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Pelak VS, Mahmood A, Abe-Ridgway K. Perspectives and a Systematic Scoping Review on Longitudinal Profiles of Posterior Cortical Atrophy Syndrome. Curr Neurol Neurosci Rep 2022; 22:803-812. [PMID: 36242715 DOI: 10.1007/s11910-022-01238-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 09/16/2022] [Indexed: 01/27/2023]
Abstract
PURPOSE OF REVIEW To provide perspectives on the importance of understanding longitudinal profiles of posterior cortical atrophy (PCA) and report results of a scoping review to identify data and knowledge gaps related to PCA survival and longitudinal clinical and biomarker outcomes. RECENT FINDINGS Thirteen longitudinal studies were identified; all but two had fewer than 30 participants with PCA. Relatively few longitudinal data exist, particularly for survival. In PCA, posterior cortical dysfunction and atrophy progress at faster rates compared to non-posterior regions, potentially up to a decade after symptom onset. Unlike typical AD, PCA phenotype-defined cognitive dysfunction and atrophy remain relatively more severe compared to other regions throughout the PCA course. Select cognitive tests hold promise as PCA outcome measures and for staging. Further longitudinal investigations are critically needed to enable PCA inclusion in treatment trials and to provide appropriate care to patients and enhance our understanding of the pathophysiology of dementing diseases.
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Affiliation(s)
- Victoria S Pelak
- Department of Neurology, University of Colorado School of Medicine, Aurora, CO, USA. .,Department of Ophthalmology, University of Colorado School of Medicine, Aurora, CO, USA.
| | - Asher Mahmood
- Department of Neurology, University of Colorado School of Medicine, Aurora, CO, USA
| | - Kathryn Abe-Ridgway
- Department of Neurology, University of Colorado School of Medicine, Aurora, CO, USA
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2
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Tuladhar A, Moore JA, Ismail Z, Forkert ND. Modeling Neurodegeneration in silico With Deep Learning. Front Neuroinform 2021; 15:748370. [PMID: 34867256 PMCID: PMC8640525 DOI: 10.3389/fninf.2021.748370] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/27/2021] [Accepted: 10/21/2021] [Indexed: 11/13/2022] Open
Abstract
Deep neural networks, inspired by information processing in the brain, can achieve human-like performance for various tasks. However, research efforts to use these networks as models of the brain have primarily focused on modeling healthy brain function so far. In this work, we propose a paradigm for modeling neural diseases in silico with deep learning and demonstrate its use in modeling posterior cortical atrophy (PCA), an atypical form of Alzheimer’s disease affecting the visual cortex. We simulated PCA in deep convolutional neural networks (DCNNs) trained for visual object recognition by randomly injuring connections between artificial neurons. Results showed that injured networks progressively lost their object recognition capability. Simulated PCA impacted learned representations hierarchically, as networks lost object-level representations before category-level representations. Incorporating this paradigm in computational neuroscience will be essential for developing in silico models of the brain and neurological diseases. The paradigm can be expanded to incorporate elements of neural plasticity and to other cognitive domains such as motor control, auditory cognition, language processing, and decision making.
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Affiliation(s)
- Anup Tuladhar
- Department of Radiology, University of Calgary, Calgary, AB, Canada.,Hotchkiss Brain Institute, University of Calgary, Calgary, AB, Canada
| | - Jasmine A Moore
- Department of Radiology, University of Calgary, Calgary, AB, Canada.,Hotchkiss Brain Institute, University of Calgary, Calgary, AB, Canada.,Biomedical Engineering Program, University of Calgary, Calgary, AB, Canada
| | - Zahinoor Ismail
- Hotchkiss Brain Institute, University of Calgary, Calgary, AB, Canada.,Department of Clinical Neurosciences, University of Calgary, Calgary, AB, Canada.,Department of Community Health Sciences, University of Calgary, Calgary, AB, Canada.,Department of Psychiatry, University of Calgary, Calgary, AB, Canada.,O'Brien Institute for Public Health, University of Calgary, Calgary, AB, Canada
| | - Nils D Forkert
- Department of Radiology, University of Calgary, Calgary, AB, Canada.,Hotchkiss Brain Institute, University of Calgary, Calgary, AB, Canada.,Department of Clinical Neurosciences, University of Calgary, Calgary, AB, Canada.,Alberta Children's Hospital Research Institute, University of Calgary, Calgary, AB, Canada
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3
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Bogolepova A, Vasenina E, Gomzyakova N, Gusev E, Dudchenko N, Emelin A, Zalutskaya N, Isaev R, Kotovskaya Y, Levin O, Litvinenko I, Lobzin V, Martynov M, Mkhitaryan E, Nikolay G, Palchikova E, Tkacheva O, Cherdak M, Chimagomedova A, Yakhno N. Clinical Guidelines for Cognitive Disorders in Elderly and Older Patients. Zh Nevrol Psikhiatr Im S S Korsakova 2021. [DOI: 10.17116/jnevro20211211036] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/17/2022]
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4
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Sintini I, Graff-Radford J, Senjem ML, Schwarz CG, Machulda MM, Martin PR, Jones DT, Boeve BF, Knopman DS, Kantarci K, Petersen RC, Jack CR, Lowe VJ, Josephs KA, Whitwell JL. Longitudinal neuroimaging biomarkers differ across Alzheimer's disease phenotypes. Brain 2020; 143:2281-2294. [PMID: 32572464 DOI: 10.1093/brain/awaa155] [Citation(s) in RCA: 45] [Impact Index Per Article: 11.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/26/2019] [Revised: 03/11/2020] [Accepted: 03/27/2020] [Indexed: 11/12/2022] Open
Abstract
Alzheimer's disease can present clinically with either the typical amnestic phenotype or with atypical phenotypes, such as logopenic progressive aphasia and posterior cortical atrophy. We have recently described longitudinal patterns of flortaucipir PET uptake and grey matter atrophy in the atypical phenotypes, demonstrating a longitudinal regional disconnect between flortaucipir accumulation and brain atrophy. However, it is unclear how these longitudinal patterns differ from typical Alzheimer's disease, to what degree flortaucipir and atrophy mirror clinical phenotype in Alzheimer's disease, and whether optimal longitudinal neuroimaging biomarkers would also differ across phenotypes. We aimed to address these unknowns using a cohort of 57 participants diagnosed with Alzheimer's disease (18 with typical amnestic Alzheimer's disease, 17 with posterior cortical atrophy and 22 with logopenic progressive aphasia) that had undergone baseline and 1-year follow-up MRI and flortaucipir PET. Typical Alzheimer's disease participants were selected to be over 65 years old at baseline scan, while no age criterion was used for atypical Alzheimer's disease participants. Region and voxel-level rates of tau accumulation and atrophy were assessed relative to 49 cognitively unimpaired individuals and among phenotypes. Principal component analysis was implemented to describe variability in baseline tau uptake and rates of accumulation and baseline grey matter volumes and rates of atrophy across phenotypes. The capability of the principal components to discriminate between phenotypes was assessed with logistic regression. The topography of longitudinal tau accumulation and atrophy differed across phenotypes, with key regions of tau accumulation in the frontal and temporal lobes for all phenotypes and key regions of atrophy in the occipitotemporal regions for posterior cortical atrophy, left temporal lobe for logopenic progressive aphasia and medial and lateral temporal lobe for typical Alzheimer's disease. Principal component analysis identified patterns of variation in baseline and longitudinal measures of tau uptake and volume that were significantly different across phenotypes. Baseline tau uptake mapped better onto clinical phenotype than longitudinal tau and MRI measures. Our study suggests that optimal longitudinal neuroimaging biomarkers for future clinical treatment trials in Alzheimer's disease are different for MRI and tau-PET and may differ across phenotypes, particularly for MRI. Baseline tau tracer retention showed the highest fidelity to clinical phenotype, supporting the important causal role of tau as a driver of clinical dysfunction in Alzheimer's disease.
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Affiliation(s)
- Irene Sintini
- Department of Radiology, Mayo Clinic, Rochester, MN, USA
| | | | - Matthew L Senjem
- Department of Radiology, Mayo Clinic, Rochester, MN, USA.,Department of Information Technology, Mayo Clinic, Rochester, MN, USA
| | | | - Mary M Machulda
- Department of Psychiatry and Psychology, Mayo Clinic, Rochester MN, USA
| | - Peter R Martin
- Department of Health Science Research, Mayo Clinic, Rochester MN, USA
| | - David T Jones
- Department of Neurology, Mayo Clinic, Rochester, MN, USA
| | | | | | - Kejal Kantarci
- Department of Radiology, Mayo Clinic, Rochester, MN, USA
| | | | | | - Val J Lowe
- Department of Radiology, Mayo Clinic, Rochester, MN, USA
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5
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Spatial patterns of correlation between cortical amyloid and cortical thickness in a tertiary clinical population with memory deficit. Sci Rep 2020; 10:20717. [PMID: 33244036 PMCID: PMC7693188 DOI: 10.1038/s41598-020-77503-2] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/09/2020] [Accepted: 11/11/2020] [Indexed: 12/28/2022] Open
Abstract
To estimate regional Alzheimer disease (AD) pathology burden clinically, analysis methods that enable tracking brain amyloid or tau positron emission tomography (PET) with magnetic resonance imaging (MRI) measures are needed. We therefore developed a robust MRI analysis method to identify brain regions that correlate linearly with regional amyloid burden in congruent PET images. This method was designed to reduce data variance and improve the sensitivity of the detection of cortical thickness-amyloid correlation by using whole brain modeling, nonlinear image coregistration, and partial volume correction. Using this method, a cross-sectional analysis of 75 tertiary memory clinic AD patients was performed to test our hypothesis that regional amyloid burden and cortical thickness are inversely correlated in medial temporal neocortical regions. Medial temporal cortical thicknesses were not correlated with their regional amyloid burden, whereas cortical thicknesses in the lateral temporal, lateral parietal, and frontal regions were inversely correlated with amyloid burden. This study demonstrates the robustness of our technique combining whole brain modeling, nonlinear image coregistration, and partial volume correction to track the differential correlation between regional amyloid burden and cortical thinning in specific brain regions. This method could be used with amyloid and tau PET to assess corresponding cortical thickness changes.
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Groot C, Yeo BTT, Vogel JW, Zhang X, Sun N, Mormino EC, Pijnenburg YAL, Miller BL, Rosen HJ, La Joie R, Barkhof F, Scheltens P, van der Flier WM, Rabinovici GD, Ossenkoppele R. Latent atrophy factors related to phenotypical variants of posterior cortical atrophy. Neurology 2020; 95:e1672-e1685. [PMID: 32675078 PMCID: PMC7713727 DOI: 10.1212/wnl.0000000000010362] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/25/2019] [Accepted: 04/06/2020] [Indexed: 01/30/2023] Open
Abstract
OBJECTIVE To determine whether atrophy relates to phenotypical variants of posterior cortical atrophy (PCA) recently proposed in clinical criteria (i.e., dorsal, ventral, dominant-parietal, and caudal) we assessed associations between latent atrophy factors and cognition. METHODS We employed a data-driven Bayesian modeling framework based on latent Dirichlet allocation to identify latent atrophy factors in a multicenter cohort of 119 individuals with PCA (age 64 ± 7 years, 38% male, Mini-Mental State Examination 21 ± 5, 71% β-amyloid positive, 29% β-amyloid status unknown). The model uses standardized gray matter density images as input (adjusted for age, sex, intracranial volume, MRI scanner field strength, and whole-brain gray matter volume) and provides voxelwise probabilistic maps for a predetermined number of atrophy factors, allowing every individual to express each factor to a degree without a priori classification. Individual factor expressions were correlated to 4 PCA-specific cognitive domains (object perception, space perception, nonvisual/parietal functions, and primary visual processing) using general linear models. RESULTS The model revealed 4 distinct yet partially overlapping atrophy factors: right-dorsal, right-ventral, left-ventral, and limbic. We found that object perception and primary visual processing were associated with atrophy that predominantly reflects the right-ventral factor. Furthermore, space perception was associated with atrophy that predominantly represents the right-dorsal and right-ventral factors. However, individual participant profiles revealed that the large majority expressed multiple atrophy factors and had mixed clinical profiles with impairments across multiple domains, rather than displaying a discrete clinical-radiologic phenotype. CONCLUSION Our results indicate that specific brain behavior networks are vulnerable in PCA, but most individuals display a constellation of affected brain regions and symptoms, indicating that classification into 4 mutually exclusive variants is unlikely to be clinically useful.
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Affiliation(s)
- Colin Groot
- From the Department of Neurology and Alzheimer Center (C.G., Y.A.L.P., P.S., W.M.v.d.F., R.O.), and Departments of Radiology and Nuclear Medicine (F.B.) and Epidemiology and Biostatistics (W.M.v.d.F.), Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, the Netherlands; Department of Electrical and Computer Engineering (B.T.T.Y., X.Z., N.S.), Clinical Imaging Research Centre, N1 Institute for Health and Memory Networks Program, National University of Singapore; Montreal Neurological Institute (J.W.V.), McGill University, Montreal, Canada; Computer Science and Artificial Intelligence Laboratory (X.Z.), Massachusetts Institute of Technology, Cambridge; Department of Neurology and Neurological Sciences (E.C.M.), Stanford University, CA; Departments of Neurology, Radiology and Biomedical Imaging (B.L.M., H.J.R., R.L.J., G.D.R.), University of California, San Francisco; Institutes of Neurology & Healthcare Engineering (F.B.), University College London, UK; and Clinical Memory Research Unit (R.O.), Lund University, Sweden.
| | - B T Thomas Yeo
- From the Department of Neurology and Alzheimer Center (C.G., Y.A.L.P., P.S., W.M.v.d.F., R.O.), and Departments of Radiology and Nuclear Medicine (F.B.) and Epidemiology and Biostatistics (W.M.v.d.F.), Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, the Netherlands; Department of Electrical and Computer Engineering (B.T.T.Y., X.Z., N.S.), Clinical Imaging Research Centre, N1 Institute for Health and Memory Networks Program, National University of Singapore; Montreal Neurological Institute (J.W.V.), McGill University, Montreal, Canada; Computer Science and Artificial Intelligence Laboratory (X.Z.), Massachusetts Institute of Technology, Cambridge; Department of Neurology and Neurological Sciences (E.C.M.), Stanford University, CA; Departments of Neurology, Radiology and Biomedical Imaging (B.L.M., H.J.R., R.L.J., G.D.R.), University of California, San Francisco; Institutes of Neurology & Healthcare Engineering (F.B.), University College London, UK; and Clinical Memory Research Unit (R.O.), Lund University, Sweden
| | - Jacob W Vogel
- From the Department of Neurology and Alzheimer Center (C.G., Y.A.L.P., P.S., W.M.v.d.F., R.O.), and Departments of Radiology and Nuclear Medicine (F.B.) and Epidemiology and Biostatistics (W.M.v.d.F.), Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, the Netherlands; Department of Electrical and Computer Engineering (B.T.T.Y., X.Z., N.S.), Clinical Imaging Research Centre, N1 Institute for Health and Memory Networks Program, National University of Singapore; Montreal Neurological Institute (J.W.V.), McGill University, Montreal, Canada; Computer Science and Artificial Intelligence Laboratory (X.Z.), Massachusetts Institute of Technology, Cambridge; Department of Neurology and Neurological Sciences (E.C.M.), Stanford University, CA; Departments of Neurology, Radiology and Biomedical Imaging (B.L.M., H.J.R., R.L.J., G.D.R.), University of California, San Francisco; Institutes of Neurology & Healthcare Engineering (F.B.), University College London, UK; and Clinical Memory Research Unit (R.O.), Lund University, Sweden
| | - Xiuming Zhang
- From the Department of Neurology and Alzheimer Center (C.G., Y.A.L.P., P.S., W.M.v.d.F., R.O.), and Departments of Radiology and Nuclear Medicine (F.B.) and Epidemiology and Biostatistics (W.M.v.d.F.), Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, the Netherlands; Department of Electrical and Computer Engineering (B.T.T.Y., X.Z., N.S.), Clinical Imaging Research Centre, N1 Institute for Health and Memory Networks Program, National University of Singapore; Montreal Neurological Institute (J.W.V.), McGill University, Montreal, Canada; Computer Science and Artificial Intelligence Laboratory (X.Z.), Massachusetts Institute of Technology, Cambridge; Department of Neurology and Neurological Sciences (E.C.M.), Stanford University, CA; Departments of Neurology, Radiology and Biomedical Imaging (B.L.M., H.J.R., R.L.J., G.D.R.), University of California, San Francisco; Institutes of Neurology & Healthcare Engineering (F.B.), University College London, UK; and Clinical Memory Research Unit (R.O.), Lund University, Sweden
| | - Nanbo Sun
- From the Department of Neurology and Alzheimer Center (C.G., Y.A.L.P., P.S., W.M.v.d.F., R.O.), and Departments of Radiology and Nuclear Medicine (F.B.) and Epidemiology and Biostatistics (W.M.v.d.F.), Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, the Netherlands; Department of Electrical and Computer Engineering (B.T.T.Y., X.Z., N.S.), Clinical Imaging Research Centre, N1 Institute for Health and Memory Networks Program, National University of Singapore; Montreal Neurological Institute (J.W.V.), McGill University, Montreal, Canada; Computer Science and Artificial Intelligence Laboratory (X.Z.), Massachusetts Institute of Technology, Cambridge; Department of Neurology and Neurological Sciences (E.C.M.), Stanford University, CA; Departments of Neurology, Radiology and Biomedical Imaging (B.L.M., H.J.R., R.L.J., G.D.R.), University of California, San Francisco; Institutes of Neurology & Healthcare Engineering (F.B.), University College London, UK; and Clinical Memory Research Unit (R.O.), Lund University, Sweden
| | - Elizabeth C Mormino
- From the Department of Neurology and Alzheimer Center (C.G., Y.A.L.P., P.S., W.M.v.d.F., R.O.), and Departments of Radiology and Nuclear Medicine (F.B.) and Epidemiology and Biostatistics (W.M.v.d.F.), Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, the Netherlands; Department of Electrical and Computer Engineering (B.T.T.Y., X.Z., N.S.), Clinical Imaging Research Centre, N1 Institute for Health and Memory Networks Program, National University of Singapore; Montreal Neurological Institute (J.W.V.), McGill University, Montreal, Canada; Computer Science and Artificial Intelligence Laboratory (X.Z.), Massachusetts Institute of Technology, Cambridge; Department of Neurology and Neurological Sciences (E.C.M.), Stanford University, CA; Departments of Neurology, Radiology and Biomedical Imaging (B.L.M., H.J.R., R.L.J., G.D.R.), University of California, San Francisco; Institutes of Neurology & Healthcare Engineering (F.B.), University College London, UK; and Clinical Memory Research Unit (R.O.), Lund University, Sweden
| | - Yolande A L Pijnenburg
- From the Department of Neurology and Alzheimer Center (C.G., Y.A.L.P., P.S., W.M.v.d.F., R.O.), and Departments of Radiology and Nuclear Medicine (F.B.) and Epidemiology and Biostatistics (W.M.v.d.F.), Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, the Netherlands; Department of Electrical and Computer Engineering (B.T.T.Y., X.Z., N.S.), Clinical Imaging Research Centre, N1 Institute for Health and Memory Networks Program, National University of Singapore; Montreal Neurological Institute (J.W.V.), McGill University, Montreal, Canada; Computer Science and Artificial Intelligence Laboratory (X.Z.), Massachusetts Institute of Technology, Cambridge; Department of Neurology and Neurological Sciences (E.C.M.), Stanford University, CA; Departments of Neurology, Radiology and Biomedical Imaging (B.L.M., H.J.R., R.L.J., G.D.R.), University of California, San Francisco; Institutes of Neurology & Healthcare Engineering (F.B.), University College London, UK; and Clinical Memory Research Unit (R.O.), Lund University, Sweden
| | - Bruce L Miller
- From the Department of Neurology and Alzheimer Center (C.G., Y.A.L.P., P.S., W.M.v.d.F., R.O.), and Departments of Radiology and Nuclear Medicine (F.B.) and Epidemiology and Biostatistics (W.M.v.d.F.), Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, the Netherlands; Department of Electrical and Computer Engineering (B.T.T.Y., X.Z., N.S.), Clinical Imaging Research Centre, N1 Institute for Health and Memory Networks Program, National University of Singapore; Montreal Neurological Institute (J.W.V.), McGill University, Montreal, Canada; Computer Science and Artificial Intelligence Laboratory (X.Z.), Massachusetts Institute of Technology, Cambridge; Department of Neurology and Neurological Sciences (E.C.M.), Stanford University, CA; Departments of Neurology, Radiology and Biomedical Imaging (B.L.M., H.J.R., R.L.J., G.D.R.), University of California, San Francisco; Institutes of Neurology & Healthcare Engineering (F.B.), University College London, UK; and Clinical Memory Research Unit (R.O.), Lund University, Sweden
| | - Howard J Rosen
- From the Department of Neurology and Alzheimer Center (C.G., Y.A.L.P., P.S., W.M.v.d.F., R.O.), and Departments of Radiology and Nuclear Medicine (F.B.) and Epidemiology and Biostatistics (W.M.v.d.F.), Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, the Netherlands; Department of Electrical and Computer Engineering (B.T.T.Y., X.Z., N.S.), Clinical Imaging Research Centre, N1 Institute for Health and Memory Networks Program, National University of Singapore; Montreal Neurological Institute (J.W.V.), McGill University, Montreal, Canada; Computer Science and Artificial Intelligence Laboratory (X.Z.), Massachusetts Institute of Technology, Cambridge; Department of Neurology and Neurological Sciences (E.C.M.), Stanford University, CA; Departments of Neurology, Radiology and Biomedical Imaging (B.L.M., H.J.R., R.L.J., G.D.R.), University of California, San Francisco; Institutes of Neurology & Healthcare Engineering (F.B.), University College London, UK; and Clinical Memory Research Unit (R.O.), Lund University, Sweden
| | - Renaud La Joie
- From the Department of Neurology and Alzheimer Center (C.G., Y.A.L.P., P.S., W.M.v.d.F., R.O.), and Departments of Radiology and Nuclear Medicine (F.B.) and Epidemiology and Biostatistics (W.M.v.d.F.), Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, the Netherlands; Department of Electrical and Computer Engineering (B.T.T.Y., X.Z., N.S.), Clinical Imaging Research Centre, N1 Institute for Health and Memory Networks Program, National University of Singapore; Montreal Neurological Institute (J.W.V.), McGill University, Montreal, Canada; Computer Science and Artificial Intelligence Laboratory (X.Z.), Massachusetts Institute of Technology, Cambridge; Department of Neurology and Neurological Sciences (E.C.M.), Stanford University, CA; Departments of Neurology, Radiology and Biomedical Imaging (B.L.M., H.J.R., R.L.J., G.D.R.), University of California, San Francisco; Institutes of Neurology & Healthcare Engineering (F.B.), University College London, UK; and Clinical Memory Research Unit (R.O.), Lund University, Sweden
| | - Frederik Barkhof
- From the Department of Neurology and Alzheimer Center (C.G., Y.A.L.P., P.S., W.M.v.d.F., R.O.), and Departments of Radiology and Nuclear Medicine (F.B.) and Epidemiology and Biostatistics (W.M.v.d.F.), Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, the Netherlands; Department of Electrical and Computer Engineering (B.T.T.Y., X.Z., N.S.), Clinical Imaging Research Centre, N1 Institute for Health and Memory Networks Program, National University of Singapore; Montreal Neurological Institute (J.W.V.), McGill University, Montreal, Canada; Computer Science and Artificial Intelligence Laboratory (X.Z.), Massachusetts Institute of Technology, Cambridge; Department of Neurology and Neurological Sciences (E.C.M.), Stanford University, CA; Departments of Neurology, Radiology and Biomedical Imaging (B.L.M., H.J.R., R.L.J., G.D.R.), University of California, San Francisco; Institutes of Neurology & Healthcare Engineering (F.B.), University College London, UK; and Clinical Memory Research Unit (R.O.), Lund University, Sweden
| | - Philip Scheltens
- From the Department of Neurology and Alzheimer Center (C.G., Y.A.L.P., P.S., W.M.v.d.F., R.O.), and Departments of Radiology and Nuclear Medicine (F.B.) and Epidemiology and Biostatistics (W.M.v.d.F.), Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, the Netherlands; Department of Electrical and Computer Engineering (B.T.T.Y., X.Z., N.S.), Clinical Imaging Research Centre, N1 Institute for Health and Memory Networks Program, National University of Singapore; Montreal Neurological Institute (J.W.V.), McGill University, Montreal, Canada; Computer Science and Artificial Intelligence Laboratory (X.Z.), Massachusetts Institute of Technology, Cambridge; Department of Neurology and Neurological Sciences (E.C.M.), Stanford University, CA; Departments of Neurology, Radiology and Biomedical Imaging (B.L.M., H.J.R., R.L.J., G.D.R.), University of California, San Francisco; Institutes of Neurology & Healthcare Engineering (F.B.), University College London, UK; and Clinical Memory Research Unit (R.O.), Lund University, Sweden
| | - Wiesje M van der Flier
- From the Department of Neurology and Alzheimer Center (C.G., Y.A.L.P., P.S., W.M.v.d.F., R.O.), and Departments of Radiology and Nuclear Medicine (F.B.) and Epidemiology and Biostatistics (W.M.v.d.F.), Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, the Netherlands; Department of Electrical and Computer Engineering (B.T.T.Y., X.Z., N.S.), Clinical Imaging Research Centre, N1 Institute for Health and Memory Networks Program, National University of Singapore; Montreal Neurological Institute (J.W.V.), McGill University, Montreal, Canada; Computer Science and Artificial Intelligence Laboratory (X.Z.), Massachusetts Institute of Technology, Cambridge; Department of Neurology and Neurological Sciences (E.C.M.), Stanford University, CA; Departments of Neurology, Radiology and Biomedical Imaging (B.L.M., H.J.R., R.L.J., G.D.R.), University of California, San Francisco; Institutes of Neurology & Healthcare Engineering (F.B.), University College London, UK; and Clinical Memory Research Unit (R.O.), Lund University, Sweden
| | - Gil D Rabinovici
- From the Department of Neurology and Alzheimer Center (C.G., Y.A.L.P., P.S., W.M.v.d.F., R.O.), and Departments of Radiology and Nuclear Medicine (F.B.) and Epidemiology and Biostatistics (W.M.v.d.F.), Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, the Netherlands; Department of Electrical and Computer Engineering (B.T.T.Y., X.Z., N.S.), Clinical Imaging Research Centre, N1 Institute for Health and Memory Networks Program, National University of Singapore; Montreal Neurological Institute (J.W.V.), McGill University, Montreal, Canada; Computer Science and Artificial Intelligence Laboratory (X.Z.), Massachusetts Institute of Technology, Cambridge; Department of Neurology and Neurological Sciences (E.C.M.), Stanford University, CA; Departments of Neurology, Radiology and Biomedical Imaging (B.L.M., H.J.R., R.L.J., G.D.R.), University of California, San Francisco; Institutes of Neurology & Healthcare Engineering (F.B.), University College London, UK; and Clinical Memory Research Unit (R.O.), Lund University, Sweden
| | - Rik Ossenkoppele
- From the Department of Neurology and Alzheimer Center (C.G., Y.A.L.P., P.S., W.M.v.d.F., R.O.), and Departments of Radiology and Nuclear Medicine (F.B.) and Epidemiology and Biostatistics (W.M.v.d.F.), Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, the Netherlands; Department of Electrical and Computer Engineering (B.T.T.Y., X.Z., N.S.), Clinical Imaging Research Centre, N1 Institute for Health and Memory Networks Program, National University of Singapore; Montreal Neurological Institute (J.W.V.), McGill University, Montreal, Canada; Computer Science and Artificial Intelligence Laboratory (X.Z.), Massachusetts Institute of Technology, Cambridge; Department of Neurology and Neurological Sciences (E.C.M.), Stanford University, CA; Departments of Neurology, Radiology and Biomedical Imaging (B.L.M., H.J.R., R.L.J., G.D.R.), University of California, San Francisco; Institutes of Neurology & Healthcare Engineering (F.B.), University College London, UK; and Clinical Memory Research Unit (R.O.), Lund University, Sweden
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7
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Firth NC, Primativo S, Brotherhood E, Young AL, Yong KXX, Crutch SJ, Alexander DC, Oxtoby NP. Sequences of cognitive decline in typical Alzheimer's disease and posterior cortical atrophy estimated using a novel event-based model of disease progression. Alzheimers Dement 2020; 16:965-973. [PMID: 32489019 PMCID: PMC8432168 DOI: 10.1002/alz.12083] [Citation(s) in RCA: 20] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/07/2019] [Revised: 01/09/2020] [Accepted: 01/15/2020] [Indexed: 12/15/2022]
Abstract
Introduction This work aims to characterize the sequence in which cognitive deficits appear in two dementia syndromes. Methods Event‐based modeling estimated fine‐grained sequences of cognitive decline in clinically‐diagnosed posterior cortical atrophy (PCA) (n=94) and typical Alzheimer's disease (tAD) (n=61) at the UCL Dementia Research Centre. Our neuropsychological battery assessed memory, vision, arithmetic, and general cognition. We adapted the event‐based model to handle highly non‐Gaussian data such as cognitive test scores where ceiling/floor effects are common. Results Experiments revealed differences and similarities in the fine‐grained ordering of cognitive decline in PCA (vision first) and tAD (memory first). Simulation experiments reveal that our new model equals or exceeds performance of the classic event‐based model, especially for highly non‐Gaussian data. Discussion Our model recovered realistic, phenotypical progression signatures that may be applied in dementia clinical trials for enrichment, and as a data‐driven composite cognitive end‐point.
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Affiliation(s)
- Nicholas C Firth
- Centre for Medical Image Computing, Department of Computer Science, UCL, London, WC1E 6BT, UK.,Dementia Research Centre, UCL Queen Square Institute of Neurology, UCL, London, WC1N 3BG, UK
| | | | - Emilie Brotherhood
- Dementia Research Centre, UCL Queen Square Institute of Neurology, UCL, London, WC1N 3BG, UK
| | - Alexandra L Young
- Centre for Medical Image Computing, Department of Computer Science, UCL, London, WC1E 6BT, UK.,Department of Neuroimaging, Institute of Psychiatry, Psychology and Neuroscience, King's College, London, UK
| | - Keir X X Yong
- Dementia Research Centre, UCL Queen Square Institute of Neurology, UCL, London, WC1N 3BG, UK
| | - Sebastian J Crutch
- Dementia Research Centre, UCL Queen Square Institute of Neurology, UCL, London, WC1N 3BG, UK
| | - Daniel C Alexander
- Centre for Medical Image Computing, Department of Computer Science, UCL, London, WC1E 6BT, UK.,Clinical Imaging Research Centre, National University of Singapore, Singapore
| | - Neil P Oxtoby
- Centre for Medical Image Computing, Department of Computer Science, UCL, London, WC1E 6BT, UK
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8
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Phillips JS, Da Re F, Irwin DJ, McMillan CT, Vaishnavi SN, Xie SX, Lee EB, Cook PA, Gee JC, Shaw LM, Trojanowski JQ, Wolk DA, Grossman M. Longitudinal progression of grey matter atrophy in non-amnestic Alzheimer's disease. Brain 2020; 142:1701-1722. [PMID: 31135048 PMCID: PMC6585881 DOI: 10.1093/brain/awz091] [Citation(s) in RCA: 31] [Impact Index Per Article: 7.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/09/2018] [Revised: 01/21/2019] [Accepted: 02/11/2019] [Indexed: 12/12/2022] Open
Abstract
Recent models of Alzheimer's disease progression propose that disease may be transmitted between brain areas either via local diffusion or long-distance transport via white matter fibre pathways. However, it is unclear whether such models are applicable in non-amnestic Alzheimer's disease, which is associated with domain-specific cognitive deficits and relatively spared episodic memory. To date, the anatomical progression of disease in non-amnestic patients remains understudied. We used longitudinal imaging to differentiate earlier atrophy and later disease spread in three non-amnestic variants, including logopenic-variant primary progressive aphasia (n = 25), posterior cortical atrophy (n = 20), and frontal-variant Alzheimer's disease (n = 12), as well as 17 amnestic Alzheimer's disease patients. Patients were compared to 37 matched controls. All patients had autopsy (n = 7) or CSF (n = 67) evidence of Alzheimer's disease pathology. We first assessed atrophy in suspected sites of disease origin, adjusting for age, sex, and severity of cognitive impairment; we then performed exploratory whole-brain analysis to investigate longitudinal disease spread both within and outside these regions. Additionally, we asked whether each phenotype exhibited more rapid change in its associated disease foci than other phenotypes. Finally, we investigated whether atrophy was related to structural brain connectivity. Each non-amnestic phenotype displayed unique patterns of initial atrophy and subsequent neocortical change that correlated with cognitive decline. Longitudinal atrophy included areas both proximal to and distant from sites of initial atrophy, suggesting heterogeneous mechanisms of disease spread. Moreover, regional rates of neocortical change differed by phenotype. Logopenic-variant patients exhibited greater initial atrophy and more rapid longitudinal change in left lateral temporal areas than other groups. Frontal-variant patients had pronounced atrophy in left insula and middle frontal gyrus, combined with more rapid atrophy of left insula than other non-amnestic patients. In the medial temporal lobes, non-amnestic patients had less atrophy at their initial scan than amnestic patients, but longitudinal rate of change did not differ between patient groups. Medial temporal sparing in non-amnestic Alzheimer's disease may thus be due in part to later onset of medial temporal degeneration than in amnestic patients rather than different rates of atrophy over time. Finally, the magnitude of longitudinal atrophy was predicted by structural connectivity, measured in terms of node degree; this result provides indirect support for the role of long-distance fibre pathways in the spread of neurodegenerative disease. 10.1093/brain/awz091_video1 awz091media1 6041544065001.
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Affiliation(s)
- Jeffrey S Phillips
- Penn Frontotemporal Degeneration Center, University of Pennsylvania, Philadelphia, PA, USA.,Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Fulvio Da Re
- Penn Frontotemporal Degeneration Center, University of Pennsylvania, Philadelphia, PA, USA.,PhD Program in Neuroscience, University of Milano-Bicocca, Milan, Italy.,School of Medicine and Surgery, Milan Center for Neuroscience (NeuroMI), University of Milano-Bicocca, Milan, Italy
| | - David J Irwin
- Penn Frontotemporal Degeneration Center, University of Pennsylvania, Philadelphia, PA, USA.,Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Corey T McMillan
- Penn Frontotemporal Degeneration Center, University of Pennsylvania, Philadelphia, PA, USA.,Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Sanjeev N Vaishnavi
- Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA.,Penn Memory Center, University of Pennsylvania, Philadelphia, PA, USA
| | - Sharon X Xie
- Department of Biostatistics, Epidemiology, and Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Edward B Lee
- Center for Neurodegenerative Disease Research, University of Pennsylvania, Philadelphia, PA, USA
| | - Philip A Cook
- Penn Image Computing and Science Laboratory, Department of Radiology, University of Pennsylvania, Philadelphia, PA, USA
| | - James C Gee
- Penn Image Computing and Science Laboratory, Department of Radiology, University of Pennsylvania, Philadelphia, PA, USA
| | - Leslie M Shaw
- Center for Neurodegenerative Disease Research, University of Pennsylvania, Philadelphia, PA, USA
| | - John Q Trojanowski
- Center for Neurodegenerative Disease Research, University of Pennsylvania, Philadelphia, PA, USA
| | - David A Wolk
- Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA.,Penn Memory Center, University of Pennsylvania, Philadelphia, PA, USA
| | - Murray Grossman
- Penn Frontotemporal Degeneration Center, University of Pennsylvania, Philadelphia, PA, USA.,Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
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9
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Wong B, Lucente DE, MacLean J, Padmanabhan J, Quimby M, Brandt KD, Putcha D, Sherman J, Frosch MP, McGinnis S, Dickerson BC. Diagnostic evaluation and monitoring of patients with posterior cortical atrophy. Neurodegener Dis Manag 2019; 9:217-239. [PMID: 31392920 PMCID: PMC6949516 DOI: 10.2217/nmt-2018-0052] [Citation(s) in RCA: 16] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/23/2018] [Accepted: 05/03/2019] [Indexed: 12/21/2022] Open
Abstract
Posterior cortical atrophy (PCA) is a progressive neurocognitive syndrome, most commonly associated with the loss of complex visuospatial functions. Diagnosis is challenging, and international consensus classification and nomenclature for PCA subtypes have only recently been reached. Presently, no established treatments exist. Efforts to develop treatments are hampered by the lack of standardized methods to monitor illness progression. Although measures developed from work with Alzheimer's disease and other dementias provide a foundation for diagnosing and monitoring progression, PCA presents unique challenges for clinicians counseling patients and families on clinical status and prognosis, and experts designing clinical trials of interventions. Here, we review issues facing PCA clinical research and care, summarize our approach to diagnosis and monitoring of disease progression, and outline ideas for developing tools for these purposes.
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Affiliation(s)
- Bonnie Wong
- Posterior Cortical Atrophy Program, Frontotemporal Disorders Unit, Massachusetts General Hospital, Boston, MA 02114, USA
- Department of Psychiatry, Massachusetts General Hospital, Boston, MA 02114, USA
| | - Diane E Lucente
- Posterior Cortical Atrophy Program, Frontotemporal Disorders Unit, Massachusetts General Hospital, Boston, MA 02114, USA
- Centerfor Genomic Medicine, Massachusetts General Hospital & Harvard Medical School, Boston, MA 02114, USA
| | - Julie MacLean
- Department of Physical & Occupational Therapy, Massachusetts General Hospital, Boston, MA 02114, USA
| | - Jaya Padmanabhan
- Posterior Cortical Atrophy Program, Frontotemporal Disorders Unit, Massachusetts General Hospital, Boston, MA 02114, USA
- Department of Neurology, Division of Cognitive Neurology, Beth Israel Deaconess Medical Center, Boston, MA 02115, USA
| | - Megan Quimby
- Posterior Cortical Atrophy Program, Frontotemporal Disorders Unit, Massachusetts General Hospital, Boston, MA 02114, USA
- Department of Neurology, Massachusetts General Hospital, Boston,MA 02114, USA
- Department of Speech & Language Pathology, Massachusetts General Hospital, Boston, MA 02114, USA
| | - Katherine D Brandt
- Posterior Cortical Atrophy Program, Frontotemporal Disorders Unit, Massachusetts General Hospital, Boston, MA 02114, USA
- Department of Neurology, Massachusetts General Hospital, Boston,MA 02114, USA
| | - Deepti Putcha
- Posterior Cortical Atrophy Program, Frontotemporal Disorders Unit, Massachusetts General Hospital, Boston, MA 02114, USA
- Department of Psychiatry, Massachusetts General Hospital, Boston, MA 02114, USA
| | - Janet Sherman
- Posterior Cortical Atrophy Program, Frontotemporal Disorders Unit, Massachusetts General Hospital, Boston, MA 02114, USA
- Department of Psychiatry, Massachusetts General Hospital, Boston, MA 02114, USA
| | - Matthew P Frosch
- Department of Pathology, Division of Neuropathology, Massachusetts General Hospital, Boston, MA 02114, USA
- Massachusetts Alzheimer’s Disease Research Center, Boston, MA 02129, USA
| | - Scott McGinnis
- Posterior Cortical Atrophy Program, Frontotemporal Disorders Unit, Massachusetts General Hospital, Boston, MA 02114, USA
- Department of Neurology, Massachusetts General Hospital, Boston,MA 02114, USA
- Department of Neurology, Division of Cognitive & Behavioral Neurology, Brigham & Women's Hospital, Boston, MA 02115, USA
| | - Bradford C Dickerson
- Posterior Cortical Atrophy Program, Frontotemporal Disorders Unit, Massachusetts General Hospital, Boston, MA 02114, USA
- Department of Neurology, Massachusetts General Hospital, Boston,MA 02114, USA
- Massachusetts Alzheimer’s Disease Research Center, Boston, MA 02129, USA
- Athinoula A Martinos Center for Biomedical Imaging, Charlestown, MA 02129, USA
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10
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Kujovic M, Malikovic A, Jochum S, Margittai Z, Lange-Asschenfeldt C, Supprian T. Longitudinal progression of posterior cortical atrophy over 11 years: Relationship between lesion topology and clinical deficits. J Clin Exp Neuropsychol 2019; 41:875-880. [PMID: 31322045 DOI: 10.1080/13803395.2019.1638345] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/26/2022]
Abstract
Posterior cortical atrophy (PCA) is a rare form of dementia primarily characterized by slowly progressing deterioration of visual processing corresponding to atrophy in the posterior parietal and occipital cortices with less prominent memory loss than are usually seen in other forms of dementia such as Alzheimer's Disease (AD). In the present case report, we describe longitudinal data over a period of 11 years regarding clinical and neuropsychological impairments and their relation to the location and extent of cortical changes related to higher order visual processing in a patient with posterior cortical atrophy. In our patient, visual processing deficits concerning space, motion and object perception emerged at the age of 50 and continued to worsen. By the age of 58, while the perception of contrast, color and figure-ground separation appeared undisturbed the patient exhibited pronounced dorsal- and ventral-related visual deficits, which continued to worsen with age. The patient's MRI scans over the course of the disease revealed increasing circumscribed and bilateral atrophy of the parietal and occipital cortices, with a right-sided predominance. The specific localization of cortical atrophy, the slow progression characterized by visual processing deficits and relatively preserved memory were the main criteria for the diagnosis of posterior cortical atrophy. The case report also highlights the importance of an early extensive neurological and neuropsychological evaluation of visual deficits that occur without the presence of ophthalmological disease.
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Affiliation(s)
- Milenko Kujovic
- a Department of Psychiatry and Psychotherapy, Medical Faculty, Heinrich Heine University , Düsseldorf , Germany
| | - Aleksandar Malikovic
- b Institute of Anatomy, Faculty of Medicine, University of Belgrade , Belgrade , Serbia
| | - Sarah Jochum
- a Department of Psychiatry and Psychotherapy, Medical Faculty, Heinrich Heine University , Düsseldorf , Germany
| | - Zsofia Margittai
- a Department of Psychiatry and Psychotherapy, Medical Faculty, Heinrich Heine University , Düsseldorf , Germany
| | | | - Tillmann Supprian
- a Department of Psychiatry and Psychotherapy, Medical Faculty, Heinrich Heine University , Düsseldorf , Germany
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11
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Firth NC, Primativo S, Marinescu RV, Shakespeare TJ, Suarez-Gonzalez A, Lehmann M, Carton A, Ocal D, Pavisic I, Paterson RW, Slattery CF, Foulkes AJM, Ridha BH, Gil-Néciga E, Oxtoby NP, Young AL, Modat M, Cardoso MJ, Ourselin S, Ryan NS, Miller BL, Rabinovici GD, Warrington EK, Rossor MN, Fox NC, Warren JD, Alexander DC, Schott JM, Yong KXX, Crutch SJ. Longitudinal neuroanatomical and cognitive progression of posterior cortical atrophy. Brain 2019; 142:2082-2095. [PMID: 31219516 PMCID: PMC6598737 DOI: 10.1093/brain/awz136] [Citation(s) in RCA: 49] [Impact Index Per Article: 9.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/19/2018] [Revised: 02/28/2019] [Accepted: 03/24/2019] [Indexed: 01/27/2023] Open
Abstract
Posterior cortical atrophy is a clinico-radiological syndrome characterized by progressive decline in visual processing and atrophy of posterior brain regions. With the majority of cases attributable to Alzheimer's disease and recent evidence for genetic risk factors specifically related to posterior cortical atrophy, the syndrome can provide important insights into selective vulnerability and phenotypic diversity. The present study describes the first major longitudinal investigation of posterior cortical atrophy disease progression. Three hundred and sixty-one individuals (117 posterior cortical atrophy, 106 typical Alzheimer's disease, 138 controls) fulfilling consensus criteria for posterior cortical atrophy-pure and typical Alzheimer's disease were recruited from three centres in the UK, Spain and USA. Participants underwent up to six annual assessments involving MRI scans and neuropsychological testing. We constructed longitudinal trajectories of regional brain volumes within posterior cortical atrophy and typical Alzheimer's disease using differential equation models. We compared and contrasted the order in which regional brain volumes become abnormal within posterior cortical atrophy and typical Alzheimer's disease using event-based models. We also examined trajectories of cognitive decline and the order in which different cognitive tests show abnormality using the same models. Temporally aligned trajectories for eight regions of interest revealed distinct (P < 0.002) patterns of progression in posterior cortical atrophy and typical Alzheimer's disease. Patients with posterior cortical atrophy showed early occipital and parietal atrophy, with subsequent higher rates of temporal atrophy and ventricular expansion leading to tissue loss of comparable extent later. Hippocampal, entorhinal and frontal regions underwent a lower rate of change and never approached the extent of posterior cortical involvement. Patients with typical Alzheimer's disease showed early hippocampal atrophy, with subsequent higher rates of temporal atrophy and ventricular expansion. Cognitive models showed tests sensitive to visuospatial dysfunction declined earlier in posterior cortical atrophy than typical Alzheimer's disease whilst tests sensitive to working memory impairment declined earlier in typical Alzheimer's disease than posterior cortical atrophy. These findings indicate that posterior cortical atrophy and typical Alzheimer's disease have distinct sites of onset and different profiles of spatial and temporal progression. The ordering of disease events both motivates investigation of biological factors underpinning phenotypic heterogeneity, and informs the selection of measures for clinical trials in posterior cortical atrophy.
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Affiliation(s)
- Nicholas C Firth
- Dementia Research Centre, Institute of Neurology, University College London, 8–11 Queen Square, London, UK
- Centre for Medical Image Computing, Department of Computer Science, University College London, Gower Street, London, UK
| | - Silvia Primativo
- Dementia Research Centre, Institute of Neurology, University College London, 8–11 Queen Square, London, UK
- Department of Human Science, LUMSA University, Via della Traspontina, 21, Rome, Italy
| | - Razvan-Valentin Marinescu
- Centre for Medical Image Computing, Department of Computer Science, University College London, Gower Street, London, UK
| | - Timothy J Shakespeare
- Dementia Research Centre, Institute of Neurology, University College London, 8–11 Queen Square, London, UK
| | - Aida Suarez-Gonzalez
- Dementia Research Centre, Institute of Neurology, University College London, 8–11 Queen Square, London, UK
- Department of Neurology, University Hospital Virgen del Rocio, Seville, Spain
| | - Manja Lehmann
- Dementia Research Centre, Institute of Neurology, University College London, 8–11 Queen Square, London, UK
- Memory and Aging Center, University of California San Francisco, San Francisco, California, USA
| | - Amelia Carton
- Dementia Research Centre, Institute of Neurology, University College London, 8–11 Queen Square, London, UK
| | - Dilek Ocal
- Dementia Research Centre, Institute of Neurology, University College London, 8–11 Queen Square, London, UK
| | - Ivanna Pavisic
- Dementia Research Centre, Institute of Neurology, University College London, 8–11 Queen Square, London, UK
| | - Ross W Paterson
- Dementia Research Centre, Institute of Neurology, University College London, 8–11 Queen Square, London, UK
| | - Catherine F Slattery
- Dementia Research Centre, Institute of Neurology, University College London, 8–11 Queen Square, London, UK
| | - Alexander J M Foulkes
- Dementia Research Centre, Institute of Neurology, University College London, 8–11 Queen Square, London, UK
| | - Basil H Ridha
- Dementia Research Centre, Institute of Neurology, University College London, 8–11 Queen Square, London, UK
| | - Eulogio Gil-Néciga
- Department of Neurology, University Hospital Virgen del Rocio, Seville, Spain
| | - Neil P Oxtoby
- Centre for Medical Image Computing, Department of Computer Science, University College London, Gower Street, London, UK
| | - Alexandra L Young
- Centre for Medical Image Computing, Department of Computer Science, University College London, Gower Street, London, UK
| | - Marc Modat
- School of Biomedical Engineering and Imaging Sciences, King's College London, UK
| | - M Jorge Cardoso
- School of Biomedical Engineering and Imaging Sciences, King's College London, UK
| | - Sebastien Ourselin
- School of Biomedical Engineering and Imaging Sciences, King's College London, UK
| | - Natalie S Ryan
- Dementia Research Centre, Institute of Neurology, University College London, 8–11 Queen Square, London, UK
| | - Bruce L Miller
- Memory and Aging Center, University of California San Francisco, San Francisco, California, USA
| | - Gil D Rabinovici
- Memory and Aging Center, University of California San Francisco, San Francisco, California, USA
| | - Elizabeth K Warrington
- Dementia Research Centre, Institute of Neurology, University College London, 8–11 Queen Square, London, UK
| | - Martin N Rossor
- Dementia Research Centre, Institute of Neurology, University College London, 8–11 Queen Square, London, UK
| | - Nick C Fox
- Dementia Research Centre, Institute of Neurology, University College London, 8–11 Queen Square, London, UK
| | - Jason D Warren
- Dementia Research Centre, Institute of Neurology, University College London, 8–11 Queen Square, London, UK
| | - Daniel C Alexander
- Centre for Medical Image Computing, Department of Computer Science, University College London, Gower Street, London, UK
| | - Jonathan M Schott
- Dementia Research Centre, Institute of Neurology, University College London, 8–11 Queen Square, London, UK
| | - Keir X X Yong
- Dementia Research Centre, Institute of Neurology, University College London, 8–11 Queen Square, London, UK
| | - Sebastian J Crutch
- Dementia Research Centre, Institute of Neurology, University College London, 8–11 Queen Square, London, UK
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12
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Steeb B, García-Cordero I, Huizing MC, Collazo L, Borovinsky G, Ferrari J, Cuitiño MM, Ibáñez A, Sedeño L, García AM. Progressive Compromise of Nouns and Action Verbs in Posterior Cortical Atrophy. Front Psychol 2018; 9:1345. [PMID: 30123155 PMCID: PMC6085559 DOI: 10.3389/fpsyg.2018.01345] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/16/2018] [Accepted: 07/13/2018] [Indexed: 12/18/2022] Open
Abstract
Processing of nouns and action verbs can be differentially compromised following lesions to posterior and anterior/motor brain regions, respectively. However, little is known about how these deficits progress in the course of neurodegeneration. To address this issue, we assessed productive lexical skills in a patient with posterior cortical atrophy (PCA) at two different stages of his pathology. On both occasions, he underwent a structural brain imaging protocol and completed semantic fluency tasks requiring retrieval of animals (nouns) and actions (verbs). Imaging results were compared with those of controls via voxel-based morphometry (VBM), whereas fluency performance was compared to age-matched norms through Crawford's t-tests. In the first assessment, the patient exhibited atrophy of more posterior regions supporting multimodal semantics (medial temporal and lingual gyri), together with a selective deficit in noun fluency. Then, by the second assessment, the patient's atrophy had progressed mainly toward fronto-motor regions (rolandic operculum, inferior and superior frontal gyri) and subcortical motor hubs (cerebellum, thalamus), and his fluency impairments had extended to action verbs. These results offer unprecedented evidence of the specificity of the pathways related to noun and action-verb impairments in the course of neurodegeneration, highlighting the latter's critical dependence on damage to regions supporting motor functions, as opposed to multimodal semantic processes.
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Affiliation(s)
- Brenda Steeb
- Laboratory of Language Research (LILEN), Institute of Cognitive and Translational Neuroscience (INCYT), INECO Foundation, Favaloro University, Buenos Aires, Argentina
| | - Indira García-Cordero
- Laboratory of Experimental Psychology and Neuroscience (LPEN), Institute of Cognitive and Translational Neuroscience (INCYT), INECO Foundation, Favaloro University, Buenos Aires, Argentina.,National Scientific and Technical Research Council (CONICET), Buenos Aires, Argentina
| | - Marjolein C Huizing
- Laboratory of Language Research (LILEN), Institute of Cognitive and Translational Neuroscience (INCYT), INECO Foundation, Favaloro University, Buenos Aires, Argentina
| | - Lucas Collazo
- Laboratory of Language Research (LILEN), Institute of Cognitive and Translational Neuroscience (INCYT), INECO Foundation, Favaloro University, Buenos Aires, Argentina
| | - Geraldine Borovinsky
- Laboratory of Language Research (LILEN), Institute of Cognitive and Translational Neuroscience (INCYT), INECO Foundation, Favaloro University, Buenos Aires, Argentina
| | - Jesica Ferrari
- Department of Language Speech, Institute of Cognitive Neurology, Buenos Aires, Argentina
| | - Macarena M Cuitiño
- Laboratory of Language Research (LILEN), Institute of Cognitive and Translational Neuroscience (INCYT), INECO Foundation, Favaloro University, Buenos Aires, Argentina.,National Scientific and Technical Research Council (CONICET), Buenos Aires, Argentina.,Faculty of Psychology, Favaloro University, Buenos Aires, Argentina.,Faculty of Psychology, University of Buenos Aires, Buenos Aires, Argentina
| | - Agustín Ibáñez
- Laboratory of Experimental Psychology and Neuroscience (LPEN), Institute of Cognitive and Translational Neuroscience (INCYT), INECO Foundation, Favaloro University, Buenos Aires, Argentina.,National Scientific and Technical Research Council (CONICET), Buenos Aires, Argentina.,Universidad Autónoma del Caribe, Barranquilla, Colombia.,Center for Social and Cognitive Neuroscience, School of Psychology, Universidad Adolfo Ibáñez, Santiago de Chile, Chile.,Centre of Excellence in Cognition and its Disorders, Australian Research Council, Sydney, NSW, Australia
| | - Lucas Sedeño
- Laboratory of Experimental Psychology and Neuroscience (LPEN), Institute of Cognitive and Translational Neuroscience (INCYT), INECO Foundation, Favaloro University, Buenos Aires, Argentina.,National Scientific and Technical Research Council (CONICET), Buenos Aires, Argentina
| | - Adolfo M García
- Laboratory of Experimental Psychology and Neuroscience (LPEN), Institute of Cognitive and Translational Neuroscience (INCYT), INECO Foundation, Favaloro University, Buenos Aires, Argentina.,National Scientific and Technical Research Council (CONICET), Buenos Aires, Argentina.,Faculty of Education, National University of Cuyo, Mendoza, Argentina
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13
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Esteves S, Ramirez Romero DA, Torralva T, Martínez Cuitiño M, Herndon S, Couto B, Ibañez A, Manes F, Roca M. Posterior cortical atrophy: a single case cognitive and radiological follow-up. Neurocase 2018; 24:16-30. [PMID: 29308699 DOI: 10.1080/13554794.2017.1421667] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/18/2023]
Abstract
Posterior cortical atrophy (PCA) is a rare neurodegenerative syndrome characterized by initial predominant visuoperceptual deficits followed by a progressive decline in other cognitive functions. This syndrome has not been as thoroughly described as other dementias, particularly from a neuropsychological evolution perspective with only a few studies describing the evolution of its cognitive progression. In this investigation we review the literature on this rare condition and we perform a 7-year neuropsychological and neuroradiological follow-up of a 64-year-old man with PCA. The subject's deficits initially appeared in his visuoperceptual skills with later affectation appearing in language and other cognitive functions, this being coherent with the patient's parieto-temporal atrophy evolution.
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Affiliation(s)
- Sol Esteves
- a Neuropsychological Research Laboratory, Institute of Cognitive and Translational Neuroscience (INCyT), INECO Foundation, Favaloro University, CONICET , Buenos Aires , Argentina
| | - Diana Andrea Ramirez Romero
- a Neuropsychological Research Laboratory, Institute of Cognitive and Translational Neuroscience (INCyT), INECO Foundation, Favaloro University, CONICET , Buenos Aires , Argentina
| | - Teresa Torralva
- a Neuropsychological Research Laboratory, Institute of Cognitive and Translational Neuroscience (INCyT), INECO Foundation, Favaloro University, CONICET , Buenos Aires , Argentina
| | - Macarena Martínez Cuitiño
- a Neuropsychological Research Laboratory, Institute of Cognitive and Translational Neuroscience (INCyT), INECO Foundation, Favaloro University, CONICET , Buenos Aires , Argentina
| | - Shannon Herndon
- a Neuropsychological Research Laboratory, Institute of Cognitive and Translational Neuroscience (INCyT), INECO Foundation, Favaloro University, CONICET , Buenos Aires , Argentina.,b Department of Psychiatry, School of Medicine, University of North Carolina Chapel Hill , Chapel Hill , USA
| | - Blas Couto
- c Laboratory of Experimental Psychology and Neuroscience (LPEN), Institute of Cognitive and Translational Neuroscience (INCyT), INECO Foundation, Favaloro University, CONICET , Buenos Aires , Argentina
| | - Agustín Ibañez
- c Laboratory of Experimental Psychology and Neuroscience (LPEN), Institute of Cognitive and Translational Neuroscience (INCyT), INECO Foundation, Favaloro University, CONICET , Buenos Aires , Argentina.,d Centre of Excellence in Cognition and its Disorders, Australian Research Council (ACR) , Sydney , Australia.,e Universidad Autónoma del Caribe, Barranquilla , Colombia.,f Centre for Social and Cognitive Neuroscience (CSCN), School of Psychology, Universidad Adolfo Ibañez , Santiago de Chile , Chile.,g National Scientific and Technical Research Council (CONICET) , Buenos Aires , Argentina
| | - Facundo Manes
- d Centre of Excellence in Cognition and its Disorders, Australian Research Council (ACR) , Sydney , Australia.,g National Scientific and Technical Research Council (CONICET) , Buenos Aires , Argentina
| | - María Roca
- g National Scientific and Technical Research Council (CONICET) , Buenos Aires , Argentina
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14
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Borges MK, Lopes TN, Biella MM, Siqueira A, Mauer S, Aprahamian I. Early-Onset Alzheimer Disease (EOAD) With Aphasia: A Case Report. Front Psychiatry 2018; 9:469. [PMID: 30319468 PMCID: PMC6170636 DOI: 10.3389/fpsyt.2018.00469] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/28/2018] [Accepted: 09/07/2018] [Indexed: 11/23/2022] Open
Abstract
Background: Alzheimer's disease (AD) is traditionally subdivided into early onset (EOAD) and late onset (LOAD). EOAD has an onset before age 65 years and accounts for 1-5% of all cases. Two main presentation types of AD are familial and sporadic. Case presentation: The authors present the case of a 68-year-old retired white man, with a college level educational background. At 55 years of age, the patient presented cognitive decline with short-term memory impairment and slowed, hesitant speech. At 57 years, he was unable to remember the way to work, exhibiting spatial disorientation. PET-CT: revealed hypometabolism and atrophy in the left temporal lobe and posterior region of the parietal lobes. Disease course: Evolving with difficulties in comprehension and sentence repetition over past 3 years and with global aphasia in past 6 months, beyond progressive memory impairment. Discussion: Possibly due to the young age and atypical presentation, and the diagnosis of EOAD is often delayed. To the best of our knowledge, this case can be classified as a sporadic EOAD with aphasia. Clinical variant and neuroimaging findings were crucial to the diagnosis and treatment of this atypical presentation of AD.
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Affiliation(s)
- Marcus Kiiti Borges
- Department of Geriatric Psychiatry, FEAES (Fundação Estatal de Atenção Especializada em Saúde), Curitiba, Brazil.,Department of Geriatrics, Hospital das Clínicas da Universidade de São Paulo, ACID (Ambulatório de Alterações Comportamentais em Idosos), São Paulo, Brazil.,Department of Psychiatry, FMUSP (Faculty of Medicine - University of São Paulo), São Paulo, Brazil
| | - Thais Nakayama Lopes
- Department of Geriatric Psychiatry, FEAES (Fundação Estatal de Atenção Especializada em Saúde), Curitiba, Brazil
| | - Marina Maria Biella
- Department of Geriatrics, Hospital das Clínicas da Universidade de São Paulo, ACID (Ambulatório de Alterações Comportamentais em Idosos), São Paulo, Brazil.,Department of Psychiatry, FMUSP (Faculty of Medicine - University of São Paulo), São Paulo, Brazil
| | - Alaíse Siqueira
- Department of Geriatrics, Hospital das Clínicas da Universidade de São Paulo, ACID (Ambulatório de Alterações Comportamentais em Idosos), São Paulo, Brazil.,Department of Psychiatry, FMUSP (Faculty of Medicine - University of São Paulo), São Paulo, Brazil
| | - Sivan Mauer
- Department of Geriatrics, Hospital das Clínicas da Universidade de São Paulo, ACID (Ambulatório de Alterações Comportamentais em Idosos), São Paulo, Brazil.,Department of Psychiatry, FMUSP (Faculty of Medicine - University of São Paulo), São Paulo, Brazil
| | - Ivan Aprahamian
- Department of Geriatrics, Hospital das Clínicas da Universidade de São Paulo, ACID (Ambulatório de Alterações Comportamentais em Idosos), São Paulo, Brazil.,Department of Psychiatry, FMUSP (Faculty of Medicine - University of São Paulo), São Paulo, Brazil.,Department of Internal Medicine, FMJ (Faculty of Medicine of Jundiaí), São Paulo, Brazil
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15
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Mattsson N, Schott JM, Hardy J, Turner MR, Zetterberg H. Selective vulnerability in neurodegeneration: insights from clinical variants of Alzheimer's disease. J Neurol Neurosurg Psychiatry 2016; 87:1000-4. [PMID: 26746185 DOI: 10.1136/jnnp-2015-311321] [Citation(s) in RCA: 51] [Impact Index Per Article: 6.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/08/2015] [Accepted: 12/05/2015] [Indexed: 11/04/2022]
Abstract
Selective vulnerability in the nervous system refers to the fact that subpopulations of neurons in different brain systems may be more or less prone to abnormal function or death in response to specific types of pathological states or injury. The concept has been used extensively as a potential way of explaining differences in degeneration patterns and the clinical presentation of different neurodegenerative diseases. Yet the increasing complexity of molecular histopathology at the cellular level in neurodegenerative disorders frequently appears at odds with phenotyping based on clinically-directed, macroscopic regional brain involvement. While cross-disease comparisons can provide insights into the differential vulnerability of networks and neuronal populations, we focus here on what is known about selective vulnerability-related factors that might explain the differential phenotypic expressions of the same disease-in this case, typical and atypical forms of Alzheimer's disease. Whereas considerable progress has been made in this area, much is yet to be elucidated; further studies comparing different phenotypic variants aimed at identifying both vulnerability and resilience factors may provide valuable insights into disease pathogenesis, and suggest novel targets for therapy.
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Affiliation(s)
- Niklas Mattsson
- Clinical Memory Research Unit, Faculty of Medicine, Lund University, Lund, Sweden
| | | | - John Hardy
- Department of Molecular Neuroscience, UCL Institute of Neurology, London, UK
| | - Martin R Turner
- Nuffield Department of Clinical Neurosciences, Oxford University, Oxford, UK
| | - Henrik Zetterberg
- Department of Molecular Neuroscience, UCL Institute of Neurology, London, UK Clinical Neurochemistry Laboratory, Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, The Sahlgrenska Academy at University of Gothenburg, Mölndal, Sweden
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16
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Visual impairment. HANDBOOK OF CLINICAL NEUROLOGY 2016. [PMID: 27430448 DOI: 10.1016/b978-0-444-53486-6.00045-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register]
Abstract
This chapter can guide the use of imaging in the evaluation of common visual syndromes: transient visual disturbance, including migraine and amaurosis fugax; acute optic neuropathy complicating multiple sclerosis, neuromyelitis optica spectrum disorder, Leber hereditary optic neuropathy, and Susac syndrome; papilledema and pseudotumor cerebri syndrome; cerebral disturbances of vision, including posterior cerebral arterial occlusion, posterior reversible encephalopathy, hemianopia after anterior temporal lobe resection, posterior cortical atrophy, and conversion blindness. Finally, practical efforts in visual rehabilitation by sensory substitution for blind patients can improve their lives and disclose new information about the brain.
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17
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Clinical and neuroimaging differences between posterior cortical atrophy and typical amnestic Alzheimer's disease patients at an early disease stage. Sci Rep 2016; 6:29372. [PMID: 27377199 PMCID: PMC4932506 DOI: 10.1038/srep29372] [Citation(s) in RCA: 17] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/31/2015] [Accepted: 06/16/2016] [Indexed: 11/09/2022] Open
Abstract
To identify clinical and neuroimaging characteristics between posterior cortical atrophy (PCA) and typical amnestic Alzheimer's disease (tAD) patients at an early disease stage, 16 PCA and 13 age-matched tAD patients were enrolled. Compared with tAD patients, PCA patients showed higher mean recognition and recall test scores, and lower mean calculation, spatial attention, shape discrimination, and writing test scores. Mean right hippocampal volume was larger in PCA patients compared with tAD patients, while cortical gray matter (GM) volume of bilateral parietal and occipital lobes was smaller in PCA patients. Further, when compared with tAD patients, significant hypometabolism was observed in bilateral parietal and occipital lobes, particularly the right occipitotemporal junction in PCA patients. Additionally, there were significant positive correlations in recognition and recall scores with hippocampal volumes. In PCA patients, calculation and visuospatial ability scores are positively associated with GM volume of parietal and occipital lobes. And only spatial attention and shape discrimination scores are positively associated with regional glucose metabolism of parietal and occipital lobes. Therefore, PCA patients display better recognition and recall scores, which are associated with larger hippocampal volumes and poorer performance in visual spatial tasks because of marked GM atrophy and hypometabolism of parietal and occipital lobes.
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18
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Ishiwata A, Kimura K. Homonymous Hemianopsia Associated with Probable Alzheimer's Disease. J NIPPON MED SCH 2016; 83:87-92. [PMID: 27180794 DOI: 10.1272/jnms.83.87] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/19/2022]
Abstract
Posterior cortical atrophy (PCA) is a rare neurodegenerative disorder that has cerebral atrophy in the parietal, occipital, or occipitotemporal cortices and is characterized by visuospatial and visuoperceptual impairments. The most cases are pathologically compatible with Alzheimer's disease (AD). We describe a case of PCA in which a combination of imaging methods, in conjunction with symptoms and neurological and neuropsychological examinations, led to its being diagnosed and to AD being identified as its probable cause. Treatment with donepezil for 6 months mildly improved alexia symptoms, but other symptoms remained unchanged. A 59-year-old Japanese woman with progressive alexia, visual deficit, and mild memory loss was referred to our neurologic clinic for the evaluation of right homonymous hemianopsia. Our neurological examination showed alexia, constructional apraxia, mild disorientation, short-term memory loss, and right homonymous hemianopsia. These findings resulted in a score of 23 (of 30) points on the Mini-Mental State Examination. Occipital atrophy was identified, with magnetic resonance imaging (MRI) showing left-side dominance. The MRI data were quantified with voxel-based morphometry, and PCA was diagnosed on the basis of these findings. Single photon emission computed tomography with (123)I-N-isopropyl-p-iodoamphetamine showed hypoperfusion in the corresponding voxel-based morphometry occipital lobes. Additionally, the finding of hypoperfusion in the posterior associate cortex, posterior cingulate gyrus, and precuneus was consistent with AD. Therefore, the PCA was considered to be a result of AD. We considered Lewy body dementia as a differential diagnosis because of the presence of hypoperfusion in the occipital lobes. However, the patient did not meet the criteria for Lewy body dementia during the course of the disease. We therefore consider including PCA in the differential diagnoses to be important for patients with visual deficit, cognitive impairment, and cerebral atrophy in the parietal, occipital, or occipitotemporal cortices. A combination of imaging methods, including MRI and single photon emission computed tomography, may help identify probable causes of PCA.
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Affiliation(s)
- Akiko Ishiwata
- Departments of Neurological Science, Graduate School of Medicine, Nippon Medical School
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19
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Suárez-González A, Lehmann M, Shakespeare TJ, Yong KXX, Paterson RW, Slattery CF, Foulkes AJM, Rabinovici GD, Gil-Néciga E, Roldán-Lora F, Schott JM, Fox NC, Crutch SJ. Effect of age at onset on cortical thickness and cognition in posterior cortical atrophy. Neurobiol Aging 2016; 44:108-113. [PMID: 27318138 PMCID: PMC4926954 DOI: 10.1016/j.neurobiolaging.2016.04.012] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/04/2015] [Revised: 03/30/2016] [Accepted: 04/16/2016] [Indexed: 11/16/2022]
Abstract
Age at onset (AAO) has been shown to influence the phenotype of Alzheimer's disease (AD), but how it affects atypical presentations of AD remains unknown. Posterior cortical atrophy (PCA) is the most common form of atypical AD. In this study, we aimed to investigate the effect of AAO on cortical thickness and cognitive function in 98 PCA patients. We used Freesurfer (v5.3.0) to compare cortical thickness with AAO both as a continuous variable, and by dichotomizing the groups based on median age (58 years). In both the continuous and dichotomized analyses, we found a pattern suggestive of thinner cortex in precuneus and parietal areas in earlier-onset PCA, and lower cortical thickness in anterior cingulate and prefrontal cortex in later-onset PCA. These cortical thickness differences between PCA subgroups were consistent with earlier-onset PCA patients performing worse on cognitive tests involving parietal functions. Our results provide a suggestion that AAO may not only affect the clinico-anatomical characteristics in AD but may also affect atrophy patterns and cognition within atypical AD phenotypes.
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Affiliation(s)
- Aida Suárez-González
- Dementia Research Centre, Department of Neurodegenerative Disease, UCL Institute of Neurology, University College London, London, UK; Department of Neurology, University Hospital Virgen del Rocio, Seville, Spain.
| | - Manja Lehmann
- Dementia Research Centre, Department of Neurodegenerative Disease, UCL Institute of Neurology, University College London, London, UK; Memory and Aging Center, University of California San Francisco, San Francisco, California, USA
| | - Timothy J Shakespeare
- Dementia Research Centre, Department of Neurodegenerative Disease, UCL Institute of Neurology, University College London, London, UK
| | - Keir X X Yong
- Dementia Research Centre, Department of Neurodegenerative Disease, UCL Institute of Neurology, University College London, London, UK
| | - Ross W Paterson
- Dementia Research Centre, Department of Neurodegenerative Disease, UCL Institute of Neurology, University College London, London, UK
| | - Catherine F Slattery
- Dementia Research Centre, Department of Neurodegenerative Disease, UCL Institute of Neurology, University College London, London, UK
| | - Alexander J M Foulkes
- Dementia Research Centre, Department of Neurodegenerative Disease, UCL Institute of Neurology, University College London, London, UK
| | - Gil D Rabinovici
- Memory and Aging Center, University of California San Francisco, San Francisco, California, USA
| | - Eulogio Gil-Néciga
- Department of Neurology, University Hospital Virgen del Rocio, Seville, Spain
| | | | - Jonathan M Schott
- Dementia Research Centre, Department of Neurodegenerative Disease, UCL Institute of Neurology, University College London, London, UK
| | - Nick C Fox
- Dementia Research Centre, Department of Neurodegenerative Disease, UCL Institute of Neurology, University College London, London, UK
| | - Sebastian J Crutch
- Dementia Research Centre, Department of Neurodegenerative Disease, UCL Institute of Neurology, University College London, London, UK
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20
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Ossenkoppele R, Cohn-Sheehy BI, La Joie R, Vogel JW, Möller C, Lehmann M, van Berckel BNM, Seeley WW, Pijnenburg YA, Gorno-Tempini ML, Kramer JH, Barkhof F, Rosen HJ, van der Flier WM, Jagust WJ, Miller BL, Scheltens P, Rabinovici GD. Atrophy patterns in early clinical stages across distinct phenotypes of Alzheimer's disease. Hum Brain Mapp 2015; 36:4421-37. [PMID: 26260856 DOI: 10.1002/hbm.22927] [Citation(s) in RCA: 172] [Impact Index Per Article: 19.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/02/2015] [Revised: 06/29/2015] [Accepted: 07/27/2015] [Indexed: 12/12/2022] Open
Abstract
Alzheimer's disease (AD) can present with distinct clinical variants. Identifying the earliest neurodegenerative changes associated with each variant has implications for early diagnosis, and for understanding the mechanisms that underlie regional vulnerability and disease progression in AD. We performed voxel-based morphometry to detect atrophy patterns in early clinical stages of four AD phenotypes: Posterior cortical atrophy (PCA, "visual variant," n=93), logopenic variant primary progressive aphasia (lvPPA, "language variant," n=74), and memory-predominant AD categorized as early age-of-onset (EOAD, <65 years, n=114) and late age-of-onset (LOAD, >65 years, n=114). Patients with each syndrome were stratified based on: (1) degree of functional impairment, as measured by the clinical dementia rating (CDR) scale, and (2) overall extent of brain atrophy, as measured by a neuroimaging approach that sums the number of brain voxels showing significantly lower gray matter volume than cognitively normal controls (n=80). Even at the earliest clinical stage (CDR=0.5 or bottom quartile of overall atrophy), patients with each syndrome showed both common and variant-specific atrophy. Common atrophy across variants was found in temporoparietal regions that comprise the posterior default mode network (DMN). Early syndrome-specific atrophy mirrored functional brain networks underlying functions that are uniquely affected in each variant: Language network in lvPPA, posterior cingulate cortex-hippocampal circuit in amnestic EOAD and LOAD, and visual networks in PCA. At more advanced stages, atrophy patterns largely converged across AD variants. These findings support a model in which neurodegeneration selectively targets both the DMN and syndrome-specific vulnerable networks at the earliest clinical stages of AD.
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Affiliation(s)
- Rik Ossenkoppele
- Department of Neurology, Memory and Aging Center, University of California San Francisco, San Francisco, California.,Helen Wills Neuroscience Institute, University of California Berkeley, Berkeley, California.,Department of Neurology & Alzheimer Center, Neuroscience Campus Amsterdam, VU University Medical Center, Amsterdam, The Netherlands.,Department of Radiology & Nuclear Medicine, VU University Medical Center, Amsterdam, The Netherlands
| | - Brendan I Cohn-Sheehy
- Department of Neurology, Memory and Aging Center, University of California San Francisco, San Francisco, California
| | - Renaud La Joie
- Helen Wills Neuroscience Institute, University of California Berkeley, Berkeley, California
| | - Jacob W Vogel
- Helen Wills Neuroscience Institute, University of California Berkeley, Berkeley, California
| | - Christiane Möller
- Department of Neurology & Alzheimer Center, Neuroscience Campus Amsterdam, VU University Medical Center, Amsterdam, The Netherlands
| | - Manja Lehmann
- Department of Neurology, Memory and Aging Center, University of California San Francisco, San Francisco, California.,Dementia Research Centre, UCL Institute of Neurology, University College London, London, United Kingdom
| | - Bart N M van Berckel
- Helen Wills Neuroscience Institute, University of California Berkeley, Berkeley, California
| | - William W Seeley
- Department of Neurology, Memory and Aging Center, University of California San Francisco, San Francisco, California
| | - Yolande A Pijnenburg
- Department of Neurology & Alzheimer Center, Neuroscience Campus Amsterdam, VU University Medical Center, Amsterdam, The Netherlands
| | - Maria L Gorno-Tempini
- Department of Neurology, Memory and Aging Center, University of California San Francisco, San Francisco, California
| | - Joel H Kramer
- Department of Neurology, Memory and Aging Center, University of California San Francisco, San Francisco, California
| | - Frederik Barkhof
- Department of Radiology & Nuclear Medicine, VU University Medical Center, Amsterdam, The Netherlands
| | - Howard J Rosen
- Department of Neurology, Memory and Aging Center, University of California San Francisco, San Francisco, California
| | - Wiesje M van der Flier
- Department of Neurology & Alzheimer Center, Neuroscience Campus Amsterdam, VU University Medical Center, Amsterdam, The Netherlands.,Department of Epidemiology & Biostatistics, VU University Medical Center, Amsterdam, The Netherlands
| | - William J Jagust
- Helen Wills Neuroscience Institute, University of California Berkeley, Berkeley, California
| | - Bruce L Miller
- Department of Neurology, Memory and Aging Center, University of California San Francisco, San Francisco, California
| | - Philip Scheltens
- Department of Neurology & Alzheimer Center, Neuroscience Campus Amsterdam, VU University Medical Center, Amsterdam, The Netherlands
| | - Gil D Rabinovici
- Department of Neurology, Memory and Aging Center, University of California San Francisco, San Francisco, California.,Helen Wills Neuroscience Institute, University of California Berkeley, Berkeley, California
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21
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Loss of functional connectivity is greater outside the default mode network in nonfamilial early-onset Alzheimer's disease variants. Neurobiol Aging 2015; 36:2678-86. [PMID: 26242705 DOI: 10.1016/j.neurobiolaging.2015.06.029] [Citation(s) in RCA: 60] [Impact Index Per Article: 6.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/17/2014] [Revised: 06/16/2015] [Accepted: 06/18/2015] [Indexed: 12/21/2022]
Abstract
The common and specific involvement of brain networks in clinical variants of Alzheimer's disease (AD) is not well understood. We performed task-free ("resting-state") functional imaging in 60 nonfamilial AD patients, including 20 early-onset AD (age at onset <65 years, amnestic/dysexecutive deficits), 24 logopenic aphasia (language deficits), and 16 posterior cortical atrophy patients (visual deficits), as well as 60 healthy controls. Seed-based connectivity analyses were conducted to assess differences between groups in 3 default mode network (DMN) components (anterior, posterior, and ventral) and 4 additional non-DMN networks: left and right executive-control, language, and higher visual networks. Significant decreases in connectivity were found across AD variants compared with controls in the non-DMN networks. Within the DMN components, patients showed higher connectivity in the anterior DMN, in particular in logopenic aphasia. No significant differences were found for the posterior and ventral DMN. Our findings suggest that loss of functional connectivity is greatest in networks outside the DMN in early-onset and nonamnestic AD variants and may thus be a better biomarker in these patients.
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22
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Solyga VM, Western E, Solheim H, Hassel B, Kerty E. [Posterior cortical atrophy]. TIDSSKRIFT FOR DEN NORSKE LEGEFORENING 2015; 135:949-52. [PMID: 26037756 DOI: 10.4045/tidsskr.14.1127] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/02/2022] Open
Abstract
BACKGROUND Posterior cortical atrophy is a neurodegenerative condition with atrophy of posterior parts of the cerebral cortex, including the visual cortex and parts of the parietal and temporal cortices. It presents early, in the 50s or 60s, with nonspecific visual disturbances that are often misinterpreted as ophthalmological, which can delay the diagnosis. The purpose of this article is to present current knowledge about symptoms, diagnostics and treatment of this condition. METHOD The review is based on a selection of relevant articles in PubMed and on the authors' own experience with the patient group. RESULTS Posterior cortical atrophy causes gradually increasing impairment in reading, distance judgement, and the ability to perceive complex images. Examination of higher visual functions, neuropsychological testing, and neuroimaging contribute to diagnosis. In the early stages, patients do not have problems with memory or insight, but cognitive impairment and dementia can develop. It is unclear whether the condition is a variant of Alzheimer's disease, or whether it is a separate disease entity. There is no established treatment, but practical measures such as the aid of social care workers, telephones with large keypads, computers with voice recognition software and audiobooks can be useful. INTERPRETATION Currently available treatment has very limited effect on the disease itself. Nevertheless it is important to identify and diagnose the condition in its early stages in order to be able to offer patients practical assistance in their daily lives.
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Affiliation(s)
| | - Elin Western
- Psykosomatisk avdeling Oslo universitetssykehus, Rikshospitalet
| | - Hanne Solheim
- Nukleærmedisinsk avdeling Oslo universitetssykehus, Radiumhospitalet
| | - Bjørnar Hassel
- Nevrologisk avdeling Oslo universitetssykehus, Rikshospitalet og Forsvarets forskningsinstitutt Kjeller
| | - Emilia Kerty
- Nevrologisk avdeling Oslo universitetssykehus, Rikshospitalet og Det medisinske fakultet Universitetet i Oslo
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23
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Abstract
Young-onset dementia is a broad category of diseases that affect adults before the age of 65, with devastating effects on individuals and families. Neuroimaging plays a clear and ever-expanding role in the workup of these diseases. MRI demonstrates classic patterns of atrophy that help to confirm the clinical diagnosis and may predict the underlying disease. Functional nuclear imaging, such as PET, demonstrates areas of brain dysfunction even in the absence of visible atrophy. These techniques can inform important aspects of the care of young-onset dementia, such as the underlying pathologic condition, treatment, and prognosis.
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Affiliation(s)
- HyungSub Shim
- Department of Neurology, University of Iowa Hospitals and Clinics, University of Iowa Carver College of Medicine, 200 Hawkins Drive, Iowa City, IA 52242, USA.
| | - Maria J Ly
- Department of Psychiatry, University of Iowa Carver College of Medicine, 200 Hawkins Drive, Iowa City, IA 52242, USA
| | - Sarah K Tighe
- Department of Psychiatry, University of Iowa Carver College of Medicine, 200 Hawkins Drive, Iowa City, IA 52242, USA
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24
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Ossenkoppele R, Mattsson N, Teunissen CE, Barkhof F, Pijnenburg Y, Scheltens P, van der Flier WM, Rabinovici GD. Cerebrospinal fluid biomarkers and cerebral atrophy in distinct clinical variants of probable Alzheimer's disease. Neurobiol Aging 2015; 36:2340-7. [PMID: 25990306 DOI: 10.1016/j.neurobiolaging.2015.04.011] [Citation(s) in RCA: 42] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/27/2015] [Revised: 03/27/2015] [Accepted: 04/18/2015] [Indexed: 11/17/2022]
Abstract
Different clinical variants of probable Alzheimer's disease (AD) share underlying plaques and tangles but show distinct atrophy patterns. We included 52 posterior cortical atrophy, 29 logopenic variant primary progressive aphasia, 53 early-onset and 42 late-onset AD patients, selected for abnormal cerebrospinal fluid (CSF)-amyloid-beta42, with CSF and magnetic resonance imaging data available. Bootstrapping revealed no differences in the prevalence of abnormal CSF total-tau and phosphorylated-tau between probable AD variants (range total-tau: 84.9%-92.3%, phosphorylated-tau: 79.2%-93.1%, p > 0.05). Voxelwise linear regressions showed various relationships between lower CSF-Aβ42 and syndrome-specific atrophy, involving precuneus, posterior cingulate, and medial temporal lobe in early-onset AD, occipital cortex and middle temporal gyrus in posterior cortical atrophy; anterior cingulate, insular cortex and precentral gyrus (left > right) in logopenic variant primary progressive aphasia; and medial temporal lobe, thalamus, and temporal pole in late-onset AD (all at p < 0.001 uncorrected). In contrast, CSF-tau was not related to gray matter atrophy in any group. Our findings suggest that lower CSF-amyloid-beta42 - and not increased total-tau and phosphorylated-tau - relates to reduced gray matter volumes, mostly in regions that are typically atrophied in distinct clinical variants of probable AD.
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Affiliation(s)
- Rik Ossenkoppele
- Department of Neurology, Memory and Aging Center, University of California San Francisco, San Francisco, CA, USA; Helen Wills Neuroscience Institute, University of California Berkeley, Berkeley, CA, USA; Department of Neurology & Alzheimer Center, VU University Medical Center, Amsterdam, The Netherlands; Department of Radiology & Nuclear Medicine, VU University Medical Center, Amsterdam, The Netherlands.
| | - Niklas Mattsson
- Department of Veterans Affairs Medical Center, Center for Imaging of Neurodegenerative diseases, San Francisco, CA, USA; Institute of Neuroscience and Physiology, Laboratory of Clinical Neurochemistry, University of Gothenburg, Gothenburg, Sweden
| | - Charlotte E Teunissen
- Department of Clinical Chemistry, VU University Medical Center, Amsterdam, The Netherlands
| | - Frederik Barkhof
- Department of Radiology & Nuclear Medicine, VU University Medical Center, Amsterdam, The Netherlands
| | - Yolande Pijnenburg
- Department of Neurology & Alzheimer Center, VU University Medical Center, Amsterdam, The Netherlands
| | - Philip Scheltens
- Department of Neurology & Alzheimer Center, VU University Medical Center, Amsterdam, The Netherlands
| | - Wiesje M van der Flier
- Department of Neurology & Alzheimer Center, VU University Medical Center, Amsterdam, The Netherlands; Department of Epidemiology and Biostatistics, VU University Medical Center, Amsterdam, The Netherlands
| | - Gil D Rabinovici
- Department of Neurology, Memory and Aging Center, University of California San Francisco, San Francisco, CA, USA; Helen Wills Neuroscience Institute, University of California Berkeley, Berkeley, CA, USA
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25
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Barnes J, Dickerson BC, Frost C, Jiskoot LC, Wolk D, van der Flier WM. Alzheimer's disease first symptoms are age dependent: Evidence from the NACC dataset. Alzheimers Dement 2015; 11:1349-57. [PMID: 25916562 DOI: 10.1016/j.jalz.2014.12.007] [Citation(s) in RCA: 80] [Impact Index Per Article: 8.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/13/2014] [Revised: 11/11/2014] [Accepted: 12/08/2014] [Indexed: 12/21/2022]
Abstract
INTRODUCTION Determining the relationship between age and Alzheimer's disease (AD) presentation is important to improve understanding and provide better patient services. METHODS We used AD patient data (N = 7815) from the National Alzheimer Coordinating Center database and multinomial logistic regression to investigate presentation age and first cognitive/behavioral symptoms. RESULTS The odds of having a nonmemory first cognitive symptom (including impairment in judgment and problem solving, language, and visuospatial function) increased with younger age (P < .001, all tests). Compared with apathy/withdrawal, the odds of having depression and "other" behavioral symptoms increased with younger age (P < .02, both tests), whereas the odds of having psychosis and no behavioral symptom increased with older age (P < .001, both tests). DISCUSSION There is considerable heterogeneity in the first cognitive/behavioral symptoms experienced by AD patients. Proportions of these symptoms change with age with patients experiencing increasing nonmemory cognitive symptoms and more behavioral symptoms at younger ages.
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Affiliation(s)
- Josephine Barnes
- Department of Neurodegenerative Disease, Dementia Research Centre, UCL Institute of Neurology, National Hospital for Neurology and Neurosurgery, London, UK.
| | - Bradford C Dickerson
- Department of Neurology, Frontotemporal Dementia Unit and Alzheimer's Disease Research Center, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Chris Frost
- Department of Medical Statistics, London School of Hygiene and Tropical Medicine, London, UK
| | - Lize C Jiskoot
- Department of Neurology, Alzheimer Center, Neuroscience Campus Amsterdam, VU University Medical Center, Amsterdam, the Netherlands; Department of Neurology, Erasmus Medical Center, Rotterdam, the Netherlands
| | - David Wolk
- Department of Neurology, Penn Memory Center, University of Pennsylvania, Philadelphia, PA, USA
| | - Wiesje M van der Flier
- Department of Neurology, Alzheimer Center, Neuroscience Campus Amsterdam, VU University Medical Center, Amsterdam, the Netherlands; Department of Epidemiology & Biostatistics, Neuroscience Campus Amsterdam, VU University Medical Center, Amsterdam, the Netherlands
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26
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Chan LTA, Lynch W, De May M, Horton JC, Miller BL, Rabinovici GD. Prodromal posterior cortical atrophy: clinical, neuropsychological, and radiological correlation. Neurocase 2015; 21:44-55. [PMID: 24308559 PMCID: PMC4318700 DOI: 10.1080/13554794.2013.860176] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/03/2023]
Abstract
We present longitudinal clinical, cognitive, and neuroimaging data from a 63-year-old woman who enrolled in research as a normal control and evolved posterior cortical atrophy (PCA) over 5 year follow-up. At baseline she reported only subtle difficulty driving and performed normally on cognitive tests, but already demonstrated atrophy in left visual association cortex. With follow-up she developed insidiously progressive visuospatial and visuoperceptual deficits, correlating with progressive atrophy in bilateral visual areas. Amyloid PET was positive. This case tracks the evolution of PCA from the prodromal stage, and illustrates challenges to early diagnosis as well as the utility of imaging biomarkers.
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Affiliation(s)
- Lung Tat Andrew Chan
- a Memory and Aging Center, Department of Neurology , University of California San Francisco , San Francisco , USA
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27
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Ryan NS, Shakespeare TJ, Lehmann M, Keihaninejad S, Nicholas JM, Leung KK, Fox NC, Crutch SJ. Motor features in posterior cortical atrophy and their imaging correlates. Neurobiol Aging 2014; 35:2845-2857. [PMID: 25086839 PMCID: PMC4236588 DOI: 10.1016/j.neurobiolaging.2014.05.028] [Citation(s) in RCA: 22] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/12/2014] [Revised: 05/06/2014] [Accepted: 05/31/2014] [Indexed: 12/28/2022]
Abstract
Posterior cortical atrophy (PCA) is a neurodegenerative syndrome characterized by impaired higher visual processing skills; however, motor features more commonly associated with corticobasal syndrome may also occur. We investigated the frequency and clinical characteristics of motor features in 44 PCA patients and, with 30 controls, conducted voxel-based morphometry, cortical thickness, and subcortical volumetric analyses of their magnetic resonance imaging. Prominent limb rigidity was used to define a PCA-motor subgroup. A total of 30% (13) had PCA-motor; all demonstrating asymmetrical left upper limb rigidity. Limb apraxia was more frequent and asymmetrical in PCA-motor, as was myoclonus. Tremor and alien limb phenomena only occurred in this subgroup. The subgroups did not differ in neuropsychological test performance or apolipoprotein E4 allele frequency. Greater asymmetry of atrophy occurred in PCA-motor, particularly involving right frontoparietal and peri-rolandic cortices, putamen, and thalamus. The 9 patients (including 4 PCA-motor) with pathology or cerebrospinal fluid all showed evidence of Alzheimer's disease. Our data suggest that PCA patients with motor features have greater atrophy of contralateral sensorimotor areas but are still likely to have underlying Alzheimer's disease.
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Affiliation(s)
- Natalie S Ryan
- Dementia Research Centre, Department of Neurodegenerative Disease, University College London (UCL) Institute of Neurology, Queen Square, London, UK.
| | - Timothy J Shakespeare
- Dementia Research Centre, Department of Neurodegenerative Disease, University College London (UCL) Institute of Neurology, Queen Square, London, UK
| | - Manja Lehmann
- Dementia Research Centre, Department of Neurodegenerative Disease, University College London (UCL) Institute of Neurology, Queen Square, London, UK
| | - Shiva Keihaninejad
- Dementia Research Centre, Department of Neurodegenerative Disease, University College London (UCL) Institute of Neurology, Queen Square, London, UK
| | - Jennifer M Nicholas
- Dementia Research Centre, Department of Neurodegenerative Disease, University College London (UCL) Institute of Neurology, Queen Square, London, UK; Department of Medical Statistics, Faculty of Epidemiology and Population Health, London School of Hygiene and Tropical Medicine, Keppel St, London, UK
| | - Kelvin K Leung
- Dementia Research Centre, Department of Neurodegenerative Disease, University College London (UCL) Institute of Neurology, Queen Square, London, UK
| | - Nick C Fox
- Dementia Research Centre, Department of Neurodegenerative Disease, University College London (UCL) Institute of Neurology, Queen Square, London, UK
| | - Sebastian J Crutch
- Dementia Research Centre, Department of Neurodegenerative Disease, University College London (UCL) Institute of Neurology, Queen Square, London, UK
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Posterior cortical atrophy and Alzheimer's disease: a meta-analytic review of neuropsychological and brain morphometry studies. Brain Imaging Behav 2014; 7:353-61. [PMID: 23690254 DOI: 10.1007/s11682-013-9236-1] [Citation(s) in RCA: 22] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/16/2022]
Abstract
This paper presents the first systematic review and meta-analysis of neuropsychological and brain morphometry studies comparing posterior cortical atrophy (PCA) to typical Alzheimer's disease (tAD). Literature searches were conducted for brain morphometry and neuropsychological studies including a PCA and a tAD group. Compared to healthy controls (HC), PCA patients exhibited significant decreases in temporal, occipital and parietal gray matter (GM) volumes, whereas tAD patients showed extensive left temporal atrophy. Compared to tAD patients, participants with PCA showed greater GM volume reduction in the right occipital gyrus extending to the posterior lobule. In addition, PCA patients showed less GM volume loss in the left parahippocampal gyrus and left hippocampus than tAD patients. PCA patients exhibit significantly greater impairment in Immediate Visuospatial Memory as well as Visuoperceptual and Visuospatial Abilities than patients with tAD. However, tAD patients showed greater impairment in Delayed Auditory/Verbal Memory than patients with PCA. PCA is characterized by significant atrophy of the occipital and parietal regions and severe impairments in visuospatial functioning.
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Laforce R, Tosun D, Ghosh P, Lehmann M, Madison CM, Weiner MW, Miller BL, Jagust WJ, Rabinovici GD. Parallel ICA of FDG-PET and PiB-PET in three conditions with underlying Alzheimer's pathology. NEUROIMAGE-CLINICAL 2014; 4:508-16. [PMID: 24818077 PMCID: PMC3984448 DOI: 10.1016/j.nicl.2014.03.005] [Citation(s) in RCA: 52] [Impact Index Per Article: 5.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 08/15/2013] [Revised: 03/12/2014] [Accepted: 03/13/2014] [Indexed: 01/18/2023]
Abstract
The relationships between clinical phenotype, β-amyloid (Aβ) deposition and neurodegeneration in Alzheimer's disease (AD) are incompletely understood yet have important ramifications for future therapy. The goal of this study was to utilize multimodality positron emission tomography (PET) data from a clinically heterogeneous population of patients with probable AD in order to: (1) identify spatial patterns of Aβ deposition measured by ((11)C)-labeled Pittsburgh Compound B (PiB-PET) and glucose metabolism measured by FDG-PET that correlate with specific clinical presentation and (2) explore associations between spatial patterns of Aβ deposition and glucose metabolism across the AD population. We included all patients meeting the criteria for probable AD (NIA-AA) who had undergone MRI, PiB and FDG-PET at our center (N = 46, mean age 63.0 ± 7.7, Mini-Mental State Examination 22.0 ± 4.8). Patients were subclassified based on their cognitive profiles into an amnestic/dysexecutive group (AD-memory; n = 27), a language-predominant group (AD-language; n = 10) and a visuospatial-predominant group (AD-visuospatial; n = 9). All patients were required to have evidence of amyloid deposition on PiB-PET. To capture the spatial distribution of Aβ deposition and glucose metabolism, we employed parallel independent component analysis (pICA), a method that enables joint analyses of multimodal imaging data. The relationships between PET components and clinical group were examined using a Receiver Operator Characteristic approach, including age, gender, education and apolipoprotein E ε4 allele carrier status as covariates. Results of the first set of analyses independently examining the relationship between components from each modality and clinical group showed three significant components for FDG: a left inferior frontal and temporoparietal component associated with AD-language (area under the curve [AUC] 0.82, p = 0.011), and two components associated with AD-visuospatial (bilateral occipito-parieto-temporal [AUC 0.85, p = 0.009] and right posterior cingulate cortex [PCC]/precuneus and right lateral parietal [AUC 0.69, p = 0.045]). The AD-memory associated component included predominantly bilateral inferior frontal, cuneus and inferior temporal, and right inferior parietal hypometabolism but did not reach significance (AUC 0.65, p = 0.062). None of the PiB components correlated with clinical group. Joint analysis of PiB and FDG with pICA revealed a correlated component pair, in which increased frontal and decreased PCC/precuneus PiB correlated with decreased FDG in the frontal, occipital and temporal regions (partial r = 0.75, p < 0.0001). Using multivariate data analysis, this study reinforced the notion that clinical phenotype in AD is tightly linked to patterns of glucose hypometabolism but not amyloid deposition. These findings are strikingly similar to those of univariate paradigms and provide additional support in favor of specific involvement of the language network, higher-order visual network, and default mode network in clinical variants of AD. The inverse relationship between Aβ deposition and glucose metabolism in partially overlapping brain regions suggests that Aβ may exert both local and remote effects on brain metabolism. Applying multivariate approaches such as pICA to multimodal imaging data is a promising approach for unraveling the complex relationships between different elements of AD pathophysiology.
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Affiliation(s)
- Robert Laforce
- Helen Wills Neuroscience Institute, University of California, Berkeley, CA, USA ; Memory and Aging Center, Department of Neurology, University of California San Francisco, CA, USA
| | - Duygu Tosun
- Center for Imaging of Neurodegenerative Diseases, Department of Radiology and Biomedical Imaging, University of California San Francisco, CA, USA
| | - Pia Ghosh
- Helen Wills Neuroscience Institute, University of California, Berkeley, CA, USA ; Memory and Aging Center, Department of Neurology, University of California San Francisco, CA, USA
| | - Manja Lehmann
- Helen Wills Neuroscience Institute, University of California, Berkeley, CA, USA ; Memory and Aging Center, Department of Neurology, University of California San Francisco, CA, USA
| | - Cindee M Madison
- Helen Wills Neuroscience Institute, University of California, Berkeley, CA, USA
| | - Michael W Weiner
- Center for Imaging of Neurodegenerative Diseases, Department of Radiology and Biomedical Imaging, University of California San Francisco, CA, USA
| | - Bruce L Miller
- Memory and Aging Center, Department of Neurology, University of California San Francisco, CA, USA
| | - William J Jagust
- Helen Wills Neuroscience Institute, University of California, Berkeley, CA, USA ; Lawrence Berkeley National Laboratory, University of California, Berkeley, CA, USA
| | - Gil D Rabinovici
- Helen Wills Neuroscience Institute, University of California, Berkeley, CA, USA ; Memory and Aging Center, Department of Neurology, University of California San Francisco, CA, USA ; Lawrence Berkeley National Laboratory, University of California, Berkeley, CA, USA
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Spehl TS, Hellwig S, Amtage F, Weiller C, Bormann T, Weber WA, Hüll M, Meyer PT, Frings L. Syndrome-specific patterns of regional cerebral glucose metabolism in posterior cortical atrophy in comparison to dementia with Lewy bodies and Alzheimer's disease--a [F-18]-FDG pet study. J Neuroimaging 2014; 25:281-288. [PMID: 24593796 DOI: 10.1111/jon.12104] [Citation(s) in RCA: 25] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/04/2013] [Revised: 10/12/2013] [Accepted: 11/19/2013] [Indexed: 01/08/2023] Open
Abstract
BACKGROUND Posterior cortical atrophy (PCA) is a rare neurodegenerative syndrome with visuospatial deficits. PET studies have identified hypometabolism of the occipital cortex in PCA. There is, however, a huge overlap in clinical presentation and involvement of the occipital cortex between PCA, dementia with Lewy bodies (DLB), and Alzheimer's disease (AD). Syndrome-specific patterns of metabolism have not yet been demonstrated that allow for a reliable differentiation with [F-18]-FDG-PET. METHODS A total of 33 dementia patients (PCA n = 6, DLB n = 12, AD n = 15) who underwent [F-18]-FDG-PET imaging and a neuropsychological examination were retrospectively analyzed. Group comparisons of regional cerebral glucose metabolism were calculated with statistical parametric mapping. Extracted clusters were used to evaluate discrimination accuracy by logistic regression. RESULTS PCA patients showed a syndrome-specific area of hypometabolism in the right lateral temporooccipital cortex. DLB patients showed specific hypometabolism predominantly in the left occipital cortex. Logistic regression based on these two regions correctly separated patients with a sensitivity/specificity of 83/93% for PCA, 75/86% for DLB and 67/78% for AD. Overall accuracy was 73%. CONCLUSION [F-18]-FDG-PET could reveal syndrome-specific patterns of glucose metabolism in PCA and DLB. Accurate group discrimination in the differential diagnosis of dementia with visuospatial impairment is feasible.
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Affiliation(s)
- Timo S Spehl
- Department of Nuclear Medicine, Freiburg, Germany
| | - Sabine Hellwig
- Department of Psychiatry and Psychotherapy, Freiburg, Germany.,Department of Neurology, Freiburg, Germany
| | | | | | | | | | - Michael Hüll
- Centre of Geriatrics and Gerontology Freiburg, Germany
| | | | - Lars Frings
- Centre of Geriatrics and Gerontology Freiburg, Germany.,Department of Radiation Oncology, University Hospital Freiburg, Freiburg, Germany
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Han DY, Shandera-Ochsner AL, Bell BD, Seeger SK. Diagnosis of posterior cortical atrophy delayed by coexisting Fuchs' Endothelial Corneal Dystrophy. Am J Alzheimers Dis Other Demen 2014; 29:138-41. [PMID: 24667904 PMCID: PMC10852802 DOI: 10.1177/1533317513506779] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
Posterior cortical atrophy (PCA), also known as the visual variant of Alzheimer's Disease, is a rare neurodegenerative disorder that affects the visuospatial systems in its initial stages. Due to the rarity of this condition and the presence of relatively preserved memory during its early stages compared to other dementias, its accurate diagnosis can be delayed. When accompanied by a comorbid visual disorder, the diagnostic process becomes even more challenging. This study describes the disease course of a patient whose diagnosis of Fuchs' Endothelial Corneal Dystrophy served to delay an additional diagnosis of PCA, illustrating the necessity of careful scrutiny of symptom presentation and especially its course.
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Affiliation(s)
- Dong Y. Han
- Department of Neurology, University of Kentucky College of Medicine, Lexington, KY, USA
| | | | - Brian D. Bell
- Department of Neurology, University of Wisconsin School of Medicine and Public Health, Madison, WI, USA
| | - Susanne K. Seeger
- Department of Neurology, University of Wisconsin School of Medicine and Public Health, Madison, WI, USA
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Millington RS, Ajina S, Bridge H. Novel brain imaging approaches to understand acquired and congenital neuro-ophthalmological conditions. Curr Opin Neurol 2014; 27:92-97. [PMID: 24300791 PMCID: PMC3983755 DOI: 10.1097/wco.0000000000000050] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/11/2022]
Abstract
PURPOSE OF REVIEW The arrival of large datasets and the on-going refinement of neuroimaging technology have led to a number of recent advances in our understanding of visual pathway disorders. This work can broadly be classified into two areas, both of which are important when considering the optimal management strategies. The first looks at the delineation of damage, teasing out subtle changes to (specific components of) the visual pathway, which may help evaluate the severity and extent of disease. The second uses neuroimaging to investigate neuroplasticity, via changes in connectivity, cortical thickness, and retinotopic maps within the visual cortex. RECENT FINDINGS Here, we give consideration to both acquired and congenital patients with damage to the visual pathway, and how they differ. Congenital disorders of the peripheral visual system can provide insight into the large-scale reorganization of the visual cortex: these are investigated with reference to disorders of the optic chiasm and anophthalmia (absence of the eyes). In acquired conditions, we consider the recent work describing patterns of degeneration, both following single insult and in neurodegenerative conditions. We also discuss the developments in functional neuroimaging, with particular reference to work on hemianopia and the controversial suggestion of cortical reorganization following acquired retinal injury. SUMMARY Techniques for comparing neuro-ophthalmological conditions with healthy visual systems provide sensitive metrics to uncover subtle differences in grey and white matter structure of the brain. It is now possible to compare the massive reorganization present in congenital conditions with the apparent lack of plasticity following acquired damage.
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Affiliation(s)
| | - Sara Ajina
- Corresponding author: Dr Sara Ajina, Oxford Centre for FMRI of the Brain, John Radcliffe Hospital, Oxford, OX3 9DU, UK. Tel: +44-1865-740348;
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Brodersen KH, Deserno L, Schlagenhauf F, Lin Z, Penny WD, Buhmann JM, Stephan KE. Dissecting psychiatric spectrum disorders by generative embedding. NEUROIMAGE-CLINICAL 2013; 4:98-111. [PMID: 24363992 PMCID: PMC3863808 DOI: 10.1016/j.nicl.2013.11.002] [Citation(s) in RCA: 116] [Impact Index Per Article: 10.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 07/04/2013] [Revised: 10/06/2013] [Accepted: 11/07/2013] [Indexed: 02/05/2023]
Abstract
This proof-of-concept study examines the feasibility of defining subgroups in psychiatric spectrum disorders by generative embedding, using dynamical system models which infer neuronal circuit mechanisms from neuroimaging data. To this end, we re-analysed an fMRI dataset of 41 patients diagnosed with schizophrenia and 42 healthy controls performing a numerical n-back working-memory task. In our generative-embedding approach, we used parameter estimates from a dynamic causal model (DCM) of a visual-parietal-prefrontal network to define a model-based feature space for the subsequent application of supervised and unsupervised learning techniques. First, using a linear support vector machine for classification, we were able to predict individual diagnostic labels significantly more accurately (78%) from DCM-based effective connectivity estimates than from functional connectivity between (62%) or local activity within the same regions (55%). Second, an unsupervised approach based on variational Bayesian Gaussian mixture modelling provided evidence for two clusters which mapped onto patients and controls with nearly the same accuracy (71%) as the supervised approach. Finally, when restricting the analysis only to the patients, Gaussian mixture modelling suggested the existence of three patient subgroups, each of which was characterised by a different architecture of the visual-parietal-prefrontal working-memory network. Critically, even though this analysis did not have access to information about the patients' clinical symptoms, the three neurophysiologically defined subgroups mapped onto three clinically distinct subgroups, distinguished by significant differences in negative symptom severity, as assessed on the Positive and Negative Syndrome Scale (PANSS). In summary, this study provides a concrete example of how psychiatric spectrum diseases may be split into subgroups that are defined in terms of neurophysiological mechanisms specified by a generative model of network dynamics such as DCM. The results corroborate our previous findings in stroke patients that generative embedding, compared to analyses of more conventional measures such as functional connectivity or regional activity, can significantly enhance both the interpretability and performance of computational approaches to clinical classification.
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Affiliation(s)
- Kay H Brodersen
- Translational Neuromodeling Unit (TNU), Institute for Biomedical Engineering, University of Zurich & ETH Zurich, Switzerland ; Machine Learning Laboratory, Department of Computer Science, ETH Zurich, Switzerland
| | - Lorenz Deserno
- Department of Psychiatry and Psychotherapy, Charité-Universitätsmedizin Berlin, Germany ; Max Planck Institute for Cognitive and Brain Sciences, Leipzig, Germany
| | - Florian Schlagenhauf
- Department of Psychiatry and Psychotherapy, Charité-Universitätsmedizin Berlin, Germany ; Max Planck Institute for Cognitive and Brain Sciences, Leipzig, Germany
| | - Zhihao Lin
- Translational Neuromodeling Unit (TNU), Institute for Biomedical Engineering, University of Zurich & ETH Zurich, Switzerland ; Machine Learning Laboratory, Department of Computer Science, ETH Zurich, Switzerland
| | - Will D Penny
- Wellcome Trust Centre for Neuroimaging, University College London, United Kingdom
| | - Joachim M Buhmann
- Machine Learning Laboratory, Department of Computer Science, ETH Zurich, Switzerland
| | - Klaas E Stephan
- Translational Neuromodeling Unit (TNU), Institute for Biomedical Engineering, University of Zurich & ETH Zurich, Switzerland ; Wellcome Trust Centre for Neuroimaging, University College London, United Kingdom ; Laboratory for Social and Neural Systems Research (SNS), University of Zurich, Switzerland
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Crutch SJ, Schott JM, Rabinovici GD, Boeve BF, Cappa SF, Dickerson BC, Dubois B, Graff-Radford NR, Krolak-Salmon P, Lehmann M, Mendez MF, Pijnenburg Y, Ryan NS, Scheltens P, Shakespeare T, Tang-Wai DF, van der Flier WM, Bain L, Carrillo MC, Fox NC. Shining a light on posterior cortical atrophy. Alzheimers Dement 2013; 9:463-5. [PMID: 23274153 DOI: 10.1016/j.jalz.2012.11.004] [Citation(s) in RCA: 53] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/02/2012] [Accepted: 11/14/2012] [Indexed: 10/27/2022]
Abstract
Posterior cortical atrophy (PCA) is a clinicoradiologic syndrome characterized by progressive decline in visual processing skills, relatively intact memory and language in the early stages, and atrophy of posterior brain regions. Misdiagnosis of PCA is common, owing not only to its relative rarity and unusual and variable presentation, but also because patients frequently first seek the opinion of an ophthalmologist, who may note normal eye examinations by their usual tests but may not appreciate cortical brain dysfunction. Seeking to raise awareness of the disease, stimulate research, and promote collaboration, a multidisciplinary group of PCA research clinicians formed an international working party, which had its first face-to-face meeting on July 13, 2012 in Vancouver, Canada, prior to the Alzheimer's Association International Conference.
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36
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Intrinsic connectivity networks in healthy subjects explain clinical variability in Alzheimer's disease. Proc Natl Acad Sci U S A 2013; 110:11606-11. [PMID: 23798398 DOI: 10.1073/pnas.1221536110] [Citation(s) in RCA: 97] [Impact Index Per Article: 8.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/17/2023] Open
Abstract
Although previous studies have emphasized the vulnerability of the default mode network (DMN) in Alzheimer's disease (AD), little is known about the involvement of other functional networks and their relationship to clinical phenotype. To test whether clinicoanatomic heterogeneity in AD is driven by the involvement of specific networks, network connectivity was assessed in healthy subjects by seeding regions commonly and specifically atrophied in three clinical AD variants: early-onset AD (age at onset, <65 y; memory and executive deficits), logopenic variant primary progressive aphasia (language deficits), and posterior cortical atrophy (visuospatial deficits). Four-millimeter seed regions of interest were used to obtain intrinsic connectivity maps in 131 healthy controls (age, 65.5 ± 3.5 y). Atrophy patterns in independent cohorts of AD variant patients and their correspondence to connectivity networks in controls were also assessed. The connectivity maps of commonly atrophied regions of interest support posterior DMN and precuneus network involvement across AD variants, whereas seeding regions specifically atrophied in each AD variant revealed distinct, syndrome-specific connectivity patterns. Goodness-of-fit analysis of each connectivity map with network templates showed the highest correspondence between the early-onset AD seed connectivity map and anterior salience and right executive-control networks, the logopenic aphasia seed connectivity map and the language network, and the posterior cortical atrophy seed connectivity map and the higher visual network. Connectivity maps derived from controls matched regions commonly and specifically atrophied in the patients. Our findings indicate that the posterior DMN and precuneus network are commonly affected in AD variants, whereas syndrome-specific neurodegenerative patterns are driven by the involvement of specific networks outside the DMN.
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Meek BP, Shelton P, Marotta JJ. Posterior cortical atrophy: visuomotor deficits in reaching and grasping. Front Hum Neurosci 2013; 7:294. [PMID: 23801956 PMCID: PMC3689034 DOI: 10.3389/fnhum.2013.00294] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/15/2013] [Accepted: 06/04/2013] [Indexed: 12/22/2022] Open
Abstract
Posterior Cortical Atrophy (PCA) is a rare clinical syndrome characterized by the predominance of higher-order visual disturbances such as optic ataxia, a characteristic of Balint's syndrome. Deficits result from progressive neurodegeneration of occipito-temporal and occipito-parietal cortices. The current study sought to explore the visuomotor functioning of four individuals with PCA by testing their ability to reach out and grasp real objects under various viewing conditions. Experiment 1 had participants reach out and grasp simple, rectangular blocks under visually- and memory-guided conditions. Experiment 2 explored participants' abilities to accurately reach for objects located in their visual periphery. This investigation revealed that PCA patients demonstrate many of the same deficits that have been previously reported in other individuals with optic ataxia, such as “magnetic misreaching”—a pathological reaching bias toward the point of visual fixation when grasping peripheral targets. Unlike many other individuals with optic ataxia, however, the patients in the current study also show symptoms indicative of damage to the more perceptual stream of visual processing, including abolished grip scaling during memory-guided grasping and deficits in face and object identification. These investigations are the first to perform a quantitative analysis of the visuomotor deficits exhibited by patients with PCA. Critically, this study helps characterize common symptoms of PCA, a vital first step for generating effective diagnostic criteria and therapeutic strategies for this understudied neurodegenerative disorder.
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Affiliation(s)
- Benjamin P Meek
- Perception and Action Laboratory, Department of Psychology, University of Manitoba Winnipeg, MB, Canada
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Möller C, Vrenken H, Jiskoot L, Versteeg A, Barkhof F, Scheltens P, van der Flier WM. Different patterns of gray matter atrophy in early- and late-onset Alzheimer's disease. Neurobiol Aging 2013; 34:2014-22. [PMID: 23561509 DOI: 10.1016/j.neurobiolaging.2013.02.013] [Citation(s) in RCA: 133] [Impact Index Per Article: 12.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/03/2012] [Revised: 01/25/2013] [Accepted: 02/17/2013] [Indexed: 12/16/2022]
Abstract
We assessed patterns of gray matter atrophy according to-age-at-onset in a large sample of 215 Alzheimer's disease (AD) patients and 129 control subjects with voxel-based morphometry using 3-Tesla 3D T1-weighted magnetic resonance imaging. Local gray matter amounts were compared between late- and early-onset AD patients and older and younger control subjects, taking into account the effect of apolipoprotein E. Additionally, combined effects of age and diagnosis on volumes of hippocampus and precuneus were assessed. Compared with age-matched control subjects, late-onset AD patients exhibited atrophy of the hippocampus, right temporal lobe, and cerebellum, whereas early-onset AD patients showed gray matter atrophy in hippocampus, temporal lobes, precuneus, cingulate gyrus, and inferior frontal cortex. Direct comparisons between late- and early-onset AD patients revealed more pronounced atrophy of precuneus in early-onset AD patients and more severe atrophy in medial temporal lobe in late-onset AD patients. Age and diagnosis independently affected the hippocampus; moreover, the interaction between age and diagnosis showed that precuneus atrophy was most prominent in early-onset AD patients. Our results suggest that patterns of atrophy might vary in the spectrum of AD.
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Affiliation(s)
- Christiane Möller
- Alzheimer Center and Department of Neurology, Neuroscience Campus Amsterdam, VU University Medical Center, Amsterdam, the Netherlands.
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Crutch SJ. Seeing why they cannot see: Understanding the syndrome and causes of posterior cortical atrophy. J Neuropsychol 2013; 8:157-70. [DOI: 10.1111/jnp.12011] [Citation(s) in RCA: 10] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/27/2012] [Accepted: 01/07/2013] [Indexed: 12/11/2022]
Affiliation(s)
- Sebastian J. Crutch
- Dementia Research Centre; Department of Neurodegeneration; UCL Institute of Neurology; University College London; UK
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Lehmann M, Ghosh PM, Madison C, Laforce R, Corbetta-Rastelli C, Weiner MW, Greicius MD, Seeley WW, Gorno-Tempini ML, Rosen HJ, Miller BL, Jagust WJ, Rabinovici GD. Diverging patterns of amyloid deposition and hypometabolism in clinical variants of probable Alzheimer's disease. Brain 2013; 136:844-58. [PMID: 23358601 DOI: 10.1093/brain/aws327] [Citation(s) in RCA: 245] [Impact Index Per Article: 22.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/14/2022] Open
Abstract
The factors driving clinical heterogeneity in Alzheimer's disease are not well understood. This study assessed the relationship between amyloid deposition, glucose metabolism and clinical phenotype in Alzheimer's disease, and investigated how these relate to the involvement of functional networks. The study included 17 patients with early-onset Alzheimer's disease (age at onset <65 years), 12 patients with logopenic variant primary progressive aphasia and 13 patients with posterior cortical atrophy [whole Alzheimer's disease group: age = 61.5 years (standard deviation 6.5 years), 55% male]. Thirty healthy control subjects [age = 70.8 (3.3) years, 47% male] were also included. Subjects underwent positron emission tomography with (11)C-labelled Pittsburgh compound B and (18)F-labelled fluorodeoxyglucose. All patients met National Institute on Ageing-Alzheimer's Association criteria for probable Alzheimer's disease and showed evidence of amyloid deposition on (11)C-labelled Pittsburgh compound B positron emission tomography. We hypothesized that hypometabolism patterns would differ across variants, reflecting involvement of specific functional networks, whereas amyloid patterns would be diffuse and similar across variants. We tested these hypotheses using three complimentary approaches: (i) mass-univariate voxel-wise group comparison of (18)F-labelled fluorodeoxyglucose and (11)C-labelled Pittsburgh compound B; (ii) generation of covariance maps across all subjects with Alzheimer's disease from seed regions of interest specifically atrophied in each variant, and comparison of these maps to functional network templates; and (iii) extraction of (11)C-labelled Pittsburgh compound B and (18)F-labelled fluorodeoxyglucose values from functional network templates. Alzheimer's disease clinical groups showed syndrome-specific (18)F-labelled fluorodeoxyglucose patterns, with greater parieto-occipital involvement in posterior cortical atrophy, and asymmetric involvement of left temporoparietal regions in logopenic variant primary progressive aphasia. In contrast, all Alzheimer's disease variants showed diffuse patterns of (11)C-labelled Pittsburgh compound B binding, with posterior cortical atrophy additionally showing elevated uptake in occipital cortex compared with early-onset Alzheimer's disease. The seed region of interest covariance analysis revealed distinct (18)F-labelled fluorodeoxyglucose correlation patterns that greatly overlapped with the right executive-control network for the early-onset Alzheimer's disease region of interest, the left language network for the logopenic variant primary progressive aphasia region of interest, and the higher visual network for the posterior cortical atrophy region of interest. In contrast, (11)C-labelled Pittsburgh compound B covariance maps for each region of interest were diffuse. Finally, (18)F-labelled fluorodeoxyglucose was similarly reduced in all Alzheimer's disease variants in the dorsal and left ventral default mode network, whereas significant differences were found in the right ventral default mode, right executive-control (both lower in early-onset Alzheimer's disease and posterior cortical atrophy than logopenic variant primary progressive aphasia) and higher-order visual network (lower in posterior cortical atrophy than in early-onset Alzheimer's disease and logopenic variant primary progressive aphasia), with a trend towards lower (18)F-labelled fluorodeoxyglucose also found in the left language network in logopenic variant primary progressive aphasia. There were no differences in (11)C-labelled Pittsburgh compound B binding between syndromes in any of the networks. Our data suggest that Alzheimer's disease syndromes are associated with degeneration of specific functional networks, and that fibrillar amyloid-β deposition explains at most a small amount of the clinico-anatomic heterogeneity in Alzheimer's disease.
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Affiliation(s)
- Manja Lehmann
- UCSF Memory and Ageing Centre, Department of Neurology, Box 1207, San Francisco, CA 94158-1207, USA.
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Shakespeare TJ, Crutch SJ, Fox NC. Posterior cortical atrophy: advice for diagnosis and implications for management. Neurodegener Dis Manag 2012. [DOI: 10.2217/nmt.12.61] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/07/2023] Open
Abstract
SUMMARY The clinical presentation of Alzheimer’s disease (AD) is heterogeneous, especially in individuals with an early age at onset, where the presenting symptoms may be language, behavior or visual impairment. Posterior cortical atrophy (PCA) refers to a syndrome where visual processing and other posterior functions are the initial symptoms. While the majority of PCA cases reflect the underlying AD, a proportion of cases are caused by dementia with Lewy bodies, corticobasal degeneration or prion disease. PCA is sometimes not recognized until late into the disease or misattributed to anxiety or malingering owing to its low frequency, the early age at onset and the relatively atypical symptoms. This article describes the PCA syndrome, emphasizing its clinical features and how it relates to early-onset AD variants. In order to aid identification of this syndrome, the neuroimaging and neuropsychological features, as well as biomarkers of the underlying pathology, are also described briefly. Finally, the implications for treatment, compensatory strategies and rehabilitation, as well as management of comorbidities, are discussed.
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Affiliation(s)
- Tim J Shakespeare
- Dementia Research Centre, Box 16, National Hospital for Neurology & Neurosurgery, Queen Square, London, WC1N 3BG, UK
| | - Sebastian J Crutch
- Dementia Research Centre, University College London Institute of Neurology, University College London, London, UK
| | - Nick C Fox
- Dementia Research Centre, University College London Institute of Neurology, University College London, London, UK
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Abstract
Posterior cortical atrophy (PCA) is a neurodegenerative syndrome that is characterised by progressive decline in visuospatial, visuoperceptual, literacy, and praxic skills. The progressive neurodegeneration affecting parietal, occipital, and occipitotemporal cortices that underlies PCA is attributable to Alzheimer's disease in most patients. However, alternative underlying causes, including dementia with Lewy bodies, corticobasal degeneration, and prion disease, have also been identified, and not all patients with PCA have atrophy on clinical imaging. This heterogeneity has led to inconsistencies in diagnosis and terminology and difficulties in comparing studies from different centres, and has restricted the generalisability of findings from clinical trials and investigations of factors that drive phenotypic variability. Important challenges remain, including the identification of factors associated not only with the selective vulnerability of posterior cortical regions but also with the young age of onset of PCA. Greater awareness of the syndrome and agreement over the correspondence between syndrome-level and disease-level classifications are needed to improve diagnostic accuracy, clinical management, and the design of research studies.
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Affiliation(s)
- Sebastian J Crutch
- Dementia Research Centre, Institute of Neurology, University College London, London, UK.
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