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Gard A, Kornaropoulos EN, Portonova Wernersson M, Rorsman I, Blennow K, Zetterberg H, Tegner Y, De Maio A, Markenroth Bloch K, Björkman-Burtscher I, Pessah-Rasmussen H, Nilsson M, Marklund N. Widespread White Matter Abnormalities in Concussed Athletes Detected by 7T Diffusion Magnetic Resonance Imaging. J Neurotrauma 2024; 41:1533-1549. [PMID: 38481124 DOI: 10.1089/neu.2023.0099] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/04/2024] Open
Abstract
Sports-related concussions may cause white matter injuries and persistent post-concussive symptoms (PPCS). We hypothesized that athletes with PPCS would have neurocognitive impairments and white matter abnormalities that could be revealed by advanced neuroimaging using ultra-high field strength diffusion tensor (DTI) and diffusion kurtosis (DKI) imaging metrics and cerebrospinal fluid (CSF) biomarkers. A cohort of athletes with PPCS severity limiting the ability to work/study and participate in sport school and/or social activities for ≥6 months completed 7T magnetic resonance imaging (MRI) (morphological T1-weighed volumetry, DTI and DKI), extensive neuropsychological testing, symptom rating, and CSF biomarker sampling. Twenty-two athletes with PPCS and 22 controls were included. Concussed athletes performed below norms and significantly lower than controls on all but one of the psychometric neuropsychology tests. Supratentorial white and gray matter, as well as hippocampal volumes did not differ between concussed athletes and controls. However, of the 72 examined white matter tracts, 16% of DTI and 35% of DKI metrics (in total 28%) were significantly different between concussed athletes and controls. DKI fractional anisotropy and axial kurtosis were increased, and DKI radial diffusivity and radial kurtosis decreased in concussed athletes when compared with controls. CSF neurofilament light (NfL; an axonal injury marker), although not glial fibrillary acidic protein, correlated with several diffusion metrics. In this first 7T DTI and DKI study investigating PPCS, widespread microstructural alterations were observed in the white matter, correlating with CSF markers of axonal injury. More white matter changes were observed using DKI than using DTI. These white matter alterations may indicate persistent pathophysiological processes following concussion in sport.
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Affiliation(s)
- Anna Gard
- Department of Clinical Sciences Lund, Neurosurgery, Neurology, Lund University, Lund, Sweden
| | - Evgenios N Kornaropoulos
- Department of Clinical Sciences Lund, Diagnostic Radiology, Neurology, Lund University, Lund, Sweden
| | - Maria Portonova Wernersson
- Department of Neurology, Rehabilitation Medicine, Memory Disorders and Geriatrics, Skåne University Hospital, Neurology, Lund University, Lund, Sweden
| | - Ia Rorsman
- Department of Clinical Sciences Lund, Neurology, Lund University, Lund, Sweden
| | - Kaj Blennow
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, Sahlgrenska University Hospital, Mölndal, Sweden
| | - Henrik Zetterberg
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, Sahlgrenska University Hospital, Mölndal, Sweden
- Department of Neurodegenerative Disease, UCL Institute of Neurology, Queen Square, London, UK
- UK Dementia Research Institute at UCL, London, UK
- Hong Kong Center for Neurodegenerative Diseases, Clear Water Bay, Hong Kong, China
| | - Yelverton Tegner
- Department of Health, Education and Technology, Division of Health and Rehabilitation, Luleå University of Technology, Luleå, Sweden
| | - Alessandro De Maio
- Department of Radiological, Oncological and Pathological Sciences. Policlinico Umberto I, Sapienza University of Rome, Rome, Italy
| | - Karin Markenroth Bloch
- Department of Clinical Sciences Lund, Lund University Bioimaging Center, Lund University, Lund, Sweden
| | - Isabella Björkman-Burtscher
- Department of Radiology, Institute of Clinical Sciences, Sahlgrenska Academy, University of Gothenburg and Sahlgrenska University Hospital, Gothenburg, Sweden
| | - Hélène Pessah-Rasmussen
- Department of Neurology, Rehabilitation Medicine, Memory Disorders and Geriatrics, Skåne University Hospital, Neurology, Lund University, Lund, Sweden
- Department of Clinical Sciences Lund, Neurology, Lund University, Lund, Sweden
| | - Markus Nilsson
- Department of Clinical Sciences Lund, Diagnostic Radiology, Neurology, Lund University, Lund, Sweden
| | - Niklas Marklund
- Department of Clinical Sciences Lund, Neurosurgery, Lund University, and Skåne University Hospital, Lund, Sweden
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2
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Cichocki AC, Zinbarg RE, Craske MG, Chat IKY, Young KS, Bookheimer SY, Nusslock R. Transdiagnostic symptom of depression and anxiety associated with reduced gray matter volume in prefrontal cortex. Psychiatry Res Neuroimaging 2024; 339:111791. [PMID: 38359709 PMCID: PMC10938645 DOI: 10.1016/j.pscychresns.2024.111791] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/10/2023] [Revised: 10/25/2023] [Accepted: 02/06/2024] [Indexed: 02/17/2024]
Abstract
Dimensional models of psychopathology may provide insight into mechanisms underlying comorbid depression and anxiety and improve specificity and sensitivity of neuroanatomical findings. The present study is the first to examine neural structure alterations using the empirically derived Tri-level Model. Depression and anxiety symptoms of 269 young adults were assessed using the Tri-level Model dimensions: General Distress (transdiagnostic depression and anxiety symptoms), Anhedonia-Apprehension (relatively specific depression symptoms), and Fears (specific anxiety symptoms). Using structural MRI, gray matter volumes were extracted for emotion generation (amygdala, nucleus accumbens) and regulation (orbitofrontal, ventrolateral, and dorsolateral prefrontal cortex) regions, often implicated in depression and anxiety. Each Tri-level symptom was regressed onto each region of interest, separately, adjusting for relevant covariates. General Distress was significantly associated with smaller gray matter volumes in bilateral orbitofrontal cortex and ventrolateral prefrontal cortex, independent of Anhedonia-Apprehension and Fears symptom dimensions. These results suggests that prefrontal alterations are associated with transdiagnostic dysphoric mood common across depression and anxiety, rather than unique symptoms of these disorders. Additionally, no regions of interest were associated with Anhedonia-Apprehension or Fears, highlighting the importance of studying transdiagnostic features of depression and anxiety. This has implications for understanding mechanisms of and interventions for depression and anxiety.
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Affiliation(s)
- Anna C Cichocki
- Department of Psychology, Northwestern University, Swift Hall, 2029 Sheridan Road, Evanston IL 60208, United States.
| | - Richard E Zinbarg
- Department of Psychology, Northwestern University, Swift Hall, 2029 Sheridan Road, Evanston IL 60208, United States; The Family Institute at Northwestern University, Evanston, IL, United States
| | - Michelle G Craske
- Department of Psychology, University of California Los Angeles, Los Angeles, CA, United States
| | - Iris K-Y Chat
- Department of Psychology, Northwestern University, Swift Hall, 2029 Sheridan Road, Evanston IL 60208, United States
| | - Katherine S Young
- Department of Psychology, University of California Los Angeles, Los Angeles, CA, United States
| | - Susan Y Bookheimer
- Department of Psychology, University of California Los Angeles, Los Angeles, CA, United States
| | - Robin Nusslock
- Department of Psychology, Northwestern University, Swift Hall, 2029 Sheridan Road, Evanston IL 60208, United States
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3
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Elyounssi S, Kunitoki K, Clauss JA, Laurent E, Kane K, Hughes DE, Hopkinson CE, Bazer O, Sussman RF, Doyle AE, Lee H, Tervo-Clemmens B, Eryilmaz H, Gollub RL, Barch DM, Satterthwaite TD, Dowling KF, Roffman JL. Uncovering and mitigating bias in large, automated MRI analyses of brain development. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.02.28.530498. [PMID: 36909456 PMCID: PMC10002762 DOI: 10.1101/2023.02.28.530498] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 03/06/2023]
Abstract
Large, population-based MRI studies of adolescents promise transformational insights into neurodevelopment and mental illness risk 1,2. However, MRI studies of youth are especially susceptible to motion and other artifacts 3,4. These artifacts may go undetected by automated quality control (QC) methods that are preferred in high-throughput imaging studies, 5 and can potentially introduce non-random noise into clinical association analyses. Here we demonstrate bias in structural MRI analyses of children due to inclusion of lower quality images, as identified through rigorous visual quality control of 11,263 T1 MRI scans obtained at age 9-10 through the Adolescent Brain Cognitive Development (ABCD) Study6. Compared to the best-rated images (44.9% of the sample), lower-quality images generally associated with decreased cortical thickness and increased cortical surface area measures (Cohen's d 0.14-2.84). Variable image quality led to counterintuitive patterns in analyses that associated structural MRI and clinical measures, as inclusion of lower-quality scans altered apparent effect sizes in ways that increased risk for both false positives and negatives. Quality-related biases were partially mitigated by controlling for surface hole number, an automated index of topological complexity that differentiated lower-quality scans with good specificity at Baseline (0.81-0.93) and in 1,000 Year 2 scans (0.88-1.00). However, even among the highest-rated images, subtle topological errors occurred during image preprocessing, and their correction through manual edits significantly and reproducibly changed thickness measurements across much of the cortex (d 0.15-0.92). These findings demonstrate that inadequate QC of youth structural MRI scans can undermine advantages of large sample size to detect meaningful associations.
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Affiliation(s)
- Safia Elyounssi
- Department of Psychiatry, Massachusetts General Hospital and Harvard Medical School
- Martinos Center for Biomedical Imaging, Massachusetts General Hospital
| | - Keiko Kunitoki
- Department of Psychiatry, Massachusetts General Hospital and Harvard Medical School
- Martinos Center for Biomedical Imaging, Massachusetts General Hospital
| | - Jacqueline A. Clauss
- Department of Psychiatry, Massachusetts General Hospital and Harvard Medical School
- Martinos Center for Biomedical Imaging, Massachusetts General Hospital
| | - Eline Laurent
- Department of Psychiatry, Massachusetts General Hospital and Harvard Medical School
- Martinos Center for Biomedical Imaging, Massachusetts General Hospital
| | - Kristina Kane
- Department of Psychiatry, Massachusetts General Hospital and Harvard Medical School
- Martinos Center for Biomedical Imaging, Massachusetts General Hospital
| | - Dylan E. Hughes
- Department of Psychiatry, Massachusetts General Hospital and Harvard Medical School
- Martinos Center for Biomedical Imaging, Massachusetts General Hospital
- Departments of Psychiatry & Biobehavioral Sciences, University of California, Los Angeles
| | - Casey E. Hopkinson
- Department of Psychiatry, Massachusetts General Hospital and Harvard Medical School
- Martinos Center for Biomedical Imaging, Massachusetts General Hospital
| | - Oren Bazer
- Department of Psychiatry, Massachusetts General Hospital and Harvard Medical School
- Martinos Center for Biomedical Imaging, Massachusetts General Hospital
| | - Rachel Freed Sussman
- Department of Psychiatry, Massachusetts General Hospital and Harvard Medical School
- Martinos Center for Biomedical Imaging, Massachusetts General Hospital
| | - Alysa E. Doyle
- Department of Psychiatry, Massachusetts General Hospital and Harvard Medical School
- Center for Genomic Medicine, Massachusetts General Hospital
| | - Hang Lee
- Biostatistics Center, Massachusetts General Hospital and Harvard Medical School
| | | | - Hamdi Eryilmaz
- Department of Psychiatry, Massachusetts General Hospital and Harvard Medical School
- Martinos Center for Biomedical Imaging, Massachusetts General Hospital
| | - Randy L. Gollub
- Department of Psychiatry, Massachusetts General Hospital and Harvard Medical School
- Martinos Center for Biomedical Imaging, Massachusetts General Hospital
| | - Deanna M. Barch
- Department of Psychological and Brain Sciences, Washington University in St. Louis
| | - Theodore D. Satterthwaite
- Department of Psychiatry, University of Pennsylvania Perelman School of Medicine
- Penn Lifespan and Neuroimaging Center, University of Pennsylvania Perelman School of Medicine
- Penn-CHOP Lifespan Brain Institute
| | - Kevin F. Dowling
- Department of Psychiatry, Massachusetts General Hospital and Harvard Medical School
- Department of Psychiatry, University of Pittsburgh
| | - Joshua L. Roffman
- Department of Psychiatry, Massachusetts General Hospital and Harvard Medical School
- Martinos Center for Biomedical Imaging, Massachusetts General Hospital
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4
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Rane RP, de Man EF, Kim J, Görgen K, Tschorn M, Rapp MA, Banaschewski T, Bokde ALW, Desrivieres S, Flor H, Grigis A, Garavan H, Gowland PA, Brühl R, Martinot JL, Martinot MLP, Artiges E, Nees F, Papadopoulos Orfanos D, Lemaitre H, Paus T, Poustka L, Fröhner J, Robinson L, Smolka MN, Winterer J, Whelan R, Schumann G, Walter H, Heinz A, Ritter K. Structural differences in adolescent brains can predict alcohol misuse. eLife 2022; 11:e77545. [PMID: 35616520 PMCID: PMC9255959 DOI: 10.7554/elife.77545] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/02/2022] [Accepted: 05/25/2022] [Indexed: 12/02/2022] Open
Abstract
Alcohol misuse during adolescence (AAM) has been associated with disruptive development of adolescent brains. In this longitudinal machine learning (ML) study, we could predict AAM significantly from brain structure (T1-weighted imaging and DTI) with accuracies of 73 -78% in the IMAGEN dataset (n∼1182). Our results not only show that structural differences in brain can predict AAM, but also suggests that such differences might precede AAM behavior in the data. We predicted 10 phenotypes of AAM at age 22 using brain MRI features at ages 14, 19, and 22. Binge drinking was found to be the most predictable phenotype. The most informative brain features were located in the ventricular CSF, and in white matter tracts of the corpus callosum, internal capsule, and brain stem. In the cortex, they were spread across the occipital, frontal, and temporal lobes and in the cingulate cortex. We also experimented with four different ML models and several confound control techniques. Support Vector Machine (SVM) with rbf kernel and Gradient Boosting consistently performed better than the linear models, linear SVM and Logistic Regression. Our study also demonstrates how the choice of the predicted phenotype, ML model, and confound correction technique are all crucial decisions in an explorative ML study analyzing psychiatric disorders with small effect sizes such as AAM.
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Affiliation(s)
- Roshan Prakash Rane
- Charité – Universitätsmedizin Berlin (corporate member of Freie Universiät at Berlin, Humboldt-Universiät at zu Berlin, and Berlin Institute of Health), Department of Psychiatry and Psychotherapy, Bernstein Center for Computational NeuroscienceBerlinGermany
| | - Evert Ferdinand de Man
- Faculty IV – Electrical Engineering and Computer Science, Technische Universität BerlinBerlinGermany
| | - JiHoon Kim
- Department of Education and Psychology, Freie Universität BerlinBerlinGermany
| | - Kai Görgen
- Charité – Universitätsmedizin Berlin (corporate member of Freie Universiät at Berlin, Humboldt-Universiät at zu Berlin, and Berlin Institute of Health), Department of Psychiatry and Psychotherapy, Bernstein Center for Computational NeuroscienceBerlinGermany
- Science of Intelligence, Research Cluster of ExcellenceBerlinGermany
| | - Mira Tschorn
- Social and Preventive Medicine, Department of Sports and Health Sciences, Intra-faculty unit “Cognitive Sciences”, Faculty of Human Science, and Faculty of Health Sciences Brandenburg, Research Area Services Research and e-Health, University of PotsdamPotsdamGermany
| | - Michael A Rapp
- Social and Preventive Medicine, Department of Sports and Health Sciences, Intra-faculty unit “Cognitive Sciences”, Faculty of Human Science, and Faculty of Health Sciences Brandenburg, Research Area Services Research and e-Health, University of PotsdamPotsdamGermany
| | - Tobias Banaschewski
- Department of Child and Adolescent Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg UniversityMannheimGermany
| | - Arun LW Bokde
- Discipline of Psychiatry, School of Medicine and Trinity College Institute of Neuroscience, Trinity College DublinDublinIreland
| | - Sylvane Desrivieres
- Centre for Population Neuroscience and Precision Medicine (PONS), Institute of Psychiatry, Psychology Neuroscience SGDP Centre, King’s College LondonLondonUnited Kingdom
| | - Herta Flor
- Institute of Cognitive and Clinical Neuroscience, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg UniversityHeidelbergGermany
- Department of Psychology, School of Social Sciences, University of MannheimMannheimGermany
| | | | - Hugh Garavan
- Departments of Psychiatry and Psychology, University of VermontBurlingtonUnited States
| | - Penny A Gowland
- Sir Peter Mansfield Imaging Centre School of Physics and Astronomy, University of NottinghamNottinghamUnited Kingdom
| | | | - Jean-Luc Martinot
- Institut National de la Santé et de la Recherche Médicale, INSERM U A10 ”Trajectoires développementales en psychiatrie” Universite Paris-Saclay, Ecole Normale Supérieure Paris-Saclay, CNRS, Centre BorelliGif-sur-YvetteFrance
| | - Marie-Laure Paillere Martinot
- Institut National de la Santé et de la Recherche Médicale, INSERM U A10 ”Trajectoires développementales en psychiatrie” Universite Paris-Saclay, Ecole Normale Supérieure Paris-Saclay, CNRS, Centre BorelliGif-sur-YvetteFrance
- AP-HP Sorbonne Université, Department of Child and Adolescent Psychiatry, Pitié-Salpêtrière HospitalParisFrance
| | - Eric Artiges
- Institut National de la Santé et de la Recherche Médicale, INSERM U A10 ”Trajectoires développementales en psychiatrie” Universite Paris-Saclay, Ecole Normale Supérieure Paris-Saclay, CNRS, Centre BorelliGif-sur-YvetteFrance
- Psychiatry Department, EPS Barthélémy DurandEtampesFrance
| | - Frauke Nees
- Department of Child and Adolescent Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg UniversityMannheimGermany
- Institute of Cognitive and Clinical Neuroscience, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg UniversityHeidelbergGermany
- PONS Research Group, Dept of Psychiatry and Psychotherapy, Campus Charite Mitte, Humboldt UniversityBerlinGermany
| | | | - Herve Lemaitre
- NeuroSpin, CEA, Université Paris-SaclayParisFrance
- Institut des Maladies Neurodégénératives, UMR 5293, CNRS, CEA, University of BordeauxBordeauxFrance
| | - Tomas Paus
- Department of Psychiatry, Faculty of Medicine and Centre Hospitalier Universitaire Sainte-Justine, University of MontrealMontrealCanada
- Departments of Psychiatry and Psychology, University of TorontoTorontoCanada
| | - Luise Poustka
- Department of Child and Adolescent Psychiatry and Psychotherapy, University Medical Centre GöttingenGöttingenGermany
| | - Juliane Fröhner
- Department of Psychiatry and Neuroimaging Center, Technische Universität DresdenDresdenGermany
| | - Lauren Robinson
- Department of Psychological Medicine, Section for Eating Disorders, Institute of Psychiatry, Psychology and Neuroscience, King’s College LondonLondonUnited Kingdom
| | - Michael N Smolka
- Department of Psychiatry and Neuroimaging Center, Technische Universität DresdenDresdenGermany
| | - Jeanne Winterer
- Charité – Universitätsmedizin Berlin (corporate member of Freie Universiät at Berlin, Humboldt-Universiät at zu Berlin, and Berlin Institute of Health), Department of Psychiatry and Psychotherapy, Bernstein Center for Computational NeuroscienceBerlinGermany
- Department of Education and Psychology, Freie Universität BerlinBerlinGermany
| | - Robert Whelan
- School of Psychology and Global Brain Health Institute, Trinity College DublinDublinIreland
| | - Gunter Schumann
- PONS Research Group, Dept of Psychiatry and Psychotherapy, Campus Charite Mitte, Humboldt UniversityBerlinGermany
| | - Henrik Walter
- Charité – Universitätsmedizin Berlin (corporate member of Freie Universiät at Berlin, Humboldt-Universiät at zu Berlin, and Berlin Institute of Health), Department of Psychiatry and Psychotherapy, Bernstein Center for Computational NeuroscienceBerlinGermany
| | - Andreas Heinz
- Charité – Universitätsmedizin Berlin (corporate member of Freie Universiät at Berlin, Humboldt-Universiät at zu Berlin, and Berlin Institute of Health), Department of Psychiatry and Psychotherapy, Bernstein Center for Computational NeuroscienceBerlinGermany
| | - Kerstin Ritter
- Charité – Universitätsmedizin Berlin (corporate member of Freie Universiät at Berlin, Humboldt-Universiät at zu Berlin, and Berlin Institute of Health), Department of Psychiatry and Psychotherapy, Bernstein Center for Computational NeuroscienceBerlinGermany
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5
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Pulli EP, Silver E, Kumpulainen V, Copeland A, Merisaari H, Saunavaara J, Parkkola R, Lähdesmäki T, Saukko E, Nolvi S, Kataja EL, Korja R, Karlsson L, Karlsson H, Tuulari JJ. Feasibility of FreeSurfer Processing for T1-Weighted Brain Images of 5-Year-Olds: Semiautomated Protocol of FinnBrain Neuroimaging Lab. Front Neurosci 2022; 16:874062. [PMID: 35585923 PMCID: PMC9108497 DOI: 10.3389/fnins.2022.874062] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/11/2022] [Accepted: 04/12/2022] [Indexed: 02/03/2023] Open
Abstract
Pediatric neuroimaging is a quickly developing field that still faces important methodological challenges. Pediatric images usually have more motion artifact than adult images. The artifact can cause visible errors in brain segmentation, and one way to address it is to manually edit the segmented images. Variability in editing and quality control protocols may complicate comparisons between studies. In this article, we describe in detail the semiautomated segmentation and quality control protocol of structural brain images that was used in FinnBrain Birth Cohort Study and relies on the well-established FreeSurfer v6.0 and ENIGMA (Enhancing Neuro Imaging Genetics through Meta Analysis) consortium tools. The participants were typically developing 5-year-olds [n = 134, 5.34 (SD 0.06) years, 62 girls]. Following a dichotomous quality rating scale for inclusion and exclusion of images, we explored the quality on a region of interest level to exclude all regions with major segmentation errors. The effects of manual edits on cortical thickness values were relatively minor: less than 2% in all regions. Supplementary Material cover registration and additional edit options in FreeSurfer and comparison to the computational anatomy toolbox (CAT12). Overall, we conclude that despite minor imperfections FreeSurfer can be reliably used to segment cortical metrics from T1-weighted images of 5-year-old children with appropriate quality assessment in place. However, custom templates may be needed to optimize the results for the subcortical areas. Through visual assessment on a level of individual regions of interest, our semiautomated segmentation protocol is hopefully helpful for investigators working with similar data sets, and for ensuring high quality pediatric neuroimaging data.
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Affiliation(s)
- Elmo P. Pulli
- Turku Brain and Mind Center, Department of Clinical Medicine, University of Turku, Turku, Finland
- Department of Psychiatry, Turku University Hospital, University of Turku, Turku, Finland
- *Correspondence: Elmo P. Pulli, ; orcid.org/0000-0003-3871-8563
| | - Eero Silver
- Turku Brain and Mind Center, Department of Clinical Medicine, University of Turku, Turku, Finland
- Department of Psychiatry, Turku University Hospital, University of Turku, Turku, Finland
| | - Venla Kumpulainen
- Turku Brain and Mind Center, Department of Clinical Medicine, University of Turku, Turku, Finland
- Department of Psychiatry, Turku University Hospital, University of Turku, Turku, Finland
| | - Anni Copeland
- Turku Brain and Mind Center, Department of Clinical Medicine, University of Turku, Turku, Finland
| | - Harri Merisaari
- Turku Brain and Mind Center, Department of Clinical Medicine, University of Turku, Turku, Finland
- Department of Radiology, University of Turku, Turku, Finland
| | - Jani Saunavaara
- Department of Medical Physics, Turku University Hospital, Turku, Finland
| | - Riitta Parkkola
- Department of Radiology, University of Turku, Turku, Finland
- Department of Radiology, Turku University Hospital, Turku, Finland
| | - Tuire Lähdesmäki
- Department of Pediatrics and Adolescent Medicine, Turku University Hospital, University of Turku, Turku, Finland
| | - Ekaterina Saukko
- Department of Radiology, Turku University Hospital, Turku, Finland
| | - Saara Nolvi
- Turku Brain and Mind Center, Department of Clinical Medicine, University of Turku, Turku, Finland
- Turku Institute for Advanced Studies, University of Turku, Turku, Finland
- Department of Psychology, University of Turku, Turku, Finland
| | - Eeva-Leena Kataja
- Turku Brain and Mind Center, Department of Clinical Medicine, University of Turku, Turku, Finland
| | - Riikka Korja
- Turku Brain and Mind Center, Department of Clinical Medicine, University of Turku, Turku, Finland
- Department of Psychology, University of Turku, Turku, Finland
| | - Linnea Karlsson
- Turku Brain and Mind Center, Department of Clinical Medicine, University of Turku, Turku, Finland
- Department of Psychiatry, Turku University Hospital, University of Turku, Turku, Finland
- Centre for Population Health Research, Turku University Hospital, University of Turku, Turku, Finland
| | - Hasse Karlsson
- Turku Brain and Mind Center, Department of Clinical Medicine, University of Turku, Turku, Finland
- Department of Psychiatry, Turku University Hospital, University of Turku, Turku, Finland
- Centre for Population Health Research, Turku University Hospital, University of Turku, Turku, Finland
| | - Jetro J. Tuulari
- Turku Brain and Mind Center, Department of Clinical Medicine, University of Turku, Turku, Finland
- Department of Psychiatry, Turku University Hospital, University of Turku, Turku, Finland
- Turku Collegium for Science, Medicine and Technology, University of Turku, Turku, Finland
- Department of Psychiatry, University of Oxford, Oxford, United Kingdom
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6
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Gard A, Al-Husseini A, Kornaropoulos EN, De Maio A, Tegner Y, Björkman-Burtscher I, Markenroth Bloch K, Nilsson M, Magnusson M, Marklund N. Post-Concussive Vestibular Dysfunction Is Related to Injury to the Inferior Vestibular Nerve. J Neurotrauma 2022; 39:829-840. [PMID: 35171721 PMCID: PMC9225415 DOI: 10.1089/neu.2021.0447] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022] Open
Abstract
Symptoms of vestibular dysfunction such as dizziness and vertigo are common after sports-related concussions (SRC) and associated with a worse outcome and a prolonged recovery. Vestibular dysfunction after SRC can be because of an impairment of the peripheral or central neural parts of the vestibular system. The aim of the present study was to establish the cause of vestibular impairment in athletes with SRC who have persisting post-concussive symptoms (PPCS). We recruited 42 participants-21 athletes with previous SRCs and PPCS ≥6 months and 21 healthy athletic age- and sex-matched controls-who underwent symptom rating, a detailed test battery of vestibular function and 7T magnetic resonance imaging with diffusion tensor imaging (DTI) and diffusion kurtosis imaging (DKI) of cerebellar white matter tracts, and T1-weighted imaging for cerebellar volumetrics. Vestibular dysfunction was observed in 13 SRC athletes and three controls (p = 0.001). Athletes with vestibular dysfunction reported more pronounced symptoms on the Dizziness Handicap Inventory (DHI; p < 0.001) and the Hospital Anxiety and Depression Scale (HADS; p < 0.001). No significant differences in DTI metrics were found, while in DKI two metrics were observed in the superior and/or inferior cerebellar tracts. Cerebellar gray and white matter volumes were similar in athletes with SRC and controls. Compared with controls, pathological video head impulse test results (vHIT; p < 0.001) and cervical vestibular evoked myogenic potentials (cVEMP; p = 0.002) were observed in athletes with SRC, indicating peripheral vestibular dysfunction and specifically suggesting injury to the inferior vestibular nerve. In athletes with persisting symptoms after SRC, vestibular dysfunction is associated with injury to the inferior vestibular nerve.
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Affiliation(s)
- Anna Gard
- Department of Clinical Sciences Lund, Lund University, Neurosurgery, Skåne University Hospital, Lund, Sweden
| | - Ali Al-Husseini
- Department of Clinical Sciences Lund, Lund University, Neurosurgery, Skåne University Hospital, Lund, Sweden
| | - Evgenios N. Kornaropoulos
- Department of Clinical Sciences Lund, Diagnostic Radiology, Lund University, Skåne University Hospital, Lund, Sweden
| | - Alessandro De Maio
- Department of Radiological, Oncological and Pathological Sciences. Policlinico Umberto I, Sapienza University of Rome, Rome, Italy
| | - Yelverton Tegner
- Department of Health Sciences, Luleå University of Technology, Luleå, Sweden
| | - Isabella Björkman-Burtscher
- Department of Radiology, Institute of Clinical Sciences, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden
| | | | - Markus Nilsson
- Department of Clinical Sciences Lund, Diagnostic Radiology, Lund University, Skåne University Hospital, Lund, Sweden
| | - Måns Magnusson
- Department of Clinical Sciences Lund, Otorhinolaryngology, Lund University, Skåne University Hospital, Lund, Sweden
| | - Niklas Marklund
- Department of Clinical Sciences Lund, Lund University, Neurosurgery, Skåne University Hospital, Lund, Sweden
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7
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Eder-Moreau E, Zhu X, Fisch CT, Bergman M, Neria Y, Helpman L. Neurobiological Alterations in Females With PTSD: A Systematic Review. Front Psychiatry 2022; 13:862476. [PMID: 35770056 PMCID: PMC9234306 DOI: 10.3389/fpsyt.2022.862476] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/26/2022] [Accepted: 04/20/2022] [Indexed: 11/13/2022] Open
Abstract
Most females experience at least one traumatic event in their lives, but not all develop PTSD. Despite considerable research, our understanding of the key factors that constitute risk for PTSD among females is limited. Previous research has largely focused on sex differences, neglecting within group comparisons, thereby obviating differences between females who do and do not develop PTSD following exposure to trauma. In this systematic review, we conducted a search for the extent of existing research utilizing magnetic resonance imaging (MRI) to examine neurobiological differences among females of all ages, with and without PTSD. Only studies of females who met full diagnostic criteria for PTSD were included. Fifty-six studies were selected and reviewed. We synthesized here findings from structural MRI (sMRI), functional MRI (fMRI), diffusion tensor imaging (DTI), and resting state functional connectivity (rs-FC MRI) studies, comparing females with and without PTSD. A range of biopsychosocial constructs that may leave females vulnerable to PTSD were discussed. First, the ways timing and type of exposure to trauma may impact PTSD risk were discussed. Second, the key role that cognitive and behavioral mechanisms may play in PTSD was described, including rumination, and deficient fear extinction. Third, the role of specific symptom patterns and common comorbidities in female-specific PTSD was described, as well as sex-specific implications on treatment and parenting outcomes. We concluded by identifying areas for future research, to address the need to better understand developmental aspects of brain alterations, the differential impact of trauma types and timing, the putative role of neuroendocrine system in neurobiology of PTSD among females, and the impact of social and cultural factors on neurobiology in females with PTSD.
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Affiliation(s)
- Elizabeth Eder-Moreau
- New York State Psychiatric Institute, Columbia University Irving Medical Center, New York, NY, United States
| | - Xi Zhu
- New York State Psychiatric Institute, Columbia University Irving Medical Center, New York, NY, United States.,Department of Psychiatry, Columbia University Irving Medical Center, New York, NY, United States
| | - Chana T Fisch
- New York State Psychiatric Institute, Columbia University Irving Medical Center, New York, NY, United States
| | - Maja Bergman
- New York State Psychiatric Institute, Columbia University Irving Medical Center, New York, NY, United States
| | - Yuval Neria
- New York State Psychiatric Institute, Columbia University Irving Medical Center, New York, NY, United States.,Department of Psychiatry, Columbia University Irving Medical Center, New York, NY, United States
| | - Liat Helpman
- Department of Counseling and Human Development, Faculty of Education, University of Haifa, Haifa, Israel.,Psychiatric Research Unit, Tel Aviv Medical Center, Tel Aviv, Israel
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