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Alzheimer Disease: HELP
Articles by Frederik Barkhof
Based on 169 articles published since 2010
(Why 169 articles?)
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Between 2010 and 2020, F. Barkhof wrote the following 169 articles about Alzheimer Disease.
 
+ Citations + Abstracts
Pages: 1 · 2 · 3 · 4 · 5 · 6 · 7
1 Guideline EFNS task force: the use of neuroimaging in the diagnosis of dementia. 2012

Filippi, M / Agosta, F / Barkhof, F / Dubois, B / Fox, N C / Frisoni, G B / Jack, C R / Johannsen, P / Miller, B L / Nestor, P J / Scheltens, P / Sorbi, S / Teipel, S / Thompson, P M / Wahlund, L-O / Anonymous3110734. ·Neuroimaging Research Unit, Division of Neuroscience, Institute of Experimental Neurology, San Raffaele Scientific Institute, Vita-Salute San Raffaele University, Milan, Italy. m.filippi@hsr.it ·Eur J Neurol · Pubmed #22900895.

ABSTRACT: BACKGROUND AND PURPOSE: The European Federation of the Neurological Societies (EFNS) guidelines on the use of neuroimaging in the diagnosis and management of dementia are designed to revise and expand previous EFNS recommendations for the diagnosis and management of patients with Alzheimer's disease (AD) and to provide an overview of the evidence for the use of neuroimaging techniques in non-AD dementias, as well as general recommendations that apply to all types of dementia in clinical practice. METHODS: The task force working group reviewed evidence from original research articles, meta-analyses and systematic reviews, published before April 2012. The evidence was classified, and consensus recommendations were given and graded according to the EFNS guidance regulations. RESULTS: Structural imaging, which should be performed at least once in the diagnostic work-up of patients with cognitive impairment, serves to exclude other potentially treatable diseases, to recognize vascular lesions and to identify specific findings to help distinguish different forms of neurodegenerative types of dementia. Although typical cases of dementia may not benefit from routine functional imaging, these tools are recommended in those cases where diagnosis remains in doubt after clinical and structural imaging work-up and in particular clinical settings. Amyloid imaging is likely to find clinical utility in several fields, including the stratification of patients with mild cognitive impairment into those with and without underlying AD and the evaluation of atypical AD presentations. CONCLUSIONS: A number of recommendations and good practice points are made to improve the diagnosis of AD and other dementias.

2 Review Secondary prevention of Alzheimer's dementia: neuroimaging contributions. 2018

Ten Kate, Mara / Ingala, Silvia / Schwarz, Adam J / Fox, Nick C / Chételat, Gaël / van Berckel, Bart N M / Ewers, Michael / Foley, Christopher / Gispert, Juan Domingo / Hill, Derek / Irizarry, Michael C / Lammertsma, Adriaan A / Molinuevo, José Luis / Ritchie, Craig / Scheltens, Philip / Schmidt, Mark E / Visser, Pieter Jelle / Waldman, Adam / Wardlaw, Joanna / Haller, Sven / Barkhof, Frederik. ·Department of Radiology and Nuclear Medicine, Neuroscience Campus Amsterdam, VU University Medical Center, Amsterdam, the Netherlands. m.tenkate1@vumc.nl. · Alzheimer Center & Department of Neurology, Neuroscience Campus Amsterdam, VU University Medical Center, PO Box 7056, 1007 MB, Amsterdam, the Netherlands. m.tenkate1@vumc.nl. · Department of Radiology and Nuclear Medicine, Neuroscience Campus Amsterdam, VU University Medical Center, Amsterdam, the Netherlands. · Takeda Pharmaceuticals Comparny, Cambridge, MA, USA. · Eli Lilly and Company, Indianapolis, Indiana, USA. · Dementia Research Centre, Department of Neurodegenerative Disease, UCL Institute of Neurology, London, UK. · Institut National de la Santé et de la Recherche Médicale, Inserm UMR-S U1237, Université de Caen-Normandie, GIP Cyceron, Caen, France. · Institute for Stroke and Dementia Research, Klinikum der Universität München, Ludwig-Maximilians-Universität LMU, Munich, Germany. · GE Healthcare Life Sciences, Amersham, UK. · Barcelonaβeta Brain Research Center, Pasqual Maragall Foundation, Barcelona, Spain. · IXICO Plc, London, UK. · Centre for Dementia Prevention, Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK. · Alzheimer Center & Department of Neurology, Neuroscience Campus Amsterdam, VU University Medical Center, PO Box 7056, 1007 MB, Amsterdam, the Netherlands. · Janssen Pharmaceutica NV, Beerse, Belgium. · Dementia Research Centre, University of Edinburgh, Edinburgh, UK. · Affidea Centre de Diagnostic Radiologique de Carouge, Geneva, Switzerland. · Insititutes of Neurology and Healthcare Engineering, University College London, London, UK. ·Alzheimers Res Ther · Pubmed #30376881.

ABSTRACT: BACKGROUND: In Alzheimer's disease (AD), pathological changes may arise up to 20 years before the onset of dementia. This pre-dementia window provides a unique opportunity for secondary prevention. However, exposing non-demented subjects to putative therapies requires reliable biomarkers for subject selection, stratification, and monitoring of treatment. Neuroimaging allows the detection of early pathological changes, and longitudinal imaging can assess the effect of interventions on markers of molecular pathology and rates of neurodegeneration. This is of particular importance in pre-dementia AD trials, where clinical outcomes have a limited ability to detect treatment effects within the typical time frame of a clinical trial. We review available evidence for the use of neuroimaging in clinical trials in pre-dementia AD. We appraise currently available imaging markers for subject selection, stratification, outcome measures, and safety in the context of such populations. MAIN BODY: Amyloid positron emission tomography (PET) is a validated in-vivo marker of fibrillar amyloid plaques. It is appropriate for inclusion in trials targeting the amyloid pathway, as well as to monitor treatment target engagement. Amyloid PET, however, has limited ability to stage the disease and does not perform well as a prognostic marker within the time frame of a pre-dementia AD trial. Structural magnetic resonance imaging (MRI), providing markers of neurodegeneration, can improve the identification of subjects at risk of imminent decline and hence play a role in subject inclusion. Atrophy rates (either hippocampal or whole brain), which can be reliably derived from structural MRI, are useful in tracking disease progression and have the potential to serve as outcome measures. MRI can also be used to assess comorbid vascular pathology and define homogeneous groups for inclusion or for subject stratification. Finally, MRI also plays an important role in trial safety monitoring, particularly the identification of amyloid-related imaging abnormalities (ARIA). Tau PET to measure neurofibrillary tangle burden is currently under development. Evidence to support the use of advanced MRI markers such as resting-state functional MRI, arterial spin labelling, and diffusion tensor imaging in pre-dementia AD is preliminary and requires further validation. CONCLUSION: We propose a strategy for longitudinal imaging to track early signs of AD including quantitative amyloid PET and yearly multiparametric MRI.

3 Review Strategic roadmap for an early diagnosis of Alzheimer's disease based on biomarkers. 2017

Frisoni, Giovanni B / Boccardi, Marina / Barkhof, Frederik / Blennow, Kaj / Cappa, Stefano / Chiotis, Konstantinos / Démonet, Jean-Francois / Garibotto, Valentina / Giannakopoulos, Panteleimon / Gietl, Anton / Hansson, Oskar / Herholz, Karl / Jack, Clifford R / Nobili, Flavio / Nordberg, Agneta / Snyder, Heather M / Ten Kate, Mara / Varrone, Andrea / Albanese, Emiliano / Becker, Stefanie / Bossuyt, Patrick / Carrillo, Maria C / Cerami, Chiara / Dubois, Bruno / Gallo, Valentina / Giacobini, Ezio / Gold, Gabriel / Hurst, Samia / Lönneborg, Anders / Lovblad, Karl-Olof / Mattsson, Niklas / Molinuevo, José-Luis / Monsch, Andreas U / Mosimann, Urs / Padovani, Alessandro / Picco, Agnese / Porteri, Corinna / Ratib, Osman / Saint-Aubert, Laure / Scerri, Charles / Scheltens, Philip / Schott, Jonathan M / Sonni, Ida / Teipel, Stefan / Vineis, Paolo / Visser, Pieter Jelle / Yasui, Yutaka / Winblad, Bengt. ·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. Electronic address: Giovanni.Frisoni@unige.ch. · 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. · 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. · 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. · 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. · Department of Neurobiology, Care Sciences and Society, Center for Alzheimer Research, Translational Alzheimer Neurobiology, Karolinska Institutet and Stockholm County Council, Stockholm, Sweden. · Leenards Memory Centre, Department of Clinical Neuroscience, Centre Hospitalier Universitaire Vaudois, Lausanne, Switzerland. · Nuclear Medicine and Molecular Imaging Division, University Hospitals and University of Geneva, Geneva, Switzerland. · Department of Psychiatry, University Hospitals and University of Geneva, Geneva, Switzerland. · Institute for Regenerative Medicine-IREM, University of Zurich Campus Schlieren, Zurich, Switzerland. · Memory Clinic, Skåne University Hospital, Lund, Sweden; Clinical Memory Research Unit, Department of Clinical Sciences Malmö, Lund University, Lund, Sweden. · Division of Neuroscience and Experimental Psychology, University of Manchester, Manchester, UK. · Department of Radiology, Mayo Clinic, Rochester, MN, USA. · 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. · 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. · Alzheimer's Association, Chicago, IL, USA. · Department of Neurology, Alzheimer Centre, VU University Medical Centre, Amsterdam, Netherlands. · Department of Clinical Neuroscience, Centre for Psychiatry Research, Karolinska Institutet and Stockholm County Council, Stockholm, Sweden. · Alzheimer's Switzerland, Yverdon-les-Bains, Switzerland. · Clinical Epidemiology, University of Amsterdam, Amsterdam, Netherlands, on behalf of the European Federation of Laboratory Medicine. · Clinical Neuroscience Department, Vita-Salute San Raffaele University, Milan, Italy; Division of Neuroscience, San Raffaele Scientific Institute, Milan, Italy. · Institut de la Mémoire et de la Maladie d'Alzheimer, Hôpital Pitié Salpêtrière, UPMC University Paris 6, Paris, France. · Centre for Primary Care and Public Health, Barts and The London School of Medicine, Blizard Institute, Queen Mary University of London, London, UK. · Department of Internal Medicine, University Hospitals and University of Geneva, Geneva, Switzerland. · Service of Geriatrics, Department of Internal Medicine Rehabilitation and Geriatrics, University Hospitals and University of Geneva, Geneva, Switzerland. · Institute for Ethics, History, and the Humanities, University Hospitals and University of Geneva, Geneva, Switzerland. · Clinical Memory Research Unit, Department of Clinical Sciences Malmö, Lund University, Lund, Sweden. · Diagnostic and Interventional Neuroradiology, University Hospital of Geneva, Geneva, Switzerland. · 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. · Barcelona Beta Brain Research Centre, Pasqual Maragall Foundation, Barcelona, Spain. · Memory Clinic, University Centre for Medicine of Ageing, Felix Platter Hospital, Basel, Switzerland. · Department of Old Age Psychiatry, University of Bern, Bern, Switzerland. · Department of Clinical Neurosciences, Faculty of Medicine, University of Brescia, Brescia, Italy. · Laboratory of Neuroimaging of Aging (LANVIE), University Hospitals and University of Geneva, Geneva, Switzerland; Department of Neuroscience (DINOGMI), University of Genoa, Genoa, Italy. · Bioethics Unit, IRCCS S Giovanni di Dio-Fatebenefratelli, Brescia, Italy. · Department of Radiology, University Hospital of Geneva, Geneva, Switzerland; Division of Nuclear Medicine, University Hospital of Geneva, Geneva, Switzerland. · Department of Pathology, Faculty of Medicine and Surgery, University of Malta, Msida, Malta; Alzheimer Europe, Luxembourg, Luxembourg. · Institute of Neurology, University College London, London, UK. · 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. · German Center for Neurodegenerative Diseases (DZNE)-Rostock/Greifswald, Rostock, Germany; Department of Psychosomatic Medicine, University of Rostock, Rostock, Germany. · Faculty of Medicine, Imperial College London, London, UK. · 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. · St Jude Children's Research Hospital, Memphis, TN, USA. · 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. ·Lancet Neurol · Pubmed #28721928.

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.

4 Review Clinical validity of medial temporal atrophy as a biomarker for Alzheimer's disease in the context of a structured 5-phase development framework. 2017

Ten Kate, Mara / Barkhof, Frederik / Boccardi, Marina / Visser, Pieter Jelle / Jack, Clifford R / Lovblad, Karl-Olof / Frisoni, Giovanni B / Scheltens, Philip / Anonymous960900. ·Department of Neurology, Alzheimer Center, Neuroscience Campus Amsterdam, VU University Medical Center, Amsterdam, the Netherlands. Electronic address: m.tenkate1@vumc.nl. · Department of Radiology & Nuclear Medicine, Neuroscience Campus Amsterdam, VU University Medical Center, Amsterdam, the Netherlands; European Society of Neuroradiology (ESNR); Institutes of Neurology and Healthcare Engineering, University College London, London, UK. · Laboratory of Alzheimer's Neuroimaging and Epidemiology (LANE), IRCCS S.Giovanni di Dio - Fatebenefratelli, Brescia, Italy; LANVIE (Laboratory of Neuroimaging of Aging) - Department of Psychiatry, University of Geneva, Geneva, Switzerland. · Department of Neurology, Alzheimer Center, Neuroscience Campus Amsterdam, VU University Medical Center, Amsterdam, the Netherlands; Department of Psychiatry & Neuropsychology, School for Mental Health and Neuroscience, Maastricht University, Maastricht, the Netherlands. · Department of Radiology, Mayo Clinic, Rochester, MN, USA. · Department of Neuroradiology, University Hospital of Geneva, Geneva, Switzerland. · Institutes of Neurology and Healthcare Engineering, University College London, London, UK; Memory Clinic - Department of Internal Medicine, University Hospital of Geneva, Geneva, Switzerland. · Department of Neurology, Alzheimer Center, Neuroscience Campus Amsterdam, VU University Medical Center, Amsterdam, the Netherlands. ·Neurobiol Aging · Pubmed #28317647.

ABSTRACT: Research criteria for Alzheimer's disease recommend the use of biomarkers for diagnosis, but whether biomarkers improve the diagnosis in clinical routine has not been systematically assessed. The aim is to evaluate the evidence for use of medial temporal lobe atrophy (MTA) as a biomarker for Alzheimer's disease at the mild cognitive impairment stage in routine clinical practice, with an adapted version of the 5-phase oncology framework for biomarker development. A literature review on visual assessment of MTA and hippocampal volumetry was conducted with other biomarkers addressed in parallel reviews. Ample evidence is available for phase 1 (rationale for use) and phase 2 (discriminative ability between diseased and control subjects). Phase 3 (early detection ability) is partly achieved: most evidence is derived from research cohorts or clinical populations with short follow-up, but validation in clinical mild cognitive impairment cohorts is required. In phase 4, only the practical feasibility has been addressed for visual rating of MTA. The rest of phase 4 and phase 5 have not yet been addressed.

5 Review Thinner temporal and parietal cortex is related to incident clinical progression to dementia in patients with subjective cognitive decline. 2016

Verfaillie, Sander C J / Tijms, Betty / Versteeg, Adriaan / Benedictus, Marije R / Bouwman, Femke H / Scheltens, Philip / Barkhof, Frederik / Vrenken, Hugo / van der Flier, Wiesje M. ·Alzheimer Center and Department of Neurology, VU University Medical Center, Amsterdam, The Netherlands. · Department of Radiology and Nuclear Medicine, VU University Medical Center, Amsterdam, The Netherlands. · Department of Radiology and Nuclear Medicine, VU University Medical Center, Amsterdam, The Netherlands; Institute of Neurology, UCL, London, UK; Institute of Healthcare Engineering, UCL, London, UK. · Department of Radiology and Nuclear Medicine, VU University Medical Center, Amsterdam, The Netherlands; Department of Physics and Medical Technology, VU University Medical Center, Amsterdam, The Netherlands. · Alzheimer Center and Department of Neurology, VU University Medical Center, Amsterdam, The Netherlands; Department of Epidemiology and Biostatistics, VU University Medical Center, Amsterdam, The Netherlands. ·Alzheimers Dement (Amst) · Pubmed #28054027.

ABSTRACT: INTRODUCTION: We aimed to investigate if thinner cortex of the Alzheimer's disease (AD)-signature region was related to clinical progression in patients with subjective cognitive decline (SCD). METHODS: We included 302 SCD patients with clinical follow-up (≥1 year) and three-dimensional T1 magnetic resonance imaging. We estimated AD-signature cortical thickness, consisting of nine frontal, parietal, and temporal gyri and hippocampal volume. We used Cox proportional hazard models (hazard ratios and 95% confidence intervals) to evaluate cortical thickness in relation to clinical progression to mild cognitive impairment (MCI) or dementia. RESULTS: After a follow-up of the mean (standard deviation) 3 (2) years, 49 patients (16%) showed clinical progression to MCI ( DISCUSSION: In SCD patients, thinner regional cortex is associated with clinical progression to dementia.

6 Review Using visual rating to diagnose dementia: a critical evaluation of MRI atrophy scales. 2015

Harper, Lorna / Barkhof, Frederik / Fox, Nick C / Schott, Jonathan M. ·Dementia Research Centre, University College London Institute of Neurology, London, UK. · Department of Radiology, VU University Medical Centre, Amsterdam, The Netherlands. ·J Neurol Neurosurg Psychiatry · Pubmed #25872513.

ABSTRACT: Visual rating scales, developed to assess atrophy in patients with cognitive impairment, offer a cost-effective diagnostic tool that is ideally suited for implementation in clinical practice. By focusing attention on brain regions susceptible to change in dementia and enforcing structured reporting of these findings, visual rating can improve the sensitivity, reliability and diagnostic value of radiological image interpretation. Brain imaging is recommended in all current diagnostic guidelines relating to dementia, and recent guidelines have also recommended the application of medial temporal lobe atrophy rating. Despite these recommendations, and the ease with which rating scales can be applied, there is still relatively low uptake in routine clinical assessments. Careful consideration of atrophy rating scales is needed to verify their diagnostic potential and encourage uptake among clinicians. Determining the added value of combining scores from visual rating in different brain regions may also increase the diagnostic value of these tools.

7 Review An algorithmic approach to structural imaging in dementia. 2014

Harper, Lorna / Barkhof, Frederik / Scheltens, Philip / Schott, Jonathan M / Fox, Nick C. ·Department of Neurodegenerative Disease, Dementia Research Centre, UCL Institute of Neurology, , London, UK. ·J Neurol Neurosurg Psychiatry · Pubmed #24133287.

ABSTRACT: Accurate and timely diagnosis of dementia is important to guide management and provide appropriate information and support to patients and families. Currently, with the exception of individuals with genetic mutations, postmortem examination of brain tissue remains the only definitive means of establishing diagnosis in most cases, however, structural neuroimaging, in combination with clinical assessment, has value in improving diagnostic accuracy during life. Beyond the exclusion of surgical pathology, signal change and cerebral atrophy visible on structural MRI can be used to identify diagnostically relevant imaging features, which provide support for clinical diagnosis of neurodegenerative dementias. While no structural imaging feature has perfect sensitivity and specificity for a given diagnosis, there are a number of imaging characteristics which provide positive predictive value and help to narrow the differential diagnosis. While neuroradiological expertise is invaluable in accurate scan interpretation, there is much that a non-radiologist can gain from a focused and structured approach to scan analysis. In this article we describe the characteristic MRI findings of the various dementias and provide a structured algorithm with the aim of providing clinicians with a practical guide to assessing scans.

8 Review Imaging markers for Alzheimer disease: which vs how. 2013

Frisoni, Giovanni B / Bocchetta, Martina / Chételat, Gael / Rabinovici, Gil D / de Leon, Mony J / Kaye, Jeffrey / Reiman, Eric M / Scheltens, Philip / Barkhof, Frederik / Black, Sandra E / Brooks, David J / Carrillo, Maria C / Fox, Nick C / Herholz, Karl / Nordberg, Agneta / Jack, Clifford R / Jagust, William J / Johnson, Keith A / Rowe, Christopher C / Sperling, Reisa A / Thies, William / Wahlund, Lars-Olof / Weiner, Michael W / Pasqualetti, Patrizio / Decarli, Charles / Anonymous2250765. ·LENITEM-Laboratory of Epidemiology, Neuroimaging and Telemedicine, IRCCS, S. Giovanni di Dio, Fatebenefratelli Brescia, Italy. gfrisoni@fatebenefratelli.it ·Neurology · Pubmed #23897875.

ABSTRACT: Revised diagnostic criteria for Alzheimer disease (AD) acknowledge a key role of imaging biomarkers for early diagnosis. Diagnostic accuracy depends on which marker (i.e., amyloid imaging, ¹⁸F-fluorodeoxyglucose [FDG]-PET, SPECT, MRI) as well as how it is measured ("metric": visual, manual, semiautomated, or automated segmentation/computation). We evaluated diagnostic accuracy of marker vs metric in separating AD from healthy and prognostic accuracy to predict progression in mild cognitive impairment. The outcome measure was positive (negative) likelihood ratio, LR+ (LR-), defined as the ratio between the probability of positive (negative) test outcome in patients and the probability of positive (negative) test outcome in healthy controls. Diagnostic LR+ of markers was between 4.4 and 9.4 and LR- between 0.25 and 0.08, whereas prognostic LR+ and LR- were between 1.7 and 7.5, and 0.50 and 0.11, respectively. Within metrics, LRs varied up to 100-fold: LR+ from approximately 1 to 100; LR- from approximately 1.00 to 0.01. Markers accounted for 11% and 18% of diagnostic and prognostic variance of LR+ and 16% and 24% of LR-. Across all markers, metrics accounted for an equal or larger amount of variance than markers: 13% and 62% of diagnostic and prognostic variance of LR+, and 29% and 18% of LR-. Within markers, the largest proportion of diagnostic LR+ and LR- variability was within ¹⁸F-FDG-PET and MRI metrics, respectively. Diagnostic and prognostic accuracy of imaging AD biomarkers is at least as dependent on how the biomarker is measured as on the biomarker itself. Standard operating procedures are key to biomarker use in the clinical routine and drug trials.

9 Review Alzheimer's disease: connecting findings from graph theoretical studies of brain networks. 2013

Tijms, Betty M / Wink, Alle Meije / de Haan, Willem / van der Flier, Wiesje M / Stam, Cornelis J / Scheltens, Philip / Barkhof, Frederik. ·Alzheimer Center and Department of Neurology, VU University Medical Center, Amsterdam, the Netherlands. betty.tijms@gmail.com ·Neurobiol Aging · Pubmed #23541878.

ABSTRACT: The interrelationships between pathological processes and emerging clinical phenotypes in Alzheimer's disease (AD) are important yet complicated to study, because the brain is a complex network where local disruptions can have widespread effects. Recently, properties in brain networks obtained with neuroimaging techniques have been studied in AD with tools from graph theory. However, the interpretation of graph alterations remains unclear, because the definition of connectivity depends on the imaging modality used. Here we examined which graph properties have been consistently reported to be disturbed in AD studies, using a heuristically defined "graph space" to investigate which theoretical models can best explain graph alterations in AD. Findings from structural and functional graphs point to a loss of highly connected areas in AD. However, studies showed considerable variability in reported group differences of most graph properties. This suggests that brain graphs might not be isometric, which complicates the interpretation of graph measurements. We highlight confounding factors such as differences in graph construction methods and provide recommendations for future research.

10 Review Imaging Alzheimer in 2011. 2011

Hazewinkel, Marieke / Barkhof, Frederik. ·Afdeling Radiologie, Academisch Ziekenhuis, Vrije Universiteit, De Boelelaan 1117, Postbus 7057, Amsterdam, The Netherlands. R.Wijhenke@vumc.nl ·Neuroradiology · Pubmed #21863421.

ABSTRACT: -- No abstract --

11 Review Heterogeneity of small vessel disease: a systematic review of MRI and histopathology correlations. 2011

Gouw, Alida A / Seewann, Alexandra / van der Flier, Wiesje M / Barkhof, Frederik / Rozemuller, Annemieke M / Scheltens, Philip / Geurts, Jeroen J G. ·VU University Medical Centre, Department of Neurology, De Boelelaan 1117, Amsterdam, The Netherlands. aa.gouw@vumc.nl ·J Neurol Neurosurg Psychiatry · Pubmed #20935330.

ABSTRACT: BACKGROUND: White matter hyperintensities (WMH), lacunes and microbleeds are regarded as typical MRI expressions of cerebral small vessel disease (SVD) and they are highly prevalent in the elderly. However, clinical expression of MRI defined SVD is generally moderate and heterogeneous. By reviewing studies that directly correlated postmortem MRI and histopathology, this paper aimed to characterise the pathological substrates of SVD in order to create more understanding as to its heterogeneous clinical manifestation. SUMMARY: Postmortem studies showed that WMH are also heterogeneous in terms of histopathology. Damage to the tissue ranges from slight disentanglement of the matrix to varying degrees of myelin and axonal loss. Glial cell responses include astrocytic reactions--for example, astrogliosis and clasmatodendrosis--as well as loss of oligodendrocytes and distinct microglial responses. Lipohyalinosis, arteriosclerosis, vessel wall leakage and collagen deposition in venular walls are recognised microvascular changes. Suggested pathogenetic mechanisms are ischaemia/hypoxia, hypoperfusion due to altered cerebrovascular autoregulation, blood-brain barrier leakage, inflammation, degeneration and amyloid angiopathy. Only a few postmortem MRI studies have addressed lacunes and microbleeds to date. Cortical microinfarcts and changes in the normal appearing white matter are 'invisible' on conventional MRI but are nevertheless expected to contribute substantially to clinical symptoms. CONCLUSION: Pathological substrates of WMH are heterogeneous in nature and severity, which may partly explain the weak clinicoradiological associations found in SVD. Lacunes and microbleeds have been relatively understudied and need to be further investigated. Future studies should also take into account 'MRI invisible' SVD features and consider the use of, for example, quantitative MRI techniques, to increase the sensitivity of MRI for these abnormalities and study their effects on clinical functioning.

12 Clinical Trial Resilience to cognitive impairment in the oldest-old: design of the EMIF-AD 90+ study. 2018

Legdeur, Nienke / Badissi, Maryam / Carter, Stephen F / de Crom, Sophie / van de Kreeke, Aleid / Vreeswijk, Ralph / Trappenburg, Marijke C / Oudega, Mardien L / Koek, Huiberdina L / van Campen, Jos P / Keijsers, Carolina J P W / Amadi, Chinenye / Hinz, Rainer / Gordon, Mark F / Novak, Gerald / Podhorna, Jana / Serné, Erik / Verbraak, Frank / Yaqub, Maqsood / Hillebrand, Arjan / Griffa, Alessandra / Pendleton, Neil / Kramer, Sophia E / Teunissen, Charlotte E / Lammertsma, Adriaan / Barkhof, Frederik / van Berckel, Bart N M / Scheltens, Philip / Muller, Majon / Maier, Andrea B / Herholz, Karl / Visser, Pieter Jelle. ·Alzheimer Center Amsterdam, Department of Neurology, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, PO Box 7057, 1007, MB, Amsterdam, the Netherlands. n.legdeur@vumc.nl. · Alzheimer Center Amsterdam, Department of Neurology, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, PO Box 7057, 1007, MB, Amsterdam, the Netherlands. · Wolfson Molecular Imaging Centre, Division of Neuroscience & Experimental Psychology, University of Manchester, Manchester, UK. · Department of Ophthalmology, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands. · Department of Geriatric Medicine, Spaarne Gasthuis, Haarlem, The Netherlands. · Department of Internal Medicine, Amstelland Hospital, Amstelveen, The Netherlands. · Department of Psychiatry, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands. · Department of Geriatric Medicine, University Medical Center Utrecht, Utrecht, The Netherlands. · Department of Geriatric Medicine, MC Slotervaart Hospital, Amsterdam, The Netherlands. · Department of Geriatric Medicine, Jeroen Bosch Hospital, 's-Hertogenbosch, The Netherlands. · Teva Pharmaceuticals, North Wales, Pennsylvania, USA. · Janssen Pharmaceutical Research and Development, Titusville, NJ, USA. · Boehringer Ingelheim International GmbH, Ingelheim/Rhein, Germany. · Department of Internal Medicine, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands. · Department of Radiology & Nuclear Medicine, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands. · Department of Clinical Neurophysiology and MEG Center, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands. · Dutch Connectome Lab, Department of Complex Trait Genetics, Center for Neuroscience and Cognitive Research, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands. · Department of Otolaryngology-Head and Neck Surgery, Section Ear & Hearing, Amsterdam Public Health Research Institute, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands. · Neurochemistry Laboratory, Department of Clinical chemistry, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands. · Institutes of Neurology and Healthcare Engineering, University College London, London, UK. · Department of Medicine and Aged Care, @AgeMelbourne, Royal Melbourne Hospital, University of Melbourne, Melbourne, Australia. · Department of Human Movement Sciences, @AgeAmsterdam, Amsterdam Movement Sciences, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands. · Department of Psychiatry & Neuropsychology, School for Mental Health and Neuroscience, Maastricht University, Maastricht, The Netherlands. ·BMC Geriatr · Pubmed #30477432.

ABSTRACT: BACKGROUND: The oldest-old (subjects aged 90 years and older) population represents the fastest growing segment of society and shows a high dementia prevalence rate of up to 40%. Only a few studies have investigated protective factors for cognitive impairment in the oldest-old. The EMIF-AD 90+ Study aims to identify factors associated with resilience to cognitive impairment in the oldest-old. In this paper we reviewed previous studies on cognitive resilience in the oldest-old and described the design of the EMIF-AD 90+ Study. METHODS: The EMIF-AD 90+ Study aimed to enroll 80 cognitively normal subjects and 40 subjects with cognitive impairment aged 90 years or older. Cognitive impairment was operationalized as amnestic mild cognitive impairment (aMCI), or possible or probable Alzheimer's Disease (AD). The study was part of the European Medical Information Framework for AD (EMIF-AD) and was conducted at the Amsterdam University Medical Centers (UMC) and at the University of Manchester. We will test whether cognitive resilience is associated with cognitive reserve, vascular comorbidities, mood, sleep, sensory system capacity, physical performance and capacity, genetic risk factors, hallmarks of ageing, and markers of neurodegeneration. Markers of neurodegeneration included an amyloid positron emission tomography, amyloid β and tau in cerebrospinal fluid/blood and neurophysiological measures. DISCUSSION: The EMIF-AD 90+ Study will extend our knowledge on resilience to cognitive impairment in the oldest-old by extensive phenotyping of the subjects and the measurement of a wide range of potential protective factors, hallmarks of aging and markers of neurodegeneration. TRIAL REGISTRATION: Nederlands Trial Register NTR5867 . Registered 20 May 2016.

13 Clinical Trial The value of subtraction MRI in detection of amyloid-related imaging abnormalities with oedema or effusion in Alzheimer's patients: An interobserver study. 2018

Martens, Roland M / Bechten, Arianne / Ingala, Silvia / van Schijndel, Ronald A / Machado, Vania B / de Jong, Marcus C / Sanchez, Esther / Purcell, Derk / Arrighi, Michael H / Brashear, Robert H / Wattjes, Mike P / Barkhof, Frederik. ·Department of Radiology and Nuclear Medicine, Neuroscience Campus Amsterdam, VU University Medical Center, PO Box 7057, 1007 MB, Amsterdam, The Netherlands. ro.martens@vumc.nl. · Department of Radiology and Nuclear Medicine, Neuroscience Campus Amsterdam, VU University Medical Center, PO Box 7057, 1007 MB, Amsterdam, The Netherlands. · Department of Radiology, California Pacific Medical Center, San Francisco, CA, USA. · BioClinica Inc, Newark, CA, USA. · Janssen Alzheimer Immunotherapy Research & Development, LLC, South San Francisco, CA, USA. · Institutes of Neurology and Healthcare Engineering, University College London, London, UK. ·Eur Radiol · Pubmed #28956123.

ABSTRACT: BACKGROUND: Immunotherapeutic treatments targeting amyloid-β plaques in Alzheimer's disease (AD) are associated with the presence of amyloid-related imaging abnormalities with oedema or effusion (ARIA-E), whose detection and classification is crucial to evaluate subjects enrolled in clinical trials. PURPOSE: To investigate the applicability of subtraction MRI in the ARIA-E detection using an established ARIA-E-rating scale. METHODS: We included 75 AD patients receiving bapineuzumab treatment, including 29 ARIA-E cases. Five neuroradiologists rated their brain MRI-scans with and without subtraction images. The accuracy of evaluating the presence of ARIA-E, intraclass correlation coefficient (ICC) and specific agreement was calculated. RESULTS: Subtraction resulted in higher sensitivity (0.966) and lower specificity (0.970) than native images (0.959, 0.991, respectively). Individual rater detection was excellent. ICC scores ranged from excellent to good, except for gyral swelling (moderate). Excellent negative and good positive specific agreement among all ARIA-E imaging features was reported in both groups. Combining sulcal hyperintensity and gyral swelling significantly increased positive agreement for subtraction images. CONCLUSION: Subtraction MRI has potential as a visual aid increasing the sensitivity of ARIA-E assessment. However, in order to improve its usefulness isotropic acquisition and enhanced training are required. The ARIA-E rating scale may benefit from combining sulcal hyperintensity and swelling. KEY POINTS: • Subtraction technique can improve detection amyloid-related imaging-abnormalities with edema/effusion in Alzheimer's patients. • The value of ARIA-E detection, classification and monitoring using subtraction was assessed. • Validation of an established ARIA-E rating scale, recommendations for improvement are reported. • Complementary statistical methods were employed to measure accuracy, inter-rater-reliability and specific agreement.

14 Clinical Trial A phase III randomized trial of gantenerumab in prodromal Alzheimer's disease. 2017

Ostrowitzki, Susanne / Lasser, Robert A / Dorflinger, Ernest / Scheltens, Philip / Barkhof, Frederik / Nikolcheva, Tania / Ashford, Elizabeth / Retout, Sylvie / Hofmann, Carsten / Delmar, Paul / Klein, Gregory / Andjelkovic, Mirjana / Dubois, Bruno / Boada, Mercè / Blennow, Kaj / Santarelli, Luca / Fontoura, Paulo / Anonymous4670929. ·Product Development, Neuroscience, Genentech Inc., South San Francisco, CA, USA. · MedDay Pharmaceuticals, Boston, MA, USA. · Formerly Roche Translational & Clinical Research Center, New York, NY, USA. · VU University Medical Center, Amsterdam, The Netherlands. · Institute of Neurology, UCL, London, UK. · Roche Pharma Research and Early Development, NORD, Basel, Switzerland. · Roche Products Limited, Welwyn Garden City, UK. · Roche Pharma Research and Early Development, Clinical Pharmacology, Roche Innovation Center, Basel, Switzerland. · Clinical Pharmacology and Bioanalytical R&D, Pharmaceutical Sciences, Roche Pharma Research and Early Development, Roche Innovation Center Basel, Basel, Switzerland. · Alzheimer Institute and ICM, UMR-S975, Salpêtrière University Hospital, AP-HP, Pierre and Marie Curie University, Paris, France. · Research Center and Memory Clinic of Fundació ACE, Institut Català de Neurociències Aplicades, Barcelona, Spain. · Formerly Roche Pharma Research and Early Development, NORD, Basel, Switzerland. · Clinical Pharmacology and Bioanalytical R&D, Pharmaceutical Sciences, Roche Pharma Research and Early Development, Roche Innovation Center Basel, Basel, Switzerland. paulo.fontoura@roche.com. ·Alzheimers Res Ther · Pubmed #29221491.

ABSTRACT: BACKGROUND: Gantenerumab is a fully human monoclonal antibody that binds aggregated amyloid-β (Aβ) and removes Aβ plaques by Fc receptor-mediated phagocytosis. In the SCarlet RoAD trial, we assessed the efficacy and safety of gantenerumab in prodromal Alzheimer's disease (AD). METHODS: In this randomized, double-blind, placebo-controlled phase III study, we investigated gantenerumab over 2 years. Patients were randomized to gantenerumab 105 mg or 225 mg or placebo every 4 weeks by subcutaneous injection. The primary endpoint was the change from baseline to week 104 in Clinical Dementia Rating Sum of Boxes (CDR-SB) score. We evaluated treatment effects on cerebrospinal fluid biomarkers (all patients) and amyloid positron emission tomography (substudy). A futility analysis was performed once 50% of patients completed 2 years of treatment. Safety was assessed in patients who received at least one dose. RESULTS: Of the 3089 patients screened, 797 were randomized. The study was halted early for futility; dosing was discontinued; and the study was unblinded. No differences between groups in the primary (least squares mean [95% CI] CDR-SB change from baseline 1.60 [1.28, 1.91], 1.69 [1.37, 2.01], and 1.73 [1.42, 2.04] for placebo, gantenerumab 105 mg, and gantenerumab 225 mg, respectively) or secondary clinical endpoints were observed. The incidence of generally asymptomatic amyloid-related imaging abnormalities increased in a dose- and APOE ε4 genotype-dependent manner. Exploratory analyses suggested a dose-dependent drug effect on clinical and biomarker endpoints. CONCLUSIONS: The study was stopped early for futility, but dose-dependent effects observed in exploratory analyses on select clinical and biomarker endpoints suggest that higher dosing with gantenerumab may be necessary to achieve clinical efficacy. TRIAL REGISTRATION: ClinicalTrials.gov, NCT01224106 . Registered on October 14, 2010.

15 Clinical Trial Central Review of Amyloid-Related Imaging Abnormalities in Two Phase III Clinical Trials of Bapineuzumab in Mild-To-Moderate Alzheimer's Disease Patients. 2017

Ketter, Nzeera / Brashear, H Robert / Bogert, Jennifer / Di, Jianing / Miaux, Yves / Gass, Achim / Purcell, Derk D / Barkhof, Frederik / Arrighi, H Michael. ·Janssen Alzheimer Immunotherapy Research and Development, LLC, South San Francisco, CA, USA. · Janssen Research and Development, LLC, Raritan, NJ, USA. · BioClinica Inc. (formerly Synarc), Newtown, PA, USA. · Department of Radiology, VU University Medical Center, Amsterdam, Netherlands. ·J Alzheimers Dis · Pubmed #28269765.

ABSTRACT: BACKGROUND: Amyloid-related imaging abnormalities (ARIA) consist of ARIA-E (with effusion or edema) and ARIA-H (hemosiderin deposits [HDs]). OBJECTIVES: To address accurate ascertainment of ARIA identification, a final magnetic resonance imaging (MRI) reading was performed on patients with mild-to-moderate Alzheimer's disease randomized to bapineuzumab IV or placebo during two Phase III trials (APOE ɛ4 allele carriers or noncarriers). METHODS: Final MRI central review consisted of a systematic sequential locked, adjudicated read in 1,331 APOE ɛ4 noncarriers and 1,121 carriers by independent neuroradiologists. Assessment of ARIA-E, ARIA-H, intracerebral hemorrhages, and age-related white matter changes is described. RESULTS: In the Final Read, treatment-emergent ARIA-E were identified in 242 patients including 76 additional cases not noted previously in real time. Overall, incidence proportion of ARIA-E was higher in carriers (active 21.2%; placebo 1.1%) than in noncarriers (pooled active 11.3%; placebo 0.6%), and was more often identified in homozygote APOE ɛ4 carriers than heterozygotes (34.5% versus 16.9%). Incidence rate of ARIA-E increased with increased dose in noncarriers. Frequency of ARIA-E first episodes was highest after the first and second bapineuzumab infusion and declined after repeated infusions. Incidence of total HDs <10 mm (cerebral microhemorrhages) was higher in active groups versus placebo. CONCLUSION: ARIA was detected more often on MRI scans when every scan was reviewed by trained neuroradiologists and results adjudicated. There was increased incidence of ARIA-E in bapineuzumab-treated carriers who had a microhemorrhage at baseline. ARIA-E was a risk factor for incident ARIA-H and late onset ARIA-E was milder radiologically. Age-related white matter changes did not progress during the study.

16 Clinical Trial Intravenous immunoglobulin for treatment of mild-to-moderate Alzheimer's disease: a phase 2, randomised, double-blind, placebo-controlled, dose-finding trial. 2013

Dodel, Richard / Rominger, Axel / Bartenstein, Peter / Barkhof, Frederik / Blennow, Kaj / Förster, Stefan / Winter, Yaroslav / Bach, Jan-Philipp / Popp, Julius / Alferink, Judith / Wiltfang, Jens / Buerger, Katharina / Otto, Markus / Antuono, Piero / Jacoby, Michael / Richter, Ralph / Stevens, James / Melamed, Isaac / Goldstein, Jerome / Haag, Stefan / Wietek, Stefan / Farlow, Martin / Jessen, Frank. ·University Hospital Giessen and Marburg, Philipps-University Marburg, Marburg, Germany. dodel@med.uni-marburg.de ·Lancet Neurol · Pubmed #23375965.

ABSTRACT: BACKGROUND: Three small trials suggest that intravenous immunoglobulin can affect biomarkers and symptoms of mild-to-moderate Alzheimer's disease. We tested the safety, effective dose, and infusion interval of intravenous immunoglobulin in such patients. METHODS: We did a multicentre, placebo-controlled phase 2 trial at seven sites in the USA and five in Germany. Participants with probable Alzheimer's disease aged 50-85 years were randomly assigned (by a computer-generated randomisation sequence, with block sizes of eight) to infusions every 4 weeks (0·2, 0·5, or 0·8 g intravenous immunoglobulin per kg bodyweight, or placebo) or infusions every 2 weeks (0·1, 0·25, or 0·4 g/kg, or placebo). Patients, caregivers, investigators assessing outcomes, and staff at imaging facilities and the clinical research organisation were masked to treatment allocation, but dispensing pharmacists, the statistician, and the person responsible for final PET analyses were not. Treatment was masked with opaque pouches and infusion lines. The primary endpoint was median area under the curve (AUC) of plasma amyloid β (Aβ)(1-40) between the last infusion and the final visit (2 weeks or 4 weeks depending on infusion interval) in the intention-to-treat population. The trial is registered at ClinicalTrials.gov (NCT00812565) and controlled-trials.com (ISRCTN64846759). FINDINGS: 89 patients were assessed for eligibility, of whom 58 were enrolled and 55 included in the primary analysis. Median AUC of plasma Aβ(1-40) was not significantly different for intravenous immunoglobulin compared with placebo for five of the six intervention groups (-18·0 [range -1347·0 to 1068·5] for 0·2 g/kg, -364·3 [-5834·5 to 1953·5] for 0·5 g/kg, and -351·8 [-1084·0 to 936·5] for 0·8 g/kg every 4 weeks vs -116·3 [-1379·0 to 5266·0] for placebo; and -13·8 [-1729·0 to 307·0] for 0·1 g/kg, and -32·5 [-1102·5 to 451·5] for 0·25 g/kg every 2 weeks vs 159·5 [51·5 to 303·0] for placebo; p>0·05 for all). The difference in median AUC of plasma Aβ(1-40) between the 0·4 g/kg every 2 weeks group (47·0 [range -341·0 to 72·5]) and the placebo group was significant (p=0·0216). 25 of 42 (60%) patients in the intervention group versus nine of 14 (64%) receiving placebo had an adverse event. Four of 42 (10%) patients in the intravenous immunoglobulin group versus four of 14 (29%) receiving placebo had a serious adverse event, including one stroke in the intervention group. INTERPRETATION: Intravenous immunoglobulin may have an acceptable safety profile. Our results did not accord with those from previous studies. Longer trials with greater power are needed to assess the cognitive and functional effects of intravenous immunoglobulin in patients with Alzheimer's disease.

17 Clinical Trial Longitudinal imaging of Alzheimer pathology using [11C]PIB, [18F]FDDNP and [18F]FDG PET. 2012

Ossenkoppele, Rik / Tolboom, Nelleke / Foster-Dingley, Jessica C / Adriaanse, Sofie F / Boellaard, Ronald / Yaqub, Maqsood / Windhorst, Albert D / Barkhof, Frederik / Lammertsma, Adriaan A / Scheltens, Philip / van der Flier, Wiesje M / van Berckel, Bart N M. ·Department of Neurology & Alzheimer Center, VU University Medical Center, PO Box 7057, 1007MB, Amsterdam, Netherlands. r.ossenkoppele@vumc.nl ·Eur J Nucl Med Mol Imaging · Pubmed #22441582.

ABSTRACT: PURPOSE: [(11)C]PIB and [(18)F]FDDNP are PET tracers for in vivo detection of the neuropathology underlying Alzheimer's disease (AD). [(18)F]FDG is a glucose analogue and its uptake reflects metabolic activity. The purpose of this study was to examine longitudinal changes in these tracers in patients with AD or mild cognitive impairment (MCI) and in healthy controls. METHODS: Longitudinal, paired, dynamic [(11)C]PIB and [(18)F]FDDNP (90 min each) and static [(18)F]FDG (15 min) PET scans were obtained in 11 controls, 12 MCI patients and 8 AD patients. The mean interval between baseline and follow-up was 2.5 years (range 2.0-4.0 years). Parametric [(11)C]PIB and [(18)F]FDDNP images of binding potential (BP(ND)) and [(18)F]FDG standardized uptake value ratio (SUVr) images were generated. RESULTS: A significant increase in global cortical [(11)C]PIB BP(ND) was found in MCI patients, but no changes were observed in AD patients or controls. Subsequent regional analysis revealed that this increase in [(11)C]PIB BP(ND) in MCI patients was most prominent in the lateral temporal lobe (p < 0.05). For [(18)F]FDDNP, no changes in global BP(ND) were found. [(18)F]FDG uptake was reduced at follow-up in the AD group only, especially in frontal, parietal and lateral temporal lobes (all p < 0.01). Changes in global [(11)C]PIB binding (ρ = -0.42, p < 0.05) and posterior cingulate [(18)F]FDG uptake (ρ = 0.54, p < 0.01) were correlated with changes in Mini-Mental-State Examination score over time across groups, whilst changes in [(18)F]FDDNP binding (ρ = -0.18, p = 0.35) were not. CONCLUSION: [(11)C]PIB and [(18)F]FDG track molecular changes in different stages of AD. We found increased amyloid load in MCI patients and progressive metabolic impairment in AD patients. [(18)F]FDDNP seems to be less useful for examining disease progression.

18 Article Prodromal Dementia with Lewy Bodies: Clinical Characterization and Predictors of Progression. 2020

van de Beek, Marleen / van Steenoven, Inger / van der Zande, Jessica J / Barkhof, Frederik / Teunissen, Charlotte E / van der Flier, Wiesje M / Lemstra, Afina W. ·Alzheimer Center Amsterdam, Department of Neurology, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam University Medical Centers, Amsterdam, The Netherlands. · Department of Radiology and Nuclear Medicine, Amsterdam Neuroscience, Amsterdam University Medical Centers, Amsterdam, the Netherlands. · Institutes of Neurology and Healthcare Engineering, University College London, London, England, United Kingdom. · Neurochemistry Laboratory and Biobank, Department of Clinical Chemistry, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam University Medical Centers, Amsterdam, the Netherlands. · Department of Epidemiology and Biostatistics, Vrije Universiteit Amsterdam, Amsterdam University Medical Centers, Amsterdam, the Netherlands. ·Mov Disord · Pubmed #32048343.

ABSTRACT: OBJECTIVE: The objective of this study was to examine clinical characteristics, cognitive decline, and predictors for time to dementia in prodromal dementia with Lewy bodies with mild cognitive impairment (MCI-LB) compared with prodromal Alzheimer's disease (MCI-AD). METHODS: We included 73 MCI-LB patients (12% female; 68 ± 6 years; Mini Mental State Examination, 27 ± 2) and 124 MCI-AD patients (48% female; 68 ± 7 years; Mini Mental State Examination, 27 ± 2) from the Amsterdam Dementia Cohort. Follow-up was available for 61 MCI-LB patients and all MCI-AD patients (3 ± 2 years). We evaluated dementia with Lewy bodies core features, neuropsychiatric symptoms, caregiver burden (Zarit caregiver burden interview), MRI, apolipoprotein genotype, and cerebrospinal fluid biomarkers (tau/Aβ RESULTS: Parkinsonism was the most frequently present core feature in MCI-LB (69%). MCI-LB patients more often had neuropsychiatric symptoms and scored higher on ZARIT when compared with the MCI-AD patients. Linear mixed models showed that at baseline, MCI-LB patients performed worse on nonmemory cognitive domains, whereas memory performance was worse in MCI-AD patients. Over time, MCI-LB patients declined faster on attention, whereas MCI-AD patients declined faster on the Mini Mental State Examination and memory. Cox proportional hazards regressions showed that in the MCI-LB patients, lower attention (hazard ratio [HR] = 1.6; 95% confidence interval [CI], 1.1-2.3) and more posterior cortical atrophy (HR = 3.0; 95% CI, 1.5-5.8) predicted shorter time to dementia. In the MCI-AD patients, worse performance on memory (HR = 1.1; 95% CI, 1.0-1.2) and executive functions (HR = 1.3; 95% CI, 1.0-1.6) were independently associated with time to Alzheimer's dementia. CONCLUSION: MCI-LB patients have distinct neuropsychiatric and cognitive profiles with prominent decline in attention when compared with MCI-AD patients. Our results highlight the importance of early diagnosis because symptoms already have an impact in the prodromal stages. © 2020 The Authors. Movement Disorders published by Wiley Periodicals, Inc. on behalf of International Parkinson and Movement Disorder Society.

19 Article Validation of Plasma Proteomic Biomarkers Relating to Brain Amyloid Burden in the EMIF-Alzheimer's Disease Multimodal Biomarker Discovery Cohort. 2020

Westwood, Sarah / Baird, Alison L / Anand, Sneha N / Nevado-Holgado, Alejo J / Kormilitzin, Andrey / Shi, Liu / Hye, Abdul / Ashton, Nicholas J / Morgan, Angharad R / Bos, Isabelle / Vos, Stephanie J B / Baker, Susan / Buckley, Noel J / Ten Kate, Mara / Scheltens, Philip / Teunissen, Charlotte E / Vandenberghe, Rik / Gabel, Silvy / Meersmans, Karen / Engelborghs, Sebastiaan / De Roeck, Ellen E / Sleegers, Kristel / Frisoni, Giovanni B / Blin, Olivier / Richardson, Jill C / Bordet, Régis / Molinuevo, José L / Rami, Lorena / Wallin, Anders / Kettunen, Petronella / Tsolaki, Magda / Verhey, Frans / Lléo, Alberto / Sala, Isabel / Popp, Julius / Peyratout, Gwendoline / Martinez-Lage, Pablo / Tainta, Mikel / Johannsen, Peter / Freund-Levi, Yvonne / Frölich, Lutz / Dobricic, Valerija / Legido-Quigley, Cristina / Bertram, Lars / Barkhof, Frederik / Zetterberg, Henrik / Morgan, B Paul / Streffer, Johannes / Visser, Pieter Jelle / Lovestone, Simon. ·Department of Psychiatry, University of Oxford, UK. · Maurice Wohl Clinical Neuroscience, Institute of Psychiatry, Psychology and Neuroscience, Kings College London, London, UK. · Department of Psychiatry and Neurochemistry, University of Gothenburg, Mölndal, Sweden. · Wallenberg Centre for Molecular & Translational Medicine, University of Gothenburg, Gothenburg, Sweden. · Dementia Research Institute Cardiff, Cardiff University, Cardiff, UK. · Department of Psychiatry and Neuropsychology, School for Mental Health and Neuroscience, Alzheimer Centrum Limburg, Maastricht University, Maastricht, the Netherlands. · Janssen R&D, Titusville, NJ, USA. · Alzheimer Center, VU University Medical Center, Amsterdam, the Netherlands. · University Hospital Leuven, Leuven, Belgium. · Laboratory for Cognitive Neurology, Department of Neurosciences, KU Leuven, Belgium. · Department of Neurology and Memory Clinic, Hospital Network Antwerp (ZNA) Middelheim and Hoge Beuken, University of Antwerp, Antwerp, Belgium. · Center for Neurosciences, Vrije Universiteit Brussel (VUB), Brussels, Belgium. · Neurodegenerative Brain Diseases Group, Center for Molecular Neurology, VIB, Belgium. · University of Geneva, Geneva, Switzerland. · IRCCS Istituto Centro San Giovanni di Dio Fatebenefratelli, Brescia, Italy. · AIX Marseille University, INS, Ap-Hm, Marseille, France. · Neurosciences Therapeutic Area, GlaxoSmithKline R&D, Stevenage, UK. · University of Lille, Inserm, CHU Lille, France. · Alzheimer's Disease & Other Cognitive Disorders Unit, Hopsital Clínic-IDIBAPS, Barcelona, Spain. · Barcelona Beta Brain Research Center, Unversitat Pompeu Fabra, Barcelona, Spain. · Institute of Neuroscience and Physiology, Sahlgrenska Academy at University of Gothenburg, Gothenburg, Sweden. · 1st Department of Neurology, AHEPA University Hospital, Makedonia, Thessaloniki, Greece. · Hospital de la Santa Creu i Sant Pau, Barcelona, Spain. · Department of Neurology, Hospital de la Santa Creu i Sant Pau, Barcelona, Spain. · University Hospital of Lausanne, Lausanne, Switzerland. · Geriatric Psychiatry, Department of Mental Health and Psychiatry, Geneva University Hospitals, Geneva, Switzerland. · CITA-Alzheimer Foundation, San Sebastian, Spain. · Danish Dementia Research Centre, Rigshospitalet, Copenhagen University Hospital, Copenhagen, Denmark. · Department of Neurobiology, Caring Sciences and Society (NVS), Division of Clinical Geriatrics, Karolinska Institutet, and Department of Geriatric Medicine, Karolinska University Hospital Huddinge, Stockholm, Sweden. · Department of Geriatric Psychiatry, Zentralinstitut für Seelische Gesundheit, University of Heidelberg, Mannheim, Germany. · Lübeck Interdisciplinary Platform for Genome Analytics, Institutes of Neurogenetics and Cardiogenetics, University of Lübeck, Lübeck, Germany. · Kings College London, London, UK. · The Systems Medicine Group, Steno Diabetes Center, Gentofte, Denmark. · Department of Psychology, University of Oslo, Oslo, Norway. · Department of Radiology and Nuclear Medicine, VU University Medical Center, Amsterdam, The Netherland. · UCL Institutes of Neurology and Healthcare Engineering, London, UK. · Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden. · UK Dementia Research Institute at UCL, London, UK. · Department of Neurodegenerative Disease, UCL Institute of Neurology, London, UK. · UCB, Braine-l'Alleud, Belgium, formerly Janssen R&D, LLC. Beerse, Belgium at the Time of Study Conduct. · Janssen R&D, UK formerly affiliation (1) at the Time of the Study Conduct. ·J Alzheimers Dis · Pubmed #31985466.

ABSTRACT: We have previously investigated, discovered, and replicated plasma protein biomarkers for use to triage potential trials participants for PET or cerebrospinal fluid measures of Alzheimer's disease (AD) pathology. This study sought to undertake validation of these candidate plasma biomarkers in a large, multi-center sample collection. Targeted plasma analyses of 34 proteins with prior evidence for prediction of in vivo pathology were conducted in up to 1,000 samples from cognitively healthy elderly individuals, people with mild cognitive impairment, and in patients with AD-type dementia, selected from the EMIF-AD catalogue. Proteins were measured using Luminex xMAP, ELISA, and Meso Scale Discovery assays. Seven proteins replicated in their ability to predict in vivo amyloid pathology. These proteins form a biomarker panel that, along with age, could significantly discriminate between individuals with high and low amyloid pathology with an area under the curve of 0.74. The performance of this biomarker panel remained consistent when tested in apolipoprotein E ɛ4 non-carrier individuals only. This blood-based panel is biologically relevant, measurable using practical immunocapture arrays, and could significantly reduce the cost incurred to clinical trials through screen failure.

20 Article Why Is Amyloid-β PET Requested After Performing CSF Biomarkers? 2020

Reimand, Juhan / Groot, Colin / Teunissen, Charlotte E / Windhorst, Albert D / Boellaard, Ronald / Barkhof, Frederik / Nazarenko, Sergei / van der Flier, Wiesje M / van Berckel, Bart N M / Scheltens, Philip / Ossenkoppele, Rik / Bouwman, Femke. ·Department of Neurology & Alzheimer Center Amsterdam, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, the Netherlands. · Department of Health Technologies, Tallinn University of Technology, Tallinn, Estonia. · Radiology Centre, North Estonia Medical Centre, Tallinn, Estonia. · Neurochemistry Laboratory, Department of Clinical Chemistry, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands. · Department of Radiology & Nuclear Medicine, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands. · Centre for Medical Image Computing, Medical Physics and Biomedical Engineering, UCL, United Kingdom. · Department of Epidemiology & Biostatistics, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, the Netherlands. · Clinical Memory Research Unit, Lund University, Lund, Sweden. ·J Alzheimers Dis · Pubmed #31796674.

ABSTRACT: BACKGROUND: Amyloid-β positron emission tomography (PET) and cerebrospinal fluid (CSF) Aβ42 are considered interchangeable for clinical diagnosis of Alzheimer's disease. OBJECTIVE: To explore the clinical reasoning for requesting additional amyloid-β PET after performing CSF biomarkers. METHODS: We retrospectively identified 72 memory clinic patients who underwent amyloid-β PET after CSF biomarkers analysis for clinical diagnostic evaluation between 2011 and 2019. We performed patient chart reviews to identify factors which led to additional amyloid-β PET. Additionally, we assessed accordance with appropriate-use-criteria (AUC) for amyloid-β PET. RESULTS: Mean patient age was 62.0 (SD = 8.1) and mean Mini-Mental State Exam score was 23.6 (SD = 3.8). CSF analysis conflicting with the clinical diagnosis was the most frequent reason for requesting an amyloid-β PET scan (n = 53, 74%), followed by incongruent MRI (n = 16, 22%), unusual clinical presentation (n = 11, 15%) and young age (n = 8, 11%). An amyloid-β PET scan was rarely (n = 5, 7%) requested in patients with a CSF Aβ+/tau+ status. Fifteen (47%) patients with a post-PET diagnosis of AD had a predominantly non-amnestic presentation. In n = 11 (15%) cases, the reason that the clinician requested amyloid-β was not covered by AUC. This happened most often (n = 7) when previous CSF analysis did not support current clinical diagnosis, which led to requesting amyloid-β PET. CONCLUSION: In this single-center study, the main reason for requesting an amyloid-β PET scan after performing CSF biomarkers was the occurrence of a mismatch between the primary clinical diagnosis and CSF Aβ/tau results.

21 Article CSF cutoffs for MCI due to AD depend on APOEε4 carrier status. 2019

Marizzoni, Moira / Ferrari, Clarissa / Babiloni, Claudio / Albani, Diego / Barkhof, Frederik / Cavaliere, Libera / Didic, Mira / Forloni, Gianluigi / Fusco, Federica / Galluzzi, Samantha / Hensch, Tilman / Jovicich, Jorge / Marra, Camillo / Molinuevo, José Luis / Nobili, Flavio / Parnetti, Lucilla / Payoux, Pierre / Ranjeva, Jean-Philippe / Ribaldi, Federica / Rolandi, Elena / Rossini, Paolo Maria / Salvatore, Marco / Soricelli, Andrea / Tsolaki, Magda / Visser, Pieter Jelle / Wiltfang, Jens / Richardson, Jill C / Bordet, Régis / Blin, Olivier / Frisoni, Giovanni B. ·Laboratory of Neuroimaging and Alzheimer's Epidemiology, IRCCS Istituto Centro San Giovanni di Dio Fatebenefratelli, Brescia, Italy. Electronic address: mmarizzoni@fatebenefratelli.eu. · Unit of Statistics, IRCCS Istituto Centro San Giovanni di Dio Fatebenefratelli, Brescia, Italy. · Department of Physiology and Pharmacology "V. Erspamer", Sapienza University of Rome, Rome, Italy; Hospital San Raffaele Cassino (FR), Cassino, Italy. · Neuroscience Department, IRCCS - Istituto di Ricerche Farmacologiche Mario Negri, Milano, Italy. · Department of Radiology and Nuclear Medicine, Amsterdam UMC Location VUmc, Amsterdam, the Netherlands; Institutes of Neurology and Healthcare Engineering, UCL, London, UK. · Laboratory of Neuroimaging and Alzheimer's Epidemiology, IRCCS Istituto Centro San Giovanni di Dio Fatebenefratelli, Brescia, Italy. · Aix Marseille Univ, INSERM, INS, Inst Neurosci Syst, Marseille, France; APHM, Timone, Service de Neurologie et Neuropsychologie, APHM Hôpital Timone Adultes, Marseille, France. · Department of Psychiatry and Psychotherapy, University of Leipzig, Leipzig, Germany. · Center for Mind/Brain Sciences, University of Trento, Trento, Italy. · Department of Gerontology, Neurosciences & Orthopedics, Catholic University, Rome, Italy. · Alzheimer's Disease Unit and Other Cognitive Disorders Unit, Hospital Clínic de Barcelona, Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona, Catalunya, Spain. · Dept. of Neuroscience (DINOGMI), University of Genoa, Genoa, Italy; Clinica Neurologica, IRCCS Ospedale Policlinico San Martino, Genoa, Italy. · Clinica Neurologica, Università di Perugia, Ospedale Santa Maria della Misericordia, Perugia, Italy. · ToNIC, Toulouse NeuroImaging Center, Université de Toulouse, Inserm, UPS, France. · Aix-Marseille Université, INSERM, Marseille, France; Service de Neurologie et Neuropsychologie, APHM Hôpital Timone Adultes, Marseille, France. · Laboratory of Neuroimaging and Alzheimer's Epidemiology, IRCCS Istituto Centro San Giovanni di Dio Fatebenefratelli, Brescia, Italy; Department of Molecular and Translational Medicine, University of Brescia, Brescia, Italy. · Area Neuroscience, IRCCS San Raffaele, Rome, Italy. · SDN Istituto di Ricerca Diagnostica e Nucleare, Napoli, Italy. · 1st University Department of Neurology, Aristotle University of Thessaloniki, Thessaloniki, Makedonia, Greece. · Department of Neurology, Alzheimer Centre, VU Medical Centre, Amsterdam, the Netherlands. · Department of Psychiatry and Psychotherapy, LVR-Hospital Essen, Faculty of Medicine, University of Duisburg-Essen, Essen, Germany; Department of Psychiatry and Psychotherapy, University Medical Center (UMG), Georg-August-University, Goettingen, Germany; Medical Sciences Department, iBiMED, University of Aveiro, Aveiro, Portugal. · Neurosciences Therapeutic Area, GlaxoSmithKline R&D, Stevenage, UK. · University of Lille, Inserm, CHU, Lille, France; U1171 - Degenerative and Vascular Cognitive Disorders, Lille, France. · Aix Marseille University, UMR-INSERM 1106, Service de Pharmacologie Clinique, APHM, Marseille, France. · Memory Clinic and LANVIE - Laboratory of Neuroimaging of Aging, University Hospitals and University of Geneva, Geneva, Switzerland. ·Neurobiol Aging · Pubmed #32029236.

ABSTRACT: Amyloid and tau pathological accumulation should be considered for Alzheimer's disease (AD) definition and before subjects' enrollment in disease-modifying trials. Although age, APOEε4, and sex influence cerebrospinal fluid (CSF) biomarker levels, none of these variables are considered by current normality/abnormality cutoffs. Using baseline CSF data from 2 independent cohorts (PharmaCOG/European Alzheimer's Disease Neuroimaging Initiative and Alzheimer's Disease Neuroimaging Initiative), we investigated the effect of age, APOEε4 status, and sex on CSF Aβ42/P-tau distribution and cutoff extraction by applying mixture models with covariates. The Aβ42/P-tau distribution revealed the presence of 3 subgroups (AD-like, intermediate, control-like) and 2 cutoffs. The identification of the intermediate subgroup and of the higher cutoff was APOEε4 dependent in both cohorts. APOE-specific classification (higher cutoff for APOEε4+, lower cutoff for APOEε4-) showed higher diagnostic accuracy in identifying MCI due to AD compared to single Aβ42 and Aβ42/P-tau cutoffs. APOEε4 influences amyloid and tau CSF markers and AD progression in MCI patients supporting i) the use of APOE-specific cutoffs to identify MCI due to AD and ii) the utility of considering APOE genotype for early AD diagnosis.

22 Article Differences in topological progression profile among neurodegenerative diseases from imaging data. 2019

Garbarino, Sara / Lorenzi, Marco / Oxtoby, Neil P / Vinke, Elisabeth J / Marinescu, Razvan V / Eshaghi, Arman / Ikram, M Arfan / Niessen, Wiro J / Ciccarelli, Olga / Barkhof, Frederik / Schott, Jonathan M / Vernooij, Meike W / Alexander, Daniel C / Anonymous3461122. ·Centre for Medical Image Computing, Department of Computer Science, University College London, London, United Kingdom. · Université Côte d'Azur, Inria, Epione Research Project, Sophia Antipolis, France. · Department of Epidemiology, Erasmus Medical Center, Rotterdam, Netherlands. · Queen Square Multiple Sclerosis Centre, UCL Queen Square Institute of Neurology, Faculty of Brain Sciences, University College London, London, United Kingdom. · Department of Radiology and Nuclear medicine, Erasmus MC, Rotterdam, Netherlands. · Department of Radiology and Nuclear medicine, VUmc, Amsterdam, Netherlands. · Dementia Research Centre, Institute of Neurology, University College London, London, United Kingdom. ·Elife · Pubmed #31793876.

ABSTRACT: The spatial distribution of atrophy in neurodegenerative diseases suggests that brain connectivity mediates disease propagation. Different descriptors of the connectivity graph potentially relate to different underlying mechanisms of propagation. Previous approaches for evaluating the influence of connectivity on neurodegeneration consider each descriptor in isolation and match predictions against late-stage atrophy patterns. We introduce the notion of a

23 Article Exploring effects of Souvenaid on cerebral glucose metabolism in Alzheimer's disease. 2019

Scheltens, Nienke M E / Briels, Casper T / Yaqub, Maqsood / Barkhof, Frederik / Boellaard, Ronald / van der Flier, Wiesje M / Schwarte, Lothar A / Teunissen, Charlotte E / Attali, Amos / Broersen, Laus M / van Berckel, Bart N M / Scheltens, Philip. ·Alzheimer Center Amsterdam, Department of Neurology, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, the Netherlands. · Department of Radiology and Nuclear Medicine, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, the Netherlands. · Institutes of Neurology and healthcare engineering, UCL, London, UK. · Department of Epidemiology and Biostatistics, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, the Netherlands. · Department of Anaesthesiology, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, the Netherlands. · Neurochemistry Laboratory and Biobank, Department of Clinical Chemistry, Vrije Universiteit Amsterdam, Amsterdam Neuroscience, Amsterdam UMC, Amsterdam, the Netherlands. · Danone Nutricia Research, Nutricia Advanced Medical Nutrition, Utrecht, the Netherlands. ·Alzheimers Dement (N Y) · Pubmed #31650005.

ABSTRACT: Introduction: Alzheimer's disease (AD) is associated with synapse loss. Souvenaid, containing the specific nutrient combination Fortasyn Connect, was designed to improve synapse formation and function. The NL-ENIGMA study explored the effect of Souvenaid on synapse function in early AD by assessing cerebral glucose metabolism (CMRglc) with Methods: We conducted an exploratory double-blind randomized controlled single-center trial. Fifty patients with mild cognitive impairment or mild dementia with evidence of amyloid pathology (cerebrospinal fluid or PET) were stratified for MMSE (20-24 and 25-30) and randomly 1:1 allocated to 24-week daily administration of 125 mL Souvenaid (n = 25) or placebo (n = 25). Dynamic 60-minute [ Results: No baseline differences between treatment groups were found (placebo/intervention: n = 25/25; age 66 ± 8/65 ± 7 years; female 44%/48%; MMSE 25 ± 3/25 ± 3). [ Discussion: In this exploratory trial, we found no robust effect of 24-week intervention with Souvenaid on synapse function measured by [

24 Article Assessment of the appropriate use criteria for amyloid PET in an unselected memory clinic cohort: The ABIDE project. 2019

de Wilde, Arno / Ossenkoppele, Rik / Pelkmans, Wiesje / Bouwman, Femke / Groot, Colin / van Maurik, Ingrid / Zwan, Marissa / Yaqub, Maqsood / Barkhof, Frederik / Lammertsma, Adriaan A / Biessels, Geert Jan / Scheltens, Philip / van Berckel, Bart N / van der Flier, Wiesje M. ·Department of Neurology, Amsterdam Neuroscience, Alzheimer Center, VU University, Amsterdam UMC, Amsterdam, the Netherlands. Electronic address: a.dewilde@amsterdamumc.nl. · Department of Neurology, Amsterdam Neuroscience, Alzheimer Center, VU University, Amsterdam UMC, Amsterdam, the Netherlands; Department of Radiology and Nuclear Medicine, Amsterdam Neuroscience, VU University, Amsterdam UMC, Amsterdam, the Netherlands; Clinical Memory Research Unit, Lund University, Malmö, Sweden. · Department of Neurology, Amsterdam Neuroscience, Alzheimer Center, VU University, Amsterdam UMC, Amsterdam, the Netherlands. · Department of Neurology, Amsterdam Neuroscience, Alzheimer Center, VU University, Amsterdam UMC, Amsterdam, the Netherlands; Department of Radiology and Nuclear Medicine, Amsterdam Neuroscience, VU University, Amsterdam UMC, Amsterdam, the Netherlands. · Department of Radiology and Nuclear Medicine, Amsterdam Neuroscience, VU University, Amsterdam UMC, Amsterdam, the Netherlands. · Department of Radiology and Nuclear Medicine, Amsterdam Neuroscience, VU University, Amsterdam UMC, Amsterdam, the Netherlands; Institutes of Neurology and Healthcare Engineering, UCL, London, UK. · Department of Neurology and Neurosurgery, Brain Center Rudolf Magnus, University Medical Center Utrecht, Utrecht, the Netherlands. · Department of Neurology, Amsterdam Neuroscience, Alzheimer Center, VU University, Amsterdam UMC, Amsterdam, the Netherlands; Department of Epidemiology and Biostatistics, Amsterdam Neuroscience, VU University of Amsterdam, Amsterdam, the Netherlands. ·Alzheimers Dement · Pubmed #31594684.

ABSTRACT: INTRODUCTION: The objective of this study was to assess the usefulness of the appropriate use criteria (AUC) for amyloid imaging in an unselected cohort. METHODS: We calculated sensitivity and specificity of appropriate use (increased confidence and management change), as defined by Amyloid Imaging Taskforce in the AUC, and other clinical utility outcomes. Furthermore, we compared differences in post-positron emission tomography diagnosis and management change between "AUC-consistent" and "AUC-inconsistent" patients. RESULTS: Almost half (250/507) of patients were AUC-consistent. In both AUC-consistent and AUC-inconsistent patients, post-positron emission tomography diagnosis (28%-21%) and management (32%-17%) change was substantial. The Amyloid Imaging Taskforce's definition of appropriate use occurred in 55/507 (13%) patients, detected by the AUC with a sensitivity of 93%, and a specificity of 56%. Diagnostic changes occurred independently of AUC status (sensitivity: 57%, specificity: 53%). DISCUSSION: The current AUC are not sufficiently able to discriminate between patients who will benefit from amyloid positron emission tomography and those who will not.

25 Article Cerebral amyloid burden is associated with white matter hyperintensity location in specific posterior white matter regions. 2019

Weaver, Nick A / Doeven, Thomas / Barkhof, Frederik / Biesbroek, J Matthijs / Groeneveld, Onno N / Kuijf, Hugo J / Prins, Niels D / Scheltens, Philip / Teunissen, Charlotte E / van der Flier, Wiesje M / Biessels, Geert Jan / Anonymous2711051. ·Department of Neurology and Neurosurgery, UMC Utrecht Brain Center, University Medical Center Utrecht, the Netherlands. Electronic address: n.a.weaver@umcutrecht.nl. · Department of Neurology and Neurosurgery, UMC Utrecht Brain Center, University Medical Center Utrecht, the Netherlands. · Institutes of Neurology and Healthcare Engineering, UCL, London, UK; Department of Radiology and Nuclear Medicine, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, the Netherlands. · Image Sciences Institute, University Medical Center Utrecht, Utrecht, the Netherlands. · Brain Research Center, Amsterdam, the Netherlands; Alzheimer Center Amsterdam, Department of Neurology, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, the Netherlands. · Alzheimer Center Amsterdam, Department of Neurology, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, the Netherlands. · Neurochemistry Lab and Biobank, Department of Clinical Chemistry, Amsterdam Neuroscience, VU University Medical Center Amsterdam, Amsterdam, the Netherlands. · Alzheimer Center Amsterdam, Department of Neurology, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, the Netherlands; Department of Epidemiology and Biostatistics, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, the Netherlands. ·Neurobiol Aging · Pubmed #31500909.

ABSTRACT: White matter hyperintensities (WMHs) are a common manifestation of cerebral small vessel disease. WMHs are also frequently observed in patients with familial and sporadic Alzheimer's disease, often with a particular posterior predominance. Whether amyloid and tau pathologies are linked to WMH occurrence is still debated. We examined whether cerebral amyloid and tau burden, reflected in cerebrospinal fluid amyloid-beta 1-42 (Aβ-42) and phosphorylated tau (p-tau), are related to WMH location in a cohort of 517 memory clinic patients. Two lesion mapping techniques were performed: voxel-based analyses and region of interest-based linear regression. Voxelwise associations were found between lower Aβ-42 and parieto-occipital periventricular WMHs. Regression analyses demonstrated that lower Aβ-42 correlated with larger WMH volumes in the splenium of the corpus callosum and posterior thalamic radiation, also after controlling for markers of vascular disease. P-tau was not consistently related to WMH occurrence. Our findings indicate that cerebral amyloid burden is associated with WMHs located in specific posterior white matter regions, possibly reflecting region-specific effects of amyloid pathology on the white matter.

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