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Quattrini G, Pini L, Boscolo Galazzo I, Jelescu IO, Jovicich J, Manenti R, Frisoni GB, Marizzoni M, Pizzini FB, Pievani M. Microstructural alterations in the locus coeruleus-entorhinal cortex pathway in Alzheimer's disease and frontotemporal dementia. ALZHEIMER'S & DEMENTIA (AMSTERDAM, NETHERLANDS) 2024; 16:e12513. [PMID: 38213948 PMCID: PMC10781651 DOI: 10.1002/dad2.12513] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 08/25/2023] [Revised: 11/04/2023] [Accepted: 11/20/2023] [Indexed: 01/13/2024]
Abstract
INTRODUCTION We investigated in vivo the microstructural integrity of the pathway connecting the locus coeruleus to the transentorhinal cortex (LC-TEC) in patients with Alzheimer's disease (AD) and frontotemporal dementia (FTD). METHODS Diffusion-weighted MRI scans were collected for 21 AD, 20 behavioral variants of FTD (bvFTD), and 20 controls. Fractional anisotropy (FA), mean, axial, and radial diffusivities (MD, AxD, RD) were computed in the LC-TEC pathway using a normative atlas. Atrophy was assessed using cortical thickness and correlated with microstructural measures. RESULTS We found (i) higher RD in AD than controls; (ii) higher MD, RD, and AxD, and lower FA in bvFTD than controls and AD; and (iii) a negative association between LC-TEC MD, RD, and AxD, and entorhinal cortex (EC) thickness in bvFTD (all p < 0.050). DISCUSSION LC-TEC microstructural alterations are more pronounced in bvFTD than AD, possibly reflecting neurodegeneration secondary to EC atrophy. Highlights Microstructural integrity of LC-TEC pathway is understudied in AD and bvFTD.LC-TEC microstructural alterations are present in both AD and bvFTD.Greater LC-TEC microstructural alterations in bvFTD than AD.LC-TEC microstructural alterations in bvFTD are associated to EC neurodegeneration.
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Affiliation(s)
- Giulia Quattrini
- Laboratory of Alzheimer's Neuroimaging and Epidemiology (LANE)IRCCS Istituto Centro San Giovanni di Dio FatebenefratelliBresciaItaly
- Department of Molecular and Translational MedicineUniversity of BresciaBresciaItaly
| | - Lorenzo Pini
- Padova Neuroscience CenterUniversity of PadovaPadovaItaly
| | | | - Ileana O. Jelescu
- Department of RadiologyLausanne University Hospital and University of LausanneLausanneSwitzerland
| | - Jorge Jovicich
- Center of Mind/Brain SciencesUniversity of TrentoRoveretoItaly
| | - Rosa Manenti
- Neuropsychology UnitIRCCS Istituto Centro San Giovanni di Dio FatebenefratelliBresciaItaly
| | - Giovanni B. Frisoni
- Memory Center and LANVIE ‐ Laboratory of Neuroimaging of AgingUniversity Hospitals and University of GenevaGenevaSwitzerland
| | - Moira Marizzoni
- Laboratory of Alzheimer's Neuroimaging and Epidemiology (LANE)IRCCS Istituto Centro San Giovanni di Dio FatebenefratelliBresciaItaly
- Laboratory of Biological PsychiatryIRCCS Istituto Centro San Giovanni di Dio FatebenefratelliBresciaItaly
| | - Francesca B. Pizzini
- Department of Engineering for Innovation MedicineUniversity of VeronaVeronaItaly
| | - Michela Pievani
- Laboratory of Alzheimer's Neuroimaging and Epidemiology (LANE)IRCCS Istituto Centro San Giovanni di Dio FatebenefratelliBresciaItaly
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Bruffaerts R, Schaeverbeke J, Radwan A, Grube M, Gabel S, De Weer AS, Dries E, Van Bouwel K, Griffiths TD, Sunaert S, Vandenberghe R. Left Frontal White Matter Links to Rhythm Processing Relevant to Speech Production in Apraxia of Speech. NEUROBIOLOGY OF LANGUAGE (CAMBRIDGE, MASS.) 2022; 3:515-537. [PMID: 37215340 PMCID: PMC10158569 DOI: 10.1162/nol_a_00075] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 05/12/2021] [Accepted: 06/03/2022] [Indexed: 05/24/2023]
Abstract
Recent mechanistic models argue for a key role of rhythm processing in both speech production and speech perception. Patients with the non-fluent variant (NFV) of primary progressive aphasia (PPA) with apraxia of speech (AOS) represent a specific study population in which this link can be examined. Previously, we observed impaired rhythm processing in NFV with AOS. We hypothesized that a shared neurocomputational mechanism structures auditory input (sound and speech) and output (speech production) in time, a "temporal scaffolding" mechanism. Since considerable white matter damage is observed in NFV, we test here whether white matter changes are related to impaired rhythm processing. Forty-seven participants performed a psychoacoustic test battery: 12 patients with NFV and AOS, 11 patients with the semantic variant of PPA, and 24 cognitively intact age- and education-matched controls. Deformation-based morphometry was used to test whether white matter volume correlated to rhythmic abilities. In 34 participants, we also obtained tract-based metrics of the left Aslant tract, which is typically damaged in patients with NFV. Nine out of 12 patients with NFV displayed impaired rhythmic processing. Left frontal white matter atrophy adjacent to the supplementary motor area (SMA) correlated with poorer rhythmic abilities. The structural integrity of the left Aslant tract also correlated with rhythmic abilities. A colocalized and perhaps shared white matter substrate adjacent to the SMA is associated with impaired rhythmic processing and motor speech impairment. Our results support the existence of a temporal scaffolding mechanism structuring perceptual input and speech output.
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Affiliation(s)
- Rose Bruffaerts
- Laboratory for Cognitive Neurology, Department of Neurosciences & Leuven Brain Institute, Katholieke Universiteit Leuven, Leuven, Belgium
- Neurology Department, University Hospitals Leuven, Leuven, Belgium
- Computational Neurology, Experimental Neurobiology Unit (ENU), Department of Biomedical Sciences, University of Antwerp, Antwerp, Belgium
- Biomedical Research Institute, Hasselt University, Diepenbeek, Belgium
| | - Jolien Schaeverbeke
- Laboratory for Cognitive Neurology, Department of Neurosciences & Leuven Brain Institute, Katholieke Universiteit Leuven, Leuven, Belgium
| | - Ahmed Radwan
- Translational MRI, Department of Imaging and Pathology & Leuven Brain Institute, Katholieke Universiteit Leuven, Leuven, Belgium
| | - Manon Grube
- Biosciences Institute, Medical School, Newcastle University, Newcastle-upon-Tyne, UK
- BIFOLD, Technische Universität Berlin, Germany; Department of Psychology, Ashoka University, India
| | - Silvy Gabel
- Laboratory for Cognitive Neurology, Department of Neurosciences & Leuven Brain Institute, Katholieke Universiteit Leuven, Leuven, Belgium
| | - An-Sofie De Weer
- Neurology Department, University Hospitals Leuven, Leuven, Belgium
| | - Eva Dries
- Neurology Department, University Hospitals Leuven, Leuven, Belgium
| | - Karen Van Bouwel
- Neurology Department, University Hospitals Leuven, Leuven, Belgium
| | - Timothy D. Griffiths
- Biosciences Institute, Medical School, Newcastle University, Newcastle-upon-Tyne, UK
| | - Stefan Sunaert
- Translational MRI, Department of Imaging and Pathology & Leuven Brain Institute, Katholieke Universiteit Leuven, Leuven, Belgium
- Radiology Department, University Hospitals Leuven, Leuven, Belgium
| | - Rik Vandenberghe
- Laboratory for Cognitive Neurology, Department of Neurosciences & Leuven Brain Institute, Katholieke Universiteit Leuven, Leuven, Belgium
- Neurology Department, University Hospitals Leuven, Leuven, Belgium
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Isella V, Licciardo D, Ferri F, Crivellaro C, Morzenti S, Appollonio I, Ferrarese C. Reduced phonemic fluency in progressive supranuclear palsy is due to dysfunction of dominant BA6. Front Aging Neurosci 2022; 14:969875. [PMID: 36158541 PMCID: PMC9492952 DOI: 10.3389/fnagi.2022.969875] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/15/2022] [Accepted: 08/24/2022] [Indexed: 11/13/2022] Open
Abstract
Background Reduced phonemic fluency is extremely frequent in progressive supranuclear palsy (PSP), but its neural correlate is yet to be defined. Objective We explored the hypothesis that poor fluency in PSP might be due to neurodegeneration within a dominant frontal circuit known to be involved in speech fluency, including the opercular area, the superior frontal cortex (BA6), and the frontal aslant tract connecting these two regions. Methods We correlated performance on a letter fluency task (F, A, and S, 60 s for each letter) with brain metabolism as measured with Fluoro-deoxy-glucose Positron Emission Tomography, using Statistical Parametric Mapping, in 31 patients with PSP. Results Reduced letter fluency was associated with significant hypometabolism at the level of left BA6. Conclusion Our finding is the first evidence that in PSP, as in other neurogical disorders, poor self-initiated, effortful verbal retrieval appears to be linked to dysfunction of the dominant opercular-aslant-BA6 circuit.
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Affiliation(s)
- Valeria Isella
- Department of Neurology, School of Medicine, University of Milano - Bicocca, Monza, Italy
- Milan Center for Neurosciences, Milan, Italy
| | - Daniele Licciardo
- Milan Center for Neurosciences, Milan, Italy
- Neurology Unit, San Gerardo Hospital, Monza, Italy
| | - Francesca Ferri
- Milan Center for Neurosciences, Milan, Italy
- Neurology Unit, San Gerardo Hospital, Monza, Italy
| | | | | | - Ildebrando Appollonio
- Department of Neurology, School of Medicine, University of Milano - Bicocca, Monza, Italy
- Milan Center for Neurosciences, Milan, Italy
- Neurology Unit, San Gerardo Hospital, Monza, Italy
| | - Carlo Ferrarese
- Department of Neurology, School of Medicine, University of Milano - Bicocca, Monza, Italy
- Milan Center for Neurosciences, Milan, Italy
- Neurology Unit, San Gerardo Hospital, Monza, Italy
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The Cognitive Profile of Atypical Parkinsonism: A Meta-Analysis. Neuropsychol Rev 2022; 33:514-543. [PMID: 35960471 DOI: 10.1007/s11065-022-09551-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/14/2021] [Accepted: 07/04/2022] [Indexed: 10/15/2022]
Abstract
Atypical Parkinsonism (AP) syndromes are characterized by a wide spectrum of non-motor symptoms including prominent attentional and executive deficits. However, the cognitive profile of AP and its differences and similarities with that of Parkinson's Disease (PD) are still a matter of debate. The present meta-analysis aimed at identifying patterns of cognitive impairment in AP by comparing global cognitive functioning, memory, executive functions, visuospatial abilities, language, non-verbal reasoning, and processing speed test performances of patients with AP relative to healthy controls and patients with PD. All investigated cognitive domains showed a substantial impairment in patients with AP compared to healthy controls. When AP syndromes were considered separately, their cognitive functioning was distributed along a continuum from Multiple Systemic Atrophy at one extreme, with the least impaired cognitive profile (similar to that observed in PD) to Progressive Supranuclear Palsy, with the greatest decline in global cognitive and executive functioning (similar to Corticobasal Syndrome). These findings indicate that widespread cognitive impairment could represent an important clinical indicator to distinguish AP from other movement disorders.
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Functional Imaging for Neurodegenerative Diseases. Presse Med 2022; 51:104121. [PMID: 35490910 DOI: 10.1016/j.lpm.2022.104121] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/14/2021] [Revised: 03/13/2022] [Accepted: 04/11/2022] [Indexed: 12/16/2022] Open
Abstract
Diagnosis and monitoring of neurodegenerative diseases has changed profoundly over the past twenty years. Biomarkers are now included in most diagnostic procedures as well as in clinical trials. Neuroimaging biomarkers provide access to brain structure and function over the course of neurodegenerative diseases. They have brought new insights into a wide range of neurodegenerative diseases and have made it possible to describe some of the imaging challenges in clinical populations. MRI mainly explores brain structure while molecular imaging, functional MRI and electro- and magnetoencephalography examine brain function. In this paper, we describe and analyse the current and potential contribution of MRI and molecular imaging in the field of neurodegenerative diseases.
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Keator LM, Yourganov G, Faria AV, Hillis AE, Tippett DC. Application of the dual stream model to neurodegenerative disease: Evidence from a multivariate classification tool in primary progressive aphasia. APHASIOLOGY 2022; 36:618-647. [PMID: 35493273 PMCID: PMC9053317 DOI: 10.1080/02687038.2021.1897079] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/15/2020] [Accepted: 02/19/2021] [Indexed: 05/20/2023]
Abstract
BACKGROUND A clinical diagnosis of primary progressive aphasia relies on behavioral characteristics and patterns of atrophy to determine a variant: logopenic; nonfluent/agrammatic; or semantic. The dual stream model (Hickok & Poeppel, 2000; 2004; 2007; 2015) is a contemporary paradigm that has been applied widely to understand brain-behavior relationships; however, applications to neurodegenerative diseases like primary progressive aphasia are limited. AIMS The primary aim of this study is to determine if the dual stream model can be applied to a neurodegenerative disease, such as primary progressive aphasia, using both behavioral and neuroimaging data. METHODS & PROCEDURES We analyzed behavioral and neuroimaging data to apply a multivariate classification tool (support vector machines) to determine if the dual stream model extends to primary progressive aphasia. Sixty-four individuals with primary progressive aphasia were enrolled (26 logopenic variant, 20 nonfluent/agrammatic variant, and 18 semantic variant) and administered four behavioral tasks to assess three linguistic domains (naming, repetition, and semantic knowledge). We used regions of interest from the dual stream model and calculated the cortical volume for gray matter regions and white matter structural volumes and fractional anisotropy. We applied a multivariate classification tool (support vector machines) to distinguish variants based on behavioral performance and patterns of atrophy. OUTCOMES & RESULTS Behavioral performance discriminates logopenic from semantic variant and nonfluent/agrammatic from semantic variant. Cortical volume distinguishes all three variants. White matter structural volumes and fractional anisotropy primarily distinguish nonfluent/agrammatic from semantic variant. Regions of interest that contribute to each classification in cortical and white matter analyses demonstrate alignment of logopenic and nonfluent/agrammatic variants to the dorsal stream, while the semantic variant aligns with the ventral stream. CONCLUSIONS A novel implementation of an automated multivariate classification suggests that the dual stream model can be extended to primary progressive aphasia. Variants are distinguished by behavioral and neuroanatomical patterns and align to the dorsal and ventral streams of the dual stream model.
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Affiliation(s)
- Lynsey M. Keator
- Department of Neurology, Johns Hopkins University School of Medicine, Phipps 446, 600 N. Wolfe Street, Baltimore, MD 21287
| | - Grigori Yourganov
- Department of Psychology, McCausland Center for Brain Imaging, 6 Medical Park Road, University of South Carolina, Columbia, South Carolina 29201
| | - Andreia V. Faria
- The Russell H. Morgan Department of Radiology and Radiological Science, 1800 Orleans Street, Johns Hopkins University, Baltimore, MD 21287
| | - Argye E. Hillis
- Department of Neurology, Johns Hopkins University School of Medicine, Phipps 446, 600 N. Wolfe Street, Baltimore, MD 21287
- Department of Physical Medicine and Rehabilitation, 600 N. Wolfe Street, Johns Hopkins University School of Medicine, Baltimore, MD 21287
- Department of Cognitive Science, Krieger School of Arts and Sciences, 3400 N. Charles Street, Johns Hopkins University, Baltimore, MD 21218
| | - Donna C. Tippett
- Department of Neurology, Johns Hopkins University School of Medicine, Phipps 446, 600 N. Wolfe Street, Baltimore, MD 21287
- Department of Physical Medicine and Rehabilitation, 600 N. Wolfe Street, Johns Hopkins University School of Medicine, Baltimore, MD 21287
- Department of Otolaryngology—Head and Neck Surgery, 601 N. Caroline Street, 6 floor, Johns Hopkins University School of Medicine, Baltimore, MD 21287
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Tippett DC, Keser Z. Clinical and neuroimaging characteristics of primary progressive aphasia. HANDBOOK OF CLINICAL NEUROLOGY 2022; 185:81-97. [PMID: 35078612 PMCID: PMC9951770 DOI: 10.1016/b978-0-12-823384-9.00016-5] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/31/2023]
Abstract
The chapter covers the clinical syndrome of a primary progressive aphasia (PPA), the demographics of this rare neurodegenerative disease, defining clinical and neuroanatomic characteristics of each PPA variant, disease progression, and behavioral features. The chapter begins with a brief introduction that includes references to seminal papers that defined this clinical syndrome and its three variants. The classic PPA subtypes discussed in the chapter are semantic variant PPA (svPPA), nonfluent/agrammatic PPA (nfaPPA), and logopenic variant PPA (lvPPA). The key language and cognitive characteristics, and language tasks that can elicit these language impairments, are detailed. Overlap in the clinical profiles of the PPA variants, which make differential diagnosis challenging, are explained. Disease progression is described, revealing that the PPA variants become more similar over time. Although PPA is language-predominant dementia, there are behavioral manifestations, particularly in svPPA. Changes in behavior in this variant are addressed as well as behavioral changes in nfaPPA and lvPPA that are less well recognized. The patterns of atrophy in the left temporal, parietal, and/or frontal cortices unique to each PPA variant are described. The underlying neuropathologies of the PPA variants are discussed, specifically tauopathies and non-tauopathies associated with svPPA and nfaPPA and Alzheimer's disease pathology in lvPPA.
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Affiliation(s)
- Donna C. Tippett
- Departments of Neurology, Otolaryngology—Head and Neck Surgery, and Physical Medicine and Rehabilitation, Johns Hopkins University School of Medicine, Baltimore, Maryland, United States
| | - Zafer Keser
- Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, Maryland, United States
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Parkinson's Disease Rating Scale Using Synchronization Analysis of Gait Dynamics. BIOMED RESEARCH INTERNATIONAL 2021; 2021:5651519. [PMID: 34485517 PMCID: PMC8413035 DOI: 10.1155/2021/5651519] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 06/23/2021] [Accepted: 08/10/2021] [Indexed: 11/29/2022]
Abstract
Analysis of gait dynamics is a noninvasive and totally painless test, and it can be an ideal method for the diagnosis of neurodegenerative diseases. In this study, based on the strength of synchronization between dynamics of strides, we have suggested a rating scale method for Parkinson's disease (PD). Methods. The sample included 15 persons with PD (age: 66.8 ± 10.9 years) and 16 healthy persons (age: 39.3 ± 18.5 years) which were recruited from the Neurology Outpatient Clinic at Massachusetts General Hospital and were instructed to walk a 77 m long, straight hallway. The time interval of strides and subphases of strides were measured. Using the Hilbert transformation method, we obtained the data phase and used mean absolute error (MAE) to calculate the synchronization strength of the data phase. Results. In order to check the accuracy of our method, we measured the correlation between our numerical results (MAE) and values of the Hoehn-Yahr scale. Spearman's rank correlation coefficients (r) and the P values were calculated. MAE of left and right stride intervals (LRSI) significantly correlates with the Hoehn-Yahr scale for the subjects with PD (with r = 0.60 and P = 0.025 < 0.05). Conclusion. We have revealed that the synchronization weakness of LRSI shows the severity of PD. This method seems to be well suited as a rating scale for people with PD.
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Villa C, Lavitrano M, Salvatore E, Combi R. Molecular and Imaging Biomarkers in Alzheimer's Disease: A Focus on Recent Insights. J Pers Med 2020; 10:jpm10030061. [PMID: 32664352 PMCID: PMC7565667 DOI: 10.3390/jpm10030061] [Citation(s) in RCA: 21] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/25/2020] [Revised: 06/28/2020] [Accepted: 07/07/2020] [Indexed: 12/15/2022] Open
Abstract
Alzheimer’s disease (AD) is the most common neurodegenerative disease among the elderly, affecting millions of people worldwide and clinically characterized by a progressive and irreversible cognitive decline. The rapid increase in the incidence of AD highlights the need for an easy, efficient and accurate diagnosis of the disease in its initial stages in order to halt or delay the progression. The currently used diagnostic methods rely on measures of amyloid-β (Aβ), phosphorylated (p-tau) and total tau (t-tau) protein levels in the cerebrospinal fluid (CSF) aided by advanced neuroimaging techniques like positron emission tomography (PET) and magnetic resonance imaging (MRI). However, the invasiveness of these procedures and the high cost restrict their utilization. Hence, biomarkers from biological fluids obtained using non-invasive methods and novel neuroimaging approaches provide an attractive alternative for the early diagnosis of AD. Such biomarkers may also be helpful for better understanding of the molecular mechanisms underlying the disease, allowing differential diagnosis or at least prolonging the pre-symptomatic stage in patients suffering from AD. Herein, we discuss the advantages and limits of the conventional biomarkers as well as recent promising candidates from alternative body fluids and new imaging techniques.
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Affiliation(s)
- Chiara Villa
- School of Medicine and Surgery, University of Milano-Bicocca, 20900 Monza, Italy
- Correspondence: (C.V.); (R.C.)
| | - Marialuisa Lavitrano
- School of Medicine and Surgery, University of Milano-Bicocca, 20900 Monza, Italy
- Institute for the Experimental Endocrinology and Oncology, National Research Council (IEOS-CNR), 80131 Naples, Italy;
| | - Elena Salvatore
- Department of Neurosciences and Reproductive and Odontostomatological Sciences, Federico II University, 80131 Naples, Italy;
| | - Romina Combi
- School of Medicine and Surgery, University of Milano-Bicocca, 20900 Monza, Italy
- Correspondence: (C.V.); (R.C.)
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Abstract
Primary progressive aphasia (PPA) is classified into three variants, logopenic variant PPA (lvPPA), nonfluent agrammatic PPA (nfaPPA), and semantic variant PPA (svPPA), based on clinical (syndromic) characteristics with support from neuroimaging and/or underlying neuropathology. Classification of PPA variants provides information valuable to disease management. International consensus criteria are widely employed to identify PPA subtypes; however, classification is complex, and some individuals do not fit neatly into the subtyping scheme. In this review, diagnostic challenges and their implications are discussed, possible explanations for these challenges are explored, and approaches to address PPA classification are considered.
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Affiliation(s)
- Donna C. Tippett
- Departments of Neurology, Otolaryngology - Head and Neck Surgery, and Department of Physical Medicine and Rehabilitation, Johns Hopkins University School of Medicine, Baltimore, Maryland, 21287, USA
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Lambertsen KL, Soares CB, Gaist D, Nielsen HH. Neurofilaments: The C-Reactive Protein of Neurology. Brain Sci 2020; 10:brainsci10010056. [PMID: 31963750 PMCID: PMC7016784 DOI: 10.3390/brainsci10010056] [Citation(s) in RCA: 42] [Impact Index Per Article: 10.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/21/2019] [Revised: 01/14/2020] [Accepted: 01/16/2020] [Indexed: 12/12/2022] Open
Abstract
Neurofilaments (NFs) are quickly becoming the biomarkers of choice in the field of neurology, suggesting their use as an unspecific screening marker, much like the use of elevated plasma C-reactive protein (CRP) in other fields. With sensitive techniques being readily available, evidence is growing regarding the diagnostic and prognostic value of NFs in many neurological disorders. Here, we review the latest literature on the structure and function of NFs and report the strengths and pitfalls of NFs as markers of neurodegeneration in the context of neurological diseases of the central and peripheral nervous systems.
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Affiliation(s)
- Kate L. Lambertsen
- Department of Neurology, Odense University Hospital, J.B. Winsloewsvej 4, 5000 Odense C, Denmark; (K.L.L.); (C.B.S.); (D.G.)
- Department of Neurobiology Research, Institute of Molecular Medicine, University of Southern Denmark, J.B. Winsloewsvej 21, st, 5000 Odense C, Denmark
- BRIDGE—Brain Research—Inter Disciplinary Guided Excellence, Department of Clinical Research, University of Southern Denmark, J.B. Winsloewsvej 19, 3. sal, 5000 Odense C, Denmark
| | - Catarina B. Soares
- Department of Neurology, Odense University Hospital, J.B. Winsloewsvej 4, 5000 Odense C, Denmark; (K.L.L.); (C.B.S.); (D.G.)
- Department of Neurobiology Research, Institute of Molecular Medicine, University of Southern Denmark, J.B. Winsloewsvej 21, st, 5000 Odense C, Denmark
| | - David Gaist
- Department of Neurology, Odense University Hospital, J.B. Winsloewsvej 4, 5000 Odense C, Denmark; (K.L.L.); (C.B.S.); (D.G.)
- BRIDGE—Brain Research—Inter Disciplinary Guided Excellence, Department of Clinical Research, University of Southern Denmark, J.B. Winsloewsvej 19, 3. sal, 5000 Odense C, Denmark
- Department of Clinical Research, Neurology Research Unit, Faculty of Health Sciences, University of Southern Denmark, Campusvej 55, 5230 Odense, Denmark
| | - Helle H. Nielsen
- Department of Neurology, Odense University Hospital, J.B. Winsloewsvej 4, 5000 Odense C, Denmark; (K.L.L.); (C.B.S.); (D.G.)
- Department of Neurobiology Research, Institute of Molecular Medicine, University of Southern Denmark, J.B. Winsloewsvej 21, st, 5000 Odense C, Denmark
- BRIDGE—Brain Research—Inter Disciplinary Guided Excellence, Department of Clinical Research, University of Southern Denmark, J.B. Winsloewsvej 19, 3. sal, 5000 Odense C, Denmark
- Department of Clinical Research, Neurology Research Unit, Faculty of Health Sciences, University of Southern Denmark, Campusvej 55, 5230 Odense, Denmark
- Correspondence:
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Middle longitudinal fascicle is associated with semantic processing deficits in primary progressive aphasia. NEUROIMAGE-CLINICAL 2019; 25:102115. [PMID: 31865024 PMCID: PMC6931233 DOI: 10.1016/j.nicl.2019.102115] [Citation(s) in RCA: 17] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 03/22/2018] [Revised: 11/26/2019] [Accepted: 12/03/2019] [Indexed: 02/05/2023]
Abstract
The middle longitudinal fascicle (MdLF) is a recently delineated association cortico-cortical fiber pathway in humans, connecting superior temporal gyrus and temporal pole principally with the angular gyrus, and is likely to be involved in language processing. However, the MdLF has not been studied in language disorders as primary progressive aphasia (PPA). We hypothesized that the MdLF will exhibit evidence of neurodegeneration in PPA patients. In this study, 20 PPA patients and 25 healthy controls were recruited in the Primary Progressive Aphasia program in the Massachusetts General Hospital Frontotemporal Disorders Unit. We used diffusion tensor imaging (DTI) tractography to reconstruct the MdLF and extract tract-specific DTI metrics (fractional anisotropy (FA), radial diffusivity (RD), mean diffusivity (MD) and axial diffusivity (AD)) to assess white matter changes in PPA and their relationship with language impairments. We found severe WM damage in the MdLF in PPA patients, which was principally pronounced in the left hemisphere. Moreover, the WM alterations in the MdLF in the dominant hemisphere were significantly correlated with impairments in word comprehension and naming, but not with articulation and fluency. In addition, asymmetry analysis revealed that the DTI metrics of controls were similar for each hemisphere, whereas PPA patients had clear laterality differences in MD, AD and RD. These findings add new insight into the localization and severity of white matter fiber bundle neurodegeneration in PPA, and provide evidence that degeneration of the MdLF contribute to impairment in semantic processing and lexical retrieval in PPA. Integrity loss of middle longitudinal fascicle (MdLF) in PPA. MdLF degeneration correlated with impairments in word comprehension and retrieval. MdLF not significantly correlated with articulation or fluency. Connectivity model: gray/white matter areas involved in human semantic processing.
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Spotorno N, Hall S, Irwin DJ, Rumetshofer T, Acosta-Cabronero J, Deik AF, Spindler MA, Lee EB, Trojanowski JQ, van Westen D, Nilsson M, Grossman M, Nestor PJ, McMillan CT, Hansson O. Diffusion Tensor MRI to Distinguish Progressive Supranuclear Palsy from α-Synucleinopathies. Radiology 2019; 293:646-653. [PMID: 31617796 PMCID: PMC6889922 DOI: 10.1148/radiol.2019190406] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/03/2019] [Revised: 07/21/2019] [Accepted: 08/21/2019] [Indexed: 01/25/2023]
Abstract
Background The differential diagnosis of progressive supranuclear palsy (PSP) and Lewy body disorders, which include Parkinson disease and dementia with Lewy bodies, is often challenging due to the overlapping symptoms. Purpose To develop a diagnostic tool based on diffusion tensor imaging (DTI) to distinguish between PSP and Lewy body disorders at the individual-subject level. Materials and Methods In this retrospective study, skeletonized DTI metrics were extracted from two independent data sets: the discovery cohort from the Swedish BioFINDER study and the validation cohort from the Penn Frontotemporal Degeneration Center (data collected between 2010 and 2018). Based on previous neuroimaging studies and neuropathologic evidence, a combination of regions hypothesized to be sensitive to pathologic features of PSP were identified (ie, the superior cerebellar peduncle and frontal white matter) and fractional anisotropy (FA) was used to compute an FA score for each individual. Classification performances were assessed by using logistic regression and receiver operating characteristic analysis. Results In the discovery cohort, 16 patients with PSP (mean age ± standard deviation, 73 years ± 5; eight women, eight men), 34 patients with Lewy body disorders (mean age, 71 years ± 6; 14 women, 20 men), and 44 healthy control participants (mean age, 66 years ± 8; 26 women, 18 men) were evaluated. The FA score distinguished between clinical PSP and Lewy body disorders with an area under the curve of 0.97 ± 0.04, a specificity of 91% (31 of 34), and a sensitivity of 94% (15 of 16). In the validation cohort, 34 patients with PSP (69 years ± 7; 22 women, 12 men), 25 patients with Lewy body disorders (70 years ± 7; nine women, 16 men), and 32 healthy control participants (64 years ± 7; 22 women, 10 men) were evaluated. The accuracy of the FA score was confirmed (area under the curve, 0.96 ± 0.04; specificity, 96% [24 of 25]; and sensitivity, 85% [29 of 34]). Conclusion These cross-validated findings lay the foundation for a clinical test to distinguish progressive supranuclear palsy from Lewy body disorders. © RSNA, 2019 Online supplemental material is available for this article. See also the editorial by Shah in this issue.
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Affiliation(s)
- Nicola Spotorno
- From the Clinical Memory Research Unit, Department of Clinical
Sciences, Malmö, Lund University, Sölvegatan 19, 22100 Lund, Sweden
(N.S., S.H., D.v.W., O.H.); Penn Frontotemporal Degeneration Center, Department
of Neurology, Perelman School of Medicine, University of Pennsylvania,
Philadelphia, Pa (N.S., D.J.I., M.G., C.T.M.); Memory Clinic, Skåne
University Hospital, Malmö, Sweden (S.H., O.H.); Center for
Neurodegenerative Disease Research, Perelman School of Medicine, University of
Pennsylvania, Philadelphia, Pa (D.J.I., E.B.L., J.Q.T.); Department of
Diagnostic Radiology, Lund University, Lund, Sweden (T.R., D.v.W., M.N.);
Wellcome Centre for Human Neuroimaging, UCL Queen Square Institute of Neurology,
University College London, London, England (J.A.C.); Parkinson’s Disease
and Movement Disorders Center, Department of Neurology, Perelman School of
Medicine, University of Pennsylvania, Philadelphia, Pa (A.F.D., M.A.S.);
Alzheimer’s Disease Core Center, Department of Pathology and Laboratory
Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia,
Pa (E.B.L., J.Q.T.); and Queensland Brain Institute, University of Queensland
and Mater Misericordiae, Brisbane, Queensland, Australia (P.J.N.)
| | - Sara Hall
- From the Clinical Memory Research Unit, Department of Clinical
Sciences, Malmö, Lund University, Sölvegatan 19, 22100 Lund, Sweden
(N.S., S.H., D.v.W., O.H.); Penn Frontotemporal Degeneration Center, Department
of Neurology, Perelman School of Medicine, University of Pennsylvania,
Philadelphia, Pa (N.S., D.J.I., M.G., C.T.M.); Memory Clinic, Skåne
University Hospital, Malmö, Sweden (S.H., O.H.); Center for
Neurodegenerative Disease Research, Perelman School of Medicine, University of
Pennsylvania, Philadelphia, Pa (D.J.I., E.B.L., J.Q.T.); Department of
Diagnostic Radiology, Lund University, Lund, Sweden (T.R., D.v.W., M.N.);
Wellcome Centre for Human Neuroimaging, UCL Queen Square Institute of Neurology,
University College London, London, England (J.A.C.); Parkinson’s Disease
and Movement Disorders Center, Department of Neurology, Perelman School of
Medicine, University of Pennsylvania, Philadelphia, Pa (A.F.D., M.A.S.);
Alzheimer’s Disease Core Center, Department of Pathology and Laboratory
Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia,
Pa (E.B.L., J.Q.T.); and Queensland Brain Institute, University of Queensland
and Mater Misericordiae, Brisbane, Queensland, Australia (P.J.N.)
| | - David J. Irwin
- From the Clinical Memory Research Unit, Department of Clinical
Sciences, Malmö, Lund University, Sölvegatan 19, 22100 Lund, Sweden
(N.S., S.H., D.v.W., O.H.); Penn Frontotemporal Degeneration Center, Department
of Neurology, Perelman School of Medicine, University of Pennsylvania,
Philadelphia, Pa (N.S., D.J.I., M.G., C.T.M.); Memory Clinic, Skåne
University Hospital, Malmö, Sweden (S.H., O.H.); Center for
Neurodegenerative Disease Research, Perelman School of Medicine, University of
Pennsylvania, Philadelphia, Pa (D.J.I., E.B.L., J.Q.T.); Department of
Diagnostic Radiology, Lund University, Lund, Sweden (T.R., D.v.W., M.N.);
Wellcome Centre for Human Neuroimaging, UCL Queen Square Institute of Neurology,
University College London, London, England (J.A.C.); Parkinson’s Disease
and Movement Disorders Center, Department of Neurology, Perelman School of
Medicine, University of Pennsylvania, Philadelphia, Pa (A.F.D., M.A.S.);
Alzheimer’s Disease Core Center, Department of Pathology and Laboratory
Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia,
Pa (E.B.L., J.Q.T.); and Queensland Brain Institute, University of Queensland
and Mater Misericordiae, Brisbane, Queensland, Australia (P.J.N.)
| | - Theodor Rumetshofer
- From the Clinical Memory Research Unit, Department of Clinical
Sciences, Malmö, Lund University, Sölvegatan 19, 22100 Lund, Sweden
(N.S., S.H., D.v.W., O.H.); Penn Frontotemporal Degeneration Center, Department
of Neurology, Perelman School of Medicine, University of Pennsylvania,
Philadelphia, Pa (N.S., D.J.I., M.G., C.T.M.); Memory Clinic, Skåne
University Hospital, Malmö, Sweden (S.H., O.H.); Center for
Neurodegenerative Disease Research, Perelman School of Medicine, University of
Pennsylvania, Philadelphia, Pa (D.J.I., E.B.L., J.Q.T.); Department of
Diagnostic Radiology, Lund University, Lund, Sweden (T.R., D.v.W., M.N.);
Wellcome Centre for Human Neuroimaging, UCL Queen Square Institute of Neurology,
University College London, London, England (J.A.C.); Parkinson’s Disease
and Movement Disorders Center, Department of Neurology, Perelman School of
Medicine, University of Pennsylvania, Philadelphia, Pa (A.F.D., M.A.S.);
Alzheimer’s Disease Core Center, Department of Pathology and Laboratory
Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia,
Pa (E.B.L., J.Q.T.); and Queensland Brain Institute, University of Queensland
and Mater Misericordiae, Brisbane, Queensland, Australia (P.J.N.)
| | - Julio Acosta-Cabronero
- From the Clinical Memory Research Unit, Department of Clinical
Sciences, Malmö, Lund University, Sölvegatan 19, 22100 Lund, Sweden
(N.S., S.H., D.v.W., O.H.); Penn Frontotemporal Degeneration Center, Department
of Neurology, Perelman School of Medicine, University of Pennsylvania,
Philadelphia, Pa (N.S., D.J.I., M.G., C.T.M.); Memory Clinic, Skåne
University Hospital, Malmö, Sweden (S.H., O.H.); Center for
Neurodegenerative Disease Research, Perelman School of Medicine, University of
Pennsylvania, Philadelphia, Pa (D.J.I., E.B.L., J.Q.T.); Department of
Diagnostic Radiology, Lund University, Lund, Sweden (T.R., D.v.W., M.N.);
Wellcome Centre for Human Neuroimaging, UCL Queen Square Institute of Neurology,
University College London, London, England (J.A.C.); Parkinson’s Disease
and Movement Disorders Center, Department of Neurology, Perelman School of
Medicine, University of Pennsylvania, Philadelphia, Pa (A.F.D., M.A.S.);
Alzheimer’s Disease Core Center, Department of Pathology and Laboratory
Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia,
Pa (E.B.L., J.Q.T.); and Queensland Brain Institute, University of Queensland
and Mater Misericordiae, Brisbane, Queensland, Australia (P.J.N.)
| | - Andres F. Deik
- From the Clinical Memory Research Unit, Department of Clinical
Sciences, Malmö, Lund University, Sölvegatan 19, 22100 Lund, Sweden
(N.S., S.H., D.v.W., O.H.); Penn Frontotemporal Degeneration Center, Department
of Neurology, Perelman School of Medicine, University of Pennsylvania,
Philadelphia, Pa (N.S., D.J.I., M.G., C.T.M.); Memory Clinic, Skåne
University Hospital, Malmö, Sweden (S.H., O.H.); Center for
Neurodegenerative Disease Research, Perelman School of Medicine, University of
Pennsylvania, Philadelphia, Pa (D.J.I., E.B.L., J.Q.T.); Department of
Diagnostic Radiology, Lund University, Lund, Sweden (T.R., D.v.W., M.N.);
Wellcome Centre for Human Neuroimaging, UCL Queen Square Institute of Neurology,
University College London, London, England (J.A.C.); Parkinson’s Disease
and Movement Disorders Center, Department of Neurology, Perelman School of
Medicine, University of Pennsylvania, Philadelphia, Pa (A.F.D., M.A.S.);
Alzheimer’s Disease Core Center, Department of Pathology and Laboratory
Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia,
Pa (E.B.L., J.Q.T.); and Queensland Brain Institute, University of Queensland
and Mater Misericordiae, Brisbane, Queensland, Australia (P.J.N.)
| | - Meredith A. Spindler
- From the Clinical Memory Research Unit, Department of Clinical
Sciences, Malmö, Lund University, Sölvegatan 19, 22100 Lund, Sweden
(N.S., S.H., D.v.W., O.H.); Penn Frontotemporal Degeneration Center, Department
of Neurology, Perelman School of Medicine, University of Pennsylvania,
Philadelphia, Pa (N.S., D.J.I., M.G., C.T.M.); Memory Clinic, Skåne
University Hospital, Malmö, Sweden (S.H., O.H.); Center for
Neurodegenerative Disease Research, Perelman School of Medicine, University of
Pennsylvania, Philadelphia, Pa (D.J.I., E.B.L., J.Q.T.); Department of
Diagnostic Radiology, Lund University, Lund, Sweden (T.R., D.v.W., M.N.);
Wellcome Centre for Human Neuroimaging, UCL Queen Square Institute of Neurology,
University College London, London, England (J.A.C.); Parkinson’s Disease
and Movement Disorders Center, Department of Neurology, Perelman School of
Medicine, University of Pennsylvania, Philadelphia, Pa (A.F.D., M.A.S.);
Alzheimer’s Disease Core Center, Department of Pathology and Laboratory
Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia,
Pa (E.B.L., J.Q.T.); and Queensland Brain Institute, University of Queensland
and Mater Misericordiae, Brisbane, Queensland, Australia (P.J.N.)
| | - Edward B. Lee
- From the Clinical Memory Research Unit, Department of Clinical
Sciences, Malmö, Lund University, Sölvegatan 19, 22100 Lund, Sweden
(N.S., S.H., D.v.W., O.H.); Penn Frontotemporal Degeneration Center, Department
of Neurology, Perelman School of Medicine, University of Pennsylvania,
Philadelphia, Pa (N.S., D.J.I., M.G., C.T.M.); Memory Clinic, Skåne
University Hospital, Malmö, Sweden (S.H., O.H.); Center for
Neurodegenerative Disease Research, Perelman School of Medicine, University of
Pennsylvania, Philadelphia, Pa (D.J.I., E.B.L., J.Q.T.); Department of
Diagnostic Radiology, Lund University, Lund, Sweden (T.R., D.v.W., M.N.);
Wellcome Centre for Human Neuroimaging, UCL Queen Square Institute of Neurology,
University College London, London, England (J.A.C.); Parkinson’s Disease
and Movement Disorders Center, Department of Neurology, Perelman School of
Medicine, University of Pennsylvania, Philadelphia, Pa (A.F.D., M.A.S.);
Alzheimer’s Disease Core Center, Department of Pathology and Laboratory
Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia,
Pa (E.B.L., J.Q.T.); and Queensland Brain Institute, University of Queensland
and Mater Misericordiae, Brisbane, Queensland, Australia (P.J.N.)
| | - John Q. Trojanowski
- From the Clinical Memory Research Unit, Department of Clinical
Sciences, Malmö, Lund University, Sölvegatan 19, 22100 Lund, Sweden
(N.S., S.H., D.v.W., O.H.); Penn Frontotemporal Degeneration Center, Department
of Neurology, Perelman School of Medicine, University of Pennsylvania,
Philadelphia, Pa (N.S., D.J.I., M.G., C.T.M.); Memory Clinic, Skåne
University Hospital, Malmö, Sweden (S.H., O.H.); Center for
Neurodegenerative Disease Research, Perelman School of Medicine, University of
Pennsylvania, Philadelphia, Pa (D.J.I., E.B.L., J.Q.T.); Department of
Diagnostic Radiology, Lund University, Lund, Sweden (T.R., D.v.W., M.N.);
Wellcome Centre for Human Neuroimaging, UCL Queen Square Institute of Neurology,
University College London, London, England (J.A.C.); Parkinson’s Disease
and Movement Disorders Center, Department of Neurology, Perelman School of
Medicine, University of Pennsylvania, Philadelphia, Pa (A.F.D., M.A.S.);
Alzheimer’s Disease Core Center, Department of Pathology and Laboratory
Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia,
Pa (E.B.L., J.Q.T.); and Queensland Brain Institute, University of Queensland
and Mater Misericordiae, Brisbane, Queensland, Australia (P.J.N.)
| | - Danielle van Westen
- From the Clinical Memory Research Unit, Department of Clinical
Sciences, Malmö, Lund University, Sölvegatan 19, 22100 Lund, Sweden
(N.S., S.H., D.v.W., O.H.); Penn Frontotemporal Degeneration Center, Department
of Neurology, Perelman School of Medicine, University of Pennsylvania,
Philadelphia, Pa (N.S., D.J.I., M.G., C.T.M.); Memory Clinic, Skåne
University Hospital, Malmö, Sweden (S.H., O.H.); Center for
Neurodegenerative Disease Research, Perelman School of Medicine, University of
Pennsylvania, Philadelphia, Pa (D.J.I., E.B.L., J.Q.T.); Department of
Diagnostic Radiology, Lund University, Lund, Sweden (T.R., D.v.W., M.N.);
Wellcome Centre for Human Neuroimaging, UCL Queen Square Institute of Neurology,
University College London, London, England (J.A.C.); Parkinson’s Disease
and Movement Disorders Center, Department of Neurology, Perelman School of
Medicine, University of Pennsylvania, Philadelphia, Pa (A.F.D., M.A.S.);
Alzheimer’s Disease Core Center, Department of Pathology and Laboratory
Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia,
Pa (E.B.L., J.Q.T.); and Queensland Brain Institute, University of Queensland
and Mater Misericordiae, Brisbane, Queensland, Australia (P.J.N.)
| | - Markus Nilsson
- From the Clinical Memory Research Unit, Department of Clinical
Sciences, Malmö, Lund University, Sölvegatan 19, 22100 Lund, Sweden
(N.S., S.H., D.v.W., O.H.); Penn Frontotemporal Degeneration Center, Department
of Neurology, Perelman School of Medicine, University of Pennsylvania,
Philadelphia, Pa (N.S., D.J.I., M.G., C.T.M.); Memory Clinic, Skåne
University Hospital, Malmö, Sweden (S.H., O.H.); Center for
Neurodegenerative Disease Research, Perelman School of Medicine, University of
Pennsylvania, Philadelphia, Pa (D.J.I., E.B.L., J.Q.T.); Department of
Diagnostic Radiology, Lund University, Lund, Sweden (T.R., D.v.W., M.N.);
Wellcome Centre for Human Neuroimaging, UCL Queen Square Institute of Neurology,
University College London, London, England (J.A.C.); Parkinson’s Disease
and Movement Disorders Center, Department of Neurology, Perelman School of
Medicine, University of Pennsylvania, Philadelphia, Pa (A.F.D., M.A.S.);
Alzheimer’s Disease Core Center, Department of Pathology and Laboratory
Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia,
Pa (E.B.L., J.Q.T.); and Queensland Brain Institute, University of Queensland
and Mater Misericordiae, Brisbane, Queensland, Australia (P.J.N.)
| | - Murray Grossman
- From the Clinical Memory Research Unit, Department of Clinical
Sciences, Malmö, Lund University, Sölvegatan 19, 22100 Lund, Sweden
(N.S., S.H., D.v.W., O.H.); Penn Frontotemporal Degeneration Center, Department
of Neurology, Perelman School of Medicine, University of Pennsylvania,
Philadelphia, Pa (N.S., D.J.I., M.G., C.T.M.); Memory Clinic, Skåne
University Hospital, Malmö, Sweden (S.H., O.H.); Center for
Neurodegenerative Disease Research, Perelman School of Medicine, University of
Pennsylvania, Philadelphia, Pa (D.J.I., E.B.L., J.Q.T.); Department of
Diagnostic Radiology, Lund University, Lund, Sweden (T.R., D.v.W., M.N.);
Wellcome Centre for Human Neuroimaging, UCL Queen Square Institute of Neurology,
University College London, London, England (J.A.C.); Parkinson’s Disease
and Movement Disorders Center, Department of Neurology, Perelman School of
Medicine, University of Pennsylvania, Philadelphia, Pa (A.F.D., M.A.S.);
Alzheimer’s Disease Core Center, Department of Pathology and Laboratory
Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia,
Pa (E.B.L., J.Q.T.); and Queensland Brain Institute, University of Queensland
and Mater Misericordiae, Brisbane, Queensland, Australia (P.J.N.)
| | - Peter J. Nestor
- From the Clinical Memory Research Unit, Department of Clinical
Sciences, Malmö, Lund University, Sölvegatan 19, 22100 Lund, Sweden
(N.S., S.H., D.v.W., O.H.); Penn Frontotemporal Degeneration Center, Department
of Neurology, Perelman School of Medicine, University of Pennsylvania,
Philadelphia, Pa (N.S., D.J.I., M.G., C.T.M.); Memory Clinic, Skåne
University Hospital, Malmö, Sweden (S.H., O.H.); Center for
Neurodegenerative Disease Research, Perelman School of Medicine, University of
Pennsylvania, Philadelphia, Pa (D.J.I., E.B.L., J.Q.T.); Department of
Diagnostic Radiology, Lund University, Lund, Sweden (T.R., D.v.W., M.N.);
Wellcome Centre for Human Neuroimaging, UCL Queen Square Institute of Neurology,
University College London, London, England (J.A.C.); Parkinson’s Disease
and Movement Disorders Center, Department of Neurology, Perelman School of
Medicine, University of Pennsylvania, Philadelphia, Pa (A.F.D., M.A.S.);
Alzheimer’s Disease Core Center, Department of Pathology and Laboratory
Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia,
Pa (E.B.L., J.Q.T.); and Queensland Brain Institute, University of Queensland
and Mater Misericordiae, Brisbane, Queensland, Australia (P.J.N.)
| | - Corey T. McMillan
- From the Clinical Memory Research Unit, Department of Clinical
Sciences, Malmö, Lund University, Sölvegatan 19, 22100 Lund, Sweden
(N.S., S.H., D.v.W., O.H.); Penn Frontotemporal Degeneration Center, Department
of Neurology, Perelman School of Medicine, University of Pennsylvania,
Philadelphia, Pa (N.S., D.J.I., M.G., C.T.M.); Memory Clinic, Skåne
University Hospital, Malmö, Sweden (S.H., O.H.); Center for
Neurodegenerative Disease Research, Perelman School of Medicine, University of
Pennsylvania, Philadelphia, Pa (D.J.I., E.B.L., J.Q.T.); Department of
Diagnostic Radiology, Lund University, Lund, Sweden (T.R., D.v.W., M.N.);
Wellcome Centre for Human Neuroimaging, UCL Queen Square Institute of Neurology,
University College London, London, England (J.A.C.); Parkinson’s Disease
and Movement Disorders Center, Department of Neurology, Perelman School of
Medicine, University of Pennsylvania, Philadelphia, Pa (A.F.D., M.A.S.);
Alzheimer’s Disease Core Center, Department of Pathology and Laboratory
Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia,
Pa (E.B.L., J.Q.T.); and Queensland Brain Institute, University of Queensland
and Mater Misericordiae, Brisbane, Queensland, Australia (P.J.N.)
| | - Oskar Hansson
- From the Clinical Memory Research Unit, Department of Clinical
Sciences, Malmö, Lund University, Sölvegatan 19, 22100 Lund, Sweden
(N.S., S.H., D.v.W., O.H.); Penn Frontotemporal Degeneration Center, Department
of Neurology, Perelman School of Medicine, University of Pennsylvania,
Philadelphia, Pa (N.S., D.J.I., M.G., C.T.M.); Memory Clinic, Skåne
University Hospital, Malmö, Sweden (S.H., O.H.); Center for
Neurodegenerative Disease Research, Perelman School of Medicine, University of
Pennsylvania, Philadelphia, Pa (D.J.I., E.B.L., J.Q.T.); Department of
Diagnostic Radiology, Lund University, Lund, Sweden (T.R., D.v.W., M.N.);
Wellcome Centre for Human Neuroimaging, UCL Queen Square Institute of Neurology,
University College London, London, England (J.A.C.); Parkinson’s Disease
and Movement Disorders Center, Department of Neurology, Perelman School of
Medicine, University of Pennsylvania, Philadelphia, Pa (A.F.D., M.A.S.);
Alzheimer’s Disease Core Center, Department of Pathology and Laboratory
Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia,
Pa (E.B.L., J.Q.T.); and Queensland Brain Institute, University of Queensland
and Mater Misericordiae, Brisbane, Queensland, Australia (P.J.N.)
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Abstract
Frontotemporal dementia is a clinically and pathologically heterogeneous group of neurodegenerative disorders, with progressive impairment of behavior and language. They can be closely related to amyotrophic lateral sclerosis, clinically and through shared genetics and similar pathology. Approximately 40% of people with frontotemporal dementia report a family history of dementia, motor neuron disease or parkinsonism, and half of these familial cases are attributed to mutations in three genes (C9orf72, MAPT and PGRN). Akinetic-rigidity is a common feature in several types of frontotemporal dementia, particularly the behavioral variant and the non-fluent agrammatic variant of primary progressive aphasia, and the familial dementias. The majority of patients develop a degree of parkinsonism during the course of the illness, and signs may be present at the time of initial diagnosis. However, the parkinsonism of frontotemporal dementia is very different from that observed in idiopathic Parkinson's disease: it may be symmetric, axial, and poorly responsive to levodopa. Tremor is uncommon, and may be postural, action or occasionally rest tremor. The emergence of parkinsonism is often part of an evolving phenotype, in which frontotemporal dementia comes to resemble corticobasal syndrome or progressive supranuclear palsy. This chapter describes the prevalence and phenomenology of parkinsonism in each of the major syndromes, and according to the common genetic forms of frontotemporal dementia. We discuss the changing nosology and terminology surrounding the diagnoses, and the significance of parkinsonism as a core feature of frontotemporal dementia, relevant to clinical management and the design of future clinical trials.
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Affiliation(s)
- James B Rowe
- Cambridge University Centre for Frontotemporal Dementia and Cambridge University Centre for Parkinson-plus, Cambridge University, Cambridge, United Kingdom
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15
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Shah GV. Using MRI to Identify Supranuclear Palsy from Parkinson Disease and Dementia with Lewy Bodies. Radiology 2019; 293:654-655. [PMID: 31617819 DOI: 10.1148/radiol.2019192183] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/11/2022]
Affiliation(s)
- Gaurang V Shah
- From the Department of Radiology, University of Michigan, 1500 E Medical Center Dr, B2A209, Ann Arbor, Mich 48109
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16
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The atrophy pattern in Alzheimer-related PPA is more widespread than that of the frontotemporal lobar degeneration associated variants. NEUROIMAGE-CLINICAL 2019; 24:101994. [PMID: 31505368 PMCID: PMC6734177 DOI: 10.1016/j.nicl.2019.101994] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 07/11/2019] [Revised: 08/16/2019] [Accepted: 08/24/2019] [Indexed: 11/30/2022]
Abstract
Objective The three recognized variants of primary progressive aphasia (PPA) are associated with different loci of degeneration—left posterior perisylvian in logopenic variant (lvPPA), left frontal operculum in non-fluent variant (nfvPPA), and left rostroventral-temporal in semantic variant (svPPA). Meanwhile, it has become apparent that patients with lvPPA, in which Alzheimer pathology is the norm, frequently have more extensive language deficits—namely semantic and grammatical problems—than is captured in the strict diagnostic recommendations for this variant. We hypothesized that this may be because the degeneration in AD-related PPA typically extends beyond the left posterior perisylvian region. Methods Magnetic resonance images from 25 PPA patients (9AD-related PPA, 10 svPPA, 6 nfvPPA) and a healthy control cohort were used to calculate cortical thickness in three regions of interest (ROIs). The three ROIs being the left-hemispheric loci of maximal reported degeneration for each of the three variants of PPA. Results Consistent with past studies, the most severe cortical thinning was in the posterior perisylvian ROI in AD-related PPA; the ventral temporal ROI in svPPA; and the frontal opercular ROI in nfvPPA. Significant cortical thinning in AD-related PPA, however, was evident in all three ROIs. In contrast, thinning in svPPA and nfvPPA was largely restricted to their known peak loci of degeneration. Conclusions Although cortical degeneration in AD-related PPA is maximal in the left posterior perisylvian region, it extends more diffusely throughout the left hemisphere language network offering a plausible explanation for why the linguistic profile of lvPPA so often includes additional semantic and grammatic deficits. lvPPA is associated with AD pathology. AD-PPA present with more extensive deficits than lvPPA. Atrophy in AD-PPA encompasses the peak atrophy sites of the other PPA subtypes. The extended atrophy in AD-PPA explains the heterogeneity of linguistic deficits.
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17
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Risacher SL, Saykin AJ. Neuroimaging in aging and neurologic diseases. HANDBOOK OF CLINICAL NEUROLOGY 2019; 167:191-227. [PMID: 31753134 DOI: 10.1016/b978-0-12-804766-8.00012-1] [Citation(s) in RCA: 20] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/12/2022]
Abstract
Neuroimaging biomarkers for neurologic diseases are important tools, both for understanding pathology associated with cognitive and clinical symptoms and for differential diagnosis. This chapter explores neuroimaging measures, including structural and functional measures from magnetic resonance imaging (MRI) and molecular measures primarily from positron emission tomography (PET), in healthy aging adults and in a number of neurologic diseases. The spectrum covers neuroimaging measures from normal aging to a variety of dementias: late-onset Alzheimer's disease [AD; including mild cognitive impairment (MCI)], familial and nonfamilial early-onset AD, atypical AD syndromes, posterior cortical atrophy (PCA), logopenic aphasia (lvPPA), cerebral amyloid angiopathy (CAA), vascular dementia (VaD), sporadic and familial behavioral-variant frontotemporal dementia (bvFTD), semantic dementia (SD), progressive nonfluent aphasia (PNFA), frontotemporal dementia with motor neuron disease (FTD-MND), frontotemporal dementia with amyotrophic lateral sclerosis (FTD-ALS), corticobasal degeneration (CBD), progressive supranuclear palsy (PSP), dementia with Lewy bodies (DLB), Parkinson's disease (PD) with and without dementia, and multiple systems atrophy (MSA). We also include a discussion of the appropriate use criteria (AUC) for amyloid imaging and conclude with a discussion of differential diagnosis of neurologic dementia disorders in the context of neuroimaging.
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Affiliation(s)
- Shannon L Risacher
- Department of Radiology and Imaging Sciences, Indiana University School of Medicine, Indianapolis, IN, United States
| | - Andrew J Saykin
- Department of Radiology and Imaging Sciences, Indiana University School of Medicine, Indianapolis, IN, United States.
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18
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Bonnier G, Fischi-Gomez E, Roche A, Hilbert T, Kober T, Krueger G, Granziera C. Personalized pathology maps to quantify diffuse and focal brain damage. NEUROIMAGE-CLINICAL 2018; 21:101607. [PMID: 30502080 PMCID: PMC6413479 DOI: 10.1016/j.nicl.2018.11.017] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 03/14/2018] [Revised: 10/02/2018] [Accepted: 11/18/2018] [Indexed: 01/04/2023]
Abstract
Background and objectives Quantitative MRI (qMRI) permits the quantification of brain changes compatible with inflammation, degeneration and repair in multiple sclerosis (MS) patients. In this study, we propose a new method to provide personalized maps of tissue alterations and longitudinal brain changes based on different qMRI metrics, which provide complementary information about brain pathology. Methods We performed baseline and two-years follow-up on (i) 13 relapsing-remitting MS patients and (ii) four healthy controls. A group consisting of up to 65 healthy controls was used to compute the reference distribution of qMRI metrics in healthy tissue. All subjects underwent 3T MRI examinations including T1, T2, T2* relaxation and Magnetization Transfer Ratio (MTR) imaging. We used a recent partial volume estimation algorithm to estimate the concentration of different brain tissue types on T1 maps; then, we computed a deviation map (z-score map) for each contrast at both time-points. Finally, we subtracted those deviation maps only for voxels showing a significant difference with healthy tissue in one of the time points, to obtain a difference map for each subject. Results and conclusion Control subjects did not show any significant z-score deviations or longitudinal z-score changes. On the other hand, MS patients showed brain regions with cross-sectional and longitudinal concomitant increase in T1, T2, T2* z-scores and decrease of MTR z-scores, suggesting brain tissue degeneration/loss. In the lesion periphery, we observed areas with cross-sectional and longitudinal decreased T1/T2 and slight decrease in T2* most likely related to iron accumulation. Moreover, we measured longitudinal decrease in T1, T2 - and to a lesser extent in T2* - as well as a concomitant increase in MTR, suggesting remyelination/repair. In summary, we have developed a method that provides whole-brain personalized maps of cross-sectional and longitudinal changes in MS patients, which are computed in patient space. These maps may open new perspectives to complement and support radiological evaluation of brain damage for a given patient.
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Affiliation(s)
- G Bonnier
- MGH/MIT/HMS Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Harvard Medical School, Charlestown, MA, United States
| | - E Fischi-Gomez
- MGH/MIT/HMS Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Harvard Medical School, Charlestown, MA, United States; Signal Processing Laboratory 5 (LTS5), École Polytechnique Fédérale de Lausanne, Lausanne, Switzerland.
| | - A Roche
- Advanced Clinical Imaging Technology (HC CEMEA SUI DI PI), Siemens Healthcare AG, Switzerland; Department of Radiology, University Hospital (CHUV), Lausanne, Switzerland; Signal Processing Laboratory 5 (LTS5), École Polytechnique Fédérale de Lausanne, Lausanne, Switzerland
| | - T Hilbert
- Advanced Clinical Imaging Technology (HC CEMEA SUI DI PI), Siemens Healthcare AG, Switzerland; Department of Radiology, University Hospital (CHUV), Lausanne, Switzerland; Signal Processing Laboratory 5 (LTS5), École Polytechnique Fédérale de Lausanne, Lausanne, Switzerland
| | - T Kober
- Advanced Clinical Imaging Technology (HC CEMEA SUI DI PI), Siemens Healthcare AG, Switzerland; Department of Radiology, University Hospital (CHUV), Lausanne, Switzerland; Signal Processing Laboratory 5 (LTS5), École Polytechnique Fédérale de Lausanne, Lausanne, Switzerland
| | - G Krueger
- Siemens Healthcare AG (HC CEMEA DI), Zürich, Switzerland
| | - C Granziera
- MGH/MIT/HMS Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Harvard Medical School, Charlestown, MA, United States; Neurologic Clinic and Policlinic, Departments of Medicine, Clinical Research and Biomedical Engineering, University Hospital Basel and University of Basel, Basel, Switzerland; Translational Imaging in Neurology (ThINk) Basel, Department of Biomedical Engineering, University Hospital Basel and University of Basel, Basel, Switzerland
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19
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Gyebnár G, Szabó Á, Sirály E, Fodor Z, Sákovics A, Salacz P, Hidasi Z, Csibri É, Rudas G, Kozák LR, Csukly G. What can DTI tell about early cognitive impairment? - Differentiation between MCI subtypes and healthy controls by diffusion tensor imaging. Psychiatry Res Neuroimaging 2018; 272:46-57. [PMID: 29126669 DOI: 10.1016/j.pscychresns.2017.10.007] [Citation(s) in RCA: 30] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/03/2017] [Revised: 10/17/2017] [Accepted: 10/21/2017] [Indexed: 01/10/2023]
Abstract
Mild cognitive impairment (MCI) gained a lot of interest recently, especially that the conversion rate to Alzheimer Disease (AD) in the amnestic subtype (aMCI) is higher than in the non-amnestic subtype (naMCI). We aimed to determine whether and how diffusion-weighted MRI (DWI) using the diffusion tensor model (DTI) can differentiate MCI subtypes from healthy subjects. High resolution 3D T1W and DWI images of patients (aMCI, n = 18; naMCI, n = 20; according to Petersen criteria) and controls (n = 27) were acquired at 3T and processed using ExploreDTI and SPM. Voxel-wise and region of interest (ROI) analyses of fractional anisotropy (FA) and mean diffusivity (MD) were performed with ANCOVA; MD was higher in aMCI compared to controls or naMCI in several grey and white matter (GM, WM) regions (especially in the temporal pole and the inferior temporal lobes), while FA was lower in WM ROI-s (e.g. left Cingulum). Moreover, significant correlations were identified between verbal fluency, visual and verbal memory performance and DTI metrics. Logistic regression showed that measuring FA of the crus of fornix along GM volumetry improves the discrimination of aMCI from naMCI. Additional information from DWI/DTI aids preclinical detection of AD and may help detecting early non-Alzheimer type dementia, too.
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Affiliation(s)
- Gyula Gyebnár
- Magnetic Resonance Research Centre, Semmelweis University, Budapest, Hungary.
| | - Ádám Szabó
- Magnetic Resonance Research Centre, Semmelweis University, Budapest, Hungary
| | - Enikő Sirály
- Department of Psychiatry and Psychotherapy, Semmelweis University, Budapest, Hungary
| | - Zsuzsanna Fodor
- Department of Psychiatry and Psychotherapy, Semmelweis University, Budapest, Hungary
| | - Anna Sákovics
- National Institute of Clinical Neurosciences, Budapest, Hungary
| | - Pál Salacz
- Department of Psychiatry and Psychotherapy, Semmelweis University, Budapest, Hungary; Department of Neurology, Péterfy Hospital and Trauma Centre, Budapest, Hungary
| | - Zoltán Hidasi
- Department of Psychiatry and Psychotherapy, Semmelweis University, Budapest, Hungary
| | - Éva Csibri
- Department of Psychiatry and Psychotherapy, Semmelweis University, Budapest, Hungary
| | - Gábor Rudas
- Magnetic Resonance Research Centre, Semmelweis University, Budapest, Hungary
| | - Lajos R Kozák
- Magnetic Resonance Research Centre, Semmelweis University, Budapest, Hungary
| | - Gábor Csukly
- Department of Psychiatry and Psychotherapy, Semmelweis University, Budapest, Hungary
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20
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Meijboom R, Steketee RME, Ham LS, van der Lugt A, van Swieten JC, Smits M. Differential Hemispheric Predilection of Microstructural White Matter and Functional Connectivity Abnormalities between Respectively Semantic and Behavioral Variant Frontotemporal Dementia. J Alzheimers Dis 2018; 56:789-804. [PMID: 28059782 DOI: 10.3233/jad-160564] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
Abstract
Semantic dementia (SD) and behavioral variant frontotemporal dementia (bvFTD), subtypes of frontotemporal dementia, are characterized by distinct clinical symptoms and neuroimaging features, with predominant left temporal grey matter (GM) atrophy in SD and bilateral or right frontal GM atrophy in bvFTD. Such differential hemispheric predilection may also be reflected by other neuroimaging features, such as brain connectivity. This study investigated white matter (WM) microstructure and functional connectivity differences between SD and bvFTD, focusing on the hemispheric predilection of these differences. Eight SD and 12 bvFTD patients, and 17 controls underwent diffusion tensor imaging and resting state functional MRI at 3T. Whole-brain WM microstructure was assessed to determine distinct WM tracts affected in SD and bvFTD. For these tracts, diffusivity measures and lateralization indices were calculated. Functional connectivity was established for GM regions affected in early stage SD or bvFTD. Results of a direct comparison between SD and bvFTD are reported. Whole-brain WM microstructure abnormalities were more pronounced in the left hemisphere in SD and bilaterally- with a slight predilection for the right- in bvFTD. Lateralization of tract-specific abnormalities was seen in SD only, toward the left hemisphere. Functional connectivity of disease-specific regions was mainly decreased bilaterally in SD and in the right hemisphere in bvFTD. SD and bvFTD show WM microstructure and functional connectivity abnormalities in different regions, that are respectively more pronounced in the left hemisphere in SD and in the right hemisphere in bvFTD. This indicates differential hemispheric predilection of brain connectivity abnormalities between SD and bvFTD.
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Affiliation(s)
- Rozanna Meijboom
- Department of Radiology and Nuclear Medicine, Erasmus MC - University Medical Centre Rotterdam, The Netherlands
| | - Rebecca M E Steketee
- Department of Radiology and Nuclear Medicine, Erasmus MC - University Medical Centre Rotterdam, The Netherlands
| | - Leontine S Ham
- Department of Radiology and Nuclear Medicine, Erasmus MC - University Medical Centre Rotterdam, The Netherlands
| | - Aad van der Lugt
- Department of Radiology and Nuclear Medicine, Erasmus MC - University Medical Centre Rotterdam, The Netherlands
| | - John C van Swieten
- Department of Neurology, Erasmus MC - University Medical Centre Rotterdam, The Netherlands
| | - Marion Smits
- Department of Radiology and Nuclear Medicine, Erasmus MC - University Medical Centre Rotterdam, The Netherlands
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21
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Oliveira LMD, Barcellos I, Teive HAG, Munhoz RP. Cognitive dysfunction in corticobasal degeneration. ARQUIVOS DE NEURO-PSIQUIATRIA 2017; 75:570-579. [PMID: 28813088 DOI: 10.1590/0004-282x20170077] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/28/2017] [Accepted: 03/30/2017] [Indexed: 01/30/2023]
Abstract
Corticobasal degeneration (CBD) was originally described as a distinct clinicopathological entity in 1967. Since then, different phenotypic presentations have emerged as possible manifestations of CBD histopathological findings. In addition, pathophysiological findings and the molecular basis have been delineated and several aspects of its cognitive manifestations have been clarified. Thus, not only the spectrum of what is currently designated as CBD has expanded, but overlap with other degenerative and even secondary disorders has made clinical diagnostic certainty even more challenging in the absence of specific and readily-available markers. Cognitive deficits in CBD are now recognized as a frequent initial presentation and may appear up to eight years before the motor symptoms, depending on the phenotypic variant. Characteristic cognitive features of CBD involve language deficits, visuospatial and executive dysfunctions, apraxia, and behavioral disorders. Semantic and episodic memories are usually preserved, while language is often impaired in the early stages.
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Affiliation(s)
- Laís Machado de Oliveira
- University Health Network, Toronto Western Hospital, Morton and Gloria Shulman Movement Disorders Centre and the Edmond J. Safra Program in Parkinson's Disease, Toronto, ON, M5T 2S8, Canada
| | - Igor Barcellos
- Pontifícia Universidade Católica do Paraná, Hospital Universitário Cajuru, Serviço de Neurologia, Curitiba PR, Brasil
| | - Hélio A G Teive
- Universidade Federal do Paraná, Hospital de Clínicas, Departamento de Medicina Interna, Serviço de Neurologia, Setor de Distúrbios do Movimento, Curitiba, PR, Brasil
| | - Renato Puppi Munhoz
- University Health Network, Toronto Western Hospital, Morton and Gloria Shulman Movement Disorders Centre and the Edmond J. Safra Program in Parkinson's Disease, Toronto, ON, M5T 2S8, Canada
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22
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Sheikh-Bahaei N, Sajjadi SA, Manavaki R, Gillard JH. Imaging Biomarkers in Alzheimer's Disease: A Practical Guide for Clinicians. J Alzheimers Dis Rep 2017; 1:71-88. [PMID: 30480230 PMCID: PMC6159632 DOI: 10.3233/adr-170013] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/26/2022] Open
Abstract
Although recent developments in imaging biomarkers have revolutionized the diagnosis of Alzheimer’s disease at early stages, the utility of most of these techniques in clinical setting remains unclear. The aim of this review is to provide a clear stepwise algorithm on using multitier imaging biomarkers for the diagnosis of Alzheimer’s disease to be used by clinicians and radiologists for day-to-day practice. We summarized the role of most common imaging techniques and their appropriate clinical use based on current consensus guidelines and recommendations with brief sections on acquisition and analysis techniques for each imaging modality. Structural imaging, preferably MRI or alternatively high resolution CT, is the essential first tier of imaging. It improves the accuracy of clinical diagnosis and excludes other potential pathologies. When the results of clinical examination and structural imaging, assessed by dementia expert, are still inconclusive, functional imaging can be used as a more advanced option. PET with ligands such as amyloid tracers and 18F-fluorodeoxyglucose can improve the sensitivity and specificity of diagnosis particularly at the early stages of the disease. There are, however, limitations in using these techniques in wider community due to a combination of lack of facilities and expertise to interpret the findings. The role of some of the more recent imaging techniques including tau imaging, functional MRI, or diffusion tensor imaging in clinical practice, remains to be established in the ongoing and future studies.
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Affiliation(s)
- Nasim Sheikh-Bahaei
- Department of Radiology, University of Cambridge School of Clinical Medicine, Cambridge, UK
| | | | - Roido Manavaki
- Department of Radiology, University of Cambridge School of Clinical Medicine, Cambridge, UK
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23
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Whitwell JL, Höglinger GU, Antonini A, Bordelon Y, Boxer AL, Colosimo C, van Eimeren T, Golbe LI, Kassubek J, Kurz C, Litvan I, Pantelyat A, Rabinovici G, Respondek G, Rominger A, Rowe JB, Stamelou M, Josephs KA. Radiological biomarkers for diagnosis in PSP: Where are we and where do we need to be? Mov Disord 2017; 32:955-971. [PMID: 28500751 PMCID: PMC5511762 DOI: 10.1002/mds.27038] [Citation(s) in RCA: 149] [Impact Index Per Article: 21.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/11/2017] [Revised: 04/11/2017] [Accepted: 04/13/2017] [Indexed: 12/11/2022] Open
Abstract
PSP is a pathologically defined neurodegenerative tauopathy with a variety of clinical presentations including typical Richardson's syndrome and other variant PSP syndromes. A large body of neuroimaging research has been conducted over the past two decades, with many studies proposing different structural MRI and molecular PET/SPECT biomarkers for PSP. These include measures of brainstem, cortical and striatal atrophy, diffusion weighted and diffusion tensor imaging abnormalities, [18F] fluorodeoxyglucose PET hypometabolism, reductions in striatal dopamine imaging and, most recently, PET imaging with ligands that bind to tau. Our aim was to critically evaluate the degree to which structural and molecular neuroimaging metrics fulfill criteria for diagnostic biomarkers of PSP. We queried the PubMed, Cochrane, Medline, and PSYCInfo databases for original research articles published in English over the past 20 years using postmortem diagnosis or the NINDS-SPSP criteria as the diagnostic standard from 1996 to 2016. We define a five-level theoretical construct for the utility of neuroimaging biomarkers in PSP, with level 1 representing group-level findings, level 2 representing biomarkers with demonstrable individual-level diagnostic utility, level 3 representing biomarkers for early disease, level 4 representing surrogate biomarkers of PSP pathology, and level 5 representing definitive PSP biomarkers of PSP pathology. We discuss the degree to which each of the currently available biomarkers fit into this theoretical construct, consider the role of biomarkers in the diagnosis of Richardson's syndrome, variant PSP syndromes and autopsy confirmed PSP, and emphasize current shortfalls in the field. © 2017 The Authors. Movement Disorders published by Wiley Periodicals, Inc. on behalf of International Parkinson and Movement Disorder Society.
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Affiliation(s)
| | - Günter U. Höglinger
- Department of Neurology, Technische Universität München, Munich, Germany
- German Center for Neurodegenerative Diseases (DZNE), Germany
| | - Angelo Antonini
- Parkinson and Movement Disorder Unit, IRCCS Hospital San Camillo, Venice and Department of Neurosciences (DNS), Padova University, Padova, Italy
| | - Yvette Bordelon
- Department of Neurology, University of California, Los Angeles, CA, USA
| | - Adam L. Boxer
- Memory and Aging Center, Department of Neurology, University of California, San Francisco, CA, USA
| | - Carlo Colosimo
- Department of Neurology, Santa Maria University Hospital, Terni, Italy
| | - Thilo van Eimeren
- German Center for Neurodegenerative Diseases (DZNE), Germany
- Department of Nuclear Medicine, University of Cologne, Cologne, Germany
| | - Lawrence I. Golbe
- Department of Neurology, Rutgers Robert Wood Johnson Medical School, New Brunswick, NJ, USA
| | - Jan Kassubek
- Department of Neurology, University of Ulm, Ulm, Germany
| | - Carolin Kurz
- Psychiatrische Klinik, Ludwigs-Maximilians-Universität, München, Germany
| | - Irene Litvan
- Department of Neurology, University of California, San Diego, CA, USA
| | | | - Gil Rabinovici
- Memory and Aging Center, Department of Neurology, University of California, San Francisco, CA, USA
| | - Gesine Respondek
- Department of Neurology, Technische Universität München, Munich, Germany
- German Center for Neurodegenerative Diseases (DZNE), Germany
| | - Axel Rominger
- Deptartment of Nuclear Medicine, Ludwig-Maximilians-Universität München, Munich, Germany
| | - James B. Rowe
- Department of Clinical Neurosciences, Cambridge University, Cambridge, UK
| | - Maria Stamelou
- Second Department of Neurology, Attikon University Hospital, University of Athens, Greece; Philipps University, Marburg, Germany; Movement Disorders Dept., HYGEIA Hospital, Athens, Greece
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24
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Canu E, Agosta F, Mandic-Stojmenovic G, Stojković T, Stefanova E, Inuggi A, Imperiale F, Copetti M, Kostic VS, Filippi M. Multiparametric MRI to distinguish early onset Alzheimer's disease and behavioural variant of frontotemporal dementia. NEUROIMAGE-CLINICAL 2017; 15:428-438. [PMID: 28616383 PMCID: PMC5458769 DOI: 10.1016/j.nicl.2017.05.018] [Citation(s) in RCA: 41] [Impact Index Per Article: 5.9] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 03/07/2017] [Revised: 05/12/2017] [Accepted: 05/25/2017] [Indexed: 12/11/2022]
Abstract
This prospective study explored whether an approach combining structural [cortical thickness and white matter (WM) microstructure] and resting state functional MRI can aid differentiation between 62 early onset Alzheimer's disease (EOAD) and 27 behavioural variant of frontotemporal dementia (bvFTD) patients. Random forest and receiver operator characteristic curve analyses assessed the ability of MRI in classifying the two clinical syndromes. All patients showed a distributed pattern of brain alterations relative to controls. Compared to bvFTD, EOAD patients showed bilateral inferior parietal cortical thinning and decreased default mode network functional connectivity. Compared to EOAD, bvFTD patients showed bilateral orbitofrontal and temporal cortical thinning, and WM damage of the corpus callosum, bilateral uncinate fasciculus, and left superior longitudinal fasciculus. Random forest analysis revealed that left inferior parietal cortical thickness (accuracy 0.78, specificity 0.76, sensitivity 0.83) and WM integrity of the right uncinate fasciculus (accuracy 0.81, specificity 0.96, sensitivity 0.43) were the best predictors of clinical diagnosis. The combination of cortical thickness and DT MRI measures was able to distinguish patients with EOAD and bvFTD with accuracy 0.82, specificity 0.76, and sensitivity 0.96. The diagnostic ability of MRI models was confirmed in a subsample of patients with biomarker-based clinical diagnosis. Multiparametric MRI is useful to identify brain alterations which are specific to EOAD and bvFTD. A severe cortical involvement is suggestive of EOAD, while a prominent WM damage is indicative of bvFTD. Multimodal MRI distinguishes in vivo EOAD and bvFTD patients EOAD and bvFTD show a distributed pattern of structural brain alterations A severe cortical involvement is suggestive of EOAD relative to bvFTD A prominent WM damage is indicative of bvFTD relative to EOAD
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Key Words
- ACE-R, Addenbrooke's Cognitive Examination-revised
- Behavioural variant of frontotemporal dementia
- CC, corpus callosum
- CSF, cerebrospinal fluid
- Cortical thickness
- DMN, default mode network
- DT, diffusion tensor
- Diagnosis
- EOAD, early onset Alzheimer's disease
- Early onset Alzheimer's disease
- GM, grey matter
- IC, independent component
- ILF, inferior longitudinal fasciculus
- LOAD, late onset Alzheimer's disease
- MNI, Montreal Neurological Institute
- NVI, Normalized Variable Importance
- RS fMRI, resting state functional MRI
- RSN, resting state network
- Resting state functional MRI
- SLF, superior longitudinal fasciculus
- TFCE, threshold-free cluster enhancement
- WM, white matter
- White matter (WM) damage
- bvFTD, behavioural variant frontotemporal dementia
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Affiliation(s)
- Elisa Canu
- Neuroimaging Research Unit, Institute of Experimental Neurology, Division of Neuroscience, San Raffaele Scientific Institute, via Olgettina 60, 20132 Milan, Italy
| | - Federica Agosta
- Neuroimaging Research Unit, Institute of Experimental Neurology, Division of Neuroscience, San Raffaele Scientific Institute, via Olgettina 60, 20132 Milan, Italy
| | - Gorana Mandic-Stojmenovic
- Neuroimaging Research Unit, Institute of Experimental Neurology, Division of Neuroscience, San Raffaele Scientific Institute, via Olgettina 60, 20132 Milan, Italy; Clinic of Neurology, Faculty of Medicine, University of Belgrade, Dr Subotića 6, PO Box 12, 11129 Belgrade 102, Serbia
| | - Tanja Stojković
- Clinic of Neurology, Faculty of Medicine, University of Belgrade, Dr Subotića 6, PO Box 12, 11129 Belgrade 102, Serbia
| | - Elka Stefanova
- Clinic of Neurology, Faculty of Medicine, University of Belgrade, Dr Subotića 6, PO Box 12, 11129 Belgrade 102, Serbia
| | - Alberto Inuggi
- Unit of Robotics, Brain and Cognitive Sciences, Istituto Italiano di Tecnologia, Via Morego, 30, 16163 Genoa, Italy
| | - Francesca Imperiale
- Neuroimaging Research Unit, Institute of Experimental Neurology, Division of Neuroscience, San Raffaele Scientific Institute, via Olgettina 60, 20132 Milan, Italy
| | - Massimiliano Copetti
- Biostatistics Unit, IRCCS-Ospedale Casa Sollievo della Sofferenza, Viale Cappuccini, San Giovanni Rotondo, 71013 Foggia, Italy
| | - Vladimir S Kostic
- Clinic of Neurology, Faculty of Medicine, University of Belgrade, Dr Subotića 6, PO Box 12, 11129 Belgrade 102, Serbia
| | - Massimo Filippi
- Neuroimaging Research Unit, Institute of Experimental Neurology, Division of Neuroscience, San Raffaele Scientific Institute, via Olgettina 60, 20132 Milan, Italy; Department of Neurology, Institute of Experimental Neurology, Division of Neuroscience, San Raffaele Scientific Institute, via Olgettina 60, 20132 Milan, Italy.
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25
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Marcotte K, Graham NL, Fraser KC, Meltzer JA, Tang-Wai DF, Chow TW, Freedman M, Leonard C, Black SE, Rochon E. White Matter Disruption and Connected Speech in Non-Fluent and Semantic Variants of Primary Progressive Aphasia. Dement Geriatr Cogn Dis Extra 2017; 7:52-73. [PMID: 28611820 PMCID: PMC5465709 DOI: 10.1159/000456710] [Citation(s) in RCA: 24] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/20/2016] [Accepted: 01/06/2017] [Indexed: 02/04/2023] Open
Abstract
Differential patterns of white matter disruption have recently been reported in the non-fluent (nfvPPA) and semantic (svPPA) variants of primary progressive aphasia (PPA). No single measure is sufficient to distinguish between the PPA variants, but connected speech allows for the quantification of multiple measures. The aim of the present study was to further investigate the white matter correlates associated with connected speech features in PPA. We examined the relationship between white matter metrics and connected speech deficits using an automated analysis of transcriptions of connected speech and diffusion tensor imaging in language-related tracts. Syntactic, lexical, and semantic features were automatically extracted from transcriptions of topic-directed interviews conducted with groups of individuals with nfvPPA or svPPA as well as with a group of healthy controls. A principal component analysis was performed in order to reduce the number of language measures and yielded a five-factor solution. The results indicated that nfvPPA patients differed from healthy controls on a syntactic factor, and svPPA patients differed from controls on two semantic factors. However, the patient groups did not differ on any factor. Moreover, a correlational analysis revealed that the lexical richness factor was significantly correlated with radial diffusivity in the left inferior longitudinal fasciculus, which suggests that semantic deficits in connected speech reflect a disruption of this ventral pathway, and which is largely consistent with the results of previous studies. Using an automated approach for the analysis of connected speech combined with probabilistic tractography, the present findings demonstrate that nfvPPA patients are impaired relative to healthy controls on syntactic measures and have increased radial diffusivity in the left superior longitudinal fasciculus, whereas the svPPA group was impaired on lexico-semantic measures relative to controls and showed increased radial diffusivity in the uncinate and inferior longitudinal fasciculus bilaterally.
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Affiliation(s)
- Karine Marcotte
- aToronto Rehabilitation Institute - University Health Network, Toronto, Ontario, Canada.,bÉcole d'orthophonie et d'audiologie, Faculté de médecine, Université de Montréal, Montréal, Québec, Canada.,cCentre de recherche de l'Hôpital du Sacré-Cœur de Montréal, Montreal, Québec, Canada
| | - Naida L Graham
- aToronto Rehabilitation Institute - University Health Network, Toronto, Ontario, Canada.,dDepartment of Speech-Language Pathology, Faculty of Medicine, University of Toronto, Toronto, Ontario, Canada
| | - Kathleen C Fraser
- eDepartment of Computer Science, University of Toronto, Toronto, Ontario, Canada
| | - Jed A Meltzer
- dDepartment of Speech-Language Pathology, Faculty of Medicine, University of Toronto, Toronto, Ontario, Canada.,fRotman Research Institute, Baycrest Health Sciences, Toronto, Ontario, Canada.,gDepartment of Psychology, University of Toronto, Toronto, Ontario, Canada.,hHeart and Stroke Foundation, Center for Stroke Recovery, Ottawa, Ontario, Canada
| | - David F Tang-Wai
- iDepartment of Medicine (Neurology), University of Toronto, Toronto, Ontario, Canada.,jUniversity Health Network Memory Clinic, Toronto Western Hospital, Toronto, Ontario, Canada
| | - Tiffany W Chow
- fRotman Research Institute, Baycrest Health Sciences, Toronto, Ontario, Canada.,iDepartment of Medicine (Neurology), University of Toronto, Toronto, Ontario, Canada.,kDepartment of Clinical Neurology, University of Southern California, Los Angeles, California, USA
| | - Morris Freedman
- fRotman Research Institute, Baycrest Health Sciences, Toronto, Ontario, Canada.,lDepartment of Medicine, Division of Neurology, Baycrest Health Sciences, University of Toronto, and Mt. Sinai Hospital, Toronto, Ontario, Canada.,mSam and Ida Ross Memory Clinic, Baycrest Health Sciences, Toronto, Ontario, Canada
| | - Carol Leonard
- dDepartment of Speech-Language Pathology, Faculty of Medicine, University of Toronto, Toronto, Ontario, Canada.,hHeart and Stroke Foundation, Center for Stroke Recovery, Ottawa, Ontario, Canada.,nSchool of Rehabilitation Sciences, Faculty of Health Sciences, University of Ottawa, Ottawa, Ontario, Canada
| | - Sandra E Black
- aToronto Rehabilitation Institute - University Health Network, Toronto, Ontario, Canada.,fRotman Research Institute, Baycrest Health Sciences, Toronto, Ontario, Canada.,hHeart and Stroke Foundation, Center for Stroke Recovery, Ottawa, Ontario, Canada.,iDepartment of Medicine (Neurology), University of Toronto, Toronto, Ontario, Canada.,oInstitute of Medical Science, University of Toronto, Toronto, Ontario, Canada.,pL.C. Campbell Cognitive Neurology Research Unit, Sunnybrook Health Sciences Centre, Toronto, Ontario, Canada.,qBrain Sciences Research Program, Sunnybrook Research Institute, Toronto, Ontario, Canada
| | - Elizabeth Rochon
- aToronto Rehabilitation Institute - University Health Network, Toronto, Ontario, Canada.,dDepartment of Speech-Language Pathology, Faculty of Medicine, University of Toronto, Toronto, Ontario, Canada.,hHeart and Stroke Foundation, Center for Stroke Recovery, Ottawa, Ontario, Canada.,rRehabilitation Sciences Institute, University of Toronto, Toronto, Ontario, Canada
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Advanced structural neuroimaging in progressive supranuclear palsy: Where do we stand? Parkinsonism Relat Disord 2017; 36:19-32. [DOI: 10.1016/j.parkreldis.2016.12.023] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/13/2016] [Revised: 12/01/2016] [Accepted: 12/23/2016] [Indexed: 12/11/2022]
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Hansson O, Janelidze S, Hall S, Magdalinou N, Lees AJ, Andreasson U, Norgren N, Linder J, Forsgren L, Constantinescu R, Zetterberg H, Blennow K. Blood-based NfL: A biomarker for differential diagnosis of parkinsonian disorder. Neurology 2017; 88:930-937. [PMID: 28179466 PMCID: PMC5333515 DOI: 10.1212/wnl.0000000000003680] [Citation(s) in RCA: 323] [Impact Index Per Article: 46.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/22/2016] [Accepted: 11/15/2016] [Indexed: 12/12/2022] Open
Abstract
OBJECTIVE To determine if blood neurofilament light chain (NfL) protein can discriminate between Parkinson disease (PD) and atypical parkinsonian disorders (APD) with equally high diagnostic accuracy as CSF NfL, and can therefore improve the diagnostic workup of parkinsonian disorders. METHODS The study included 3 independent prospective cohorts: the Lund (n = 278) and London (n = 117) cohorts, comprising healthy controls and patients with PD, progressive supranuclear palsy (PSP), corticobasal syndrome (CBS), and multiple system atrophy (MSA), as well as an early disease cohort (n = 109) of patients with PD, PSP, MSA, or CBS with disease duration ≤3 years. Blood NfL concentration was measured using an ultrasensitive single molecule array (Simoa) method, and the diagnostic accuracy to distinguish PD from APD was investigated. RESULTS We found strong correlations between blood and CSF concentrations of NfL (ρ ≥ 0.73-0.84, p ≤ 0.001). Blood NfL was increased in patients with MSA, PSP, and CBS (i.e., all APD groups) when compared to patients with PD as well as healthy controls in all cohorts (p < 0.001). Furthermore, in the Lund cohort, blood NfL could accurately distinguish PD from APD (area under the curve [AUC] 0.91) with similar results in both the London cohort (AUC 0.85) and the early disease cohort (AUC 0.81). CONCLUSIONS Quantification of blood NfL concentration can be used to distinguish PD from APD. Blood-based NfL might consequently be included in the diagnostic workup of patients with parkinsonian symptoms in both primary care and specialized clinics. CLASSIFICATION OF EVIDENCE This study provides Class III evidence that blood NfL levels discriminate between PD and APD.
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Affiliation(s)
- Oskar Hansson
- From the Clinical Memory Research Unit (O.H., S.J., S.H.), Department of Clinical Sciences, Lund University; Memory Clinic (O.H., S.J., S.H.), Skåne University Hospital, Sweden; UCL Institute of Neurology (N.M., A.J.L., H.Z.), Queen Square, London, UK; Clinical Neurochemistry Laboratory (R.C., H.Z., K.B.), Institute of Neuroscience and Physiology (U.A.), The Sahlgrenska Academy at University of Gothenburg, Mölndal; UmanDiagnostics (N.N.), Umeå; and Department of Pharmacology and Clinical Neuroscience (J.L., L.F.), Umeå University, Sweden.
| | - Shorena Janelidze
- From the Clinical Memory Research Unit (O.H., S.J., S.H.), Department of Clinical Sciences, Lund University; Memory Clinic (O.H., S.J., S.H.), Skåne University Hospital, Sweden; UCL Institute of Neurology (N.M., A.J.L., H.Z.), Queen Square, London, UK; Clinical Neurochemistry Laboratory (R.C., H.Z., K.B.), Institute of Neuroscience and Physiology (U.A.), The Sahlgrenska Academy at University of Gothenburg, Mölndal; UmanDiagnostics (N.N.), Umeå; and Department of Pharmacology and Clinical Neuroscience (J.L., L.F.), Umeå University, Sweden
| | - Sara Hall
- From the Clinical Memory Research Unit (O.H., S.J., S.H.), Department of Clinical Sciences, Lund University; Memory Clinic (O.H., S.J., S.H.), Skåne University Hospital, Sweden; UCL Institute of Neurology (N.M., A.J.L., H.Z.), Queen Square, London, UK; Clinical Neurochemistry Laboratory (R.C., H.Z., K.B.), Institute of Neuroscience and Physiology (U.A.), The Sahlgrenska Academy at University of Gothenburg, Mölndal; UmanDiagnostics (N.N.), Umeå; and Department of Pharmacology and Clinical Neuroscience (J.L., L.F.), Umeå University, Sweden
| | - Nadia Magdalinou
- From the Clinical Memory Research Unit (O.H., S.J., S.H.), Department of Clinical Sciences, Lund University; Memory Clinic (O.H., S.J., S.H.), Skåne University Hospital, Sweden; UCL Institute of Neurology (N.M., A.J.L., H.Z.), Queen Square, London, UK; Clinical Neurochemistry Laboratory (R.C., H.Z., K.B.), Institute of Neuroscience and Physiology (U.A.), The Sahlgrenska Academy at University of Gothenburg, Mölndal; UmanDiagnostics (N.N.), Umeå; and Department of Pharmacology and Clinical Neuroscience (J.L., L.F.), Umeå University, Sweden
| | - Andrew J Lees
- From the Clinical Memory Research Unit (O.H., S.J., S.H.), Department of Clinical Sciences, Lund University; Memory Clinic (O.H., S.J., S.H.), Skåne University Hospital, Sweden; UCL Institute of Neurology (N.M., A.J.L., H.Z.), Queen Square, London, UK; Clinical Neurochemistry Laboratory (R.C., H.Z., K.B.), Institute of Neuroscience and Physiology (U.A.), The Sahlgrenska Academy at University of Gothenburg, Mölndal; UmanDiagnostics (N.N.), Umeå; and Department of Pharmacology and Clinical Neuroscience (J.L., L.F.), Umeå University, Sweden
| | - Ulf Andreasson
- From the Clinical Memory Research Unit (O.H., S.J., S.H.), Department of Clinical Sciences, Lund University; Memory Clinic (O.H., S.J., S.H.), Skåne University Hospital, Sweden; UCL Institute of Neurology (N.M., A.J.L., H.Z.), Queen Square, London, UK; Clinical Neurochemistry Laboratory (R.C., H.Z., K.B.), Institute of Neuroscience and Physiology (U.A.), The Sahlgrenska Academy at University of Gothenburg, Mölndal; UmanDiagnostics (N.N.), Umeå; and Department of Pharmacology and Clinical Neuroscience (J.L., L.F.), Umeå University, Sweden
| | - Niklas Norgren
- From the Clinical Memory Research Unit (O.H., S.J., S.H.), Department of Clinical Sciences, Lund University; Memory Clinic (O.H., S.J., S.H.), Skåne University Hospital, Sweden; UCL Institute of Neurology (N.M., A.J.L., H.Z.), Queen Square, London, UK; Clinical Neurochemistry Laboratory (R.C., H.Z., K.B.), Institute of Neuroscience and Physiology (U.A.), The Sahlgrenska Academy at University of Gothenburg, Mölndal; UmanDiagnostics (N.N.), Umeå; and Department of Pharmacology and Clinical Neuroscience (J.L., L.F.), Umeå University, Sweden
| | - Jan Linder
- From the Clinical Memory Research Unit (O.H., S.J., S.H.), Department of Clinical Sciences, Lund University; Memory Clinic (O.H., S.J., S.H.), Skåne University Hospital, Sweden; UCL Institute of Neurology (N.M., A.J.L., H.Z.), Queen Square, London, UK; Clinical Neurochemistry Laboratory (R.C., H.Z., K.B.), Institute of Neuroscience and Physiology (U.A.), The Sahlgrenska Academy at University of Gothenburg, Mölndal; UmanDiagnostics (N.N.), Umeå; and Department of Pharmacology and Clinical Neuroscience (J.L., L.F.), Umeå University, Sweden
| | - Lars Forsgren
- From the Clinical Memory Research Unit (O.H., S.J., S.H.), Department of Clinical Sciences, Lund University; Memory Clinic (O.H., S.J., S.H.), Skåne University Hospital, Sweden; UCL Institute of Neurology (N.M., A.J.L., H.Z.), Queen Square, London, UK; Clinical Neurochemistry Laboratory (R.C., H.Z., K.B.), Institute of Neuroscience and Physiology (U.A.), The Sahlgrenska Academy at University of Gothenburg, Mölndal; UmanDiagnostics (N.N.), Umeå; and Department of Pharmacology and Clinical Neuroscience (J.L., L.F.), Umeå University, Sweden
| | - Radu Constantinescu
- From the Clinical Memory Research Unit (O.H., S.J., S.H.), Department of Clinical Sciences, Lund University; Memory Clinic (O.H., S.J., S.H.), Skåne University Hospital, Sweden; UCL Institute of Neurology (N.M., A.J.L., H.Z.), Queen Square, London, UK; Clinical Neurochemistry Laboratory (R.C., H.Z., K.B.), Institute of Neuroscience and Physiology (U.A.), The Sahlgrenska Academy at University of Gothenburg, Mölndal; UmanDiagnostics (N.N.), Umeå; and Department of Pharmacology and Clinical Neuroscience (J.L., L.F.), Umeå University, Sweden
| | - Henrik Zetterberg
- From the Clinical Memory Research Unit (O.H., S.J., S.H.), Department of Clinical Sciences, Lund University; Memory Clinic (O.H., S.J., S.H.), Skåne University Hospital, Sweden; UCL Institute of Neurology (N.M., A.J.L., H.Z.), Queen Square, London, UK; Clinical Neurochemistry Laboratory (R.C., H.Z., K.B.), Institute of Neuroscience and Physiology (U.A.), The Sahlgrenska Academy at University of Gothenburg, Mölndal; UmanDiagnostics (N.N.), Umeå; and Department of Pharmacology and Clinical Neuroscience (J.L., L.F.), Umeå University, Sweden
| | - Kaj Blennow
- From the Clinical Memory Research Unit (O.H., S.J., S.H.), Department of Clinical Sciences, Lund University; Memory Clinic (O.H., S.J., S.H.), Skåne University Hospital, Sweden; UCL Institute of Neurology (N.M., A.J.L., H.Z.), Queen Square, London, UK; Clinical Neurochemistry Laboratory (R.C., H.Z., K.B.), Institute of Neuroscience and Physiology (U.A.), The Sahlgrenska Academy at University of Gothenburg, Mölndal; UmanDiagnostics (N.N.), Umeå; and Department of Pharmacology and Clinical Neuroscience (J.L., L.F.), Umeå University, Sweden
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Pini L, Pievani M, Bocchetta M, Altomare D, Bosco P, Cavedo E, Galluzzi S, Marizzoni M, Frisoni GB. Brain atrophy in Alzheimer's Disease and aging. Ageing Res Rev 2016; 30:25-48. [PMID: 26827786 DOI: 10.1016/j.arr.2016.01.002] [Citation(s) in RCA: 409] [Impact Index Per Article: 51.1] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/18/2015] [Revised: 01/15/2016] [Accepted: 01/20/2016] [Indexed: 01/22/2023]
Abstract
Thanks to its safety and accessibility, magnetic resonance imaging (MRI) is extensively used in clinical routine and research field, largely contributing to our understanding of the pathophysiology of neurodegenerative disorders such as Alzheimer's disease (AD). This review aims to provide a comprehensive overview of the main findings in AD and normal aging over the past twenty years, focusing on the patterns of gray and white matter changes assessed in vivo using MRI. Major progresses in the field concern the segmentation of the hippocampus with novel manual and automatic segmentation approaches, which might soon enable to assess also hippocampal subfields. Advancements in quantification of hippocampal volumetry might pave the way to its broader use as outcome marker in AD clinical trials. Patterns of cortical atrophy have been shown to accurately track disease progression and seem promising in distinguishing among AD subtypes. Disease progression has also been associated with changes in white matter tracts. Recent studies have investigated two areas often overlooked in AD, such as the striatum and basal forebrain, reporting significant atrophy, although the impact of these changes on cognition is still unclear. Future integration of different MRI modalities may further advance the field by providing more powerful biomarkers of disease onset and progression.
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Affiliation(s)
- Lorenzo Pini
- Laboratory Alzheimer's Neuroimaging & Epidemiology, IRCCS Fatebenefratelli, Brescia, Italy; Department of Molecular and Translational Medicine, University of Brescia, Brescia, Italy
| | - Michela Pievani
- Laboratory Alzheimer's Neuroimaging & Epidemiology, IRCCS Fatebenefratelli, Brescia, Italy
| | - Martina Bocchetta
- Laboratory Alzheimer's Neuroimaging & Epidemiology, IRCCS Fatebenefratelli, Brescia, Italy; Dementia Research Centre, Department of Neurodegenerative Disease, UCL Institute of Neurology, University College London, London, UK
| | - Daniele Altomare
- Laboratory Alzheimer's Neuroimaging & Epidemiology, IRCCS Fatebenefratelli, Brescia, Italy; Department of Molecular and Translational Medicine, University of Brescia, Brescia, Italy
| | - Paolo Bosco
- Laboratory Alzheimer's Neuroimaging & Epidemiology, IRCCS Fatebenefratelli, Brescia, Italy
| | - Enrica Cavedo
- Laboratory Alzheimer's Neuroimaging & Epidemiology, IRCCS Fatebenefratelli, Brescia, Italy; Sorbonne Universités, Université Pierre et Marie Curie, Paris 06, Institut de la Mémoire et de la Maladie d'Alzheimer (IM2A) Hôpital de la Pitié-Salpétrière & Institut du Cerveau et de la Moelle épinière (ICM), UMR S 1127, Hôpital de la Pitié-Salpétrière Paris & CATI Multicenter Neuroimaging Platform, France
| | - Samantha Galluzzi
- Laboratory Alzheimer's Neuroimaging & Epidemiology, IRCCS Fatebenefratelli, Brescia, Italy
| | - Moira Marizzoni
- Laboratory Alzheimer's Neuroimaging & Epidemiology, IRCCS Fatebenefratelli, Brescia, Italy
| | - Giovanni B Frisoni
- Laboratory Alzheimer's Neuroimaging & Epidemiology, IRCCS Fatebenefratelli, Brescia, Italy; Memory Clinic and LANVIE-Laboratory of Neuroimaging of Aging, University Hospitals and University of Geneva, Geneva, Switzerland.
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Mandelli ML, Vilaplana E, Brown JA, Hubbard HI, Binney RJ, Attygalle S, Santos-Santos MA, Miller ZA, Pakvasa M, Henry ML, Rosen HJ, Henry RG, Rabinovici GD, Miller BL, Seeley WW, Gorno-Tempini ML. Healthy brain connectivity predicts atrophy progression in non-fluent variant of primary progressive aphasia. Brain 2016; 139:2778-2791. [PMID: 27497488 DOI: 10.1093/brain/aww195] [Citation(s) in RCA: 90] [Impact Index Per Article: 11.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/12/2016] [Accepted: 06/02/2016] [Indexed: 11/12/2022] Open
Abstract
Neurodegeneration has been hypothesized to follow predetermined large-scale networks through the trans-synaptic spread of toxic proteins from a syndrome-specific epicentre. To date, no longitudinal neuroimaging study has tested this hypothesis in vivo in frontotemporal dementia spectrum disorders. The aim of this study was to demonstrate that longitudinal progression of atrophy in non-fluent/agrammatic variant primary progressive aphasia spreads over time from a syndrome-specific epicentre to additional regions, based on their connectivity to the epicentre in healthy control subjects. The syndrome-specific epicentre of the non-fluent/agrammatic variant of primary progressive aphasia was derived in a group of 10 mildly affected patients (clinical dementia rating equal to 0) using voxel-based morphometry. From this region, the inferior frontal gyrus (pars opercularis), we derived functional and structural connectivity maps in healthy controls (n = 30) using functional magnetic resonance imaging at rest and diffusion-weighted imaging tractography. Graph theory analysis was applied to derive functional network features. Atrophy progression was calculated using voxel-based morphometry longitudinal analysis on 34 non-fluent/agrammatic patients. Correlation analyses were performed to compare volume changes in patients with connectivity measures of the healthy functional and structural speech/language network. The default mode network was used as a control network. From the epicentre, the healthy functional connectivity network included the left supplementary motor area and the prefrontal, inferior parietal and temporal regions, which were connected through the aslant, superior longitudinal and arcuate fasciculi. Longitudinal grey and white matter changes were found in the left language-related regions and in the right inferior frontal gyrus. Functional connectivity strength in the healthy speech/language network, but not in the default network, correlated with longitudinal grey matter changes in the non-fluent/agrammatic variant of primary progressive aphasia. Graph theoretical analysis of the speech/language network showed that regions with shorter functional paths to the epicentre exhibited greater longitudinal atrophy. The network contained three modules, including a left inferior frontal gyrus/supplementary motor area, which was most strongly connected with the epicentre. The aslant tract was the white matter pathway connecting these two regions and showed the most significant correlation between fractional anisotropy and white matter longitudinal atrophy changes. This study showed that the pattern of longitudinal atrophy progression in the non-fluent/agrammatic variant of primary progressive aphasia relates to the strength of connectivity in pre-determined functional and structural large-scale speech production networks. These findings support the hypothesis that the spread of neurodegeneration occurs by following specific anatomical and functional neuronal network architectures.
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Affiliation(s)
- Maria Luisa Mandelli
- 1 Department of Neurology, Memory and Aging Center, University of California San Francisco, CA, USA
| | - Eduard Vilaplana
- 2 Memory Unit, Department of Neurology, Hospital de la Santa Creu i Sant Pau - Biomedical Research Institute Sant Pau - Universitat Autonoma de Barcelona, Spain 3 Centro de Investigacion Biomedica en Red de Enfermedades Neurodegenerativas - CIBERNED, Spain
| | - Jesse A Brown
- 1 Department of Neurology, Memory and Aging Center, University of California San Francisco, CA, USA
| | - H Isabel Hubbard
- 1 Department of Neurology, Memory and Aging Center, University of California San Francisco, CA, USA
| | - Richard J Binney
- 4 Department of Communication Sciences and Disorders, Temple University, Philadelphia, Pennsylvania, USA
| | - Suneth Attygalle
- 1 Department of Neurology, Memory and Aging Center, University of California San Francisco, CA, USA
| | - Miguel A Santos-Santos
- 1 Department of Neurology, Memory and Aging Center, University of California San Francisco, CA, USA
| | - Zachary A Miller
- 1 Department of Neurology, Memory and Aging Center, University of California San Francisco, CA, USA
| | - Mikhail Pakvasa
- 1 Department of Neurology, Memory and Aging Center, University of California San Francisco, CA, USA
| | - Maya L Henry
- 5 Department of Communication Sciences and Disorders, University of Texas, Austin, USA
| | - Howard J Rosen
- 1 Department of Neurology, Memory and Aging Center, University of California San Francisco, CA, USA
| | - Roland G Henry
- 6 Department of Neurology, University of California San Francisco, CA, USA 7 Bioengineering Graduate Group, University of California Berkeley, San Francisco, CA, USA 8 Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, CA, USA
| | - Gil D Rabinovici
- 1 Department of Neurology, Memory and Aging Center, University of California San Francisco, CA, USA
| | - Bruce L Miller
- 1 Department of Neurology, Memory and Aging Center, University of California San Francisco, CA, USA
| | - William W Seeley
- 1 Department of Neurology, Memory and Aging Center, University of California San Francisco, CA, USA 9 Department of Pathology, University of California San Francisco, CA, USA
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Progression of Microstructural Degeneration in Progressive Supranuclear Palsy and Corticobasal Syndrome: A Longitudinal Diffusion Tensor Imaging Study. PLoS One 2016; 11:e0157218. [PMID: 27310132 PMCID: PMC4911077 DOI: 10.1371/journal.pone.0157218] [Citation(s) in RCA: 35] [Impact Index Per Article: 4.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/02/2016] [Accepted: 05/26/2016] [Indexed: 11/19/2022] Open
Abstract
Progressive supranuclear palsy (PSP) and corticobasal syndrome (CBS) are both 4 microtubule binding repeat tauopathy related disorders. Clinical trials need new biomarkers to assess the effectiveness of tau-directed therapies. This study investigated the regional distribution of longitudinal diffusion tensor imaging changes, measured by fractional anisotropy, radial and axial diffusivity over 6 months median interval, in 23 normal control subjects, 35 patients with PSP, and 25 patients with CBS. A mixed-effects framework was used to test longitudinal changes within and between groups. Correlations between changes in diffusion variables and clinical progression were also tested. The study found that over a 6 month period and compared to controls, the most prominent changes in PSP were up to 3±1% higher rates of FA reduction predominantly in superior cerebellar peduncles, and up to 18±6% higher rates of diffusivity increases in caudate nuclei. The most prominent changes in CBS compared to controls were up to 4±1% higher rates of anisotropy reduction and 18±6% higher rates of diffusivity increase in basal ganglia and widespread white matter regions. Compared to PSP, CBS was mainly associated with up to 3±1% greater rates of anisotropy reduction around the central sulci, and 11±3% greater rates of diffusivity increase in superior fronto-occipital fascicules. Rates of diffusivity increases in the superior cerebellar peduncle correlated with rates of ocular motor decline in PSP patients. This study demonstrated that longitudinal diffusion tensor imaging measurement is a promising surrogate marker of disease progression in PSP and CBS over a relatively short period.
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Ribeiro LG, Busatto G. Voxel-based morphometry in Alzheimers disease and mild cognitive impairment: Systematic review of studies addressing the frontal lobe. Dement Neuropsychol 2016; 10:104-112. [PMID: 29213441 PMCID: PMC5642401 DOI: 10.1590/s1980-5764-2016dn1002006] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/22/2022] Open
Abstract
Voxel-based morphometry (VBM) is a useful approach for investigating neurostructural brain changes in dementia. We systematically reviewed VBM studies of Alzheimer's disease (AD) and mild cognitive impairment (MCI), specifically focusing on grey matter (GM) atrophy in the frontal lobe. Methods Two searches were performed on the Pubmed database. A set of exclusion criteria was applied to ensure the selection of only VBM studies that directly investigated GM volume abnormalities in AD and/or MCI patients compared to cognitively normal controls. Results From a total of 46 selected articles, 35 VBM studies reported GM volume reductions in the frontal lobe. The frontal subregions, where most of the volume reductions were reported, included the inferior, superior and middle frontal gyri, as well as the anterior cingulate gyrus. We also found studies in which reduced frontal GM was detected in MCI patients who converted to AD. In a minority of studies, correlations between frontal GM volumes and behavioural changes or cognitive deficits in AD patients were investigated, with variable findings. Conclusion Results of VBM studies indicate that the frontal lobe should be regarded as an important brain area when investigating GM volume deficits in association with AD. Frontal GM loss might not be a feature specific to late AD only. Future VBM studies involving large AD samples are warranted to further investigate correlations between frontal volume deficits and both cognitive impairment and neuropsychiatric symptoms.
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Affiliation(s)
- Luís Gustavo Ribeiro
- BSc, Molecular Sciences Program, Universidade de São Paulo, São Paulo SP, Brazil
| | - Geraldo Busatto
- PhD, Department of Psychiatry, Faculdade de Medicina da Universidade de São Paulo, São Paulo SP, Brazil
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Abstract
OBJECTIVES Behavioral variant frontotemporal dementia (bvFTD) is characterized by early atrophy in the frontotemporoinsular regions. These regions overlap with networks that are engaged in social cognition-executive functions, two hallmarks deficits of bvFTD. We examine (i) whether Network Centrality (a graph theory metric that measures how important a node is in a brain network) in the frontotemporoinsular network is disrupted in bvFTD, and (ii) the level of involvement of this network in social-executive performance. METHODS Patients with probable bvFTD, healthy controls, and frontoinsular stroke patients underwent functional MRI resting-state recordings and completed social-executive behavioral measures. RESULTS Relative to the controls and the stroke group, the bvFTD patients presented decreased Network Centrality. In addition, this measure was associated with social cognition and executive functions. To test the specificity of these results for the Network Centrality of the frontotemporoinsular network, we assessed the main areas from six resting-state networks. No group differences or behavioral associations were found in these networks. Finally, Network Centrality and behavior distinguished bvFTD patients from the other groups with a high classification rate. CONCLUSIONS bvFTD selectively affects Network Centrality in the frontotemporoinsular network, which is associated with high-level social and executive profile.
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Masdeu JC, Pascual B. Genetic and degenerative disorders primarily causing dementia. HANDBOOK OF CLINICAL NEUROLOGY 2016; 135:525-564. [PMID: 27432682 DOI: 10.1016/b978-0-444-53485-9.00026-x] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/23/2022]
Abstract
Neuroimaging comprises a powerful set of instruments to diagnose the different causes of dementia, clarify their neurobiology, and monitor their treatment. Magnetic resonance imaging (MRI) depicts volume changes with neurodegeneration and inflammation, as well as abnormalities in functional and structural connectivity. MRI arterial spin labeling allows for the quantification of regional cerebral blood flow, characteristically altered in Alzheimer's disease, diffuse Lewy-body disease, and the frontotemporal dementias. Positron emission tomography allows for the determination of regional metabolism, with similar abnormalities as flow, and for the measurement of β-amyloid and abnormal tau deposition in the brain, as well as regional inflammation. These instruments allow for the quantification in vivo of most of the pathologic features observed in disorders causing dementia. Importantly, they allow for the longitudinal study of these abnormalities, having revealed, for instance, that the deposition of β-amyloid in the brain can antecede by decades the onset of dementia. Thus, a therapeutic window has been opened and the efficacy of immunotherapies directed at removing β-amyloid from the brain of asymptomatic individuals is currently being tested. Tau and inflammation imaging, still in their infancy, combined with genomics, should provide powerful insights into these disorders and facilitate their treatment.
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Affiliation(s)
- Joseph C Masdeu
- Department of Neurology, Houston Methodist Hospital, Houston, TX, USA.
| | - Belen Pascual
- Department of Neurology, Houston Methodist Hospital, Houston, TX, USA
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Filippi M, Agosta F, Ferraro PM. Charting Frontotemporal Dementia: From Genes to Networks. J Neuroimaging 2015; 26:16-27. [PMID: 26617288 DOI: 10.1111/jon.12316] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/07/2015] [Revised: 10/19/2015] [Accepted: 10/20/2015] [Indexed: 12/11/2022] Open
Abstract
Frontotemporal dementia (FTD) is a genetically and clinically heterogeneous syndrome that is characterized by overlapping clinical symptoms involving behavior, personality, language and/or motor functions and degeneration of the frontal and temporal lobes. The term frontotemporal lobar degeneration (FTLD) is used to describe the proteinopathies associated with clinical FTD. Emerging evidence from network-based neuroimaging studies, such as resting state functional MRI and diffusion tensor MRI studies, have implicated specific large-scale brain networks in the pathogenesis of FTD syndromes, suggesting a new paradigm for explaining the distributed and heterogeneous spreading patterns of pathological proteins in FTLD. In this review, we overview recent research on the study of FTD syndromes as connectivity disorders in symptomatic patients as well as genotype-specific changes in asymptomatic FTD-related gene mutation carriers. Characterizing brain network breakdown in these subjects using neuroimaging may help anticipate the diagnosis and perhaps prevent the devastating impact of FTD.
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Affiliation(s)
- Massimo Filippi
- Neuroimaging Research Unit, Institute of Experimental Neurology, Division of Neuroscience, San Raffaele Scientific Institute, Vita-Salute San Raffaele University, Milan, Italy.,Department of Neurology, Institute of Experimental Neurology, Division of Neuroscience, San Raffaele Scientific Institute, Vita-Salute San Raffaele University, Milan, Italy
| | - Federica Agosta
- Neuroimaging Research Unit, Institute of Experimental Neurology, Division of Neuroscience, San Raffaele Scientific Institute, Vita-Salute San Raffaele University, Milan, Italy
| | - Pilar M Ferraro
- Neuroimaging Research Unit, Institute of Experimental Neurology, Division of Neuroscience, San Raffaele Scientific Institute, Vita-Salute San Raffaele University, Milan, Italy
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Yang Q, Guo QH, Bi YC. The brain connectivity basis of semantic dementia: a selective review. CNS Neurosci Ther 2015; 21:784-92. [PMID: 26336932 DOI: 10.1111/cns.12449] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/28/2015] [Revised: 08/07/2015] [Accepted: 08/07/2015] [Indexed: 01/19/2023] Open
Abstract
Semantic dementia (SD) is a neurodegenerative disorder characterized by the progressive loss of semantic memory and conceptual knowledge, coupled with asymmetric local brain atrophy concentrated in the anterior temporal lobe. Recent developments in neuroimaging techniques, especially the emergence of the "human connectomics," have made possible the study of the brain's functional and structural connections and the topological properties of the brain networks. Recent studies applying these techniques have shown that SD manifests extensive structural and functional connectivity alterations, providing important insights into the pathogenesis of SD and the neural basis of semantic memory in general. In this review, we present and discuss the existing findings about the brain connectivity changes in SD and how they might be related to the various behavioral deficits associated with this disorder and propose important unanswered questions that warrant further investigation.
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Affiliation(s)
- Qing Yang
- Department of Neurology, Huashan Hospital, Fudan University, Shanghai, China
| | - Qi-Hao Guo
- Department of Neurology, Huashan Hospital, Fudan University, Shanghai, China
| | - Yan-Chao Bi
- State Key Laboratory of Cognitive Neuroscience and Learning & IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China
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Agosta F, Galantucci S, Magnani G, Marcone A, Martinelli D, Antonietta Volontè M, Riva N, Iannaccone S, Ferraro PM, Caso F, Chiò A, Comi G, Falini A, Filippi M. MRI signatures of the frontotemporal lobar degeneration continuum. Hum Brain Mapp 2015; 36:2602-14. [PMID: 25821176 DOI: 10.1002/hbm.22794] [Citation(s) in RCA: 34] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/12/2014] [Revised: 02/16/2015] [Accepted: 03/11/2015] [Indexed: 11/05/2022] Open
Abstract
OBJECTIVE To identify overlapping and unique grey (GM) and white matter (WM) signatures within the frontotemporal lobar degeneration (FTLD) continuum, and discriminate likely FTLD-TAU and FTLD-TDP patients using structural and diffusion tensor (DT) magnetic resonance imaging (MRI). METHODS T1-weighted and DT MRI were collected from 121 subjects: 35 motor neuron disease (MND), 14 behavioral variant of frontotemporal dementia, 12 semantic and 11 nonfluent primary progressive aphasia, 21 progressive supranuclear palsy syndrome patients, and 28 healthy controls. Patterns of GM atrophy were established using voxel-based morphometry. Tract-based spatial statistics was used to perform a WM voxelwise analysis of mean diffusivity and fractional anisotropy. RESULTS In all clinical FTLD phenotypes, the pattern of WM damage was more distributed than that of GM atrophy. All patient groups, with the exception of MND cases with a pure motor syndrome, shared a focal GM atrophy centered around the dorsolateral and medial frontal cortex and a largely overlapping pattern of WM damage involving the genu and body of the corpus callosum and ventral frontotemporal and dorsal frontoparietal WM pathways. Surrounding this common area, phenotype (symptom)-specific GM and WM regions of damage were found in each group. CONCLUSIONS In the FTLD spectrum, WM disruption is more severe than GM damage. Frontal cortex and WM pathways represent the common target of neurodegeneration in these conditions. The topographic pattern of damage supports a "prion-like" protein propagation through WM connections as underlying mechanism of the stereotyped progression of FTLD.
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Affiliation(s)
| | | | - Giuseppe Magnani
- Department of Neurology, Institute of Experimental Neurology, Division of Neuroscience
| | - Alessandra Marcone
- Department of Clinical Neurosciences, San Raffaele Scientific Institute, Vita-Salute San Raffaele University, Milan, Italy
| | | | | | - Nilo Riva
- Department of Neurology, Institute of Experimental Neurology, Division of Neuroscience
| | - Sandro Iannaccone
- Department of Clinical Neurosciences, San Raffaele Scientific Institute, Vita-Salute San Raffaele University, Milan, Italy
| | | | | | - Adriano Chiò
- Department of Neuroscience, ALS Center, "Rita Levi Montalcini" University of Torino, Torino, Italy
| | - Giancarlo Comi
- Department of Neurology, Institute of Experimental Neurology, Division of Neuroscience
| | - Andrea Falini
- Department of Neuroradiology and CERMAC, San Raffaele Scientific Institute, Vita-Salute San Raffaele University, Milan, Italy
| | - Massimo Filippi
- Neuroimaging Research Unit.,Department of Neurology, Institute of Experimental Neurology, Division of Neuroscience
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Agosta F, Ferraro PM, Canu E, Copetti M, Galantucci S, Magnani G, Marcone A, Valsasina P, Sodero A, Comi G, Falini A, Filippi M. Differentiation between Subtypes of Primary Progressive Aphasia by Using Cortical Thickness and Diffusion-Tensor MR Imaging Measures. Radiology 2015; 276:219-27. [PMID: 25734554 DOI: 10.1148/radiol.15141869] [Citation(s) in RCA: 22] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/11/2022]
Abstract
PURPOSE To test a multimodal magnetic resonance (MR) imaging-based approach composed of cortical thickness and white matter (WM) damage metrics to discriminate between variants of primary progressive aphasia (PPA) that are nonfluent and/or agrammatic (NFVPPA) and semantic (SVPPA). MATERIALS AND METHODS This study was approved by the local ethics committees on human studies, and written informed consent from all patients was obtained before their enrollment. T1-weighted and diffusion-tensor (DT) MR images were obtained from 13 NFVPPA patients, 13 SVPPA patients, and 23 healthy control participants. Cortical thickness and DT MR imaging indices from the long-associative and interhemispheric WM tracts were obtained. A random forest (RF) analysis was used to identify the image features associated with each clinical syndrome. Individual patient classification was performed by using receiver operator characteristic curve analysis with cortical thickness, DT MR imaging, and a combination of the two modalities. RESULTS RF analysis showed that the best markers to differentiate the two PPA variants at an individual patient level among cortical thickness and DT MR imaging metrics were diffusivity abnormalities of the left inferior longitudinal and uncinate fasciculi and cortical thickness measures of the left temporal pole and inferior frontal gyrus. A combination of cortical thickness and DT MR imaging measures (the so-called gray-matter-and-WM model) was able to distinguish patients with NFVPPA and SVPPA with the following classification pattern: area under the curve, 0.91; accuracy, 0.89; sensitivity, 0.92; specificity, 0.85. Leave-one-out analysis demonstrated that the gray matter and WM model is more robust than the single MR modality models to distinguish PPA variants (accuracy was 0.86, 0.73, and 0.68 for the gray matter and WM model, the gray matter-only model, and the WM-only model, respectively). CONCLUSION A combination of structural and DT MR imaging metrics may provide a quantitative procedure to distinguish NFVPPA and SVPPA patients at an individual patient level. The discrimination accuracies obtained suggest that the gray matter and WM model is potentially relevant for the differential diagnosis of the PPA variants in clinical practice.
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Affiliation(s)
- Federica Agosta
- From the Neuroimaging Research Unit (F.A., P.M.F., E.C., S.G., P.V., A.S., M.F.), Department of Neurology, Institute of Experimental Neurology (G.M., G.C., M.F.), Department of Clinical Neurosciences (A.M.), and Department of Neuroradiology and CERMAC, Division of Neuroscience (A.F.), San Raffaele Scientific Institute, Vita-Salute San Raffaele University, Via Olgettina 60, 20132 Milan, Italy; and Biostatistics Unit, IRCCS-Ospedale Casa Sollievo della Sofferenza, San Giovanni Rotondo, Foggia, Italy (M.C.)
| | - Pilar M Ferraro
- From the Neuroimaging Research Unit (F.A., P.M.F., E.C., S.G., P.V., A.S., M.F.), Department of Neurology, Institute of Experimental Neurology (G.M., G.C., M.F.), Department of Clinical Neurosciences (A.M.), and Department of Neuroradiology and CERMAC, Division of Neuroscience (A.F.), San Raffaele Scientific Institute, Vita-Salute San Raffaele University, Via Olgettina 60, 20132 Milan, Italy; and Biostatistics Unit, IRCCS-Ospedale Casa Sollievo della Sofferenza, San Giovanni Rotondo, Foggia, Italy (M.C.)
| | - Elisa Canu
- From the Neuroimaging Research Unit (F.A., P.M.F., E.C., S.G., P.V., A.S., M.F.), Department of Neurology, Institute of Experimental Neurology (G.M., G.C., M.F.), Department of Clinical Neurosciences (A.M.), and Department of Neuroradiology and CERMAC, Division of Neuroscience (A.F.), San Raffaele Scientific Institute, Vita-Salute San Raffaele University, Via Olgettina 60, 20132 Milan, Italy; and Biostatistics Unit, IRCCS-Ospedale Casa Sollievo della Sofferenza, San Giovanni Rotondo, Foggia, Italy (M.C.)
| | - Massimiliano Copetti
- From the Neuroimaging Research Unit (F.A., P.M.F., E.C., S.G., P.V., A.S., M.F.), Department of Neurology, Institute of Experimental Neurology (G.M., G.C., M.F.), Department of Clinical Neurosciences (A.M.), and Department of Neuroradiology and CERMAC, Division of Neuroscience (A.F.), San Raffaele Scientific Institute, Vita-Salute San Raffaele University, Via Olgettina 60, 20132 Milan, Italy; and Biostatistics Unit, IRCCS-Ospedale Casa Sollievo della Sofferenza, San Giovanni Rotondo, Foggia, Italy (M.C.)
| | - Sebastiano Galantucci
- From the Neuroimaging Research Unit (F.A., P.M.F., E.C., S.G., P.V., A.S., M.F.), Department of Neurology, Institute of Experimental Neurology (G.M., G.C., M.F.), Department of Clinical Neurosciences (A.M.), and Department of Neuroradiology and CERMAC, Division of Neuroscience (A.F.), San Raffaele Scientific Institute, Vita-Salute San Raffaele University, Via Olgettina 60, 20132 Milan, Italy; and Biostatistics Unit, IRCCS-Ospedale Casa Sollievo della Sofferenza, San Giovanni Rotondo, Foggia, Italy (M.C.)
| | - Giuseppe Magnani
- From the Neuroimaging Research Unit (F.A., P.M.F., E.C., S.G., P.V., A.S., M.F.), Department of Neurology, Institute of Experimental Neurology (G.M., G.C., M.F.), Department of Clinical Neurosciences (A.M.), and Department of Neuroradiology and CERMAC, Division of Neuroscience (A.F.), San Raffaele Scientific Institute, Vita-Salute San Raffaele University, Via Olgettina 60, 20132 Milan, Italy; and Biostatistics Unit, IRCCS-Ospedale Casa Sollievo della Sofferenza, San Giovanni Rotondo, Foggia, Italy (M.C.)
| | - Alessandra Marcone
- From the Neuroimaging Research Unit (F.A., P.M.F., E.C., S.G., P.V., A.S., M.F.), Department of Neurology, Institute of Experimental Neurology (G.M., G.C., M.F.), Department of Clinical Neurosciences (A.M.), and Department of Neuroradiology and CERMAC, Division of Neuroscience (A.F.), San Raffaele Scientific Institute, Vita-Salute San Raffaele University, Via Olgettina 60, 20132 Milan, Italy; and Biostatistics Unit, IRCCS-Ospedale Casa Sollievo della Sofferenza, San Giovanni Rotondo, Foggia, Italy (M.C.)
| | - Paola Valsasina
- From the Neuroimaging Research Unit (F.A., P.M.F., E.C., S.G., P.V., A.S., M.F.), Department of Neurology, Institute of Experimental Neurology (G.M., G.C., M.F.), Department of Clinical Neurosciences (A.M.), and Department of Neuroradiology and CERMAC, Division of Neuroscience (A.F.), San Raffaele Scientific Institute, Vita-Salute San Raffaele University, Via Olgettina 60, 20132 Milan, Italy; and Biostatistics Unit, IRCCS-Ospedale Casa Sollievo della Sofferenza, San Giovanni Rotondo, Foggia, Italy (M.C.)
| | - Alessandro Sodero
- From the Neuroimaging Research Unit (F.A., P.M.F., E.C., S.G., P.V., A.S., M.F.), Department of Neurology, Institute of Experimental Neurology (G.M., G.C., M.F.), Department of Clinical Neurosciences (A.M.), and Department of Neuroradiology and CERMAC, Division of Neuroscience (A.F.), San Raffaele Scientific Institute, Vita-Salute San Raffaele University, Via Olgettina 60, 20132 Milan, Italy; and Biostatistics Unit, IRCCS-Ospedale Casa Sollievo della Sofferenza, San Giovanni Rotondo, Foggia, Italy (M.C.)
| | - Giancarlo Comi
- From the Neuroimaging Research Unit (F.A., P.M.F., E.C., S.G., P.V., A.S., M.F.), Department of Neurology, Institute of Experimental Neurology (G.M., G.C., M.F.), Department of Clinical Neurosciences (A.M.), and Department of Neuroradiology and CERMAC, Division of Neuroscience (A.F.), San Raffaele Scientific Institute, Vita-Salute San Raffaele University, Via Olgettina 60, 20132 Milan, Italy; and Biostatistics Unit, IRCCS-Ospedale Casa Sollievo della Sofferenza, San Giovanni Rotondo, Foggia, Italy (M.C.)
| | - Andrea Falini
- From the Neuroimaging Research Unit (F.A., P.M.F., E.C., S.G., P.V., A.S., M.F.), Department of Neurology, Institute of Experimental Neurology (G.M., G.C., M.F.), Department of Clinical Neurosciences (A.M.), and Department of Neuroradiology and CERMAC, Division of Neuroscience (A.F.), San Raffaele Scientific Institute, Vita-Salute San Raffaele University, Via Olgettina 60, 20132 Milan, Italy; and Biostatistics Unit, IRCCS-Ospedale Casa Sollievo della Sofferenza, San Giovanni Rotondo, Foggia, Italy (M.C.)
| | - Massimo Filippi
- From the Neuroimaging Research Unit (F.A., P.M.F., E.C., S.G., P.V., A.S., M.F.), Department of Neurology, Institute of Experimental Neurology (G.M., G.C., M.F.), Department of Clinical Neurosciences (A.M.), and Department of Neuroradiology and CERMAC, Division of Neuroscience (A.F.), San Raffaele Scientific Institute, Vita-Salute San Raffaele University, Via Olgettina 60, 20132 Milan, Italy; and Biostatistics Unit, IRCCS-Ospedale Casa Sollievo della Sofferenza, San Giovanni Rotondo, Foggia, Italy (M.C.)
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Magnin E, Teichmann M, Martinaud O, Moreaud O, Ryff I, Belliard S, Pariente J, Moulin T, Vandel P, Démonet JF. Particularités du variant logopénique au sein des aphasies progressives primaires. Rev Neurol (Paris) 2015; 171:16-30. [DOI: 10.1016/j.neurol.2014.08.004] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/30/2014] [Revised: 07/16/2014] [Accepted: 08/29/2014] [Indexed: 11/26/2022]
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Abstract
Background Spinocerebellar ataxias (SCAs) are autosomal-dominant neurodegenerative diseases that are clinically and genetically heterogeneous. SCAs are characterized by a range of neurological symptoms. SCA12 is an autosomal-dominant (AD) ataxia caused by a CAG repeat expansion mutation in a presumed promoter region of the gene PPP2R2B in a non-coding region on chromosome 5q32. This study sought to determine changes in different positions in a single Uyghur SCA12 pedigree by measuring the apparent diffusion coefficient (ADC) and fractional anisotropy (FA). Material/Methods A single Uyghur pedigree was collected and was confirmed to possess SCA12 by genetic diagnosis, among which 13 cases were patients and 54 cases were “healthy” individuals. Five patients were presymptomatic and 15 individuals selected as a control group were examination in the same time. DTI was performed on a 1.5T scanner, with b=1000 s/mm2 and 15 directions. ADC and FA were measured by regions of interest positioned in the corticospinal tract at the level of the pons (pons), superior peduncle (SCP), middle cerebellar peduncle (MCP), cerebellar cortex (CeC), cerebral cortex (CC), and cerebellar vermis (CV) white matter. Results Compared with the controls, the ADC was significantly elevated in the CeC, SCP, CC, and CV regions in SCA12 patients. The FA significantly decreased in the CC region in SCA12 patients and the CC and CV regions in SCA12 presymptomatic patients. The course of the disease, SARA score, and ADC values in CV showed highly positive correlations. Conclusions SCA12 pedigree patients exhibited microstructural damage in the brain white matter. The damage in white matter fiber may first occur in the CC and CV regions in SCA12 presymptomatic patients. The ADC values in the CV region could reflect disease severity in SCA12 patients.
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Affiliation(s)
- Haitao Li
- Department of Neurology, First Affiliated Hospital, Xinjiang Medical University, Urumuqi, China (mainland)
| | - Jingjing Ma
- Department of Neurology, First Affiliated Hospital, Xinjiang Medical University, Urumuqi, China (mainland)
| | - Xiaoning Zhang
- Department of Neurology, First Affiliated Hospital, Xinjiang Medical University, Urumuqi, China (mainland)
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Abstract
In primary progressive aphasia (PPA), speech and language difficulties are caused by neurodegeneration of specific brain networks. In the nonfluent/agrammatic variant (nfvPPA), motor speech and grammatical deficits are associated with atrophy in a left fronto-insular-striatal network previously implicated in speech production. In vivo dissection of the crossing white matter (WM) tracts within this "speech production network" is complex and has rarely been performed in health or in PPA. We hypothesized that damage to these tracts would be specific to nfvPPA and would correlate with differential aspects of the patients' fluency abilities. We prospectively studied 25 PPA and 21 healthy individuals who underwent extensive cognitive testing and 3 T MRI. Using residual bootstrap Q-ball probabilistic tractography on high angular resolution diffusion-weighted imaging (HARDI), we reconstructed pathways connecting posterior inferior frontal, inferior premotor, insula, supplementary motor area (SMA) complex, striatum, and standard ventral and dorsal language pathways. We extracted tract-specific diffusion tensor imaging (DTI) metrics to assess changes across PPA variants and perform brain-behavioral correlations. Significant WM changes in the left intrafrontal and frontostriatal pathways were found in nfvPPA, but not in the semantic or logopenic variants. Correlations between tract-specific DTI metrics with cognitive scores confirmed the specific involvement of this anterior-dorsal network in fluency and suggested a preferential role of a posterior premotor-SMA pathway in motor speech. This study shows that left WM pathways connecting the speech production network are selectively damaged in nfvPPA and suggests that different tracts within this system are involved in subcomponents of fluency. These findings emphasize the emerging role of diffusion imaging in the differential diagnosis of neurodegenerative diseases.
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Ibanez A, Richly P, Roca M, Manes F. Methodological considerations regarding cognitive interventions in dementia. Front Aging Neurosci 2014; 6:212. [PMID: 25165450 PMCID: PMC4131264 DOI: 10.3389/fnagi.2014.00212] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/16/2014] [Accepted: 08/01/2014] [Indexed: 11/13/2022] Open
Affiliation(s)
- Agustín Ibanez
- Laboratory of Experimental Psychology and Neuroscience (LPEN), Institute of Cognitive Neurology (INECO), Favaloro University , Buenos Aires , Argentina ; UDP-INECO Foundation Core on Neuroscience (UIFCoN), Diego Portales University , Santiago , Chile ; National Scientific and Technical Research Council (CONICET) , Buenos Aires , Argentina ; Universidad Autónoma del Caribe , Barranquilla , Colombia ; Australian Research Council Centre of Excellence in Cognition and its Disorders , Sydney, NSW , Australia
| | - Pablo Richly
- Laboratory of Experimental Psychology and Neuroscience (LPEN), Institute of Cognitive Neurology (INECO), Favaloro University , Buenos Aires , Argentina ; Australian Research Council Centre of Excellence in Cognition and its Disorders , Sydney, NSW , Australia
| | - María Roca
- Laboratory of Experimental Psychology and Neuroscience (LPEN), Institute of Cognitive Neurology (INECO), Favaloro University , Buenos Aires , Argentina ; UDP-INECO Foundation Core on Neuroscience (UIFCoN), Diego Portales University , Santiago , Chile
| | - Facundo Manes
- Laboratory of Experimental Psychology and Neuroscience (LPEN), Institute of Cognitive Neurology (INECO), Favaloro University , Buenos Aires , Argentina ; UDP-INECO Foundation Core on Neuroscience (UIFCoN), Diego Portales University , Santiago , Chile ; National Scientific and Technical Research Council (CONICET) , Buenos Aires , Argentina ; Australian Research Council Centre of Excellence in Cognition and its Disorders , Sydney, NSW , Australia
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Cardenas-Blanco A, Machts J, Acosta-Cabronero J, Kaufmann J, Abdulla S, Kollewe K, Petri S, Heinze HJ, Dengler R, Vielhaber S, Nestor PJ. Central white matter degeneration in bulbar- and limb-onset amyotrophic lateral sclerosis. J Neurol 2014; 261:1961-7. [PMID: 25059391 DOI: 10.1007/s00415-014-7434-4] [Citation(s) in RCA: 25] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/07/2014] [Revised: 07/03/2014] [Accepted: 07/04/2014] [Indexed: 11/30/2022]
Abstract
Previous studies using diffusion tensor imaging (DTI) have examined for differences between bulbar- and limb-onset amyotrophic lateral sclerosis (ALS). Findings between studies have been markedly inconsistent, though possibly as a consequence of poor matching for confounding variables. To address this problem, this study contrasted the DTI profiles of limb-onset (ALS-L) and bulbar-onset (ALS-B) in groups that were tightly matched for the potential confounding effects of power, age, cognitive impairment and motor dysfunction. 14 ALS-L and 14 ALS-B patients were selected from a large prospective study so as to be matched on clinical and demographic features. All subjects, including 29 controls, underwent neuropsychological and neurological assessment. Tract-based spatial statistics and region of interest techniques were used to analyse fractional anisotropy (FA), mean diffusivity (MD), radial diffusivity (RD) and axial diffusivity (λ₁). Extensive bilateral FA and RD changes along the corticospinal tract were found in ALS-B compared to controls, p (corrected) <0.05; a similar distribution was seen for ALS-L at a less stringent statistical threshold. ROI analyses also showed more significant changes in ALS-B than ALS-L when each was compared to controls; for FA, MD and RD the changes reached statistical significance in the direct contrast between the two patient groups. With careful matching for confounding factors, the results suggest that ALS-B is associated with greater central white matter degeneration than ALS-L, possibly contributing to the known worse prognosis of ALS-B. The study, however, found no evidence that the spatial distribution of white matter degeneration differs between these groups.
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Affiliation(s)
- Arturo Cardenas-Blanco
- German Center for Neurodegenerative Diseases (DZNE), Leipziger Strasse 44, 39120, Magdeburg, Germany,
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Tovar-Moll F, de Oliveira-Souza R, Bramati IE, Zahn R, Cavanagh A, Tierney M, Moll J, Grafman J. White matter tract damage in the behavioral variant of frontotemporal and corticobasal dementia syndromes. PLoS One 2014; 9:e102656. [PMID: 25054218 PMCID: PMC4108323 DOI: 10.1371/journal.pone.0102656] [Citation(s) in RCA: 23] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/26/2014] [Accepted: 06/22/2014] [Indexed: 11/24/2022] Open
Abstract
The phenotypes of the behavioral variant of frontotemporal dementia and the corticobasal syndrome present considerable clinical and anatomical overlap. The respective patterns of white matter damage in these syndromes have not been directly contrasted. Beyond cortical involvement, damage to white matter pathways may critically contribute to both common and specific symptoms in both conditions. Here we assessed patients with the behavioral variant of frontotemporal dementia and corticobasal syndrome with whole-brain diffusion tensor imaging to identify the white matter networks underlying these pathologies. Twenty patients with the behavioral variant of frontotemporal dementia, 19 with corticobasal syndrome, and 15 healthy controls were enrolled in the study. Differences in tract integrity between (i) patients and controls, and (ii) patients with the corticobasal syndrome and the behavioral variant of frontotemporal dementia were assessed with whole brain tract-based spatial statistics and analyses of regions of interest. Behavioral variant of frontotemporal dementia and the corticobasal syndrome shared a pattern of bilaterally decreased white matter integrity in the anterior commissure, genu and body of the corpus callosum, corona radiata and in the long intrahemispheric association pathways. Patients with the behavioral variant of frontotemporal dementia showed greater damage to the uncinate fasciculus, genu of corpus callosum and forceps minor. In contrast, corticobasal syndrome patients had greater damage to the midbody of the corpus callosum and perirolandic corona radiata. Whereas several compact white matter pathways were damaged in both the behavioral variant of frontotemporal dementia and corticobasal syndrome, the distribution and degree of white matter damage differed between them. These findings concur with the distinctive clinical manifestations of these conditions and may improve the in vivo neuroanatomical and diagnostic characterization of these disorders.
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Affiliation(s)
- Fernanda Tovar-Moll
- D'Or Institute for Research and Education (IDOR), Rio de Janeiro, Brazil
- Institute of Biomedical Sciences and National Center of Structural Biology and Bioimaging (CENABIO), Federal University of Rio de Janeiro, Rio de Janeiro, Brazil
| | | | - Ivanei Edson Bramati
- D'Or Institute for Research and Education (IDOR), Rio de Janeiro, Brazil
- Institute of Biomedical Sciences and National Center of Structural Biology and Bioimaging (CENABIO), Federal University of Rio de Janeiro, Rio de Janeiro, Brazil
| | - Roland Zahn
- D'Or Institute for Research and Education (IDOR), Rio de Janeiro, Brazil
- Institute of Psychiatry at King's College, De Crespigny Park, London, United Kingdom
| | - Alyson Cavanagh
- National Institute of Neurological Disorders and Stroke, National Institute of Health (NIH), Bethesda, Maryland, United States of America
| | - Michael Tierney
- National Institute of Neurological Disorders and Stroke, National Institute of Health (NIH), Bethesda, Maryland, United States of America
| | - Jorge Moll
- D'Or Institute for Research and Education (IDOR), Rio de Janeiro, Brazil
| | - Jordan Grafman
- National Institute of Neurological Disorders and Stroke, National Institute of Health (NIH), Bethesda, Maryland, United States of America
- Rehabilitation Institute of Chicago, Chicago, Illinois, United States of America
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Burrell JR, Hodges JR, Rowe JB. Cognition in corticobasal syndrome and progressive supranuclear palsy: A review. Mov Disord 2014; 29:684-93. [DOI: 10.1002/mds.25872] [Citation(s) in RCA: 112] [Impact Index Per Article: 11.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/15/2014] [Revised: 02/18/2014] [Accepted: 02/27/2014] [Indexed: 11/12/2022] Open
Affiliation(s)
- James R. Burrell
- Neuroscience Research Australia; Sydney Australia
- University of New South Wales; Sydney Australia
| | - John R. Hodges
- Neuroscience Research Australia; Sydney Australia
- University of New South Wales; Sydney Australia
| | - James B. Rowe
- Department of Clinical Neurosciences; Cambridge University; Cambridge United Kingdom
- Behavioral and Clinical Neuroscience Institute; Cambridge United Kingdom
- Medical Research Council; Cognition and Brain Sciences Unit; Cambridge United Kingdom
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Kong Y, Wang D, Shi L, Hui SCN, Chu WCW. Adaptive distance metric learning for diffusion tensor image segmentation. PLoS One 2014; 9:e92069. [PMID: 24651858 PMCID: PMC3961296 DOI: 10.1371/journal.pone.0092069] [Citation(s) in RCA: 9] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/15/2013] [Accepted: 02/17/2014] [Indexed: 11/23/2022] Open
Abstract
High quality segmentation of diffusion tensor images (DTI) is of key interest in biomedical research and clinical application. In previous studies, most efforts have been made to construct predefined metrics for different DTI segmentation tasks. These methods require adequate prior knowledge and tuning parameters. To overcome these disadvantages, we proposed to automatically learn an adaptive distance metric by a graph based semi-supervised learning model for DTI segmentation. An original discriminative distance vector was first formulated by combining both geometry and orientation distances derived from diffusion tensors. The kernel metric over the original distance and labels of all voxels were then simultaneously optimized in a graph based semi-supervised learning approach. Finally, the optimization task was efficiently solved with an iterative gradient descent method to achieve the optimal solution. With our approach, an adaptive distance metric could be available for each specific segmentation task. Experiments on synthetic and real brain DTI datasets were performed to demonstrate the effectiveness and robustness of the proposed distance metric learning approach. The performance of our approach was compared with three classical metrics in the graph based semi-supervised learning framework.
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Affiliation(s)
- Youyong Kong
- Department of Imaging and Interventional Radiology, The Chinese University of Hong Kong, Shatin, New Territories, Hong Kong, China
- Research Center for Medical Image Computing, The Chinese University of Hong Kong, Shatin, New Territories, Hong Kong, China
| | - Defeng Wang
- Department of Imaging and Interventional Radiology, The Chinese University of Hong Kong, Shatin, New Territories, Hong Kong, China
- Research Center for Medical Image Computing, The Chinese University of Hong Kong, Shatin, New Territories, Hong Kong, China
- The Chinese University of Hong Kong Shenzhen Research Institute, Shenzhen, China
- Department of Biomedical Engineering and Shun Hing Institute of Advanced Engineering, The Chinese University of Hong Kong, Shatin, New Territories, Hong Kong, China
- * E-mail: (DW); (WCWC)
| | - Lin Shi
- Department of Imaging and Interventional Radiology, The Chinese University of Hong Kong, Shatin, New Territories, Hong Kong, China
- Research Center for Medical Image Computing, The Chinese University of Hong Kong, Shatin, New Territories, Hong Kong, China
- Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China
| | - Steve C. N. Hui
- Department of Imaging and Interventional Radiology, The Chinese University of Hong Kong, Shatin, New Territories, Hong Kong, China
- Research Center for Medical Image Computing, The Chinese University of Hong Kong, Shatin, New Territories, Hong Kong, China
| | - Winnie C. W. Chu
- Department of Imaging and Interventional Radiology, The Chinese University of Hong Kong, Shatin, New Territories, Hong Kong, China
- Research Center for Medical Image Computing, The Chinese University of Hong Kong, Shatin, New Territories, Hong Kong, China
- The Chinese University of Hong Kong Shenzhen Research Institute, Shenzhen, China
- * E-mail: (DW); (WCWC)
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Clinical, cognitive, and behavioural correlates of white matter damage in progressive supranuclear palsy. J Neurol 2014; 261:913-24. [PMID: 24599641 DOI: 10.1007/s00415-014-7301-3] [Citation(s) in RCA: 38] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/27/2014] [Revised: 02/21/2014] [Accepted: 02/22/2014] [Indexed: 10/25/2022]
Abstract
White matter (WM) tract alterations were assessed in patients with progressive supranuclear palsy (PSP) relative to healthy controls and patients with idiopathic Parkinson's disease (PD) to explore the relationship of WM tract damage with clinical disease severity, performance on cognitive tests, and apathy. 37 PSP patients, 41 PD patients, and 34 healthy controls underwent an MRI scan and clinical testing to evaluate physical disability, cognitive impairment, and apathy. In PSP, the contribution of WM tract damage to global disease severity and cognitive and behavioural disturbances was assessed using Random Forest analysis. Relative to controls, PSP patients showed diffusion tensor (DT) MRI abnormalities of the corpus callosum, superior cerebellar peduncle (SCP), cingulum and uncinate fasciculus bilaterally, and right inferior longitudinal fasciculus. Corpus callosum and SCP DT MRI measures distinguished PSP from PD patients with high accuracy (area under the curve ranging from 0.89 to 0.72). In PSP, DT MRI metrics of the corpus callosum and superior cerebellar peduncles were the best predictors of global disease severity scale scores. DT MRI metrics of the corpus callosum, right superior longitudinal and inferior longitudinal fasciculus, and left uncinate were the best predictors of executive dysfunction. In PSP, apathy severity was related to the damage to the corpus callosum, right superior longitudinal, and uncinate fasciculi. In conclusion, WM tract damage contributes to the motor, cognitive, and behavioural deficits in PSP. DT MRI offers markers for PSP diagnosis, assessment, and monitoring.
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Golbe LI. The tau of PSP: a long road to treatment. Mov Disord 2014; 29:431-4. [PMID: 24585428 DOI: 10.1002/mds.25855] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/26/2014] [Accepted: 02/03/2014] [Indexed: 11/10/2022] Open
Affiliation(s)
- Lawrence I Golbe
- Department of Neurology, Rutgers Robert Wood Johnson Medical School, New Brunswick, New Jersey, USA
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