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Kelly CE, Shaul M, Thompson DK, Mainzer RM, Yang JY, Dhollander T, Cheong JL, Inder TE, Doyle LW, Anderson PJ. Long-lasting effects of very preterm birth on brain structure in adulthood: A systematic review and meta-analysis. Neurosci Biobehav Rev 2023; 147:105082. [PMID: 36775083 DOI: 10.1016/j.neubiorev.2023.105082] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/24/2022] [Revised: 01/01/2023] [Accepted: 02/05/2023] [Indexed: 02/12/2023]
Abstract
Early life experiences, such as very preterm (VP) birth, can affect brain and cognitive development. Several prior studies investigated brain structure in adults born VP; synthesising these studies may help to provide a clearer understanding of long-term effects of VP birth on the brain. We systematically searched Medline and Embase for articles that investigated brain structure using MRI in adulthood in individuals born VP (<32 weeks' gestation) or with very low birth weight (VLBW; <1500 g), and controls born at term or with normal birth weight. In total, 77 studies met the review inclusion criteria, of which 28 studies were eligible for meta-analyses, including data from up to 797 VP/VLBW participants and 518 controls, aged 18-33 years. VP/VLBW adults exhibited volumetric, morphologic and microstructural alterations in subcortical and temporal cortical regions compared with controls, with pooled standardised mean differences up to - 1.0 (95% confidence interval: -1.2, -0.8). This study suggests there is a persisting neurological impact of VP birth, which may provide developmental neurobiological insights for adult cognition in high-risk populations.
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Affiliation(s)
- Claire E Kelly
- Turner Institute for Brain and Mental Health, School of Psychological Sciences, Monash University, Melbourne, Australia; Victorian Infant Brain Studies (VIBeS), Murdoch Children's Research Institute, Melbourne, Australia; Developmental Imaging, Murdoch Children's Research Institute, Melbourne, Australia.
| | - Michelle Shaul
- Victorian Infant Brain Studies (VIBeS), Murdoch Children's Research Institute, Melbourne, Australia; Deakin University, Melbourne, Australia
| | - Deanne K Thompson
- Victorian Infant Brain Studies (VIBeS), Murdoch Children's Research Institute, Melbourne, Australia; Developmental Imaging, Murdoch Children's Research Institute, Melbourne, Australia; Department of Paediatrics, The University of Melbourne, Melbourne, Australia
| | - Rheanna M Mainzer
- Department of Paediatrics, The University of Melbourne, Melbourne, Australia; Clinical Epidemiology and Biostatistics Unit, Population Health, Murdoch Children's Research Institute, Melbourne, Australia
| | - Joseph Ym Yang
- Developmental Imaging, Murdoch Children's Research Institute, Melbourne, Australia; Department of Paediatrics, The University of Melbourne, Melbourne, Australia; Neuroscience Advanced Clinical Imaging Service (NACIS), Department of Neurosurgery, The Royal Children's Hospital, Melbourne, Australia; Neuroscience Research, Murdoch Children's Research Institute, Melbourne, Australia
| | - Thijs Dhollander
- Developmental Imaging, Murdoch Children's Research Institute, Melbourne, Australia
| | - Jeanie Ly Cheong
- Victorian Infant Brain Studies (VIBeS), Murdoch Children's Research Institute, Melbourne, Australia; The Royal Women's Hospital, Melbourne, Australia; Department of Obstetrics and Gynaecology, The University of Melbourne, Melbourne, Australia
| | - Terrie E Inder
- Department of Pediatrics, Children's Hospital of Orange County, University of California Irvine, CA, USA
| | - Lex W Doyle
- Victorian Infant Brain Studies (VIBeS), Murdoch Children's Research Institute, Melbourne, Australia; Department of Paediatrics, The University of Melbourne, Melbourne, Australia; The Royal Women's Hospital, Melbourne, Australia; Department of Obstetrics and Gynaecology, The University of Melbourne, Melbourne, Australia
| | - Peter J Anderson
- Turner Institute for Brain and Mental Health, School of Psychological Sciences, Monash University, Melbourne, Australia; Victorian Infant Brain Studies (VIBeS), Murdoch Children's Research Institute, Melbourne, Australia
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2
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Chandler HL, Stickland RC, Patitucci E, Germuska M, Chiarelli AM, Foster C, Bhome-Dhaliwal S, Lancaster TM, Saxena N, Khot S, Tomassini V, Wise RG. Reduced brain oxygen metabolism in patients with multiple sclerosis: Evidence from dual-calibrated functional MRI. J Cereb Blood Flow Metab 2023; 43:115-128. [PMID: 36071645 PMCID: PMC9875355 DOI: 10.1177/0271678x221121849] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/20/2022] [Revised: 06/01/2022] [Accepted: 07/21/2022] [Indexed: 01/28/2023]
Abstract
Cerebral energy deficiency is increasingly recognised as an important feature of multiple sclerosis (MS). Until now, we have lacked non-invasive imaging methods to quantify energy utilisation and mitochondrial function in the human brain. Here, we used novel dual-calibrated functional magnetic resonance imaging (dc-fMRI) to map grey-matter (GM) deoxy-haemoglobin sensitive cerebral blood volume (CBVdHb), cerebral blood flow (CBF), oxygen extraction fraction (OEF), and cerebral metabolic rate of oxygen consumption (CMRO2) in patients with MS (PwMS) and age/sex matched controls. By integrating a flow-diffusion model of oxygen transport, we evaluated the effective oxygen diffusivity of the capillary network (DC) and the partial pressure of oxygen at the mitochondria (PmO2). Significant between-group differences were observed as decreased CBF (p = 0.010), CMRO2 (p < 0.001) and DC (p = 0.002), and increased PmO2 (p = 0.043) in patients compared to controls. No significant differences were observed for CBVdHb (p = 0.389), OEF (p = 0.358), or GM volume (p = 0.302). Regional analysis showed widespread reductions in CMRO2 and DC for PwMS. Our findings may be indicative of reduced oxygen demand or utilisation in the MS brain and mitochondrial dysfunction. Our results suggest changes in brain physiology may precede MRI-detectable GM loss and may contribute to disease progression and neurodegeneration.
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Affiliation(s)
| | - Rachael C Stickland
- CUBRIC, School of Psychology, Cardiff University, Cardiff,
UK
- Department of Physical Therapy and Human Movement Sciences,
Northwestern University, Chicago, IL, USA
| | | | | | - Antonio M Chiarelli
- Institute for Advanced Biomedical Technologies, University “G.
d'Annunzio” of Chieti-Pescara, Chieti, Italy
- Department of Neurosciences, Imaging and Clinical Sciences,
University “G. d'Annunzio” of Chieti-Pescara, Chieti, Italy
| | - Catherine Foster
- CUBRIC, School of Psychology, Cardiff University, Cardiff,
UK
- Wales Institute of Social and Economic Research and Data,
Cardiff University, Cardiff, UK
| | | | - Thomas M Lancaster
- CUBRIC, School of Psychology, Cardiff University, Cardiff,
UK
- Department of Psychology, University of Bath, Bath, UK
| | - Neeraj Saxena
- CUBRIC, School of Psychology, Cardiff University, Cardiff,
UK
- Department of Anaesthetics, Intensive Care and Pain Medicine,
Cwm Taf Morgannwg University Health Board, Abercynon, UK
| | - Sharmila Khot
- CUBRIC, School of Psychology, Cardiff University, Cardiff,
UK
- Cardiff University School of Medicine, Cardiff, UK
| | - Valentina Tomassini
- CUBRIC, School of Psychology, Cardiff University, Cardiff,
UK
- Institute for Advanced Biomedical Technologies, University “G.
d'Annunzio” of Chieti-Pescara, Chieti, Italy
- Department of Neurosciences, Imaging and Clinical Sciences,
University “G. d'Annunzio” of Chieti-Pescara, Chieti, Italy
- MS Centre, Neurology Unit, “SS. Annunziata” University Hospital,
Chieti, Italy
- Division of Psychological Medicine and Clinical Neurosciences,
School of Medicine, Cardiff University, Cardiff, UK
- Helen Durham Centre for Neuroinflammation, University Hospital
of Wales, Cardiff, UK
| | - Richard G Wise
- CUBRIC, School of Psychology, Cardiff University, Cardiff,
UK
- Institute for Advanced Biomedical Technologies, University “G.
d'Annunzio” of Chieti-Pescara, Chieti, Italy
- Department of Neurosciences, Imaging and Clinical Sciences,
University “G. d'Annunzio” of Chieti-Pescara, Chieti, Italy
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3
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Yu D, Wang L, Kong D, Zhu H. Mapping the Genetic-Imaging-Clinical Pathway with Applications to Alzheimer’s Disease. J Am Stat Assoc 2022; 117:1656-1668. [PMID: 37009529 PMCID: PMC10062702 DOI: 10.1080/01621459.2022.2087658] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/06/2023]
Abstract
Alzheimer's disease is a progressive form of dementia that results in problems with memory, thinking, and behavior. It often starts with abnormal aggregation and deposition of β amyloid and tau, followed by neuronal damage such as atrophy of the hippocampi, leading to Alzheimers Disease (AD). The aim of this paper is to map the genetic-imaging-clinical pathway for AD in order to delineate the genetically-regulated brain changes that drive disease progression based on the Alzheimers Disease Neuroimaging Initiative (ADNI) dataset. We develop a novel two-step approach to delineate the association between high-dimensional 2D hippocampal surface exposures and the Alzheimers Disease Assessment Scale (ADAS) cognitive score, while taking into account the ultra-high dimensional clinical and genetic covariates at baseline. Analysis results suggest that the radial distance of each pixel of both hippocampi is negatively associated with the severity of behavioral deficits conditional on observed clinical and genetic covariates. These associations are stronger in Cornu Ammonis region 1 (CA1) and subiculum subregions compared to Cornu Ammonis region 2 (CA2) and Cornu Ammonis region 3 (CA3) subregions. Supplementary materials for this article, including a standardized description of the materials available for reproducing the work, are available as an online supplement.
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Affiliation(s)
- Dengdeng Yu
- Department of Mathematics, University of Texas at Arlington
| | - Linbo Wang
- Department of Statistical Sciences, University of Toronto
| | - Dehan Kong
- Department of Statistical Sciences, University of Toronto
| | - Hongtu Zhu
- Department of Biostatistics, University of North Carolina, Chapel Hill for the Alzheimer’s Disease Neuroimaging Initiative*
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4
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Mangesius S, Haider L, Lenhart L, Steiger R, Prados Carrasco F, Scherfler C, Gizewski ER. Qualitative and Quantitative Comparison of Hippocampal Volumetric Software Applications: Do All Roads Lead to Rome? Biomedicines 2022; 10:biomedicines10020432. [PMID: 35203641 PMCID: PMC8962257 DOI: 10.3390/biomedicines10020432] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/21/2021] [Revised: 01/30/2022] [Accepted: 02/10/2022] [Indexed: 02/06/2023] Open
Abstract
Brain volumetric software is increasingly suggested for clinical routine. The present study quantifies the agreement across different software applications. Ten cases with and ten gender- and age-adjusted healthy controls without hippocampal atrophy (median age: 70; 25–75% range: 64–77 years and 74; 66–78 years) were retrospectively selected from a previously published cohort of Alzheimer’s dementia patients and normal ageing controls. Hippocampal volumes were computed based on 3 Tesla T1-MPRAGE-sequences with FreeSurfer (FS), Statistical-Parametric-Mapping (SPM; Neuromorphometrics and Hammers atlases), Geodesic-Information-Flows (GIF), Similarity-and-Truth-Estimation-for-Propagated-Segmentations (STEPS), and Quantib™. MTA (medial temporal lobe atrophy) scores were manually rated. Volumetric measures of each individual were compared against the mean of all applications with intraclass correlation coefficients (ICC) and Bland–Altman plots. Comparing against the mean of all methods, moderate to low agreement was present considering categorization of hippocampal volumes into quartiles. ICCs ranged noticeably between applications (left hippocampus (LH): from 0.42 (STEPS) to 0.88 (FS); right hippocampus (RH): from 0.36 (Quantib™) to 0.86 (FS). Mean differences between individual methods and the mean of all methods [mm3] were considerable (LH: FS −209, SPM-Neuromorphometrics −820; SPM-Hammers −1474; Quantib™ −680; GIF 891; STEPS 2218; RH: FS −232, SPM-Neuromorphometrics −745; SPM-Hammers −1547; Quantib™ −723; GIF 982; STEPS 2188). In this clinically relevant sample size with large spread in data ranging from normal aging to severe atrophy, hippocampal volumes derived by well-accepted applications were quantitatively different. Thus, interchangeable use is not recommended.
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Affiliation(s)
- Stephanie Mangesius
- Department of Neuroradiology, Medical University of Innsbruck, Anichstrasse 35, 6020 Innsbruck, Austria; (S.M.); (L.L.); (R.S.); (E.R.G.)
- Neuroimaging Core Facility, Medical University of Innsbruck, Anichstrasse 35, 6020 Innsbruck, Austria
| | - Lukas Haider
- NMR Research Unit, Queen Square Multiple Sclerosis Centre, University College London Institute of Neurology, Russell Square House, Russell Square 10-12, London WC1B 5EH, UK;
- Department of Biomedical Imaging and Image Guided Therapy, Medical University of Vienna, Währinger Gürtel 18-20, 1090 Vienna, Austria
- Correspondence:
| | - Lukas Lenhart
- Department of Neuroradiology, Medical University of Innsbruck, Anichstrasse 35, 6020 Innsbruck, Austria; (S.M.); (L.L.); (R.S.); (E.R.G.)
- Neuroimaging Core Facility, Medical University of Innsbruck, Anichstrasse 35, 6020 Innsbruck, Austria
| | - Ruth Steiger
- Department of Neuroradiology, Medical University of Innsbruck, Anichstrasse 35, 6020 Innsbruck, Austria; (S.M.); (L.L.); (R.S.); (E.R.G.)
- Neuroimaging Core Facility, Medical University of Innsbruck, Anichstrasse 35, 6020 Innsbruck, Austria
| | - Ferran Prados Carrasco
- NMR Research Unit, Queen Square Multiple Sclerosis Centre, University College London Institute of Neurology, Russell Square House, Russell Square 10-12, London WC1B 5EH, UK;
- Centre for Medical Image Computing (CMIC), Department of Medical Physics and Biomedical Engineering, University College London, Malet Place Engineering Building, Gower Street, London WC1E 6BT, UK
- e-Health Centre, Universitat Oberta de Catalunya, Rambla del Poblenou 156, 08018 Barcelona, Spain
| | - Christoph Scherfler
- Department of Neurology, Medical University of Innsbruck, Anichstrasse 35, 6020 Innsbruck, Austria;
| | - Elke R. Gizewski
- Department of Neuroradiology, Medical University of Innsbruck, Anichstrasse 35, 6020 Innsbruck, Austria; (S.M.); (L.L.); (R.S.); (E.R.G.)
- Neuroimaging Core Facility, Medical University of Innsbruck, Anichstrasse 35, 6020 Innsbruck, Austria
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5
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Filip P, Bednarik P, Eberly LE, Moheet A, Svatkova A, Grohn H, Kumar AF, Seaquist ER, Mangia S. Different FreeSurfer versions might generate different statistical outcomes in case-control comparison studies. Neuroradiology 2022; 64:765-773. [PMID: 34988592 DOI: 10.1007/s00234-021-02862-0] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/25/2021] [Accepted: 11/12/2021] [Indexed: 10/19/2022]
Abstract
PURPOSE Neuroimaging pipelines have long been known to generate mildly differing results depending on various factors, including software version. While considered generally acceptable and within the margin of reasonable error, little is known about their effect in common research scenarios such as inter-group comparisons between healthy controls and various pathological conditions. The aim of the presented study was to explore the differences in the inferences and statistical significances in a model situation comparing volumetric parameters between healthy controls and type 1 diabetes patients using various FreeSurfer versions. METHODS T1- and T2-weighted structural scans of healthy controls and type 1 diabetes patients were processed with FreeSurfer 5.3, FreeSurfer 5.3 HCP, FreeSurfer 6.0 and FreeSurfer 7.1, followed by inter-group statistical comparison using outputs of individual FreeSurfer versions. RESULTS Worryingly, FreeSurfer 5.3 detected both cortical and subcortical volume differences out of the preselected regions of interest, but newer versions such as FreeSurfer 5.3 HCP and FreeSurfer 6.0 reported only subcortical differences of lower magnitude and FreeSurfer 7.1 failed to find any statistically significant inter-group differences. CONCLUSION Since group averages of individual FreeSurfer versions closely matched, in keeping with previous literature, the main origin of this disparity seemed to lie in substantially higher within-group variability in the model pathological condition. Ergo, until validation in common research scenarios as case-control comparison studies is included into the development process of new software suites, confirmatory analyses utilising a similar software based on analogous, but not fully equivalent principles, might be considered as supplement to careful quality control.
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Affiliation(s)
- Pavel Filip
- Center for Magnetic Resonance Research (CMRR), University of Minnesota, 2021 Sixth St. SE, Minneapolis, MN, 55455, USA.,Department of Neurology, Charles University, First Faculty of Medicine and General University Hospital, Prague, Czech Republic
| | - Petr Bednarik
- Center for Magnetic Resonance Research (CMRR), University of Minnesota, 2021 Sixth St. SE, Minneapolis, MN, 55455, USA.,High Field MR Centre, Department of Biomedical Imaging and Image-Guided Therapy, Medical University of Vienna, Vienna, Austria
| | - Lynn E Eberly
- Center for Magnetic Resonance Research (CMRR), University of Minnesota, 2021 Sixth St. SE, Minneapolis, MN, 55455, USA.,Division of Biostatistics, School of Public Health, University of Minnesota, Minnesota, MN, USA
| | - Amir Moheet
- Department of Medicine, University of Minnesota, Minneapolis, MN, USA
| | - Alena Svatkova
- Department of Medicine III, Clinical Division of Endocrinology and Metabolism, Medical University of Vienna, Vienna, Austria.,Department of Imaging Methods, Faculty of Medicine, University of Ostrava, Ostrava, Czechia
| | - Heidi Grohn
- Center for Magnetic Resonance Research (CMRR), University of Minnesota, 2021 Sixth St. SE, Minneapolis, MN, 55455, USA.,Diagnostic Imaging Center, Kuopio University Hospital, Kuopio, Finland
| | - Anjali F Kumar
- Department of Medicine, University of Minnesota, Minneapolis, MN, USA
| | | | - Silvia Mangia
- Center for Magnetic Resonance Research (CMRR), University of Minnesota, 2021 Sixth St. SE, Minneapolis, MN, 55455, USA.
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6
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Zhang Z, Robinson L, Jia T, Quinlan EB, Tay N, Chu C, Barker ED, Banaschewski T, Barker GJ, Bokde ALW, Flor H, Grigis A, Garavan H, Gowland P, Heinz A, Ittermann B, Martinot JL, Stringaris A, Penttilä J, van Noort B, Grimmer Y, Paillère Martinot ML, Isensee C, Becker A, Nees F, Orfanos DP, Paus T, Poustka L, Hohmann S, Fröhner JH, Smolka MN, Walter H, Whelan R, Schumann G, Schmidt U, Desrivières S. Development of Disordered Eating Behaviors and Comorbid Depressive Symptoms in Adolescence: Neural and Psychopathological Predictors. Biol Psychiatry 2021; 90:853-862. [PMID: 32778392 DOI: 10.1016/j.biopsych.2020.06.003] [Citation(s) in RCA: 14] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/13/2019] [Revised: 06/01/2020] [Accepted: 06/01/2020] [Indexed: 12/26/2022]
Abstract
BACKGROUND Eating disorders are common in adolescence and are devastating and strongly comorbid with other psychiatric disorders. Yet little is known about their etiology, knowing which would aid in developing effective preventive measures. METHODS Longitudinal assessments of disordered eating behaviors (DEBs)-binge-eating, purging, and dieting-and comorbid psychopathology were measured in 1386 adolescents from the IMAGEN study. Development of DEBs and associated mental health problems was investigated by comparing participants who reported symptoms at ages 16 or 19 years, but not at age 14 years, with asymptomatic control participants. Voxel-based morphometry and psychopathological differences at age 14 were investigated to identify risk factors for the development of DEBs and associated mental health problems. RESULTS DEBs and depressive symptoms developed together. Emotional and behavioral problems, including symptoms of attention-deficit/hyperactivity disorder and conduct disorder, predated their development. Alterations in frontostriatal brain areas also predated the development of DEBs and depressive symptoms. Specifically, development of binge-eating was predicted by higher gray matter volumes in the right putamen/globus pallidus at age 14. Conversely, development of purging and depressive symptoms was predicted by lower volumes in the medial orbitofrontal, dorsomedial, and dorsolateral prefrontal cortices. Lower gray matter volumes in the orbitofrontal and anterior cingulate cortices mediated the relationship between attention-deficit/hyperactivity disorder and conduct disorder symptoms and future purging and depressive symptoms. CONCLUSIONS These findings suggest that alterations in frontal brain circuits are part of the shared etiology among eating disorders, attention-deficit/hyperactivity disorder, conduct disorder, and depression and highlight the importance of a transdiagnostic approach to treating these conditions.
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Affiliation(s)
- Zuo Zhang
- Centre for Population Neuroscience and Precision Medicine, Institute of Psychiatry, Psychology and Neuroscience, Social, Genetic and Developmental Psychiatry Centre, King's College London, London, United Kingdom
| | - Lauren Robinson
- Section of Eating Disorders, Department of Psychological Medicine, London, United Kingdom
| | - Tianye Jia
- Centre for Population Neuroscience and Precision Medicine, Institute of Psychiatry, Psychology and Neuroscience, Social, Genetic and Developmental Psychiatry Centre, King's College London, London, United Kingdom; Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China; Ministry of Education-Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence, Fudan University, Shanghai, China
| | - Erin Burke Quinlan
- Centre for Population Neuroscience and Precision Medicine, Institute of Psychiatry, Psychology and Neuroscience, Social, Genetic and Developmental Psychiatry Centre, King's College London, London, United Kingdom
| | - Nicole Tay
- Centre for Population Neuroscience and Precision Medicine, Institute of Psychiatry, Psychology and Neuroscience, Social, Genetic and Developmental Psychiatry Centre, King's College London, London, United Kingdom
| | - Congying Chu
- Centre for Population Neuroscience and Precision Medicine, Institute of Psychiatry, Psychology and Neuroscience, Social, Genetic and Developmental Psychiatry Centre, King's College London, London, United Kingdom
| | - Edward D Barker
- Centre for Population Neuroscience and Precision Medicine, Institute of Psychiatry, Psychology and Neuroscience, Social, Genetic and Developmental Psychiatry Centre, King's College London, London, United Kingdom; Developmental Psychopathology Lab, Department of Psychology, King's College London, London, United Kingdom
| | - Tobias Banaschewski
- Department of Child and Adolescent Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany
| | - Gareth J Barker
- Department of Neuroimaging, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, United Kingdom
| | - Arun L W Bokde
- Discipline of Psychiatry, School of Medicine and Trinity College Institute of Neuroscience, Trinity College, Dublin, Ireland
| | - Herta Flor
- Department of Cognitive and Clinical Neuroscience, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany; Department of Psychology, School of Social Sciences, University of Mannheim, Mannheim, Germany
| | - Antoine Grigis
- NeuroSpin, Commissariat à l'Énergie Atomique, Université Paris-Saclay, Gif-sur-Yvette, France
| | - Hugh Garavan
- Departments of Psychiatry and Psychology, University of Vermont, Burlington, Vermont, USA
| | - Penny Gowland
- Sir Peter Mansfield Imaging Centre, School of Physics and Astronomy, University of Nottingham, University Park, Nottingham, United Kingdom
| | - Andreas Heinz
- Department of Psychiatry and Psychotherapy, Charité-Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Campus Charite Mitte, Berlin, Germany
| | - Bernd Ittermann
- Physikalisch-Technische Bundesanstalt, Braunschweig and Berlin, Germany
| | - Jean-Luc Martinot
- Institut National de la Santé et de la Recherche Médicale U A10 "Developmental Trajectories and Psychiatry", Université Paris-Saclay, École Normale Supérieure Paris-Saclay, Centre National de la Recherche Scientifique, Centre Borelli, Gif-sur-Yvette, France
| | - Argyris Stringaris
- National Institute of Mental Health, National Institutes of Health, Bethesda, Maryland, USA
| | - Jani Penttilä
- Department of Social and Health Care, Psychosocial Services Adolescent Outpatient Clinic, Kauppakatu, Lahti, Finland
| | | | - Yvonne Grimmer
- Department of Child and Adolescent Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany
| | - Marie-Laure Paillère Martinot
- Institut National de la Santé et de la Recherche Médicale Unit 1000 "Neuroimaging & Psychiatry", Université Paris-Saclay, Université Paris Descartes, Sorbonne Université, Paris, France; Department of Child and Adolescent Psychiatry, Assistance Publique-Hôpitaux de Paris, Pitié-Salpêtrière Hospital, Paris, France
| | - Corinna Isensee
- Department of Child and Adolescent Psychiatry and Psychotherapy, University Medical Center Göttingen, Göttingen, Germany
| | - Andreas Becker
- Department of Child and Adolescent Psychiatry and Psychotherapy, University Medical Center Göttingen, Göttingen, Germany
| | - Frauke Nees
- Department of Child and Adolescent Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany; Department of Cognitive and Clinical Neuroscience, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany; Institute of Medical Psychology and Medical Sociology, University Medical Center Schleswig Holstein, Kiel University, Kiel, Germany
| | | | - Tomáš Paus
- Bloorview Research Institute, Holland Bloorview Kids Rehabilitation Hospital, Toronto, Ontario, Canada; Departments of Psychology and Psychiatry, University of Toronto, Toronto, Ontario, Canada
| | - Luise Poustka
- Department of Child and Adolescent Psychiatry and Psychotherapy, University Medical Center Göttingen, Göttingen, Germany
| | - Sarah Hohmann
- Department of Child and Adolescent Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany
| | - Juliane H Fröhner
- Department of Psychiatry and Neuroimaging Center, Technische Universitat Dresden, Dresden, Germany
| | - Michael N Smolka
- Department of Psychiatry and Neuroimaging Center, Technische Universitat Dresden, Dresden, Germany
| | - Henrik Walter
- Department of Psychiatry and Psychotherapy, Charité-Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Campus Charite Mitte, Berlin, Germany
| | - Robert Whelan
- School of Psychology and Global Brain Health Institute, Trinity College, Dublin, Ireland
| | - Gunter Schumann
- Centre for Population Neuroscience and Precision Medicine, Institute of Psychiatry, Psychology and Neuroscience, Social, Genetic and Developmental Psychiatry Centre, King's College London, London, United Kingdom; Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China; Department of Psychiatry and Psychotherapy, Charité-Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Campus Charite Mitte, Berlin, Germany
| | - Ulrike Schmidt
- Section of Eating Disorders, Department of Psychological Medicine, London, United Kingdom; The Eating Disorders Service, Maudsley Hospital, South London, and Maudsley NHS Foundation Trust, London, United Kingdom
| | - Sylvane Desrivières
- Centre for Population Neuroscience and Precision Medicine, Institute of Psychiatry, Psychology and Neuroscience, Social, Genetic and Developmental Psychiatry Centre, King's College London, London, United Kingdom.
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7
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Singh M, Pahl E, Wang S, Carass A, Lee J, Prince JL. Accurate Estimation of Total Intracranial Volume in MRI using a Multi-tasked Image-to-Image Translation Network. PROCEEDINGS OF SPIE--THE INTERNATIONAL SOCIETY FOR OPTICAL ENGINEERING 2021; 11596. [PMID: 34548736 DOI: 10.1117/12.2582264] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/14/2022]
Abstract
Total intracranial volume (TIV) is the volume enclosed inside the cranium, inclusive of the meninges and the brain. TIV is extensively used to correct variations in inter-subject head size for the evaluation of neurodegenerative diseases. In this work, we present an automatic method to generate a TIV mask from MR images while synthesizing a CT image to be used in subsequent analysis. In addition, we propose an alternative way to obtain ground truth TIV masks using a semi-manual approach, which results in significant time savings. We train a conditional generative adversarial network (cGAN) using 2D MR slices to realize our tasks. The quantitative evaluation showed that the model was able to synthesize CT and generate TIV masks that closely approximate the reference images. This study also provides a comparison of the described method against skull stripping tools that output a mask enclosing the cranial volume, using MRI scan. In particular, highlighting the deficiencies in using such tools to approximate the volume using MRI scan.
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Affiliation(s)
- Mallika Singh
- Dept. of Biomedical Engineering, The Johns Hopkins University, Baltimore, MD 21218
| | - Eleanor Pahl
- Dept. of Aerospace Engineering, Embry-Riddle Aeronautical University (ERAU), Prescott, AZ 86301
| | - Shangxian Wang
- Dept. of Electrical and Computer Engineering, The Johns Hopkins University, Baltimore, MD 21218
| | - Aaron Carass
- Dept. of Electrical and Computer Engineering, The Johns Hopkins University, Baltimore, MD 21218
| | - Junghoon Lee
- Dept. of Radiation Oncology and Molecular Radiation Sciences, The Johns Hopkins School of Medicine, Baltimore, MD 21231
| | - Jerry L Prince
- Dept. of Biomedical Engineering, The Johns Hopkins University, Baltimore, MD 21218.,Dept. of Electrical and Computer Engineering, The Johns Hopkins University, Baltimore, MD 21218
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Ancelin ML, Carrière I, Artero S, Maller JJ, Meslin C, Dupuy AM, Ritchie K, Ryan J, Chaudieu I. Structural brain alterations in older adults exposed to early-life adversity. Psychoneuroendocrinology 2021; 129:105272. [PMID: 34023732 DOI: 10.1016/j.psyneuen.2021.105272] [Citation(s) in RCA: 15] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/23/2021] [Revised: 04/12/2021] [Accepted: 05/11/2021] [Indexed: 11/25/2022]
Abstract
BACKGROUND Adverse childhood events may have differential effects on the brain that persist into adulthood. Findings on structural brain alterations in older adults exposed to early-life adversity are inconsistent notably due to heterogeneity in imaging studies, population, psychiatric comorbidities, nature of adverse events, and genetic vulnerability. This study examines whether exposure related to physical or sexual maltreatment, emotional maltreatment, and global adverse environment during childhood are associated with specific alterations in grey matter volumes and if this varies according to sex and serotonin transporter-linked promoter region (5-HTTLPR) genotype. METHOD Structural MRI was used to acquire anatomical scans from 398 community-dwelling older adults. Quantitative regional estimates of 23 subregional volumes were derived using FreeSurfer software. Retrospective reporting of childhood adversity was collected using structured self-reported questionnaire. Analyses adjusted for age, sex, brain volume, head injury, lifetime depression and anxiety disorder, psychiatric medication, and cardiovascular ischemic pathologies. RESULTS Exposure to adverse family environment was associated with smaller volumes of several frontal, cingulate, and parietal subregions and larger amygdala in the 5-HTTLPR SS genotype participants specifically but larger volumes of caudate, putamen, pallidum, and nucleus accumbens in the SL genotype participants. Highly significant differences were found with excessive sharing of parent problems with children, associated with larger grey-matter volumes in the thalamus and several frontal and parietal regions in 5-HTTLPR SL male participants specifically. CONCLUSIONS Early-life adversity is associated with grey-matter volume alterations in older adults and this varies according to the type of adversity experienced, sex, and serotonergic genetic vulnerability; 5-HTTLPR SS participants appearing most vulnerable and SL individuals most resilient.
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Affiliation(s)
| | | | | | - Jerome J Maller
- Monash Alfred Psychiatry Research Centre, Central Clinical School, Monash University and the Alfred Hospital, Melbourne, VIC, Australia; Centre for Mental Health Research, Australian National University, Canberra, Australia; General Electric Healthcare, Australia
| | - Chantal Meslin
- Centre for Mental Health Research, Australian National University, Canberra, Australia
| | - Anne-Marie Dupuy
- INM, Univ Montpellier, INSERM, Montpellier, France; INM, Univ Montpellier, INSERM, CHU Montpellier, Montpellier, France
| | - Karen Ritchie
- INM, Univ Montpellier, INSERM, Montpellier, France; Center for Clinical Brain Sciences, University of Edinburgh, UK
| | - Joanne Ryan
- Biological Neuropsychiatry Unit, School of Public Health and Preventive Medicine, Monash University, Melbourne, VIC, Australia
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10
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Easy Identification of Optimal Coronal Slice on Brain Magnetic Resonance Imaging to Measure Hippocampal Area in Alzheimer's Disease Patients. BIOMED RESEARCH INTERNATIONAL 2020; 2020:5894021. [PMID: 33029517 PMCID: PMC7532424 DOI: 10.1155/2020/5894021] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 06/04/2020] [Accepted: 08/03/2020] [Indexed: 11/27/2022]
Abstract
Introduction Measurement of an- hippocampal area or volume is useful in clinical practice as a supportive aid for diagnosis of Alzheimer's disease. Since it is time-consuming and not simple, it is not being used very often. We present a simplified protocol for hippocampal atrophy evaluation based on a single optimal slice in Alzheimer's disease. Methods We defined a single optimal slice for hippocampal measurement on brain magnetic resonance imaging (MRI) at the plane where the amygdala disappears and only the hippocampus is present. We compared an absolute area and volume of the hippocampus on this optimal slice between 40 patients with Alzheimer disease and 40 age-, education- and gender-mateched elderly controls. Furthermore, we compared these results with those relative to the size of the brain or the skull: the area of the optimal slice normalized to the area of the brain at anterior commissure and the volume of the hippocampus normalized to the total intracranial volume. Results Hippocampal areas on the single optimal slice and hippocampal volumes on the left and right in the control group were significantly higher than those in the AD group. Normalized hippocampal areas and volumes on the left and right in the control group were significantly higher compared to the AD group. Absolute hippocampal areas and volumes did not significantly differ from corresponding normalized hippocampal areas as well as normalized hippocampal volumes using comparisons of areas under the receiver operating characteristic curves. Conclusion The hippocampal area on the well-defined optimal slice of brain MRI can reliably substitute a complicated measurement of the hippocampal volume. Surprisingly, brain or skull normalization of these variables does not add any incremental differentiation between Alzheimer disease patients and controls or give better results.
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Forouzannezhad P, Abbaspour A, Li C, Fang C, Williams U, Cabrerizo M, Barreto A, Andrian J, Rishe N, Curiel RE, Loewenstein D, Duara R, Adjouadi M. A Gaussian-based model for early detection of mild cognitive impairment using multimodal neuroimaging. J Neurosci Methods 2020; 333:108544. [PMID: 31838182 PMCID: PMC11163390 DOI: 10.1016/j.jneumeth.2019.108544] [Citation(s) in RCA: 16] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/17/2018] [Revised: 11/26/2019] [Accepted: 12/05/2019] [Indexed: 12/14/2022]
Abstract
BACKGROUND Diagnosis of early mild cognitive impairment (EMCI) as a prodromal stage of Alzheimer's disease (AD) with its delineation from the cognitively normal (CN) group remains a challenging but essential step for the planning of early treatment. Although several studies have focused on the MCI diagnosis, this study introduces the early stage of MCI to assess more thoroughly the earliest signs of disease manifestation and progression. NEW METHOD We used random forest feature selection model with a Gaussian-based algorithm to perform method evaluation. This integrated method serves to define multivariate normal distributions in order to classify different stages of AD, with the focus placed on detecting EMCI subjects in the most challenging classification of CN vs. EMCI. RESULTS Using 896 participants classified into the four categories of CN, EMCI, late mild cognitive impairment (LMCI) and AD, the results show that the EMCI group can be delineated from the CN group with a relatively high accuracy of 78.8% and sensitivity of 81.3%. COMPARISON WITH EXISTING METHOD(S) The feature selection model and classifier are compared with some other prominent algorithms. Although higher accuracy has been achieved using the Gaussian process (GP) model (78.8%) over the SVM classifier (75.6%) for CN vs. EMCI classification, with 0.05 being the cutoff for significance, and based on student's t-test, it was determined that the differences for accuracy, sensitivity, specificity between the GP method and support vector machine (SVM) are not statistically significant. CONCLUSION Addressing the challenging classification of CN vs. EMCI provides useful information to help clinicians and researchers determine essential measures that can help in the early detection of AD.
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Affiliation(s)
- Parisa Forouzannezhad
- Department of Electrical and Computer Engineering, Florida International University, Miami, FL, USA
| | - Alireza Abbaspour
- Department of Electrical and Computer Engineering, Florida International University, Miami, FL, USA
| | - Chunfei Li
- Department of Electrical and Computer Engineering, Florida International University, Miami, FL, USA
| | - Chen Fang
- Department of Electrical and Computer Engineering, Florida International University, Miami, FL, USA
| | - Ulyana Williams
- Department of Electrical and Computer Engineering, Florida International University, Miami, FL, USA
| | - Mercedes Cabrerizo
- Department of Electrical and Computer Engineering, Florida International University, Miami, FL, USA
| | - Armando Barreto
- Department of Electrical and Computer Engineering, Florida International University, Miami, FL, USA
| | - Jean Andrian
- Department of Electrical and Computer Engineering, Florida International University, Miami, FL, USA
| | - Naphtali Rishe
- School of Computing and Information Sciences, Florida International University, Miami, FL, USA
| | - Rosie E Curiel
- Center for Cognitive Neuroscience and Aging, Department of Psychiatry and Behavioral Sciences, University of Miami School of Medicine, Miami, FL, USA; 1Florida Alzheimer's Disease Research Center (ADRC), University of Florida, Gainesville, FL, USA
| | - David Loewenstein
- Center for Cognitive Neuroscience and Aging, Department of Psychiatry and Behavioral Sciences, University of Miami School of Medicine, Miami, FL, USA; 1Florida Alzheimer's Disease Research Center (ADRC), University of Florida, Gainesville, FL, USA; Wien Center for Alzheimer's Disease and Memory Disorders, Mount Sinai Medical Center, Miami Beach, FL, USA
| | - Ranjan Duara
- 1Florida Alzheimer's Disease Research Center (ADRC), University of Florida, Gainesville, FL, USA; Wien Center for Alzheimer's Disease and Memory Disorders, Mount Sinai Medical Center, Miami Beach, FL, USA
| | - Malek Adjouadi
- Department of Electrical and Computer Engineering, Florida International University, Miami, FL, USA; 1Florida Alzheimer's Disease Research Center (ADRC), University of Florida, Gainesville, FL, USA
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Buchpiguel M, Rosa P, Squarzoni P, Duran FL, Tamashiro-Duran JH, Leite CC, Lotufo P, Scazufca M, Alves TC, Busatto GF. Differences in Total Brain Volume between Sexes in a Cognitively Unimpaired Elderly Population. Clinics (Sao Paulo) 2020; 75:e2245. [PMID: 33331399 PMCID: PMC7690962 DOI: 10.6061/clinics/2020/e2245] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/17/2020] [Accepted: 10/20/2020] [Indexed: 11/26/2022] Open
Abstract
OBJECTIVES Although a large number of studies have shown brain volumetric differences between men and women, only a few investigations have analyzed brain tissue volumes in representative samples of the general elderly population. We investigated differences in gray matter (GM) volumes, white matter (WM) volumes, and intracranial volumes (ICVs) between the sexes in individuals older than 66 years using structural magnetic resonance imaging (MRI). METHODS Using FreeSurfer version 5.3, we obtained the ICVs and GM and WM volumes from the MRI datasets of 84 men and 92 women. To correct for interindividual variations in ICV, GM and WM volumes were adjusted with a method using the residuals of a least-square-derived linear regression between raw volumes and ICVs. We then performed an analysis of covariance comparing men and women, including age and years of schooling as confounding factors. RESULTS Women had a lower socioeconomic status overall and fewer years of schooling than men. The comparison of unadjusted brain volumes showed larger GM and WM volumes in men. After the ICV correction, the adjusted volumes of GM and WM were larger in women. CONCLUSION After the ICV correction and taking into account differences in socioeconomic status and years of schooling, our results confirm previous findings of proportionally larger GM in women, as well as larger WM volumes. These results in an elderly population indicate that brain volumetric differences between sexes persist throughout the aging process. Additional studies combining MRI and other biomarkers to identify the hormonal and molecular bases influencing such differences are warranted.
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Affiliation(s)
- Marina Buchpiguel
- Departamento e Instituto de Psiquiatria, Faculdade de Medicina (FMUSP), Universidade de Sao Paulo, Sao Paulo, SP, BR
- Laboratorio Neuro-Imagem em Psiquiatria (LIM/21), Departamento e Instituto de Psiquiatria, Faculdade de Medicina (FMUSP), Universidade de Sao Paulo, Sao Paulo, SP, BR
- Escola de Ciencias Medicas, Santa Casa de Sao Paulo, Sao Paulo SP, BR
- *Corresponding Author. E-mail:
| | - Pedro Rosa
- Departamento e Instituto de Psiquiatria, Faculdade de Medicina (FMUSP), Universidade de Sao Paulo, Sao Paulo, SP, BR
| | - Paula Squarzoni
- Laboratorio Neuro-Imagem em Psiquiatria (LIM/21), Departamento e Instituto de Psiquiatria, Faculdade de Medicina (FMUSP), Universidade de Sao Paulo, Sao Paulo, SP, BR
| | - Fabio L.S. Duran
- Laboratorio Neuro-Imagem em Psiquiatria (LIM/21), Departamento e Instituto de Psiquiatria, Faculdade de Medicina (FMUSP), Universidade de Sao Paulo, Sao Paulo, SP, BR
| | - Jaqueline H. Tamashiro-Duran
- Laboratorio Neuro-Imagem em Psiquiatria (LIM/21), Departamento e Instituto de Psiquiatria, Faculdade de Medicina (FMUSP), Universidade de Sao Paulo, Sao Paulo, SP, BR
| | - Claudia C. Leite
- Departamento de Radiologia, Faculdade de Medicina (FMUSP), Universidade de Sao Paulo, Sao Paulo, SP, BR
| | - Paulo Lotufo
- Unidade de Pesquisa Clinica e Epidemiologia, Faculdade de Medicina (FMUSP), Universidade de Sao Paulo, Sao Paulo, SP, BR
| | - Marcia Scazufca
- Departamento e Instituto de Psiquiatria, Faculdade de Medicina (FMUSP), Universidade de Sao Paulo, Sao Paulo, SP, BR
| | - Tania C.T.F. Alves
- Departamento e Instituto de Psiquiatria, Faculdade de Medicina (FMUSP), Universidade de Sao Paulo, Sao Paulo, SP, BR
| | - Geraldo F. Busatto
- Laboratorio Neuro-Imagem em Psiquiatria (LIM/21), Departamento e Instituto de Psiquiatria, Faculdade de Medicina (FMUSP), Universidade de Sao Paulo, Sao Paulo, SP, BR
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Rodrigues MAS, Rodrigues TP, Zatz M, Lebrão ML, Duarte YA, Naslavsky MS, do Nascimento FBP, Amaro Junior E. Quantitative evaluation of brain volume among elderly individuals in São Paulo, Brazil: a population-based study. Radiol Bras 2019; 52:293-298. [PMID: 31656345 PMCID: PMC6808618 DOI: 10.1590/0100-3984.2018.0074] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/20/2023] Open
Abstract
Objective To perform a quantitative analysis of the brain volume of elderly
individuals in a population-based sample. Materials and Methods This was a radiological assessment and voxel-based quantitative analysis,
with surface alignment, of 525 magnetic resonance imaging scans of
individuals between 60 and 103 years of age who participated in the
Saúde, Bem-estar e Envelhecimento (Health,
Well-being, and Aging) study in the city of São Paulo, Brazil. Results We noted a median rate of reduction in total brain volume of 2.4% per decade
after 60 years of age. Gray and white matter both showed volume reductions
with age. The total brain volume/intracranial brain volume ratio differed
between males and females. Conclusion We have corroborated the findings of studies conducted in the United States
and Europe. The total brain volume/intracranial brain volume ratio is higher
in men, representing a potential bias for the conventional radiological
assessment of atrophy, which is typically based on the evaluation of the
cerebrospinal fluid spaces.
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Affiliation(s)
| | - Thiago Pereira Rodrigues
- Escola Paulista de Medicina da Universidade Federal de São Paulo (EPM-Unifesp), São Paulo, SP, Brazil
| | - Mayana Zatz
- Biosciences Institute, Universidade de São Paulo, São Paulo, SP, Brazil
| | - Maria Lúcia Lebrão
- School of Public Health, Universidade de São Paulo, São Paulo, SP, Brazil
| | | | | | | | - Edson Amaro Junior
- Department of Radiology and Diagnostic Imaging, Hospital Israelita Albert Einstein, São Paulo, SP, Brazil
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Serrano N, López-Sanz D, Bruña R, Garcés P, Rodríguez-Rojo IC, Marcos A, Crespo DP, Maestú F. Spatiotemporal Oscillatory Patterns During Working Memory Maintenance in Mild Cognitive Impairment and Subjective Cognitive Decline. Int J Neural Syst 2019; 30:1950019. [DOI: 10.1142/s0129065719500199] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022]
Abstract
Working memory (WM) is a crucial cognitive process and its disruption is among the earliest symptoms of Alzheimer’s disease. While alterations of the neuronal processes underlying WM have been evidenced in mild cognitive impairment (MCI), scarce literature is available in subjective cognitive decline (SCD). We used magnetoencephalography during a WM task performed by MCI [Formula: see text], SCD [Formula: see text] and healthy elders [Formula: see text] to examine group differences during the maintenance period (0–4000[Formula: see text]ms). Data were analyzed using time–frequency analysis and significant oscillatory differences were localized at the source level. Our results indicated significant differences between groups, mainly during the early maintenance (250–1250[Formula: see text]ms) in the theta, alpha and beta bands and in the late maintenance (2750–3750[Formula: see text]ms) in the theta band. MCI showed lower local synchronization in fronto-temporal cortical regions in the early theta–alpha window relative to controls [Formula: see text] and SCD [Formula: see text], and in the late theta window relative to controls [Formula: see text] and SCD [Formula: see text]. Early theta–alpha power was significantly correlated with memory scores [Formula: see text] and late theta power was correlated with task performance [Formula: see text] and functional activity scores [Formula: see text]. In the early beta window, MCI showed reduced power in temporo-posterior regions relative to controls [Formula: see text] and SCD [Formula: see text]. Our results may suggest that these alterations would reflect that memory-related networks are damaged.
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Affiliation(s)
- N. Serrano
- Department of Experimental Psychology, Complutense University of Madrid, Pozuelo de Alarcón, Madrid 28223, Spain
- Laboratory of Cognitive and Computational Neuroscience (UCM-UPM), Center for Biomedical Technology (CTB), Pozuelo de Alarcón, Madrid 28223, Spain
| | - D. López-Sanz
- Department of Experimental Psychology, Complutense University of Madrid, Pozuelo de Alarcón, Madrid 28223, Spain
- Laboratory of Cognitive and Computational Neuroscience (UCM-UPM), Center for Biomedical Technology (CTB), Pozuelo de Alarcón, Madrid 28223, Spain
| | - R. Bruña
- Department of Experimental Psychology, Complutense University of Madrid, Pozuelo de Alarcón, Madrid 28223, Spain
- Laboratory of Cognitive and Computational Neuroscience (UCM-UPM), Center for Biomedical Technology (CTB), Pozuelo de Alarcón, Madrid 28223, Spain
- CIBER’s Bioengineering, Biomaterials and Nanomedicine (CIBER-BBN), Institute of Health Carlos III, Madrid, Spain
| | - P. Garcés
- Laboratory of Cognitive and Computational Neuroscience (UCM-UPM), Center for Biomedical Technology (CTB), Pozuelo de Alarcón, Madrid 28223, Spain
| | - I. C. Rodríguez-Rojo
- Department of Experimental Psychology, Complutense University of Madrid, Pozuelo de Alarcón, Madrid 28223, Spain
- Laboratory of Cognitive and Computational Neuroscience (UCM-UPM), Center for Biomedical Technology (CTB), Pozuelo de Alarcón, Madrid 28223, Spain
| | - A. Marcos
- Neurology Department, San Carlos Clinical Hospital, Madrid, Spain
| | - D. Prada Crespo
- Centro de Prevención del Deterioro Cognitivo del Ayuntamiento, de Madrid Madrid, Spain
| | - F. Maestú
- Department of Experimental Psychology, Complutense University of Madrid, Pozuelo de Alarcón, Madrid 28223, Spain
- Laboratory of Cognitive and Computational Neuroscience (UCM-UPM), Center for Biomedical Technology (CTB), Pozuelo de Alarcón, Madrid 28223, Spain
- CIBER’s Bioengineering, Biomaterials and Nanomedicine (CIBER-BBN), Institute of Health Carlos III, Madrid, Spain
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Ma D, Popuri K, Bhalla M, Sangha O, Lu D, Cao J, Jacova C, Wang L, Beg MF. Quantitative assessment of field strength, total intracranial volume, sex, and age effects on the goodness of harmonization for volumetric analysis on the ADNI database. Hum Brain Mapp 2019; 40:1507-1527. [PMID: 30431208 PMCID: PMC6449147 DOI: 10.1002/hbm.24463] [Citation(s) in RCA: 23] [Impact Index Per Article: 4.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/07/2018] [Revised: 10/25/2018] [Accepted: 10/26/2018] [Indexed: 12/29/2022] Open
Abstract
When analyzing large multicenter databases, the effects of multiple confounding covariates increase the variability in the data and may reduce the ability to detect changes due to the actual effect of interest, for example, changes due to disease. Efficient ways to evaluate the effect of covariates toward the data harmonization are therefore important. In this article, we showcase techniques to assess the "goodness of harmonization" of covariates. We analyze 7,656 MR images in the multisite, multiscanner Alzheimer's Disease Neuroimaging Initiative (ADNI) database. We present a comparison of three methods for estimating total intracranial volume to assess their robustness and correct the brain structure volumes using the residual method and the proportional (normalization by division) method. We then evaluated the distribution of brain structure volumes over the entire ADNI database before and after accounting for multiple covariates such as total intracranial volume, scanner field strength, sex, and age using two techniques: (a) Zscapes, a panoramic visualization technique to analyze the entire database and (b) empirical cumulative distributions functions. The results from this study highlight the importance of assessing the goodness of data harmonization as a necessary preprocessing step when pooling large data set with multiple covariates, prior to further statistical data analysis.
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Affiliation(s)
- Da Ma
- School of Engineering ScienceSimon Fraser UniversityBurnabyBritish ColumbiaCanada
| | - Karteek Popuri
- School of Engineering ScienceSimon Fraser UniversityBurnabyBritish ColumbiaCanada
| | - Mahadev Bhalla
- School of Engineering ScienceSimon Fraser UniversityBurnabyBritish ColumbiaCanada
- Faculty of MedicineUniversity of British ColumbiaVancouverBritish ColumbiaCanada
| | - Oshin Sangha
- School of Engineering ScienceSimon Fraser UniversityBurnabyBritish ColumbiaCanada
| | - Donghuan Lu
- School of Engineering ScienceSimon Fraser UniversityBurnabyBritish ColumbiaCanada
| | - Jiguo Cao
- Department of Statistics and Actuarial ScienceSimon Fraser UniversityBurnabyBritish ColumbiaCanada
| | - Claudia Jacova
- Department of Medicine, Division of NeurologyUniversity of British ColumbiaVancouverBritish ColumbiaCanada
| | - Lei Wang
- Feinberg School of Medicine, Northwestern UniversityChicagoIllinois
| | - Mirza Faisal Beg
- School of Engineering ScienceSimon Fraser UniversityBurnabyBritish ColumbiaCanada
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Ancelin ML, Carrière I, Artero S, Maller J, Meslin C, Ritchie K, Ryan J, Chaudieu I. Lifetime major depression and grey-matter volume. J Psychiatry Neurosci 2019; 44:45-53. [PMID: 30565905 PMCID: PMC6306287 DOI: 10.1503/jpn.180026] [Citation(s) in RCA: 65] [Impact Index Per Article: 13.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/21/2022] Open
Abstract
BACKGROUND There is evidence of structural brain alterations in major depressive disorder (MDD), but little is known about how these alterations might be affected by age at onset or genetic vulnerability. This study examines whether lifetime episodes of MDD are associated with specific alterations in grey-matter volume, and whether those alterations vary according to sex or serotonin transporter-linked promoter region (5-HTTLPR) genotype (LL, SL or SS). METHODS We used structural MRI to acquire anatomic scans from 610 community-dwelling participants. We derived quantitative regional estimates of grey-matter volume in 16 subregions using FreeSurfer software. We diagnosed MDD according to DSM-IV criteria. We adjusted analyses for age, sex, total brain volume, education level, head injury and comorbidities. RESULTS Lifetime MDD was associated with a smaller insula, thalamus, ventral diencephalon, pallidum and nucleus accumbens and with a larger pericalcarine region in both men and women. These associations remained after adjustment for false discovery rate. Lifetime MDD was also associated with a smaller caudate nucleus and amygdala in men and with a larger rostral anterior cingulate cortex in women. Late-onset first episodes of MDD (after age 50 years) were associated with a larger rostral anterior cingulate cortex and lingual and pericalcarine regions; early-onset MDD was associated with a smaller ventral diencephalon and nucleus accumbens. Some associations differed according to 5-HTTLPR genotype: the thalamus was smaller in participants with MDD and the LL genotype; pericalcarine and lingual volumes were higher in those with the SL genotype. LIMITATIONS This study was limited by its cross-sectional design. CONCLUSION Major depressive disorder was associated with persistent volume reductions in the deep nuclei and insula and with enlargements in visual cortex subregions; alterations varied according to age of onset and genotype.
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Affiliation(s)
- Marie-Laure Ancelin
- From INSERM, Univ Montpellier, Neuropsychiatry: Epidemiological and Clinical Research, Montpellier, France (Ancelin, Carrière, Artero, Ritchie, Ryan, Chaudieu); Monash Alfred Psychiatry Research Centre, Central Clinical School, Monash University and Alfred Hospital, Australia (Maller); Centre for Mental Health Research, Australian National University, Canberra, Australia (Maller, Meslin); General Electric Healthcare, Australia (Maller); Center for Clinical Brain Sciences, University of Edinburgh, Edinburgh, United Kingdom (Ritchie); and Department of Epidemiology and Preventive Medicine, Monash University, Melbourne, Australia (Ryan)
| | - Isabelle Carrière
- From INSERM, Univ Montpellier, Neuropsychiatry: Epidemiological and Clinical Research, Montpellier, France (Ancelin, Carrière, Artero, Ritchie, Ryan, Chaudieu); Monash Alfred Psychiatry Research Centre, Central Clinical School, Monash University and Alfred Hospital, Australia (Maller); Centre for Mental Health Research, Australian National University, Canberra, Australia (Maller, Meslin); General Electric Healthcare, Australia (Maller); Center for Clinical Brain Sciences, University of Edinburgh, Edinburgh, United Kingdom (Ritchie); and Department of Epidemiology and Preventive Medicine, Monash University, Melbourne, Australia (Ryan)
| | - Sylvaine Artero
- From INSERM, Univ Montpellier, Neuropsychiatry: Epidemiological and Clinical Research, Montpellier, France (Ancelin, Carrière, Artero, Ritchie, Ryan, Chaudieu); Monash Alfred Psychiatry Research Centre, Central Clinical School, Monash University and Alfred Hospital, Australia (Maller); Centre for Mental Health Research, Australian National University, Canberra, Australia (Maller, Meslin); General Electric Healthcare, Australia (Maller); Center for Clinical Brain Sciences, University of Edinburgh, Edinburgh, United Kingdom (Ritchie); and Department of Epidemiology and Preventive Medicine, Monash University, Melbourne, Australia (Ryan)
| | - Jerome Maller
- From INSERM, Univ Montpellier, Neuropsychiatry: Epidemiological and Clinical Research, Montpellier, France (Ancelin, Carrière, Artero, Ritchie, Ryan, Chaudieu); Monash Alfred Psychiatry Research Centre, Central Clinical School, Monash University and Alfred Hospital, Australia (Maller); Centre for Mental Health Research, Australian National University, Canberra, Australia (Maller, Meslin); General Electric Healthcare, Australia (Maller); Center for Clinical Brain Sciences, University of Edinburgh, Edinburgh, United Kingdom (Ritchie); and Department of Epidemiology and Preventive Medicine, Monash University, Melbourne, Australia (Ryan)
| | - Chantal Meslin
- From INSERM, Univ Montpellier, Neuropsychiatry: Epidemiological and Clinical Research, Montpellier, France (Ancelin, Carrière, Artero, Ritchie, Ryan, Chaudieu); Monash Alfred Psychiatry Research Centre, Central Clinical School, Monash University and Alfred Hospital, Australia (Maller); Centre for Mental Health Research, Australian National University, Canberra, Australia (Maller, Meslin); General Electric Healthcare, Australia (Maller); Center for Clinical Brain Sciences, University of Edinburgh, Edinburgh, United Kingdom (Ritchie); and Department of Epidemiology and Preventive Medicine, Monash University, Melbourne, Australia (Ryan)
| | - Karen Ritchie
- From INSERM, Univ Montpellier, Neuropsychiatry: Epidemiological and Clinical Research, Montpellier, France (Ancelin, Carrière, Artero, Ritchie, Ryan, Chaudieu); Monash Alfred Psychiatry Research Centre, Central Clinical School, Monash University and Alfred Hospital, Australia (Maller); Centre for Mental Health Research, Australian National University, Canberra, Australia (Maller, Meslin); General Electric Healthcare, Australia (Maller); Center for Clinical Brain Sciences, University of Edinburgh, Edinburgh, United Kingdom (Ritchie); and Department of Epidemiology and Preventive Medicine, Monash University, Melbourne, Australia (Ryan)
| | - Joanne Ryan
- From INSERM, Univ Montpellier, Neuropsychiatry: Epidemiological and Clinical Research, Montpellier, France (Ancelin, Carrière, Artero, Ritchie, Ryan, Chaudieu); Monash Alfred Psychiatry Research Centre, Central Clinical School, Monash University and Alfred Hospital, Australia (Maller); Centre for Mental Health Research, Australian National University, Canberra, Australia (Maller, Meslin); General Electric Healthcare, Australia (Maller); Center for Clinical Brain Sciences, University of Edinburgh, Edinburgh, United Kingdom (Ritchie); and Department of Epidemiology and Preventive Medicine, Monash University, Melbourne, Australia (Ryan)
| | - Isabelle Chaudieu
- From INSERM, Univ Montpellier, Neuropsychiatry: Epidemiological and Clinical Research, Montpellier, France (Ancelin, Carrière, Artero, Ritchie, Ryan, Chaudieu); Monash Alfred Psychiatry Research Centre, Central Clinical School, Monash University and Alfred Hospital, Australia (Maller); Centre for Mental Health Research, Australian National University, Canberra, Australia (Maller, Meslin); General Electric Healthcare, Australia (Maller); Center for Clinical Brain Sciences, University of Edinburgh, Edinburgh, United Kingdom (Ritchie); and Department of Epidemiology and Preventive Medicine, Monash University, Melbourne, Australia (Ryan)
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Neuroimaging in Fabry disease: current knowledge and future directions. Insights Imaging 2018; 9:1077-1088. [PMID: 30390274 PMCID: PMC6269338 DOI: 10.1007/s13244-018-0664-8] [Citation(s) in RCA: 17] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/05/2018] [Revised: 09/07/2018] [Accepted: 09/27/2018] [Indexed: 12/14/2022] Open
Abstract
Abstract Fabry disease (FD) is a rare X-linked disorder characterised by abnormal progressive lysosomal deposition of globotriaosylceramide in a large variety of cell types. The central nervous system (CNS) is often involved in FD, with a wide spectrum of manifestations ranging from mild symptoms to more severe courses related to acute cerebrovascular events. In this review we present the current knowledge on brain imaging for this condition, with a comprehensive and critical description of its most common neuroradiological imaging findings. Moreover, we report results from studies that investigated brain physiopathology underlying this disorder by using advanced imaging techniques, suggesting possible future directions to further explore CNS involvement in FD patients. Teaching Points • Conventional neuroradiological findings in FD are aspecific. • White matter hyperintensities represent the more consistent brain imaging feature of FD • Abnormalities of the vasculature wall of posterior circulation are also consistent features. • The pulvinar sign is not reliable as a finding pathognomonic for FD. • Advanced imaging techniques have increased our knowledge about brain involvement in FD.
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Sargolzaei S, Cai Y, Wolahan SM, Gaonkar B, Sargolzaei A, Giza CC, Harris NG. A Comparative Study of Automatic Approaches for Preclinical MRI-based Brain Segmentation in the Developing Rat. ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. ANNUAL INTERNATIONAL CONFERENCE 2018; 2018:652-655. [PMID: 30440481 PMCID: PMC6354582 DOI: 10.1109/embc.2018.8512402] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/09/2023]
Abstract
Accurate pre-clinical study reporting requires validated processing tools to increase data reproducibility within and between laboratories. Segmentation of rodent brain from non-brain tissue is an important first step in preclinical imaging pipelines for which well validated tools are still under development. The current study aims to clarify the best approach to automatic brain extraction for studies in the immature rat. Skull stripping modules from AFNI, PCNN-3D, and RATS software packages were assessed for their ability to accurately segment brain from non-brain by comparison to manual segmentation. Comparison was performed using Dice coefficient of similarity. Results showed that the RATS package outperformed the others by including a lower percentage of false positive, non-brain voxels in the brain mask. However, AFNI resulted in a lower percentage of false negative voxels. Although the automatic approaches for brain segmentation significantly facilitate the data stream process, the current study findings suggest that the task of rodent brain segmentation from T2 weighted MRI needs to be accompanied by a supervised quality control step when developmental brain imaging studies were targeted.
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Adduru VR, Michael AM, Helguera M, Baum SA, Moore GJ. Leveraging Clinical Imaging Archives for Radiomics: Reliability of Automated Methods for Brain Volume Measurement. Radiology 2017; 284:862-869. [DOI: 10.1148/radiol.2017161928] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/31/2023]
Affiliation(s)
- Viraj R. Adduru
- From the Institute for Advanced Application (V.R.A., A.M.M., G.J.M.), Autism and Developmental Medicine Institute (A.M.M.), and Department of Radiology (G.J.M.), Geisinger Health System, 100 N Academy Ave, Danville, PA 17822; and Chester F. Carlson Center for Imaging Science, Rochester Institute of Technology, Rochester, NY (V.R.A., A.M.M., M.H., S.A.B.)
| | - Andrew M. Michael
- From the Institute for Advanced Application (V.R.A., A.M.M., G.J.M.), Autism and Developmental Medicine Institute (A.M.M.), and Department of Radiology (G.J.M.), Geisinger Health System, 100 N Academy Ave, Danville, PA 17822; and Chester F. Carlson Center for Imaging Science, Rochester Institute of Technology, Rochester, NY (V.R.A., A.M.M., M.H., S.A.B.)
| | - Maria Helguera
- From the Institute for Advanced Application (V.R.A., A.M.M., G.J.M.), Autism and Developmental Medicine Institute (A.M.M.), and Department of Radiology (G.J.M.), Geisinger Health System, 100 N Academy Ave, Danville, PA 17822; and Chester F. Carlson Center for Imaging Science, Rochester Institute of Technology, Rochester, NY (V.R.A., A.M.M., M.H., S.A.B.)
| | - Stefi A. Baum
- From the Institute for Advanced Application (V.R.A., A.M.M., G.J.M.), Autism and Developmental Medicine Institute (A.M.M.), and Department of Radiology (G.J.M.), Geisinger Health System, 100 N Academy Ave, Danville, PA 17822; and Chester F. Carlson Center for Imaging Science, Rochester Institute of Technology, Rochester, NY (V.R.A., A.M.M., M.H., S.A.B.)
| | - Gregory J. Moore
- From the Institute for Advanced Application (V.R.A., A.M.M., G.J.M.), Autism and Developmental Medicine Institute (A.M.M.), and Department of Radiology (G.J.M.), Geisinger Health System, 100 N Academy Ave, Danville, PA 17822; and Chester F. Carlson Center for Imaging Science, Rochester Institute of Technology, Rochester, NY (V.R.A., A.M.M., M.H., S.A.B.)
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20
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Jiang Y, Abiri R, Zhao X. Tuning Up the Old Brain with New Tricks: Attention Training via Neurofeedback. Front Aging Neurosci 2017; 9:52. [PMID: 28348527 PMCID: PMC5346575 DOI: 10.3389/fnagi.2017.00052] [Citation(s) in RCA: 32] [Impact Index Per Article: 4.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/01/2016] [Accepted: 02/22/2017] [Indexed: 12/03/2022] Open
Abstract
Neurofeedback (NF) is a form of biofeedback that uses real-time (RT) modulation of brain activity to enhance brain function and behavioral performance. Recent advances in Brain-Computer Interfaces (BCI) and cognitive training (CT) have provided new tools and evidence that NF improves cognitive functions, such as attention and working memory (WM), beyond what is provided by traditional CT. More published studies have demonstrated the efficacy of NF, particularly for treating attention deficit hyperactivity disorder (ADHD) in children. In contrast, there have been fewer studies done in older adults with or without cognitive impairment, with some notable exceptions. The focus of this review is to summarize current success in RT NF training of older brains aiming to match those of younger brains during attention/WM tasks. We also outline potential future advances in RT brainwave-based NF for improving attention training in older populations. The rapid growth in wireless recording of brain activity, machine learning classification and brain network analysis provides new tools for combating cognitive decline and brain aging in older adults. We optimistically conclude that NF, combined with new neuro-markers (event-related potentials and connectivity) and traditional features, promises to provide new hope for brain and CT in the growing older population.
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Affiliation(s)
- Yang Jiang
- Aging Brain and Cognition Laboratory, Department of Behavioral Science, College of Medicine, University of KentuckyLexington, KY, USA; Sanders-Brown Center on Aging, College of Medicine, University of KentuckyLexington, KY, USA
| | - Reza Abiri
- Department of Mechanical, Aerospace, and Biomedical Engineering, University of Tennessee Knoxville, TN, USA
| | - Xiaopeng Zhao
- Department of Mechanical, Aerospace, and Biomedical Engineering, University of TennesseeKnoxville, TN, USA; Institute for Medical Engineering and Science, Massachusetts Institute of TechnologyCambridge, MA, USA
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Meng F, Wang J, Ding F, Xie Y, Zhang Y, Zhu J. Neuroprotective effect of matrine on MPTP-induced Parkinson's disease and on Nrf2 expression. Oncol Lett 2017; 13:296-300. [PMID: 28123558 PMCID: PMC5245127 DOI: 10.3892/ol.2016.5383] [Citation(s) in RCA: 39] [Impact Index Per Article: 5.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/14/2015] [Accepted: 09/02/2016] [Indexed: 01/18/2023] Open
Abstract
The incidence rate of Parkinson's disease (PD) is ≤2% in Chinese individuals >65 years old, accounting for 40% of the global total of PD patients. The pathogenesis of PD is not yet clear, and oxidative stress-induced mitochondrial dysfunction is considered to be the main reason for the onset of PD. Studies have shown that matrine exhibits good antioxidant activity. Thus, the present study aimed to observe the protective effect and mechanism of matrine on 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP)-induced dopaminergic neuron damage. A total of 25 C57BL male mice were randomly divided into 5 groups, consisting of the control group (group A), the MPTP group (group B) and three matrine (4, 8 and 16 mg/kg) plus MPTP treatment groups (groups C, D and E, respectively). Results from a pole-climbing test and locomotor activity experiments were recorded. The mice were sacrificed 4 days later and brain dissection was performed. The levels of superoxide dismutase (SOD) and glutathione (GSH) were assessed. The expression level of tyrosine hydroxylase (TH) in the ventral midbrain was studied by immunofluorescence analysis. The expression level of nuclear factor erythroid 2-related factor 2 (Nrf2) in the ventral midbrain was studied by western blot analysis. The experiments were repeated three times. Compared with control mice, the PD mice exhibited the typical behaviors associated with PD; matrine can alleviate this phenomenon, and with increasing matrine concentration, the symptoms were reduced significantly. Compared with the control mice, the PD mice had lower SOD and GSH activity, and matrine partially reversed the change in SOD and GSH activity. Immunofluorescence analysis showed that the level of TH in the ventral midbrain decreased significantly in the PD mice, and that the mice administered matrine showed higher expression of TH and levels of TH-positive cells. Western blotting results showed that the expression of Nrf2 in the ventral midbrain decreased significantly in the PD mice, and that matrine was able to reverse this phenomenon. In conclusion, by promoting antioxidant-related Nrf2 signaling pathways in the ventral midbrain, matrine can inhibit the oxidative damage of dopamine neurons in PD.
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Affiliation(s)
- Fanhua Meng
- Department of Neurology, The First Hospital, Jilin University, Changchun, Jilin 130021, P.R. China
- Neurology Department 1, The Affiliated Hospital of Beihua University, Jilin 132011, P.R. China
| | - Jianhui Wang
- Neurology Department 1, The Affiliated Hospital of Beihua University, Jilin 132011, P.R. China
| | - Fuxiang Ding
- Cardiovascular Department 1, The Affiliated Hospital of Beihua University, Jilin 132011, P.R. China
| | - Yunliang Xie
- Neurology Department 2, The Affiliated Hospital of Beihua University, Jilin 132011, P.R. China
| | - Yingjie Zhang
- Neurology Department 2, The Affiliated Hospital of Beihua University, Jilin 132011, P.R. China
| | - Jie Zhu
- Department of Neurology, The First Hospital, Jilin University, Changchun, Jilin 130021, P.R. China
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Fogel S, Vien C, Karni A, Benali H, Carrier J, Doyon J. Sleep spindles: a physiological marker of age-related changes in gray matter in brain regions supporting motor skill memory consolidation. Neurobiol Aging 2016; 49:154-164. [PMID: 27815989 DOI: 10.1016/j.neurobiolaging.2016.10.009] [Citation(s) in RCA: 71] [Impact Index Per Article: 8.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/16/2016] [Revised: 09/08/2016] [Accepted: 10/03/2016] [Indexed: 12/21/2022]
Abstract
Sleep is necessary for the optimal consolidation of procedural learning, and in particular, for motor sequential skills. Motor sequence learning remains intact with age, but sleep-dependent consolidation is impaired, suggesting that memory deficits for procedural skills are specifically impacted by age-related changes in sleep. Age-related changes in spindles may be responsible for impaired motor sequence learning consolidation, but the morphological basis for this deficit is unknown. Here, we found that gray matter in the hippocampus and cerebellum was positively correlated with both sleep spindles and offline improvements in performance in young participants but not in older participants. These results suggest that age-related changes in gray matter in the hippocampus relate to spindles and may underlie age-related deficits in sleep-related motor sequence memory consolidation. In this way, spindles can serve as a biological marker for structural brain changes and the related memory deficits in older adults.
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Affiliation(s)
- Stuart Fogel
- Functional Neuroimaging Unit, Centre de Recherche, Institut Universitaire de Gériatrie de Montréal, Montreal, Canada; Department of Psychology, University of Montreal, Montreal, Canada; School of Psychology, University of Ottawa, Ottawa, Canada; University of Ottawa Institute of Mental Health Research, Ottawa, Canada; University of Ottawa Brain and Mind Research Institute, Ottawa, Canada
| | - Catherine Vien
- Functional Neuroimaging Unit, Centre de Recherche, Institut Universitaire de Gériatrie de Montréal, Montreal, Canada; Department of Psychology, University of Montreal, Montreal, Canada
| | - Avi Karni
- Laboratory for Human Brain & Learning, Sagol Department of Neurobiology & the E.J. Safra Brain Research Center, University of Haifa, Haifa, Israel
| | - Habib Benali
- Functional Neuroimaging Unit, Centre de Recherche, Institut Universitaire de Gériatrie de Montréal, Montreal, Canada; Functional Neuroimaging Laboratory, INSERM, Paris, France
| | - Julie Carrier
- Functional Neuroimaging Unit, Centre de Recherche, Institut Universitaire de Gériatrie de Montréal, Montreal, Canada; Department of Psychology, University of Montreal, Montreal, Canada; Centre d'études Avancées en Médecine du Sommeil, Hôpital du Sacré-Cœur de Montréal, Montreal, Canada
| | - Julien Doyon
- Functional Neuroimaging Unit, Centre de Recherche, Institut Universitaire de Gériatrie de Montréal, Montreal, Canada; Department of Psychology, University of Montreal, Montreal, Canada.
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Pirpamer L, Hofer E, Gesierich B, De Guio F, Freudenberger P, Seiler S, Duering M, Jouvent E, Duchesnay E, Dichgans M, Ropele S, Schmidt R. Determinants of iron accumulation in the normal aging brain. Neurobiol Aging 2016; 43:149-55. [DOI: 10.1016/j.neurobiolaging.2016.04.002] [Citation(s) in RCA: 52] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/18/2015] [Revised: 03/22/2016] [Accepted: 04/05/2016] [Indexed: 12/13/2022]
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Cheng Y, Leng W, Zhang J. Protective Effect of Puerarin Against Oxidative Stress Injury of Neural Cells and Related Mechanisms. Med Sci Monit 2016; 22:1244-9. [PMID: 27074962 PMCID: PMC4835157 DOI: 10.12659/msm.896058] [Citation(s) in RCA: 22] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/22/2022] Open
Abstract
Background Parkinson’s disease (PD) is manifested as degeneration of dopaminergic neurons in substantia nigra compacta. The mitochondrial dysfunction induced by oxidative stress is believed to a major cause of PD. Puerarin has been widely applied due to its estrogen nature and anti-oxidative function. This study thus investigated the protective role of puerarin against oxidative stress injury on PC12 neural cells, in addition to related mechanisms. Material/Methods PC12 cells were pre-treated with gradient concentrations of puerarin, followed by the induction of 0.5 mM H2O2. MTT assay was used to detect cell viability. Enzyme-linked immunosorbent assay (ELISA) was employed to detect intracellular level of superoxide dismutase (SOD), malondialdehyde (MDA), and glutathione (GSH). Cell apoptosis was determined by Annexin-V/7-AAD double labelling. Reactive oxidative species (ROS) and lactate dehydrogenase (LDH) activities were then measured. Cellular levels of caspase-3 and caspase-9 were also determined. Results The pre-treatment using puerarin significantly reversed H2O2-induced oxidative stress injury, as it can increase proliferation, SOD and GSH activities, decrease MDA activity, suppress apoptosis of PC12 cells, and decrease ROS and LDH production (p<0.05 in all cases). Further assays showed depressed up-regulation of caspase-3 and caspase-9 after puerarin pretreatment. Conclusions Puerarin pretreatment can decrease activity of caspase-3 and caspase-9 activity in PC12 cells, thus protecting cells from oxidative injury.
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Affiliation(s)
- Yuan Cheng
- Department of Neurology, The Affiliated Hospital to Changchun University of Chinese Medicine, Changchun, Jilin, China (mainland)
| | - Wei Leng
- Department of Neurology, The Affiliated Hospital to Changchun University of Chinese Medicine, Changchun, Jilin, China (mainland)
| | - Jingshu Zhang
- Department of Neurology, The Affiliated Hospital to Changchun University of Chinese Medicine, Changchun, Jilin, China (mainland)
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