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Arshad NH, Abu Hassan H, Omar NF, Zainudin Z. Quantifying myelin in neonates using magnetic resonance imaging: a systematic literature review. Clin Exp Pediatr 2024; 67:371-385. [PMID: 38062713 PMCID: PMC11298773 DOI: 10.3345/cep.2023.00514] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/29/2023] [Revised: 08/11/2023] [Accepted: 08/12/2023] [Indexed: 08/03/2024] Open
Abstract
This review aimed to assess the usefulness of various magnetic resonance imaging (MRI) techniques for the quantification of neonatal white matter myelination. The Scopus, PubMed, and Web of Science databases were searched to identify studies following the PRISMA (preferred reporting items for systematic reviews and meta-analyses) statement using quantitative MRI techniques to examine samples collected from neonates to quantify myelin. Twelve studies were ultimately included. The results demonstrated that in validation studies, relaxometry is the most frequently explored approach (83.33%), followed by magnetization transfer imaging (8.33%) and a new automatic segmentation technique (8.33%). Synthetic MRI is recommended for quantifying myelin in neonates because of several advantages that outweigh a few negligible limitations.
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Affiliation(s)
- Nabila Hanem Arshad
- Department of Radiology, Faculty of Medicine and Health Sciences, Universiti Putra Malaysia, Selangor, Malaysia
- Department of Radiology, Hospital Sultan Abdul Aziz Shah, Universiti Putra Malaysia, Selangor, Malaysia
| | - Hasyma Abu Hassan
- Department of Radiology, Faculty of Medicine and Health Sciences, Universiti Putra Malaysia, Selangor, Malaysia
| | - Nur Farhayu Omar
- Department of Radiology, Faculty of Medicine and Health Sciences, Universiti Putra Malaysia, Selangor, Malaysia
| | - Zurina Zainudin
- Department of Paediatrics, Faculty of Medicine and Health Sciences, Universiti Putra Malaysia, Selangor, Malaysia
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2
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Laureano B, Irzan H, O'Reilly H, Ourselin S, Marlow N, Melbourne A. Myelination of preterm brain networks at adolescence. Magn Reson Imaging 2024; 105:114-124. [PMID: 37984490 DOI: 10.1016/j.mri.2023.11.001] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/09/2022] [Revised: 10/31/2023] [Accepted: 11/04/2023] [Indexed: 11/22/2023]
Abstract
Prematurity and preterm stressors severely affect the development of infants born before 37 weeks of gestation, with increasing effects seen at earlier gestations. Although preterm mortality rates have declined due to the advances in neonatal care, disability rates, especially in middle-income settings, continue to grow. With the advances in MR imaging technology, there has been a focus on safely imaging the preterm brain to better understand its development and discover the brain regions and networks affected by prematurity. Such studies aim to support interventions and improve the neurodevelopment of preterm infants and deliver accurate prognoses. Few studies, however, have focused on the fully developed brain of preterm born infants, especially in extremely preterm subjects. To assess the long-term effect of prematurity on the adult brain, myelin related biomarkers such as myelin water fraction and g-ratio are measured for a cohort of 19-year-old extremely preterm born subjects. Using multi-modal imaging techniques that combine T2 relaxometry and neurite density information, the results show that specific brain regions associated with white matter injuries due to preterm birth, such as the posterior limb of the internal capsule and corpus callosum, are still less myelinated in adulthood. Furthermore, a weak positive relationship between myelin water fraction values and Full-Scale Intelligence Quotient (FSIQ) scores was found in multiple brain regions previously defined as less myelinated in the Extremely Preterm (EPT) cohort. These findings might suggest altered connectivity in the adult preterm brain and explain differences in cognitive outcomes.
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Affiliation(s)
- Beatriz Laureano
- School of Biomedical Engineering & Imaging Sciences, King's College London, UK.
| | - Hassna Irzan
- School of Biomedical Engineering & Imaging Sciences, King's College London, UK; Dept. of Medical Physics and Biomedical Engineering, University College London, London, UK
| | - Helen O'Reilly
- Children's Disability Network Team, St. Michael's House, Dublin, Ireland
| | - Sebastian Ourselin
- School of Biomedical Engineering & Imaging Sciences, King's College London, UK; Dept. of Medical Physics and Biomedical Engineering, University College London, London, UK
| | - Neil Marlow
- Institute for Women's Health, University College London, London, UK
| | - Andrew Melbourne
- School of Biomedical Engineering & Imaging Sciences, King's College London, UK; Dept. of Medical Physics and Biomedical Engineering, University College London, London, UK
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3
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Dong Y, Deng X, Xie M, Yu L, Qian L, Chen G, Zhang Y, Tang Y, Zhou Z, Long L. Gestational age-related changes in relaxation times of neonatal brain by quantitative synthetic magnetic resonance imaging. Brain Behav 2023:e3068. [PMID: 37248768 DOI: 10.1002/brb3.3068] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/08/2022] [Revised: 03/24/2023] [Accepted: 05/03/2023] [Indexed: 05/31/2023] Open
Abstract
OBJECTIVE This study aimed to explore the correlation between T1 and T2 relaxation times of synthetic MRI (SyMRI) and gestational age (GA) in each hemisphere of preterm and term newborns at the initial 28 days of birth. METHODS Seventy preterm and full-term infants were prospectively included in this study. All subjects completed 3.0 T routine MRI and SyMRI (MAGiC) one-stop scanning within 28 days of birth (aged 34-42 W at examination). The SyMRI postprocessing software (v8.0.4) was used to measure the T1 and T2 relaxation values of each brain region. The linear regression equations of quantitative relaxation values with GA were established to compare the variation speed in each brain region. RESULTS A significant linear and negative correlation was found between relaxation times and GA in the neonate cerebral cortex and subcortical gray and white matter regions (All p<.05). The relaxation time of the left centrum semiovale decreased with maximum variance with increasing GA among all white matter regions (T1: b = -51.45, β = -0.65, p < .0001; T2: b = -8.77, β = -0.71, p < .0001), whereas the right posterior limb of internal capsule showed minimal variance (T1: b = -27.94, β = -0.60, p < .0001; T2: b = -3.25, β = -0.68, p < .0001). Among all gray matter regions, the right globus pallidus and thalamus indicated the most significant decreasing degree of T1 and T2 relaxation values with GA (right globus pallidus T1: b = -33.14, β = -0.64, p < .0001; right thalamus T2: b = -3.94, β = -0.81, p < .0001), and the right and left occipital lobes indicated the least significant decreasing degree of T1 and T2 relaxation values with GA, respectively (right occipital lobes T1: b = -11.18, β = -0.26, p = .028; left occipital lobes T2: b = -1.22, β = -0.27, p = .024). CONCLUSIONS SyMRI could quantitatively evaluate the linear changes of T1 and T2 relaxation values with GA in brain gray and white matter of preterm and term neonates.
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Affiliation(s)
- Yan Dong
- Department of Radiology, The First Affiliated Hospital of Guangxi Medical University, Nanning, China
- Department of Radiology, Affiliated Hospital of Guilin Medical University, Guilin Medical University, Guilin, China
| | - Xianyu Deng
- Department of Cardiovascular, Guilin People's Hospital, Guilin, China
| | - Meizhen Xie
- Department of Radiology, The First Affiliated Hospital of Guangxi Medical University, Nanning, China
| | - Lan Yu
- Department of Radiology, The First Affiliated Hospital of Guangxi Medical University, Nanning, China
| | - Long Qian
- Department of Biomedical Engineering, College of Engineering, Peking University, Beijing, China
| | - Ge Chen
- Department of Radiology, Affiliated Hospital of Guilin Medical University, Guilin Medical University, Guilin, China
| | - Yali Zhang
- Department of Radiology, Affiliated Hospital of Guilin Medical University, Guilin Medical University, Guilin, China
| | - Yanyun Tang
- Department of Radiology, Affiliated Hospital of Guilin Medical University, Guilin Medical University, Guilin, China
| | - Zhipeng Zhou
- Department of Radiology, Affiliated Hospital of Guilin Medical University, Guilin Medical University, Guilin, China
| | - Liling Long
- Department of Radiology, The First Affiliated Hospital of Guangxi Medical University, Nanning, China
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4
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Song Y, Lally PJ, Yanez Lopez M, Oeltzschner G, Nebel MB, Gagoski B, Kecskemeti S, Hui SCN, Zöllner HJ, Shukla D, Arichi T, De Vita E, Yedavalli V, Thayyil S, Fallin D, Dean DC, Grant PE, Wisnowski JL, Edden RAE. Edited magnetic resonance spectroscopy in the neonatal brain. Neuroradiology 2022; 64:217-232. [PMID: 34654960 PMCID: PMC8887832 DOI: 10.1007/s00234-021-02821-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/13/2021] [Accepted: 09/20/2021] [Indexed: 10/20/2022]
Abstract
J-difference-edited spectroscopy is a valuable approach for the detection of low-concentration metabolites with magnetic resonance spectroscopy (MRS). Currently, few edited MRS studies are performed in neonates due to suboptimal signal-to-noise ratio, relatively long acquisition times, and vulnerability to motion artifacts. Nonetheless, the technique presents an exciting opportunity in pediatric imaging research to study rapid maturational changes of neurotransmitter systems and other metabolic systems in early postnatal life. Studying these metabolic processes is vital to understanding the widespread and rapid structural and functional changes that occur in the first years of life. The overarching goal of this review is to provide an introduction to edited MRS for neonates, including the current state-of-the-art in editing methods and editable metabolites, as well as to review the current literature applying edited MRS to the neonatal brain. Existing challenges and future opportunities, including the lack of age-specific reference data, are also discussed.
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Affiliation(s)
- Yulu Song
- Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, MD, USA.,F. M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, USA
| | - Peter J Lally
- Department of Brain Sciences, Imperial College London, London, UK
| | - Maria Yanez Lopez
- Center for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK
| | - Georg Oeltzschner
- Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, MD, USA.,F. M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, USA
| | - Mary Beth Nebel
- Center for Neurodevelopmental and Imaging Research, Kennedy Krieger Institute, Baltimore, MD, 21205, USA.,Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Borjan Gagoski
- Department of Radiology, Division of Neuroradiology, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA.,Fetal Neonatal Neuroimaging and Developmental Science Center, Boston Children's Hospital, Boston, MA, USA
| | | | - Steve C N Hui
- Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, MD, USA.,F. M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, USA
| | - Helge J Zöllner
- Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, MD, USA.,F. M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, USA
| | - Deepika Shukla
- Centre for Perinatal Neuroscience, Department of Brain Sciences, Imperial College London, London, UK
| | - Tomoki Arichi
- Center for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK.,Department of Bioengineering, Imperial College London, South Kensington Campus, London, UK
| | - Enrico De Vita
- Center for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK.,Biomedical Engineering Department, School of Biomedical Engineering and Imaging Sciences, St Thomas's Hospital, Westminster Bridge Road, Lambeth Wing, 3rd Floor, London, SE1 7EH, UK
| | - Vivek Yedavalli
- Division of Neuroradiology, Park 367G, The Johns Hopkins University School of Medicine, 600 N. Wolfe St. B-112 D, Baltimore, MD, 21287, USA
| | - Sudhin Thayyil
- Centre for Perinatal Neuroscience, Department of Brain Sciences, Imperial College London, London, UK
| | - Daniele Fallin
- Wendy Klag Center for Autism and Developmental Disabilities, Johns Hopkins University, Baltimore, USA.,Department of Mental Health, Bloomberg School of Public Health, Johns Hopkins University, Baltimore, USA
| | - Douglas C Dean
- Waisman Center, University of WI-Madison, Madison, WI, 53705, USA.,Department of Pediatrics, Division of Neonatology and Newborn Nursery, University of WI-Madison, School of Medicine and Public Health, Madison, WI, 53705, USA.,Department of Medical Physics, University of WI-Madison, School of Medicine and Public Health, Madison, WI, 53705, USA
| | - P Ellen Grant
- Department of Radiology, Division of Neuroradiology, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA.,Fetal Neonatal Neuroimaging and Developmental Science Center, Boston Children's Hospital, Boston, MA, USA.,Department of Medicine, Division of Newborn Medicine, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA
| | - Jessica L Wisnowski
- Children's Hospital Los Angeles, Los Angeles, CA, 90027, USA.,Department of Radiology and Fetal and Neonatal Institute, CHLA Division of Neonatology, Department of Pediatrics, Children's Hospital of Los Angeles, University of Southern California, Los Angeles, CA, 90033, USA
| | - Richard A E Edden
- Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, MD, USA. .,F. M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, USA. .,Division of Neuroradiology, Park 367G, The Johns Hopkins University School of Medicine, 600 N. Wolfe St. B-112 D, Baltimore, MD, 21287, USA.
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5
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Korom M, Camacho MC, Filippi CA, Licandro R, Moore LA, Dufford A, Zöllei L, Graham AM, Spann M, Howell B, Shultz S, Scheinost D. Dear reviewers: Responses to common reviewer critiques about infant neuroimaging studies. Dev Cogn Neurosci 2021; 53:101055. [PMID: 34974250 PMCID: PMC8733260 DOI: 10.1016/j.dcn.2021.101055] [Citation(s) in RCA: 16] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/15/2021] [Revised: 11/28/2021] [Accepted: 12/26/2021] [Indexed: 01/07/2023] Open
Abstract
The field of adult neuroimaging relies on well-established principles in research design, imaging sequences, processing pipelines, as well as safety and data collection protocols. The field of infant magnetic resonance imaging, by comparison, is a young field with tremendous scientific potential but continuously evolving standards. The present article aims to initiate a constructive dialog between researchers who grapple with the challenges and inherent limitations of a nascent field and reviewers who evaluate their work. We address 20 questions that researchers commonly receive from research ethics boards, grant, and manuscript reviewers related to infant neuroimaging data collection, safety protocols, study planning, imaging sequences, decisions related to software and hardware, and data processing and sharing, while acknowledging both the accomplishments of the field and areas of much needed future advancements. This article reflects the cumulative knowledge of experts in the FIT’NG community and can act as a resource for both researchers and reviewers alike seeking a deeper understanding of the standards and tradeoffs involved in infant neuroimaging. The field of infant MRI is young with evolving standards. We address 20 questions that researchers commonly receive reviewers. These come from research ethics boards, grant, and manuscript reviewers. This article reflects the cumulative knowledge of experts in the FIT’NG community.
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Affiliation(s)
- Marta Korom
- Department of Psychological and Brain Sciences, University of Delaware, Newark, DE, USA.
| | - M Catalina Camacho
- Division of Biology and Biomedical Sciences (Neurosciences), Washington University School of Medicine, St. Louis, MO, USA.
| | - Courtney A Filippi
- Emotion and Development Branch, National Institute of Mental Health, Bethesda, MD, USA
| | - Roxane Licandro
- Institute of Visual Computing and Human-Centered Technology, Computer Vision Lab, TU Wien, Vienna, Austria; Department of Biomedical Imaging and Image-guided Therapy, Computational Imaging Research, Medical University of Vienna, Vienna, Austria
| | - Lucille A Moore
- Department of Psychiatry, Oregon Health and Science University, Portland, OR, USA
| | - Alexander Dufford
- Department of Radiology & Biomedical Imaging, Yale School of Medicine, New Haven, CT, USA
| | - Lilla Zöllei
- A.A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Boston, MA, USA
| | - Alice M Graham
- Department of Psychiatry, Oregon Health and Science University, Portland, OR, USA
| | - Marisa Spann
- Department of Psychiatry, Columbia University Irving Medical Center, New York, NY, USA
| | - Brittany Howell
- Fralin Biomedical Research Institute at Virginia Tech Carilion, Department of Human Development and Family Science, Virginia Polytechnic Institute and State University, Roanoke, VA, USA
| | | | - Sarah Shultz
- Division of Autism & Department of Pediatrics, Emory University School of Medicine, Atlanta, GA, USA; Marcus Autism Center, Children's Healthcare of Atlanta, Atlanta, GA, USA.
| | - Dustin Scheinost
- Department of Radiology & Biomedical Imaging, Yale School of Medicine, New Haven, CT, USA.
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6
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Dubois J, Alison M, Counsell SJ, Hertz‐Pannier L, Hüppi PS, Benders MJ. MRI of the Neonatal Brain: A Review of Methodological Challenges and Neuroscientific Advances. J Magn Reson Imaging 2021; 53:1318-1343. [PMID: 32420684 PMCID: PMC8247362 DOI: 10.1002/jmri.27192] [Citation(s) in RCA: 57] [Impact Index Per Article: 19.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/23/2019] [Revised: 04/24/2020] [Accepted: 04/24/2020] [Indexed: 01/04/2023] Open
Abstract
In recent years, exploration of the developing brain has become a major focus for researchers and clinicians in an attempt to understand what allows children to acquire amazing and unique abilities, as well as the impact of early disruptions (eg, prematurity, neonatal insults) that can lead to a wide range of neurodevelopmental disorders. Noninvasive neuroimaging methods such as MRI are essential to establish links between the brain and behavioral changes in newborns and infants. In this review article, we aim to highlight recent and representative studies using the various techniques available: anatomical MRI, quantitative MRI (relaxometry, diffusion MRI), multiparametric approaches, and functional MRI. Today, protocols use 1.5 or 3T MRI scanners, and specialized methodologies have been put in place for data acquisition and processing to address the methodological challenges specific to this population, such as sensitivity to motion. MR sequences must be adapted to the brains of newborns and infants to obtain relevant good soft-tissue contrast, given the small size of the cerebral structures and the incomplete maturation of tissues. The use of age-specific image postprocessing tools is also essential, as signal and contrast differ from the adult brain. Appropriate methodologies then make it possible to explore multiple neurodevelopmental mechanisms in a precise way, and assess changes with age or differences between groups of subjects, particularly through large-scale projects. Although MRI measurements only indirectly reflect the complex series of dynamic processes observed throughout development at the molecular and cellular levels, this technique can provide information on brain morphology, structural connectivity, microstructural properties of gray and white matter, and on the functional architecture. Finally, MRI measures related to clinical, behavioral, and electrophysiological markers have a key role to play from a diagnostic and prognostic perspective in the implementation of early interventions to avoid long-term disabilities in children. EVIDENCE LEVEL: 2 TECHNICAL EFFICACY STAGE: 1.
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Affiliation(s)
- Jessica Dubois
- University of ParisNeuroDiderot, INSERM,ParisFrance
- UNIACT, NeuroSpin, CEA; Paris‐Saclay UniversityGif‐sur‐YvetteFrance
| | - Marianne Alison
- University of ParisNeuroDiderot, INSERM,ParisFrance
- Department of Pediatric RadiologyAPHP, Robert‐Debré HospitalParisFrance
| | - Serena J. Counsell
- Centre for the Developing BrainSchool of Biomedical Engineering & Imaging Sciences, King's College LondonLondonUK
| | - Lucie Hertz‐Pannier
- University of ParisNeuroDiderot, INSERM,ParisFrance
- UNIACT, NeuroSpin, CEA; Paris‐Saclay UniversityGif‐sur‐YvetteFrance
| | - Petra S. Hüppi
- Division of Development and Growth, Department of Woman, Child and AdolescentUniversity Hospitals of GenevaGenevaSwitzerland
| | - Manon J.N.L. Benders
- Department of NeonatologyUniversity Medical Center Utrecht, Utrecht UniversityUtrechtthe Netherlands
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7
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Morrison JL, Ayonrinde OT, Care AS, Clarke GD, Darby JRT, David AL, Dean JM, Hooper SB, Kitchen MJ, Macgowan CK, Melbourne A, McGillick EV, McKenzie CA, Michael N, Mohammed N, Sadananthan SA, Schrauben E, Regnault TRH, Velan SS. Seeing the fetus from a DOHaD perspective: discussion paper from the advanced imaging techniques of DOHaD applications workshop held at the 2019 DOHaD World Congress. J Dev Orig Health Dis 2021; 12:153-167. [PMID: 32955011 DOI: 10.1017/s2040174420000884] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/07/2023]
Abstract
Advanced imaging techniques are enhancing research capacity focussed on the developmental origins of adult health and disease (DOHaD) hypothesis, and consequently increasing awareness of future health risks across various subareas of DOHaD research themes. Understanding how these advanced imaging techniques in animal models and human population studies can be both additively and synergistically used alongside traditional techniques in DOHaD-focussed laboratories is therefore of great interest. Global experts in advanced imaging techniques congregated at the advanced imaging workshop at the 2019 DOHaD World Congress in Melbourne, Australia. This review summarizes the presentations of new imaging modalities and novel applications to DOHaD research and discussions had by DOHaD researchers that are currently utilizing advanced imaging techniques including MRI, hyperpolarized MRI, ultrasound, and synchrotron-based techniques to aid their DOHaD research focus.
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Affiliation(s)
- Janna L Morrison
- Early Origins of Adult Health Research Group, Health and Biomedical Innovation, UniSA: Clinical and Health Sciences, University of South Australia, Adelaide, SA, Australia
| | - Oyekoya T Ayonrinde
- Fiona Stanley Hospital, Murdoch, WA, Australia
- Medical School, The University of Western Australia, Perth, WA, Australia
| | - Alison S Care
- The Robinson Research Institute and Adelaide Medical School, University of Adelaide, Adelaide, SA, Australia
| | - Geoffrey D Clarke
- Department of Radiology, University of Texas Health Science Center, San Antonio, TX, USA
| | - Jack R T Darby
- Early Origins of Adult Health Research Group, Health and Biomedical Innovation, UniSA: Clinical and Health Sciences, University of South Australia, Adelaide, SA, Australia
| | - Anna L David
- Elizabeth Garrett Anderson Institute for Women's Health, University College London, London, UK
| | - Justin M Dean
- Department of Physiology, Faculty of Medical and Health Sciences, University of Auckland, Auckland, New Zealand
| | - Stuart B Hooper
- The Ritchie Centre, Hudson Institute of Medical Research, Melbourne, Victoria, Australia
- The Department of Obstetrics and Gynecology, Monash University, Melbourne, Victoria, Australia
| | - Marcus J Kitchen
- School of Physics and Astronomy, Monash University, Melbourne, Victoria, Australia
| | | | - Andrew Melbourne
- School of Biomedical Engineering and Imaging Sciences, Kings College London, London, UK
| | - Erin V McGillick
- The Ritchie Centre, Hudson Institute of Medical Research, Melbourne, Victoria, Australia
- The Department of Obstetrics and Gynecology, Monash University, Melbourne, Victoria, Australia
| | - Charles A McKenzie
- Department of Medical Biophysics, Western University, London, ON, Canada
- Lawson Health Research Institute and Children's Health Research Institute, London, ON, Canada
| | - Navin Michael
- Singapore Institute for Clinical Sciences, Agency for Science, Technology, and Research (A*STAR), Singapore, Singapore
| | - Nuruddin Mohammed
- Maternal Fetal Medicine Unit, Department of Obstetrics and Gynecology, Aga Khan University Hospital, Karachi, Pakistan
| | - Suresh Anand Sadananthan
- Singapore Institute for Clinical Sciences, Agency for Science, Technology, and Research (A*STAR), Singapore, Singapore
| | - Eric Schrauben
- Translational Medicine, Hospital for Sick Children, Toronto, ON, Canada
| | - Timothy R H Regnault
- Lawson Health Research Institute and Children's Health Research Institute, London, ON, Canada
- Department of Obstetrics and Gynecology, Western University, London, ON, Canada
- Department of Physiology and Pharmacology, Western University, London, ON, Canada
| | - S Sendhil Velan
- Singapore Bioimaging Consortium, Agency for Science, Technology, and Research (A*STAR), Singapore, Singapore
- Singapore Institute for Clinical Sciences, Agency for Science, Technology, and Research (A*STAR), Singapore, Singapore
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8
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Mohammadi S, Callaghan MF. Towards in vivo g-ratio mapping using MRI: Unifying myelin and diffusion imaging. J Neurosci Methods 2021; 348:108990. [PMID: 33129894 PMCID: PMC7840525 DOI: 10.1016/j.jneumeth.2020.108990] [Citation(s) in RCA: 29] [Impact Index Per Article: 9.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/21/2020] [Revised: 09/21/2020] [Accepted: 10/20/2020] [Indexed: 12/19/2022]
Abstract
BACKGROUND The g-ratio, quantifying the comparative thickness of the myelin sheath encasing an axon, is a geometrical invariant that has high functional relevance because of its importance in determining neuronal conduction velocity. Advances in MRI data acquisition and signal modelling have put in vivo mapping of the g-ratio, across the entire white matter, within our reach. This capacity would greatly increase our knowledge of the nervous system: how it functions, and how it is impacted by disease. NEW METHOD This is the second review on the topic of g-ratio mapping using MRI. RESULTS This review summarizes the most recent developments in the field, while also providing methodological background pertinent to aggregate g-ratio weighted mapping, and discussing pitfalls associated with these approaches. COMPARISON WITH EXISTING METHODS Using simulations based on recently published data, this review reveals caveats to the state-of-the-art calibration methods that have been used for in vivo g-ratio mapping. It highlights the need to estimate both the slope and offset of the relationship between these MRI-based markers and the true myelin volume fraction if we are really to achieve the goal of precise, high sensitivity g-ratio mapping in vivo. Other challenges discussed in this review further evidence the need for gold standard measurements of human brain tissue from ex vivo histology. CONCLUSIONS We conclude that the quest to find the most appropriate MRI biomarkers to enable in vivo g-ratio mapping is ongoing, with the full potential of many novel techniques yet to be investigated.
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Affiliation(s)
- Siawoosh Mohammadi
- Department of Systems Neuroscience, University Medical Center Hamburg-Eppendorf, Hamburg, Germany; Department of Neurophysics, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany.
| | - Martina F Callaghan
- Wellcome Centre for Human Neuroimaging, UCL Queen Square Institute of Neurology, University College London, UK
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9
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White matter injury and neurodevelopmental disabilities: A cross-disease (dis)connection. Prog Neurobiol 2020; 193:101845. [PMID: 32505757 DOI: 10.1016/j.pneurobio.2020.101845] [Citation(s) in RCA: 37] [Impact Index Per Article: 9.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/07/2019] [Revised: 05/19/2020] [Accepted: 06/01/2020] [Indexed: 12/13/2022]
Abstract
White matter (WM) injury, once known primarily in preterm newborns, is emerging in its non-focal (diffused), non-necrotic form as a critical component of subtle brain injuries in many early-life diseases like prematurity, intrauterine growth restriction, congenital heart defects, and hypoxic-ischemic encephalopathy. While advances in medical techniques have reduced the number of severe outcomes, the incidence of tardive impairments in complex cognitive functions or psychopathology remains high, with lifelong detrimental effects. The importance of WM in coordinating neuronal assemblies firing and neural groups synchronizing within multiple frequency bands through myelination, even mild alterations in WM structure, may interfere with the cognitive performance that increasing social and learning demands would exploit tardively during children growth. This phenomenon may contribute to explaining longitudinally the high incidence of late-appearing impairments that affect children with a history of perinatal insults. Furthermore, WM abnormalities have been highlighted in several neuropsychiatric disorders, such as autism and schizophrenia. In this review, we gather and organize evidence on how diffused WM injuries contribute to neurodevelopmental disorders through different perinatal diseases and insults. An insight into a possible common, cross-disease, mechanism, neuroimaging and monitoring, biomarkers, and neuroprotective strategies will also be presented.
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10
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Galdi P, Blesa M, Stoye DQ, Sullivan G, Lamb GJ, Quigley AJ, Thrippleton MJ, Bastin ME, Boardman JP. Neonatal morphometric similarity mapping for predicting brain age and characterizing neuroanatomic variation associated with preterm birth. Neuroimage Clin 2020; 25:102195. [PMID: 32044713 PMCID: PMC7016043 DOI: 10.1016/j.nicl.2020.102195] [Citation(s) in RCA: 26] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/23/2019] [Revised: 01/14/2020] [Accepted: 01/21/2020] [Indexed: 01/01/2023]
Abstract
Multi-contrast MRI captures information about brain macro- and micro-structure which can be combined in an integrated model to obtain a detailed "fingerprint" of the anatomical properties of an individual's brain. Inter-regional similarities between features derived from structural and diffusion MRI, including regional volumes, diffusion tensor metrics, neurite orientation dispersion and density imaging measures, can be modelled as morphometric similarity networks (MSNs). Here, individual MSNs were derived from 105 neonates (59 preterm and 46 term) who were scanned between 38 and 45 weeks postmenstrual age (PMA). Inter-regional similarities were used as predictors in a regression model of age at the time of scanning and in a classification model to discriminate between preterm and term infant brains. When tested on unseen data, the regression model predicted PMA at scan with a mean absolute error of 0.70 ± 0.56 weeks, and the classification model achieved 92% accuracy. We conclude that MSNs predict chronological brain age accurately; and they provide a data-driven approach to identify networks that characterise typical maturation and those that contribute most to neuroanatomic variation associated with preterm birth.
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Affiliation(s)
- Paola Galdi
- MRC Centre for Reproductive Health, University of Edinburgh, Edinburgh EH16 4TJ, UK.
| | - Manuel Blesa
- MRC Centre for Reproductive Health, University of Edinburgh, Edinburgh EH16 4TJ, UK
| | - David Q Stoye
- MRC Centre for Reproductive Health, University of Edinburgh, Edinburgh EH16 4TJ, UK
| | - Gemma Sullivan
- MRC Centre for Reproductive Health, University of Edinburgh, Edinburgh EH16 4TJ, UK
| | - Gillian J Lamb
- MRC Centre for Reproductive Health, University of Edinburgh, Edinburgh EH16 4TJ, UK
| | - Alan J Quigley
- Department of Radiology, Royal Hospital for Sick Children, Edinburgh EH9 1LF, UK
| | - Michael J Thrippleton
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh EH16 4SB, UK; Edinburgh Imaging, University of Edinburgh, Edinburgh EH16 4SB, UK
| | - Mark E Bastin
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh EH16 4SB, UK
| | - James P Boardman
- MRC Centre for Reproductive Health, University of Edinburgh, Edinburgh EH16 4TJ, UK; Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh EH16 4SB, UK
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11
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Young JM, Vandewouw MM, Mossad SI, Morgan BR, Lee W, Smith ML, Sled JG, Taylor MJ. White matter microstructural differences identified using multi-shell diffusion imaging in six-year-old children born very preterm. NEUROIMAGE-CLINICAL 2019; 23:101855. [PMID: 31103872 PMCID: PMC6737393 DOI: 10.1016/j.nicl.2019.101855] [Citation(s) in RCA: 37] [Impact Index Per Article: 7.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 08/03/2018] [Revised: 04/08/2019] [Accepted: 05/02/2019] [Indexed: 10/29/2022]
Abstract
INTRODUCTION The underlying microstructural properties of white matter differences in children born very preterm (<32 weeks gestational age) can be investigated in depth using multi-shell diffusion imaging. The present study compared white matter across the whole brain using diffusion tensor imaging (DTI) and neurite orientation dispersion and density imaging (NODDI) metrics in children born very preterm and full-term children at six years of age. We also investigated associations between white matter microstructure with early brain injury and developmental outcomes. METHOD Multi-shell diffusion imaging, T1-weighted anatomical MR images and developmental assessments were acquired in 23 children born very preterm (16 males; mean scan age: 6.57 ± 0.34 years) and 24 full-term controls (10 males, mean scan age: 6.62 ± 0.37 years). DTI metrics were obtained and neurite orientation dispersion index (ODI) and density index (NDI) were estimated using the NODDI diffusion model. FSL's tract-based spatial statistics were performed on traditional DTI metrics and NODDI metrics. Voxel-wise comparisons were performed to test between-group differences and within-group associations with developmental outcomes (intelligence and visual motor abilities) as well as early white matter injury and germinal matrix/intraventricular haemorrhage (GMH/IVH). RESULTS In comparison to term-born children, the children born very preterm exhibited lower fractional anisotropy (FA) across many white matter regions as well as higher mean diffusivity (MD), radial diffusivity (RD), and ODI. Within-group analyses of the children born very preterm revealed associations between higher FA and NDI with higher IQ and VMI. Lower ODI was found within the corona radiata in those with a history of white matter injury. Within the full-term group, associations were found between higher NDI and ODI with lower IQ. CONCLUSION Children born very preterm exhibit lower FA and higher ODI than full-term children. NODDI metrics provide more biologically specific information beyond DTI metrics as well as additional information of the impact of prematurity and white matter microstructure on cognitive outcomes at six years of age.
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Affiliation(s)
- Julia M Young
- Diagnostic Imaging, Hospital for Sick Children, Toronto, ON, Canada; Neurosciences and Mental Health, SickKids Research Institute, Toronto, ON, Canada; Department of Psychology, University of Toronto, Toronto, ON, Canada.
| | - Marlee M Vandewouw
- Diagnostic Imaging, Hospital for Sick Children, Toronto, ON, Canada; Neurosciences and Mental Health, SickKids Research Institute, Toronto, ON, Canada
| | - Sarah I Mossad
- Diagnostic Imaging, Hospital for Sick Children, Toronto, ON, Canada; Neurosciences and Mental Health, SickKids Research Institute, Toronto, ON, Canada; Department of Psychology, University of Toronto, Toronto, ON, Canada
| | - Benjamin R Morgan
- Diagnostic Imaging, Hospital for Sick Children, Toronto, ON, Canada; Neurosciences and Mental Health, SickKids Research Institute, Toronto, ON, Canada
| | - Wayne Lee
- Diagnostic Imaging, Hospital for Sick Children, Toronto, ON, Canada
| | - Mary Lou Smith
- Department of Psychology, Hospital for Sick Children, Toronto, ON, Canada; Neurosciences and Mental Health, SickKids Research Institute, Toronto, ON, Canada; Department of Psychology, University of Toronto, Toronto, ON, Canada
| | - John G Sled
- Translational Medicine, SickKids Research Institute, Toronto, ON, Canada; Department of Biomedical Physics, University of Toronto, Toronto, ON, Canada
| | - Margot J Taylor
- Diagnostic Imaging, Hospital for Sick Children, Toronto, ON, Canada; Neurosciences and Mental Health, SickKids Research Institute, Toronto, ON, Canada; Department of Medical Imaging, University of Toronto, Toronto, ON, Canada; Department of Psychology, University of Toronto, Toronto, ON, Canada
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12
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Ouyang M, Dubois J, Yu Q, Mukherjee P, Huang H. Delineation of early brain development from fetuses to infants with diffusion MRI and beyond. Neuroimage 2018; 185:836-850. [PMID: 29655938 DOI: 10.1016/j.neuroimage.2018.04.017] [Citation(s) in RCA: 135] [Impact Index Per Article: 22.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/31/2017] [Revised: 04/01/2018] [Accepted: 04/08/2018] [Indexed: 02/08/2023] Open
Abstract
Dynamic macrostructural and microstructural changes take place from the mid-fetal stage to 2 years after birth. Delineating structural changes of the brain during early development provides new insights into the complicated processes of both typical development and the pathological mechanisms underlying various psychiatric and neurological disorders including autism, attention deficit hyperactivity disorder and schizophrenia. Decades of histological studies have identified strong spatial and functional maturation gradients in human brain gray and white matter. The recent improvements in magnetic resonance imaging (MRI) techniques, especially diffusion MRI (dMRI), relaxometry imaging, and magnetization transfer imaging (MTI) have provided unprecedented opportunities to non-invasively quantify and map the early developmental changes at whole brain and regional levels. Here, we review the recent advances in understanding early brain structural development during the second half of gestation and the first two postnatal years using modern MR techniques. Specifically, we review studies that delineate the emergence and microstructural maturation of white matter tracts, as well as dynamic mapping of inhomogeneous cortical microstructural organization unique to fetuses and infants. These imaging studies converge into maturational curves of MRI measurements that are distinctive across different white matter tracts and cortical regions. Furthermore, contemporary models offering biophysical interpretations of the dMRI-derived measurements are illustrated to infer the underlying microstructural changes. Collectively, this review summarizes findings that contribute to charting spatiotemporally heterogeneous gray and white matter structural development, offering MRI-based biomarkers of typical brain development and setting the stage for understanding aberrant brain development in neurodevelopmental disorders.
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Affiliation(s)
- Minhui Ouyang
- Radiology Research, Children's Hospital of Philadelphia, PA, United States
| | - Jessica Dubois
- INSERM, UMR992, CEA, NeuroSpin Center, University Paris Saclay, Gif-sur-Yvette, France
| | - Qinlin Yu
- Radiology Research, Children's Hospital of Philadelphia, PA, United States
| | - Pratik Mukherjee
- Department of Radiology & Biomedical Imaging, University of California, San Francisco, CA, United States
| | - Hao Huang
- Radiology Research, Children's Hospital of Philadelphia, PA, United States; Department of Radiology, Perelman School of Medicine, University of Pennsylvania, PA, United States.
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13
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Batalle D, Edwards AD, O'Muircheartaigh J. Annual Research Review: Not just a small adult brain: understanding later neurodevelopment through imaging the neonatal brain. J Child Psychol Psychiatry 2018; 59:350-371. [PMID: 29105061 PMCID: PMC5900873 DOI: 10.1111/jcpp.12838] [Citation(s) in RCA: 51] [Impact Index Per Article: 8.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 10/04/2017] [Indexed: 12/27/2022]
Abstract
BACKGROUND There has been a recent proliferation in neuroimaging research focusing on brain development in the prenatal, neonatal and very early childhood brain. Early brain injury and preterm birth are associated with increased risk of neurodevelopmental disorders, indicating the importance of this early period for later outcome. SCOPE AND METHODOLOGY Although using a wide range of different methodologies and investigating diverse samples, the common aim of many of these studies has been to both track normative development and investigate deviations in this development to predict behavioural, cognitive and neurological function in childhood. Here we review structural and functional neuroimaging studies investigating the developing brain. We focus on practical and technical complexities of studying this early age range and discuss how neuroimaging techniques have been successfully applied to investigate later neurodevelopmental outcome. CONCLUSIONS Neuroimaging markers of later outcome still have surprisingly low predictive power and their specificity to individual neurodevelopmental disorders is still under question. However, the field is still young, and substantial challenges to both acquiring and modeling neonatal data are being met.
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Affiliation(s)
- Dafnis Batalle
- Centre for the Developing BrainSchool of Imaging Sciences & Biomedical EngineeringKing's College LondonLondonUK
| | - A. David Edwards
- Centre for the Developing BrainSchool of Imaging Sciences & Biomedical EngineeringKing's College LondonLondonUK
| | - Jonathan O'Muircheartaigh
- Centre for the Developing BrainSchool of Imaging Sciences & Biomedical EngineeringKing's College LondonLondonUK
- Department of NeuroimagingInstitute of Psychiatry, Psychology and NeuroscienceKing's College LondonLondonUK
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14
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Hagiwara A, Hori M, Yokoyama K, Nakazawa M, Ueda R, Horita M, Andica C, Abe O, Aoki S. Analysis of White Matter Damage in Patients with Multiple Sclerosis via a Novel In Vivo MR Method for Measuring Myelin, Axons, and G-Ratio. AJNR Am J Neuroradiol 2017; 38:1934-1940. [PMID: 28775058 PMCID: PMC7963610 DOI: 10.3174/ajnr.a5312] [Citation(s) in RCA: 34] [Impact Index Per Article: 4.9] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/15/2017] [Accepted: 05/24/2017] [Indexed: 11/07/2022]
Abstract
BACKGROUND AND PURPOSE Myelin and axon volume fractions can now be estimated via MR imaging in vivo, as can the g-ratio, which equals the ratio of the inner to the outer diameter of a nerve fiber. The purpose of this study was to evaluate WM damage in patients with MS via this novel MR imaging technique. MATERIALS AND METHODS Twenty patients with relapsing-remitting MS with a combined total of 149 chronic plaques were analyzed. Myelin volume fraction was calculated based on simultaneous tissue relaxometry. Intracellular and CSF compartment volume fractions were quantified via neurite orientation dispersion and density imaging. Axon volume fraction and g-ratio were calculated by combining these measurements. Myelin and axon volume fractions and g-ratio were measured in plaques, periplaque WM, and normal-appearing WM. RESULTS All metrics differed significantly across the 3 groups (P < .001, except P = .027 for g-ratio between periplaque WM and normal-appearing WM). Those in plaques differed most from those in normal-appearing WM. The percentage changes in plaque and periplaque WM metrics relative to normal-appearing WM were significantly larger in absolute value for myelin volume fraction than for axon volume fraction and g-ratio (P < .001, except P = .033 in periplaque WM relative to normal-appearing WM for comparison between myelin and axon volume fraction). CONCLUSIONS In this in vivo MR imaging study, the myelin of WM was more damaged than axons in plaques and periplaque WM of patients with MS. Myelin and axon volume fractions and g-ratio may potentially be useful for evaluating WM damage in patients with MS.
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Affiliation(s)
- A Hagiwara
- From the Departments of Radiology (A.H., M. Hori., M.N., R.U., M. Horita, C.A., S.A.)
- Department of Radiology (A.H., O.A.), Graduate School of Medicine, University of Tokyo, Tokyo, Japan
| | - M Hori
- From the Departments of Radiology (A.H., M. Hori., M.N., R.U., M. Horita, C.A., S.A.)
| | - K Yokoyama
- Neurology (K.Y.), Juntendo University School of Medicine, Tokyo, Japan
| | - M Nakazawa
- From the Departments of Radiology (A.H., M. Hori., M.N., R.U., M. Horita, C.A., S.A.)
| | - R Ueda
- From the Departments of Radiology (A.H., M. Hori., M.N., R.U., M. Horita, C.A., S.A.)
- Department of Radiological Sciences (R.U.), Graduate School of Human Health Sciences, Tokyo Metropolitan University, Tokyo, Japan
| | - M Horita
- From the Departments of Radiology (A.H., M. Hori., M.N., R.U., M. Horita, C.A., S.A.)
| | - C Andica
- From the Departments of Radiology (A.H., M. Hori., M.N., R.U., M. Horita, C.A., S.A.)
| | - O Abe
- Department of Radiology (A.H., O.A.), Graduate School of Medicine, University of Tokyo, Tokyo, Japan
| | - S Aoki
- From the Departments of Radiology (A.H., M. Hori., M.N., R.U., M. Horita, C.A., S.A.)
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15
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Mancini M, Giulietti G, Dowell N, Spanò B, Harrison N, Bozzali M, Cercignani M. Introducing axonal myelination in connectomics: A preliminary analysis of g-ratio distribution in healthy subjects. Neuroimage 2017; 182:351-359. [PMID: 28917698 DOI: 10.1016/j.neuroimage.2017.09.018] [Citation(s) in RCA: 26] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/02/2017] [Revised: 08/16/2017] [Accepted: 09/08/2017] [Indexed: 12/21/2022] Open
Abstract
Microstructural imaging and connectomics are two research areas that hold great potential for investigating brain structure and function. Combining these two approaches can lead to a better and more complete characterization of the brain as a network. The aim of this work is characterizing the connectome from a novel perspective using the myelination measure given by the g-ratio. The g-ratio is the ratio of the inner to the outer diameters of a myelinated axon, whose aggregated value can now be estimated in vivo using MRI. In two different datasets of healthy subjects, we reconstructed the structural connectome and then used the g-ratio estimated from diffusion and magnetization transfer data to characterize the network structure. Significant characteristics of g-ratio weighted graphs emerged. First, the g-ratio distribution across the edges of the graph did not show the power-law distribution observed using the number of streamlines as a weight. Second, connections involving regions related to motor and sensory functions were the highest in myelin content. We also observed significant differences in terms of the hub structure and the rich-club organization suggesting that connections involving hub regions present higher myelination than peripheral connections. Taken together, these findings offer a characterization of g-ratio distribution across the connectome in healthy subjects and lay the foundations for further investigating plasticity and pathology using a similar approach.
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Affiliation(s)
- Matteo Mancini
- Neuroimaging Laboratory, Santa Lucia Foundation, Rome, Italy; Department of Neuroscience, Brighton and Sussex Medical School, University of Sussex, Brighton, UK.
| | | | - Nicholas Dowell
- Department of Neuroscience, Brighton and Sussex Medical School, University of Sussex, Brighton, UK
| | - Barbara Spanò
- Neuroimaging Laboratory, Santa Lucia Foundation, Rome, Italy
| | - Neil Harrison
- Department of Neuroscience, Brighton and Sussex Medical School, University of Sussex, Brighton, UK
| | - Marco Bozzali
- Neuroimaging Laboratory, Santa Lucia Foundation, Rome, Italy; Department of Neuroscience, Brighton and Sussex Medical School, University of Sussex, Brighton, UK
| | - Mara Cercignani
- Neuroimaging Laboratory, Santa Lucia Foundation, Rome, Italy; Department of Neuroscience, Brighton and Sussex Medical School, University of Sussex, Brighton, UK
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16
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Campbell JSW, Leppert IR, Narayanan S, Boudreau M, Duval T, Cohen-Adad J, Pike GB, Stikov N. Promise and pitfalls of g-ratio estimation with MRI. Neuroimage 2017; 182:80-96. [PMID: 28822750 DOI: 10.1016/j.neuroimage.2017.08.038] [Citation(s) in RCA: 82] [Impact Index Per Article: 11.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/09/2017] [Revised: 07/28/2017] [Accepted: 08/12/2017] [Indexed: 12/13/2022] Open
Abstract
The fiber g-ratio is the ratio of the inner to the outer diameter of the myelin sheath of a myelinated axon. It has a limited dynamic range in healthy white matter, as it is optimized for speed of signal conduction, cellular energetics, and spatial constraints. In vivo imaging of the g-ratio in health and disease would greatly increase our knowledge of the nervous system and our ability to diagnose, monitor, and treat disease. MRI based g-ratio imaging was first conceived in 2011, and expanded to be feasible in full brain white matter with preliminary results in 2013. This manuscript reviews the growing g-ratio imaging literature and speculates on future applications. It details the methodology for imaging the g-ratio with MRI, and describes the known pitfalls and challenges in doing so.
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Affiliation(s)
- Jennifer S W Campbell
- Montreal Neurological Institute, McGill University, Montreal, QC, Canada; NeuroPoly Lab, Institute of Biomedical Engineering, Polytechnique Montréal, Montréal, QC, Canada.
| | - Ilana R Leppert
- Montreal Neurological Institute, McGill University, Montreal, QC, Canada
| | - Sridar Narayanan
- Montreal Neurological Institute, McGill University, Montreal, QC, Canada
| | - Mathieu Boudreau
- Montreal Neurological Institute, McGill University, Montreal, QC, Canada
| | - Tanguy Duval
- NeuroPoly Lab, Institute of Biomedical Engineering, Polytechnique Montréal, Montréal, QC, Canada
| | - Julien Cohen-Adad
- NeuroPoly Lab, Institute of Biomedical Engineering, Polytechnique Montréal, Montréal, QC, Canada; Functional Neuroimaging Unit, CRIUGM, Université de Montréal, Montréal, QC, Canada
| | | | - Nikola Stikov
- NeuroPoly Lab, Institute of Biomedical Engineering, Polytechnique Montréal, Montréal, QC, Canada; Montreal Heart Institute, Université de Montréal, Montréal, QC, Canada
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17
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Dubois J, Adibpour P, Poupon C, Hertz-Pannier L, Dehaene-Lambertz G. MRI and M/EEG studies of the White Matter Development in Human Fetuses and Infants: Review and Opinion. Brain Plast 2016; 2:49-69. [PMID: 29765848 PMCID: PMC5928537 DOI: 10.3233/bpl-160031] [Citation(s) in RCA: 26] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/22/2022] Open
Abstract
Already during the last trimester of gestation, functional responses are recorded in foetuses and preterm newborns, attesting an already complex cerebral architecture. Then throughout childhood, anatomical connections are further refined but at different rates and over asynchronous periods across functional networks. Concurrently, infants gradually achieve new psychomotor and cognitive skills. Only the recent use of non-invasive techniques such as magnetic resonance imaging (MRI) and magneto- and electroencephalography (M/EEG) has opened the possibility to understand the relationships between brain maturation and skills development in vivo. In this review, we describe how these techniques have been applied to study the white matter maturation. At the structural level, the early architecture and myelination of bundles have been assessed with diffusion and relaxometry MRI, recently integrated in multi-compartment models and multi-parametric approaches. Nevertheless, technical limitations prevent us to map major developmental mechanisms such as fibers growth and pruning, and the progressive maturation at the bundle scale in case of mixing trajectories. At the functional level, M/EEG have been used to record different visual, somatosensory and auditory evoked responses. Because the conduction velocity of neural impulses increases with the myelination of connections, major changes in the components latency are observed throughout development. But so far, only a few studies have related structural and functional markers of white matter myelination. Such multi-modal approaches will be a major challenge in future research, not only to understand normal development, but also to characterize early mechanisms of pathologies and the influence of fetal and perinatal interventions on later outcome.
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Affiliation(s)
- Jessica Dubois
- INSERM, UMR992; CEA, NeuroSpin Center; University Paris Saclay, Gif-sur-Yvette, France
| | - Parvaneh Adibpour
- INSERM, UMR992; CEA, NeuroSpin Center; University Paris Saclay, Gif-sur-Yvette, France
| | - Cyril Poupon
- CEA, NeuroSpin Center, UNIRS; University Paris Saclay, Gif-sur-Yvette, France
| | - Lucie Hertz-Pannier
- CEA, NeuroSpin Center, UNIACT; University Paris Saclay, Gif-sur-Yvette, France; INSERM, UMR1129; University Paris Descartes, Paris, France
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18
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Abstract
Myelin is critical for healthy brain function. An accurate in vivo measure of myelin content has important implications for understanding brain plasticity and neurodegenerative diseases. Myelin water imaging is a magnetic resonance imaging method which can be used to visualize myelination in the brain and spinal cord in vivo. This review presents an overview of myelin water imaging data acquisition and analysis, post-mortem validation work, findings in both animal and human studies and a brief discussion about other MR techniques purported to provide in vivo myelin content. Multi-echo T2 relaxation approaches continue to undergo development and whole-brain imaging time now takes less than 10 minutes; the standard analysis method for this type of data acquisition is a non-negative least squares approach. Alternate methods including the multi-flip angle gradient echo mcDESPOT are also being used for myelin water imaging. Histological validation studies in animal and human brain and spinal cord tissue demonstrate high specificity of myelin water imaging for myelin. Potential confounding factors for in vivo myelin water fraction measurement include the presence of myelin debris and magnetization exchange processes. Myelin water imaging has successfully been used to study animal models of injury, applied in healthy human controls and can be used to assess damage and injury in conditions such as multiple sclerosis, neuromyelitis optica, schizophrenia, phenylketonuria, neurofibromatosis, niemann pick’s disease, stroke and concussion. Other quantitative magnetic resonance approaches that are sensitive to, but not specific for, myelin exist including magnetization transfer, diffusion tensor imaging and T1 weighted imaging.
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Affiliation(s)
- Alex L MacKay
- Department of Radiology, University of British Columbia, Vancouver, Canada.,Department of Physics and Astronomy, University of British Columbia, Vancouver, Canada
| | - Cornelia Laule
- Department of Radiology, University of British Columbia, Vancouver, Canada.,Department of Pathology & Laboratory Medicine, University of British Columbia, Vancouver, Canada.,International Collaboration on Repair Discoveries, University of British Columbia, Vancouver, Canada
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19
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Kulikova S, Hertz-Pannier L, Dehaene-Lambertz G, Poupon C, Dubois J. A New Strategy for Fast MRI-Based Quantification of the Myelin Water Fraction: Application to Brain Imaging in Infants. PLoS One 2016; 11:e0163143. [PMID: 27736872 PMCID: PMC5063462 DOI: 10.1371/journal.pone.0163143] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/13/2016] [Accepted: 09/02/2016] [Indexed: 11/19/2022] Open
Abstract
The volume fraction of water related to myelin (fmy) is a promising MRI index for in vivo assessment of brain myelination, that can be derived from multi-component analysis of T1 and T2 relaxometry signals. However, existing quantification methods require rather long acquisition and/or post-processing times, making implementation difficult both in research studies on healthy unsedated children and in clinical examinations. The goal of this work was to propose a novel strategy for fmy quantification within acceptable acquisition and post-processing times. Our approach is based on a 3-compartment model (myelin-related water, intra/extra-cellular water and unrestricted water), and uses calibrated values of inherent relaxation times (T1c and T2c) for each compartment c. Calibration was first performed on adult relaxometry datasets (N = 3) acquired with large numbers of inversion times (TI) and echo times (TE), using an original combination of a region contraction approach and a non-negative least-square (NNLS) algorithm. This strategy was compared with voxel-wise fitting, and showed robust estimation of T1c and T2c. The accuracy of fmy calculations depending on multiple factors was investigated using simulated data. In the testing stage, our strategy enabled fast fmy mapping, based on relaxometry datasets acquired with reduced TI and TE numbers (acquisition <6 min), and analyzed with NNLS algorithm (post-processing <5min). In adults (N = 13, mean age 22.4±1.6 years), fmy maps showed variability across white matter regions, in agreement with previous studies. In healthy infants (N = 18, aged 3 to 34 weeks), asynchronous changes in fmy values were demonstrated across bundles, confirming the well-known progression of myelination.
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Affiliation(s)
- Sofya Kulikova
- INSERM U1129, CEA/DRF/I2BM/Neurospin/UNIACT, Gif-sur-Yvette, France; Université Paris-Saclay, Université Paris Descartes, Sorbonne Paris Cité, Paris, France
| | - Lucie Hertz-Pannier
- INSERM U1129, CEA/DRF/I2BM/Neurospin/UNIACT, Gif-sur-Yvette, France; Université Paris-Saclay, Université Paris Descartes, Sorbonne Paris Cité, Paris, France
| | - Ghislaine Dehaene-Lambertz
- INSERM U992, CEA/DRF/I2BM/Neurospin/UNICOG, Gif-sur-Yvette, France; Université Paris Saclay, Université Paris-Sud, Gif-sur-Yvette, France
| | - Cyril Poupon
- CEA/DRF/I2BM/Neurospin/UNIRS, Gif-sur-Yvette, France; Université Paris Saclay, Université Paris-Sud, Gif-sur-Yvette, France
| | - Jessica Dubois
- INSERM U992, CEA/DRF/I2BM/Neurospin/UNICOG, Gif-sur-Yvette, France; Université Paris Saclay, Université Paris-Sud, Gif-sur-Yvette, France
- * E-mail:
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