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Jovalekic A, Roé-Vellvé N, Koglin N, Quintana ML, Nelson A, Diemling M, Lilja J, Gómez-González JP, Doré V, Bourgeat P, Whittington A, Gunn R, Stephens AW, Bullich S. Validation of quantitative assessment of florbetaben PET scans as an adjunct to the visual assessment across 15 software methods. Eur J Nucl Med Mol Imaging 2023; 50:3276-3289. [PMID: 37300571 PMCID: PMC10542295 DOI: 10.1007/s00259-023-06279-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/27/2023] [Accepted: 05/19/2023] [Indexed: 06/12/2023]
Abstract
PURPOSE Amyloid positron emission tomography (PET) with [18F]florbetaben (FBB) is an established tool for detecting Aβ deposition in the brain in vivo based on visual assessment of PET scans. Quantitative measures are commonly used in the research context and allow continuous measurement of amyloid burden. The aim of this study was to demonstrate the robustness of FBB PET quantification. METHODS This is a retrospective analysis of FBB PET images from 589 subjects. PET scans were quantified with 15 analytical methods using nine software packages (MIMneuro, Hermes BRASS, Neurocloud, Neurology Toolkit, statistical parametric mapping (SPM8), PMOD Neuro, CapAIBL, non-negative matrix factorization (NMF), AmyloidIQ) that used several metrics to estimate Aβ load (SUVR, centiloid, amyloid load, and amyloid index). Six analytical methods reported centiloid (MIMneuro, standard centiloid, Neurology Toolkit, SPM8 (PET only), CapAIBL, NMF). All results were quality controlled. RESULTS The mean sensitivity, specificity, and accuracy were 96.1 ± 1.6%, 96.9 ± 1.0%, and 96.4 ± 1.1%, respectively, for all quantitative methods tested when compared to histopathology, where available. The mean percentage of agreement between binary quantitative assessment across all 15 methods and visual majority assessment was 92.4 ± 1.5%. Assessments of reliability, correlation analyses, and comparisons across software packages showed excellent performance and consistent results between analytical methods. CONCLUSION This study demonstrated that quantitative methods using both CE marked software and other widely available processing tools provided comparable results to visual assessments of FBB PET scans. Software quantification methods, such as centiloid analysis, can complement visual assessment of FBB PET images and could be used in the future for identification of early amyloid deposition, monitoring disease progression and treatment effectiveness.
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Affiliation(s)
| | | | | | | | | | | | | | | | - Vincent Doré
- Department of Molecular Imaging & Therapy, Austin Health, Melbourne, Australia
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2
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Bullich S, Mueller A, De Santi S, Koglin N, Krause S, Kaplow J, Kanekiyo M, Roé-Vellvé N, Perrotin A, Jovalekic A, Scott D, Gee M, Stephens A, Irizarry M. Evaluation of tau deposition using 18F-PI-2620 PET in MCI and early AD subjects—a MissionAD tau sub-study. Alzheimers Res Ther 2022; 14:105. [PMID: 35897078 PMCID: PMC9327167 DOI: 10.1186/s13195-022-01048-x] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/11/2022] [Accepted: 07/11/2022] [Indexed: 11/10/2022]
Abstract
Background The ability of 18F-PI-2620 PET to measure the spatial distribution of tau pathology in Alzheimer’s disease (AD) has been demonstrated in previous studies. The objective of this work was to evaluate tau deposition using 18F-PI-2620 PET in beta-amyloid positive subjects with a diagnosis of mild cognitive impairment (MCI) or mild AD dementia and characterize it with respect to amyloid deposition, cerebrospinal fluid (CSF) assessment, hippocampal volume, and cognition. Methods Subjects with a diagnosis of MCI due to AD or mild AD dementia and a visually amyloid-positive 18F-florbetaben PET scan (n=74, 76 ± 7 years, 38 females) underwent a baseline 18F-PI-2620 PET, T1-weighted magnetic resonance imaging (MRI), CSF assessment (Aβ42/Aβ40 ratio, p-tau, t-tau) (n=22) and several cognitive tests. A 1-year follow-up 18F-PI-2620 PET scans and cognitive assessments were done in 15 subjects. Results Percentage of visually tau-positive scans increased with amyloid-beta deposition measured in 18F-florbetaben Centiloids (CL) (7.7% (<36 CL), 80% (>83 CL)). 18F-PI-2620 standardized uptake value ratio (SUVR) was correlated with increased 18F-florbetaben CL in several regions of interest. Elevated 18F-PI-2620 SUVR (fusiform gyrus) was associated to high CSF p-tau and t-tau (p=0.0006 and p=0.01, respectively). Low hippocampal volume was associated with increased tau load at baseline (p=0.006 (mesial temporal); p=0.01 (fusiform gyrus)). Significant increases in tau SUVR were observed after 12 months, particularly in the mesial temporal cortex, fusiform gyrus, and inferior temporal cortex (p=0.04, p=0.047, p=0.02, respectively). However, no statistically significant increase in amyloid-beta load was measured over the observation time. The MMSE (Recall score), ADAS-Cog14 (Word recognition score), and CBB (One-card learning score) showed the strongest association with tau deposition at baseline. Conclusions The findings support the hypothesis that 18F-PI-2620 PET imaging of neuropathologic tau deposits may reflect underlying neurodegeneration in AD with significant correlations with hippocampal volume, CSF biomarkers, and amyloid-beta load. Furthermore, quantifiable increases in 18F-PI-2620 SUVR over a 12-month period in regions with early tau deposition are consistent with the hypothesis that cortical tau is associated with cognitive impairment. This study supports the utility of 18F-PI-2620 PET to assess tau deposits in an early AD population. Quantifiable tau load and its corresponding increase in early AD cases could be a relevant target engagement marker in clinical trials of anti-amyloid and anti-tau agents. Trial registration Data used in this manuscript belong to a tau PET imaging sub-study of the elenbecestat MissionAD Phase 3 program registered in ClinicalTrials.gov (NCT02956486; NCT03036280). Supplementary Information The online version contains supplementary material available at 10.1186/s13195-022-01048-x.
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Bullich S, Roé-Vellvé N, Marquié M, Landau SM, Barthel H, Villemagne VL, Sanabria Á, Tartari JP, Sotolongo-Grau O, Doré V, Koglin N, Müller A, Perrotin A, Jovalekic A, De Santi S, Tárraga L, Stephens AW, Rowe CC, Sabri O, Seibyl JP, Boada M. Early detection of amyloid load using 18F-florbetaben PET. Alzheimers Res Ther 2021; 13:67. [PMID: 33773598 PMCID: PMC8005243 DOI: 10.1186/s13195-021-00807-6] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 12/23/2020] [Accepted: 03/10/2021] [Indexed: 03/26/2023]
Abstract
BACKGROUND A low amount and extent of Aβ deposition at early stages of Alzheimer's disease (AD) may limit the use of previously developed pathology-proven composite SUVR cutoffs. This study aims to characterize the population with earliest abnormal Aβ accumulation using 18F-florbetaben PET. Quantitative thresholds for the early (SUVRearly) and established (SUVRestab) Aβ deposition were developed, and the topography of early Aβ deposition was assessed. Subsequently, Aβ accumulation over time, progression from mild cognitive impairment (MCI) to AD dementia, and tau deposition were assessed in subjects with early and established Aβ deposition. METHODS The study population consisted of 686 subjects (n = 287 (cognitively normal healthy controls), n = 166 (subjects with subjective cognitive decline (SCD)), n = 129 (subjects with MCI), and n = 101 (subjects with AD dementia)). Three categories in the Aβ-deposition continuum were defined based on the developed SUVR cutoffs: Aβ-negative subjects, subjects with early Aβ deposition ("gray zone"), and subjects with established Aβ pathology. RESULTS SUVR using the whole cerebellum as the reference region and centiloid (CL) cutoffs for early and established amyloid pathology were 1.10 (13.5 CL) and 1.24 (35.7 CL), respectively. Cingulate cortices and precuneus, frontal, and inferior lateral temporal cortices were the regions showing the initial pathological tracer retention. Subjects in the "gray zone" or with established Aβ pathology accumulated more amyloid over time than Aβ-negative subjects. After a 4-year clinical follow-up, none of the Aβ-negative or the gray zone subjects progressed to AD dementia while 91% of the MCI subjects with established Aβ pathology progressed. Tau deposition was infrequent in those subjects without established Aβ pathology. CONCLUSIONS This study supports the utility of using two cutoffs for amyloid PET abnormality defining a "gray zone": a lower cutoff of 13.5 CL indicating emerging Aβ pathology and a higher cutoff of 35.7 CL where amyloid burden levels correspond to established neuropathology findings. These cutoffs define a subset of subjects characterized by pre-AD dementia levels of amyloid burden that precede other biomarkers such as tau deposition or clinical symptoms and accelerated amyloid accumulation. The determination of different amyloid loads, particularly low amyloid levels, is useful in determining who will eventually progress to dementia. Quantitation of amyloid provides a sensitive measure in these low-load cases and may help to identify a group of subjects most likely to benefit from intervention. TRIAL REGISTRATION Data used in this manuscript belong to clinical trials registered in ClinicalTrials.gov ( NCT00928304 , NCT00750282 , NCT01138111 , NCT02854033 ) and EudraCT (2014-000798-38).
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Affiliation(s)
- Santiago Bullich
- Life Molecular Imaging GmbH, Tegeler Str. 6-7, 13353, Berlin, Germany.
| | - Núria Roé-Vellvé
- Life Molecular Imaging GmbH, Tegeler Str. 6-7, 13353, Berlin, Germany
| | - Marta Marquié
- Fundació ACE Institut Català de Neurociències Aplicades, Research Center and Memory Unit - Universitat Internacional de Catalunya (UIC), Barcelona, Spain.,Centro de Investigación Biomédica en Red Enfermedades Neurodegenerativas (CIBERNED), Instituto de Salud Carlos III, Madrid, Spain
| | - Susan M Landau
- Helen Wills Neuroscience Institute, University of California, Berkeley and Lawrence Berkeley National Laboratory, Berkeley, CA, USA
| | - Henryk Barthel
- Department of Nuclear Medicine, University Hospital Leipzig, Leipzig, Germany
| | - Victor L Villemagne
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA, USA.,Departments of Medicine and Molecular Imaging, University of Melbourne, Austin Health, Melbourne, Victoria, Australia
| | - Ángela Sanabria
- Fundació ACE Institut Català de Neurociències Aplicades, Research Center and Memory Unit - Universitat Internacional de Catalunya (UIC), Barcelona, Spain.,Centro de Investigación Biomédica en Red Enfermedades Neurodegenerativas (CIBERNED), Instituto de Salud Carlos III, Madrid, Spain
| | - Juan Pablo Tartari
- Fundació ACE Institut Català de Neurociències Aplicades, Research Center and Memory Unit - Universitat Internacional de Catalunya (UIC), Barcelona, Spain
| | - Oscar Sotolongo-Grau
- Fundació ACE Institut Català de Neurociències Aplicades, Research Center and Memory Unit - Universitat Internacional de Catalunya (UIC), Barcelona, Spain
| | - Vincent Doré
- Departments of Medicine and Molecular Imaging, University of Melbourne, Austin Health, Melbourne, Victoria, Australia.,The Australian e-Health Research Centre, Health and Biosecurity, CSIRO, Melbourne, Victoria, Australia
| | - Norman Koglin
- Life Molecular Imaging GmbH, Tegeler Str. 6-7, 13353, Berlin, Germany
| | - Andre Müller
- Life Molecular Imaging GmbH, Tegeler Str. 6-7, 13353, Berlin, Germany
| | - Audrey Perrotin
- Life Molecular Imaging GmbH, Tegeler Str. 6-7, 13353, Berlin, Germany
| | | | | | - Lluís Tárraga
- Fundació ACE Institut Català de Neurociències Aplicades, Research Center and Memory Unit - Universitat Internacional de Catalunya (UIC), Barcelona, Spain.,Centro de Investigación Biomédica en Red Enfermedades Neurodegenerativas (CIBERNED), Instituto de Salud Carlos III, Madrid, Spain
| | - Andrew W Stephens
- Life Molecular Imaging GmbH, Tegeler Str. 6-7, 13353, Berlin, Germany
| | - Christopher C Rowe
- Departments of Medicine and Molecular Imaging, University of Melbourne, Austin Health, Melbourne, Victoria, Australia
| | - Osama Sabri
- Department of Nuclear Medicine, University Hospital Leipzig, Leipzig, Germany
| | | | - Mercè Boada
- Fundació ACE Institut Català de Neurociències Aplicades, Research Center and Memory Unit - Universitat Internacional de Catalunya (UIC), Barcelona, Spain.,Centro de Investigación Biomédica en Red Enfermedades Neurodegenerativas (CIBERNED), Instituto de Salud Carlos III, Madrid, Spain
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4
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Roé‐Vellvé N, Bullich S, Marquie M, Barthel H, Villemagne VLL, Sanabria A, Tartari JP, Sotolongo‐Grau O, Dore V, Koglin N, Mueller A, Perrotin A, Jovalekic A, de Santi S, Tarraga L, Stephens AW, Rowe CC, Sabri O, Seibyl J, Boada M. Quantitative thresholds for
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F‐florbetaben PET for the detection of low amyloid load. Alzheimers Dement 2020. [DOI: 10.1002/alz.042933] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/06/2022]
Affiliation(s)
- Núria Roé‐Vellvé
- Life Molecular Imaging GmbH Berlin Germany
- On behalf of the AMYPAD consortium Brussels Belgium
| | - Santiago Bullich
- Life Molecular Imaging GmbH Berlin Germany
- On behalf of the AMYPAD consortium Brussels Belgium
| | - Marta Marquie
- On behalf of the AMYPAD consortium Brussels Belgium
- Research Center and Memory Clinic, Fundació ACE Institut Català de Neurociències Aplicades Universitat Internacional de Catalunya (UIC) Barcelona Spain
- CIBERNED, Network Center for Biomedical Research in Neurodegenerative Diseases National Institute of Health Carlos III Madrid Spain
- FACEHBI Study Group Barcelona Spain
| | - Henryk Barthel
- Department of Nuclear Medicine University of Leipzig Leipzig Germany
| | - Victor LL Villemagne
- Departments of Medicine and Molecular Imaging University of Melbourne, Austin Health Melbourne Australia
| | - Angela Sanabria
- CIBERNED, Network Center for Biomedical Research in Neurodegenerative Diseases National Institute of Health Carlos III Madrid Spain
- FACEHBI Study Group Barcelona Spain
- Research Center and Memory Clinic Fundació ACE Institut Català de Neurociències Aplicades Universitat Internacional de Catalunya Barcelona Spain
| | - Juan Pablo Tartari
- FACEHBI Study Group Barcelona Spain
- Research Center and Memory Clinic Fundació ACE Institut Català de Neurociències Aplicades Universitat Internacional de Catalunya Barcelona Spain
| | - Oscar Sotolongo‐Grau
- FACEHBI Study Group Barcelona Spain
- Research Center and Memory Clinic Fundació ACE Institut Català de Neurociències Aplicades Universitat Internacional de Catalunya Barcelona Spain
| | - Vincent Dore
- Departments of Medicine and Molecular Imaging University of Melbourne, Austin Health Melbourne Australia
| | - Norman Koglin
- Life Molecular Imaging GmbH Berlin Germany
- On behalf of the AMYPAD consortium Brussels Belgium
| | - Andre Mueller
- Life Molecular Imaging GmbH Berlin Germany
- On behalf of the AMYPAD consortium Brussels Belgium
| | - Audrey Perrotin
- Life Molecular Imaging GmbH Berlin Germany
- On behalf of the AMYPAD consortium Brussels Belgium
| | - Aleksandar Jovalekic
- Life Molecular Imaging GmbH Berlin Germany
- On behalf of the AMYPAD consortium Brussels Belgium
| | | | - Lluis Tarraga
- On behalf of the AMYPAD consortium Brussels Belgium
- Research Center and Memory Clinic, Fundació ACE Institut Català de Neurociències Aplicades Universitat Internacional de Catalunya (UIC) Barcelona Spain
- CIBERNED, Network Center for Biomedical Research in Neurodegenerative Diseases National Institute of Health Carlos III Madrid Spain
- FACEHBI Study Group Barcelona Spain
| | - Andrew W Stephens
- Life Molecular Imaging GmbH Berlin Germany
- On behalf of the AMYPAD consortium Brussels Belgium
| | - Christopher C Rowe
- Departments of Medicine and Molecular Imaging University of Melbourne, Austin Health Melbourne Australia
| | - Osama Sabri
- Department of Nuclear Medicine University of Leipzig Leipzig Germany
| | | | - Mercè Boada
- Research Center and Memory Clinic, Fundació ACE Institut Català de Neurociències Aplicades Universitat Internacional de Catalunya (UIC) Barcelona Spain
- CIBERNED, Network Center for Biomedical Research in Neurodegenerative Diseases National Institute of Health Carlos III Madrid Spain
- FACEHBI Study Group Barcelona Spain
- ACE Foundation Barcelona Spain
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5
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Sabbagh MN, Schäuble B, Anand K, Richards D, Murayama S, Akatsu H, Takao M, Rowe CC, Masters CL, Barthel H, Gertz HJ, Peters O, Rasgon N, Jovalekic A, Sabri O, Schulz-Schaeffer WJ, Seibyl J. Histopathology and Florbetaben PET in Patients Incorrectly Diagnosed with Alzheimer's Disease. J Alzheimers Dis 2018; 56:441-446. [PMID: 27983552 DOI: 10.3233/jad-160821] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
Abstract
Of 57 individuals diagnosed with Alzheimer's disease (AD) in a phase III study, 13 (23%) had amyloid-β (Aβ) levels on postmortem histopathology that did not explain the dementia. Based on postmortem histopathology, a wide range of different non-AD conditions was identified, including frontotemporal dementia, hippocampal sclerosis, and dementia with Lewy bodies. Of the histopathologically Aβ negative scored cases ante-mortem Florbetaben PET scans were classified as negative for Aβ in 11 patients based on visual analysis and in all 12 quantifiable cases based on composite standardized uptake value ratios. Thus, florbetaben PET can assist physicians in the differential diagnosis of neurodegenerative disorders by reliably excluding Aβ pathology.
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Affiliation(s)
- Marwan N Sabbagh
- Alzheimer's and Memory Disorders Division, Barrow Neurological Institute, Phoenix, AZ, USA
| | | | - Keshav Anand
- Alzheimer's and Memory Disorders Division, Barrow Neurological Institute, Phoenix, AZ, USA
| | | | - Shigeo Murayama
- Tokyo Metropolitan Geriatric Hospital, Tokyo, Japan.,Tokyo Metropolitan Institute of Gerontology, Tokyo, Japan
| | - Hiroyasu Akatsu
- Fukushimura Hospital, Toyohashi, Japan.,Departments of Community-based Medicine and Neurology, Nagoya City University Graduate School of Medical Sciences, Nagoya City, Aichi, Japan
| | - Masaki Takao
- Tokyo Metropolitan Institute of Gerontology, Tokyo, Japan.,Mihara Memorial Hospital, Isesaki, Japan
| | | | - Colin L Masters
- The Florey Institute, The University of Melbourne, Australia
| | - Henryk Barthel
- Department of Nuclear Medicine, Leipzig University, Leipzig, Germany
| | | | - Oliver Peters
- Department of Psychiatry and Psychotherapy, Charité Berlin, Berlin, Germany
| | - Natalie Rasgon
- Department of Psychiatry, Stanford School of Medicine, Stanford, USA
| | | | - Osama Sabri
- Department of Nuclear Medicine, Leipzig University, Leipzig, Germany
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6
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Bullich S, Barthel H, Koglin N, Becker GA, De Santi S, Jovalekic A, Stephens AW, Sabri O. Validation of Noninvasive Tracer Kinetic Analysis of 18F-Florbetaben PET Using a Dual-Time-Window Acquisition Protocol. J Nucl Med 2017; 59:1104-1110. [PMID: 29175981 DOI: 10.2967/jnumed.117.200964] [Citation(s) in RCA: 20] [Impact Index Per Article: 2.9] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/25/2017] [Accepted: 11/10/2017] [Indexed: 11/16/2022] Open
Abstract
Accurate amyloid PET quantification is necessary for monitoring amyloid-β accumulation and response to therapy. Currently, most of the studies are analyzed using the static SUV ratio (SUVR) approach because of its simplicity. However, this approach may be influenced by changes in cerebral blood flow (CBF) or radiotracer clearance. Full tracer kinetic models require arterial blood sampling and dynamic image acquisition. The objectives of this work were, first, to validate a noninvasive kinetic modeling approach for 18F-florbetaben PET using an acquisition protocol with the best compromise between quantification accuracy and simplicity and, second, to assess the impact of CBF changes and radiotracer clearance on SUVRs and noninvasive kinetic modeling data in 18F-florbetaben PET. Methods: Using data from 20 subjects (10 patients with probable Alzheimer dementia and 10 healthy volunteers), the nondisplaceable binding potential (BPND) obtained from the full kinetic analysis was compared with the SUVR and with noninvasive tracer kinetic methods (simplified reference tissue model and multilinear reference tissue model 2). Various approaches using shortened or interrupted acquisitions were compared with the results of the full acquisition (0-140 min). Simulations were performed to assess the effect of CBF and radiotracer clearance changes on SUVRs and noninvasive kinetic modeling outputs. Results: An acquisition protocol using time windows of 0-30 and 120-140 min with appropriate interpolation of the missing time points provided the best compromise between patient comfort and quantification accuracy. Excellent agreement was found between BPND obtained using the full protocol and BPND obtained using the dual-window protocol (for multilinear reference tissue model 2, BPND [dual-window] = 0.01 + 1.00·BPND [full], R2 = 0.97; for simplified reference tissue model, BPND [dual-window] = 0.05 + 0.92·BPND [full], R2 = 0.93). Simulations showed a limited impact of CBF and radiotracer clearance changes on multilinear reference tissue model parameters and SUVR. Conclusion: This study demonstrated accurate noninvasive kinetic modeling of 18F-florbetaben PET data using a dual-window acquisition, thus providing a good compromise between quantification accuracy, scan duration, and patient burden. The influence of CBF and radiotracer clearance changes on amyloid-β load estimates was small. For most clinical research applications, the SUVR approach is appropriate. However, for longitudinal studies in which maximum quantification accuracy is desired, this noninvasive dual-window acquisition with kinetic analysis is recommended.
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Affiliation(s)
| | - Henryk Barthel
- Department of Nuclear Medicine, University Hospital Leipzig, Leipzig, Germany; and
| | | | - Georg A Becker
- Department of Nuclear Medicine, University Hospital Leipzig, Leipzig, Germany; and
| | | | | | | | - Osama Sabri
- Department of Nuclear Medicine, University Hospital Leipzig, Leipzig, Germany; and
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7
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Ceccaldi M, Jonveaux T, Verger A, Krolak‐Salmon P, Houzard C, Godefroy O, Shields T, Perrotin A, Gismondi R, Bullich S, Jovalekic A, Raffa N, Pasquier F, Semah F, Dubois B, Habert M, Wallon D, Chastan M, Payoux P, Ceccaldi M, Guedj E, Ceccaldi M, Felician O, Didic M, Gueriot C, Koric L, Kletchkova‐Gantchev R, Guedj E, Godefroy O, Andriuta D, Devendeville A, Dupuis D, Binot I, Barbay M, Meyer M, Moullard V, Magnin E, Chamard L, Haffen S, Morel O, Drouet C, Boulahdour H, Goas P, Querellou‐Lefranc S, Sayette V, Cogez J, Branger P, Agostini D, Manrique A, Rouaud O, Bejot Y, Jacquin‐Piques A, Dygai‐Cochet I, Berriolo‐Riedinger A, Moreaud O, Sauvee M, Crépin CG, Pasquier F, Bombois S, Lebouvier T, Mackowiak‐Cordoliani M, Deramecourt V, Rollin‐Sillaire A, Cassagnaud‐Thuillet P, Chen Y, Semah F, Petyt G, Krolak‐Salmon P, Federico D, Danaila KL, Guilhermet Y, Magnier C, Makaroff Z, Rouch I, Xie J, Roubaud C, Coste M, David K, Sarciron A, Waissi AS, Scheiber C, Houzard C, Gabelle‐Deloustal A, Bennys K, Marelli C, Touati L, Mariano‐Goulart D, Verbizier‐Lonjon D, Jonveaux T, Benetos A, Kearney‐Schwartz A, Perret‐Guillaume C, Verger A, Vercelletto M, Boutoleau‐Bretonniere C, Pouclet‐Courtemanche H, Wagemann N, Pallardy A, Hugon J, Paquet C, Dumurgier J, Millet P, Queneau M, Dubois B, Epelbaum S, Levy M, Habert M, Novella J, Jaidi Y, Papathanassiou D, Morland D, Belliard S, Salmon A, Lejeune F, Hannequin D, Wallon D, Martinaud O, Zarea A, Chastan M, Pariente J, Thalamas C, Galitzky‐Gerber M, Tricoire Ricard A, Calvas F, Rigal E, Payoux P, Hitzel A, Delrieu J, Ousset P, Lala F, Sastre‐Hengan N, Stephens A, Guedj E. Added value of
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F‐florbetaben amyloid PET in the diagnostic workup of most complex patients with dementia in France: A naturalistic study. Alzheimers Dement 2017; 14:293-305. [DOI: 10.1016/j.jalz.2017.09.009] [Citation(s) in RCA: 39] [Impact Index Per Article: 5.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/02/2017] [Revised: 08/29/2017] [Accepted: 09/06/2017] [Indexed: 11/25/2022]
Affiliation(s)
- Mathieu Ceccaldi
- AP‐HM–Hôpital de la Timone, Neurology and Neuropsychology Department Aix Marseille University, Inserm, INS, Institut de Neurosciences des Systèmes Marseille France
| | - Thérèse Jonveaux
- Geriatric Department CHRU de Nancy–Hôpital Brabois Vandoeuvre‐les‐Nancy France
| | - Antoine Verger
- INSERM U947 Unité d'Imagerie Adaptative Diagnostique et Interventionnelle Nancy France
| | - Pierre Krolak‐Salmon
- Clinical and Research Memory Center of Lyon Hospices civils de Lyon, Université Claude Bernard Lyon 1 Inserm 1028 Lyon France
| | | | - Olivier Godefroy
- Neurology Department CHU Amiens Picardie–Hôpital Sud Amiens France
| | - Trevor Shields
- Nuclear Medicine Department CHU Amiens Picardie–Hôpital Sud Amiens France
| | - Audrey Perrotin
- Piramal Imaging Clinical Research and Development Berlin Germany
| | | | - Santiago Bullich
- AP‐HP–Hôpital Pitié Salpétrière Memory and Alzheimer Disease Institute IM2A Paris France
| | - Aleksandar Jovalekic
- Laboratoire d'Imagerie Biomédicale Sorbonne Universités, UPMC Univ Paris 06, Inserm U 1146, CNRS UMR 7371 Paris France
| | - Nicola Raffa
- AP‐HM–Hôpital de la Timone, Neurology and Neuropsychology Department Aix Marseille University, Inserm, INS, Institut de Neurosciences des Systèmes Marseille France
| | - Florence Pasquier
- AP‐HM–Hôpital de la Timone, Neurology and Neuropsychology Department Aix Marseille University, Inserm, INS, Institut de Neurosciences des Systèmes Marseille France
| | - Franck Semah
- AP‐HM–Hôpital de la Timone, Neurology and Neuropsychology Department Aix Marseille University, Inserm, INS, Institut de Neurosciences des Systèmes Marseille France
| | - Bruno Dubois
- AP‐HM–Hôpital de la Timone, Neurology and Neuropsychology Department Aix Marseille University, Inserm, INS, Institut de Neurosciences des Systèmes Marseille France
| | - Marie‐Odile Habert
- AP‐HM–Hôpital de la Timone, Neurology and Neuropsychology Department Aix Marseille University, Inserm, INS, Institut de Neurosciences des Systèmes Marseille France
| | - David Wallon
- AP‐HM–Hôpital de la Timone, Neurology and Neuropsychology Department Aix Marseille University, Inserm, INS, Institut de Neurosciences des Systèmes Marseille France
| | - Mathieu Chastan
- AP‐HM–Hôpital de la Timone, Neurology and Neuropsychology Department Aix Marseille University, Inserm, INS, Institut de Neurosciences des Systèmes Marseille France
| | - Pierre Payoux
- AP‐HM–Hôpital de la Timone, Neurology and Neuropsychology Department Aix Marseille University, Inserm, INS, Institut de Neurosciences des Systèmes Marseille France
| | - Mathieu Ceccaldi
- AP‐HM–Hôpital de la Timone, Neurology and Neuropsychology Department Aix Marseille University, Inserm, INS, Institut de Neurosciences des Systèmes Marseille France
| | - Eric Guedj
- AP‐HM–Hôpital de la Timone, Neurology and Neuropsychology Department Aix Marseille University, Inserm, INS, Institut de Neurosciences des Systèmes Marseille France
| | - Mathieu Ceccaldi
- AP‐HM–Hôpital de la Timone, Neurology and Neuropsychology Department Aix Marseille University, Inserm, INS, Institut de Neurosciences des Systèmes Marseille France
| | - Olivier Felician
- AP‐HM–Hôpital de la Timone, Neurology and Neuropsychology Department Aix Marseille University, Inserm, INS, Institut de Neurosciences des Systèmes Marseille France
| | - Mira Didic
- AP‐HM–Hôpital de la Timone, Neurology and Neuropsychology Department Aix Marseille University, Inserm, INS, Institut de Neurosciences des Systèmes Marseille France
| | - Claude Gueriot
- AP‐HM–Hôpital de la Timone, Neurology and Neuropsychology Department Aix Marseille University, Inserm, INS, Institut de Neurosciences des Systèmes Marseille France
| | - Lejla Koric
- AP‐HM–Hôpital de la Timone, Neurology and Neuropsychology Department Aix Marseille University, Inserm, INS, Institut de Neurosciences des Systèmes Marseille France
| | - Radka Kletchkova‐Gantchev
- AP‐HM–Hôpital de la Timone, Neurology and Neuropsychology Department Aix Marseille University, Inserm, INS, Institut de Neurosciences des Systèmes Marseille France
| | - Eric Guedj
- AP‐HM–Hôpital de la Timone, Neurology and Neuropsychology Department Aix Marseille University, Inserm, INS, Institut de Neurosciences des Systèmes Marseille France
| | - Olivier Godefroy
- AP‐HM–Hôpital de la Timone, Neurology and Neuropsychology Department Aix Marseille University, Inserm, INS, Institut de Neurosciences des Systèmes Marseille France
| | - Daniela Andriuta
- AP‐HM–Hôpital de la Timone, Neurology and Neuropsychology Department Aix Marseille University, Inserm, INS, Institut de Neurosciences des Systèmes Marseille France
| | - Agnès Devendeville
- AP‐HM–Hôpital de la Timone, Neurology and Neuropsychology Department Aix Marseille University, Inserm, INS, Institut de Neurosciences des Systèmes Marseille France
| | - Diane Dupuis
- AP‐HM–Hôpital de la Timone, Neurology and Neuropsychology Department Aix Marseille University, Inserm, INS, Institut de Neurosciences des Systèmes Marseille France
| | - Ingrid Binot
- AP‐HM–Hôpital de la Timone, Neurology and Neuropsychology Department Aix Marseille University, Inserm, INS, Institut de Neurosciences des Systèmes Marseille France
| | - Mélanie Barbay
- AP‐HM–Hôpital de la Timone, Neurology and Neuropsychology Department Aix Marseille University, Inserm, INS, Institut de Neurosciences des Systèmes Marseille France
| | - Marc‐Etienne Meyer
- AP‐HM–Hôpital de la Timone, Neurology and Neuropsychology Department Aix Marseille University, Inserm, INS, Institut de Neurosciences des Systèmes Marseille France
| | - Véronique Moullard
- AP‐HM–Hôpital de la Timone, Neurology and Neuropsychology Department Aix Marseille University, Inserm, INS, Institut de Neurosciences des Systèmes Marseille France
| | - Eloi Magnin
- AP‐HM–Hôpital de la Timone, Neurology and Neuropsychology Department Aix Marseille University, Inserm, INS, Institut de Neurosciences des Systèmes Marseille France
| | - Ludivine Chamard
- AP‐HM–Hôpital de la Timone, Neurology and Neuropsychology Department Aix Marseille University, Inserm, INS, Institut de Neurosciences des Systèmes Marseille France
| | - Sophie Haffen
- AP‐HM–Hôpital de la Timone, Neurology and Neuropsychology Department Aix Marseille University, Inserm, INS, Institut de Neurosciences des Systèmes Marseille France
| | - Olivier Morel
- AP‐HM–Hôpital de la Timone, Neurology and Neuropsychology Department Aix Marseille University, Inserm, INS, Institut de Neurosciences des Systèmes Marseille France
| | - Clément Drouet
- AP‐HM–Hôpital de la Timone, Neurology and Neuropsychology Department Aix Marseille University, Inserm, INS, Institut de Neurosciences des Systèmes Marseille France
| | - Hatem Boulahdour
- AP‐HM–Hôpital de la Timone, Neurology and Neuropsychology Department Aix Marseille University, Inserm, INS, Institut de Neurosciences des Systèmes Marseille France
| | - Philippe Goas
- AP‐HM–Hôpital de la Timone, Neurology and Neuropsychology Department Aix Marseille University, Inserm, INS, Institut de Neurosciences des Systèmes Marseille France
| | - Solène Querellou‐Lefranc
- AP‐HM–Hôpital de la Timone, Neurology and Neuropsychology Department Aix Marseille University, Inserm, INS, Institut de Neurosciences des Systèmes Marseille France
| | - Vincent Sayette
- AP‐HM–Hôpital de la Timone, Neurology and Neuropsychology Department Aix Marseille University, Inserm, INS, Institut de Neurosciences des Systèmes Marseille France
| | - Julien Cogez
- AP‐HM–Hôpital de la Timone, Neurology and Neuropsychology Department Aix Marseille University, Inserm, INS, Institut de Neurosciences des Systèmes Marseille France
| | - Pierre Branger
- AP‐HM–Hôpital de la Timone, Neurology and Neuropsychology Department Aix Marseille University, Inserm, INS, Institut de Neurosciences des Systèmes Marseille France
| | - Denis Agostini
- AP‐HM–Hôpital de la Timone, Neurology and Neuropsychology Department Aix Marseille University, Inserm, INS, Institut de Neurosciences des Systèmes Marseille France
| | - Alain Manrique
- AP‐HM–Hôpital de la Timone, Neurology and Neuropsychology Department Aix Marseille University, Inserm, INS, Institut de Neurosciences des Systèmes Marseille France
| | - Olivier Rouaud
- AP‐HM–Hôpital de la Timone, Neurology and Neuropsychology Department Aix Marseille University, Inserm, INS, Institut de Neurosciences des Systèmes Marseille France
| | - Yannick Bejot
- AP‐HM–Hôpital de la Timone, Neurology and Neuropsychology Department Aix Marseille University, Inserm, INS, Institut de Neurosciences des Systèmes Marseille France
| | - Agnès Jacquin‐Piques
- AP‐HM–Hôpital de la Timone, Neurology and Neuropsychology Department Aix Marseille University, Inserm, INS, Institut de Neurosciences des Systèmes Marseille France
| | - Inna Dygai‐Cochet
- AP‐HM–Hôpital de la Timone, Neurology and Neuropsychology Department Aix Marseille University, Inserm, INS, Institut de Neurosciences des Systèmes Marseille France
| | - Alina Berriolo‐Riedinger
- AP‐HM–Hôpital de la Timone, Neurology and Neuropsychology Department Aix Marseille University, Inserm, INS, Institut de Neurosciences des Systèmes Marseille France
| | - Olivier Moreaud
- AP‐HM–Hôpital de la Timone, Neurology and Neuropsychology Department Aix Marseille University, Inserm, INS, Institut de Neurosciences des Systèmes Marseille France
| | - Mathilde Sauvee
- AP‐HM–Hôpital de la Timone, Neurology and Neuropsychology Department Aix Marseille University, Inserm, INS, Institut de Neurosciences des Systèmes Marseille France
| | - Céline Gallazzani Crépin
- AP‐HM–Hôpital de la Timone, Neurology and Neuropsychology Department Aix Marseille University, Inserm, INS, Institut de Neurosciences des Systèmes Marseille France
| | - Florence Pasquier
- AP‐HM–Hôpital de la Timone, Neurology and Neuropsychology Department Aix Marseille University, Inserm, INS, Institut de Neurosciences des Systèmes Marseille France
| | - Stéphanie Bombois
- AP‐HM–Hôpital de la Timone, Neurology and Neuropsychology Department Aix Marseille University, Inserm, INS, Institut de Neurosciences des Systèmes Marseille France
| | - Thibaud Lebouvier
- AP‐HM–Hôpital de la Timone, Neurology and Neuropsychology Department Aix Marseille University, Inserm, INS, Institut de Neurosciences des Systèmes Marseille France
| | - Marie‐Anne Mackowiak‐Cordoliani
- AP‐HM–Hôpital de la Timone, Neurology and Neuropsychology Department Aix Marseille University, Inserm, INS, Institut de Neurosciences des Systèmes Marseille France
| | - Vincent Deramecourt
- AP‐HM–Hôpital de la Timone, Neurology and Neuropsychology Department Aix Marseille University, Inserm, INS, Institut de Neurosciences des Systèmes Marseille France
| | - Adeline Rollin‐Sillaire
- AP‐HM–Hôpital de la Timone, Neurology and Neuropsychology Department Aix Marseille University, Inserm, INS, Institut de Neurosciences des Systèmes Marseille France
| | - Pascaline Cassagnaud‐Thuillet
- AP‐HM–Hôpital de la Timone, Neurology and Neuropsychology Department Aix Marseille University, Inserm, INS, Institut de Neurosciences des Systèmes Marseille France
| | - Yaohua Chen
- AP‐HM–Hôpital de la Timone, Neurology and Neuropsychology Department Aix Marseille University, Inserm, INS, Institut de Neurosciences des Systèmes Marseille France
| | - Franck Semah
- AP‐HM–Hôpital de la Timone, Neurology and Neuropsychology Department Aix Marseille University, Inserm, INS, Institut de Neurosciences des Systèmes Marseille France
| | - Grégory Petyt
- AP‐HM–Hôpital de la Timone, Neurology and Neuropsychology Department Aix Marseille University, Inserm, INS, Institut de Neurosciences des Systèmes Marseille France
| | - Pierre Krolak‐Salmon
- AP‐HM–Hôpital de la Timone, Neurology and Neuropsychology Department Aix Marseille University, Inserm, INS, Institut de Neurosciences des Systèmes Marseille France
| | - Denis Federico
- AP‐HM–Hôpital de la Timone, Neurology and Neuropsychology Department Aix Marseille University, Inserm, INS, Institut de Neurosciences des Systèmes Marseille France
| | - Keren Liora Danaila
- AP‐HM–Hôpital de la Timone, Neurology and Neuropsychology Department Aix Marseille University, Inserm, INS, Institut de Neurosciences des Systèmes Marseille France
| | - Yves Guilhermet
- AP‐HM–Hôpital de la Timone, Neurology and Neuropsychology Department Aix Marseille University, Inserm, INS, Institut de Neurosciences des Systèmes Marseille France
| | - Christophe Magnier
- AP‐HM–Hôpital de la Timone, Neurology and Neuropsychology Department Aix Marseille University, Inserm, INS, Institut de Neurosciences des Systèmes Marseille France
| | - Zaza Makaroff
- AP‐HM–Hôpital de la Timone, Neurology and Neuropsychology Department Aix Marseille University, Inserm, INS, Institut de Neurosciences des Systèmes Marseille France
| | - Isabelle Rouch
- AP‐HM–Hôpital de la Timone, Neurology and Neuropsychology Department Aix Marseille University, Inserm, INS, Institut de Neurosciences des Systèmes Marseille France
| | - Jing Xie
- AP‐HM–Hôpital de la Timone, Neurology and Neuropsychology Department Aix Marseille University, Inserm, INS, Institut de Neurosciences des Systèmes Marseille France
| | - Caroline Roubaud
- AP‐HM–Hôpital de la Timone, Neurology and Neuropsychology Department Aix Marseille University, Inserm, INS, Institut de Neurosciences des Systèmes Marseille France
| | - Marie‐Hélène Coste
- AP‐HM–Hôpital de la Timone, Neurology and Neuropsychology Department Aix Marseille University, Inserm, INS, Institut de Neurosciences des Systèmes Marseille France
| | - Kenny David
- AP‐HM–Hôpital de la Timone, Neurology and Neuropsychology Department Aix Marseille University, Inserm, INS, Institut de Neurosciences des Systèmes Marseille France
| | - Alain Sarciron
- AP‐HM–Hôpital de la Timone, Neurology and Neuropsychology Department Aix Marseille University, Inserm, INS, Institut de Neurosciences des Systèmes Marseille France
| | - Aziza Sediq Waissi
- AP‐HM–Hôpital de la Timone, Neurology and Neuropsychology Department Aix Marseille University, Inserm, INS, Institut de Neurosciences des Systèmes Marseille France
| | - Christian Scheiber
- AP‐HM–Hôpital de la Timone, Neurology and Neuropsychology Department Aix Marseille University, Inserm, INS, Institut de Neurosciences des Systèmes Marseille France
| | - Claire Houzard
- AP‐HM–Hôpital de la Timone, Neurology and Neuropsychology Department Aix Marseille University, Inserm, INS, Institut de Neurosciences des Systèmes Marseille France
| | - Audrey Gabelle‐Deloustal
- AP‐HM–Hôpital de la Timone, Neurology and Neuropsychology Department Aix Marseille University, Inserm, INS, Institut de Neurosciences des Systèmes Marseille France
| | - Karim Bennys
- AP‐HM–Hôpital de la Timone, Neurology and Neuropsychology Department Aix Marseille University, Inserm, INS, Institut de Neurosciences des Systèmes Marseille France
| | - Cecilia Marelli
- AP‐HM–Hôpital de la Timone, Neurology and Neuropsychology Department Aix Marseille University, Inserm, INS, Institut de Neurosciences des Systèmes Marseille France
| | - Lynda Touati
- AP‐HM–Hôpital de la Timone, Neurology and Neuropsychology Department Aix Marseille University, Inserm, INS, Institut de Neurosciences des Systèmes Marseille France
| | - Denis Mariano‐Goulart
- AP‐HM–Hôpital de la Timone, Neurology and Neuropsychology Department Aix Marseille University, Inserm, INS, Institut de Neurosciences des Systèmes Marseille France
| | - Delphine Verbizier‐Lonjon
- AP‐HM–Hôpital de la Timone, Neurology and Neuropsychology Department Aix Marseille University, Inserm, INS, Institut de Neurosciences des Systèmes Marseille France
| | - Thérèse Jonveaux
- AP‐HM–Hôpital de la Timone, Neurology and Neuropsychology Department Aix Marseille University, Inserm, INS, Institut de Neurosciences des Systèmes Marseille France
| | - Athanase Benetos
- AP‐HM–Hôpital de la Timone, Neurology and Neuropsychology Department Aix Marseille University, Inserm, INS, Institut de Neurosciences des Systèmes Marseille France
| | - Anna Kearney‐Schwartz
- AP‐HM–Hôpital de la Timone, Neurology and Neuropsychology Department Aix Marseille University, Inserm, INS, Institut de Neurosciences des Systèmes Marseille France
| | - Christine Perret‐Guillaume
- AP‐HM–Hôpital de la Timone, Neurology and Neuropsychology Department Aix Marseille University, Inserm, INS, Institut de Neurosciences des Systèmes Marseille France
| | - Antoine Verger
- AP‐HM–Hôpital de la Timone, Neurology and Neuropsychology Department Aix Marseille University, Inserm, INS, Institut de Neurosciences des Systèmes Marseille France
| | - Martine Vercelletto
- AP‐HM–Hôpital de la Timone, Neurology and Neuropsychology Department Aix Marseille University, Inserm, INS, Institut de Neurosciences des Systèmes Marseille France
| | - Claire Boutoleau‐Bretonniere
- AP‐HM–Hôpital de la Timone, Neurology and Neuropsychology Department Aix Marseille University, Inserm, INS, Institut de Neurosciences des Systèmes Marseille France
| | - Hélène Pouclet‐Courtemanche
- AP‐HM–Hôpital de la Timone, Neurology and Neuropsychology Department Aix Marseille University, Inserm, INS, Institut de Neurosciences des Systèmes Marseille France
| | - Nathalie Wagemann
- AP‐HM–Hôpital de la Timone, Neurology and Neuropsychology Department Aix Marseille University, Inserm, INS, Institut de Neurosciences des Systèmes Marseille France
| | - Amandine Pallardy
- AP‐HM–Hôpital de la Timone, Neurology and Neuropsychology Department Aix Marseille University, Inserm, INS, Institut de Neurosciences des Systèmes Marseille France
| | - Jacques Hugon
- AP‐HM–Hôpital de la Timone, Neurology and Neuropsychology Department Aix Marseille University, Inserm, INS, Institut de Neurosciences des Systèmes Marseille France
| | - Claire Paquet
- AP‐HM–Hôpital de la Timone, Neurology and Neuropsychology Department Aix Marseille University, Inserm, INS, Institut de Neurosciences des Systèmes Marseille France
| | - Julien Dumurgier
- AP‐HM–Hôpital de la Timone, Neurology and Neuropsychology Department Aix Marseille University, Inserm, INS, Institut de Neurosciences des Systèmes Marseille France
| | - Pascal Millet
- AP‐HM–Hôpital de la Timone, Neurology and Neuropsychology Department Aix Marseille University, Inserm, INS, Institut de Neurosciences des Systèmes Marseille France
| | - Mathieu Queneau
- AP‐HM–Hôpital de la Timone, Neurology and Neuropsychology Department Aix Marseille University, Inserm, INS, Institut de Neurosciences des Systèmes Marseille France
| | - Bruno Dubois
- AP‐HM–Hôpital de la Timone, Neurology and Neuropsychology Department Aix Marseille University, Inserm, INS, Institut de Neurosciences des Systèmes Marseille France
| | - Stéphane Epelbaum
- AP‐HM–Hôpital de la Timone, Neurology and Neuropsychology Department Aix Marseille University, Inserm, INS, Institut de Neurosciences des Systèmes Marseille France
| | - Marcel Levy
- AP‐HM–Hôpital de la Timone, Neurology and Neuropsychology Department Aix Marseille University, Inserm, INS, Institut de Neurosciences des Systèmes Marseille France
| | | | - Jean‐Luc Novella
- AP‐HM–Hôpital de la Timone, Neurology and Neuropsychology Department Aix Marseille University, Inserm, INS, Institut de Neurosciences des Systèmes Marseille France
| | - Yacine Jaidi
- AP‐HM–Hôpital de la Timone, Neurology and Neuropsychology Department Aix Marseille University, Inserm, INS, Institut de Neurosciences des Systèmes Marseille France
| | - Dimitri Papathanassiou
- AP‐HM–Hôpital de la Timone, Neurology and Neuropsychology Department Aix Marseille University, Inserm, INS, Institut de Neurosciences des Systèmes Marseille France
| | | | - Serge Belliard
- AP‐HM–Hôpital de la Timone, Neurology and Neuropsychology Department Aix Marseille University, Inserm, INS, Institut de Neurosciences des Systèmes Marseille France
| | - Anne Salmon
- AP‐HM–Hôpital de la Timone, Neurology and Neuropsychology Department Aix Marseille University, Inserm, INS, Institut de Neurosciences des Systèmes Marseille France
| | - Florence Lejeune
- AP‐HM–Hôpital de la Timone, Neurology and Neuropsychology Department Aix Marseille University, Inserm, INS, Institut de Neurosciences des Systèmes Marseille France
| | - Didier Hannequin
- AP‐HM–Hôpital de la Timone, Neurology and Neuropsychology Department Aix Marseille University, Inserm, INS, Institut de Neurosciences des Systèmes Marseille France
| | - David Wallon
- AP‐HM–Hôpital de la Timone, Neurology and Neuropsychology Department Aix Marseille University, Inserm, INS, Institut de Neurosciences des Systèmes Marseille France
| | - Olivier Martinaud
- AP‐HM–Hôpital de la Timone, Neurology and Neuropsychology Department Aix Marseille University, Inserm, INS, Institut de Neurosciences des Systèmes Marseille France
| | - Aline Zarea
- AP‐HM–Hôpital de la Timone, Neurology and Neuropsychology Department Aix Marseille University, Inserm, INS, Institut de Neurosciences des Systèmes Marseille France
| | - Mathieu Chastan
- AP‐HM–Hôpital de la Timone, Neurology and Neuropsychology Department Aix Marseille University, Inserm, INS, Institut de Neurosciences des Systèmes Marseille France
| | | | - Claire Thalamas
- AP‐HM–Hôpital de la Timone, Neurology and Neuropsychology Department Aix Marseille University, Inserm, INS, Institut de Neurosciences des Systèmes Marseille France
| | | | | | - Fabienne Calvas
- AP‐HM–Hôpital de la Timone, Neurology and Neuropsychology Department Aix Marseille University, Inserm, INS, Institut de Neurosciences des Systèmes Marseille France
| | - Emilie Rigal
- ToNIC, Toulouse NeuroImaging Center Université de Toulouse, Inserm, UPS Toulouse France
| | - Pierre Payoux
- AP‐HM–Hôpital de la Timone, Neurology and Neuropsychology Department Aix Marseille University, Inserm, INS, Institut de Neurosciences des Systèmes Marseille France
| | - Anne Hitzel
- AP‐HM–Hôpital de la Timone, Neurology and Neuropsychology Department Aix Marseille University, Inserm, INS, Institut de Neurosciences des Systèmes Marseille France
| | - Julien Delrieu
- Neurology Department CHU de Rouen–Hôpital Charles Nicolle Rouen France
| | - Pierre‐Jean Ousset
- AP‐HM–Hôpital de la Timone, Neurology and Neuropsychology Department Aix Marseille University, Inserm, INS, Institut de Neurosciences des Systèmes Marseille France
| | - Françoise Lala
- AP‐HM–Hôpital de la Timone, Neurology and Neuropsychology Department Aix Marseille University, Inserm, INS, Institut de Neurosciences des Systèmes Marseille France
| | - Nathalie Sastre‐Hengan
- AP‐HM–Hôpital de la Timone, Neurology and Neuropsychology Department Aix Marseille University, Inserm, INS, Institut de Neurosciences des Systèmes Marseille France
| | - Andrew Stephens
- AP‐HM–Hôpital de la Timone, Neurology and Neuropsychology Department Aix Marseille University, Inserm, INS, Institut de Neurosciences des Systèmes Marseille France
| | - Eric Guedj
- AP‐HM–Hôpital de la Timone, Nuclear Medicine Department Aix‐Marseille University, CERIMED, CNRS, INT, Institut de Neurosciences de la Timone Marseille France
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8
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Bullich S, Seibyl J, Catafau AM, Jovalekic A, Koglin N, Barthel H, Sabri O, De Santi S. Optimized classification of 18F-Florbetaben PET scans as positive and negative using an SUVR quantitative approach and comparison to visual assessment. Neuroimage Clin 2017; 15:325-332. [PMID: 28560157 PMCID: PMC5440277 DOI: 10.1016/j.nicl.2017.04.025] [Citation(s) in RCA: 78] [Impact Index Per Article: 11.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 02/20/2017] [Revised: 04/24/2017] [Accepted: 04/25/2017] [Indexed: 11/28/2022]
Abstract
Introduction Standardized uptake value ratios (SUVRs) calculated from cerebral cortical areas can be used to categorize 18F-Florbetaben (FBB) PET scans by applying appropriate cutoffs. The objective of this work was first to generate FBB SUVR cutoffs using visual assessment (VA) as standard of truth (SoT) for a number of reference regions (RR) (cerebellar gray matter (GCER), whole cerebellum (WCER), pons (PONS), and subcortical white matter (SWM)). Secondly, to validate the FBB PET scan categorization performed by SUVR cutoffs against the categorization made by post-mortem histopathological confirmation of the Aβ presence. Finally, to evaluate the added value of SUVR cutoff categorization to VA. Methods SUVR cutoffs were generated for each RR using FBB scans from 143 subjects who were visually assessed by 3 readers. SUVR cutoffs were validated in 78 end-of life subjects using VA from 8 independent blinded readers (3 expert readers and 5 non-expert readers) and histopathological confirmation of the presence of neuritic beta-amyloid plaques as SoT. Finally, the number of correctly or incorrectly classified scans according to pathology results using VA and SUVR cutoffs was compared. Results Composite SUVR cutoffs generated were 1.43 (GCER), 0.96 (WCER), 0.78 (PONS) and 0.71 (SWM). Accuracy values were high and consistent across RR (range 83–94% for histopathology, and 85–94% for VA). SUVR cutoff performed similarly as VA but did not improve VA classification of FBB scans read either by expert readers or the majority read but provided higher accuracy than some non-expert readers. Conclusion The accurate scan classification obtained in this study supports the use of VA as SoT to generate site-specific SUVR cutoffs. For an elderly end of life population, VA and SUVR cutoff categorization perform similarly in classifying FBB scans as Aβ-positive or Aβ-negative. These results emphasize the additional contribution that SUVR cutoff classification may have compared with VA performed by non-expert readers. SUVR cutoffs to classify Florbetaben PET scans as positive and negative were generated. SUVR cutoffs were validated against post-mortem histopathological confirmation. Added value of SUVR cutoff classification to visual assessment was evaluated. SUVR cutoff classification provided higher accuracy than some non-expert readers. Results emphasize the contribution that SUVR cutoffs may have to visual assessment.
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Affiliation(s)
| | | | | | | | | | - Henryk Barthel
- Department of Nuclear Medicine, University Hospital Leipzig, Leipzig, Germany
| | - Osama Sabri
- Department of Nuclear Medicine, University Hospital Leipzig, Leipzig, Germany
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9
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Ganz ML, Tawah AF, Guo S, Chitnis AS, Silies H, Schäuble B, Jovalekic A, Foster NL. The impact of β-amyloid positron emission tomography on the diagnostic and treatment decisions of dementia experts. Neurodegener Dis Manag 2017; 7:107-117. [DOI: 10.2217/nmt-2016-0059] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/21/2022] Open
Abstract
Aim: Amyloid positron emission tomography (aPET) measurement of Alzheimer's disease (AD) pathology could improve the accurate diagnosis of cognitive disorders. Appropriate use criteria recommend that only dementia experts order aPET. Materials & methods: We surveyed 145 dementia experts about their current approaches to evaluation and treatment and the likely influence of aPET. Results: Experts expected aPET to alter diagnostic procedures and patient management and also increase diagnostic certainty. They anticipated confirming AD or altering pharmacological treatment following positive results more than excluding AD following negative results. Experts familiar with aPET reported changes that were more consistent with appropriate use criteria and published evidence. Conclusions: Knowledge about aPET strongly influenced effects on diagnostic certainty and changed clinical practice. Dementia experts may need additional training to achieve optimal benefit from aPET.
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Affiliation(s)
- Michael L Ganz
- Evidera, 500 Totten Pond Road, 5th Floor, Waltham, MA 02451, USA
| | - Alie F Tawah
- Evidera, 500 Totten Pond Road, 5th Floor, Waltham, MA 02451, USA
| | - Shien Guo
- Evidera, 500 Totten Pond Road, 5th Floor, Waltham, MA 02451, USA
| | - Abhishek S Chitnis
- Johnson & Johnson Co, 410 George Street, New Brunswick, NJ 08901, USA (This study was completed while AS Chitnis was an employee of Evidera)
| | - Hedwig Silies
- formerly Piramal Imaging Ltd., Market Access & HEOR, 23 Science Park, Cambridge, UK
| | - Barbara Schäuble
- formerly Piramal Imaging GmbH, Global Medical Affairs, Tegeler Strasse 6–7 D13353 Berlin, Germany
| | | | - Norman L Foster
- Center for Alzheimer's Care, Imaging & Research, Department of Neurology, 729 Arapeen Drive, Salt Lake City, University of Utah, Salt Lake City, UT 84108, USA
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10
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Bullich S, Villemagne VL, Catafau AM, Jovalekic A, Koglin N, Rowe CC, De Santi S. Optimal Reference Region to Measure Longitudinal Amyloid-β Change with 18F-Florbetaben PET. J Nucl Med 2017; 58:1300-1306. [PMID: 28183994 DOI: 10.2967/jnumed.116.187351] [Citation(s) in RCA: 38] [Impact Index Per Article: 5.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/17/2016] [Accepted: 01/05/2017] [Indexed: 12/24/2022] Open
Abstract
Accurate measurement of changes in amyloid-β (Aβ) deposition over time is important in longitudinal studies, particularly in anti-Aβ therapeutic trials. To achieve this, the optimal reference region (RR) must be selected to reduce variance of Aβ PET measurements, allowing early detection of treatment efficacy. The aim of this study was to determine the RR that allows earlier detection of subtle Aβ changes using 18F-florbetaben PET. Methods: Forty-five patients with mild cognitive impairment (mean age ± SD, 72.69 ± 6.54 y; 29 men/16 women) who underwent up to 3 18F-florbetaben scans were included. Baseline scans were visually classified as high (Aβ+) or low (Aβ-) amyloid. Six cortical regions were quantified using a standardized region-of-interest atlas applied to the spatially normalized gray matter image obtained from segmentation of the baseline T1-weighted volumetric MRI. Four RRs (cerebellar gray matter [CGM], whole cerebellum [WCER], pons, and subcortical white matter [SWM]) were studied. The SUV ratio (SUVR) for each RR was calculated by dividing cortex activity by RR activity, with a composite SUVR averaged over 6 cortical regions. SUVR increase from baseline to 1 and 2 y, and percentage Aβ deposition per year, were assessed across Aβ+ and Aβ- groups. Results: SUVs for any RR were not significantly different over time. Percentage Aβ accumulation per year derived from composite SUVR was 0.10 ± 1.72 (Aβ-) and 1.36 ± 1.98 (Aβ+) (P = 0.02) for CGM and 0.13 ± 1.47 and 1.32 ± 1.75 (P = 0.01), respectively, for WCER. Compared with baseline, the composite SUVR increase in Aβ+ scans was significantly larger than in Aβ- scans at 1 y (P = 0.04 [CGM]; P = 0.03 [WCER]) and 2 y (P = 0.02 [CGM]; P = 0.01 [WCER]) using these 2 RRs. Significant SUVR changes using the pons as the RR were detected only at 2 y (P = 0.46 [1 y], P = 0.001 [2 y]). SUVR using the SWM as the RR showed no significant differences at either follow-up (P = 0.39 [1 y], P = 0.09 [2 y]). Conclusion: RR selection influences reliable early measurement of Aβ changes over time. Compared with SWM and pons, which do not fulfil the RR requirements and have limited sensitivity to detect Aβ changes, cerebellar RRs are recommended for 18F-florbetaben PET because they allow earlier detection of Aβ accumulation.
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Affiliation(s)
| | - Victor L Villemagne
- Departments of Medicine and Molecular Imaging, University of Melbourne, Austin Health, Melbourne, Victoria, Australia; and
| | | | | | | | - Christopher C Rowe
- Departments of Medicine and Molecular Imaging, University of Melbourne, Austin Health, Melbourne, Victoria, Australia; and
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Jovalekic A, Cavé-Lopez S, Canopoli A, Ondracek JM, Nager A, Vyssotski AL, Hahnloser RHR. A lightweight feedback-controlled microdrive for chronic neural recordings. J Neural Eng 2017; 14:026006. [DOI: 10.1088/1741-2552/aa5848] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/28/2023]
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Jovalekic A, Bullich S, Catafau A, de Santi S. Advances in Aβ plaque detection and the value of knowing: overcoming challenges to improving patient outcomes in Alzheimer's disease. Neurodegener Dis Manag 2016; 6:491-497. [PMID: 27813444 DOI: 10.2217/nmt-2016-0026] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/21/2022] Open
Abstract
Clinical diagnosis of Alzheimer's disease (AD) can be challenging as numerous diseases mimic the characteristics of AD. In this light, recent guidelines developed by different associations and working groups point out the need for biomarkers to support AD diagnosis. This paper discusses 18F-labeled radiotracers (which are indicated for PET imaging of the brain) and ongoing clinical studies that aim to generate new evidence for the usage of amyloid imaging. In addition to their relatively long half-life, these agents are known for their high sensitivity and high negative predictive values for detection of neuritic Aβ plaques. Comparisons with other biomarkers are provided and implications of diagnostic disclosures discussed. Finally, recent data from clinical trials underscore the importance of amyloid PET for detecting, quantifying and monitoring Aβ plaque deposits.
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Affiliation(s)
| | | | - Ana Catafau
- formerly Piramal Imaging GmbH, Berlin, Germany
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13
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Abstract
Traditional nuclear medicine ligands were designed to target cellular receptors or transporters with a binding pocket and a defined structure-activity relationship. More recently, tracers have been developed to target pathological protein aggregations, which have less well-defined structure-activity relationships. Aggregations of proteins such as tau, α-synuclein, and β-amyloid (Aβ) have been identified in neurodegenerative diseases, including Alzheimer's disease (AD) and other dementias, and Parkinson's disease (PD). Indeed, Aβ deposition is a hallmark of AD, and detection methods have evolved from coloured dyes to modern 18F-labelled positron emission tomography (PET) tracers. Such tracers are becoming increasingly established in routine clinical practice for evaluation of Aβ neuritic plaque density in the brains of adults who are being evaluated for AD and other causes of cognitive impairment. While similar in structure, there are key differences between the available compounds in terms of dosing/dosimetry, pharmacokinetics, and interpretation of visual reads. In the future, quantification of Aβ-PET may further improve its utility. Tracers are now being developed for evaluation of tau protein, which is associated with decreased cognitive function and neurodegenerative changes in AD, and is implicated in the pathogenesis of other neurodegenerative diseases. While no compound has yet been approved for tau imaging in clinical use, it is a very active area of research. Development of tau tracers comprises in-depth characterisation of existing radiotracers, clinical validation, a better understanding of uptake patterns, test-retest/dosimetry data, and neuropathological correlations with PET. Tau imaging may allow early, more accurate diagnosis, and monitoring of disease progression, in a range of conditions. Another marker for which imaging modalities are needed is α-synuclein, which has potential for conditions including PD and dementia with Lewy bodies. Efforts to develop a suitable tracer are ongoing, but are still in their infancy. In conclusion, several PET tracers for detection of pathological protein depositions are now available for clinical use, particularly PET tracers that bind to Aβ plaques. Tau-PET tracers are currently in clinical development, and α-synuclein protein deposition tracers are at early stage of research. These tracers will continue to change our understanding of complex disease processes.
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Affiliation(s)
| | - Norman Koglin
- Piramal Imaging GmbH, Tegeler Straße 6-7, 13353 Berlin, Germany
| | - Andre Mueller
- Piramal Imaging GmbH, Tegeler Straße 6-7, 13353 Berlin, Germany
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14
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Abstract
Hippocampal place cells support spatial memory using sensory information from the environment and self-motion information to localize their firing fields. Currently, there is disagreement about whether CA1 place cells can use pure self-motion information to disambiguate different compartments in environments containing multiple visually identical compartments. Some studies report that place cells can disambiguate different compartments, while others report that they do not. Furthermore, while numerous studies have examined remapping, there has been little examination of remapping in different subregions of a single environment. Is remapping purely local or do place fields in neighboring, unaffected, regions detect the change? We recorded place cells as rats foraged across a 4-compartment environment and report 3 new findings. First, we find that, unlike studies in which rats foraged in 2 compartments, place fields showed a high degree of spatial repetition with a slight degree of rate-based discrimination. Second, this repetition does not diminish with extended experience. Third, remapping was found to be purely local for both geometric change and contextual change. Our results reveal the limited capacity of the path integrator to drive pattern separation in hippocampal representations, and suggest that doorways may play a privileged role in segmenting the neural representation of space.
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Affiliation(s)
- Hugo J Spiers
- Department of Cognitive, Perceptual and Brain Sciences, Division of Psychology and Language Sciences, Institute of Behavioural Neuroscience, University College London, UK
| | - Robin M A Hayman
- Department of Cognitive, Perceptual and Brain Sciences, Division of Psychology and Language Sciences, Institute of Behavioural Neuroscience, University College London, UK
| | - Aleksandar Jovalekic
- Department of Cognitive, Perceptual and Brain Sciences, Division of Psychology and Language Sciences, Institute of Behavioural Neuroscience, University College London, UK Axona Ltd, Unit 4U St Albans Enterprise Centre, St Albans, UK
| | - Elizabeth Marozzi
- Department of Cognitive, Perceptual and Brain Sciences, Division of Psychology and Language Sciences, Institute of Behavioural Neuroscience, University College London, UK
| | - Kathryn J Jeffery
- Department of Cognitive, Perceptual and Brain Sciences, Division of Psychology and Language Sciences, Institute of Behavioural Neuroscience, University College London, UK
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Jovalekic A, Hayman R, Becares N, Reid H, Thomas G, Wilson J, Jeffery K. Horizontal biases in rats' use of three-dimensional space. Behav Brain Res 2011; 222:279-88. [PMID: 21419172 PMCID: PMC3157560 DOI: 10.1016/j.bbr.2011.02.035] [Citation(s) in RCA: 41] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/10/2011] [Revised: 02/16/2011] [Accepted: 02/24/2011] [Indexed: 11/18/2022]
Abstract
Rodent spatial cognition studies allow links to be made between neural and behavioural phenomena, and much is now known about the encoding and use of horizontal space. However, the real world is three dimensional, providing cognitive challenges that have yet to be explored. Motivated by neural findings suggesting weaker encoding of vertical than horizontal space, we examined whether rats show a similar behavioural anisotropy when distributing their time freely between vertical and horizontal movements. We found that in two- or three-dimensional environments with a vertical dimension, rats showed a prioritization of horizontal over vertical movements in both foraging and detour tasks. In the foraging tasks, the animals executed more horizontal than vertical movements and adopted a "layer strategy" in which food was collected from one horizontal level before moving to the next. In the detour tasks, rats preferred the routes that allowed them to execute the horizontal leg first. We suggest three possible reasons for this behavioural bias. First, as suggested by Grobety and Schenk, it allows minimisation of energy expenditure, inasmuch as costly vertical movements are minimised. Second, it may be a manifestation of the temporal discounting of effort, in which animals value delayed effort as less costly than immediate effort. Finally, it may be that at the neural level rats encode the vertical dimension less precisely, and thus prefer to bias their movements in the more accurately encoded horizontal dimension. We suggest that all three factors are related, and all play a part.
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Affiliation(s)
- Aleksandar Jovalekic
- Institute of Behavioural Neuroscience, Department of Cognitive, Perceptual and Brain Sciences, Division of Psychology and Language Sciences, University College London, 26 Bedford Way, London WC1H 0AP, UK
- Axona Ltd, Unit 4U, Long Spring, Porters Wood, St. Albans AL3 6EN, UK
| | - Robin Hayman
- Institute of Behavioural Neuroscience, Department of Cognitive, Perceptual and Brain Sciences, Division of Psychology and Language Sciences, University College London, 26 Bedford Way, London WC1H 0AP, UK
| | - Natalia Becares
- Institute of Behavioural Neuroscience, Department of Cognitive, Perceptual and Brain Sciences, Division of Psychology and Language Sciences, University College London, 26 Bedford Way, London WC1H 0AP, UK
| | - Harry Reid
- Institute of Behavioural Neuroscience, Department of Cognitive, Perceptual and Brain Sciences, Division of Psychology and Language Sciences, University College London, 26 Bedford Way, London WC1H 0AP, UK
| | - George Thomas
- Institute of Behavioural Neuroscience, Department of Cognitive, Perceptual and Brain Sciences, Division of Psychology and Language Sciences, University College London, 26 Bedford Way, London WC1H 0AP, UK
| | - Jonathan Wilson
- Institute of Behavioural Neuroscience, Department of Cognitive, Perceptual and Brain Sciences, Division of Psychology and Language Sciences, University College London, 26 Bedford Way, London WC1H 0AP, UK
| | - Kate Jeffery
- Institute of Behavioural Neuroscience, Department of Cognitive, Perceptual and Brain Sciences, Division of Psychology and Language Sciences, University College London, 26 Bedford Way, London WC1H 0AP, UK
- Corresponding author. Tel.: +44 20 7679 5308.
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