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Hunter S, Smailagic N, Brayne C. Aβ and the dementia syndrome: Simple versus complex perspectives. Eur J Clin Invest 2018; 48:e13025. [PMID: 30246866 DOI: 10.1111/eci.13025] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/14/2017] [Revised: 08/15/2018] [Accepted: 09/06/2018] [Indexed: 02/06/2023]
Abstract
BACKGROUND The amyloid cascade hypothesis (ACH) has dominated strategy in dementia research for decades despite evidence of its limitations including known heterogeneity of the dementia syndrome in the population and the narrow focus on a single molecule - the amyloid beta protein (Aβ) as causal for all Alzheimer-type dementia. Other hypotheses relevant to Aβ are the presenilin (PS) hypothesis (PSH) relating to the involvement of PS in the generation of Aβ, and the amyloid precursor protein (APP) matrix approach (AMA), relating to the complex and dynamic breakdown of APP, from which Aβ derives. MATERIALS AND METHODS In this article we explore perspectives relating to complex disorders occurring mainly in older populations through a detailed case study of the role of Aβ in AD. RESULTS Scrutiny of the evidence generated so far reveals and a lack of understanding of the wider APP proteolytic system and how narrow research into the dementia syndrome has been to date. Confounding factors add significant limitations to the understanding of the current evidence base. CONCLUSIONS A better characterisation of the entire APP proteolytic system in the human brain is urgently required to place Aβ in its complex physiological context. From a molecular perspective, a combination of the alternative hypotheses, the PSH and the AMA may better describe the complexity of the APP proteolytic system leading to new therapeutic approaches. The reductionist approach is widespread throughout biomedical research and this example highlights how neglect of complexity can undermine investigations of complex disorders, particularly those arising in the oldest in our populations.
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Affiliation(s)
- Sally Hunter
- Department of Public Health and Primary Care, Institute of Public Health, School of Clinical Medicine, University of Cambridge, Cambridge, UK
| | - Nadja Smailagic
- Department of Public Health and Primary Care, Institute of Public Health, School of Clinical Medicine, University of Cambridge, Cambridge, UK
| | - Carol Brayne
- Department of Public Health and Primary Care, Institute of Public Health, School of Clinical Medicine, University of Cambridge, Cambridge, UK
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Tau PET imaging evidence in patients with cognitive impairment: preparing for clinical use. Clin Transl Imaging 2018. [DOI: 10.1007/s40336-018-0297-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/28/2022]
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Frisoni GB, Barkhof F, Altomare D, Berkhof J, Boccardi M, Canzoneri E, Collij L, Drzezga A, Farrar G, Garibotto V, Gismondi R, Gispert JD, Jessen F, Kivipelto M, Lopes Alves I, Molinuevo JL, Nordberg A, Payoux P, Ritchie C, Savicheva I, Scheltens P, Schmidt ME, Schott JM, Stephens A, van Berckel B, Vellas B, Walker Z, Raffa N. AMYPAD Diagnostic and Patient Management Study: Rationale and design. Alzheimers Dement 2018; 15:388-399. [PMID: 30339801 DOI: 10.1016/j.jalz.2018.09.003] [Citation(s) in RCA: 34] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/16/2018] [Revised: 08/27/2018] [Accepted: 09/06/2018] [Indexed: 01/09/2023]
Abstract
INTRODUCTION Reimbursement of amyloid-positron emission tomography (PET) is lagging due to the lack of definitive evidence on its clinical utility and cost-effectiveness. The Amyloid Imaging to Prevent Alzheimer's Disease-Diagnostic and Patient Management Study (AMYPAD-DPMS) is designed to fill this gap. METHODS AMYPAD-DPMS is a phase 4, multicenter, prospective, randomized controlled study. Nine hundred patients with subjective cognitive decline plus, mild cognitive impairment, and dementia possibly due to Alzheimer's disease will be randomized to ARM1, amyloid-PET performed early in the diagnostic workup; ARM2, amyloid-PET performed after 8 months; and ARM3, amyloid-PET performed whenever the physician chooses to do so. ENDPOINTS The primary endpoint is the difference between ARM1 and ARM2 in the proportion of patients receiving a very-high-confidence etiologic diagnosis after 3 months. Secondary endpoints address diagnosis and diagnostic confidence, diagnostic/therapeutic management, health economics and patient-related outcomes, and methods for image quantitation. EXPECTED IMPACTS AMYPAD-DPMS will supply physicians and health care payers with real-world data to plan management decisions.
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Affiliation(s)
- Giovanni B Frisoni
- Laboratory of Neuroimaging of Aging (LANVIE), University of Geneva, Geneva, Switzerland; Memory Clinic, University Hospital of Geneva, Geneva, Switzerland; Laboratory of Alzheimer's Neuroimaging and Epidemiology (LANE), Saint John of God Clinical Research Centre, Brescia, Italy.
| | - Frederik Barkhof
- Department of Radiology and Nuclear Medicine, Amsterdam Neuroscience, VU University Medical Center, Amsterdam, the Netherlands; Institutes of Neurology and Healthcare Engineering, UCL, London, United Kingdom
| | - Daniele Altomare
- Laboratory of Alzheimer's Neuroimaging and Epidemiology (LANE), Saint John of God Clinical Research Centre, Brescia, Italy; Department of Molecular and Translational Medicine, University of Brescia, Brescia, Italy
| | - Johannes Berkhof
- Department of Epidemiology and Biostatistics, VU University Medical Center, Amsterdam, the Netherlands
| | - Marina Boccardi
- Laboratory of Neuroimaging of Aging (LANVIE), University of Geneva, Geneva, Switzerland; Laboratory of Alzheimer's Neuroimaging and Epidemiology (LANE), Saint John of God Clinical Research Centre, Brescia, Italy
| | - Elisa Canzoneri
- Laboratory of Neuroimaging of Aging (LANVIE), University of Geneva, Geneva, Switzerland
| | - Lyduine Collij
- Department of Radiology and Nuclear Medicine, Amsterdam Neuroscience, VU University Medical Center, Amsterdam, the Netherlands
| | - Alexander Drzezga
- Department of Nuclear Medicine, University Hospital of Cologne, University of Cologne and German Center for Neurodegenerative Diseases (DZNE), Germany
| | - Gill Farrar
- Life Sciences, GE Healthcare, Amersham, Buckinghamshire, United Kingdom
| | - Valentina Garibotto
- Division of Nuclear Medicine and Molecular Imaging, Department of Medical Imaging, University Hospitals of Geneva, Geneva, Switzerland; NIMTlab, Faculty of Medicine, Geneva University, Geneva, Switzerland
| | | | - Juan-Domingo Gispert
- Barcelonaβeta Brain Research Center, Pasqual Maragall Foundation, Barcelona, Spain; Centro de Investigación Biomédica en Red de Bioingeniería, Biomateriales y Nanomedicina (CIBER-BBN), Madrid, Spain
| | - Frank Jessen
- Department of Psychiatry and Psychotherapy, University of Cologne, Cologne, Germany; German Center for Neurodegenerative Diseases (DZNE), Bonn, Germany
| | - Miia Kivipelto
- Department of Neurobiology, Care Sciences and Society, Center for Alzheimer Research, Division of Clinical Geriatrics, Karolinska Institutet, Stockholm, Sweden; Aging Theme, Karolinska University Hospital Stockholm, Sweden; University of Eastern Finland, Finland; School of Public Health, Imperial College, London, United Kingdom
| | - Isadora Lopes Alves
- Department of Radiology and Nuclear Medicine, Amsterdam Neuroscience, VU University Medical Center, Amsterdam, the Netherlands
| | - José Luis Molinuevo
- Barcelonaβeta Brain Research Center, Pasqual Maragall Foundation, Barcelona, Spain
| | - Agneta Nordberg
- Department of Neurobiology, Care Sciences and Society, Center for Alzheimer Research, Division of Clinical Geriatrics, Karolinska Institutet, Stockholm, Sweden; Aging Theme, Karolinska University Hospital Stockholm, Sweden
| | - Pierre Payoux
- Nuclear Medicine Department, University Hospital of Toulouse (CHU-Toulouse), Toulouse, France; ToNIC, Toulouse NeuroImaging Center, Université de Toulouse, Inserm, UPS, Toulouse, France
| | - Craig Ritchie
- Centre for Clinical Brain Sciences, Department of Psychiatry, University of Edinburgh, Edinburgh, United Kingdom
| | - Irina Savicheva
- Nuclear Medicine IRA, Medical Radiation Physics and Nuclear Medicine Imaging, Karolinska University Hospital, Sweden
| | - Philip Scheltens
- Alzheimer Center and Department of Neurology, Amsterdam Neuroscience, VU University Medical Center, Amsterdam, the Netherlands
| | - Mark E Schmidt
- Experimental Medicine, Janssen Pharmaceutica NV, Beerse, Belgium
| | - Jonathan M Schott
- Institute of Neurology, University College London, London, United Kingdom
| | - Andrew Stephens
- Piramal Imaging, Clinical Research and Development, Berlin, Germany
| | - Bart van Berckel
- Department of Radiology and Nuclear Medicine, Amsterdam Neuroscience, VU University Medical Center, Amsterdam, the Netherlands
| | - Bruno Vellas
- Gerontopole of Toulouse, University Hospital of Toulouse (CHU-Toulouse), Toulouse, France; UMR INSERM 1027, University of Toulouse III, Toulouse, France
| | - Zuzana Walker
- Division of Psychiatry, University College London, London, United Kingdom; Essex Partnership University NHS Foundation Trust, United Kingdom
| | - Nicola Raffa
- Piramal Imaging, Market Access and HEOR, Berlin, Germany
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Nobili F, Arbizu J, Bouwman F, Drzezga A, Agosta F, Nestor P, Walker Z, Boccardi M. European Association of Nuclear Medicine and European Academy of Neurology recommendations for the use of brain 18 F-fluorodeoxyglucose positron emission tomography in neurodegenerative cognitive impairment and dementia: Delphi consensus. Eur J Neurol 2018; 25:1201-1217. [PMID: 29932266 DOI: 10.1111/ene.13728] [Citation(s) in RCA: 126] [Impact Index Per Article: 21.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/13/2018] [Accepted: 06/20/2018] [Indexed: 12/17/2022]
Abstract
BACKGROUND AND PURPOSE Recommendations for using fluorodeoxyglucose positron emission tomography (FDG-PET) to support the diagnosis of dementing neurodegenerative disorders are sparse and poorly structured. METHODS Twenty-one questions on diagnostic issues and on semi-automated analysis to assist visual reading were defined. Literature was reviewed to assess study design, risk of bias, inconsistency, imprecision, indirectness and effect size. Critical outcomes were sensitivity, specificity, accuracy, positive/negative predictive value, area under the receiver operating characteristic curve, and positive/negative likelihood ratio of FDG-PET in detecting the target conditions. Using the Delphi method, an expert panel voted for/against the use of FDG-PET based on published evidence and expert opinion. RESULTS Of the 1435 papers, 58 papers provided proper quantitative assessment of test performance. The panel agreed on recommending FDG-PET for 14 questions: diagnosing mild cognitive impairment due to Alzheimer's disease (AD), frontotemporal lobar degeneration (FTLD) or dementia with Lewy bodies (DLB); diagnosing atypical AD and pseudo-dementia; differentiating between AD and DLB, FTLD or vascular dementia, between DLB and FTLD, and between Parkinson's disease and progressive supranuclear palsy; suggesting underlying pathophysiology in corticobasal degeneration and progressive primary aphasia, and cortical dysfunction in Parkinson's disease; using semi-automated assessment to assist visual reading. Panellists did not support FDG-PET use for pre-clinical stages of neurodegenerative disorders, for amyotrophic lateral sclerosis and Huntington disease diagnoses, and for amyotrophic lateral sclerosis or Huntington-disease-related cognitive decline. CONCLUSIONS Despite limited formal evidence, panellists deemed FDG-PET useful in the early and differential diagnosis of the main neurodegenerative disorders, and semi-automated assessment helpful to assist visual reading. These decisions are proposed as interim recommendations.
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Affiliation(s)
- F Nobili
- Department of Neuroscience (DINOGMI), University of Genoa and Polyclinic San Martino Hospital, Genoa, Italy
| | - J Arbizu
- Department of Nuclear Medicine, Clinica Universidad de Navarra, University of Navarra, Pamplona, Spain
| | - F Bouwman
- Department of Neurology and Alzheimer Center, Amsterdam Neuroscience, VU University Medical Center, Amsterdam, The Netherlands
| | - A Drzezga
- Department of Nuclear Medicine, University Hospital of Cologne, University of Cologne and German Center for Neurodegenerative Diseases (DZNE), Cologne, Germany
| | - F Agosta
- Neuroimaging Research Unit, Institute of Experimental Neurology, Division of Neuroscience, San Raffaele Scientific Institute, Vita-Salute San Raffaele University, Milan, Italy
| | - P Nestor
- German Center for Neurodegenerative Diseases (DZNE), Magdeburg, Germany
| | - Z Walker
- Division of Psychiatry, Essex Partnership University NHS Foundation Trust, University College London, London, UK
| | - M Boccardi
- Department of Psychiatry, Laboratoire du Neuroimagerie du Vieillissement (LANVIE), University of Geneva, Geneva, Switzerland
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Buschiazzo A, Cossu V, Bauckneht M, Orengo A, Piccioli P, Emionite L, Bianchi G, Grillo F, Rocchi A, Di Giulio F, Fiz F, Raffaghello L, Nobili F, Bruno S, Caviglia G, Ravera S, Benfenati F, Piana M, Morbelli S, Sambuceti G, Marini C. Effect of starvation on brain glucose metabolism and 18F-2-fluoro-2-deoxyglucose uptake: an experimental in-vivo and ex-vivo study. EJNMMI Res 2018; 8:44. [PMID: 29892963 PMCID: PMC5995768 DOI: 10.1186/s13550-018-0398-0] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/10/2018] [Accepted: 05/13/2018] [Indexed: 01/04/2023] Open
Abstract
BACKGROUND The close connection between neuronal activity and glucose consumption accounts for the clinical value of 18F-fluoro-2-deoxyglucose (FDG) imaging in neurodegenerative disorders. Nevertheless, brain metabolic response to starvation (STS) might hamper the diagnostic accuracy of FDG PET/CT when the cognitive impairment results in a severe food deprivation. METHODS Thirty six-week-old BALB/c female mice were divided into two groups: "control" group (n = 15) were kept under standard conditions and exposed to fasting for 6 h before the study; the remaining "STS" mice were submitted to 48 h STS (absence of food and free access to water) before imaging. In each group, nine mice were submitted to dynamic micro-PET imaging to estimate brain and skeletal muscle glucose consumption (C- and SM-MRGlu*) by Patlak approach, while six mice were sacrificed for ex vivo determination of the lumped constant, defined as the ratio between CMRGlu* and glucose consumption measured by glucose removal from the incubation medium (n = 3) or biochemical analyses (n = 3), respectively. RESULTS CMRGlu* was lower in starved than in control mice (46.1 ± 23.3 vs 119.5 ± 40.2 nmol × min-1 × g-1, respectively, p < 0.001). Ex vivo evaluation documented a remarkable stability of lumped constant as documented by the stability of GLUT expression, G6Pase activity, and kinetic features of hexokinase-catalyzed phosphorylation. However, brain SUV in STS mice was even (though not significantly) higher with respect to control mice. Conversely, a marked decrease in both SM-MRGlu* and SM-SUV was documented in STS mice with respect to controls. CONCLUSIONS STS markedly decreases brain glucose consumption without altering measured FDG SUV in mouse experimental models. This apparent paradox does not reflect any change in lumped constant. Rather, it might be explained by the metabolic response of the whole body: the decrease in FDG sequestration by the skeletal muscle is as profound as to prolong tracer persistence in the bloodstream and thus its availability for brain uptake.
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Affiliation(s)
- Ambra Buschiazzo
- Department of Health Science, Nuclear Medicine Unit, University of Genoa, Genoa, Italy
| | - Vanessa Cossu
- Nuclear Medicine Unit, Polyclinic San Martino Hospital, Largo R. Benzi 10, 16132, Genoa, Italy
| | - Matteo Bauckneht
- Department of Health Science, Nuclear Medicine Unit, University of Genoa, Genoa, Italy
| | - Annamaria Orengo
- Nuclear Medicine Unit, Polyclinic San Martino Hospital, Largo R. Benzi 10, 16132, Genoa, Italy
| | | | - Laura Emionite
- Animal Facility, Polyclinic San Martino Hospital, Genoa, Italy
| | | | - Federica Grillo
- Pathology, Department of Integrated Surgical and Diagnosic Sciences (DISC), University of Genoa, Genoa, Italy
| | - Anna Rocchi
- Center for Synaptic Neuroscience and Technology, Istituto Italiano di Tecnologia (IIT), Genoa, Italy.,Department of Experimental Medicine, University of Genoa, Genoa, Italy
| | - Francesco Di Giulio
- Nuclear Medicine Unit, Polyclinic San Martino Hospital, Largo R. Benzi 10, 16132, Genoa, Italy
| | - Francesco Fiz
- Department of Health Science, Nuclear Medicine Unit, University of Genoa, Genoa, Italy.,Nuclear Medicine Unit, Department of Radiology, Uni-Klinikum, Tuebingen, Germany
| | | | - Flavio Nobili
- Clinical Neurology, Polyclinic San Martino Hospital, Genoa, Italy.,Department of Neuroscience (DINOGMI), University of Genoa, Genoa, Italy
| | - Silvia Bruno
- Department of Experimental Medicine, University of Genoa, Genoa, Italy
| | - Giacomo Caviglia
- Department of Mathematics (DIMA), University of Genoa, Genoa, Italy
| | - Silvia Ravera
- Department of Pharmacy, Biochemistry Laboratory, University of Genoa, Genoa, Italy
| | - Fabio Benfenati
- Center for Synaptic Neuroscience and Technology, Istituto Italiano di Tecnologia (IIT), Genoa, Italy.,Department of Experimental Medicine, University of Genoa, Genoa, Italy
| | - Michele Piana
- Department of Mathematics (DIMA), University of Genoa, Genoa, Italy.,SPIN Institute, CNR, Genoa, Italy
| | - Silvia Morbelli
- Department of Health Science, Nuclear Medicine Unit, University of Genoa, Genoa, Italy.,Nuclear Medicine Unit, Polyclinic San Martino Hospital, Largo R. Benzi 10, 16132, Genoa, Italy
| | - Gianmario Sambuceti
- Department of Health Science, Nuclear Medicine Unit, University of Genoa, Genoa, Italy.,Nuclear Medicine Unit, Polyclinic San Martino Hospital, Largo R. Benzi 10, 16132, Genoa, Italy
| | - Cecilia Marini
- Nuclear Medicine Unit, Polyclinic San Martino Hospital, Largo R. Benzi 10, 16132, Genoa, Italy. .,CNR Institute of Molecular Bioimaging and Physiology (IBFM), Milan, Italy.
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Mainta I, Trombella S, Morbelli S, Frisoni G, Garibotto V. Education-Adjusted Normality Thresholds for FDG-PET in the Diagnosis of Alzheimer Disease. NEURODEGENER DIS 2018; 18:120-126. [DOI: 10.1159/000488915] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/26/2018] [Accepted: 04/03/2018] [Indexed: 11/19/2022] Open
Abstract
Background: A corollary of the reserve hypothesis is that what is regarded as pathological cortical metabolism in patients might vary according to education. Objective: The aim of this study is to assess the incremental diagnostic value of education-adjusted over unadjusted thresholds on the diagnostic accuracy of FDG-PET as a biomarker for Alzheimer disease (AD). Methods: We compared cortical metabolism in 90 healthy controls and 181 AD patients from the Alzheimer Disease Neuroimaging Initiative (ADNI) database. The AUC of the ROC curve did not differ significantly between the whole group and the higher-education patients or the lower-education subjects. Results: The threshold of wMetaROI values providing 80% sensitivity was lower in higher-education patients and higher in the lower-education patients, compared to the standard threshold derived over the whole AD collective, without, however, significant changes in sensitivity and specificity. Conclusion: These data show that education, as a proxy of reserve, is not a major confounder in the diagnostic accuracy of FDG-PET in AD and the adoption of education-adjusted thresholds is not required in daily practice.
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Abstract
PURPOSE OF REVIEW To present the new PET markers that could become in the coming years, relevant to advanced clinical approaches to dementia diagnosis, drug trials, and treatment strategies and discuss their advantages and limitations. RECENT FINDINGS The most advanced new PET tracers are the markers of the amyloid plaques, the τ compounds and the tracers of the translocator protein as markers of neuroinflammation. The main advantages but also the weaknesses of each of these markers are discussed. The main pitfall remains the heterogeneity of the available results that cast doubt to a rapid introduction of these new ligands in clinical practice. SUMMARY With the advent of biomarkers in clinical management and findings of molecular neuroimaging studies in the evaluation of patients with suspected dementia, the impact of functional neuroimaging has increased considerably these last years and has been integrated into many clinical guidelines in the field of dementia. In addition to conventional single PET brain perfusion and dopaminergic neurotransmission, 18F-fluorodeoxyglucose (18F-FDG) PET is used in advanced diagnosis procedures. Furthermore, new tracers are being developed to quantify key neuropathological features in the brain tissue as highly specific diagnosis is crucial to comply with the global medical and public health objectives in this domain. A strategic road map for further developments, adapted from the approach to cancer biomarkers, should be proposed so as to optimize the rationale of the PET-based molecular diagnosis of Alzheimer's disease and related disorders.
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Diagnostic utility of 18F-Fluorodeoxyglucose positron emission tomography (FDG-PET) in asymptomatic subjects at increased risk for Alzheimer's disease. Eur J Nucl Med Mol Imaging 2018; 45:1487-1496. [PMID: 29756163 DOI: 10.1007/s00259-018-4032-1] [Citation(s) in RCA: 17] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/11/2018] [Accepted: 04/16/2018] [Indexed: 12/14/2022]
Abstract
PURPOSE To assess the clinical utility of 18F-Fluorodeoxyglucose positron emission tomography (FDG-PET) for detection of early signs of neurodegeneration in conditions of increased risk for Alzheimer's disease (AD) as defined by: subjective cognitive decline (SCD), evidence of cerebral amyloid-pathology, apolipoprotein E (APOE) ε4-positive genotype, or autosomal dominant forms of AD (ADAD) in asymptomatic stages. METHODS A comprehensive literature search was conducted using the PICO model to extract evidence from relevant studies. An expert panel then voted using the Delphi method on three different diagnostic scenarios. RESULTS The level of empirical study evidence for the use of FDG-PET to detect meaningful early signs of neurodegeneration was considered to be poor for ADAD and lacking for SCD and asymptomatic persons at risk, based on APOE ε4-positive genotype or cerebral amyloid pathology. Consequently, and consistent with current diagnostic criteria, panelists decided not to recommend routine clinical use of FDG-PET in these situations and to currently mainly reserve it for research purposes. CONCLUSION Currently, there is limited evidence on which to base recommendations regarding the clinical routine use of FDG-PET to detect diagnostically meaningful early signs of neurodegeneration in asymptomatic subjects with ADAD, with APOE ε4-positive genotype, or with cerebral amyloid pathology, and in subjects with SCD. Future prospective studies are warranted and in part already ongoing, aiming to assess the added value of FDG-PET in this context beyond research applications.
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Diagnostic utility of FDG-PET in the differential diagnosis between different forms of primary progressive aphasia. Eur J Nucl Med Mol Imaging 2018; 45:1526-1533. [PMID: 29744573 PMCID: PMC6061469 DOI: 10.1007/s00259-018-4034-z] [Citation(s) in RCA: 21] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/12/2018] [Accepted: 04/16/2018] [Indexed: 12/14/2022]
Abstract
Purpose A joint effort of the European Association of Nuclear Medicine (EANM) and the European Academy of Neurology (EAN) aims at clinical guidance for the use of FDG-PET in neurodegenerative diseases. This paper addresses the diagnostic utility of FDG-PET over clinical/neuropsychological assessment in the differentiation of the three forms of primary progressive aphasia (PPA). Methods Seven panelists were appointed by the EANM and EAN and a literature search was performed by using harmonized PICO (Population, Intervention, Comparison, Outcome) question keywords. The studies were screened for eligibility, and data extracted to assess their methodological quality. Critical outcomes were accuracy indices in differentiating different PPA clinical forms. Subsequently Delphi rounds were held with the extracted data and quality assessment to reach a consensus based on both literature and expert opinion. Results Critical outcomes for this PICO were available in four of the examined papers. The level of formal evidence supporting clinical utility of FDG-PET in differentiating among PPA variants was considered as poor. However, the consensual recommendation was defined on Delphi round I, with six out of seven panelists supporting clinical use. Conclusions Quantitative evidence demonstrating utility or lack thereof is still missing. Panelists decided consistently to provide interim support for clinical use based on the fact that a typical atrophy or metabolic pattern is needed for PPA according to the diagnostic criteria, and the synaptic failure detected by FDG-PET is an earlier phenomenon than atrophy. Also, a normal FDG-PET points to a non-neurodegenerative cause.
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Clinical utility of FDG-PET for the clinical diagnosis in MCI. Eur J Nucl Med Mol Imaging 2018; 45:1497-1508. [DOI: 10.1007/s00259-018-4039-7] [Citation(s) in RCA: 35] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/14/2018] [Accepted: 04/19/2018] [Indexed: 10/17/2022]
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Popuri K, Balachandar R, Alpert K, Lu D, Bhalla M, Mackenzie IR, Hsiung RGY, Wang L, Beg MF. Development and validation of a novel dementia of Alzheimer's type (DAT) score based on metabolism FDG-PET imaging. NEUROIMAGE-CLINICAL 2018; 18:802-813. [PMID: 29876266 PMCID: PMC5988459 DOI: 10.1016/j.nicl.2018.03.007] [Citation(s) in RCA: 28] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 12/28/2017] [Revised: 02/25/2018] [Accepted: 03/07/2018] [Indexed: 12/22/2022]
Abstract
Fluorodeoxyglucose positron emission tomography (FDG-PET) imaging based 3D topographic brain glucose metabolism patterns from normal controls (NC) and individuals with dementia of Alzheimer's type (DAT) are used to train a novel multi-scale ensemble classification model. This ensemble model outputs a FDG-PET DAT score (FPDS) between 0 and 1 denoting the probability of a subject to be clinically diagnosed with DAT based on their metabolism profile. A novel 7 group image stratification scheme is devised that groups images not only based on their associated clinical diagnosis but also on past and future trajectories of the clinical diagnoses, yielding a more continuous representation of the different stages of DAT spectrum that mimics a real-world clinical setting. The potential for using FPDS as a DAT biomarker was validated on a large number of FDG-PET images (N=2984) obtained from the Alzheimer's Disease Neuroimaging Initiative (ADNI) database taken across the proposed stratification, and a good classification AUC (area under the curve) of 0.78 was achieved in distinguishing between images belonging to subjects on a DAT trajectory and those images taken from subjects not progressing to a DAT diagnosis. Further, the FPDS biomarker achieved state-of-the-art performance on the mild cognitive impairment (MCI) to DAT conversion prediction task with an AUC of 0.81, 0.80, 0.77 for the 2, 3, 5 years to conversion windows respectively.
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Affiliation(s)
- Karteek Popuri
- School of Engineering Science, Simon Fraser University, Canada
| | | | - Kathryn Alpert
- Feinberg School of Medicine, Northwestern University, USA
| | - Donghuan Lu
- School of Engineering Science, Simon Fraser University, Canada
| | - Mahadev Bhalla
- School of Engineering Science, Simon Fraser University, Canada
| | - Ian R Mackenzie
- Department of Pathology and Laboratory Medicine, University of British Columbia, Canada
| | | | - Lei Wang
- Feinberg School of Medicine, Northwestern University, USA
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Apostolova I, Lange C, Suppa P, Spies L, Klutmann S, Adam G, Grothe MJ, Buchert R. Impact of plasma glucose level on the pattern of brain FDG uptake and the predictive power of FDG PET in mild cognitive impairment. Eur J Nucl Med Mol Imaging 2018; 45:1417-1422. [DOI: 10.1007/s00259-018-3985-4] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/07/2017] [Accepted: 02/19/2018] [Indexed: 02/02/2023]
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Caminiti SP, Ballarini T, Sala A, Cerami C, Presotto L, Santangelo R, Fallanca F, Vanoli EG, Gianolli L, Iannaccone S, Magnani G, Perani D. FDG-PET and CSF biomarker accuracy in prediction of conversion to different dementias in a large multicentre MCI cohort. Neuroimage Clin 2018; 18:167-177. [PMID: 29387532 PMCID: PMC5790816 DOI: 10.1016/j.nicl.2018.01.019] [Citation(s) in RCA: 91] [Impact Index Per Article: 15.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/31/2017] [Revised: 11/15/2017] [Accepted: 01/18/2018] [Indexed: 01/29/2023]
Abstract
Background/aims In this multicentre study in clinical settings, we assessed the accuracy of optimized procedures for FDG-PET brain metabolism and CSF classifications in predicting or excluding the conversion to Alzheimer's disease (AD) dementia and non-AD dementias. Methods We included 80 MCI subjects with neurological and neuropsychological assessments, FDG-PET scan and CSF measures at entry, all with clinical follow-up. FDG-PET data were analysed with a validated voxel-based SPM method. Resulting single-subject SPM maps were classified by five imaging experts according to the disease-specific patterns, as "typical-AD", "atypical-AD" (i.e. posterior cortical atrophy, asymmetric logopenic AD variant, frontal-AD variant), "non-AD" (i.e. behavioural variant FTD, corticobasal degeneration, semantic variant FTD; dementia with Lewy bodies) or "negative" patterns. To perform the statistical analyses, the individual patterns were grouped either as "AD dementia vs. non-AD dementia (all diseases)" or as "FTD vs. non-FTD (all diseases)". Aβ42, total and phosphorylated Tau CSF-levels were classified dichotomously, and using the Erlangen Score algorithm. Multivariate logistic models tested the prognostic accuracy of FDG-PET-SPM and CSF dichotomous classifications. Accuracy of Erlangen score and Erlangen Score aided by FDG-PET SPM classification was evaluated. Results The multivariate logistic model identified FDG-PET "AD" SPM classification (Expβ = 19.35, 95% C.I. 4.8-77.8, p < 0.001) and CSF Aβ42 (Expβ = 6.5, 95% C.I. 1.64-25.43, p < 0.05) as the best predictors of conversion from MCI to AD dementia. The "FTD" SPM pattern significantly predicted conversion to FTD dementias at follow-up (Expβ = 14, 95% C.I. 3.1-63, p < 0.001). Overall, FDG-PET-SPM classification was the most accurate biomarker, able to correctly differentiate either the MCI subjects who converted to AD or FTD dementias, and those who remained stable or reverted to normal cognition (Expβ = 17.9, 95% C.I. 4.55-70.46, p < 0.001). Conclusions Our results support the relevant role of FDG-PET-SPM classification in predicting progression to different dementia conditions in prodromal MCI phase, and in the exclusion of progression, outperforming CSF biomarkers.
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Key Words
- AD, Alzheimer's disease
- AUC, area under curve
- Alzheimer's disease dementia
- CBD, corticobasal degeneration
- CDR, Clinical Dementia Rating
- CSF, cerebrospinal fluid
- Clinical setting
- DLB, dementia with Lewy bodies
- EANM, European Association of Nuclear Medicine
- Erlangen Score
- FDG, fluorodeoxyglucose
- FTD, frontotemporal dementia
- Frontotemporal dementia
- LR+, positive likelihood ratio
- LR-, negative likelihood ratio
- MCI, mild cognitive impairment
- PET, positron emission tomography
- PSP, progressive supranuclear palsy
- Prognosis
- aMCI, single-domain amnestic mild cognitive impairment
- bvFTD, behavioral variant of frontotemporal dementia
- md aMCI, multi-domain amnestic mild cognitive impairment
- md naMCI, multi-domain non-amnestic mild cognitive impairment
- naMCI, single-domain non-amnestic mild cognitive impairment
- p-tau, phosphorylated tau
- t-tau, total tau
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Affiliation(s)
- Silvia Paola Caminiti
- Vita-Salute San Raffaele University, Milan, Italy; Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Tommaso Ballarini
- Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Arianna Sala
- Vita-Salute San Raffaele University, Milan, Italy; Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Chiara Cerami
- Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy; Clinical Neuroscience Department, San Raffaele Turro Hospital, Milan, Italy
| | - Luca Presotto
- Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Roberto Santangelo
- Department of Neurology and INSPE, San Raffaele Scientific Institute, Milan, Italy
| | | | | | - Luigi Gianolli
- Nuclear Medicine Unit, IRCCS San Raffaele Hospital, Milan, Italy
| | - Sandro Iannaccone
- Clinical Neuroscience Department, San Raffaele Turro Hospital, Milan, Italy
| | - Giuseppe Magnani
- Department of Neurology and INSPE, San Raffaele Scientific Institute, Milan, Italy
| | - Daniela Perani
- Vita-Salute San Raffaele University, Milan, Italy; Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy; Nuclear Medicine Unit, IRCCS San Raffaele Hospital, Milan, Italy.
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Boccardi M, Gallo V, Yasui Y, Vineis P, Padovani A, Mosimann U, Giannakopoulos P, Gold G, Dubois B, Jack CR, Winblad B, Frisoni GB, Albanese E. The biomarker-based diagnosis of Alzheimer's disease. 2-lessons from oncology. Neurobiol Aging 2017; 52:141-152. [PMID: 28317645 DOI: 10.1016/j.neurobiolaging.2017.01.021] [Citation(s) in RCA: 33] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/05/2016] [Revised: 01/19/2017] [Accepted: 01/27/2017] [Indexed: 12/20/2022]
Abstract
Biomarkers for the diagnosis of Alzheimer's disease (AD) are not yet validated for use in clinical settings. We aim to provide a methodological framework for their systematic validation, by reference to that developed for oncology biomarkers. As for this discipline, the steps for the systematic validation of AD biomarkers need to target analytical validity, clinical validity, and clinical utility. However, the premises are different from oncology: the nature of disease (neurodegeneration vs. cancer), the purpose (improve diagnosis in clinically affected vs. screening preclinical individuals), and the target population (mild cognitive impairment patients referring to memory clinics vs. general population) lead to important differences, influencing both the design of validation studies and the use of selected biomarkers. This framework is applied within a wider initiative to assess the current available evidence on the clinical validity of biomarkers for AD, for the final aim to identify gaps and research priorities, and to inform coordinated research efforts boosting AD biomarkers research.
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Affiliation(s)
- Marina Boccardi
- Department of Psychiatry, LANVIE-Laboratory of Neuroimaging of Aging, University of Geneva, Geneva, Switzerland; Laboratory of Alzheimer's Neuroimaging and Epidemiology (LANE), IRCCS S.Giovanni di Dio-Fatebenefratelli, Brescia, Italy.
| | - Valentina Gallo
- Centre of Primary Care and Public Health, Queen Mary, University of London, Barts and the London School of Medicine, Blizard Institute, London, UK
| | - Yutaka Yasui
- School of Public Health, University of Alberta, Alberta, Canada; Department of Epidemiology & Cancer Control, St. Jude Children's Research Hospital, Memphis, TN, USA
| | - Paolo Vineis
- School of Public Health, Imperial College London, London, UK
| | - Alessandro Padovani
- Neurology Unit, Department of Clinical and Experimental Sciences, University Health and Wealth of Brescia, Brescia, Italy
| | - Urs Mosimann
- Gerontechnology & Rehabilitation Group, University of Bern, Bern, Switzerland; University Hospital of Old Age Psychiatry and Psychotherapy, University of Bern, Bern, Switzerland
| | | | - Gabriel Gold
- Department of Internal Medicine, Rehabilitation and Geriatrics, University Hospitals and University of Geneva, Thônex, Switzerland
| | - Bruno Dubois
- Dementia Research Center and Department of Neurology, Salpêtrière University Hospital, Paris University, Paris, France
| | | | - Bengt Winblad
- Center for Alzheimer Research, Division of Neurogeriatrics, Department of NVS, Karolinska Institutet, Huddinge, Sweden
| | - Giovanni B Frisoni
- Department of Psychiatry, LANVIE-Laboratory of Neuroimaging of Aging, University of Geneva, Geneva, Switzerland; Laboratory of Alzheimer's Neuroimaging and Epidemiology (LANE), IRCCS S.Giovanni di Dio-Fatebenefratelli, Brescia, Italy; Memory Clinic, University Hospitals and University of Geneva, Geneva, Switzerland
| | - Emiliano Albanese
- Department of Psychiatry, WHO Collaborating Centre, University of Geneva, Geneva, Switzerland
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65
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Abstract
A compelling need in the field of neurodegenerative diseases is the development and validation of biomarkers for early identification and differential diagnosis. The availability of positron emission tomography (PET) neuroimaging tools for the assessment of molecular biology and neuropathology has opened new venues in the diagnostic design and the conduction of new clinical trials. PET techniques, allowing the in vivo assessment of brain function and pathology changes, are increasingly showing great potential in supporting clinical diagnosis also in the early and even preclinical phases of dementia. This review will summarize the most recent evidence on fluorine-18 fluorodeoxyglucose-, amyloid -, tau -, and neuroinflammation - PET tools, highlighting strengths and limitations and possible new perspectives in research and clinical applications. Appropriate use of PET tools is crucial for a prompt diagnosis and target evaluation of new developed drugs aimed at slowing or preventing dementia.
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Affiliation(s)
- Leonardo Iaccarino
- 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
| | - Arianna Sala
- 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
| | - Silvia Paola Caminiti
- 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
| | - 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, IRCCS San Raffaele Hospital, Milan, Italy
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66
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Rice L, Bisdas S. The diagnostic value of FDG and amyloid PET in Alzheimer’s disease—A systematic review. Eur J Radiol 2017; 94:16-24. [DOI: 10.1016/j.ejrad.2017.07.014] [Citation(s) in RCA: 74] [Impact Index Per Article: 10.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/02/2017] [Revised: 06/13/2017] [Accepted: 07/17/2017] [Indexed: 12/12/2022]
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67
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Frisoni GB, Boccardi M, Barkhof F, Blennow K, Cappa S, Chiotis K, Démonet JF, Garibotto V, Giannakopoulos P, Gietl A, Hansson O, Herholz K, Jack CR, Nobili F, Nordberg A, Snyder HM, Ten Kate M, Varrone A, Albanese E, Becker S, Bossuyt P, Carrillo MC, Cerami C, Dubois B, Gallo V, Giacobini E, Gold G, Hurst S, Lönneborg A, Lovblad KO, Mattsson N, Molinuevo JL, Monsch AU, Mosimann U, Padovani A, Picco A, Porteri C, Ratib O, Saint-Aubert L, Scerri C, Scheltens P, Schott JM, Sonni I, Teipel S, Vineis P, Visser PJ, Yasui Y, Winblad B. Strategic roadmap for an early diagnosis of Alzheimer's disease based on biomarkers. Lancet Neurol 2017; 16:661-676. [PMID: 28721928 DOI: 10.1016/s1474-4422(17)30159-x] [Citation(s) in RCA: 406] [Impact Index Per Article: 58.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/19/2016] [Revised: 04/27/2017] [Accepted: 04/28/2017] [Indexed: 12/15/2022]
Abstract
The diagnosis of Alzheimer's disease can be improved by the use of biological measures. Biomarkers of functional impairment, neuronal loss, and protein deposition that can be assessed by neuroimaging (ie, MRI and PET) or CSF analysis are increasingly being used to diagnose Alzheimer's disease in research studies and specialist clinical settings. However, the validation of the clinical usefulness of these biomarkers is incomplete, and that is hampering reimbursement for these tests by health insurance providers, their widespread clinical implementation, and improvements in quality of health care. We have developed a strategic five-phase roadmap to foster the clinical validation of biomarkers in Alzheimer's disease, adapted from the approach for cancer biomarkers. Sufficient evidence of analytical validity (phase 1 of a structured framework adapted from oncology) is available for all biomarkers, but their clinical validity (phases 2 and 3) and clinical utility (phases 4 and 5) are incomplete. To complete these phases, research priorities include the standardisation of the readout of these assays and thresholds for normality, the evaluation of their performance in detecting early disease, the development of diagnostic algorithms comprising combinations of biomarkers, and the development of clinical guidelines for the use of biomarkers in qualified memory clinics.
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Affiliation(s)
- Giovanni B Frisoni
- Laboratory of Neuroimaging of Aging (LANVIE), University Hospitals and University of Geneva, Geneva, Switzerland; Department of Internal Medicine, University Hospitals and University of Geneva, Geneva, Switzerland.
| | - Marina Boccardi
- Laboratory of Neuroimaging of Aging (LANVIE), University Hospitals and University of Geneva, Geneva, Switzerland; Laboratory of Alzheimer Neuroimaging and Epidemiology (LANE), IRCCS S Giovanni di Dio-Fatebenefratelli, Brescia, Italy
| | - Frederik Barkhof
- Department of Radiology and Nuclear Medicine, VU University Medical Centre, Amsterdam, Netherlands; Institute of Neurology, University College London, London, UK; Institute of Healthcare Engineering, University College London, London, UK; European Society of Neuroradiology, Zurich, Switzerland
| | - Kaj Blennow
- Institute of Neuroscience and Physiology, Department of Psychiatry and Neurochemistry, Sahlgrenska Academy at University of Gothenburg, Gothenburg, Sweden; Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden; International Federation of Clinical Chemistry and Laboratory Medicine Working Group for CSF proteins (IFCC WG-CSF), Gothenburg, Sweden
| | - Stefano Cappa
- Department of Radiology and Nuclear Medicine, VU University Medical Centre, Amsterdam, Netherlands; Istituto Universitario di Studi Superiori di Pavia, Pavia, Italy, on behalf of Federation of European Neuropsychological Societies
| | - Konstantinos Chiotis
- Department of Neurobiology, Care Sciences and Society, Center for Alzheimer Research, Translational Alzheimer Neurobiology, Karolinska Institutet and Stockholm County Council, Stockholm, Sweden
| | - Jean-Francois Démonet
- Leenards Memory Centre, Department of Clinical Neuroscience, Centre Hospitalier Universitaire Vaudois, Lausanne, Switzerland
| | - Valentina Garibotto
- Nuclear Medicine and Molecular Imaging Division, University Hospitals and University of Geneva, Geneva, Switzerland
| | | | - Anton Gietl
- Institute for Regenerative Medicine-IREM, University of Zurich Campus Schlieren, Zurich, Switzerland
| | - Oskar Hansson
- Memory Clinic, Skåne University Hospital, Lund, Sweden; Clinical Memory Research Unit, Department of Clinical Sciences Malmö, Lund University, Lund, Sweden
| | - Karl Herholz
- Division of Neuroscience and Experimental Psychology, University of Manchester, Manchester, UK
| | | | - Flavio Nobili
- Department of Neuroscience (DINOGMI), University of Genoa, Genoa, Italy; IRCCS AOU San Martino-IST, Genoa, Italy, on behalf of the European Association of Nuclear Medicine
| | - Agneta Nordberg
- Department of Neurobiology, Care Sciences and Society, Center for Alzheimer Research, Translational Alzheimer Neurobiology, Karolinska Institutet and Stockholm County Council, Stockholm, Sweden; Department of Geriatric Medicine, Karolinska University Hospital Huddinge, Stockholm, Sweden
| | | | - Mara Ten Kate
- Department of Neurology, Alzheimer Centre, VU University Medical Centre, Amsterdam, Netherlands
| | - Andrea Varrone
- Department of Clinical Neuroscience, Centre for Psychiatry Research, Karolinska Institutet and Stockholm County Council, Stockholm, Sweden
| | - Emiliano Albanese
- Department of Psychiatry, University Hospitals and University of Geneva, Geneva, Switzerland
| | | | - Patrick Bossuyt
- Clinical Epidemiology, University of Amsterdam, Amsterdam, Netherlands, on behalf of the European Federation of Laboratory Medicine
| | | | - Chiara Cerami
- Clinical Neuroscience Department, Vita-Salute San Raffaele University, Milan, Italy; Division of Neuroscience, San Raffaele Scientific Institute, Milan, Italy
| | - Bruno Dubois
- Institut de la Mémoire et de la Maladie d'Alzheimer, Hôpital Pitié Salpêtrière, UPMC University Paris 6, Paris, France
| | - Valentina Gallo
- Centre for Primary Care and Public Health, Barts and The London School of Medicine, Blizard Institute, Queen Mary University of London, London, UK
| | - Ezio Giacobini
- Department of Internal Medicine, University Hospitals and University of Geneva, Geneva, Switzerland
| | - Gabriel Gold
- Service of Geriatrics, Department of Internal Medicine Rehabilitation and Geriatrics, University Hospitals and University of Geneva, Geneva, Switzerland
| | - Samia Hurst
- Institute for Ethics, History, and the Humanities, University Hospitals and University of Geneva, Geneva, Switzerland
| | - Anders Lönneborg
- Clinical Memory Research Unit, Department of Clinical Sciences Malmö, Lund University, Lund, Sweden
| | - Karl-Olof Lovblad
- Diagnostic and Interventional Neuroradiology, University Hospital of Geneva, Geneva, Switzerland
| | - Niklas Mattsson
- Memory Clinic, Skåne University Hospital, Lund, Sweden; Department of Neurology, Skåne University Hospital, Lund, Sweden; Clinical Memory Research Unit, Department of Clinical Sciences Malmö, Lund University, Lund, Sweden
| | - José-Luis Molinuevo
- Barcelona Beta Brain Research Centre, Pasqual Maragall Foundation, Barcelona, Spain
| | - Andreas U Monsch
- Memory Clinic, University Centre for Medicine of Ageing, Felix Platter Hospital, Basel, Switzerland
| | - Urs Mosimann
- Department of Old Age Psychiatry, University of Bern, Bern, Switzerland
| | - Alessandro Padovani
- Department of Clinical Neurosciences, Faculty of Medicine, University of Brescia, Brescia, Italy
| | - Agnese Picco
- Laboratory of Neuroimaging of Aging (LANVIE), University Hospitals and University of Geneva, Geneva, Switzerland; Department of Neuroscience (DINOGMI), University of Genoa, Genoa, Italy
| | - Corinna Porteri
- Bioethics Unit, IRCCS S Giovanni di Dio-Fatebenefratelli, Brescia, Italy
| | - Osman Ratib
- Department of Radiology, University Hospital of Geneva, Geneva, Switzerland; Division of Nuclear Medicine, University Hospital of Geneva, Geneva, Switzerland
| | - Laure Saint-Aubert
- Department of Neurobiology, Care Sciences and Society, Center for Alzheimer Research, Translational Alzheimer Neurobiology, Karolinska Institutet and Stockholm County Council, Stockholm, Sweden
| | - Charles Scerri
- Department of Pathology, Faculty of Medicine and Surgery, University of Malta, Msida, Malta; Alzheimer Europe, Luxembourg, Luxembourg
| | - Philip Scheltens
- Department of Neurology, Alzheimer Centre, VU University Medical Centre, Amsterdam, Netherlands
| | | | - Ida Sonni
- PET Centre, Department of Clinical Neurosciences, Karolinska Institutet and Stockholm County Council, Stockholm, Sweden; Division of Nuclear Medicine and Molecular Imaging, Stanford University, Standford, CA, USA
| | - Stefan Teipel
- German Center for Neurodegenerative Diseases (DZNE)-Rostock/Greifswald, Rostock, Germany; Department of Psychosomatic Medicine, University of Rostock, Rostock, Germany
| | - Paolo Vineis
- Faculty of Medicine, Imperial College London, London, UK
| | - Pieter Jelle Visser
- Department of Neurology, Alzheimer Centre, VU University Medical Centre, Amsterdam, Netherlands; Department of Psychiatry and Neuropsychology, School for Mental Health and Neuroscience, Maastricht University, Maastricht, the Netherlands
| | - Yutaka Yasui
- St Jude Children's Research Hospital, Memphis, TN, USA
| | - Bengt Winblad
- Department of Geriatric Medicine, Karolinska University Hospital Huddinge, Stockholm, Sweden; Department of Neurobiology, Care Siences and Society, Centre for Alzheimer Research, Division of Neurogeriatrics, Karolinska Institutet, Huddinge, Sweden; European Alzheimer's Disease Consortium
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68
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Abstract
The most definitive classification systems for dementia are based on the underlying pathology which, in turn, is categorized largely according to the observed accumulation of abnormal protein aggregates in neurons and glia. These aggregates perturb molecular processes, cellular functions and, ultimately, cell survival, with ensuing disruption of large-scale neural networks subserving cognitive, behavioural and sensorimotor functions. The functional domains affected and the evolution of deficits in these domains over time serve as footprints that the clinician can trace back with various levels of certainty to the underlying neuropathology. The process of phenotyping and syndromic classification has substantially improved over decades of careful clinicopathological correlation, and through the discovery of in vivo biomarkers of disease. Here, we present an overview of the salient features of the most common dementia subtypes - Alzheimer disease, vascular dementia, frontotemporal dementia and related syndromes, Lewy body dementias, and prion diseases - with an emphasis on neuropathology, relevant epidemiology, risk factors, and signature signs and symptoms.
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69
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Pagani M, Nobili F, Morbelli S, Arnaldi D, Giuliani A, Öberg J, Girtler N, Brugnolo A, Picco A, Bauckneht M, Piva R, Chincarini A, Sambuceti G, Jonsson C, De Carli F. Early identification of MCI converting to AD: a FDG PET study. Eur J Nucl Med Mol Imaging 2017; 44:2042-2052. [PMID: 28664464 DOI: 10.1007/s00259-017-3761-x] [Citation(s) in RCA: 66] [Impact Index Per Article: 9.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/09/2017] [Accepted: 06/13/2017] [Indexed: 01/02/2023]
Abstract
PURPOSE Mild cognitive impairment (MCI) is a transitional pathological stage between normal ageing (NA) and Alzheimer's disease (AD). Although subjects with MCI show a decline at different rates, some individuals remain stable or even show an improvement in their cognitive level after some years. We assessed the accuracy of FDG PET in discriminating MCI patients who converted to AD from those who did not. METHODS FDG PET was performed in 42 NA subjects, 27 MCI patients who had not converted to AD at 5 years (nc-MCI; mean follow-up time 7.5 ± 1.5 years), and 95 MCI patients who converted to AD within 5 years (MCI-AD; mean conversion time 1.8 ± 1.1 years). Relative FDG uptake values in 26 meta-volumes of interest were submitted to ANCOVA and support vector machine analyses to evaluate regional differences and discrimination accuracy. RESULTS The MCI-AD group showed significantly lower FDG uptake values in the temporoparietal cortex than the other two groups. FDG uptake values in the nc-MCI group were similar to those in the NA group. Support vector machine analysis discriminated nc-MCI from MCI-AD patients with an accuracy of 89% (AUC 0.91), correctly detecting 93% of the nc-MCI patients. CONCLUSION In MCI patients not converting to AD within a minimum follow-up time of 5 years and MCI patients converting within 5 years, baseline FDG PET and volume-based analysis identified those who converted with an accuracy of 89%. However, further analysis is needed in patients with amnestic MCI who convert to a dementia other than AD.
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Affiliation(s)
- Marco Pagani
- Institute of Cognitive Sciences and Technologies, CNR, Via Palestro 32, 00185, Rome, Italy. .,Department of Nuclear Medicine, Karolinska Hospital Stockholm, Stockholm, Sweden.
| | - Flavio Nobili
- Clinical Neurology, Department of Neuroscience (DINOGMI), University of Genoa and IRCCS AOU San Martino-IST, Genoa, Italy
| | - Silvia Morbelli
- Department of Nuclear Medicine, Department of Health Science (DISSAL), University of Genoa and IRCCS AOU San Martino-IST, Genoa, Italy
| | - Dario Arnaldi
- Clinical Neurology, Department of Neuroscience (DINOGMI), University of Genoa and IRCCS AOU San Martino-IST, Genoa, Italy
| | - Alessandro Giuliani
- Environment and Health Department, Istituto Superiore di Sanità, Rome, Italy
| | - Johanna Öberg
- Department of Hospital Physics, Karolinska Hospital, Stockholm, Sweden
| | - Nicola Girtler
- Clinical Neurology, Department of Neuroscience (DINOGMI), University of Genoa and IRCCS AOU San Martino-IST, Genoa, Italy.,Clinical Psychology, IRCCS AOU San Martino-IST, Genoa, Italy
| | - Andrea Brugnolo
- Clinical Neurology, Department of Neuroscience (DINOGMI), University of Genoa and IRCCS AOU San Martino-IST, Genoa, Italy
| | - Agnese Picco
- Clinical Neurology, Department of Neuroscience (DINOGMI), University of Genoa and IRCCS AOU San Martino-IST, Genoa, Italy
| | - Matteo Bauckneht
- Department of Nuclear Medicine, Department of Health Science (DISSAL), University of Genoa and IRCCS AOU San Martino-IST, Genoa, Italy
| | - Roberta Piva
- Department of Nuclear Medicine, Department of Health Science (DISSAL), University of Genoa and IRCCS AOU San Martino-IST, Genoa, Italy
| | - Andrea Chincarini
- National Institute of Nuclear Physics (INFN), Genoa section, Genoa, Italy
| | - Gianmario Sambuceti
- Department of Nuclear Medicine, Department of Health Science (DISSAL), University of Genoa and IRCCS AOU San Martino-IST, Genoa, Italy
| | - Cathrine Jonsson
- Medical Radiation Physics and Nuclear Medicine, Imaging and Physiology, Karolinska University Hospital, Stockholm, Sweden
| | - Fabrizio De Carli
- Institute of Molecular Bioimaging and Physiology, CNR - Genoa Unit, AOU San Martino-IST, Genoa, Italy
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