101
|
Debnath A, Hariharan H, Nanga RPR, Reddy R, Singh A. Glutamate-Weighted CEST Contrast After Removal of Magnetization Transfer Effect in Human Brain and Rat Brain with Tumor. Mol Imaging Biol 2020; 22:1087-1101. [DOI: 10.1007/s11307-019-01465-9] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/18/2022]
|
102
|
Bontempi P, Cisterna B, Malatesta M, Nicolato E, Mucignat-Caretta C, Zancanaro C. A smaller olfactory bulb in a mouse model of Down syndrome. Acta Neurobiol Exp (Wars) 2020. [DOI: 10.21307/ane-2020-034] [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]
|
103
|
Gregory S, Johnson E, Byrne LM, Rodrigues FB, Henderson A, Moss J, Thomas D, Zhang H, De Vita E, Tabrizi SJ, Rees G, Scahill RI, Wild EJ. Characterizing White Matter in Huntington's Disease. Mov Disord Clin Pract 2020; 7:52-60. [PMID: 31970212 PMCID: PMC6962665 DOI: 10.1002/mdc3.12866] [Citation(s) in RCA: 16] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/24/2019] [Revised: 09/27/2019] [Accepted: 10/28/2019] [Indexed: 01/10/2023] Open
Abstract
BACKGROUND Investigating early white matter (WM) change in Huntington's disease (HD) can improve our understanding of the way in which disease spreads from the striatum. OBJECTIVES We provide a detailed characterization of pathology-related WM change in HD. We first examined WM microstructure using diffusion-weighted imaging and then investigated both underlying biological properties of WM and products of WM damage including iron, myelin plus neurofilament light, a biofluid marker of axonal degeneration-in parallel with the mutant huntingtin protein. METHODS We examined WM change in HD gene carriers from the HD-CSFcohort, baseline visit. We used standard-diffusion magnetic resonance imaging to measure metrics including fractional anisotropy, a marker of WM integrity, and diffusivity; a novel diffusion model (neurite orientation dispersion and density imaging) to measure axonal density and organization; T1-weighted and T2-weighted structural magnetic resonance imaging images to derive proxy iron content and myelin-contrast measures; and biofluid concentrations of neurofilament light (in cerebrospinal fluid (CSF) and plasma) and mutant huntingtin protein (in CSF). RESULTS HD gene carriers displayed reduced fractional anisotropy and increased diffusivity when compared with controls, both of which were also associated with disease progression, CSF, and mutant huntingtin protein levels. HD gene carriers also displayed proxy measures of reduced myelin contrast and iron in the striatum. CONCLUSION Collectively, these findings present a more complete characterization of HD-related microstructural brain changes. The correlation between reduced fractional anisotropy, increased axonal orientation, and biofluid markers suggest that axonal breakdown is associated with increased WM degeneration, whereas higher quantitative T2 signal and lower myelin-contrast may indicate a process of demyelination limited to the striatum.
Collapse
Affiliation(s)
- Sarah Gregory
- University College London Huntington's Disease Centre, Department of Neurodegenerative DiseaseUniversity College London Queen Square Institute of Neurology, University College LondonLondonUnited Kingdom
| | - Eileanoir Johnson
- University College London Huntington's Disease Centre, Department of Neurodegenerative DiseaseUniversity College London Queen Square Institute of Neurology, University College LondonLondonUnited Kingdom
| | - Lauren M. Byrne
- University College London Huntington's Disease Centre, Department of Neurodegenerative DiseaseUniversity College London Queen Square Institute of Neurology, University College LondonLondonUnited Kingdom
| | - Filipe B. Rodrigues
- University College London Huntington's Disease Centre, Department of Neurodegenerative DiseaseUniversity College London Queen Square Institute of Neurology, University College LondonLondonUnited Kingdom
| | - Alexandra Henderson
- University College London Huntington's Disease Centre, Department of Neurodegenerative DiseaseUniversity College London Queen Square Institute of Neurology, University College LondonLondonUnited Kingdom
| | - John Moss
- University College London Huntington's Disease Centre, Department of Neurodegenerative DiseaseUniversity College London Queen Square Institute of Neurology, University College LondonLondonUnited Kingdom
| | - David Thomas
- Department of Brain Repair and Rehabilitation, University College London Queen Square Institute of NeurologyUniversity College LondonUnited Kingdom
- Leonard Wolfson Experimental Neurology Centre, University College London Queen Square Institute of NeurologyUniversity College LondonUnited Kingdom
| | - Hui Zhang
- Department of Computer Science and Centre for Medical Image ComputingUniversity College LondonLondonUnited Kingdom
| | - Enrico De Vita
- Lysholm Department of NeuroradiologyNational Hospital for Neurology and NeurosurgeryLondonUnited Kingdom
- Department of Biomedical Engineering, School of Biomedical Engineering and Imaging SciencesKing's College LondonLondonUnited Kingdom
| | - Sarah J. Tabrizi
- University College London Huntington's Disease Centre, Department of Neurodegenerative DiseaseUniversity College London Queen Square Institute of Neurology, University College LondonLondonUnited Kingdom
| | - Geraint Rees
- Wellcome Trust Centre for Neuroimaging, Institute of NeurologyUniversity College LondonLondonUnited Kingdom
| | - Rachael I. Scahill
- University College London Huntington's Disease Centre, Department of Neurodegenerative DiseaseUniversity College London Queen Square Institute of Neurology, University College LondonLondonUnited Kingdom
| | - Edward J. Wild
- University College London Huntington's Disease Centre, Department of Neurodegenerative DiseaseUniversity College London Queen Square Institute of Neurology, University College LondonLondonUnited Kingdom
| |
Collapse
|
104
|
Kupeli A, Kocak M, Goktepeli M, Karavas E, Danisan G. Role of T1 mapping to evaluate brain aging in a healthy population. Clin Imaging 2020; 59:56-60. [DOI: 10.1016/j.clinimag.2019.09.005] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/15/2019] [Revised: 07/24/2019] [Accepted: 09/23/2019] [Indexed: 11/25/2022]
|
105
|
Tullo S, Patel R, Devenyi GA, Salaciak A, Bedford SA, Farzin S, Wlodarski N, Tardif CL, Breitner JCS, Chakravarty MM. MR-based age-related effects on the striatum, globus pallidus, and thalamus in healthy individuals across the adult lifespan. Hum Brain Mapp 2019; 40:5269-5288. [PMID: 31452289 PMCID: PMC6864890 DOI: 10.1002/hbm.24771] [Citation(s) in RCA: 41] [Impact Index Per Article: 8.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/08/2019] [Revised: 07/17/2019] [Accepted: 08/05/2019] [Indexed: 01/18/2023] Open
Abstract
While numerous studies have used magnetic resonance imaging (MRI) to elucidate normative age-related trajectories in subcortical structures across the human lifespan, there exists substantial heterogeneity among different studies. Here, we investigated the normative relationships between age and morphology (i.e., volume and shape), and microstructure (using the T1-weighted/T2-weighted [T1w/T2w] signal ratio as a putative index of myelin and microstructure) of the striatum, globus pallidus, and thalamus across the adult lifespan using a dataset carefully quality controlled, yielding a final sample of 178 for the morphological analyses, and 162 for the T1w/T2w analyses from an initial dataset of 253 healthy subjects, aged 18-83. In accordance with previous cross-sectional studies of adults, we observed age-related volume decrease that followed a quadratic relationship between age and bilateral striatal and thalamic volumes, and a linear relationship in the globus pallidus. Our shape indices consistently demonstrated age-related posterior and medial areal contraction bilaterally across all three structures. Beyond morphology, we observed a quadratic inverted U-shaped relationship between T1w/T2w signal ratio and age, with a peak value occurring in middle age (at around 50 years old). After permutation testing, the Akaike information criterion determined age relationships remained significant for the bilateral globus pallidus and thalamus, for both the volumetric and T1w/T2w analyses. Our findings serve to strengthen and expand upon previous volumetric analyses by providing a normative baseline of morphology and microstructure of these structures to which future studies investigating patients with various disorders can be compared.
Collapse
Affiliation(s)
- Stephanie Tullo
- Integrated Program in NeuroscienceMcGill UniversityMontrealQuebecCanada
- Computational Brain Anatomy Laboratory, Cerebral Imaging CentreDouglas Mental Health University InstituteVerdunQuebecCanada
| | - Raihaan Patel
- Computational Brain Anatomy Laboratory, Cerebral Imaging CentreDouglas Mental Health University InstituteVerdunQuebecCanada
- Department of Biological and Biomedical EngineeringMcGill UniversityMontrealQuebecCanada
| | - Gabriel A. Devenyi
- Computational Brain Anatomy Laboratory, Cerebral Imaging CentreDouglas Mental Health University InstituteVerdunQuebecCanada
- Department of PsychiatryMcGill UniversityMontrealQuebecCanada
| | - Alyssa Salaciak
- Computational Brain Anatomy Laboratory, Cerebral Imaging CentreDouglas Mental Health University InstituteVerdunQuebecCanada
| | - Saashi A. Bedford
- Integrated Program in NeuroscienceMcGill UniversityMontrealQuebecCanada
- Computational Brain Anatomy Laboratory, Cerebral Imaging CentreDouglas Mental Health University InstituteVerdunQuebecCanada
| | - Sarah Farzin
- Computational Brain Anatomy Laboratory, Cerebral Imaging CentreDouglas Mental Health University InstituteVerdunQuebecCanada
| | - Nancy Wlodarski
- Computational Brain Anatomy Laboratory, Cerebral Imaging CentreDouglas Mental Health University InstituteVerdunQuebecCanada
| | - Christine L. Tardif
- McConnell Brain Imaging CenterMontreal Neurological Institute, McGill UniversityMontrealQuebecCanada
| | | | - John C. S. Breitner
- Centre for the Studies on the Prevention of ADDouglas Mental Health University InstituteVerdunQuebecCanada
| | - M. Mallar Chakravarty
- Integrated Program in NeuroscienceMcGill UniversityMontrealQuebecCanada
- Computational Brain Anatomy Laboratory, Cerebral Imaging CentreDouglas Mental Health University InstituteVerdunQuebecCanada
- Department of Biological and Biomedical EngineeringMcGill UniversityMontrealQuebecCanada
- Department of PsychiatryMcGill UniversityMontrealQuebecCanada
| |
Collapse
|
106
|
Freund P, Seif M, Weiskopf N, Friston K, Fehlings MG, Thompson AJ, Curt A. MRI in traumatic spinal cord injury: from clinical assessment to neuroimaging biomarkers. Lancet Neurol 2019; 18:1123-1135. [DOI: 10.1016/s1474-4422(19)30138-3] [Citation(s) in RCA: 72] [Impact Index Per Article: 14.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/03/2018] [Revised: 03/22/2019] [Accepted: 03/28/2019] [Indexed: 01/18/2023]
|
107
|
Düzel E, Acosta-Cabronero J, Berron D, Biessels GJ, Björkman-Burtscher I, Bottlaender M, Bowtell R, Buchem MV, Cardenas-Blanco A, Boumezbeur F, Chan D, Clare S, Costagli M, de Rochefort L, Fillmer A, Gowland P, Hansson O, Hendrikse J, Kraff O, Ladd ME, Ronen I, Petersen E, Rowe JB, Siebner H, Stoecker T, Straub S, Tosetti M, Uludag K, Vignaud A, Zwanenburg J, Speck O. European Ultrahigh-Field Imaging Network for Neurodegenerative Diseases (EUFIND). ALZHEIMER'S & DEMENTIA (AMSTERDAM, NETHERLANDS) 2019; 11:538-549. [PMID: 31388558 PMCID: PMC6675944 DOI: 10.1016/j.dadm.2019.04.010] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 12/12/2022]
Abstract
INTRODUCTION The goal of European Ultrahigh-Field Imaging Network in Neurodegenerative Diseases (EUFIND) is to identify opportunities and challenges of 7 Tesla (7T) MRI for clinical and research applications in neurodegeneration. EUFIND comprises 22 European and one US site, including over 50 MRI and dementia experts as well as neuroscientists. METHODS EUFIND combined consensus workshops and data sharing for multisite analysis, focusing on 7 core topics: clinical applications/clinical research, highest resolution anatomy, functional imaging, vascular systems/vascular pathology, iron mapping and neuropathology detection, spectroscopy, and quality assurance. Across these topics, EUFIND considered standard operating procedures, safety, and multivendor harmonization. RESULTS The clinical and research opportunities and challenges of 7T MRI in each subtopic are set out as a roadmap. Specific MRI sequences for each subtopic were implemented in a pilot study presented in this report. Results show that a large multisite 7T imaging network with highly advanced and harmonized imaging sequences is feasible and may enable future multicentre ultrahigh-field MRI studies and clinical trials. DISCUSSION The EUFIND network can be a major driver for advancing clinical neuroimaging research using 7T and for identifying use-cases for clinical applications in neurodegeneration.
Collapse
Affiliation(s)
- Emrah Düzel
- Institute of Cognitive Neurology and Dementia Research, Otto-von-Guericke University Magdeburg, Magdeburg, Germany
- German Center for Neurodegenerative Diseases (DZNE), Magdeburg, Magdeburg, Germany
- Institute of Cognitive Neuroscience, University College London, London, UK
- Center for Behavioral Brain Science, Magdeburg, Germany
| | - Julio Acosta-Cabronero
- German Center for Neurodegenerative Diseases (DZNE), Magdeburg, Magdeburg, Germany
- Wellcome Centre for Human Neuroimaging, UCL Queen Square Institute of Neurology, University College London, London, UK
| | - David Berron
- German Center for Neurodegenerative Diseases (DZNE), Magdeburg, Magdeburg, Germany
- 7Lund University BioImaging Center, Lund University, Lund, Sweden
| | - Geert Jan Biessels
- Department of Neurology, UMC Utrecht, Utrecht University, Utrecht, The Netherlands
| | - Isabella Björkman-Burtscher
- 7Lund University BioImaging Center, Lund University, Lund, Sweden
- Departement of Radiology, Sahlgrenska Akademy, University of Gothenburg, Gothenburg, Sweden
| | | | - Richard Bowtell
- Sir Peter Mansfield Imaging Centre, School of Physics and Astronomy, University of Nottingham, Nottingham, UK
| | - Mark v Buchem
- Department of Radiology, University Medical Center Leiden, Leiden, The Netherlands
| | - Arturo Cardenas-Blanco
- Institute of Cognitive Neurology and Dementia Research, Otto-von-Guericke University Magdeburg, Magdeburg, Germany
- German Center for Neurodegenerative Diseases (DZNE), Magdeburg, Magdeburg, Germany
| | - Fawzi Boumezbeur
- NeuroSpin, CEA & Université Paris-Saclay, Gif-Sur-Yvette, France
| | - Dennis Chan
- Department of Clinical Neurosciences, University of Cambridge, Cambridge, UK
| | - Stuart Clare
- Wellcome Centre for Integrative Neuroimaging, University of Oxford, Oxford, UK
| | - Mauro Costagli
- Imago 7 Research Foundation, Pisa, Italy
- Laboratory of Medical Physics and Magnetic Resonance, IRCCS Stella Maris, Pisa, Italy
| | - Ludovic de Rochefort
- Center for Magnetic Resonance in Biology and Medicine (UMR 7339), CRMBM, CNRS - Aix Marseille Université, Marseille, France
| | - Ariane Fillmer
- Physikalisch-Technische Bundesanstalt (PTB), Berlin, Germany
| | - Penny Gowland
- Sir Peter Mansfield Imaging Centre, School of Physics and Astronomy, University of Nottingham, Nottingham, UK
| | - Oskar Hansson
- 7Lund University BioImaging Center, Lund University, Lund, Sweden
- Memory Clinic, Skåne University Hospital, Malmö, Sweden
| | - Jeroen Hendrikse
- Department of Neurology, UMC Utrecht, Utrecht University, Utrecht, The Netherlands
| | - Oliver Kraff
- Erwin L. Hahn Institute for Magnetic Resonance Imaging, University of Duisburg-Essen, Essen, Germany
| | - Mark E. Ladd
- Medical Physics in Radiology, German Cancer Research Center (DKFZ), Heidelberg, Germany
- Faculty of Physics and Astronomy and Faculty of Medicine, University of Heidelberg, Heidelberg, Germany
| | - Itamar Ronen
- Department of Radiology, University Medical Center Leiden, Leiden, The Netherlands
| | - Esben Petersen
- Danish Center for Magnetic Resonance, Copenhagen University Hospital Hvidovre, Hvidovre, Denmark
| | - James B. Rowe
- Department of Clinical Neurosciences, University of Cambridge, Cambridge, UK
| | - Hartwig Siebner
- Danish Center for Magnetic Resonance, Copenhagen University Hospital Hvidovre, Hvidovre, Denmark
- Department of Neurology, Copenhagen University Hospital Bispebjerg, Copenhagen, Denmark
| | - Tony Stoecker
- German Center for Neurodegenerative Diseases (DZNE), Bonn, Germany
| | - Sina Straub
- Medical Physics in Radiology, German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Michela Tosetti
- Imago 7 Research Foundation, Pisa, Italy
- Laboratory of Medical Physics and Magnetic Resonance, IRCCS Stella Maris, Pisa, Italy
| | - Kamil Uludag
- Center for Neuroscience Imaging Research, Institute for Basic Science and Department of Biomedical Engineering, Sungkyunkwan University, Suwon, Republic of Korea
- Techna Institute & Koerner Scientist in MR Imaging, University Health Network, Toronto, Ontario, Canada
| | | | - Jaco Zwanenburg
- Department of Neurology, UMC Utrecht, Utrecht University, Utrecht, The Netherlands
| | - Oliver Speck
- German Center for Neurodegenerative Diseases (DZNE), Magdeburg, Magdeburg, Germany
- Center for Behavioral Brain Science, Magdeburg, Germany
- Biomedical Magnetic Resonance, Otto-von-Guericke University, Magdeburg, Germany
- Leibniz-Institute for Neurobiology (LIN), Magdeburg, Germany
| |
Collapse
|
108
|
Bouhrara M, Rejimon AC, Cortina LE, Khattar N, Spencer RG. Four-angle method for practical ultra-high-resolution magnetic resonance mapping of brain longitudinal relaxation time and apparent proton density. Magn Reson Imaging 2019; 66:57-68. [PMID: 31730882 DOI: 10.1016/j.mri.2019.11.013] [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: 08/23/2019] [Revised: 11/09/2019] [Accepted: 11/10/2019] [Indexed: 10/25/2022]
Abstract
Changes in longitudinal relaxation time (T1) and proton density (PD) are sensitive indicators of microstructural alterations associated with various central nervous system diseases as well as brain maturation and aging. In this work, we introduce a new approach for rapid and accurate high-resolution (HR) or ultra HR (UHR) mapping of T1 and apparent PD (APD) of the brain with correction of radiofrequency field, B1, inhomogeneities. The four-angle method (FAM) uses four spoiled-gradient recalled-echo (SPGR) images acquired at different flip angles (FA) and short repetition times (TRs). The first two SPGR images are acquired at low-spatial resolution and used to accurately map the active B1+ field with the recently introduced steady-state double angle method (SS-DAM). The estimated B1+ map is used in conjunction with the two other SPGR images, acquired at HR or UHR, to map T1 and APD. The method is evaluated with numerical, phantom, and in-vivo imaging measurements. Furthermore, we investigated imaging acceleration methods to further shorten the acquisition time. Our results indicate that FAM provides an accurate method for simultaneous HR or UHR mapping of T1 and APD in human brain in clinical high-field MRI. Derived parameter maps without B1+correction suffer from large inaccuracies, but this issue is well-corrected through use of the SS-DAM. Furthermore, the use of SPGR imaging with short TR and phased-array coil acquisition permits substantial imaging acceleration and enables robust HR or UHR T1 and APD mapping in a clinically acceptable time frame, with whole brain coverage obtained in less than 2 min or 5 min, respectively. The method exhibits high reproducibility and benefits from the use of the conventional SPGR sequence, available in all preclinical and clinical MRI machines, and very simple modeling to address a critical outstanding issue in neuroimaging.
Collapse
Affiliation(s)
- Mustapha Bouhrara
- Laboratory of Clinical Investigation, National Institute on Aging, National Institutes of Health, Baltimore, MD, USA.
| | - Abinand C Rejimon
- Laboratory of Clinical Investigation, National Institute on Aging, National Institutes of Health, Baltimore, MD, USA
| | - Luis E Cortina
- Laboratory of Clinical Investigation, National Institute on Aging, National Institutes of Health, Baltimore, MD, USA
| | - Nikkita Khattar
- Laboratory of Clinical Investigation, National Institute on Aging, National Institutes of Health, Baltimore, MD, USA
| | - Richard G Spencer
- Laboratory of Clinical Investigation, National Institute on Aging, National Institutes of Health, Baltimore, MD, USA
| |
Collapse
|
109
|
Fujita S, Hagiwara A, Hori M, Warntjes M, Kamagata K, Fukunaga I, Andica C, Maekawa T, Irie R, Takemura MY, Kumamaru KK, Wada A, Suzuki M, Ozaki Y, Abe O, Aoki S. Three-dimensional high-resolution simultaneous quantitative mapping of the whole brain with 3D-QALAS: An accuracy and repeatability study. Magn Reson Imaging 2019; 63:235-243. [DOI: 10.1016/j.mri.2019.08.031] [Citation(s) in RCA: 27] [Impact Index Per Article: 5.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/09/2019] [Revised: 08/19/2019] [Accepted: 08/19/2019] [Indexed: 11/24/2022]
|
110
|
Vanes LD, Moutoussis M, Ziegler G, Goodyer IM, Fonagy P, Jones PB, Bullmore ET, Dolan RJ. White matter tract myelin maturation and its association with general psychopathology in adolescence and early adulthood. Hum Brain Mapp 2019; 41:827-839. [PMID: 31661180 PMCID: PMC7268015 DOI: 10.1002/hbm.24842] [Citation(s) in RCA: 36] [Impact Index Per Article: 7.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/23/2019] [Revised: 09/30/2019] [Accepted: 10/14/2019] [Indexed: 12/12/2022] Open
Abstract
Adolescence is a time period associated with marked brain maturation that coincides with an enhanced risk for onset of psychiatric disorder. White matter tract myelination, a process that continues to unfold throughout adolescence, is reported to be abnormal in several psychiatric disorders. Here, we ask whether psychiatric vulnerability is linked to aberrant developmental myelination trajectories. We assessed a marker of myelin maturation, using magnetisation transfer (MT) imaging, in 10 major white matter tracts. We then investigated its relationship to the expression of a general psychopathology "p-factor" in a longitudinal analysis of 293 healthy participants between the ages of 14 and 24. We observed significant longitudinal MT increase across the full age spectrum in anterior thalamic radiation, hippocampal cingulum, dorsal cingulum and superior longitudinal fasciculus. MT increase in the inferior fronto-occipital fasciculus, inferior longitudinal fasciculus and uncinate fasciculus was pronounced in younger participants but levelled off during the transition into young adulthood. Crucially, longitudinal MT increase in dorsal cingulum and uncinate fasciculus decelerated as a function of mean p-factor scores over the study period. This suggests that an increased expression of psychopathology is closely linked to lower rates of myelin maturation in selective brain tracts over time. Impaired myelin growth in limbic association fibres may serve as a neural marker for emerging mental illness during the course of adolescence and early adulthood.
Collapse
Affiliation(s)
- Lucy D Vanes
- Max Planck UCL Centre for Computational Psychiatry and Ageing Research, University College London, London, UK.,Wellcome Centre for Human Neuroimaging, University College London, London, UK
| | - Michael Moutoussis
- Max Planck UCL Centre for Computational Psychiatry and Ageing Research, University College London, London, UK.,Wellcome Centre for Human Neuroimaging, University College London, London, UK
| | - Gabriel Ziegler
- Institute of Cognitive Neurology and Dementia Research, Otto-von-Guericke-University Magdeburg, Magdeburg, Germany
| | - Ian M Goodyer
- Department of Psychiatry, University of Cambridge Clinical School, Cambridge, UK
| | - Peter Fonagy
- Department of Clinical, Educational and Health Psychology, University College London, London, UK
| | - Peter B Jones
- Department of Psychiatry, University of Cambridge Clinical School, Cambridge, UK
| | - Edward T Bullmore
- Department of Psychiatry, University of Cambridge Clinical School, Cambridge, UK
| | -
- Department of Psychiatry, University of Cambridge Clinical School, Cambridge, UK
| | - Raymond J Dolan
- Max Planck UCL Centre for Computational Psychiatry and Ageing Research, University College London, London, UK.,Wellcome Centre for Human Neuroimaging, University College London, London, UK
| |
Collapse
|
111
|
Brain iron content in systemic iron overload: A beta-thalassemia quantitative MRI study. NEUROIMAGE-CLINICAL 2019; 24:102058. [PMID: 31711032 PMCID: PMC6849415 DOI: 10.1016/j.nicl.2019.102058] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 04/18/2019] [Revised: 10/15/2019] [Accepted: 10/23/2019] [Indexed: 01/20/2023]
Abstract
Iron overload is a life-threatening condition in beta-thalassemia. Data on brain involvement in systemic iron overload are conflicting. MRI quantification of brain tissue iron content is feasible in a voxel-based approach. No iron tissue excess is evident in beta-thalassemia but in the choroid plexuses.
Objective Multisystem iron poisoning is a major concern for long-term beta-thalassemia management. Quantitative MRI-based techniques routinely show iron overload in heart, liver, endocrine glands and kidneys. However, data on the brain are conflicting and monitoring of brain iron content is still matter of debate. Methods This 3T-MRI study applied a well validated high-resolution whole-brain quantitative MRI assessment of iron content on 47 transfusion-dependent (mean-age: 36.9 ± 10.3 years, 63% females), 23 non-transfusion dependent (mean-age: 29.2 ± 11.7 years, 56% females) and 57 healthy controls (mean-age: 33.9 ± 10.8 years, 65% females). Clinical data, Wechsler Adult Intelligence Scale scores and treatment regimens were recorded. Beside whole-brain R2* analyses, regional R2*-values were extracted in putamen, globus pallidum, caudate nucleus, thalamus and red nucleus; hippocampal volumes were also determined. Results Regional analyses yielded no significant differences between patients and controls, except in those treated with deferiprone that showed lower R2*-values (p<0.05). Whole-brain analyses of R2*-maps revealed strong age-R2* correlations (r2=0.51) in both groups and clusters of significantly increased R2*-values in beta-thalassemia patients in the hippocampal formations and around the Luschka foramina; transfusion treatment was associated with additional R2* increase in dorsal thalami. Hippocampal formation R2*-values did not correlate with hippocampal volume; hippocampal volume did not differ between patients and controls. All regions with increased R2*-values shared a strict anatomical contiguity with choroid plexuses suggesting a blooming effect as the likely cause of R2* increase, in agreement with the available histopathologic literature evidence. Conclusion According to our MRI findings and the available histopathologic literature evidence, concerns about neural tissue iron overload in beta-thalassemia appear to be unjustified.
Collapse
|
112
|
Quantitative age-dependent differences in human brainstem myelination assessed using high-resolution magnetic resonance mapping. Neuroimage 2019; 206:116307. [PMID: 31669302 DOI: 10.1016/j.neuroimage.2019.116307] [Citation(s) in RCA: 16] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/22/2019] [Revised: 10/18/2019] [Accepted: 10/21/2019] [Indexed: 12/13/2022] Open
Abstract
Previous in-vivo magnetic resonance imaging (MRI)-based studies of age-related differences in the human brainstem have focused on volumetric morphometry. These investigations have provided pivotal insights into regional brainstem atrophy but have not addressed microstructural age differences. However, growing evidence indicates the sensitivity of quantitative MRI to microstructural tissue changes in the brain. These studies have largely focused on the cerebrum, with very few MR investigations addressing age-dependent differences in the brainstem, in spite of its central role in the regulation of vital functions. Several studies indicate early brainstem alterations in a myriad of neurodegenerative diseases and dementias. The paucity of MR-focused investigations is likely due in part to the challenges imposed by the small structural scale of the brainstem itself as well as of substructures within, requiring accurate high spatial resolution imaging studies. In this work, we applied our recently developed approach to high-resolution myelin water fraction (MWF) mapping, a proxy for myelin content, to investigate myelin differences with normal aging within the brainstem. In this cross-sectional investigation, we studied a large cohort (n = 125) of cognitively unimpaired participants spanning a wide age range (21-94 years) and found a decrease in myelination with age in most brainstem regions studied, with several regions exhibiting a quadratic association between myelin and age. We believe that this study is the first investigation of MWF differences with normative aging in the adult brainstem. Further, our results provide reference MWF values.
Collapse
|
113
|
Park J, Han JW, Lee JR, Byun S, Suh SW, Kim T, Yoon IY, Kim KW. Lifetime coffee consumption, pineal gland volume, and sleep quality in late life. Sleep 2019; 41:5053876. [PMID: 30011049 DOI: 10.1093/sleep/zsy127] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/24/2018] [Indexed: 12/22/2022] Open
Abstract
Study Objectives Previous studies have shown that coffee consumption may suppress the production of melatonin in pinealocytes through competitive inhibition of adenosine A2 receptors by caffeine. We investigated the impact of lifetime coffee consumption on pineal gland volume and the resulting effects on sleep quality. Methods We enrolled 162 cognitively normal elderly individuals among the participants in the Korean Longitudinal Study on Cognitive Aging and Dementia. We evaluated the patterns and amounts of coffee consumption using a study-specific standardized interview and assessed sleep quality using the Pittsburgh Sleep Quality Index. We measured the volume of pineal parenchyma (VPP) by manually segmenting the pineal gland on high-resolution three-dimensional T1-weighted magnetic resonance images. We examined the impact of lifetime coffee consumption on the VPP and the resulting effects on sleep quality using analysis of covariance, multiple linear regression, and mediation analyses. Results We found that smaller VPP was associated with higher cumulative lifetime coffee consumption. Participants who consumed more than 60 cup-years of coffee had VPPs that were smaller by about 20% than individuals who consumed less than 60 cup-years of coffee. The VPP mediated the association between lifetime coffee consumption and sleep efficiency and quality. Conclusions Our findings suggest that high lifetime coffee consumption may reduce VPP, and that this reduction in VPP may impair the quality of sleep in late life.
Collapse
Affiliation(s)
- Jeongbin Park
- Department of Brain and Cognitive Science, Seoul National University College of Natural Sciences, Seoul, South Korea
| | - Ji Won Han
- Department of Neuropsychiatry, Seoul National University Bundang Hospital, Seongnam, South Korea
| | - Ju Ri Lee
- Department of Neuropsychiatry, Seoul National University Bundang Hospital, Seongnam, South Korea
| | - Seonjeong Byun
- Department of Neuropsychiatry, Seoul National University Bundang Hospital, Seongnam, South Korea
| | - Seung Wan Suh
- Department of Neuropsychiatry, Seoul National University Bundang Hospital, Seongnam, South Korea
| | - Tae Kim
- Department of Biomedical Science and Engineering and School of Life Sciences, Gwangju Institute of Science and Technology, Gwangju, South Korea
| | - In Young Yoon
- Department of Neuropsychiatry, Seoul National University Bundang Hospital, Seongnam, South Korea.,Department of Psychiatry, Seoul National University College of Medicine, Seoul, South Korea
| | - Ki Woong Kim
- Department of Brain and Cognitive Science, Seoul National University College of Natural Sciences, Seoul, South Korea.,Department of Neuropsychiatry, Seoul National University Bundang Hospital, Seongnam, South Korea.,Department of Psychiatry, Seoul National University College of Medicine, Seoul, South Korea
| |
Collapse
|
114
|
7T GRE-MRI signal compartments are sensitive to dysplastic tissue in focal epilepsy. Magn Reson Imaging 2019; 61:1-8. [DOI: 10.1016/j.mri.2019.05.011] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/15/2018] [Revised: 04/19/2019] [Accepted: 05/04/2019] [Indexed: 12/11/2022]
|
115
|
Chappus-McCendie H, Chevalier L, Roberge C, Plourde M. Omega-3 PUFA metabolism and brain modifications during aging. Prog Neuropsychopharmacol Biol Psychiatry 2019; 94:109662. [PMID: 31152862 DOI: 10.1016/j.pnpbp.2019.109662] [Citation(s) in RCA: 22] [Impact Index Per Article: 4.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/04/2019] [Accepted: 05/28/2019] [Indexed: 12/20/2022]
Abstract
In Canada, 5.5 million (16% of Canadians) adults are >65 years old and projections suggest this number will be approximately 20% of Canadians by 2024. A major concern regarding old age is a decline in health, especially if this entails a loss of self-sufficiency and independence caused by a decline in cognition. The brain contains 60% of fat and is one of the most concentrated organs in long chain omega-3 fatty acids such as docosahexaenoic acid (DHA). During aging, there are physiological modifications in the metabolism of lipids that could also have consequences on brain structure and levels of DHA. This review will hence discuss the physiological modifications in the metabolism of lipids during aging with a focus on long chain omega-3 and omega-6 fatty acids and also outline the structural and functional modifications of the brain during aging including brain lipid modifications and its relation to higher levels of DHA and cognition. Therefore, in this review, we outline the importance of collecting more data on the biology of aging since it might highly improve our understanding about what are «normal» modifications occurring during aging and what can become pathological.
Collapse
Affiliation(s)
- Hillary Chappus-McCendie
- Research Center on Aging, Health and Social Services Centre, University Institute of Geriatrics of Sherbrooke, Department of Medicine, Université de Sherbrooke, 1036 Belvédère Sud, Sherbrooke J1H 4C4, Canada
| | - Laurie Chevalier
- Research Center on Aging, Health and Social Services Centre, University Institute of Geriatrics of Sherbrooke, Department of Medicine, Université de Sherbrooke, 1036 Belvédère Sud, Sherbrooke J1H 4C4, Canada
| | - Claude Roberge
- Research Center on Aging, Health and Social Services Centre, University Institute of Geriatrics of Sherbrooke, Department of Medicine, Université de Sherbrooke, 1036 Belvédère Sud, Sherbrooke J1H 4C4, Canada
| | - Mélanie Plourde
- Research Center on Aging, Health and Social Services Centre, University Institute of Geriatrics of Sherbrooke, Department of Medicine, Université de Sherbrooke, 1036 Belvédère Sud, Sherbrooke J1H 4C4, Canada.
| |
Collapse
|
116
|
Differences between normal and diabetic brains in middle-aged rats by MRI. Brain Res 2019; 1724:146407. [PMID: 31465773 DOI: 10.1016/j.brainres.2019.146407] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/22/2019] [Revised: 08/23/2019] [Accepted: 08/24/2019] [Indexed: 01/01/2023]
Abstract
Normal aging is a risk factor for metabolic disorders such as diabetes, and diabetes is also a recognized cause of accelerated aging. Being able to distinguish changes caused by normal aging from those caused by diabetes, would provide insight into how the aging brain interacts with diabetes. Eight types of MRI metric maps (magnetization relaxation time constants of T1 and T2, cerebral blood flow, cerebrovascular permeability, mean diffusivity, diffusion fractional anisotropy, mean diffusion kurtosis and diffusion directional entropy) were generated for all rats from the three groups of normal young, healthy and 1.5-month diabetic middle-aged rats under investigation. Measurements of multiple MRI indices of cerebral white and gray matter from animals of the three groups provide complementary results and insight into differences between healthy and diabetic white / gray matter in the mid-aged rats. Our data indicate that MRI may distinguish between the normal and diabetes in mid-aged rat brains by measuring either T1 and T2 of gray matter, or fractional anisotropy of white matter and gray matter. Therefore, MRI can distinguish changes of cerebral tissue due to the normal aging from diabetic aging, which may lead to be able to better understand how diabetes accelerates aging in normal brain.
Collapse
|
117
|
Liu PP, Xie Y, Meng XY, Kang JS. History and progress of hypotheses and clinical trials for Alzheimer's disease. Signal Transduct Target Ther 2019; 4:29. [PMID: 31637009 PMCID: PMC6799833 DOI: 10.1038/s41392-019-0063-8] [Citation(s) in RCA: 332] [Impact Index Per Article: 66.4] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/28/2019] [Revised: 07/07/2019] [Accepted: 07/17/2019] [Indexed: 12/20/2022] Open
Abstract
Alzheimer's disease (AD) is a neurodegenerative disease characterized by progressive memory loss along with neuropsychiatric symptoms and a decline in activities of daily life. Its main pathological features are cerebral atrophy, amyloid plaques, and neurofibrillary tangles in the brains of patients. There are various descriptive hypotheses regarding the causes of AD, including the cholinergic hypothesis, amyloid hypothesis, tau propagation hypothesis, mitochondrial cascade hypothesis, calcium homeostasis hypothesis, neurovascular hypothesis, inflammatory hypothesis, metal ion hypothesis, and lymphatic system hypothesis. However, the ultimate etiology of AD remains obscure. In this review, we discuss the main hypotheses of AD and related clinical trials. Wealthy puzzles and lessons have made it possible to develop explanatory theories and identify potential strategies for therapeutic interventions for AD. The combination of hypometabolism and autophagy deficiency is likely to be a causative factor for AD. We further propose that fluoxetine, a selective serotonin reuptake inhibitor, has the potential to treat AD.
Collapse
Affiliation(s)
- Pei-Pei Liu
- Clinical Systems Biology Laboratories, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, 450052 Henan China
| | - Yi Xie
- Clinical Systems Biology Laboratories, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, 450052 Henan China
| | - Xiao-Yan Meng
- Clinical Systems Biology Laboratories, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, 450052 Henan China
| | - Jian-Sheng Kang
- Clinical Systems Biology Laboratories, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, 450052 Henan China
| |
Collapse
|
118
|
Filo S, Shtangel O, Salamon N, Kol A, Weisinger B, Shifman S, Mezer AA. Disentangling molecular alterations from water-content changes in the aging human brain using quantitative MRI. Nat Commun 2019; 10:3403. [PMID: 31363094 PMCID: PMC6667463 DOI: 10.1038/s41467-019-11319-1] [Citation(s) in RCA: 43] [Impact Index Per Article: 8.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/22/2018] [Accepted: 07/05/2019] [Indexed: 11/30/2022] Open
Abstract
It is an open question whether aging-related changes throughout the brain are driven by a common factor or result from several distinct molecular mechanisms. Quantitative magnetic resonance imaging (qMRI) provides biophysical parametric measurements allowing for non-invasive mapping of the aging human brain. However, qMRI measurements change in response to both molecular composition and water content. Here, we present a tissue relaxivity approach that disentangles these two tissue components and decodes molecular information from the MRI signal. Our approach enables us to reveal the molecular composition of lipid samples and predict lipidomics measurements of the brain. It produces unique molecular signatures across the brain, which are correlated with specific gene-expression profiles. We uncover region-specific molecular changes associated with brain aging. These changes are independent from other MRI aging markers. Our approach opens the door to a quantitative characterization of the biological sources for aging, that until now was possible only post-mortem.
Collapse
Affiliation(s)
- Shir Filo
- The Edmond and Lily Safra Center for Brain Sciences, The Hebrew University of Jerusalem, Jerusalem, 9190401, Israel
| | - Oshrat Shtangel
- The Edmond and Lily Safra Center for Brain Sciences, The Hebrew University of Jerusalem, Jerusalem, 9190401, Israel
| | - Noga Salamon
- The Edmond and Lily Safra Center for Brain Sciences, The Hebrew University of Jerusalem, Jerusalem, 9190401, Israel
| | - Adi Kol
- The Edmond and Lily Safra Center for Brain Sciences, The Hebrew University of Jerusalem, Jerusalem, 9190401, Israel
| | - Batsheva Weisinger
- The Edmond and Lily Safra Center for Brain Sciences, The Hebrew University of Jerusalem, Jerusalem, 9190401, Israel
| | - Sagiv Shifman
- Department of Genetics, The Institute of Life Sciences, The Hebrew University of Jerusalem, Jerusalem, 9190401, Israel
| | - Aviv A Mezer
- The Edmond and Lily Safra Center for Brain Sciences, The Hebrew University of Jerusalem, Jerusalem, 9190401, Israel.
| |
Collapse
|
119
|
How Does iReadMore Therapy Change the Reading Network of Patients with Central Alexia? J Neurosci 2019; 39:5719-5727. [PMID: 31085605 DOI: 10.1523/jneurosci.1426-18.2019] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/29/2018] [Revised: 03/07/2019] [Accepted: 03/16/2019] [Indexed: 11/21/2022] Open
Abstract
Central alexia (CA) is an acquired reading disorder co-occurring with a generalized language deficit (aphasia). The roles of perilesional and ipsilesional tissue in recovery from poststroke aphasia are unclear. We investigated the impact of reading training (using iReadMore, a therapy app) on the connections within and between the right and left hemisphere of the reading network of patients with CA. In patients with pure alexia, iReadMore increased feedback from left inferior frontal gyrus (IFG) region to the left occipital (OCC) region. We aimed to identify whether iReadMore therapy was effective through a similar mechanism in patients with CA. Participants with chronic poststroke CA (n = 23) completed 35 h of iReadMore training over 4 weeks. Reading accuracy for trained and untrained words was assessed before and after therapy. The neural response to reading trained and untrained words in the left and right OCC, ventral occipitotemporal, and IFG regions was examined using event-related magnetoencephalography. The training-related modulation in effective connectivity between regions was modeled at the group level with dynamic causal modeling. iReadMore training improved participants' reading accuracy by an average of 8.4% (range, -2.77 to 31.66) while accuracy for untrained words was stable. Training increased regional sensitivity in bilateral frontal and occipital regions, and strengthened feedforward connections within the left hemisphere. Our data suggest that iReadMore training in these patients modulates lower-order visual representations, as opposed to higher-order, more abstract representations, to improve word-reading accuracy.SIGNIFICANCE STATEMENT This is the first study to conduct a network-level analysis of therapy effects in participants with poststroke central alexia. When patients trained with iReadMore (a multimodal, behavioral, mass practice, computer-based therapy), reading accuracy improved by an average 8.4% on trained items. A network analysis of the magnetoencephalography data associated with this improvement revealed an increase in regional sensitivity in bilateral frontal and occipital regions and strengthening of feedforward connections within the left hemisphere. This indicates that in patients with CA iReadMore engages lower-order, intact resources within the left hemisphere (posterior to their lesion locations) to improve word reading. This provides a foundation for future research to investigate reading network modulation in different CA subtypes, or for sentence-level therapy.
Collapse
|
120
|
Buonincontri G, Biagi L, Retico A, Cecchi P, Cosottini M, Gallagher FA, Gómez PA, Graves MJ, McLean MA, Riemer F, Schulte RF, Tosetti M, Zaccagna F, Kaggie JD. Multi-site repeatability and reproducibility of MR fingerprinting of the healthy brain at 1.5 and 3.0 T. Neuroimage 2019; 195:362-372. [PMID: 30923028 DOI: 10.1016/j.neuroimage.2019.03.047] [Citation(s) in RCA: 60] [Impact Index Per Article: 12.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/13/2018] [Revised: 03/08/2019] [Accepted: 03/20/2019] [Indexed: 12/19/2022] Open
Abstract
Fully-quantitative MR imaging methods are useful for longitudinal characterization of disease and assessment of treatment efficacy. However, current quantitative MRI protocols have not been widely adopted in the clinic, mostly due to lengthy scan times. Magnetic Resonance Fingerprinting (MRF) is a new technique that can reconstruct multiple parametric maps from a single fast acquisition in the transient state of the MR signal. Due to the relative novelty of this technique, the repeatability and reproducibility of quantitative measurements obtained using MRF has not been extensively studied. Our study acquired test/retest data from the brains of nine healthy volunteers, each scanned on five MRI systems (two at 3.0 T and three at 1.5 T, all from a single vendor) located at two different centers. The pulse sequence and reconstruction algorithm were the same for all acquisitions. After registration of the MRF-derived M0, T1 and T2 maps to an anatomical atlas, coefficients-of-variation (CVs) were computed to assess test/retest repeatability and inter-site reproducibility in each voxel, while a General Linear Model (GLM) was used to determine the voxel-wise variability between all confounders, which included test/retest, subject, field strength and site. Our analysis demonstrated an excellent repeatability (CVs of 2-3% for T1, 5-8% for T2, 3% for normalized-M0) and a good reproducibility (CVs of 3-8% for T1, 8-14% for T2, 5% for normalized-M0) in grey and white matter.
Collapse
Affiliation(s)
- Guido Buonincontri
- IMAGO7 Foundation, Pisa, Italy; IRCCS Fondazione Stella Maris, Pisa, Italy
| | - Laura Biagi
- IMAGO7 Foundation, Pisa, Italy; IRCCS Fondazione Stella Maris, Pisa, Italy
| | | | - Paolo Cecchi
- Department of Radiology, University of Pisa, Italy
| | | | | | - Pedro A Gómez
- Munich School of Bioengineering, Technical University of Munich, Germany
| | - Martin J Graves
- Department of Radiology, University of Cambridge, United Kingdom
| | - Mary A McLean
- Cancer Research UK Cambridge Institute, University of Cambridge, United Kingdom
| | - Frank Riemer
- Department of Radiology, University of Cambridge, United Kingdom
| | | | - Michela Tosetti
- IMAGO7 Foundation, Pisa, Italy; IRCCS Fondazione Stella Maris, Pisa, Italy.
| | - Fulvio Zaccagna
- Department of Radiology, University of Cambridge, United Kingdom
| | - Joshua D Kaggie
- Department of Radiology, University of Cambridge, United Kingdom
| |
Collapse
|
121
|
Tabelow K, Balteau E, Ashburner J, Callaghan MF, Draganski B, Helms G, Kherif F, Leutritz T, Lutti A, Phillips C, Reimer E, Ruthotto L, Seif M, Weiskopf N, Ziegler G, Mohammadi S. hMRI - A toolbox for quantitative MRI in neuroscience and clinical research. Neuroimage 2019; 194:191-210. [PMID: 30677501 PMCID: PMC6547054 DOI: 10.1016/j.neuroimage.2019.01.029] [Citation(s) in RCA: 129] [Impact Index Per Article: 25.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/07/2018] [Revised: 12/21/2018] [Accepted: 01/10/2019] [Indexed: 12/20/2022] Open
Abstract
Neuroscience and clinical researchers are increasingly interested in quantitative magnetic resonance imaging (qMRI) due to its sensitivity to micro-structural properties of brain tissue such as axon, myelin, iron and water concentration. We introduce the hMRI-toolbox, an open-source, easy-to-use tool available on GitHub, for qMRI data handling and processing, presented together with a tutorial and example dataset. This toolbox allows the estimation of high-quality multi-parameter qMRI maps (longitudinal and effective transverse relaxation rates R1 and R2⋆, proton density PD and magnetisation transfer MT saturation) that can be used for quantitative parameter analysis and accurate delineation of subcortical brain structures. The qMRI maps generated by the toolbox are key input parameters for biophysical models designed to estimate tissue microstructure properties such as the MR g-ratio and to derive standard and novel MRI biomarkers. Thus, the current version of the toolbox is a first step towards in vivo histology using MRI (hMRI) and is being extended further in this direction. Embedded in the Statistical Parametric Mapping (SPM) framework, it benefits from the extensive range of established SPM tools for high-accuracy spatial registration and statistical inferences and can be readily combined with existing SPM toolboxes for estimating diffusion MRI parameter maps. From a user's perspective, the hMRI-toolbox is an efficient, robust and simple framework for investigating qMRI data in neuroscience and clinical research.
Collapse
Affiliation(s)
| | | | | | | | - Bogdan Draganski
- Laboratory for Research in Neuroimaging, Department of Clinical Neuroscience, Lausanne University Hospital and University of Lausanne, Switzerland; Department of Neurology, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
| | - Gunther Helms
- Medical Radiation Physics, Department of Clinical Sciences Lund, Lund University, Lund, Sweden
| | - Ferath Kherif
- Laboratory for Research in Neuroimaging, Department of Clinical Neuroscience, Lausanne University Hospital and University of Lausanne, Switzerland
| | - Tobias Leutritz
- Department of Neurophysics, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
| | - Antoine Lutti
- Laboratory for Research in Neuroimaging, Department of Clinical Neuroscience, Lausanne University Hospital and University of Lausanne, Switzerland
| | | | - Enrico Reimer
- Department of Neurophysics, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
| | | | | | - Nikolaus Weiskopf
- Department of Neurophysics, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
| | - Gabriel Ziegler
- Institute for Cognitive Neurology and Dementia Research, University of Magdeburg, Germany
| | | |
Collapse
|
122
|
Ziegler G, Hauser TU, Moutoussis M, Bullmore ET, Goodyer IM, Fonagy P, Jones PB, Lindenberger U, Dolan RJ. Compulsivity and impulsivity traits linked to attenuated developmental frontostriatal myelination trajectories. Nat Neurosci 2019; 22:992-999. [PMID: 31086316 PMCID: PMC7610393 DOI: 10.1038/s41593-019-0394-3] [Citation(s) in RCA: 64] [Impact Index Per Article: 12.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/26/2018] [Accepted: 03/25/2019] [Indexed: 01/06/2023]
Abstract
The transition from adolescence to adulthood is a period when ongoing brain development coincides with a substantially increased risk of psychiatric disorders. The developmental brain changes accounting for this emergent psychiatric symptomatology remain obscure. Capitalizing on a unique longitudinal dataset that includes in vivo myelin-sensitive magnetization transfer (MT) MRI scans, we show that this developmental period is characterized by brain-wide growth in MT trajectories within both gray matter and adjacent juxtacortical white matter. In this healthy population, the expression of common developmental traits, namely compulsivity and impulsivity, is tied to a reduced growth of these MT trajectories in frontostriatal regions. This reduction is most marked in dorsomedial and dorsolateral prefrontal regions for compulsivity and in lateral and medial prefrontal regions for impulsivity. These findings highlight that psychiatric traits of compulsivity and impulsivity are linked to regionally specific reductions in myelin-related growth in late adolescent brain development.
Collapse
Affiliation(s)
- Gabriel Ziegler
- Max Planck University College London Centre for Computational Psychiatry and Ageing Research, London, UK.
- Wellcome Centre for Human Neuroimaging, University College London, London, UK.
- Institute of Cognitive Neurology and Dementia Research, Otto-von-Guericke-University Magdeburg, Magdeburg, Germany.
- German Center for Neurodegenerative Diseases (DZNE), Magdeburg, Germany.
| | - Tobias U Hauser
- Max Planck University College London Centre for Computational Psychiatry and Ageing Research, London, UK.
- Wellcome Centre for Human Neuroimaging, University College London, London, UK.
| | - Michael Moutoussis
- Max Planck University College London Centre for Computational Psychiatry and Ageing Research, London, UK
- Wellcome Centre for Human Neuroimaging, University College London, London, UK
| | - Edward T Bullmore
- Department of Psychiatry, University of Cambridge, Cambridge, UK
- Cambridgeshire and Peterborough National Health Service Foundation Trust, Cambridge, UK
- Medical Research Council/Wellcome Trust Behavioural and Clinical Neuroscience Institute, University of Cambridge, Cambridge, UK
- ImmunoPsychiatry, GlaxoSmithKline Research and Development, Stevenage, UK
| | - Ian M Goodyer
- Department of Psychiatry, University of Cambridge, Cambridge, UK
- Cambridgeshire and Peterborough National Health Service Foundation Trust, Cambridge, UK
| | - Peter Fonagy
- Research Department of Clinical, Educational and Health Psychology, University College London, London, UK
| | - Peter B Jones
- Department of Psychiatry, University of Cambridge, Cambridge, UK
- Cambridgeshire and Peterborough National Health Service Foundation Trust, Cambridge, UK
| | - Ulman Lindenberger
- Max Planck University College London Centre for Computational Psychiatry and Ageing Research, London, UK
- Center for Lifespan Psychology, Max Planck Institute for Human Development, Berlin, Germany
| | - Raymond J Dolan
- Max Planck University College London Centre for Computational Psychiatry and Ageing Research, London, UK
- Wellcome Centre for Human Neuroimaging, University College London, London, UK
| |
Collapse
|
123
|
Schall M, Iordanishvili E, Mauler J, Oros-Peusquens AM, Shah NJ. Increasing body mass index in an elderly cohort: Effects on the quantitative MR parameters of the brain. J Magn Reson Imaging 2019; 51:514-523. [PMID: 31150149 DOI: 10.1002/jmri.26807] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/24/2019] [Revised: 05/14/2019] [Accepted: 05/16/2019] [Indexed: 12/25/2022] Open
Abstract
BACKGROUND Body mass index (BMI) is increasing in a large number of elderly persons. This increase in BMI is known to put one at risk for many "diseases of aging," although less is known about how a change in BMI may affect the brains of the elderly. PURPOSE To investigate the relationship between BMI and quantitative water content, T1 , T2 *, and the semi-quantitative magnetization transfer ratio (MTR) of various structures in elderly brains. STUDY TYPE Cross-sectional. SUBJECTS Forty-two adults (BMI range: 19.1-33.5 kg/m2 , age range: 58-80 years). FIELD STRENGTH 3T MRI (two multi-echo gradient echoes, actual flip angle imaging, magnetization prepared rapid gradient echo, fluid attenuated inversion recovery). ASSESSMENT The 3D two-point method was used to derive (semi-)quantitative parameters in global white (WM) and gray matter (GM) and their regions as defined by the Johns Hopkins University and the Montreal Neurological Institute atlases. STATISTICAL TESTS Multivariate linear regression with BMI as principal regressor, corrected for the additional regressors age, gender, and glycated hemoglobin. Spearman correlation between quantitative parameters of the regions showing significant changes and the lipid spectra / C-reactive protein (CRP). Voxel-based morphometry and analysis of covariance (ANCOVA) to explore changes in the GM volume. RESULTS T1 increased significantly (P < 0.05) in the frontal, temporal, and parietal cortices, while the bilateral corona radiata, right superior longitudinal fasciculus, as well as the corpus callosum showed significant changes in the WM regions. T2 * increased significantly in the global WM and left corona radiata. Changes in MTR and the free water content did not reach significance. No significant correlation between any quantitative parameter and the lipid spectra or CRP could be identified. DATA CONCLUSION These results suggest that an elevated BMI predominantly affects T1 in WM as well as GM structures in the elderly human brain. LEVEL OF EVIDENCE 3 Technical Efficacy: Stage 3 J. Magn. Reson. Imaging 2020;51:514-523.
Collapse
Affiliation(s)
- Melissa Schall
- Research Centre Jülich, Institute of Neuroscience and Medicine 4 (INM-4), Jülich, Germany
| | - Elene Iordanishvili
- Research Centre Jülich, Institute of Neuroscience and Medicine 4 (INM-4), Jülich, Germany
| | - Jörg Mauler
- Research Centre Jülich, Institute of Neuroscience and Medicine 4 (INM-4), Jülich, Germany
| | | | - N Jon Shah
- Research Centre Jülich, Institute of Neuroscience and Medicine 4 (INM-4), Jülich, Germany.,Research Centre Jülich, Institute of Neuroscience and Medicine 11 (INM-11), Jülich, Germany.,Jülich Aachen Research Alliance (JARA-BRAIN) - Translational Medicine, Aachen, Germany.,Department of Neurology of the RWTH Aachen University, Aachen, Germany
| |
Collapse
|
124
|
Lommers E, Simon J, Reuter G, Delrue G, Dive D, Degueldre C, Balteau E, Phillips C, Maquet P. Multiparameter MRI quantification of microstructural tissue alterations in multiple sclerosis. NEUROIMAGE-CLINICAL 2019; 23:101879. [PMID: 31176293 PMCID: PMC6555891 DOI: 10.1016/j.nicl.2019.101879] [Citation(s) in RCA: 41] [Impact Index Per Article: 8.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 01/29/2019] [Revised: 04/23/2019] [Accepted: 05/25/2019] [Indexed: 01/25/2023]
Abstract
Objectives Conventional MRI is not sensitive to many pathological processes underpinning multiple sclerosis (MS) ongoing in normal appearing brain tissue (NABT). Quantitative MRI (qMRI) and a multiparameter mapping (MPM) protocol are used to simultaneously quantify magnetization transfer (MT) saturation, transverse relaxation rate R2* (1/T2*) and longitudinal relaxation rate R1 (1/T1), and assess differences in NABT microstructure between MS patients and healthy controls (HC). Methods This prospective cross-sectional study involves 36 MS patients (21 females, 15 males; age range 22–63 years; 15 relapsing-remitting MS - RRMS; 21 primary or secondary progressive MS - PMS) and 36 age-matched HC (20 females, 16 males); age range 21–61 years). The qMRI maps are computed and segmented in lesions and 3 normal appearing cerebral tissue classes: normal appearing cortical grey matter (NACGM), normal appearing deep grey matter (NADGM), normal appearing white matter (NAWM). Individual median values are extracted for each tissue class and MR parameter. MANOVAs and stepwise regressions assess differences between patients and HC. Results MS patients are characterized by a decrease in MT, R2* and R1 within NACGM (p < .0001) and NAWM (p < .0001). In NADGM, MT decreases (p < .0001) but R2* and R1 remain normal. These observations tend to be more pronounced in PMS. Quantitative MRI parameters are independent predictors of clinical status: EDSS is significantly related to R1 in NACGM and R2* in NADGM; the latter also predicts motor score. Cognitive score is best predicted by MT parameter within lesions. Conclusions Multiparametric data of brain microstructure concord with the literature, predict clinical performance and suggest a diffuse reduction in myelin and/or iron content within NABT of MS patients. We revisit microstructural alterations of NABT in MS patients by simultaneously quantifying three MRI parameters. Data suggest reduction of MT/R2*/R1 in NABT of MS patients, suggesting a reduction in myelin and/or iron content. Quantitative MRI parameters in NABT are independent predictors of clinical status.
Collapse
Affiliation(s)
- Emilie Lommers
- GIGA - CRC in vivo Imaging, University of Liège, Liège, Belgium; Clinical Neuroimmunology Unit, Neurology Department, CHU Liège, Belgium.
| | - Jessica Simon
- Psychology and Neurosciences of Cognition Research Unit, University of Liège, Belgium
| | - Gilles Reuter
- GIGA - CRC in vivo Imaging, University of Liège, Liège, Belgium; Neurosurgery Department, CHU Liège, Belgium
| | - Gaël Delrue
- Clinical Neuroimmunology Unit, Neurology Department, CHU Liège, Belgium
| | - Dominique Dive
- Clinical Neuroimmunology Unit, Neurology Department, CHU Liège, Belgium
| | | | - Evelyne Balteau
- GIGA - CRC in vivo Imaging, University of Liège, Liège, Belgium
| | - Christophe Phillips
- GIGA - CRC in vivo Imaging, University of Liège, Liège, Belgium; GIGA - in silico Medicine, University of Liège, Liège, Belgium
| | - Pierre Maquet
- GIGA - CRC in vivo Imaging, University of Liège, Liège, Belgium; Clinical Neuroimmunology Unit, Neurology Department, CHU Liège, Belgium
| |
Collapse
|
125
|
Russo AG, Ponticorvo S, Tartaglione I, Caiazza M, Roberti D, Elefante A, Casale M, Di Concilio R, Ciancio A, De Michele E, Canna A, Cirillo M, Perrotta S, Esposito F, Manara R. No increased cerebrovascular involvement in adult beta-thalassemia by advanced MRI analyses. Blood Cells Mol Dis 2019; 78:9-13. [PMID: 31102961 DOI: 10.1016/j.bcmd.2019.05.001] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/31/2019] [Revised: 05/01/2019] [Accepted: 05/02/2019] [Indexed: 10/26/2022]
Abstract
Beta-thalassemia-related anemia and chronic hypercoagulative state are supposed to cause cumulative cerebrovascular damage with consequent parenchymal/vascular changes and functional impairment. However, recent conventional MRI/MR-angiography investigations failed to show an increased cerebrovascular involvement in beta-thalassemia patients managed according to current treatment guidelines, in spite of significantly decreased full-scale IQ scores. We therefore investigated those patients and controls by means of advanced quantitative MRI analyses (based on magnetization transfer and diffusion tensor imaging) searching for signs of possible cerebrovascular injuries undetected by conventional MRI/MR-angiography. The 3 T-MRI study protocol included diffusion tensor imaging and 3D-multi-echo FLASH sequences for magnetization transfer analysis. Whole-brain voxel-based analyses showed that magnetization transfer, fractional anisotropy, and mean, radial and axial diffusivity do not differ between healthy controls and beta-thalassemia patients (considered as a whole group or as distinct transfusion dependent and non-transfusion dependent subgroups). No correlation emerged between all the considered MRI metrics and cognitive findings (full-scale IQ) or the main clinical and laboratory data. According to our findings, adult neurologically-asymptomatic beta-thalassemia patients (regardless of clinical severity) do not seem to present an increased disease-related cerebrovascular vulnerability compared to healthy controls downsizing the need of regular brain MRI monitoring, at least when the current treatment guidelines are followed.
Collapse
Affiliation(s)
- Andrea Gerardo Russo
- Dipartimento di Medicina e Chirurgia, Scuola Medica Salernitana, Sezione di Neuroscienze, Università di Salerno, Salerno, Italy
| | - Sara Ponticorvo
- Dipartimento di Medicina e Chirurgia, Scuola Medica Salernitana, Sezione di Neuroscienze, Università di Salerno, Salerno, Italy
| | - Immacolata Tartaglione
- Dipartimento della Donna, del Bambino e di Chirurgia Generale e Specialistica, Università degli studi della Campania "Luigi Vanvitelli", Napoli, Italy
| | - Martina Caiazza
- Dipartimento della Donna, del Bambino e di Chirurgia Generale e Specialistica, Università degli studi della Campania "Luigi Vanvitelli", Napoli, Italy
| | - Domenico Roberti
- Dipartimento della Donna, del Bambino e di Chirurgia Generale e Specialistica, Università degli studi della Campania "Luigi Vanvitelli", Napoli, Italy
| | - Andrea Elefante
- Neuroradiologia, Università degli Studi di Napoli "Federico II", Napoli, Italy
| | - Maddalena Casale
- Dipartimento della Donna, del Bambino e di Chirurgia Generale e Specialistica, Università degli studi della Campania "Luigi Vanvitelli", Napoli, Italy
| | | | - Angela Ciancio
- Unità Operativa Ematologia - Day Hospital di Talassemia, Ospedale "Madonna delle Grazie", Matera, Italy
| | - Elisa De Michele
- Medicina Trasfusionale AUO "San Giovanni di Dio e Ruggi D'Aragona", Salerno, Italy
| | - Antonietta Canna
- Dipartimento di Medicina e Chirurgia, Scuola Medica Salernitana, Sezione di Neuroscienze, Università di Salerno, Salerno, Italy
| | - Mario Cirillo
- Dipartimento di Scienze Mediche, Chirurgiche, Neurologiche, Metaboliche e dell'Invecchiamento, Università della Campania "Luigi Vanvitelli", Napoli, Italy
| | - Silverio Perrotta
- Dipartimento della Donna, del Bambino e di Chirurgia Generale e Specialistica, Università degli studi della Campania "Luigi Vanvitelli", Napoli, Italy
| | - Fabrizio Esposito
- Dipartimento di Medicina e Chirurgia, Scuola Medica Salernitana, Sezione di Neuroscienze, Università di Salerno, Salerno, Italy
| | - Renzo Manara
- Dipartimento di Medicina e Chirurgia, Scuola Medica Salernitana, Sezione di Neuroscienze, Università di Salerno, Salerno, Italy.
| |
Collapse
|
126
|
Slater DA, Melie‐Garcia L, Preisig M, Kherif F, Lutti A, Draganski B. Evolution of white matter tract microstructure across the life span. Hum Brain Mapp 2019; 40:2252-2268. [PMID: 30673158 PMCID: PMC6865588 DOI: 10.1002/hbm.24522] [Citation(s) in RCA: 75] [Impact Index Per Article: 15.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/05/2018] [Revised: 12/28/2018] [Accepted: 01/02/2019] [Indexed: 01/13/2023] Open
Abstract
The human brain undergoes dramatic structural change over the life span. In a large imaging cohort of 801 individuals aged 7-84 years, we applied quantitative relaxometry and diffusion microstructure imaging in combination with diffusion tractography to investigate tissue property dynamics across the human life span. Significant nonlinear aging effects were consistently observed across tracts and tissue measures. The age at which white matter (WM) fascicles attain peak maturation varies substantially across tissue measurements and tracts. These observations of heterochronicity and spatial heterogeneity of tract maturation highlight the importance of using multiple tissue measurements to investigate each region of the WM. Our data further provide additional quantitative evidence in support of the last-in-first-out retrogenesis hypothesis of aging, demonstrating a strong correlational relationship between peak maturational timing and the extent of quadratic measurement differences across the life span for the most myelin sensitive measures. These findings present an important baseline from which to assess divergence from normative aging trends in developmental and degenerative disorders, and to further investigate the mechanisms connecting WM microstructure to cognition.
Collapse
Affiliation(s)
- David A. Slater
- Laboratory of Research in Neuroimaging (LREN) – Department of Clinical Neurosciences – CHUVUniversity of LausanneLausanneSwitzerland
| | - Lester Melie‐Garcia
- Laboratory of Research in Neuroimaging (LREN) – Department of Clinical Neurosciences – CHUVUniversity of LausanneLausanneSwitzerland
| | - Martin Preisig
- Department of Psychiatry – CHUVUniversity of LausanneLausanneSwitzerland
| | - Ferath Kherif
- Laboratory of Research in Neuroimaging (LREN) – Department of Clinical Neurosciences – CHUVUniversity of LausanneLausanneSwitzerland
| | - Antoine Lutti
- Laboratory of Research in Neuroimaging (LREN) – Department of Clinical Neurosciences – CHUVUniversity of LausanneLausanneSwitzerland
| | - Bogdan Draganski
- Laboratory of Research in Neuroimaging (LREN) – Department of Clinical Neurosciences – CHUVUniversity of LausanneLausanneSwitzerland
- Department of Clinical NeurosciencesMax‐Planck‐Institute for Human Cognitive and Brain SciencesLeipzigGermany
| |
Collapse
|
127
|
Karolis VR, Callaghan MF, Tseng CEJ, Hope T, Weiskopf N, Rees G, Cappelletti M. Spatial gradients of healthy aging: a study of myelin-sensitive maps. Neurobiol Aging 2019; 79:83-92. [PMID: 31029019 DOI: 10.1016/j.neurobiolaging.2019.03.002] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/08/2017] [Revised: 02/06/2019] [Accepted: 03/05/2019] [Indexed: 10/27/2022]
Abstract
Protracted development of a brain network may entail greater susceptibility to aging decline, supported by evidence of an earlier onset of age-related changes in late-maturing anterior areas, that is, an anterior-to-posterior gradient of brain aging. Here we analyzed the spatiotemporal features of age-related differences in myelin content across the human brain indexed by magnetization transfer (MT) concentration in a cross-sectional cohort of healthy adults. We described age-related spatial gradients in MT, which may reflect the reversal of patterns observed in development. We confirmed an anterior-to-posterior gradient of age-related MT decrease and also showed a lateral-to-ventral gradient inversely mirroring the sequence of connectivity development and myelination. MT concentration in the lateral white matter regions continued to increase up to the age of 45 years and decreased moderately following a peak. In contrast, ventral white matter regions reflected life-long stable MT concentration levels, followed by a rapid decrease at a later age. We discussed our findings in relation with existing theories of brain aging, including the lack of support for the proposal that areas which mature later decline at an accelerated rate.
Collapse
Affiliation(s)
- Vyacheslav R Karolis
- FMRIB centre, John Radcliffe Hospital, University of Oxford, Oxford, UK; Institute of Psychiatry, Psychology, and Neuroscience, King's College London, London, UK.
| | - Martina F Callaghan
- Wellcome Trust Centre for Neuroimaging, UCL Institute of Neurology, London, UK
| | - Chieh-En Jane Tseng
- Institute of Psychiatry, Psychology, and Neuroscience, King's College London, London, UK; Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Charlestown, USA
| | - Thomas Hope
- Wellcome Trust Centre for Neuroimaging, UCL Institute of Neurology, London, UK
| | - Nikolaus Weiskopf
- Wellcome Trust Centre for Neuroimaging, UCL Institute of Neurology, London, UK; Department of Neurophysics, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
| | - Geraint Rees
- UCL Institute of Cognitive Neuroscience, London, UK
| | - Marinella Cappelletti
- UCL Institute of Cognitive Neuroscience, London, UK; Psychology Department, Goldsmiths University of London, London, UK
| |
Collapse
|
128
|
Papadaki E, Kavroulakis E, Kalaitzakis G, Karageorgou D, Makrakis D, Maris TG, Simos PG. Age‐related deep white matter changes in myelin and water content: A T
2
relaxometry study. J Magn Reson Imaging 2019; 50:1393-1404. [DOI: 10.1002/jmri.26707] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/05/2018] [Revised: 02/16/2019] [Accepted: 02/19/2019] [Indexed: 11/11/2022] Open
Affiliation(s)
- Efrosini Papadaki
- Department of RadiologySchool of Medicine, University of Crete Heraklion, Crete Greece
- Institute of Computer ScienceFoundation of Research and Technology Heraklion Greece
| | | | - Georgios Kalaitzakis
- Department of Medical PhysicsSchool of Medicine, University of Crete Heraklion, Crete Greece
| | - Dimitra Karageorgou
- Department of RadiologySchool of Medicine, University of Crete Heraklion, Crete Greece
| | - Dimitrios Makrakis
- Department of RadiologySchool of Medicine, University of Crete Heraklion, Crete Greece
| | - Thomas G. Maris
- Institute of Computer ScienceFoundation of Research and Technology Heraklion Greece
- Department of Medical PhysicsSchool of Medicine, University of Crete Heraklion, Crete Greece
| | - Panagiotis G. Simos
- Institute of Computer ScienceFoundation of Research and Technology Heraklion Greece
- Department of PsychiatrySchool of Medicine, University of Crete Heraklion, Crete Greece
| |
Collapse
|
129
|
O'Muircheartaigh J, Vavasour I, Ljungberg E, Li DKB, Rauscher A, Levesque V, Garren H, Clayton D, Tam R, Traboulsee A, Kolind S. Quantitative neuroimaging measures of myelin in the healthy brain and in multiple sclerosis. Hum Brain Mapp 2019; 40:2104-2116. [PMID: 30648315 PMCID: PMC6590140 DOI: 10.1002/hbm.24510] [Citation(s) in RCA: 44] [Impact Index Per Article: 8.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/20/2018] [Revised: 12/28/2018] [Accepted: 01/02/2019] [Indexed: 12/25/2022] Open
Abstract
Quantitative magnetic resonance imaging (MRI) techniques have been developed as imaging biomarkers, aiming to improve the specificity of MRI to underlying pathology compared to conventional weighted MRI. For assessing the integrity of white matter (WM), myelin, in particular, several techniques have been proposed and investigated individually. However, comparisons between these methods are lacking. In this study, we compared four established myelin‐sensitive MRI techniques in 56 patients with relapsing–remitting multiple sclerosis (MS) and 38 healthy controls. We used T2‐relaxation with combined GRadient And Spin Echoes (GRASE) to measure myelin water fraction (MWF‐G), multi‐component driven equilibrium single pulse observation of T1 and T2 (mcDESPOT) to measure MWF‐D, magnetization‐transfer imaging to measure magnetization‐transfer ratio (MTR), and T1 relaxation to measure quantitative T1 (qT1). Using voxelwise Spearman correlations, we tested the correspondence of methods throughout the brain. All four methods showed associations that varied across tissue types; the highest correlations were found between MWF‐D and qT1 (median ρ across tissue classes 0.8) and MWF‐G and MWF‐D (median ρ = 0.59). In eight WM tracts, all measures showed differences (p < 0.05) between MS normal‐appearing WM and healthy control WM, with qT1 showing the highest number of different regions (8), followed by MWF‐D and MTR (6), and MWF‐G (n = 4). Comparing the methods in terms of their statistical sensitivity to MS lesions in WM, MWF‐D demonstrated the best accuracy (p < 0.05, after multiple comparison correction). To aid future power analysis, we provide the average and standard deviation volumes of the four techniques, estimated from the healthy control sample.
Collapse
Affiliation(s)
- Jonathan O'Muircheartaigh
- Department of Forensic and Neurodevelopmental Sciences, Institute of Psychiatry Psychology and Neuroscience, King's College London, London, United Kingdom.,Centre for the Developing Brain, Department of Perinatal Imaging and Health, St. Thomas' Hospital, King's College London, London, United Kingdom.,Department of Neuroimaging, Institute of Psychiatry Psychology and Neuroscience, King's College London, London, United Kingdom.,MRC Centre for Neurodevelopmental Disorders, King's College London, London, United Kingdom
| | - Irene Vavasour
- Department of Radiology, University of British Columbia, Vancouver, British Columbia, Canada
| | - Emil Ljungberg
- Department of Neuroimaging, Institute of Psychiatry Psychology and Neuroscience, King's College London, London, United Kingdom
| | - David K B Li
- Department of Radiology, University of British Columbia, Vancouver, British Columbia, Canada.,MS/MRI Research Group, Djavad Mowafaghian Centre for Brain Health, University of British Columbia, Vancouver, British Columbia, Canada
| | - Alexander Rauscher
- Department of Radiology, University of British Columbia, Vancouver, British Columbia, Canada.,Department of Physics and Astronomy, University of British Columbia, Vancouver, British Columbia, Canada.,Department of Pediatrics, University of British Columbia, Vancouver, British Columbia, Canada
| | | | | | | | - Roger Tam
- Department of Radiology, University of British Columbia, Vancouver, British Columbia, Canada.,MS/MRI Research Group, Djavad Mowafaghian Centre for Brain Health, University of British Columbia, Vancouver, British Columbia, Canada.,School of Biomedical Engineering, University of British Columbia, Vancouver, British Columbia, Canada
| | - Anthony Traboulsee
- MS/MRI Research Group, Djavad Mowafaghian Centre for Brain Health, University of British Columbia, Vancouver, British Columbia, Canada.,Division of Neurology, Department of Medicine, University of British Columbia, Vancouver, British Columbia, Canada
| | - Shannon Kolind
- Department of Radiology, University of British Columbia, Vancouver, British Columbia, Canada.,MS/MRI Research Group, Djavad Mowafaghian Centre for Brain Health, University of British Columbia, Vancouver, British Columbia, Canada.,Department of Physics and Astronomy, University of British Columbia, Vancouver, British Columbia, Canada.,Division of Neurology, Department of Medicine, University of British Columbia, Vancouver, British Columbia, Canada
| |
Collapse
|
130
|
Carey D, Nolan H, Kenny RA, Meaney J. Cortical covariance networks in ageing: Cross-sectional data from the Irish Longitudinal Study on Ageing (TILDA). Neuropsychologia 2019; 122:51-61. [DOI: 10.1016/j.neuropsychologia.2018.11.013] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/28/2018] [Revised: 11/24/2018] [Accepted: 11/26/2018] [Indexed: 01/06/2023]
|
131
|
Volz S, Callaghan MF, Josephs O, Weiskopf N. Maximising BOLD sensitivity through automated EPI protocol optimisation. Neuroimage 2018; 189:159-170. [PMID: 30593904 PMCID: PMC6435104 DOI: 10.1016/j.neuroimage.2018.12.052] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/11/2018] [Revised: 12/23/2018] [Accepted: 12/24/2018] [Indexed: 11/23/2022] Open
Abstract
Gradient echo echo-planar imaging (GE EPI) is used for most fMRI studies but can suffer substantially from image distortions and BOLD sensitivity (BS) loss due to susceptibility-induced magnetic field inhomogeneities. While there are various post-processing methods for correcting image distortions, signal dropouts cannot be recovered and therefore need to be addressed at the data acquisition stage. Common approaches for reducing susceptibility-related BS loss in selected brain areas are: z-shimming, inverting the phase encoding (PE) gradient polarity, optimizing the slice tilt and increasing spatial resolution. The optimization of these parameters can be based on atlases derived from multiple echo-planar imaging (EPI) acquisitions. However, this requires resource and time, which imposes a practical limitation on the range over which parameters can be optimised meaning that the chosen settings may still be sub-optimal. To address this issue, we have developed an automated method that can be used to optimize across a large parameter space. It is based on numerical signal simulations of the BS loss predicted by physical models informed by a large database of magnetic field (B0) maps acquired on a broad cohort of participants. The advantage of our simulation-based approach compared to previous methods is that it saves time and expensive measurements and allows for optimizing EPI protocols by incorporating a broad range of factors, including different resolutions, echo times or slice orientations. To verify the numerical optimisation, results are compared to those from an earlier study and to experimental BS measurements carried out in six healthy volunteers. Significant BOLD sensitivity increase by optimization of z-shim, gradient polarity and slice tilt. Method based on numerical signal simulations informed by large database of magnetic field maps. Saves time and expensive measurements. Automated and flexible optimization of multiple EPI parameter settings.
Collapse
Affiliation(s)
- Steffen Volz
- Department of Neurophysics, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany; Wellcome Centre for Human Neuroimaging, UCL Institute of Neurology, University College London, London, UK.
| | - Martina F Callaghan
- Wellcome Centre for Human Neuroimaging, UCL Institute of Neurology, University College London, London, UK
| | - Oliver Josephs
- Wellcome Centre for Human Neuroimaging, UCL Institute of Neurology, University College London, London, UK
| | - Nikolaus Weiskopf
- Department of Neurophysics, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany; Wellcome Centre for Human Neuroimaging, UCL Institute of Neurology, University College London, London, UK
| |
Collapse
|
132
|
Guerreri M, Palombo M, Caporale A, Fasano F, Macaluso E, Bozzali M, Capuani S. Age-related microstructural and physiological changes in normal brain measured by MRI γ-metrics derived from anomalous diffusion signal representation. Neuroimage 2018; 188:654-667. [PMID: 30583064 DOI: 10.1016/j.neuroimage.2018.12.044] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/14/2018] [Revised: 12/11/2018] [Accepted: 12/20/2018] [Indexed: 12/29/2022] Open
Abstract
Nowadays, increasing longevity associated with declining cerebral nervous system functions, suggests the need for continued development of new imaging contrast mechanisms to support the differential diagnosis of age-related decline. In our previous papers, we developed a new imaging contrast metrics derived from anomalous diffusion signal representation and obtained from diffusion-weighted (DW) data collected by varying diffusion gradient strengths. Recently, we highlighted that the new metrics, named γ-metrics, depended on the local inhomogeneity due to differences in magnetic susceptibility between tissues and diffusion compartments in young healthy subjects, thus providing information about myelin orientation and iron content within cerebral regions. The major structural modifications occurring in brain aging are myelinated fibers damage in nerve fibers and iron accumulation in gray matter nuclei. Therefore, we investigated the potential of γ-metrics in relation to other conventional diffusion metrics such as DTI, DKI and NODDI in detecting age-related structural changes in white matter (WM) and subcortical gray matter (scGM). DW-images were acquired in 32 healthy subjects, adults and elderly (age range 20-77 years) using 3.0T and 12 b-values up to 5000 s/mm2. Association between diffusion metrics and subjects' age was assessed using linear regression. A decline in mean γ (Mγ) in the scGM and a complementary increase in radial γ (γ⊥) in frontal WM, genu of corpus callosum and anterior corona radiata with advancing age were found. We suggested that the increase in γ⊥ might reflect declined myelin density, and Mγ decrease might mirror iron accumulation. An increase in D// and a decrease in the orientation dispersion index (ODI) were associated with axonal loss in the pyramidal tracts, while their inverted trends within the thalamus were thought to be linked to reduced architectural complexity of nerve fibers. γ-metrics together with conventional diffusion-metrics can more comprehensively characterize the complex mechanisms underlining age-related changes than conventional diffusion techniques alone.
Collapse
Affiliation(s)
- Michele Guerreri
- SAIMLAL Department, Sapienza, Piazzale Aldo Moro, 5, 00185, Roma, RM, Italy; Institute for Complex Systems, CNR, Rome, Italy.
| | - Marco Palombo
- Institute for Complex Systems, CNR, Rome, Italy; Department of Computer Science & Centre for Medical Image Computing, University College London, London, United Kingdom
| | - Alessandra Caporale
- Institute for Complex Systems, CNR, Rome, Italy; Laboratory for Structural, Physiologic and Functional Imaging, Perelman School of Medicine University of Pennsylvania, Philadelphia, PA, USA
| | | | | | - Marco Bozzali
- Neuroimaging Laboratory, Santa Lucia Foundation, Rome, Italy
| | - Silvia Capuani
- Institute for Complex Systems, CNR, Rome, Italy; Neuroimaging Laboratory, Santa Lucia Foundation, Rome, Italy
| |
Collapse
|
133
|
Chen Y, Chen MH, Baluyot KR, Potts TM, Jimenez J, Lin W. MR fingerprinting enables quantitative measures of brain tissue relaxation times and myelin water fraction in the first five years of life. Neuroimage 2018; 186:782-793. [PMID: 30472371 DOI: 10.1016/j.neuroimage.2018.11.038] [Citation(s) in RCA: 44] [Impact Index Per Article: 7.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/27/2018] [Revised: 11/20/2018] [Accepted: 11/21/2018] [Indexed: 12/19/2022] Open
Abstract
Quantitative assessments of normative brain development using MRI are of critical importance to gain insights into healthy neurodevelopment. However, quantitative MR imaging poses significant technical challenges and requires prohibitively long acquisition times, making it impractical for pediatric imaging. This is particularly relevant for healthy subjects, where imaging under sedation is not clinically indicated. MR Fingerprinting (MRF), a novel MR imaging framework, provides rapid, efficient, and simultaneous quantification of multiple tissue properties. In this study, a 2D MR Fingerprinting method was developed that achieves a spatial resolution of 1 × 1 × 3 mm3 with rapid and simultaneous quantification of T1, T2 and myelin water fraction (MWF). Phantom experiments demonstrated that accurate measurements of T1 and T2 relaxation times were achieved over a wide range of T1 and T2 values. MRF images were acquired cross-sectionally from 28 typically developing children, 0 to five years old, who were enrolled in the UNC/UMN Baby Connectome Project. Differences associated with age of R1 (=1/T1), R2 (=1/T2) and MWF were obtained from several predefined white matter regions. Both R1 and R2 exhibit a marked increase until ∼20 months of age, followed by a slower increase for all WM regions. In contrast, the MWF remains at a negligible level until ∼6 months of age for all predefined ROIs and gradually increases afterwards. Depending on the brain region, rapid increases are observed between 6 and 12 months to 6-18 months, followed by a slower pace of increase in MWF. Neither relaxivities nor MWF were significantly different between the left and right hemispheres. However, regional differences in age-related R1 and MWF measures were observed across different white matter regions. In conclusion, our results demonstrate that the MRF technique holds great potential for multi-parametric assessments of normative brain development in early childhood.
Collapse
Affiliation(s)
- Yong Chen
- Departments of Radiology, University of North Carolina, Chapel Hill, NC, USA; Biomedical Research Imaging Center (BRIC), University of North Carolina at Chapel Hill, NC, USA
| | | | - Kristine R Baluyot
- Biomedical Research Imaging Center (BRIC), University of North Carolina at Chapel Hill, NC, USA
| | - Taylor M Potts
- Biomedical Research Imaging Center (BRIC), University of North Carolina at Chapel Hill, NC, USA
| | - Jordan Jimenez
- Biomedical Research Imaging Center (BRIC), University of North Carolina at Chapel Hill, NC, USA
| | - Weili Lin
- Departments of Radiology, University of North Carolina, Chapel Hill, NC, USA; Biomedical Research Imaging Center (BRIC), University of North Carolina at Chapel Hill, NC, USA.
| | | |
Collapse
|
134
|
Gonzalez-Escamilla G, Muthuraman M, Chirumamilla VC, Vogt J, Groppa S. Brain Networks Reorganization During Maturation and Healthy Aging-Emphases for Resilience. Front Psychiatry 2018; 9:601. [PMID: 30519196 PMCID: PMC6258799 DOI: 10.3389/fpsyt.2018.00601] [Citation(s) in RCA: 19] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/06/2018] [Accepted: 10/29/2018] [Indexed: 12/31/2022] Open
Abstract
Maturation and aging are important life periods that are linked to drastic brain reorganization processes which are essential for mental health. However, the development of generalized theories for delimiting physiological and pathological brain remodeling through life periods linked to healthy states and resilience on one side or mental dysfunction on the other remains a challenge. Furthermore, important processes of preservation and compensation of brain function occur continuously in the cerebral brain networks and drive physiological responses to life events. Here, we review research on brain reorganization processes across the lifespan, demonstrating brain circuits remodeling at the structural and functional level that support mental health and are parallelized by physiological trajectories during maturation and healthy aging. We show evidence that aberrations leading to mental disorders result from the specific alterations of cerebral networks and their pathological dynamics leading to distinct excitability patterns. We discuss how these series of large-scale responses of brain circuits can be viewed as protective or malfunctioning mechanisms for the maintenance of mental health and resilience.
Collapse
Affiliation(s)
| | - Muthuraman Muthuraman
- Department of Neurology, University Medical Center, Johannes Gutenberg University Mainz, Mainz, Germany
| | - Venkata C. Chirumamilla
- Department of Neurology, University Medical Center, Johannes Gutenberg University Mainz, Mainz, Germany
| | - Johannes Vogt
- Institute for Microscopic Anatomy and Neurobiology, University Medical Center, Johannes Gutenberg University Mainz, Mainz, Germany
| | - Sergiu Groppa
- Department of Neurology, University Medical Center, Johannes Gutenberg University Mainz, Mainz, Germany
| |
Collapse
|
135
|
Microstructural imaging of human neocortex in vivo. Neuroimage 2018; 182:184-206. [DOI: 10.1016/j.neuroimage.2018.02.055] [Citation(s) in RCA: 75] [Impact Index Per Article: 12.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/09/2017] [Revised: 02/13/2018] [Accepted: 02/26/2018] [Indexed: 12/12/2022] Open
|
136
|
Evidence of Human Parvovirus B19 Infection in the Post-Mortem Brain Tissue of the Elderly. Viruses 2018; 10:v10110582. [PMID: 30366357 PMCID: PMC6267580 DOI: 10.3390/v10110582] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/23/2018] [Revised: 10/23/2018] [Accepted: 10/24/2018] [Indexed: 02/06/2023] Open
Abstract
After primary exposure, the human parvovirus B19 (B19V) genome may remain in the central nervous system (CNS), establishing a lifelong latency. The structural characteristics and functions of the infected cells are essential for the virus to complete its life cycle. Although B19V has been detected in the brain tissue by sequencing PCR products, little is known about its in vivo cell tropism and pathogenic potential in the CNS. To detect B19V and investigate the distribution of its target cells in the CNS, we studied brain autopsies of elderly subjects using molecular virology, and optical and electron microscopy methods. Our study detected B19V in brain tissue samples from both encephalopathy and control groups, suggesting virus persistence within the CNS throughout the host’s lifetime. It appears that within the CNS, the main target of B19V is oligodendrocytes. The greatest number of B19V-positive oligodendrocytes was found in the white matter of the frontal lobe. The number was significantly lower in the gray matter of the frontal lobe (p = 0.008) and the gray and white matter of the temporal lobes (p < 0.0001). The morphological changes observed in the encephalopathy group, propose a possible B19V involvement in the demyelination process.
Collapse
|
137
|
Liu C, Jin C, Jian Z, Wang M, Li X, Liu H, Sun Q, Zeng L, Yang J. Assessment of myelination progression in subcortical white matter of children aged 6–48 months using T2-weighted imaging. Neuroradiology 2018; 60:1343-1351. [DOI: 10.1007/s00234-018-2108-z] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/06/2018] [Accepted: 09/27/2018] [Indexed: 11/29/2022]
|
138
|
Kievit RA, Brandmaier AM, Ziegler G, van Harmelen AL, de Mooij SMM, Moutoussis M, Goodyer IM, Bullmore E, Jones PB, Fonagy P, Lindenberger U, Dolan RJ. Developmental cognitive neuroscience using latent change score models: A tutorial and applications. Dev Cogn Neurosci 2018; 33:99-117. [PMID: 29325701 PMCID: PMC6614039 DOI: 10.1016/j.dcn.2017.11.007] [Citation(s) in RCA: 229] [Impact Index Per Article: 38.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/17/2017] [Revised: 10/17/2017] [Accepted: 11/17/2017] [Indexed: 12/14/2022] Open
Abstract
Assessing and analysing individual differences in change over time is of central scientific importance to developmental neuroscience. However, the literature is based largely on cross-sectional comparisons, which reflect a variety of influences and cannot directly represent change. We advocate using latent change score (LCS) models in longitudinal samples as a statistical framework to tease apart the complex processes underlying lifespan development in brain and behaviour using longitudinal data. LCS models provide a flexible framework that naturally accommodates key developmental questions as model parameters and can even be used, with some limitations, in cases with only two measurement occasions. We illustrate the use of LCS models with two empirical examples. In a lifespan cognitive training study (COGITO, N = 204 (N = 32 imaging) on two waves) we observe correlated change in brain and behaviour in the context of a high-intensity training intervention. In an adolescent development cohort (NSPN, N = 176, two waves) we find greater variability in cortical thinning in males than in females. To facilitate the adoption of LCS by the developmental community, we provide analysis code that can be adapted by other researchers and basic primers in two freely available SEM software packages (lavaan and Ωnyx).
Collapse
Affiliation(s)
- Rogier A Kievit
- Max Planck Centre for Computational Psychiatry and Ageing Research, London/Berlin; MRC Cognition and Brain Sciences Unit University of Cambridge, Cambridge, 15 Chaucer Rd, Cambridge CB2 7EF.
| | - Andreas M Brandmaier
- Max Planck Centre for Computational Psychiatry and Ageing Research, London/Berlin; Center for Lifespan Psychology, Max Planck Institute for Human Development, Berlin, Germany
| | - Gabriel Ziegler
- Institute of Cognitive Neurology and Dementia Research, Otto-von-Guericke-University Magdeburg, Germany; German Center for Neurodegenerative Diseases (DZNE), Magdeburg, Germany
| | | | | | - Michael Moutoussis
- Max Planck Centre for Computational Psychiatry and Ageing Research, London/Berlin; The Wellcome Centre for Human Neuroimaging, University College London, London WC1N 3BG, United Kingdom
| | - Ian M Goodyer
- Department of Psychiatry, University of Cambridge, United Kingdom
| | - Ed Bullmore
- Department of Psychiatry, University of Cambridge, United Kingdom; Cambridgeshire and Peterborough National Health Service Foundation Trust, Cambridge, CB21 5EF, United Kingdom; ImmunoPsychiatry, GlaxoSmithKline Research and Development, Stevenage SG1 2NY, United Kingdom; Medical Research Council/Wellcome Trust Behavioural and Clinical Neuroscience Institute, University of Cambridge
| | - Peter B Jones
- Department of Psychiatry, University of Cambridge, United Kingdom; Cambridgeshire and Peterborough National Health Service Foundation Trust, Cambridge, CB21 5EF, United Kingdom
| | - Peter Fonagy
- Research Department of Clinical, Educational and Health Psychology, University College London
| | - Ulman Lindenberger
- Max Planck Centre for Computational Psychiatry and Ageing Research, London/Berlin; Center for Lifespan Psychology, Max Planck Institute for Human Development, Berlin, Germany; European University Institute, San Domenico di Fiesole (FI), Italy
| | - Raymond J Dolan
- Max Planck Centre for Computational Psychiatry and Ageing Research, London/Berlin; The Wellcome Centre for Human Neuroimaging, University College London, London WC1N 3BG, United Kingdom
| |
Collapse
|
139
|
Role of gamma-amino-butyric acid in the dorsal anterior cingulate in age-associated changes in cognition. Neuropsychopharmacology 2018; 43:2285-2291. [PMID: 30050047 PMCID: PMC6135795 DOI: 10.1038/s41386-018-0134-5] [Citation(s) in RCA: 23] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/29/2018] [Revised: 05/13/2018] [Accepted: 06/18/2018] [Indexed: 11/08/2022]
Abstract
GABAergic mechanisms have been shown to contribute to cognitive aging in animal models, but there is currently limited in vivo evidence to support this relationship in humans. It is also unclear whether aging is associated with changes in GABA levels measured with proton magnetic resonance spectroscopy (MRS). Spectral-editing MRS at 3 T was used to measure GABA in the dorsal anterior cingulate cortex (dACC) for a large sample of healthy volunteers (N = 229) aged 18-55. In a subset of 171 participants, age effects on several cognitive tasks were studied. We formally tested whether the MRS measures mediated the relationship between age and cognition. Robust associations of age with performance were found for the Wisconsin Card Sorting Test ([WCST], p < 0.0001). Age was also significantly associated with declining levels of GABA in the dACC (p < 0.001), and GABA levels significantly predicted WCST performance (p < 0.0004). Mediation analysis revealed that GABA in the dACC mediated the effect of age on WCST performance (p < 0.01). Other metabolites were similarly associated with age, but only GABA and creatine levels were significantly associated with WCST performance. No association with age or cognitive performance was found in a frontal white matter control region in a subset of participants. The association of GABA with WCST performance was not related to the amount of brain atrophy associated with aging as measured by the proportion of CSF, gray, and white matter in the MRS voxel. These results implicate GABAergic and possibly energetic metabolism in the dACC as mechanisms of age effects in executive function.
Collapse
|
140
|
Liu JL, Fan YG, Yang ZS, Wang ZY, Guo C. Iron and Alzheimer's Disease: From Pathogenesis to Therapeutic Implications. Front Neurosci 2018; 12:632. [PMID: 30250423 PMCID: PMC6139360 DOI: 10.3389/fnins.2018.00632] [Citation(s) in RCA: 174] [Impact Index Per Article: 29.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/03/2018] [Accepted: 08/22/2018] [Indexed: 12/28/2022] Open
Abstract
As people age, iron deposits in different areas of the brain may impair normal cognitive function and behavior. Abnormal iron metabolism generates hydroxyl radicals through the Fenton reaction, triggers oxidative stress reactions, damages cell lipids, protein and DNA structure and function, and ultimately leads to cell death. There is an imbalance in iron homeostasis in Alzheimer's disease (AD). Excessive iron contributes to the deposition of β-amyloid and the formation of neurofibrillary tangles, which in turn, promotes the development of AD. Therefore, iron-targeted therapeutic strategies have become a new direction. Iron chelators, such as desferoxamine, deferiprone, deferasirox, and clioquinol, have received a great deal of attention and have obtained good results in scientific experiments and some clinical trials. Given the limitations and side effects of the long-term application of traditional iron chelators, alpha-lipoic acid and lactoferrin, as self-synthesized naturally small molecules, have shown very intriguing biological activities in blocking Aβ-aggregation, tauopathy and neuronal damage. Despite a lack of evidence for any clinical benefits, the conjecture that therapeutic chelation, with a special focus on iron ions, is a valuable approach for treating AD remains widespread.
Collapse
Affiliation(s)
- Jun-Lin Liu
- College of Life and Health Sciences, Northeastern University, Shenyang, China
| | - Yong-Gang Fan
- College of Life and Health Sciences, Northeastern University, Shenyang, China
| | - Zheng-Sheng Yang
- Department of Dermatology, First Hospital of Qinhuangdao, Qinhuangdao, China
| | - Zhan-You Wang
- College of Life and Health Sciences, Northeastern University, Shenyang, China.,Key Laboratory of Medical Cell Biology of Ministry of Education, Institute of Health Sciences, China Medical University, Shenyang, China
| | - Chuang Guo
- College of Life and Health Sciences, Northeastern University, Shenyang, China
| |
Collapse
|
141
|
Canna A, Ponticorvo S, Russo AG, Manara R, Di Salle F, Saponiero R, Callaghan MF, Weiskopf N, Esposito F. A group-level comparison of volumetric and combined volumetric-surface normalization for whole brain analyses of myelin and iron maps. Magn Reson Imaging 2018; 54:225-240. [PMID: 30176374 DOI: 10.1016/j.mri.2018.08.021] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/18/2018] [Revised: 08/28/2018] [Accepted: 08/28/2018] [Indexed: 12/17/2022]
Abstract
Quantitative MRI (qMRI) provides surrogate brain maps of myelin and iron content. After spatial normalization to a common standard brain space, these may be used to detect altered myelination and iron accumulation in clinical populations. Here, volumetric and combined volumetric and surface-based (CVS) normalization were compared to identify which procedure would afford the greatest sensitivity to inter-regional differences (contrast), and the lowest inter-subject variability (under normal conditions), of myelin- and iron-related qMRI parameters, in whole-brain group-level studies. Ten healthy volunteers were scanned twice at 3 Tesla. Three-dimensional T1-weighted, T2-weighted and multi-parametric mapping sequences for brain qMRI were used to map myelin and iron content over the whole brain. Parameter maps were spatially normalized using volumetric (DARTEL) and CVS procedures. Tissue probability weighting and isotropic Gaussian smoothing were integrated in DARTEL for voxel-based quantification (VBQ). Contrasts, coefficients of variations and sensitivity to detecting differences in the parameters were estimated in standard space for each approach on region of interest (ROI) and voxel-by-voxel bases. The contrast between cortical and subcortical ROIs with respectively different myelin and iron content was higher following CVS, compared to DARTEL-VBQ, normalization. Across cortical voxels, the inter-individual variability of myelin and iron qMRI maps were comparable between CVS (with no smoothing) and DARTEL-VBQ (with smoothing). CVS normalization of qMRI maps preserves higher myelin and iron contrast than DARTEL-VBQ over the entire brain, while exhibiting comparable variability in the cerebral cortex without extra smoothing. Thus, CVS may prove useful for detecting small microstructural differences in whole-brain group-level qMRI studies.
Collapse
Affiliation(s)
- Antonietta Canna
- Department of Medicine, Surgery and Dentistry, Scuola Medica Salernitana, University of Salerno, Baronissi, Salerno, Italy
| | - Sara Ponticorvo
- Department of Medicine, Surgery and Dentistry, Scuola Medica Salernitana, University of Salerno, Baronissi, Salerno, Italy
| | - Andrea G Russo
- Department of Medicine, Surgery and Dentistry, Scuola Medica Salernitana, University of Salerno, Baronissi, Salerno, Italy
| | - Renzo Manara
- Department of Medicine, Surgery and Dentistry, Scuola Medica Salernitana, University of Salerno, Baronissi, Salerno, Italy
| | - Francesco Di Salle
- Department of Medicine, Surgery and Dentistry, Scuola Medica Salernitana, University of Salerno, Baronissi, Salerno, Italy; Department of Diagnostic Imaging, University Hospital "San Giovanni di Dio e Ruggi D'Aragona", Scuola Medica Salernitana, Salerno, Italy
| | - Renato Saponiero
- Department of Diagnostic Imaging, University Hospital "San Giovanni di Dio e Ruggi D'Aragona", Scuola Medica Salernitana, Salerno, Italy
| | - Martina F Callaghan
- Wellcome Centre for Human Neuroimaging, UCL Institute of Neurology, London, UK
| | - Nikolaus Weiskopf
- Department of Neurophysics, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
| | - Fabrizio Esposito
- Department of Medicine, Surgery and Dentistry, Scuola Medica Salernitana, University of Salerno, Baronissi, Salerno, Italy; Department of Diagnostic Imaging, University Hospital "San Giovanni di Dio e Ruggi D'Aragona", Scuola Medica Salernitana, Salerno, Italy.
| |
Collapse
|
142
|
Xue Z, Zeng S, Hao J. Non-invasive through-skull brain vascular imaging and small tumor diagnosis based on NIR-II emissive lanthanide nanoprobes beyond 1500 nm. Biomaterials 2018; 171:153-163. [DOI: 10.1016/j.biomaterials.2018.04.037] [Citation(s) in RCA: 88] [Impact Index Per Article: 14.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/15/2017] [Revised: 04/09/2018] [Accepted: 04/14/2018] [Indexed: 01/08/2023]
|
143
|
Tang X, Cai F, Ding DX, Zhang LL, Cai XY, Fang Q. Magnetic resonance imaging relaxation time in Alzheimer's disease. Brain Res Bull 2018; 140:176-189. [PMID: 29738781 DOI: 10.1016/j.brainresbull.2018.05.004] [Citation(s) in RCA: 26] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/18/2018] [Revised: 04/18/2018] [Accepted: 05/04/2018] [Indexed: 12/26/2022]
Abstract
The magnetic resonance imaging (MRI) relaxation time constants, T1 and T2, are sensitive to changes in brain tissue microstructure integrity. Quantitative T1 and T2 relaxation times have been proposed to serve as non-invasive biomarkers of Alzheimer's disease (AD), in which alterations are believed to not only reflect AD-related neuropathology but also cognitive impairment. In this review, we summarize the applications and key findings of MRI techniques in the context of both AD subjects and AD transgenic mouse models. Furthermore, the possible mechanisms of relaxation time alterations in AD will be discussed. Future studies could focus on relaxation time alterations in the early stage of AD, and longitudinal studies are needed to further explore relaxation time alterations during disease progression.
Collapse
Affiliation(s)
- Xiang Tang
- Department of Neurology, The First Affiliated Hospital of Soochow University, No. 899, Pinghai Road, Suzhou, Jiangsu 215006, China
| | - Feng Cai
- Department of Orthopedics, The First Affiliated Hospital of Soochow University, No. 899, Pinghai Road, Suzhou, Jiangsu 215006, China
| | - Dong-Xue Ding
- Department of Neurology, The First Affiliated Hospital of Soochow University, No. 899, Pinghai Road, Suzhou, Jiangsu 215006, China
| | - Lu-Lu Zhang
- Department of Neurology, The First Affiliated Hospital of Soochow University, No. 899, Pinghai Road, Suzhou, Jiangsu 215006, China
| | - Xiu-Ying Cai
- Department of Neurology, The First Affiliated Hospital of Soochow University, No. 899, Pinghai Road, Suzhou, Jiangsu 215006, China.
| | - Qi Fang
- Department of Neurology, The First Affiliated Hospital of Soochow University, No. 899, Pinghai Road, Suzhou, Jiangsu 215006, China.
| |
Collapse
|
144
|
Castella R, Arn L, Dupuis E, Callaghan MF, Draganski B, Lutti A. Controlling motion artefact levels in MR images by suspending data acquisition during periods of head motion. Magn Reson Med 2018; 80:2415-2426. [DOI: 10.1002/mrm.27214] [Citation(s) in RCA: 23] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/01/2017] [Revised: 02/20/2018] [Accepted: 03/18/2018] [Indexed: 01/28/2023]
Affiliation(s)
- Rémi Castella
- LREN, Department for Clinical Neurosciences; CHUV; Lausanne Switzerland
| | - Lionel Arn
- LREN, Department for Clinical Neurosciences; CHUV; Lausanne Switzerland
- Ecole Polytechnique Fédérale de Lausanne; Lausanne Switzerland
| | - Estelle Dupuis
- LREN, Department for Clinical Neurosciences; CHUV; Lausanne Switzerland
| | - Martina F. Callaghan
- Wellcome Trust Centre for Neuroimaging, UCL Institute of Neurology; University College London; London United Kingdom
| | - Bogdan Draganski
- LREN, Department for Clinical Neurosciences; CHUV; Lausanne Switzerland
- Max Planck Institute for Human Cognitive and Brain Sciences; Leipzig Germany
| | - Antoine Lutti
- LREN, Department for Clinical Neurosciences; CHUV; Lausanne Switzerland
| |
Collapse
|
145
|
Ziegler G, Grabher P, Thompson A, Altmann D, Hupp M, Ashburner J, Friston K, Weiskopf N, Curt A, Freund P. Progressive neurodegeneration following spinal cord injury: Implications for clinical trials. Neurology 2018. [PMID: 29514946 PMCID: PMC5890610 DOI: 10.1212/wnl.0000000000005258] [Citation(s) in RCA: 88] [Impact Index Per Article: 14.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/03/2023] Open
Abstract
Objective To quantify atrophy, demyelination, and iron accumulation over 2 years following acute spinal cord injury and to identify MRI predictors of clinical outcomes and determine their suitability as surrogate markers of therapeutic intervention. Methods We assessed 156 quantitative MRI datasets from 15 patients with spinal cord injury and 18 controls at baseline and 2, 6, 12, and 24 months after injury. Clinical recovery (including neuropathic pain) was assessed at each time point. Between-group differences in linear and nonlinear trajectories of volume, myelin, and iron change were estimated. Structural changes by 6 months were used to predict clinical outcomes at 2 years. Results The majority of patients showed clinical improvement with recovery stabilizing at 2 years. Cord atrophy decelerated, while cortical white and gray matter atrophy progressed over 2 years. Myelin content in the spinal cord and cortex decreased progressively over time, while cerebellar loss decreases decelerated. As atrophy progressed in the thalamus, sustained iron accumulation was evident. Smaller cord and cranial corticospinal tract atrophy, and myelin changes within the sensorimotor cortices, by 6 months predicted recovery in lower extremity motor score at 2 years. Whereas greater cord atrophy and microstructural changes in the cerebellum, anterior cingulate cortex, and secondary sensory cortex by 6 months predicted worse sensory impairment and greater neuropathic pain intensity at 2 years. Conclusion These results draw attention to trauma-induced neuroplastic processes and highlight the intimate relationships among neurodegenerative processes in the cord and brain. These measurable changes are sufficiently large, systematic, and predictive to render them viable outcome measures for clinical trials.
Collapse
Affiliation(s)
- Gabriel Ziegler
- From the Institute of Cognitive Neurology and Dementia Research (G.Z.), Otto-von-Guericke-University Magdeburg; German Center for Neurodegenerative Diseases (G.Z.), Magdeburg, Germany; Spinal Cord Injury Center Balgrist (P.G., M.H., A.C., P.F.), University Hospital Zurich, University of Zurich, Switzerland; Department of Brain Repair & Rehabilitation (A.T., P.F.) and Wellcome Trust Centre for Neuroimaging (J.A., K.F., N.W., P.F.), UCL Institute of Neurology, UCL, London; Queen Square Multiple Sclerosis Centre (D.A.), Institute of Neurology, University College London; Medical Statistics Department (D.A.), London School of Hygiene & Tropical Medicine, London, UK; and Department of Neurophysics (N.W., P.F.), Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
| | - Patrick Grabher
- From the Institute of Cognitive Neurology and Dementia Research (G.Z.), Otto-von-Guericke-University Magdeburg; German Center for Neurodegenerative Diseases (G.Z.), Magdeburg, Germany; Spinal Cord Injury Center Balgrist (P.G., M.H., A.C., P.F.), University Hospital Zurich, University of Zurich, Switzerland; Department of Brain Repair & Rehabilitation (A.T., P.F.) and Wellcome Trust Centre for Neuroimaging (J.A., K.F., N.W., P.F.), UCL Institute of Neurology, UCL, London; Queen Square Multiple Sclerosis Centre (D.A.), Institute of Neurology, University College London; Medical Statistics Department (D.A.), London School of Hygiene & Tropical Medicine, London, UK; and Department of Neurophysics (N.W., P.F.), Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
| | - Alan Thompson
- From the Institute of Cognitive Neurology and Dementia Research (G.Z.), Otto-von-Guericke-University Magdeburg; German Center for Neurodegenerative Diseases (G.Z.), Magdeburg, Germany; Spinal Cord Injury Center Balgrist (P.G., M.H., A.C., P.F.), University Hospital Zurich, University of Zurich, Switzerland; Department of Brain Repair & Rehabilitation (A.T., P.F.) and Wellcome Trust Centre for Neuroimaging (J.A., K.F., N.W., P.F.), UCL Institute of Neurology, UCL, London; Queen Square Multiple Sclerosis Centre (D.A.), Institute of Neurology, University College London; Medical Statistics Department (D.A.), London School of Hygiene & Tropical Medicine, London, UK; and Department of Neurophysics (N.W., P.F.), Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
| | - Daniel Altmann
- From the Institute of Cognitive Neurology and Dementia Research (G.Z.), Otto-von-Guericke-University Magdeburg; German Center for Neurodegenerative Diseases (G.Z.), Magdeburg, Germany; Spinal Cord Injury Center Balgrist (P.G., M.H., A.C., P.F.), University Hospital Zurich, University of Zurich, Switzerland; Department of Brain Repair & Rehabilitation (A.T., P.F.) and Wellcome Trust Centre for Neuroimaging (J.A., K.F., N.W., P.F.), UCL Institute of Neurology, UCL, London; Queen Square Multiple Sclerosis Centre (D.A.), Institute of Neurology, University College London; Medical Statistics Department (D.A.), London School of Hygiene & Tropical Medicine, London, UK; and Department of Neurophysics (N.W., P.F.), Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
| | - Markus Hupp
- From the Institute of Cognitive Neurology and Dementia Research (G.Z.), Otto-von-Guericke-University Magdeburg; German Center for Neurodegenerative Diseases (G.Z.), Magdeburg, Germany; Spinal Cord Injury Center Balgrist (P.G., M.H., A.C., P.F.), University Hospital Zurich, University of Zurich, Switzerland; Department of Brain Repair & Rehabilitation (A.T., P.F.) and Wellcome Trust Centre for Neuroimaging (J.A., K.F., N.W., P.F.), UCL Institute of Neurology, UCL, London; Queen Square Multiple Sclerosis Centre (D.A.), Institute of Neurology, University College London; Medical Statistics Department (D.A.), London School of Hygiene & Tropical Medicine, London, UK; and Department of Neurophysics (N.W., P.F.), Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
| | - John Ashburner
- From the Institute of Cognitive Neurology and Dementia Research (G.Z.), Otto-von-Guericke-University Magdeburg; German Center for Neurodegenerative Diseases (G.Z.), Magdeburg, Germany; Spinal Cord Injury Center Balgrist (P.G., M.H., A.C., P.F.), University Hospital Zurich, University of Zurich, Switzerland; Department of Brain Repair & Rehabilitation (A.T., P.F.) and Wellcome Trust Centre for Neuroimaging (J.A., K.F., N.W., P.F.), UCL Institute of Neurology, UCL, London; Queen Square Multiple Sclerosis Centre (D.A.), Institute of Neurology, University College London; Medical Statistics Department (D.A.), London School of Hygiene & Tropical Medicine, London, UK; and Department of Neurophysics (N.W., P.F.), Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
| | - Karl Friston
- From the Institute of Cognitive Neurology and Dementia Research (G.Z.), Otto-von-Guericke-University Magdeburg; German Center for Neurodegenerative Diseases (G.Z.), Magdeburg, Germany; Spinal Cord Injury Center Balgrist (P.G., M.H., A.C., P.F.), University Hospital Zurich, University of Zurich, Switzerland; Department of Brain Repair & Rehabilitation (A.T., P.F.) and Wellcome Trust Centre for Neuroimaging (J.A., K.F., N.W., P.F.), UCL Institute of Neurology, UCL, London; Queen Square Multiple Sclerosis Centre (D.A.), Institute of Neurology, University College London; Medical Statistics Department (D.A.), London School of Hygiene & Tropical Medicine, London, UK; and Department of Neurophysics (N.W., P.F.), Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
| | - Nikolaus Weiskopf
- From the Institute of Cognitive Neurology and Dementia Research (G.Z.), Otto-von-Guericke-University Magdeburg; German Center for Neurodegenerative Diseases (G.Z.), Magdeburg, Germany; Spinal Cord Injury Center Balgrist (P.G., M.H., A.C., P.F.), University Hospital Zurich, University of Zurich, Switzerland; Department of Brain Repair & Rehabilitation (A.T., P.F.) and Wellcome Trust Centre for Neuroimaging (J.A., K.F., N.W., P.F.), UCL Institute of Neurology, UCL, London; Queen Square Multiple Sclerosis Centre (D.A.), Institute of Neurology, University College London; Medical Statistics Department (D.A.), London School of Hygiene & Tropical Medicine, London, UK; and Department of Neurophysics (N.W., P.F.), Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
| | - Armin Curt
- From the Institute of Cognitive Neurology and Dementia Research (G.Z.), Otto-von-Guericke-University Magdeburg; German Center for Neurodegenerative Diseases (G.Z.), Magdeburg, Germany; Spinal Cord Injury Center Balgrist (P.G., M.H., A.C., P.F.), University Hospital Zurich, University of Zurich, Switzerland; Department of Brain Repair & Rehabilitation (A.T., P.F.) and Wellcome Trust Centre for Neuroimaging (J.A., K.F., N.W., P.F.), UCL Institute of Neurology, UCL, London; Queen Square Multiple Sclerosis Centre (D.A.), Institute of Neurology, University College London; Medical Statistics Department (D.A.), London School of Hygiene & Tropical Medicine, London, UK; and Department of Neurophysics (N.W., P.F.), Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
| | - Patrick Freund
- From the Institute of Cognitive Neurology and Dementia Research (G.Z.), Otto-von-Guericke-University Magdeburg; German Center for Neurodegenerative Diseases (G.Z.), Magdeburg, Germany; Spinal Cord Injury Center Balgrist (P.G., M.H., A.C., P.F.), University Hospital Zurich, University of Zurich, Switzerland; Department of Brain Repair & Rehabilitation (A.T., P.F.) and Wellcome Trust Centre for Neuroimaging (J.A., K.F., N.W., P.F.), UCL Institute of Neurology, UCL, London; Queen Square Multiple Sclerosis Centre (D.A.), Institute of Neurology, University College London; Medical Statistics Department (D.A.), London School of Hygiene & Tropical Medicine, London, UK; and Department of Neurophysics (N.W., P.F.), Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany.
| |
Collapse
|
146
|
Papoutsi M, Weiskopf N, Langbehn D, Reilmann R, Rees G, Tabrizi SJ. Stimulating neural plasticity with real-time fMRI neurofeedback in Huntington's disease: A proof of concept study. Hum Brain Mapp 2018; 39:1339-1353. [PMID: 29239063 PMCID: PMC5838530 DOI: 10.1002/hbm.23921] [Citation(s) in RCA: 29] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/05/2017] [Revised: 11/14/2017] [Accepted: 12/07/2017] [Indexed: 01/28/2023] Open
Abstract
Novel methods that stimulate neuroplasticity are increasingly being studied to treat neurological and psychiatric conditions. We sought to determine whether real-time fMRI neurofeedback training is feasible in Huntington's disease (HD), and assess any factors that contribute to its effectiveness. In this proof-of-concept study, we used this technique to train 10 patients with HD to volitionally regulate the activity of their supplementary motor area (SMA). We collected detailed behavioral and neuroimaging data before and after training to examine changes of brain function and structure, and cognitive and motor performance. We found that patients overall learned to increase activity of the target region during training with variable effects on cognitive and motor behavior. Improved cognitive and motor performance after training predicted increases in pre-SMA grey matter volume, fMRI activity in the left putamen, and increased SMA-left putamen functional connectivity. Although we did not directly target the putamen and corticostriatal connectivity during neurofeedback training, our results suggest that training the SMA can lead to regulation of associated networks with beneficial effects in behavior. We conclude that neurofeedback training can induce plasticity in patients with Huntington's disease despite the presence of neurodegeneration, and the effects of training a single region may engage other regions and circuits implicated in disease pathology.
Collapse
Affiliation(s)
- Marina Papoutsi
- UCL Huntington's Disease Centre, Institute of Neurology, University College LondonLondonUnited Kingdom
| | - Nikolaus Weiskopf
- Max Planck Institute for Human Cognitive and Brain SciencesLeipzigGermany
- Wellcome Trust Centre for NeuroimagingInstitute of Neurology, University College LondonLondonUnited Kingdom
| | | | - Ralf Reilmann
- George Huntington Institute and Department of RadiologyUniversity of MuensterMünsterGermany
- Section for Neurodegeneration and Hertie Institute for Clinical Brain Research, University of TuebingenTübingenGermany
| | - Geraint Rees
- Wellcome Trust Centre for NeuroimagingInstitute of Neurology, University College LondonLondonUnited Kingdom
- Institute of Cognitive Neuroscience, University College LondonLondonUnited Kingdom
| | - Sarah J Tabrizi
- UCL Huntington's Disease Centre, Institute of Neurology, University College LondonLondonUnited Kingdom
| |
Collapse
|
147
|
How to choose the right MR sequence for your research question at 7 T and above? Neuroimage 2018; 168:119-140. [DOI: 10.1016/j.neuroimage.2017.04.044] [Citation(s) in RCA: 40] [Impact Index Per Article: 6.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/12/2016] [Revised: 04/18/2017] [Accepted: 04/19/2017] [Indexed: 12/29/2022] Open
|
148
|
Schyboll F, Jaekel U, Weber B, Neeb H. The impact of fibre orientation on T1-relaxation and apparent tissue water content in white matter. MAGNETIC RESONANCE MATERIALS IN PHYSICS BIOLOGY AND MEDICINE 2018; 31:501-510. [DOI: 10.1007/s10334-018-0678-8] [Citation(s) in RCA: 18] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/26/2017] [Revised: 02/07/2018] [Accepted: 02/07/2018] [Indexed: 11/29/2022]
|
149
|
High-resolution magnetic resonance elastography reveals differences in subcortical gray matter viscoelasticity between young and healthy older adults. Neurobiol Aging 2018; 65:158-167. [PMID: 29494862 PMCID: PMC5883326 DOI: 10.1016/j.neurobiolaging.2018.01.010] [Citation(s) in RCA: 66] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/27/2017] [Revised: 01/10/2018] [Accepted: 01/16/2018] [Indexed: 12/13/2022]
Abstract
Volumetric structural magnetic resonance imaging (MRI) is commonly used to determine the extent of neuronal loss in aging, indicated by cerebral atrophy. The brain, however, exhibits other biophysical characteristics such as mechanical properties, which can be quantified with magnetic resonance elastography (MRE). MRE is an emerging noninvasive imaging technique for measuring viscoelastic tissue properties, proven to be sensitive metrics of neural tissue integrity, as described by shear stiffness, μ and damping ratio, ξ parameters. The study objective was to evaluate global and regional MRE parameter differences between young (19–30 years, n = 12) and healthy older adults (66–73 years, n = 12) and to assess whether MRE measures provide additive value over volumetric magnetic resonance imaging measurements. We investigated the viscoelasticity of the global cerebrum and 6 regions of interest (ROIs) including the amygdala, hippocampus, caudate, pallidum, putamen, and thalamus. In older adults, we found a decrease in μ in all ROIs, except for the hippocampus, indicating widespread brain softening; an effect that remained significant after controlling for ROI volume. In contrast, the relative viscous-to-elastic behavior of the brain ξ did not differ between age groups, suggesting a preservation of the organization of the tissue microstructure. These data support the use of MRE as a novel imaging biomarker for characterizing age-related differences to neural tissue not captured by volumetric imaging alone.
Collapse
|
150
|
Vázquez‐Costa JF, Mazón M, Carreres‐Polo J, Hervás D, Pérez‐Tur J, Martí‐Bonmatí L, Sevilla T. Brain signal intensity changes as biomarkers in amyotrophic lateral sclerosis. Acta Neurol Scand 2018; 137:262-271. [PMID: 29082510 DOI: 10.1111/ane.12863] [Citation(s) in RCA: 23] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 10/11/2017] [Indexed: 01/31/2023]
Abstract
OBJECTIVES To evaluate the contribution of the demographical, clinical, analytical and genetic factors to brain signal intensity changes in T2-weighted MR images in amyotrophic lateral sclerosis (ALS) patients and controls. METHODS Susceptibility-weighted and FLAIR sequences were obtained in a 3T MR scanner. Iron-related hypointensities in the motor cortex (IRhMC) and hyperintensities of the corticospinal tract (HCT) were qualitatively scored. Age, gender, family history and clinical variables were recorded. Baseline levels of ferritin were measured. C9orf72 was tested in all patients and SOD1 only in familial ALS patients not carrying a C9orf72 expansion. Patients who carried a mutation were categorized as genetic. Associations of these variables with visual scores were assessed with multivariable analysis. RESULTS A total of 102 ALS patients (92 non-genetic and 10 genetic) and 48 controls (28 ALS mimics and 20 healthy controls) were recruited. In controls, IRhMC associated with age, but HCT did not. In ALS patients, both HTC and IRhMC strongly associated with clinical UMN impairment and bulbar onset. The intensity/extent of IRhMC in the different motor homunculus regions (lower limbs, upper limbs and bulbar) were linked to the symptoms onset site. Between genetic and sporadic patients, no difference in IRhMC and HCT was found. CONCLUSIONS IRhMC and HCT are reliable markers of UMN degeneration in ALS patients and are more frequent in bulbar onset patients, independently of the mutation status. Age should be considered when evaluating IRhMC. The regional measurement of IRhMC following the motor homunculus could be used as a measure of disease progression.
Collapse
Affiliation(s)
- Juan F. Vázquez‐Costa
- Neuromuscular Research Unit Instituto de Investigación Sanitaria la Fe Valencia Spain
- ALS Unit Department of Neurology Hospital Universitario y Politécnico La Fe Valencia Spain
- Centro de Investigación Biomédica en Red de Enfermedades Raras (CIBERER) Valencia Spain
| | - Miguel Mazón
- Department of Radiology and Biomedical Imaging Research Group GIBI2 Hospital Universitario y Politécnico La Fe and Instituto de Investigación Sanitaria la Fe Valencia Spain
| | - Joan Carreres‐Polo
- Department of Radiology and Biomedical Imaging Research Group GIBI2 Hospital Universitario y Politécnico La Fe and Instituto de Investigación Sanitaria la Fe Valencia Spain
| | - David Hervás
- Biostatistics Unit Instituto de Investigación Sanitaria la Fe Valencia Spain
| | - Jordi Pérez‐Tur
- Laboratory of Molecular Genetics Institut de Biomedicina de València‐CSIC Valencia Spain
- Centro de Investigación Biomédica en Red de Enfermedades Neurodegenerativas (CIBERNED) Valencia Spain
- Unidad mixta de Neurología y Genética Instituto de Investigación Sanitaria la Fe (IIS La Fe) Valencia Spain
| | - Luis Martí‐Bonmatí
- Department of Radiology and Biomedical Imaging Research Group GIBI2 Hospital Universitario y Politécnico La Fe and Instituto de Investigación Sanitaria la Fe Valencia Spain
| | - Teresa Sevilla
- Neuromuscular Research Unit Instituto de Investigación Sanitaria la Fe Valencia Spain
- ALS Unit Department of Neurology Hospital Universitario y Politécnico La Fe Valencia Spain
- Centro de Investigación Biomédica en Red de Enfermedades Raras (CIBERER) Valencia Spain
- Department of Medicine University of Valencia Valencia Spain
| |
Collapse
|