University of Toronto, Toronto, Ontario, Canada.,Keenan Research Centre for Biomedical Research, St. Michael's Hospital, Toronto, Ontario, Canada
| | - Alastair Flint
- Department of Psychiatry, University of Toronto, Toronto, Ontario, Canada.,Centre for Mental Health, University Health Network, Toronto, Ontario, Canada
| | - Linda Mah
- Department of Psychiatry, University of Toronto, Toronto, Ontario, Canada.,Rotman Research Institute, Baycrest Health Sciences Centre, Toronto, Ontario, Canada
| | - Nathan Herrmann
- Department of Psychiatry, University of Toronto, Toronto, Ontario, Canada.,Sunnybrook Health Sciences Centre, Toronto, Ontario, Canada
| | - Christopher R Bowie
- Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, Ontario, Canada.,Temerty Centre for Therapeutic Brain Intervention, Centre for Addiction and Mental Health, Toronto, Ontario, Canada.,Queen's University, Kingston, Ontario, Canada
| | - Aristotle N Voineskos
- Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, Ontario, Canada.,Adult Neurodevelopment and Geriatric Psychiatry Division, Centre for Addiction and Mental Health, Toronto, Ontario, Canada.,Department of Psychiatry, University of Toronto, Toronto, Ontario, Canada.,Institute of Medical Science, University of Toronto, Toronto, Ontario, Canada
| | - Ariel Graff-Guerrero
- Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, Ontario, Canada.,Adult Neurodevelopment and Geriatric Psychiatry Division, Centre for Addiction and Mental Health, Toronto, Ontario, Canada.,Department of Psychiatry, University of Toronto, Toronto, Ontario, Canada.,Institute of Medical Science, University of Toronto, Toronto, Ontario, Canada
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- Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, Ontario, Canada
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Peretti DE, Vállez García D, Reesink FE, Doorduin J, de Jong BM, De Deyn PP, Dierckx RAJO, Boellaard R. Diagnostic performance of regional cerebral blood flow images derived from dynamic PIB scans in Alzheimer's disease. EJNMMI Res 2019; 9:59. [PMID: 31273465 PMCID: PMC6609664 DOI: 10.1186/s13550-019-0528-3] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/15/2019] [Accepted: 06/20/2019] [Indexed: 12/28/2022] Open
Abstract
BACKGROUND In clinical practice, visual assessment of glucose metabolism images is often used for the diagnosis of Alzheimer's disease (AD) through 2-[18F]-fluoro-2-deoxy-D-glucose (FDG) positron emission tomography (PET) scans. However, visual assessment of the characteristic AD hypometabolic pattern relies on the expertise of the reader. Therefore, user-independent pipelines are preferred to evaluate the images and to classify the subjects. Moreover, glucose consumption is highly correlated with cerebral perfusion. Regional cerebral blood flow (rCBF) images can be derived from dynamic 11C-labelled Pittsburgh Compound B PET scans, which are also used for the assessment of the deposition of amyloid-β plaques on the brain, a fundamental characteristic of AD. The aim of this study was to explore whether these rCBF PIB images could be used for diagnostic purposes through the PMOD Alzheimer's Discrimination Tool. RESULTS Both tracer relative cerebral flow (R1) and early PIB (ePIB) (20-130 s) uptake presented a good correlation when compared to FDG standardized uptake value ratio (SUVR), while ePIB (1-8 min) showed a worse correlation. All receiver operating characteristic curves exhibited a similar shape, with high area under the curve values, and no statistically significant differences were found between curves. However, R1 and ePIB (1-8 min) had the highest sensitivity, while FDG SUVR had the highest specificity. CONCLUSION rCBF images were suggested to be a good surrogate for FDG scans for diagnostic purposes considering an adjusted threshold value.
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Affiliation(s)
- Débora E. Peretti
- Department of Nuclear Medicine and Molecular Imaging, University Medical Center Groningen, University of Groningen, Hanzeplein 1, 9713 GZ Groningen, The Netherlands
| | - David Vállez García
- Department of Nuclear Medicine and Molecular Imaging, University Medical Center Groningen, University of Groningen, Hanzeplein 1, 9713 GZ Groningen, The Netherlands
| | - Fransje E. Reesink
- Department of Neurology, Alzheimer Centrum Groningen, University Medical Center Groningen, University of Groningen, Hanzeplein 1, 9713 GZ Groningen, The Netherlands
| | - Janine Doorduin
- Department of Nuclear Medicine and Molecular Imaging, University Medical Center Groningen, University of Groningen, Hanzeplein 1, 9713 GZ Groningen, The Netherlands
| | - Bauke M. de Jong
- Department of Neurology, Alzheimer Centrum Groningen, University Medical Center Groningen, University of Groningen, Hanzeplein 1, 9713 GZ Groningen, The Netherlands
| | - Peter P. De Deyn
- Department of Neurology, Alzheimer Centrum Groningen, University Medical Center Groningen, University of Groningen, Hanzeplein 1, 9713 GZ Groningen, The Netherlands
- Laboratory of Neurochemistry and Behaviour, Institute Born-Bunge, University of Antwerp, Universiteitsplein 1, 2610 Antwerpen, Belgium
| | - Rudi A. J. O. Dierckx
- Department of Nuclear Medicine and Molecular Imaging, University Medical Center Groningen, University of Groningen, Hanzeplein 1, 9713 GZ Groningen, The Netherlands
| | - Ronald Boellaard
- Department of Nuclear Medicine and Molecular Imaging, University Medical Center Groningen, University of Groningen, Hanzeplein 1, 9713 GZ Groningen, The Netherlands
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Peretti DE, Vállez García D, Reesink FE, van der Goot T, De Deyn PP, de Jong BM, Dierckx RAJO, Boellaard R. Correction: Relative cerebral flow from dynamic PIB scans as an alternative for FDG scans in Alzheimer's disease PET studies. PLoS One 2019; 14:e0214187. [PMID: 30883613 PMCID: PMC6422286 DOI: 10.1371/journal.pone.0214187] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/26/2022] Open
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