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Bridgen P, Tomi-Tricot R, Uus A, Cromb D, Quirke M, Almalbis J, Bonse B, De la Fuente Botella M, Maggioni A, Cio PD, Cawley P, Casella C, Dokumaci AS, Thomson AR, Willers Moore J, Bridglal D, Saravia J, Finck T, Price AN, Pickles E, Cordero-Grande L, Egloff A, O’Muircheartaigh J, Counsell SJ, Giles SL, Deprez M, De Vita E, Rutherford MA, Edwards AD, Hajnal JV, Malik SJ, Arichi T. High resolution and contrast 7 tesla MR brain imaging of the neonate. Front Radiol 2024; 3:1327075. [PMID: 38304343 PMCID: PMC10830693 DOI: 10.3389/fradi.2023.1327075] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 10/24/2023] [Accepted: 12/29/2023] [Indexed: 02/03/2024]
Abstract
Introduction Ultra-high field MR imaging offers marked gains in signal-to-noise ratio, spatial resolution, and contrast which translate to improved pathological and anatomical sensitivity. These benefits are particularly relevant for the neonatal brain which is rapidly developing and sensitive to injury. However, experience of imaging neonates at 7T has been limited due to regulatory, safety, and practical considerations. We aimed to establish a program for safely acquiring high resolution and contrast brain images from neonates on a 7T system. Methods Images were acquired from 35 neonates on 44 occasions (median age 39 + 6 postmenstrual weeks, range 33 + 4 to 52 + 6; median body weight 2.93 kg, range 1.57 to 5.3 kg) over a median time of 49 mins 30 s. Peripheral body temperature and physiological measures were recorded throughout scanning. Acquired sequences included T2 weighted (TSE), Actual Flip angle Imaging (AFI), functional MRI (BOLD EPI), susceptibility weighted imaging (SWI), and MR spectroscopy (STEAM). Results There was no significant difference between temperature before and after scanning (p = 0.76) and image quality assessment compared favorably to state-of-the-art 3T acquisitions. Anatomical imaging demonstrated excellent sensitivity to structures which are typically hard to visualize at lower field strengths including the hippocampus, cerebellum, and vasculature. Images were also acquired with contrast mechanisms which are enhanced at ultra-high field including susceptibility weighted imaging, functional MRI, and MR spectroscopy. Discussion We demonstrate safety and feasibility of imaging vulnerable neonates at ultra-high field and highlight the untapped potential for providing important new insights into brain development and pathological processes during this critical phase of early life.
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Affiliation(s)
- Philippa Bridgen
- LondonCollaborative Ultra High Field System (LoCUS), King’s College London, London, United Kingdom
- Guys and St Thomas’ NHS Foundation Trust, London, United Kingdom
| | - Raphael Tomi-Tricot
- LondonCollaborative Ultra High Field System (LoCUS), King’s College London, London, United Kingdom
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King’s College London, London, United Kingdom
- Biomedical Engineering Department, School of Biomedical Engineering and Imaging Sciences, King’s College London, London, United Kingdom
- MR Research Collaborations, Siemens Healthcare Limited, London, United Kingdom
| | - Alena Uus
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King’s College London, London, United Kingdom
- Biomedical Engineering Department, School of Biomedical Engineering and Imaging Sciences, King’s College London, London, United Kingdom
| | - Daniel Cromb
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King’s College London, London, United Kingdom
| | - Megan Quirke
- Guys and St Thomas’ NHS Foundation Trust, London, United Kingdom
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King’s College London, London, United Kingdom
| | - Jennifer Almalbis
- Guys and St Thomas’ NHS Foundation Trust, London, United Kingdom
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King’s College London, London, United Kingdom
| | - Beya Bonse
- Guys and St Thomas’ NHS Foundation Trust, London, United Kingdom
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King’s College London, London, United Kingdom
| | - Miguel De la Fuente Botella
- Guys and St Thomas’ NHS Foundation Trust, London, United Kingdom
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King’s College London, London, United Kingdom
| | - Alessandra Maggioni
- Guys and St Thomas’ NHS Foundation Trust, London, United Kingdom
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King’s College London, London, United Kingdom
| | - Pierluigi Di Cio
- LondonCollaborative Ultra High Field System (LoCUS), King’s College London, London, United Kingdom
- Guys and St Thomas’ NHS Foundation Trust, London, United Kingdom
| | - Paul Cawley
- Guys and St Thomas’ NHS Foundation Trust, London, United Kingdom
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King’s College London, London, United Kingdom
| | - Chiara Casella
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King’s College London, London, United Kingdom
| | - Ayse Sila Dokumaci
- Biomedical Engineering Department, School of Biomedical Engineering and Imaging Sciences, King’s College London, London, United Kingdom
| | - Alice R. Thomson
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King’s College London, London, United Kingdom
- MRC Centre for Neurodevelopmental Disorders, King’s College London, London, United Kingdom
| | - Jucha Willers Moore
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King’s College London, London, United Kingdom
- MRC Centre for Neurodevelopmental Disorders, King’s College London, London, United Kingdom
| | - Devi Bridglal
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King’s College London, London, United Kingdom
| | - Joao Saravia
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King’s College London, London, United Kingdom
| | - Thomas Finck
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King’s College London, London, United Kingdom
| | - Anthony N. Price
- Guys and St Thomas’ NHS Foundation Trust, London, United Kingdom
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King’s College London, London, United Kingdom
| | - Elisabeth Pickles
- LondonCollaborative Ultra High Field System (LoCUS), King’s College London, London, United Kingdom
- Guys and St Thomas’ NHS Foundation Trust, London, United Kingdom
- Biomedical Engineering Department, School of Biomedical Engineering and Imaging Sciences, King’s College London, London, United Kingdom
| | - Lucilio Cordero-Grande
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King’s College London, London, United Kingdom
- Biomedical Engineering Department, School of Biomedical Engineering and Imaging Sciences, King’s College London, London, United Kingdom
- Biomedical Image Technologies, ETSI Telecomunicación, Universidad Politécnica de Madrid and CIBER-BBN, ISCIII, Madrid, Spain
| | - Alexia Egloff
- Guys and St Thomas’ NHS Foundation Trust, London, United Kingdom
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King’s College London, London, United Kingdom
| | - Jonathan O’Muircheartaigh
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King’s College London, London, United Kingdom
- MRC Centre for Neurodevelopmental Disorders, King’s College London, London, United Kingdom
- Department of Forensic and Neurodevelopmental Sciences, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London, United Kingdom
| | - Serena J. Counsell
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King’s College London, London, United Kingdom
| | - Sharon L. Giles
- LondonCollaborative Ultra High Field System (LoCUS), King’s College London, London, United Kingdom
- Guys and St Thomas’ NHS Foundation Trust, London, United Kingdom
- Biomedical Engineering Department, School of Biomedical Engineering and Imaging Sciences, King’s College London, London, United Kingdom
| | - Maria Deprez
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King’s College London, London, United Kingdom
- Biomedical Engineering Department, School of Biomedical Engineering and Imaging Sciences, King’s College London, London, United Kingdom
| | - Enrico De Vita
- LondonCollaborative Ultra High Field System (LoCUS), King’s College London, London, United Kingdom
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King’s College London, London, United Kingdom
- Biomedical Engineering Department, School of Biomedical Engineering and Imaging Sciences, King’s College London, London, United Kingdom
- MR Physics, Radiology Department, Great Ormond Street Hospital for Children, London, United Kingdom
| | - Mary A. Rutherford
- Guys and St Thomas’ NHS Foundation Trust, London, United Kingdom
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King’s College London, London, United Kingdom
- MRC Centre for Neurodevelopmental Disorders, King’s College London, London, United Kingdom
| | - A. David Edwards
- Guys and St Thomas’ NHS Foundation Trust, London, United Kingdom
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King’s College London, London, United Kingdom
- MRC Centre for Neurodevelopmental Disorders, King’s College London, London, United Kingdom
| | - Joseph V. Hajnal
- LondonCollaborative Ultra High Field System (LoCUS), King’s College London, London, United Kingdom
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King’s College London, London, United Kingdom
- Biomedical Engineering Department, School of Biomedical Engineering and Imaging Sciences, King’s College London, London, United Kingdom
| | - Shaihan J. Malik
- LondonCollaborative Ultra High Field System (LoCUS), King’s College London, London, United Kingdom
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King’s College London, London, United Kingdom
- Biomedical Engineering Department, School of Biomedical Engineering and Imaging Sciences, King’s College London, London, United Kingdom
| | - Tomoki Arichi
- Guys and St Thomas’ NHS Foundation Trust, London, United Kingdom
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King’s College London, London, United Kingdom
- MRC Centre for Neurodevelopmental Disorders, King’s College London, London, United Kingdom
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Cawley P, Padormo F, Cromb D, Almalbis J, Marenzana M, Teixeira R, Uus A, O’Muircheartaigh J, Williams SC, Counsell SJ, Arichi T, Rutherford MA, Hajnal JV, Edwards AD. Development of neonatal-specific sequences for portable ultralow field magnetic resonance brain imaging: a prospective, single-centre, cohort study. EClinicalMedicine 2023; 65:102253. [PMID: 38106560 PMCID: PMC10725077 DOI: 10.1016/j.eclinm.2023.102253] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/26/2023] [Revised: 09/14/2023] [Accepted: 09/15/2023] [Indexed: 12/19/2023] Open
Abstract
Background Magnetic Resonance (MR) imaging is key for investigation of suspected newborn brain abnormalities. Access is limited in low-resource settings and challenging in infants needing intensive care. Portable ultralow field (ULF) MRI is showing promise in bedside adult brain imaging. Use in infants and children has been limited as brain-tissue composition differences necessitate sequence modification. The aim of this study was to develop neonatal-specific ULF structural sequences and test these across a range of gestational maturities and pathologies to inform future validation studies. Methods Prospective cohort study within a UK neonatal specialist referral centre. Infants undergoing 3T MRI were recruited for paired ULF (64mT) portable MRI by convenience sampling from the neonatal unit and post-natal ward. Key inclusion criteria: 1) Infants with risk or suspicion of brain abnormality, or 2) preterm and term infants without suspicion of major genetic, chromosomal or neurological abnormality. Exclusions: presence of contra-indication for MR scanning. ULF sequence parameters were optimised for neonatal brain-tissues by iterative and explorative design. Neuroanatomic and pathologic features were compared by unblinded review, informing optimisation of subsequent sequence generations in a step-wise manner. Main outcome: visual identification of healthy and abnormal brain tissues/structures. ULF MR spectroscopy, diffusion, susceptibility weighted imaging, arteriography, and venography require pre-clinical technical development and have not been tested. Findings Between September 23, 2021 and October 25, 2022, 102 paired scans were acquired in 87 infants; 1.17 paired scans per infant. Median age 9 days, median postmenstrual age 40+2 weeks (range: 31+3-53+4). Infants had a range of intensive care requirements. No adverse events observed. Optimised ULF sequences can visualise key neuroanatomy and brain abnormalities. In finalised neonatal sequences: T2w imaging distinguished grey and white matter (7/7 infants), ventricles (7/7), pituitary tissue (5/7), corpus callosum (7/7) and optic nerves (7/7). Signal congruence was seen within the posterior limb of the internal capsule in 10/11 infants on finalised T1w scans. In addition, brain abnormalities visualised on ULF optimised sequences have similar MR signal patterns to 3T imaging, including injury secondary to infarction (6/6 infants on T2w scans), hypoxia-ischaemia (abnormal signal in basal ganglia, thalami and white matter 2/2 infants on T2w scans, cortical highlighting 1/1 infant on T1w scan), and congenital malformations: polymicrogyria 3/3, absent corpus callosum 2/2, and vermian hypoplasia 3/3 infants on T2w scans. Sequences are susceptible to motion corruption, noise, and ULF artefact. Non-identified pathologies were small or subtle. Interpretation On unblinded review, optimised portable MR can provide sufficient contrast, signal, and resolution for neuroanatomical identification and detection of a range of clinically important abnormalities. Blinded validation studies are now warranted. Funding The Bill and Melinda Gates Foundation, the MRC, the Wellcome/EPSRC Centre for Medical Engineering, the MRC Centre for Neurodevelopmental Disorders, and the National Institute for Health Research (NIHR) Biomedical Research Centres based at Guy's and St Thomas' and South London & Maudsley NHS Foundation Trusts and King's College London.
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Affiliation(s)
- Paul Cawley
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King’s College London, London SE1 7EH, UK
- Neonatal Intensive Care Unit, Evelina Children’s Hospital London, St Thomas’ Hospital, 6th Floor North Wing, Westminster Bridge Road, London SE1 7EH, UK
- MRC Centre for Neurodevelopmental Disorders, King’s College London, London SE1 1UL, UK
| | - Francesco Padormo
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King’s College London, London SE1 7EH, UK
- Medical Physics, Guy’s & St. Thomas' NHS Foundation Trust, London, UK
- Hyperfine, Inc., 351 New Whitfield St., Guilford, Connecticut 06437, USA
| | - Daniel Cromb
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King’s College London, London SE1 7EH, UK
- Neonatal Intensive Care Unit, Evelina Children’s Hospital London, St Thomas’ Hospital, 6th Floor North Wing, Westminster Bridge Road, London SE1 7EH, UK
| | - Jennifer Almalbis
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King’s College London, London SE1 7EH, UK
- Neonatal Intensive Care Unit, Evelina Children’s Hospital London, St Thomas’ Hospital, 6th Floor North Wing, Westminster Bridge Road, London SE1 7EH, UK
| | - Massimo Marenzana
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King’s College London, London SE1 7EH, UK
| | - Rui Teixeira
- Hyperfine, Inc., 351 New Whitfield St., Guilford, Connecticut 06437, USA
| | - Alena Uus
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King’s College London, London SE1 7EH, UK
| | - Jonathan O’Muircheartaigh
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King’s College London, London SE1 7EH, UK
- MRC Centre for Neurodevelopmental Disorders, King’s College London, London SE1 1UL, UK
- Department of Forensic and Neurodevelopmental Science, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London, UK
| | - Steven C.R. Williams
- Centre for Neuroimaging Sciences, King’s College London, De Crespigny Park, London SE5 8AF, UK
| | - Serena J. Counsell
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King’s College London, London SE1 7EH, UK
| | - Tomoki Arichi
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King’s College London, London SE1 7EH, UK
- MRC Centre for Neurodevelopmental Disorders, King’s College London, London SE1 1UL, UK
- Paediatric Neurosciences, Evelina London Children’s Hospital, Guy’s and St Thomas’ NHS Foundation Trust, London SE1 7EH, UK
| | - Mary A. Rutherford
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King’s College London, London SE1 7EH, UK
- MRC Centre for Neurodevelopmental Disorders, King’s College London, London SE1 1UL, UK
| | - Joseph V. Hajnal
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King’s College London, London SE1 7EH, UK
| | - A. David Edwards
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King’s College London, London SE1 7EH, UK
- Neonatal Intensive Care Unit, Evelina Children’s Hospital London, St Thomas’ Hospital, 6th Floor North Wing, Westminster Bridge Road, London SE1 7EH, UK
- MRC Centre for Neurodevelopmental Disorders, King’s College London, London SE1 1UL, UK
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Fukami-Gartner A, Baburamani AA, Dimitrova R, Patkee PA, Ojinaga-Alfageme O, Bonthrone AF, Cromb D, Uus AU, Counsell SJ, Hajnal JV, O’Muircheartaigh J, Rutherford MA. Comprehensive volumetric phenotyping of the neonatal brain in Down syndrome. Cereb Cortex 2023; 33:8921-8941. [PMID: 37254801 PMCID: PMC10350827 DOI: 10.1093/cercor/bhad171] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/17/2023] [Revised: 04/28/2023] [Accepted: 04/29/2023] [Indexed: 06/01/2023] Open
Abstract
Down syndrome (DS) is the most common genetic cause of intellectual disability with a wide range of neurodevelopmental outcomes. To date, there have been very few in vivo neuroimaging studies of the neonatal brain in DS. In this study we used a cross-sectional sample of 493 preterm- to term-born control neonates from the developing Human Connectome Project to perform normative modeling of regional brain tissue volumes from 32 to 46 weeks postmenstrual age, accounting for sex and age variables. Deviation from the normative mean was quantified in 25 neonates with DS with postnatally confirmed karyotypes from the Early Brain Imaging in DS study. Here, we provide the first comprehensive volumetric phenotyping of the neonatal brain in DS, which is characterized by significantly reduced whole brain, cerebral white matter, and cerebellar volumes; reduced relative frontal and occipital lobar volumes, in contrast with enlarged relative temporal and parietal lobar volumes; enlarged relative deep gray matter volume (particularly the lentiform nuclei); and enlargement of the lateral ventricles, amongst other features. In future, the ability to assess phenotypic severity at the neonatal stage may help guide early interventions and, ultimately, help improve neurodevelopmental outcomes in children with DS.
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Affiliation(s)
- Abi Fukami-Gartner
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King’s College London, St. Thomas’ Hospital, London SE1 7EH, United Kingdom
- MRC Centre for Neurodevelopmental Disorders, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London SE1 1UL, United Kingdom
| | - Ana A Baburamani
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King’s College London, St. Thomas’ Hospital, London SE1 7EH, United Kingdom
| | - Ralica Dimitrova
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King’s College London, St. Thomas’ Hospital, London SE1 7EH, United Kingdom
- Department of Forensic and Neurodevelopmental Science, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London SE5 8AF, United Kingdom
| | - Prachi A Patkee
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King’s College London, St. Thomas’ Hospital, London SE1 7EH, United Kingdom
| | - Olatz Ojinaga-Alfageme
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King’s College London, St. Thomas’ Hospital, London SE1 7EH, United Kingdom
- Centre for Brain and Cognitive Development, Birkbeck, University of London, London WC1E 7HX, United Kingdom
| | - Alexandra F Bonthrone
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King’s College London, St. Thomas’ Hospital, London SE1 7EH, United Kingdom
| | - Daniel Cromb
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King’s College London, St. Thomas’ Hospital, London SE1 7EH, United Kingdom
| | - Alena U Uus
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King’s College London, St. Thomas’ Hospital, London SE1 7EH, United Kingdom
- Department of Biomedical Engineering, School of Biomedical Engineering and Imaging Sciences, King’s College London, London SE1 7EH, United Kingdom
| | - Serena J Counsell
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King’s College London, St. Thomas’ Hospital, London SE1 7EH, United Kingdom
| | - Joseph V Hajnal
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King’s College London, St. Thomas’ Hospital, London SE1 7EH, United Kingdom
- Department of Biomedical Engineering, School of Biomedical Engineering and Imaging Sciences, King’s College London, London SE1 7EH, United Kingdom
| | - Jonathan O’Muircheartaigh
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King’s College London, St. Thomas’ Hospital, London SE1 7EH, United Kingdom
- MRC Centre for Neurodevelopmental Disorders, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London SE1 1UL, United Kingdom
- Department of Forensic and Neurodevelopmental Science, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London SE5 8AF, United Kingdom
| | - Mary A Rutherford
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King’s College London, St. Thomas’ Hospital, London SE1 7EH, United Kingdom
- MRC Centre for Neurodevelopmental Disorders, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London SE1 1UL, United Kingdom
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4
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Fenn-Moltu S, Fitzgibbon SP, Ciarrusta J, Eyre M, Cordero-Grande L, Chew A, Falconer S, Gale-Grant O, Harper N, Dimitrova R, Vecchiato K, Fenchel D, Javed A, Earl M, Price AN, Hughes E, Duff EP, O’Muircheartaigh J, Nosarti C, Arichi T, Rueckert D, Counsell S, Hajnal JV, Edwards AD, McAlonan G, Batalle D. Development of neonatal brain functional centrality and alterations associated with preterm birth. Cereb Cortex 2023; 33:5585-5596. [PMID: 36408638 PMCID: PMC10152096 DOI: 10.1093/cercor/bhac444] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/02/2022] [Revised: 09/21/2022] [Accepted: 10/11/2022] [Indexed: 11/22/2022] Open
Abstract
Formation of the functional connectome in early life underpins future learning and behavior. However, our understanding of how the functional organization of brain regions into interconnected hubs (centrality) matures in the early postnatal period is limited, especially in response to factors associated with adverse neurodevelopmental outcomes such as preterm birth. We characterized voxel-wise functional centrality (weighted degree) in 366 neonates from the Developing Human Connectome Project. We tested the hypothesis that functional centrality matures with age at scan in term-born babies and is disrupted by preterm birth. Finally, we asked whether neonatal functional centrality predicts general neurodevelopmental outcomes at 18 months. We report an age-related increase in functional centrality predominantly within visual regions and a decrease within the motor and auditory regions in term-born infants. Preterm-born infants scanned at term equivalent age had higher functional centrality predominantly within visual regions and lower measures in motor regions. Functional centrality was not related to outcome at 18 months old. Thus, preterm birth appears to affect functional centrality in regions undergoing substantial development during the perinatal period. Our work raises the question of whether these alterations are adaptive or disruptive and whether they predict neurodevelopmental characteristics that are more subtle or emerge later in life.
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Affiliation(s)
- Sunniva Fenn-Moltu
- Department of Forensic and Neurodevelopmental Sciences, Institute of Psychiatry, Psychology & Neuroscience, King’s College London, London, SE5 8AF, United Kingdom
- Centre for the Developing Brain, School of Biomedical Engineering & Imaging Sciences, King's College London, London, SE1 7EH, United Kingdom
| | - Sean P Fitzgibbon
- Wellcome Centre for Integrative Neuroimaging (WIN FMRIB), University of Oxford, Oxford, OX3 9DU, United Kingdom
| | - Judit Ciarrusta
- Department of Forensic and Neurodevelopmental Sciences, Institute of Psychiatry, Psychology & Neuroscience, King’s College London, London, SE5 8AF, United Kingdom
- Centre for the Developing Brain, School of Biomedical Engineering & Imaging Sciences, King's College London, London, SE1 7EH, United Kingdom
| | - Michael Eyre
- Centre for the Developing Brain, School of Biomedical Engineering & Imaging Sciences, King's College London, London, SE1 7EH, United Kingdom
| | - Lucilio Cordero-Grande
- Centre for the Developing Brain, School of Biomedical Engineering & Imaging Sciences, King's College London, London, SE1 7EH, United Kingdom
- Biomedical Image Technologies, ETSI Telecomunicación, Universidad Politécnica de Madrid & CIBER-BBN, Madrid, 28040, Spain
| | - Andrew Chew
- Centre for the Developing Brain, School of Biomedical Engineering & Imaging Sciences, King's College London, London, SE1 7EH, United Kingdom
| | - Shona Falconer
- Centre for the Developing Brain, School of Biomedical Engineering & Imaging Sciences, King's College London, London, SE1 7EH, United Kingdom
| | - Oliver Gale-Grant
- Department of Forensic and Neurodevelopmental Sciences, Institute of Psychiatry, Psychology & Neuroscience, King’s College London, London, SE5 8AF, United Kingdom
- Centre for the Developing Brain, School of Biomedical Engineering & Imaging Sciences, King's College London, London, SE1 7EH, United Kingdom
- MRC Centre for Neurodevelopmental Disorders, King’s College London, London, SE1 1UL, United Kingdom
| | - Nicholas Harper
- Centre for the Developing Brain, School of Biomedical Engineering & Imaging Sciences, King's College London, London, SE1 7EH, United Kingdom
| | - Ralica Dimitrova
- Department of Forensic and Neurodevelopmental Sciences, Institute of Psychiatry, Psychology & Neuroscience, King’s College London, London, SE5 8AF, United Kingdom
- Centre for the Developing Brain, School of Biomedical Engineering & Imaging Sciences, King's College London, London, SE1 7EH, United Kingdom
| | - Katy Vecchiato
- Department of Forensic and Neurodevelopmental Sciences, Institute of Psychiatry, Psychology & Neuroscience, King’s College London, London, SE5 8AF, United Kingdom
- Centre for the Developing Brain, School of Biomedical Engineering & Imaging Sciences, King's College London, London, SE1 7EH, United Kingdom
| | - Daphna Fenchel
- Department of Forensic and Neurodevelopmental Sciences, Institute of Psychiatry, Psychology & Neuroscience, King’s College London, London, SE5 8AF, United Kingdom
- Centre for the Developing Brain, School of Biomedical Engineering & Imaging Sciences, King's College London, London, SE1 7EH, United Kingdom
- MRC Centre for Neurodevelopmental Disorders, King’s College London, London, SE1 1UL, United Kingdom
| | - Ayesha Javed
- Department of Forensic and Neurodevelopmental Sciences, Institute of Psychiatry, Psychology & Neuroscience, King’s College London, London, SE5 8AF, United Kingdom
- Centre for the Developing Brain, School of Biomedical Engineering & Imaging Sciences, King's College London, London, SE1 7EH, United Kingdom
| | - Megan Earl
- Department of Forensic and Neurodevelopmental Sciences, Institute of Psychiatry, Psychology & Neuroscience, King’s College London, London, SE5 8AF, United Kingdom
- Centre for the Developing Brain, School of Biomedical Engineering & Imaging Sciences, King's College London, London, SE1 7EH, United Kingdom
- Paediatric Liver, GI and Nutrition Centre and MowatLabs, King’s College London, London, SE5 9RS, United Kingdom
| | - Anthony N Price
- Centre for the Developing Brain, School of Biomedical Engineering & Imaging Sciences, King's College London, London, SE1 7EH, United Kingdom
| | - Emer Hughes
- Centre for the Developing Brain, School of Biomedical Engineering & Imaging Sciences, King's College London, London, SE1 7EH, United Kingdom
| | - Eugene P Duff
- Wellcome Centre for Integrative Neuroimaging (WIN FMRIB), University of Oxford, Oxford, OX3 9DU, United Kingdom
- Department of Paediatrics, University of Oxford, Oxford, OX3 9DU, United Kingdom
| | - Jonathan O’Muircheartaigh
- Department of Forensic and Neurodevelopmental Sciences, Institute of Psychiatry, Psychology & Neuroscience, King’s College London, London, SE5 8AF, United Kingdom
- Centre for the Developing Brain, School of Biomedical Engineering & Imaging Sciences, King's College London, London, SE1 7EH, United Kingdom
- MRC Centre for Neurodevelopmental Disorders, King’s College London, London, SE1 1UL, United Kingdom
| | - Chiara Nosarti
- Centre for the Developing Brain, School of Biomedical Engineering & Imaging Sciences, King's College London, London, SE1 7EH, United Kingdom
- Department of Child and Adolescent Psychiatry, Institute of Psychiatry Psychology and Neuroscience, King’s College London, London, SE5 8AF, United Kingdom
| | - Tomoki Arichi
- Centre for the Developing Brain, School of Biomedical Engineering & Imaging Sciences, King's College London, London, SE1 7EH, United Kingdom
- MRC Centre for Neurodevelopmental Disorders, King’s College London, London, SE1 1UL, United Kingdom
- Paediatric Neurosciences, Evelina London Children’s Hospital, Guy’s and St Thomas’ NHS Foundation Trust, London, SE1 7EH, United Kingdom
- Department of Bioengineering, Imperial College London, London, SW7 2AZ, United Kingdom
| | - Daniel Rueckert
- Biomedical Image Analysis Group, Imperial College London, London, SW7 2AZ, United Kingdom
- Institute for AI and Informatics in Medicine, Klinikum rechts der Isar, Technical University of Munich, Munich, 81675, Germany
| | - Serena Counsell
- Centre for the Developing Brain, School of Biomedical Engineering & Imaging Sciences, King's College London, London, SE1 7EH, United Kingdom
| | - Joseph V Hajnal
- Centre for the Developing Brain, School of Biomedical Engineering & Imaging Sciences, King's College London, London, SE1 7EH, United Kingdom
| | - A David Edwards
- Centre for the Developing Brain, School of Biomedical Engineering & Imaging Sciences, King's College London, London, SE1 7EH, United Kingdom
- MRC Centre for Neurodevelopmental Disorders, King’s College London, London, SE1 1UL, United Kingdom
| | - Grainne McAlonan
- Department of Forensic and Neurodevelopmental Sciences, Institute of Psychiatry, Psychology & Neuroscience, King’s College London, London, SE5 8AF, United Kingdom
- MRC Centre for Neurodevelopmental Disorders, King’s College London, London, SE1 1UL, United Kingdom
| | - Dafnis Batalle
- Department of Forensic and Neurodevelopmental Sciences, Institute of Psychiatry, Psychology & Neuroscience, King’s College London, London, SE5 8AF, United Kingdom
- Centre for the Developing Brain, School of Biomedical Engineering & Imaging Sciences, King's College London, London, SE1 7EH, United Kingdom
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5
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Wilson S, Pietsch M, Cordero-Grande L, Christiaens D, Uus A, Karolis VR, Kyriakopoulou V, Colford K, Price AN, Hutter J, Rutherford MA, Hughes EJ, Counsell SJ, Tournier JD, Hajnal JV, Edwards AD, O’Muircheartaigh J, Arichi T. Spatiotemporal tissue maturation of thalamocortical pathways in the human fetal brain. eLife 2023; 12:e83727. [PMID: 37010273 PMCID: PMC10125021 DOI: 10.7554/elife.83727] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/26/2022] [Accepted: 03/31/2023] [Indexed: 04/04/2023] Open
Abstract
The development of connectivity between the thalamus and maturing cortex is a fundamental process in the second half of human gestation, establishing the neural circuits that are the basis for several important brain functions. In this study, we acquired high-resolution in utero diffusion magnetic resonance imaging (MRI) from 140 fetuses as part of the Developing Human Connectome Project, to examine the emergence of thalamocortical white matter over the second to third trimester. We delineate developing thalamocortical pathways and parcellate the fetal thalamus according to its cortical connectivity using diffusion tractography. We then quantify microstructural tissue components along the tracts in fetal compartments that are critical substrates for white matter maturation, such as the subplate and intermediate zone. We identify patterns of change in the diffusion metrics that reflect critical neurobiological transitions occurring in the second to third trimester, such as the disassembly of radial glial scaffolding and the lamination of the cortical plate. These maturational trajectories of MR signal in transient fetal compartments provide a normative reference to complement histological knowledge, facilitating future studies to establish how developmental disruptions in these regions contribute to pathophysiology.
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Affiliation(s)
- Siân Wilson
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King’s College LondonLondonUnited Kingdom
- Centre for Neurodevelopmental Disorders, King’s College LondonLondonUnited Kingdom
| | - Maximilian Pietsch
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King’s College LondonLondonUnited Kingdom
| | - Lucilio Cordero-Grande
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King’s College LondonLondonUnited Kingdom
- Biomedical Image Technologies, ETSI Telecomunicación, Universidad Politécnica de MadridMadridSpain
- Biomedical Research Networking Center in Bioengineering, Biomaterials and Nanomedicine (CIBER-BBN)MadridSpain
| | - Daan Christiaens
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King’s College LondonLondonUnited Kingdom
- Department of Electrical Engineering (ESAT/PSI), Katholieke Universiteit LeuvenLeuvenBelgium
| | - Alena Uus
- Department of Biomedical Engineering, School Biomedical Engineering and Imaging Sciences, King’s College London, St. Thomas' HospitalLondonUnited Kingdom
| | - Vyacheslav R Karolis
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King’s College LondonLondonUnited Kingdom
| | - Vanessa Kyriakopoulou
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King’s College LondonLondonUnited Kingdom
| | - Kathleen Colford
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King’s College LondonLondonUnited Kingdom
| | - Anthony N Price
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King’s College LondonLondonUnited Kingdom
| | - Jana Hutter
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King’s College LondonLondonUnited Kingdom
| | - Mary A Rutherford
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King’s College LondonLondonUnited Kingdom
| | - Emer J Hughes
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King’s College LondonLondonUnited Kingdom
| | - Serena J Counsell
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King’s College LondonLondonUnited Kingdom
| | - Jacques-Donald Tournier
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King’s College LondonLondonUnited Kingdom
| | - Joseph V Hajnal
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King’s College LondonLondonUnited Kingdom
| | - A David Edwards
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King’s College LondonLondonUnited Kingdom
- Centre for Neurodevelopmental Disorders, King’s College LondonLondonUnited Kingdom
| | - Jonathan O’Muircheartaigh
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King’s College LondonLondonUnited Kingdom
- Centre for Neurodevelopmental Disorders, King’s College LondonLondonUnited Kingdom
- Department of Forensic and Neurodevelopmental Sciences, King’s College LondonLondonUnited Kingdom
- Department of Neuroimaging, Institute of Psychiatry, Psychology and Neuroscience, King’s College LondonLondonUnited Kingdom
| | - Tomoki Arichi
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King’s College LondonLondonUnited Kingdom
- Centre for Neurodevelopmental Disorders, King’s College LondonLondonUnited Kingdom
- Children’s Neurosciences, Evelina London Children’s Hospital, Guy’s and St Thomas’ NHS Foundation TrustLondonUnited Kingdom
- Department of Bioengineering, Imperial College LondonLondonUnited Kingdom
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6
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Zhou Y, Müller HG, Zhu C, Chen Y, Wang JL, O'Muircheartaigh J, Bruchhage M, Deoni S, Bruchhage M, Carnell S, Deoni S, D’Sa V, Huentelman M, Klepac-Ceraj V, LeBourgeois M, Müller HG, O’Muircheartaigh J, Wang JL. Network evolution of regional brain volumes in young children reflects neurocognitive scores and mother's education. Sci Rep 2023; 13:2984. [PMID: 36804963 PMCID: PMC9941570 DOI: 10.1038/s41598-023-29797-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/19/2022] [Accepted: 02/10/2023] [Indexed: 02/22/2023] Open
Abstract
The maturation of regional brain volumes from birth to preadolescence is a critical developmental process that underlies emerging brain structural connectivity and function. Regulated by genes and environment, the coordinated growth of different brain regions plays an important role in cognitive development. Current knowledge about structural network evolution is limited, partly due to the sparse and irregular nature of most longitudinal neuroimaging data. In particular, it is unknown how factors such as mother's education or sex of the child impact the structural network evolution. To address this issue, we propose a method to construct evolving structural networks and study how the evolving connections among brain regions as reflected at the network level are related to maternal education and biological sex of the child and also how they are associated with cognitive development. Our methodology is based on applying local Fréchet regression to longitudinal neuroimaging data acquired from the RESONANCE cohort, a cohort of healthy children (245 females and 309 males) ranging in age from 9 weeks to 10 years. Our findings reveal that sustained highly coordinated volume growth across brain regions is associated with lower maternal education and lower cognitive development. This suggests that higher neurocognitive performance levels in children are associated with increased variability of regional growth patterns as children age.
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Affiliation(s)
- Yidong Zhou
- Department of Statistics, University of California, Davis, Davis, CA, 95616, USA.
| | - Hans-Georg Müller
- Department of Statistics, University of California, Davis, Davis, CA, 95616, USA
| | - Changbo Zhu
- Department of Applied and Computational Mathematics and Statistics, University of Notre Dame, Notre Dame, IN, 46556, USA
| | - Yaqing Chen
- Department of Statistics, Rutgers University, New Brunswick, NJ, 08901, USA
| | - Jane-Ling Wang
- Department of Statistics, University of California, Davis, Davis, CA, 95616, USA
| | - Jonathan O'Muircheartaigh
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK.,Department of Forensic and Neurodevelopmental Sciences, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK.,MRC Centre for Neurodevelopmental Disorders, King's College London, London, UK
| | - Muriel Bruchhage
- Department of Pediatrics, Warren Alpert Medical School at Brown University, Providence, USA.,Department of Diagnostic Imaging, Rhode Island Hospital, Providence, USA.,Institute of Social Sciences, Stavanger University, Stavanger, 4021, Norway
| | - Sean Deoni
- Maternal, Newborn, and Child Health Discovery and Tools, Bill and Melinda Gates Foundation, Seattle, WA, USA
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7
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Spitzer H, Ripart M, Whitaker K, D’Arco F, Mankad K, Chen AA, Napolitano A, De Palma L, De Benedictis A, Foldes S, Humphreys Z, Zhang K, Hu W, Mo J, Likeman M, Davies S, Güttler C, Lenge M, Cohen NT, Tang Y, Wang S, Chari A, Tisdall M, Bargallo N, Conde-Blanco E, Pariente JC, Pascual-Diaz S, Delgado-Martínez I, Pérez-Enríquez C, Lagorio I, Abela E, Mullatti N, O’Muircheartaigh J, Vecchiato K, Liu Y, Caligiuri ME, Sinclair B, Vivash L, Willard A, Kandasamy J, McLellan A, Sokol D, Semmelroch M, Kloster AG, Opheim G, Ribeiro L, Yasuda C, Rossi-Espagnet C, Hamandi K, Tietze A, Barba C, Guerrini R, Gaillard WD, You X, Wang I, González-Ortiz S, Severino M, Striano P, Tortora D, Kälviäinen R, Gambardella A, Labate A, Desmond P, Lui E, O’Brien T, Shetty J, Jackson G, Duncan JS, Winston GP, Pinborg LH, Cendes F, Theis FJ, Shinohara RT, Cross JH, Baldeweg T, Adler S, Wagstyl K. Interpretable surface-based detection of focal cortical dysplasias: a Multi-centre Epilepsy Lesion Detection study. Brain 2022; 145:3859-3871. [PMID: 35953082 PMCID: PMC9679165 DOI: 10.1093/brain/awac224] [Citation(s) in RCA: 25] [Impact Index Per Article: 12.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/14/2021] [Revised: 04/22/2022] [Accepted: 05/26/2022] [Indexed: 11/13/2022] Open
Abstract
One outstanding challenge for machine learning in diagnostic biomedical imaging is algorithm interpretability. A key application is the identification of subtle epileptogenic focal cortical dysplasias (FCDs) from structural MRI. FCDs are difficult to visualize on structural MRI but are often amenable to surgical resection. We aimed to develop an open-source, interpretable, surface-based machine-learning algorithm to automatically identify FCDs on heterogeneous structural MRI data from epilepsy surgery centres worldwide. The Multi-centre Epilepsy Lesion Detection (MELD) Project collated and harmonized a retrospective MRI cohort of 1015 participants, 618 patients with focal FCD-related epilepsy and 397 controls, from 22 epilepsy centres worldwide. We created a neural network for FCD detection based on 33 surface-based features. The network was trained and cross-validated on 50% of the total cohort and tested on the remaining 50% as well as on 2 independent test sites. Multidimensional feature analysis and integrated gradient saliencies were used to interrogate network performance. Our pipeline outputs individual patient reports, which identify the location of predicted lesions, alongside their imaging features and relative saliency to the classifier. On a restricted 'gold-standard' subcohort of seizure-free patients with FCD type IIB who had T1 and fluid-attenuated inversion recovery MRI data, the MELD FCD surface-based algorithm had a sensitivity of 85%. Across the entire withheld test cohort the sensitivity was 59% and specificity was 54%. After including a border zone around lesions, to account for uncertainty around the borders of manually delineated lesion masks, the sensitivity was 67%. This multicentre, multinational study with open access protocols and code has developed a robust and interpretable machine-learning algorithm for automated detection of focal cortical dysplasias, giving physicians greater confidence in the identification of subtle MRI lesions in individuals with epilepsy.
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Affiliation(s)
- Hannah Spitzer
- Institute of Computational Biology, Helmholtz Center Munich, Munich 85764, Germany
| | - Mathilde Ripart
- Department of Developmental Neuroscience, UCL Great Ormond Street Institute for Child Health, London WC1N 1EH, UK
| | | | - Felice D’Arco
- Great Ormond Street Hospital NHS Foundation Trust, London WC1N 3JH, UK
| | - Kshitij Mankad
- Great Ormond Street Hospital NHS Foundation Trust, London WC1N 3JH, UK
| | - Andrew A Chen
- Penn Statistics in Imaging and Visualization Center, Department of Biostatistics, Epidemiology, and Informatics, University of Pennsylvania, Philadelphia, PA 19104, USA
- Center for Biomedical Image Computing and Analytics, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Antonio Napolitano
- Medical Physics Department, Bambino Gesù Children’s Hospital, Rome 00165, Italy
| | - Luca De Palma
- Rare and Complex Epilepsies, Department of Neurosciences, Bambino Gesù Children’s Hospital, IRCCS, Rome 00165, Italy
| | - Alessandro De Benedictis
- Neurosurgery Unit, Department of Neurosciences, Bambino Gesù Children’s Hospital, IRCCS, Rome 00165, Italy
| | - Stephen Foldes
- Barrow Neurological Institute at Phoenix Children’s Hospital, Phoenix, AZ 85016, USA
| | - Zachary Humphreys
- Barrow Neurological Institute at Phoenix Children’s Hospital, Phoenix, AZ 85016, USA
| | - Kai Zhang
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing 100054, China
| | - Wenhan Hu
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing 100054, China
| | - Jiajie Mo
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing 100054, China
| | - Marcus Likeman
- Bristol Royal Hospital for Children, Bristol BS2 8BJ, UK
| | - Shirin Davies
- School of Psychology, Cardiff University Brain Research Imaging Centre, Cardiff CF24 4HQ, UK
- The Welsh Epilepsy Unit, Cardiff and Vale University Health Board, University Hospital of Wales, Cardiff CF14 4XW, UK
| | | | - Matteo Lenge
- Neuroscience Department, Children’s Hospital Meyer-University of Florence, Florence 50139, Italy
| | - Nathan T Cohen
- Center for Neuroscience, Children’s National Hospital, Washington, DC 20012, USA
| | - Yingying Tang
- Department of Neurology, West China Hospital of Sichuan University, Chengdu 610093, China
- Epilepsy Center, Cleveland Clinic, Cleveland, OH 44106, USA
| | - Shan Wang
- Epilepsy Center, Cleveland Clinic, Cleveland, OH 44106, USA
- Department of Neurology, Epilepsy Center, Second Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou 310058, China
| | - Aswin Chari
- Department of Developmental Neuroscience, UCL Great Ormond Street Institute for Child Health, London WC1N 1EH, UK
- Great Ormond Street Hospital NHS Foundation Trust, London WC1N 3JH, UK
| | - Martin Tisdall
- Department of Developmental Neuroscience, UCL Great Ormond Street Institute for Child Health, London WC1N 1EH, UK
- Great Ormond Street Hospital NHS Foundation Trust, London WC1N 3JH, UK
| | - Nuria Bargallo
- Department of Neuroradiology, Hospital Clinic Barcelona and Magnetic Resonance Imaging, Core Facility, IDIBAPS, Barcelona 08036, Spain
- Centro de Investigación Biomédica en Red de Salud Mental, CIBERSAM, Madrid 28029, Spain
| | | | | | - Saül Pascual-Diaz
- Magnetic Resonance Imaging, Core Facility, IDIBAPS, Barcelona 08036, Spain
| | | | | | | | - Eugenio Abela
- Center for Neuropsychiatry and Intellectual Disability, Psychiatrische Dienste Aargau AG, Windisch 5120, Switzerland
| | - Nandini Mullatti
- Institute of Psychiatry, Psychology and Neuroscience, King’s College, London SE5 8AF, UK
| | - Jonathan O’Muircheartaigh
- Institute of Psychiatry, Psychology and Neuroscience, King’s College, London SE5 8AF, UK
- Department of Perinatal Imaging and Health, St. Thomas’ Hospital, King’s College London, London SE1 7EH, UK
| | - Katy Vecchiato
- Department of Perinatal Imaging and Health, St. Thomas’ Hospital, King’s College London, London SE1 7EH, UK
- Department of Forensic and Neurodevelopmental Sciences, Institute of Psychiatry, Psychology and Neuroscience, King’s College, London SE5 8AF, UK
| | - Yawu Liu
- Department of Neurology, University of Eastern Finland, Kuopio 70210, Finland
| | - Maria Eugenia Caligiuri
- Department of Medical and Surgical Sciences, Magna Graecia University of Catanzaro, Catanzaro 88100, Italy
| | - Ben Sinclair
- Department of Neuroscience, Central Clinical School, Monash University, Melbourne, VIC 3004, Australia
| | - Lucy Vivash
- Department of Neuroscience, Central Clinical School, Monash University, Melbourne, VIC 3004, Australia
- Department of Neurology, Monash University, Melbourne, VIC 3004, Australia
| | - Anna Willard
- Department of Neuroscience, Central Clinical School, Monash University, Melbourne, VIC 3004, Australia
| | - Jothy Kandasamy
- Royal Hospital for Children and Young People, Edinburgh EH16 4TJ, UK
| | - Ailsa McLellan
- Royal Hospital for Children and Young People, Edinburgh EH16 4TJ, UK
| | - Drahoslav Sokol
- Royal Hospital for Children and Young People, Edinburgh EH16 4TJ, UK
| | - Mira Semmelroch
- The Florey Institute of Neuroscience and Mental Health, University of Melbourne, Parkville, VIC 3052, Australia
| | - Ane G Kloster
- Neurobiology Research Unit, Copenhagen University Hospital—Rigshospitalet, Copenhagen 2100, Denmark
| | - Giske Opheim
- Neurobiology Research Unit, Copenhagen University Hospital—Rigshospitalet, Copenhagen 2100, Denmark
- Department of Neuroradiology, Copenhagen University Hospital—Rigshospitalet, Copenhagen 2100, Denmark
| | - Letícia Ribeiro
- Department of Neurology, University of Campinas, Campinas 13083-888, Brazil
- Brazilian Institute of Neuroscience and Neurotechnology (BRAINN), University of Campinas, Campinas 13083-888, Brazil
| | - Clarissa Yasuda
- Department of Neurology, University of Campinas, Campinas 13083-888, Brazil
- Brazilian Institute of Neuroscience and Neurotechnology (BRAINN), University of Campinas, Campinas 13083-888, Brazil
| | | | - Khalid Hamandi
- School of Psychology, Cardiff University Brain Research Imaging Centre, Cardiff CF24 4HQ, UK
- The Welsh Epilepsy Unit, University Hospital of Wales, Cardiff CF14 4XW, UK
| | - Anna Tietze
- Charité University Hospital, Berlin 10117, Germany
| | - Carmen Barba
- Neuroscience Department, Children’s Hospital Meyer-University of Florence, Florence 50139, Italy
| | - Renzo Guerrini
- Neuroscience Department, Children’s Hospital Meyer-University of Florence, Florence 50139, Italy
| | | | - Xiaozhen You
- Center for Neuroscience, Children’s National Hospital, Washington, DC 20012, USA
| | - Irene Wang
- Epilepsy Center, Cleveland Clinic, Cleveland, OH 44106, USA
| | - Sofía González-Ortiz
- Department of Neuroradiology, Hospital del Mar, Barcelona 08003, Spain
- Magnetic Resonance Imaging Core Facility, Institut d’Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona 08036, Spain
| | | | - Pasquale Striano
- IRCCS Istituto Giannina Gaslini, Genova 16147, Italy
- Department of Neurosciences, Rehabilitation, Ophthalmology, Genetics, Maternal and Child Health, University of Genova, Genova, Italy
| | | | - Reetta Kälviäinen
- Department of Neurology, University of Eastern Finland, Kuopio 70210, Finland
- Kuopio Epilepsy Center, Neurocenter, Kuopio University Hospital, Kuopio 70210, Finland
| | - Antonio Gambardella
- Institute of Neurology, Department of Medical and Surgical Sciences, Magna Graecia University, Catanzaro 88100, Italy
| | - Angelo Labate
- Neurology Unit, Department of BIOMORF, University of Messina, Messina 98168, Italy
| | - Patricia Desmond
- Department of Radiology, The Royal Melbourne Hospital, University of Melbourne, Parkville, VIC 3050, Australia
| | - Elaine Lui
- Department of Radiology, The Royal Melbourne Hospital, University of Melbourne, Parkville, VIC 3050, Australia
| | - Terence O’Brien
- Department of Neuroscience, Central Clinical School, Monash University, Melbourne, VIC 3004, Australia
- Department of Medicine, The Royal Melbourne Hospital, Parkville, VIC, 3052, Australia
| | - Jay Shetty
- Royal Hospital for Children and Young People, Edinburgh EH16 4TJ, UK
| | - Graeme Jackson
- The Florey Institute of Neuroscience and Mental Health, Austin Campus, Heidelberg, VIC 3071, Australia
- Department of Neurology, Austin Health, Heidelberg, VIC 3084, Australia
| | - John S Duncan
- UCL Queen Square Institute of Neurology, London WC1N 3BG, UK
| | - Gavin P Winston
- UCL Queen Square Institute of Neurology, London WC1N 3BG, UK
- Department of Medicine, Division of Neurology, Queen’s University, Kingston, ON, Canada K7L 3N6
| | - Lars H Pinborg
- Neurobiology Research Unit, Copenhagen University Hospital—Rigshospitalet, Copenhagen 2100, Denmark
- Epilepsy Clinic, Department of Neurology, Copenhagen University Hospital—Rigshopsitalet, Copenhagen 2100, Denmark
| | - Fernando Cendes
- Department of Neurology, University of Campinas, Campinas 13083-888, Brazil
- Brazilian Institute of Neuroscience and Neurotechnology (BRAINN), University of Campinas, Campinas 13083-888, Brazil
| | - Fabian J Theis
- Institute of Computational Biology, Helmholtz Center Munich, Munich 85764, Germany
- Department of Mathematics, Technical University of Munich, Garching 85748, Germany
| | - Russell T Shinohara
- Penn Statistics in Imaging and Visualization Center, Department of Biostatistics, Epidemiology, and Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - J Helen Cross
- Department of Developmental Neuroscience, UCL Great Ormond Street Institute for Child Health, London WC1N 1EH, UK
- Young Epilepsy, Lingfield, Surrey RH7 6PW, UK
| | - Torsten Baldeweg
- Department of Developmental Neuroscience, UCL Great Ormond Street Institute for Child Health, London WC1N 1EH, UK
- Great Ormond Street Hospital NHS Foundation Trust, London WC1N 3JH, UK
| | - Sophie Adler
- Department of Developmental Neuroscience, UCL Great Ormond Street Institute for Child Health, London WC1N 1EH, UK
| | - Konrad Wagstyl
- Department of Developmental Neuroscience, UCL Great Ormond Street Institute for Child Health, London WC1N 1EH, UK
- Wellcome Centre for Human Neuroimaging, University College London, London WC1N 3AR, UK
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8
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Edwards AD, Rueckert D, Smith SM, Abo Seada S, Alansary A, Almalbis J, Allsop J, Andersson J, Arichi T, Arulkumaran S, Bastiani M, Batalle D, Baxter L, Bozek J, Braithwaite E, Brandon J, Carney O, Chew A, Christiaens D, Chung R, Colford K, Cordero-Grande L, Counsell SJ, Cullen H, Cupitt J, Curtis C, Davidson A, Deprez M, Dillon L, Dimitrakopoulou K, Dimitrova R, Duff E, Falconer S, Farahibozorg SR, Fitzgibbon SP, Gao J, Gaspar A, Harper N, Harrison SJ, Hughes EJ, Hutter J, Jenkinson M, Jbabdi S, Jones E, Karolis V, Kyriakopoulou V, Lenz G, Makropoulos A, Malik S, Mason L, Mortari F, Nosarti C, Nunes RG, O’Keeffe C, O’Muircheartaigh J, Patel H, Passerat-Palmbach J, Pietsch M, Price AN, Robinson EC, Rutherford MA, Schuh A, Sotiropoulos S, Steinweg J, Teixeira RPAG, Tenev T, Tournier JD, Tusor N, Uus A, Vecchiato K, Williams LZJ, Wright R, Wurie J, Hajnal JV. The Developing Human Connectome Project Neonatal Data Release. Front Neurosci 2022; 16:886772. [PMID: 35677357 PMCID: PMC9169090 DOI: 10.3389/fnins.2022.886772] [Citation(s) in RCA: 22] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/28/2022] [Accepted: 04/19/2022] [Indexed: 11/24/2022] Open
Abstract
The Developing Human Connectome Project has created a large open science resource which provides researchers with data for investigating typical and atypical brain development across the perinatal period. It has collected 1228 multimodal magnetic resonance imaging (MRI) brain datasets from 1173 fetal and/or neonatal participants, together with collateral demographic, clinical, family, neurocognitive and genomic data from 1173 participants, together with collateral demographic, clinical, family, neurocognitive and genomic data. All subjects were studied in utero and/or soon after birth on a single MRI scanner using specially developed scanning sequences which included novel motion-tolerant imaging methods. Imaging data are complemented by rich demographic, clinical, neurodevelopmental, and genomic information. The project is now releasing a large set of neonatal data; fetal data will be described and released separately. This release includes scans from 783 infants of whom: 583 were healthy infants born at term; as well as preterm infants; and infants at high risk of atypical neurocognitive development. Many infants were imaged more than once to provide longitudinal data, and the total number of datasets being released is 887. We now describe the dHCP image acquisition and processing protocols, summarize the available imaging and collateral data, and provide information on how the data can be accessed.
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Affiliation(s)
- A. David Edwards
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King’s College London, London, United Kingdom
- MRC Centre for Neurodevelopmental Disorders, King’s College London, London, United Kingdom
| | - Daniel Rueckert
- Biomedical Image Analysis Group, Department of Computing, Imperial College London, London, United Kingdom
- Institute for AI and Informatics in Medicine, Klinikum Rechts der Isar, Technical University of Munich, Munich, Germany
| | - Stephen M. Smith
- Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, United Kingdom
| | - Samy Abo Seada
- Biomedical Engineering Department, School of Biomedical Engineering & Imaging Sciences, King’s College London, London, United Kingdom
| | - Amir Alansary
- Biomedical Image Analysis Group, Department of Computing, Imperial College London, London, United Kingdom
| | - Jennifer Almalbis
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King’s College London, London, United Kingdom
| | - Joanna Allsop
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King’s College London, London, United Kingdom
| | - Jesper Andersson
- Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, United Kingdom
| | - Tomoki Arichi
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King’s College London, London, United Kingdom
- MRC Centre for Neurodevelopmental Disorders, King’s College London, London, United Kingdom
| | - Sophie Arulkumaran
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King’s College London, London, United Kingdom
| | - Matteo Bastiani
- Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, United Kingdom
- Sir Peter Mansfield Imaging Centre, Mental Health and Clinical Neurosciences, School of Medicine, University of Nottingham, Nottingham, United Kingdom
| | - Dafnis Batalle
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King’s College London, London, United Kingdom
- Department of Forensic and Neurodevelopmental Sciences, Institute of Psychiatry, Psychology & Neuroscience, King’s College London, London, United Kingdom
| | - Luke Baxter
- Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, United Kingdom
| | - Jelena Bozek
- Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, United Kingdom
- Faculty of Electrical Engineering and Computing, University of Zagreb, Zagreb, Croatia
| | - Eleanor Braithwaite
- Centre for Brain and Cognitive Development, Department of Psychological Sciences, Birkbeck, University of London, London, United Kingdom
| | - Jacqueline Brandon
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King’s College London, London, United Kingdom
| | - Olivia Carney
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King’s College London, London, United Kingdom
| | - Andrew Chew
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King’s College London, London, United Kingdom
| | - Daan Christiaens
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King’s College London, London, United Kingdom
- Department of Electrical Engineering, ESAT/PSI, KU Leuven, Leuven, Belgium
| | - Raymond Chung
- BioResource Centre, NIHR Biomedical Research Centre, South London and Maudsley NHS Trust, London, United Kingdom
| | - Kathleen Colford
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King’s College London, London, United Kingdom
| | - Lucilio Cordero-Grande
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King’s College London, London, United Kingdom
- Biomedical Image Technologies, ETSI Telecomunicación, Universidad Politécnica de Madrid and CIBER-BBN, Madrid, Spain
| | - Serena J. Counsell
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King’s College London, London, United Kingdom
| | - Harriet Cullen
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King’s College London, London, United Kingdom
- Department of Medical and Molecular Genetics, School of Basic and Medical Biosciences, King’s College London, London, United Kingdom
| | - John Cupitt
- Biomedical Image Analysis Group, Department of Computing, Imperial College London, London, United Kingdom
| | - Charles Curtis
- BioResource Centre, NIHR Biomedical Research Centre, South London and Maudsley NHS Trust, London, United Kingdom
| | - Alice Davidson
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King’s College London, London, United Kingdom
| | - Maria Deprez
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King’s College London, London, United Kingdom
- Biomedical Engineering Department, School of Biomedical Engineering & Imaging Sciences, King’s College London, London, United Kingdom
| | - Louise Dillon
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King’s College London, London, United Kingdom
| | - Konstantina Dimitrakopoulou
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King’s College London, London, United Kingdom
- Translational Bioinformatics Platform, NIHR Biomedical Research Centre, Guy’s and St. Thomas’ NHS Foundation Trust and King’s College London, London, United Kingdom
| | - Ralica Dimitrova
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King’s College London, London, United Kingdom
- Department of Forensic and Neurodevelopmental Sciences, Institute of Psychiatry, Psychology & Neuroscience, King’s College London, London, United Kingdom
| | - Eugene Duff
- Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, United Kingdom
| | - Shona Falconer
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King’s College London, London, United Kingdom
| | - Seyedeh-Rezvan Farahibozorg
- Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, United Kingdom
| | - Sean P. Fitzgibbon
- Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, United Kingdom
| | - Jianliang Gao
- Biomedical Image Analysis Group, Department of Computing, Imperial College London, London, United Kingdom
| | - Andreia Gaspar
- Institute for Systems and Robotics (ISR-Lisboa)/LaRSyS, Department of Bioengineering, Instituto Superior Técnico, Universidade de Lisboa, Lisbon, Portugal
| | - Nicholas Harper
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King’s College London, London, United Kingdom
| | - Sam J. Harrison
- Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, United Kingdom
| | - Emer J. Hughes
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King’s College London, London, United Kingdom
| | - Jana Hutter
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King’s College London, London, United Kingdom
- Biomedical Engineering Department, School of Biomedical Engineering & Imaging Sciences, King’s College London, London, United Kingdom
| | - Mark Jenkinson
- Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, United Kingdom
| | - Saad Jbabdi
- Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, United Kingdom
| | - Emily Jones
- Centre for Brain and Cognitive Development, Department of Psychological Sciences, Birkbeck, University of London, London, United Kingdom
| | - Vyacheslav Karolis
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King’s College London, London, United Kingdom
- Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, United Kingdom
| | - Vanessa Kyriakopoulou
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King’s College London, London, United Kingdom
| | - Gregor Lenz
- Biomedical Image Analysis Group, Department of Computing, Imperial College London, London, United Kingdom
| | - Antonios Makropoulos
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King’s College London, London, United Kingdom
- Biomedical Image Analysis Group, Department of Computing, Imperial College London, London, United Kingdom
| | - Shaihan Malik
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King’s College London, London, United Kingdom
- Biomedical Engineering Department, School of Biomedical Engineering & Imaging Sciences, King’s College London, London, United Kingdom
| | - Luke Mason
- Centre for Brain and Cognitive Development, Department of Psychological Sciences, Birkbeck, University of London, London, United Kingdom
| | - Filippo Mortari
- Biomedical Image Analysis Group, Department of Computing, Imperial College London, London, United Kingdom
| | - Chiara Nosarti
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King’s College London, London, United Kingdom
- Department of Child and Adolescent Psychiatry, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London, United Kingdom
| | - Rita G. Nunes
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King’s College London, London, United Kingdom
- Institute for Systems and Robotics (ISR-Lisboa)/LaRSyS, Department of Bioengineering, Instituto Superior Técnico, Universidade de Lisboa, Lisbon, Portugal
| | - Camilla O’Keeffe
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King’s College London, London, United Kingdom
| | - Jonathan O’Muircheartaigh
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King’s College London, London, United Kingdom
- MRC Centre for Neurodevelopmental Disorders, King’s College London, London, United Kingdom
- Department of Forensic and Neurodevelopmental Sciences, Institute of Psychiatry, Psychology & Neuroscience, King’s College London, London, United Kingdom
| | - Hamel Patel
- BioResource Centre, NIHR Biomedical Research Centre, South London and Maudsley NHS Trust, London, United Kingdom
| | - Jonathan Passerat-Palmbach
- Biomedical Image Analysis Group, Department of Computing, Imperial College London, London, United Kingdom
| | - Maximillian Pietsch
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King’s College London, London, United Kingdom
- Department of Forensic and Neurodevelopmental Sciences, Institute of Psychiatry, Psychology & Neuroscience, King’s College London, London, United Kingdom
| | - Anthony N. Price
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King’s College London, London, United Kingdom
- Biomedical Engineering Department, School of Biomedical Engineering & Imaging Sciences, King’s College London, London, United Kingdom
| | - Emma C. Robinson
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King’s College London, London, United Kingdom
- Biomedical Engineering Department, School of Biomedical Engineering & Imaging Sciences, King’s College London, London, United Kingdom
| | - Mary A. Rutherford
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King’s College London, London, United Kingdom
| | - Andreas Schuh
- Biomedical Image Analysis Group, Department of Computing, Imperial College London, London, United Kingdom
| | - Stamatios Sotiropoulos
- Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, United Kingdom
- Sir Peter Mansfield Imaging Centre, Mental Health and Clinical Neurosciences, School of Medicine, University of Nottingham, Nottingham, United Kingdom
| | - Johannes Steinweg
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King’s College London, London, United Kingdom
| | - Rui Pedro Azeredo Gomes Teixeira
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King’s College London, London, United Kingdom
- Biomedical Engineering Department, School of Biomedical Engineering & Imaging Sciences, King’s College London, London, United Kingdom
| | - Tencho Tenev
- Biomedical Image Analysis Group, Department of Computing, Imperial College London, London, United Kingdom
| | - Jacques-Donald Tournier
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King’s College London, London, United Kingdom
- Biomedical Engineering Department, School of Biomedical Engineering & Imaging Sciences, King’s College London, London, United Kingdom
| | - Nora Tusor
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King’s College London, London, United Kingdom
| | - Alena Uus
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King’s College London, London, United Kingdom
- Biomedical Engineering Department, School of Biomedical Engineering & Imaging Sciences, King’s College London, London, United Kingdom
| | - Katy Vecchiato
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King’s College London, London, United Kingdom
| | - Logan Z. J. Williams
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King’s College London, London, United Kingdom
| | - Robert Wright
- Biomedical Image Analysis Group, Department of Computing, Imperial College London, London, United Kingdom
| | - Julia Wurie
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King’s College London, London, United Kingdom
| | - Joseph V. Hajnal
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King’s College London, London, United Kingdom
- Biomedical Engineering Department, School of Biomedical Engineering & Imaging Sciences, King’s College London, London, United Kingdom
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9
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Dimitrova R, Arulkumaran S, Carney O, Chew A, Falconer S, Ciarrusta J, Wolfers T, Batalle D, Cordero-Grande L, Price AN, Teixeira RPAG, Hughes E, Egloff A, Hutter J, Makropoulos A, Robinson EC, Schuh A, Vecchiato K, Steinweg JK, Macleod R, Marquand AF, McAlonan G, Rutherford MA, Counsell SJ, Smith SM, Rueckert D, Hajnal JV, O’Muircheartaigh J, Edwards AD. Phenotyping the Preterm Brain: Characterizing Individual Deviations From Normative Volumetric Development in Two Large Infant Cohorts. Cereb Cortex 2021; 31:3665-3677. [PMID: 33822913 PMCID: PMC8258435 DOI: 10.1093/cercor/bhab039] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/17/2020] [Revised: 01/15/2021] [Accepted: 02/05/2021] [Indexed: 12/20/2022] Open
Abstract
The diverse cerebral consequences of preterm birth create significant challenges for understanding pathogenesis or predicting later outcome. Instead of focusing on describing effects common to the group, comparing individual infants against robust normative data offers a powerful alternative to study brain maturation. Here we used Gaussian process regression to create normative curves characterizing brain volumetric development in 274 term-born infants, modeling for age at scan and sex. We then compared 89 preterm infants scanned at term-equivalent age with these normative charts, relating individual deviations from typical volumetric development to perinatal risk factors and later neurocognitive scores. To test generalizability, we used a second independent dataset comprising of 253 preterm infants scanned using different acquisition parameters and scanner. We describe rapid, nonuniform brain growth during the neonatal period. In both preterm cohorts, cerebral atypicalities were widespread, often multiple, and varied highly between individuals. Deviations from normative development were associated with respiratory support, nutrition, birth weight, and later neurocognition, demonstrating their clinical relevance. Group-level understanding of the preterm brain disguises a large degree of individual differences. We provide a method and normative dataset that offer a more precise characterization of the cerebral consequences of preterm birth by profiling the individual neonatal brain.
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Affiliation(s)
- Ralica Dimitrova
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King’s College London, London SE1 7EH, UK
- Department of Forensic and Neurodevelopmental Sciences, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London SE5 8AF, UK
| | - Sophie Arulkumaran
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King’s College London, London SE1 7EH, UK
| | - Olivia Carney
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King’s College London, London SE1 7EH, UK
| | - Andrew Chew
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King’s College London, London SE1 7EH, UK
| | - Shona Falconer
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King’s College London, London SE1 7EH, UK
| | - Judit Ciarrusta
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King’s College London, London SE1 7EH, UK
- Department of Forensic and Neurodevelopmental Sciences, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London SE5 8AF, UK
| | - Thomas Wolfers
- Donders Centre for Cognitive Neuroimaging, Donders Institute for Brain, Cognition and Behaviour, Radboud University, Nijmegen 6525EN, the Netherlands
- Department of Cognitive Neuroscience, Radboud University Medical Centre, Nijmegen 6525EN, the Netherlands
| | - Dafnis Batalle
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King’s College London, London SE1 7EH, UK
- Department of Forensic and Neurodevelopmental Sciences, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London SE5 8AF, UK
| | - Lucilio Cordero-Grande
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King’s College London, London SE1 7EH, UK
- Biomedical Image Technologies, ETSI Telecomunicacion, Universidad Politecnica de Madrid and CIBER-BBN, Madrid 28040, Spain
| | - Anthony N Price
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King’s College London, London SE1 7EH, UK
| | - Rui P A G Teixeira
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King’s College London, London SE1 7EH, UK
| | - Emer Hughes
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King’s College London, London SE1 7EH, UK
| | - Alexia Egloff
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King’s College London, London SE1 7EH, UK
| | - Jana Hutter
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King’s College London, London SE1 7EH, UK
| | - Antonios Makropoulos
- Biomedical Image Analysis Group, Department of Computing, Imperial College London, London SW7 2AZ, UK
| | - Emma C Robinson
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King’s College London, London SE1 7EH, UK
| | - Andreas Schuh
- Biomedical Image Analysis Group, Department of Computing, Imperial College London, London SW7 2AZ, UK
| | - Katy Vecchiato
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King’s College London, London SE1 7EH, UK
- Department of Forensic and Neurodevelopmental Sciences, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London SE5 8AF, UK
| | - Johannes K Steinweg
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King’s College London, London SE1 7EH, UK
| | - Russell Macleod
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King’s College London, London SE1 7EH, UK
| | - Andre F Marquand
- Donders Centre for Cognitive Neuroimaging, Donders Institute for Brain, Cognition and Behaviour, Radboud University, Nijmegen 6525EN, the Netherlands
- Department of Cognitive Neuroscience, Radboud University Medical Centre, Nijmegen 6525EN, the Netherlands
| | - Grainne McAlonan
- Department of Forensic and Neurodevelopmental Sciences, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London SE5 8AF, UK
- MRC Centre for Neurodevelopmental Disorders, King’s College London, London SE1 1UL, UK
- South London and Maudsley NHS Foundation Trust, London SE5 8AZ, UK
| | - Mary A Rutherford
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King’s College London, London SE1 7EH, UK
| | - Serena J Counsell
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King’s College London, London SE1 7EH, UK
| | - Stephen M Smith
- Centre for Functional MRI of the Brain (FMRIB), Wellcome Centre for Integrative Neuroimaging, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford OX3 9DU, UK
| | - Daniel Rueckert
- Biomedical Image Analysis Group, Department of Computing, Imperial College London, London SW7 2AZ, UK
| | - Joseph V Hajnal
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King’s College London, London SE1 7EH, UK
| | - Jonathan O’Muircheartaigh
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King’s College London, London SE1 7EH, UK
- Department of Forensic and Neurodevelopmental Sciences, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London SE5 8AF, UK
- MRC Centre for Neurodevelopmental Disorders, King’s College London, London SE1 1UL, UK
| | - A David Edwards
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King’s College London, London SE1 7EH, UK
- MRC Centre for Neurodevelopmental Disorders, King’s College London, London SE1 1UL, UK
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10
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Bonthrone AF, Dimitrova R, Chew A, Kelly CJ, Cordero-Grande L, Carney O, Egloff A, Hughes E, Vecchiato K, Simpson J, Hajnal JV, Pushparajah K, Victor S, Nosarti C, Rutherford MA, Edwards AD, O’Muircheartaigh J, Counsell SJ. Individualized brain development and cognitive outcome in infants with congenital heart disease. Brain Commun 2021; 3:fcab046. [PMID: 33860226 PMCID: PMC8032964 DOI: 10.1093/braincomms/fcab046] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/15/2020] [Revised: 01/29/2021] [Accepted: 02/15/2021] [Indexed: 11/13/2022] Open
Abstract
Infants with congenital heart disease are at risk of neurodevelopmental impairments, the origins of which are currently unclear. This study aimed to characterize the relationship between neonatal brain development, cerebral oxygen delivery and neurodevelopmental outcome in infants with congenital heart disease. A cohort of infants with serious or critical congenital heart disease (N = 66; N = 62 born ≥37 weeks) underwent brain MRI before surgery on a 3T scanner situated on the neonatal unit. T2-weighted images were segmented into brain regions using a neonatal-specific algorithm. We generated normative curves of typical volumetric brain development using a data-driven technique applied to 219 healthy infants from the Developing Human Connectome Project (dHCP). Atypicality indices, representing the degree of positive or negative deviation of a regional volume from the normative mean for a given gestational age, sex and postnatal age, were calculated for each infant with congenital heart disease. Phase contrast angiography was acquired in 53 infants with congenital heart disease and cerebral oxygen delivery was calculated. Cognitive and motor abilities were assessed at 22 months (N = 46) using the Bayley scales of Infant and Toddler Development-Third Edition. We assessed the relationship between atypicality indices, cerebral oxygen delivery and cognitive and motor outcome. Additionally, we examined whether cerebral oxygen delivery was associated with neurodevelopmental outcome through the mediating effect of brain volume. Negative atypicality indices in deep grey matter were associated with both reduced neonatal cerebral oxygen delivery and poorer cognitive abilities at 22 months across the whole sample. In infants with congenital heart disease born ≥37 weeks, negative cortical grey matter and total tissue volume atypicality indices, in addition to deep grey matter structures, were associated with poorer cognition. There was a significant indirect relationship between cerebral oxygen delivery and cognition through the mediating effect of negative deep grey matter atypicality indices across the whole sample. In infants born ≥37 weeks, cortical grey matter and total tissue volume atypicality indices were also mediators of this relationship. In summary, lower cognitive abilities in toddlers with congenital heart disease were associated with smaller grey matter volumes before cardiac surgery. The aetiology of poor cognition may encompass poor cerebral oxygen delivery leading to impaired grey matter growth. Interventions to improve cerebral oxygen delivery may promote early brain growth and improve cognitive outcomes in infants with congenital heart disease.
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Affiliation(s)
- Alexandra F Bonthrone
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King’s College London, London SE1 7EH, UK
| | - Ralica Dimitrova
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King’s College London, London SE1 7EH, UK
- Department for Forensic and Neurodevelopmental Sciences, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London SE5 8AF, UK
| | - Andrew Chew
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King’s College London, London SE1 7EH, UK
| | - Christopher J Kelly
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King’s College London, London SE1 7EH, UK
| | - Lucilio Cordero-Grande
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King’s College London, London SE1 7EH, UK
- Biomedical Image Technologies, ETSI Telecomunicación, Universidad Politécnica de Madrid and CIBER-BBN, 28040 Madrid, Spain
| | - Olivia Carney
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King’s College London, London SE1 7EH, UK
| | - Alexia Egloff
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King’s College London, London SE1 7EH, UK
| | - Emer Hughes
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King’s College London, London SE1 7EH, UK
| | - Katy Vecchiato
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King’s College London, London SE1 7EH, UK
- Department for Forensic and Neurodevelopmental Sciences, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London SE5 8AF, UK
| | - John Simpson
- Paediatric Cardiology Department, Evelina London Children’s Healthcare, London SE1 7EH, UK
| | - Joseph V Hajnal
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King’s College London, London SE1 7EH, UK
| | - Kuberan Pushparajah
- Paediatric Cardiology Department, Evelina London Children’s Healthcare, London SE1 7EH, UK
| | - Suresh Victor
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King’s College London, London SE1 7EH, UK
| | - Chiara Nosarti
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King’s College London, London SE1 7EH, UK
- Department of Child and Adolescent Psychiatry, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London SE5 8AF, UK
| | - Mary A Rutherford
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King’s College London, London SE1 7EH, UK
| | - A David Edwards
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King’s College London, London SE1 7EH, UK
| | - Jonathan O’Muircheartaigh
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King’s College London, London SE1 7EH, UK
- Department for Forensic and Neurodevelopmental Sciences, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London SE5 8AF, UK
| | - Serena J Counsell
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King’s College London, London SE1 7EH, UK
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11
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Ball G, Seidlitz J, O’Muircheartaigh J, Dimitrova R, Fenchel D, Makropoulos A, Christiaens D, Schuh A, Passerat-Palmbach J, Hutter J, Cordero-Grande L, Hughes E, Price A, Hajnal JV, Rueckert D, Robinson EC, Edwards AD. Cortical morphology at birth reflects spatiotemporal patterns of gene expression in the fetal human brain. PLoS Biol 2020; 18:e3000976. [PMID: 33226978 PMCID: PMC7721147 DOI: 10.1371/journal.pbio.3000976] [Citation(s) in RCA: 24] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/20/2020] [Revised: 12/07/2020] [Accepted: 11/02/2020] [Indexed: 02/07/2023] Open
Abstract
Interruption to gestation through preterm birth can significantly impact cortical development and have long-lasting adverse effects on neurodevelopmental outcome. We compared cortical morphology captured by high-resolution, multimodal magnetic resonance imaging (MRI) in n = 292 healthy newborn infants (mean age at birth = 39.9 weeks) with regional patterns of gene expression in the fetal cortex across gestation (n = 156 samples from 16 brains, aged 12 to 37 postconceptional weeks [pcw]). We tested the hypothesis that noninvasive measures of cortical structure at birth mirror areal differences in cortical gene expression across gestation, and in a cohort of n = 64 preterm infants (mean age at birth = 32.0 weeks), we tested whether cortical alterations observed after preterm birth were associated with altered gene expression in specific developmental cell populations. Neonatal cortical structure was aligned to differential patterns of cell-specific gene expression in the fetal cortex. Principal component analysis (PCA) of 6 measures of cortical morphology and microstructure showed that cortical regions were ordered along a principal axis, with primary cortex clearly separated from heteromodal cortex. This axis was correlated with estimated tissue maturity, indexed by differential expression of genes expressed by progenitor cells and neurons, and engaged in stem cell differentiation, neuron migration, and forebrain development. Preterm birth was associated with altered regional MRI metrics and patterns of differential gene expression in glial cell populations. The spatial patterning of gene expression in the developing cortex was thus mirrored by regional variation in cortical morphology and microstructure at term, and this was disrupted by preterm birth. This work provides a framework to link molecular mechanisms to noninvasive measures of cortical development in early life and highlights novel pathways to injury in neonatal populations at increased risk of neurodevelopmental disorder. Interruption to gestation through preterm birth can significantly impact cortical development and have long-lasting adverse effects on neurodevelopmental outcome. A large neuroimaging study of newborn infants reveals how their cortical structure at birth is associated with patterns of gene expression in the fetal cortex and how this relationship is affected by preterm birth.
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Affiliation(s)
- Gareth Ball
- Developmental Imaging, Murdoch Children’s Research Institute, Melbourne, Australia
- Centre for the Developing Brain, Department of Perinatal Imaging & Health, King’s College London, United Kingdom
- Department of Paediatrics, University of Melbourne, Melbourne, Australia
- * E-mail:
| | - Jakob Seidlitz
- Developmental Neurogenomics Unit, National Institute of Mental Health, Bethesda, United States of America
- Department of Psychiatry, University of Cambridge, United Kingdom
| | - Jonathan O’Muircheartaigh
- Centre for the Developing Brain, Department of Perinatal Imaging & Health, King’s College London, United Kingdom
| | - Ralica Dimitrova
- Centre for the Developing Brain, Department of Perinatal Imaging & Health, King’s College London, United Kingdom
| | - Daphna Fenchel
- Centre for the Developing Brain, Department of Perinatal Imaging & Health, King’s College London, United Kingdom
| | - Antonios Makropoulos
- Centre for the Developing Brain, Department of Perinatal Imaging & Health, King’s College London, United Kingdom
| | - Daan Christiaens
- Centre for the Developing Brain, Department of Perinatal Imaging & Health, King’s College London, United Kingdom
- Department of Electrical Engineering, ESAT/PSI, KU Leuven, Belgium
| | - Andreas Schuh
- Biomedical Image Analysis Group, Department of Computing, Imperial College London, United Kingdom
| | | | - Jana Hutter
- Centre for the Developing Brain, Department of Perinatal Imaging & Health, King’s College London, United Kingdom
| | - Lucilio Cordero-Grande
- Centre for the Developing Brain, Department of Perinatal Imaging & Health, King’s College London, United Kingdom
| | - Emer Hughes
- Centre for the Developing Brain, Department of Perinatal Imaging & Health, King’s College London, United Kingdom
| | - Anthony Price
- Centre for the Developing Brain, Department of Perinatal Imaging & Health, King’s College London, United Kingdom
| | - Jo V. Hajnal
- Centre for the Developing Brain, Department of Perinatal Imaging & Health, King’s College London, United Kingdom
| | - Daniel Rueckert
- Biomedical Image Analysis Group, Department of Computing, Imperial College London, United Kingdom
| | - Emma C. Robinson
- Centre for the Developing Brain, Department of Perinatal Imaging & Health, King’s College London, United Kingdom
| | - A David Edwards
- Centre for the Developing Brain, Department of Perinatal Imaging & Health, King’s College London, United Kingdom
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12
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Dimitrova R, Pietsch M, Christiaens D, Ciarrusta J, Wolfers T, Batalle D, Hughes E, Hutter J, Cordero-Grande L, Price AN, Chew A, Falconer S, Vecchiato K, Steinweg JK, Carney O, Rutherford MA, Tournier JD, Counsell SJ, Marquand AF, Rueckert D, Hajnal JV, McAlonan G, Edwards AD, O’Muircheartaigh J. Heterogeneity in Brain Microstructural Development Following Preterm Birth. Cereb Cortex 2020; 30:4800-4810. [PMID: 32306044 PMCID: PMC7391275 DOI: 10.1093/cercor/bhaa069] [Citation(s) in RCA: 40] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/28/2019] [Revised: 01/24/2020] [Accepted: 02/23/2020] [Indexed: 01/08/2023] Open
Abstract
Preterm-born children are at increased risk of lifelong neurodevelopmental difficulties. Group-wise analyses of magnetic resonance imaging show many differences between preterm- and term-born infants but do not reliably predict neurocognitive prognosis for individual infants. This might be due to the unrecognized heterogeneity of cerebral injury within the preterm group. This study aimed to determine whether atypical brain microstructural development following preterm birth is significantly variable between infants. Using Gaussian process regression, a technique that allows a single-individual inference, we characterized typical variation of brain microstructure using maps of fractional anisotropy and mean diffusivity in a sample of 270 term-born neonates. Then, we compared 82 preterm infants to these normative values to identify brain regions with atypical microstructure and relate observed deviations to degree of prematurity and neurocognition at 18 months. Preterm infants showed strikingly heterogeneous deviations from typical development, with little spatial overlap between infants. Greater and more extensive deviations, captured by a whole brain atypicality index, were associated with more extreme prematurity and predicted poorer cognitive and language abilities at 18 months. Brain microstructural development after preterm birth is highly variable between individual infants. This poorly understood heterogeneity likely relates to both the etiology and prognosis of brain injury.
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Affiliation(s)
- Ralica Dimitrova
- Centre for the Developing Brain, Department of Perinatal Imaging and Health, School of Biomedical Engineering and Imaging Sciences, King’s College London, London, SE1 7EH, UK
- Department for Forensic and Neurodevelopmental Sciences, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London, SE5 8AF, UK
| | - Maximilian Pietsch
- Centre for the Developing Brain, Department of Perinatal Imaging and Health, School of Biomedical Engineering and Imaging Sciences, King’s College London, London, SE1 7EH, UK
| | - Daan Christiaens
- Centre for the Developing Brain, Department of Perinatal Imaging and Health, School of Biomedical Engineering and Imaging Sciences, King’s College London, London, SE1 7EH, UK
- Department of Electrical Engineering, ESAT/PSI, KU Leuven, Leuven, 3001, Belgium
| | - Judit Ciarrusta
- Centre for the Developing Brain, Department of Perinatal Imaging and Health, School of Biomedical Engineering and Imaging Sciences, King’s College London, London, SE1 7EH, UK
- Department for Forensic and Neurodevelopmental Sciences, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London, SE5 8AF, UK
| | - Thomas Wolfers
- Donders Centre for Cognitive Neuroimaging, Donders Institute for Brain, Cognition and Behaviour, Radbound University, Nijmegen, 6525EN, the Netherlands
- Department of Cognitive Neuroscience, Radbound University Medical Centre, Nijmegen, 6525EN, the Netherlands
| | - Dafnis Batalle
- Centre for the Developing Brain, Department of Perinatal Imaging and Health, School of Biomedical Engineering and Imaging Sciences, King’s College London, London, SE1 7EH, UK
- Department for Forensic and Neurodevelopmental Sciences, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London, SE5 8AF, UK
| | - Emer Hughes
- Centre for the Developing Brain, Department of Perinatal Imaging and Health, School of Biomedical Engineering and Imaging Sciences, King’s College London, London, SE1 7EH, UK
| | - Jana Hutter
- Centre for the Developing Brain, Department of Perinatal Imaging and Health, School of Biomedical Engineering and Imaging Sciences, King’s College London, London, SE1 7EH, UK
| | - Lucilio Cordero-Grande
- Centre for the Developing Brain, Department of Perinatal Imaging and Health, School of Biomedical Engineering and Imaging Sciences, King’s College London, London, SE1 7EH, UK
- Biomedical Image Technologies, ETSI Telecomunicacion, Universidad Politecnica de Madrid and CIBER-BBN, Madrid, 28040, Spain
| | - Anthony N Price
- Centre for the Developing Brain, Department of Perinatal Imaging and Health, School of Biomedical Engineering and Imaging Sciences, King’s College London, London, SE1 7EH, UK
| | - Andrew Chew
- Centre for the Developing Brain, Department of Perinatal Imaging and Health, School of Biomedical Engineering and Imaging Sciences, King’s College London, London, SE1 7EH, UK
| | - Shona Falconer
- Centre for the Developing Brain, Department of Perinatal Imaging and Health, School of Biomedical Engineering and Imaging Sciences, King’s College London, London, SE1 7EH, UK
| | - Katy Vecchiato
- Centre for the Developing Brain, Department of Perinatal Imaging and Health, School of Biomedical Engineering and Imaging Sciences, King’s College London, London, SE1 7EH, UK
- Department for Forensic and Neurodevelopmental Sciences, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London, SE5 8AF, UK
| | - Johannes K Steinweg
- Centre for the Developing Brain, Department of Perinatal Imaging and Health, School of Biomedical Engineering and Imaging Sciences, King’s College London, London, SE1 7EH, UK
| | - Olivia Carney
- Centre for the Developing Brain, Department of Perinatal Imaging and Health, School of Biomedical Engineering and Imaging Sciences, King’s College London, London, SE1 7EH, UK
| | - Mary A Rutherford
- Centre for the Developing Brain, Department of Perinatal Imaging and Health, School of Biomedical Engineering and Imaging Sciences, King’s College London, London, SE1 7EH, UK
| | - J-Donald Tournier
- Centre for the Developing Brain, Department of Perinatal Imaging and Health, School of Biomedical Engineering and Imaging Sciences, King’s College London, London, SE1 7EH, UK
| | - Serena J Counsell
- Centre for the Developing Brain, Department of Perinatal Imaging and Health, School of Biomedical Engineering and Imaging Sciences, King’s College London, London, SE1 7EH, UK
| | - Andre F Marquand
- Donders Centre for Cognitive Neuroimaging, Donders Institute for Brain, Cognition and Behaviour, Radbound University, Nijmegen, 6525EN, the Netherlands
- Department of Cognitive Neuroscience, Radbound University Medical Centre, Nijmegen, 6525EN, the Netherlands
| | - Daniel Rueckert
- Biomedical Image Analysis Group, Department of Computing, Imperial College London, London, SW7 2AZ, UK
| | - Joseph V Hajnal
- Centre for the Developing Brain, Department of Perinatal Imaging and Health, School of Biomedical Engineering and Imaging Sciences, King’s College London, London, SE1 7EH, UK
| | - Grainne McAlonan
- Department for Forensic and Neurodevelopmental Sciences, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London, SE5 8AF, UK
- MRC Centre for Neurodevelopmental Disorders, King’s College London, London, SE1 1UL, UK
- South London and Maudsley NHS Foundation Trust, London, SE5 8AZ, UK
| | - A David Edwards
- Centre for the Developing Brain, Department of Perinatal Imaging and Health, School of Biomedical Engineering and Imaging Sciences, King’s College London, London, SE1 7EH, UK
- MRC Centre for Neurodevelopmental Disorders, King’s College London, London, SE1 1UL, UK
| | - Jonathan O’Muircheartaigh
- Centre for the Developing Brain, Department of Perinatal Imaging and Health, School of Biomedical Engineering and Imaging Sciences, King’s College London, London, SE1 7EH, UK
- Department for Forensic and Neurodevelopmental Sciences, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London, SE5 8AF, UK
- MRC Centre for Neurodevelopmental Disorders, King’s College London, London, SE1 1UL, UK
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Thompson A, Shahidiani A, Fritz A, O’Muircheartaigh J, Walker L, D’Almeida V, Murphy C, Daly E, Murphy D, Williams S, Deoni S, Ecker C. Age-related differences in white matter diffusion measures in autism spectrum condition. Mol Autism 2020; 11:36. [PMID: 32423424 PMCID: PMC7236504 DOI: 10.1186/s13229-020-00325-6] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/07/2019] [Accepted: 03/03/2020] [Indexed: 01/11/2023] Open
Abstract
BACKGROUND Autism spectrum condition (ASC) is accompanied by developmental differences in brain anatomy and connectivity. White matter differences in ASC have been widely studied with diffusion imaging but results are heterogeneous and vary across the age range of study participants and varying methodological approaches. To characterize the neurodevelopmental trajectory of white matter maturation, it is necessary to examine a broad age range of individuals on the autism spectrum and typically developing controls, and investigate age × group interactions. METHODS Here, we employed a spatially unbiased tract-based spatial statistics (TBSS) approach to examine age-related differences in white matter connectivity in a sample of 41 individuals with ASC, and 41 matched controls between 7-17 years of age. RESULTS We found significant age-related differences between the ASC and control group in widespread brain regions. This included age-related differences in the uncinate fasciculus, corticospinal tract, inferior longitudinal fasciculus, inferior fronto-occipital fasciculus, anterior thalamic radiation, superior longitudinal fasciculus and forceps major. Measures of fractional anisotropy (FA) were significantly positively associated with age in both groups. However, this relationship was significantly stronger in the ASC group relative to controls. Measures of radial diffusivity (RD) were significantly negatively associated with age in both groups, but this relationship was significantly stronger in the ASC group relative to controls. LIMITATIONS The generalisability of our findings is limited by the restriction of the sample to right-handed males with an IQ > 70. Furthermore, a longitudinal design would be required to fully investigate maturational processes across this age group. CONCLUSIONS Taken together, our findings suggest that autistic males have an altered trajectory of white matter maturation relative to controls. Future longitudinal analyses are required to further characterize the extent and time course of these differences.
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Affiliation(s)
- Abigail Thompson
- Department of Forensic & Neurodevelopmental Sciences, Institute of Psychiatry, Psychology & Neuroscience, King’s College London, London, UK
- Developmental Change & Plasticity Lab, Department of Psychology & Language Sciences, University College London, 26 Bedford Way, Bloomsbury, London, WC1H 0AP UK
| | - Asal Shahidiani
- Department of Forensic & Neurodevelopmental Sciences, Institute of Psychiatry, Psychology & Neuroscience, King’s College London, London, UK
| | - Anne Fritz
- The Centre for Research in Autism and Education (CRAE), Psychology and Human Development, UCL, London, UK
| | - Jonathan O’Muircheartaigh
- Department of Forensic & Neurodevelopmental Sciences, Institute of Psychiatry, Psychology & Neuroscience, King’s College London, London, UK
- Centre for the Developing Brain, Department of Perinatal Imaging and Health, St. Thomas’ Hospital, King’s College London, London, UK
- MRC Centre for Neurodevelopmental Disorders, King’s College London, London, UK
| | - Lindsay Walker
- Advanced Baby Imaging Lab, Hasbro Childrens Hospital, Providence, RI USA
- Pediatrics and Radiology, Warren Alpert medical school, Brown University, Providence, USA
| | - Vera D’Almeida
- Department of Forensic & Neurodevelopmental Sciences, Institute of Psychiatry, Psychology & Neuroscience, King’s College London, London, UK
| | - Clodagh Murphy
- Department of Forensic & Neurodevelopmental Sciences, Institute of Psychiatry, Psychology & Neuroscience, King’s College London, London, UK
| | - Eileen Daly
- Department of Forensic & Neurodevelopmental Sciences, Institute of Psychiatry, Psychology & Neuroscience, King’s College London, London, UK
| | - Declan Murphy
- Department of Forensic & Neurodevelopmental Sciences, Institute of Psychiatry, Psychology & Neuroscience, King’s College London, London, UK
- MRC Centre for Neurodevelopmental Disorders, King’s College London, London, UK
| | - Steve Williams
- Department of Neuroimaging, Institute of Psychiatry, Psychology & Neuroscience, King’s College London, London, UK
- MRC Centre for Neurodevelopmental Disorders, King’s College London, London, UK
| | - Sean Deoni
- Advanced Baby Imaging Lab, Hasbro Childrens Hospital, Providence, RI USA
- Pediatrics and Radiology, Warren Alpert medical school, Brown University, Providence, USA
- Maternal, Newborn & Child Health Discovery & Tools at the Bill and Melinda Gates Foundation, Seattle, USA
| | - Christine Ecker
- Department of Forensic & Neurodevelopmental Sciences, Institute of Psychiatry, Psychology & Neuroscience, King’s College London, London, UK
- Department of Child and Adolescent Psychiatry, Psychosomatics and Psychotherapy, University Hospital, Goethe University Frankfurt am Main, Deutschordenstrasse 50, 60528 Frankfurt am Main, Germany
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14
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Wolfers T, Floris DL, Dinga R, van Rooij D, Isakoglou C, Kia SM, Zabihi M, Llera A, Chowdanayaka R, Kumar VJ, Peng H, Laidi C, Batalle D, Dimitrova R, Charman T, Loth E, Lai MC, Jones E, Baumeister S, Moessnang C, Banaschewski T, Ecker C, Dumas G, O’Muircheartaigh J, Murphy D, Buitelaar JK, Marquand AF, Beckmann CF. From pattern classification to stratification: towards conceptualizing the heterogeneity of Autism Spectrum Disorder. Neurosci Biobehav Rev 2019; 104:240-254. [DOI: 10.1016/j.neubiorev.2019.07.010] [Citation(s) in RCA: 54] [Impact Index Per Article: 10.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/15/2019] [Revised: 07/10/2019] [Accepted: 07/15/2019] [Indexed: 11/17/2022]
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Hutter J, Slator PJ, Jackson L, Gomes ADS, Ho A, Story L, O’Muircheartaigh J, Teixeira RPAG, Chappell LC, Alexander DC, Rutherford MA, Hajnal JV. Multi-modal functional MRI to explore placental function over gestation. Magn Reson Med 2019; 81:1191-1204. [PMID: 30242899 PMCID: PMC6585747 DOI: 10.1002/mrm.27447] [Citation(s) in RCA: 48] [Impact Index Per Article: 9.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/15/2018] [Revised: 06/08/2018] [Accepted: 06/12/2018] [Indexed: 01/16/2023]
Abstract
PURPOSE To investigate, visualize and quantify the physiology of the human placenta in several dimensions - functional, temporal over gestation, and spatial over the whole organ. METHODS Bespoke MRI techniques, combining a rich diffusion protocol, anatomical data and T2* mapping together with a multi-modal pipeline including motion correction and extracted quantitative features were developed and employed on pregnant women between 22 and 38 weeks gestational age including two pregnancies diagnosed with pre-eclampsia. RESULTS A multi-faceted assessment was demonstrated showing trends of increasing lacunarity, and decreasing T2* and diffusivity over gestation. CONCLUSIONS The obtained multi-modal acquisition and quantification shows promising opportunities for studying evolution, adaptation and compensation processes.
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Affiliation(s)
- Jana Hutter
- Centre for the Developing BrainKing's College LondonUnited Kingdom
- Biomedical Engineering DepartmentKing's College LondonUnited Kingdom
| | - Paddy J. Slator
- Biomedical Engineering DepartmentKing's College LondonUnited Kingdom
| | - Laurence Jackson
- Centre for the Developing BrainKing's College LondonUnited Kingdom
- Biomedical Engineering DepartmentKing's College LondonUnited Kingdom
| | - Ana Dos Santos Gomes
- Centre for the Developing BrainKing's College LondonUnited Kingdom
- Biomedical Engineering DepartmentKing's College LondonUnited Kingdom
| | - Alison Ho
- Women's Health Academic CentreKing's College LondonLondonUnited Kingdom
| | - Lisa Story
- Centre for the Developing BrainKing's College LondonUnited Kingdom
- Women's Health Academic CentreKing's College LondonLondonUnited Kingdom
| | | | - Rui P. A. G. Teixeira
- Centre for the Developing BrainKing's College LondonUnited Kingdom
- Biomedical Engineering DepartmentKing's College LondonUnited Kingdom
| | - Lucy C. Chappell
- Women's Health Academic CentreKing's College LondonLondonUnited Kingdom
| | - Daniel C. Alexander
- Centre for Medical Image Computing and Department of Computer ScienceUniversity College LondonUnited Kingdom
| | | | - Joseph V. Hajnal
- Centre for the Developing BrainKing's College LondonUnited Kingdom
- Biomedical Engineering DepartmentKing's College LondonUnited Kingdom
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Chevalier N, Kurth S, Doucette MR, Wiseheart M, Deoni SCL, Dean DC, O’Muircheartaigh J, Blackwell KA, Munakata Y, LeBourgeois MK. Myelination Is Associated with Processing Speed in Early Childhood: Preliminary Insights. PLoS One 2015; 10:e0139897. [PMID: 26440654 PMCID: PMC4595421 DOI: 10.1371/journal.pone.0139897] [Citation(s) in RCA: 49] [Impact Index Per Article: 5.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/21/2015] [Accepted: 09/18/2015] [Indexed: 11/22/2022] Open
Abstract
Processing speed is an important contributor to working memory performance and fluid intelligence in young children. Myelinated white matter plays a central role in brain messaging, and likely mediates processing speed, but little is known about the relationship between myelination and processing speed in young children. In the present study, processing speed was measured through inspection times, and myelin volume fraction (VFM) was quantified using a multicomponent magnetic resonance imaging (MRI) approach in 2- to 5-years of age. Both inspection times and VFM were found to increase with age. Greater VFM in the right and left occipital lobes, the body of the corpus callosum, and the right cerebellum was significantly associated with shorter inspection times, after controlling for age. A hierarchical regression showed that VFM in the left occipital lobe predicted inspection times over and beyond the effects of age and the VFM in the other brain regions. These findings are consistent with the hypothesis that myelin supports processing speed in early childhood.
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Affiliation(s)
- Nicolas Chevalier
- Department of Psychology, University of Edinburgh, Edinburgh, United Kingdom
- * E-mail:
| | - Salome Kurth
- Department of Integrative Physiology, University of Colorado Boulder, Boulder, Colorado, United States of America
| | - Margaret Rae Doucette
- Department of Integrative Physiology, University of Colorado Boulder, Boulder, Colorado, United States of America
| | - Melody Wiseheart
- Department of Psychology, York University, Toronto, Ontario, Canada
| | - Sean C. L. Deoni
- Brown University School of Engineering, Providence, Rhodes Island, United States of America
| | - Douglas C. Dean
- Brown University School of Engineering, Providence, Rhodes Island, United States of America
| | | | - Katharine A. Blackwell
- Department of Psychology, Salem College, Winston-Salem, North Carolina, United States of America
| | - Yuko Munakata
- Department of Psychology and Neuroscience, University of Colorado Boulder, Boulder, Colorado, United States of America
| | - Monique K. LeBourgeois
- Department of Integrative Physiology, University of Colorado Boulder, Boulder, Colorado, United States of America
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Dean DC, Dirks H, O’Muircheartaigh J, Walker L, Jerskey BA, Lehman K, Han M, Waskiewicz N, Deoni SCL. Pediatric neuroimaging using magnetic resonance imaging during non-sedated sleep. Pediatr Radiol 2014; 44:64-72. [PMID: 23917588 PMCID: PMC3889986 DOI: 10.1007/s00247-013-2752-8] [Citation(s) in RCA: 91] [Impact Index Per Article: 9.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/12/2013] [Revised: 05/30/2013] [Accepted: 06/24/2013] [Indexed: 01/08/2023]
Abstract
BACKGROUND Etiological studies of many neurological and psychiatric disorders are increasingly turning toward longitudinal investigations of infant brain development in order to discern predisposing structural and/or functional differences prior to the onset of overt clinical symptoms. While MRI provides a noninvasive window into the developing brain, MRI of infants and toddlers is challenging due to the modality's extreme motion sensitivity and children's difficulty in remaining still during image acquisition. OBJECTIVE Here, we outline a broad research protocol for successful MRI of children under 4 years of age during natural, non-sedated sleep. MATERIALS AND METHODS All children were imaged during natural, non-sedated sleep. Active and passive measures to reduce acoustic noise were implemented to reduce the likelihood of the children waking up during acquisition. Foam cushions and vacuum immobilizers were used to limit intra-scan motion artifacts. RESULTS More than 380 MRI datasets have been successfully acquired from 220 children younger than 4 years of age within the past 39 months. Implemented measures permitted children to remain asleep for the duration of the scan and allowed the data to be acquired with an overall 97% success rate. CONCLUSION The proposed method greatly advances current pediatric imaging techniques and may be readily implemented in other research and clinical settings to facilitate and further improve pediatric neuroimaging.
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Affiliation(s)
- Douglas C. Dean
- Advanced Baby Imaging Lab, School of Engineering, Brown University, Providence, RI 02912 USA
| | - Holly Dirks
- Advanced Baby Imaging Lab, School of Engineering, Brown University, Providence, RI 02912 USA
| | - Jonathan O’Muircheartaigh
- Advanced Baby Imaging Lab, School of Engineering, Brown University, Providence, RI 02912 USA ,Department of NeuroImaging Sciences, King’s College London, Institute of Psychiatry, Delaware Crespigny Park, London, UK
| | - Lindsay Walker
- Advanced Baby Imaging Lab, School of Engineering, Brown University, Providence, RI 02912 USA
| | - Beth A. Jerskey
- Department of Human Behaviour and Psychiatry, Warren Alpert Medical School, Brown University, Providence, RI USA
| | - Katie Lehman
- Advanced Baby Imaging Lab, School of Engineering, Brown University, Providence, RI 02912 USA
| | - Michelle Han
- Advanced Baby Imaging Lab, School of Engineering, Brown University, Providence, RI 02912 USA
| | - Nicole Waskiewicz
- Advanced Baby Imaging Lab, School of Engineering, Brown University, Providence, RI 02912 USA
| | - Sean C. L. Deoni
- Advanced Baby Imaging Lab, School of Engineering, Brown University, Providence, RI 02912 USA
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18
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Sugranyes G, Kyriakopoulos M, Dima D, O’Muircheartaigh J, Corrigall R, Pendelbury G, Hayes D, Calhoun VD, Frangou S. Multimodal analyses identify linked functional and white matter abnormalities within the working memory network in schizophrenia. Schizophr Res 2012; 138:136-42. [PMID: 22475381 PMCID: PMC4429523 DOI: 10.1016/j.schres.2012.03.011] [Citation(s) in RCA: 46] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/26/2011] [Revised: 03/02/2012] [Accepted: 03/06/2012] [Indexed: 11/19/2022]
Abstract
BACKGROUND Dysconnectivity between brain regions is thought to underlie the cognitive abnormalities that characterise schizophrenia (SZ). Consistent with this notion functional magnetic resonance imaging (fMRI) and diffusion tensor imaging (DTI) studies in SZ have reliably provided evidence of abnormalities in functional integration and in white matter connectivity. Yet little is known about how alterations at the functional level related to abnormalities in anatomical connectivity. METHODS We obtained fMRI data during the 2-back working memory task from 25 patients with SZ and 19 healthy controls matched for age, sex and IQ. DTI data were also acquired in the same session. In addition to conventional unimodal analyses we extracted "features" [contrast maps for fMRI and fractional anisotropy (FA) for DTI] that were subjected to joint independent component analysis (JICA) in order to examine interactions between fMRI and DTI data sources. RESULTS Conventional unimodal analyses revealed both functional and structural deficits in patients with SZ. The JICA identified regions of joint, multimodal brain sources that differed in patients and controls. The fMRI source implicated regions within the anterior cingulate and ventrolateral prefrontal cortex and in the cuneus where patients showed relative hypoactivation and within the frontopolar cortex where patients showed relative hyperactivation. The DTI source localised reduced FA in patients in the splenium and posterior cingulum. CONCLUSIONS This study promotes our understanding of structure-function relationships in SZ by characterising linked functional and white matter changes that contribute to working memory dysfunction in this disorder.
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Affiliation(s)
- Gisela Sugranyes
- Section of Neurobiology of Psychosis, Dept. of Psychosis Studies, Institute of Psychiatry, King’s College London, UK
- Child and Adolescent Mental Health Services, South London and Maudsley NHS Foundation Trust, UK
- Department of Child and Adolescent Psychiatry and Psychology, Institute of Neuroscience, Hospital Clinic of Barcelona, Spain
| | - Marinos Kyriakopoulos
- Section of Neurobiology of Psychosis, Dept. of Psychosis Studies, Institute of Psychiatry, King’s College London, UK
- Child and Adolescent Mental Health Services, South London and Maudsley NHS Foundation Trust, UK
| | - Danai Dima
- Section of Neurobiology of Psychosis, Dept. of Psychosis Studies, Institute of Psychiatry, King’s College London, UK
| | | | - Richard Corrigall
- Child and Adolescent Mental Health Services, South London and Maudsley NHS Foundation Trust, UK
| | - Gabrielle Pendelbury
- Section of Neurobiology of Psychosis, Dept. of Psychosis Studies, Institute of Psychiatry, King’s College London, UK
| | - Daniel Hayes
- Child and Adolescent Mental Health Services, South London and Maudsley NHS Foundation Trust, UK
| | - Vince D. Calhoun
- The Mind Research Network, Albuquerque, NM, USA
- Department of Electrical and Computer Engineering, University of New Mexico, Albuquerque, NM, USA
- Dept. of Psychiatry, Yale University School of Medicine, New Haven, CT, USA
| | - Sophia Frangou
- Section of Neurobiology of Psychosis, Dept. of Psychosis Studies, Institute of Psychiatry, King’s College London, UK
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19
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O’Muircheartaigh J, Richardson MP. Epilepsy and the frontal lobes. Cortex 2012; 48:144-55. [DOI: 10.1016/j.cortex.2011.11.012] [Citation(s) in RCA: 39] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/23/2010] [Revised: 03/19/2011] [Accepted: 06/27/2011] [Indexed: 10/15/2022]
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20
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Vulliemoz S, Vollmar C, Koepp MJ, Yogarajah M, O’Muircheartaigh J, Carmichael DW, Stretton J, Richardson MP, Symms MR, Duncan JS. Connectivity of the supplementary motor area in juvenile myoclonic epilepsy and frontal lobe epilepsy. Epilepsia 2010; 52:507-14. [DOI: 10.1111/j.1528-1167.2010.02770.x] [Citation(s) in RCA: 72] [Impact Index Per Article: 5.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
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