Mapping an index of the myelin g-ratio in infants using magnetic resonance imaging

Optimal myelination of neuronal axons is essential for effective brain and cognitive function. The ratio of the axon diameter to the outer fiber diameter, known as the g-ratio, is a reliable measure to assess axonal myelination and is an important index reflecting the efficiency and maximal conduction velocity of white matter pathways. Although advanced neuroimaging techniques including multicomponent relaxometry (MCR) and diffusion tensor imaging afford insight into the microstructural characteristics of brain tissue, by themselves they do not allow direct analysis of the myelin g-ratio. Here, we show that by combining myelin content information (obtained with mcDESPOT MCR) with neurite density information (obtained through NODDI diffusion imaging) an index of the myelin g-ratio may be estimated. Using this framework, we present the first quantitative study of myelin g-ratio index changes across childhood, examining 18 typically developing children 3 months to 7.5 years of age. We report a spatio-temporal pattern of maturation that is consistent with histological and developmental MRI studies, as well as theoretical studies of the myelin g-ratio. This work represents the first ever in vivo visualization of the evolution of white matter g-ratio indices throughout early childhood.

[1]  Paul M. Thompson,et al.  Lifespan trajectory of myelin integrity and maximum motor speed , 2010, Neurobiology of Aging.

[2]  F. Dick,et al.  Whole-Brain In-vivo Measurements of the Axonal G-Ratio in a Group of 37 Healthy Volunteers , 2015, Front. Neurosci..

[3]  Lindsay Walker,et al.  Modeling healthy male white matter and myelin development: 3 through 60 months of age , 2014, NeuroImage.

[4]  R. S. Smith,et al.  Myelinated nerve fibers: computed effect of myelin thickness on conduction velocity. , 1970, The American journal of physiology.

[5]  Alan C. Evans,et al.  Maturation of white matter in the human brain: a review of magnetic resonance studies , 2001, Brain Research Bulletin.

[6]  David Fitzpatrick,et al.  Increased Conduction Velocity as a Result of Myelination , 2001 .

[7]  Jing Zhang,et al.  Comparison of myelin water fraction from multiecho T2 decay curve and steady‐state methods , 2015, Magnetic resonance in medicine.

[8]  S. Waxman Determinants of conduction velocity in myelinated nerve fibers , 1980, Muscle & nerve.

[9]  Mark H. Johnson,et al.  Mapping Infant Brain Myelination with Magnetic Resonance Imaging , 2011, The Journal of Neuroscience.

[10]  Mark H. Johnson,et al.  Processes of change in brain and cognitive development , 2005, Trends in Cognitive Sciences.

[11]  Hui Zhang,et al.  Assessing white matter microstructure of the newborn with multi-shell diffusion MRI and biophysical compartment models , 2014, NeuroImage.

[12]  J. Hursh CONDUCTION VELOCITY AND DIAMETER OF NERVE FIBERS , 1939 .

[13]  P. Basser Diffusion MRI: From Quantitative Measurement to In vivo Neuroanatomy , 2009 .

[14]  John H. Gilmore,et al.  Frequency of spontaneous BOLD signal shifts during infancy and correlates with cognitive performance , 2014, Developmental Cognitive Neuroscience.

[15]  D. Graf von Keyserlingk,et al.  Diameter of axons and thickness of myelin sheaths of the pyramidal tract fibres in the adult human medullary pyramid. , 1984, Anatomischer Anzeiger.

[16]  Tomáš Paus,et al.  Growth of white matter in the adolescent brain: Myelin or axon? , 2010, Brain and Cognition.

[17]  Holly Dirks,et al.  Pediatric neuroimaging using magnetic resonance imaging during non-sedated sleep , 2013, Pediatric Radiology.

[18]  Christopher L Lankford,et al.  On the inherent precision of mcDESPOT , 2013, Magnetic resonance in medicine.

[19]  Michael Brady,et al.  Improved Optimization for the Robust and Accurate Linear Registration and Motion Correction of Brain Images , 2002, NeuroImage.

[20]  C. Laule,et al.  Myelin water imaging in multiple sclerosis: quantitative correlations with histopathology , 2006, Multiple sclerosis.

[21]  P. Basser,et al.  Axcaliber: A method for measuring axon diameter distribution from diffusion MRI , 2008, Magnetic resonance in medicine.

[22]  Heidi Johansen-Berg,et al.  Myelin water imaging reflects clinical variability in multiple sclerosis , 2012, NeuroImage.

[23]  R. Fields,et al.  Astrocytes Promote Myelination in Response to Electrical Impulses , 2006, Neuron.

[24]  Julien Cohen-Adad,et al.  In vivo histology of the myelin g-ratio with magnetic resonance imaging , 2015, NeuroImage.

[25]  John H. Gilmore,et al.  A new framework for analyzing white matter maturation in early brain development , 2010, 2010 IEEE International Symposium on Biomedical Imaging: From Nano to Macro.

[26]  V. Wedeen,et al.  Reduction of eddy‐current‐induced distortion in diffusion MRI using a twice‐refocused spin echo , 2003, Magnetic resonance in medicine.

[27]  Derek K. Jones,et al.  Resolving relaxometry and diffusion properties within the same voxel in the presence of crossing fibres by combining inversion recovery and diffusion‐weighted acquisitions , 2015, Magnetic resonance in medicine.

[28]  David H. Miller,et al.  Quantitative magnetization transfer imaging in postmortem multiple sclerosis brain , 2007, Journal of magnetic resonance imaging : JMRI.

[29]  Kathryn L. West,et al.  A revised model for estimating g-ratio from MRI , 2016, NeuroImage.

[30]  A. Dale,et al.  Life-span changes of the human brain white matter: diffusion tensor imaging (DTI) and volumetry. , 2010, Cerebral cortex.

[31]  Jonathan O'Muircheartaigh,et al.  Investigating white matter development in infancy and early childhood using myelin water faction and relaxation time mapping , 2012, NeuroImage.

[32]  Roberto Toro,et al.  Could Sex Differences in White Matter be Explained by g ratio? , 2009, Front. Neuroanat..

[33]  Tomás Paus,et al.  Axon diameter and axonal transport: In vivo and in vitro effects of androgens , 2015, NeuroImage.

[34]  Heidi Johansen-Berg,et al.  Myelin imaging in amyotrophic and primary lateral sclerosis , 2013, Amyotrophic lateral sclerosis & frontotemporal degeneration.

[35]  T. Klingberg,et al.  Maturation of White Matter is Associated with the Development of Cognitive Functions during Childhood , 2004, Journal of Cognitive Neuroscience.

[36]  B. Mädler,et al.  Insights into brain microstructure from the T2 distribution. , 2006, Magnetic resonance imaging.

[37]  M. Mallar Chakravarty,et al.  Neurite density from magnetic resonance diffusion measurements at ultrahigh field: Comparison with light microscopy and electron microscopy , 2010, NeuroImage.

[38]  Alan C. Evans,et al.  Brain development during childhood and adolescence: a longitudinal MRI study , 1999, Nature Neuroscience.

[39]  D. Louis Collins,et al.  Application of Information Technology: A Four-Dimensional Probabilistic Atlas of the Human Brain , 2001, J. Am. Medical Informatics Assoc..

[40]  R. Stein,et al.  The relationship between axon diameter, myelin thickness and conduction velocity during atrophy of mammalian peripheral nerves , 1983, Brain Research.

[41]  B. Brody,et al.  Sequence of Central Nervous System Myelination in Human Infancy. I. An Autopsy Study of Myelination , 1987, Journal of neuropathology and experimental neurology.

[42]  Masayoshi Ikeda,et al.  The relationship between nerve conduction velocity and fiber morphology during peripheral nerve regeneration , 2012, Brain and behavior.

[43]  Shannon H Kolind,et al.  One component? Two components? Three? The effect of including a nonexchanging “free” water component in multicomponent driven equilibrium single pulse observation of T1 and T2 , 2013, Magnetic resonance in medicine.

[44]  T. Chomiak,et al.  What Is the Optimal Value of the g-Ratio for Myelinated Fibers in the Rat CNS? A Theoretical Approach , 2009, PloS one.

[45]  Piotr Kozlowski,et al.  Myelin water imaging of multiple sclerosis at 7 T: Correlations with histopathology , 2008, NeuroImage.

[46]  Hui Zhang,et al.  Axon diameter mapping in the presence of orientation dispersion with diffusion MRI , 2011, NeuroImage.

[47]  D. Gochberg,et al.  Multiexponential T2, magnetization transfer, and quantitative histology in white matter tracts of rat spinal cord , 2010, Magnetic resonance in medicine.

[48]  Ameer Pasha Hosseinbor,et al.  Characterization of Cerebral White Matter Properties Using Quantitative Magnetic Resonance Imaging Stains , 2011, Brain Connect..

[49]  W. Rushton A theory of the effects of fibre size in medullated nerve , 1951, The Journal of physiology.

[50]  Brian K. Rutt,et al.  Deficient MWF mapping in multiple sclerosis using 3D whole-brain multi-component relaxation MRI , 2012, NeuroImage.

[51]  Brian A. Wandell,et al.  Bound pool fractions complement diffusion measures to describe white matter micro and macrostructure , 2011, NeuroImage.

[52]  Cedric E. Ginestet,et al.  White matter development and early cognition in babies and toddlers , 2014, Human brain mapping.

[53]  M. Rydmark,et al.  Axon diameter and myelin sheath thickness in nerve fibres of the ventral spinal root of the seventh lumbar nerve of the adult and developing cat. , 1983, Journal of anatomy.

[54]  Sébastien Ourselin,et al.  Multi-modal Measurement of the Myelin-to-Axon Diameter g-ratio in Preterm-born Neonates and Adult Controls , 2014, MICCAI.

[55]  Lucie Hertz-Pannier,et al.  Microstructural Correlates of Infant Functional Development: Example of the Visual Pathways , 2008, The Journal of Neuroscience.

[56]  Derek K. Jones,et al.  Gleaning multicomponent T1 and T2 information from steady‐state imaging data , 2008, Magnetic resonance in medicine.

[57]  Danielle S Bassett,et al.  Brain graphs: graphical models of the human brain connectome. , 2011, Annual review of clinical psychology.

[58]  S. Deoni,et al.  Characterizing longitudinal white matter development during early childhood , 2014, Brain Structure and Function.

[59]  Jennifer S. W. Campbell,et al.  Quantitative analysis of the myelin g-ratio from electron microscopy images of the macaque corpus callosum , 2015, Data in brief.

[60]  B. J. Casey,et al.  Quantitative magnetic resonance imaging of human brain development: ages 4-18. , 1996, Cerebral cortex.

[61]  G. Yovel,et al.  In vivo correlation between axon diameter and conduction velocity in the human brain , 2014, Brain Structure and Function.

[62]  B. J. Casey,et al.  Structural and functional brain development and its relation to cognitive development , 2000, Biological Psychology.

[63]  Alan C. Evans,et al.  The NIH MRI study of normal brain development , 2006, NeuroImage.

[64]  Matthew F. Glasser,et al.  Trends and Properties of Human Cerebral Cortex: Correlations with Cortical Myelin Content Introduction and Review , 2022 .

[65]  Jonathan O'Muircheartaigh,et al.  Cortical maturation and myelination in healthy toddlers and young children , 2015, NeuroImage.

[66]  S. Deoni,et al.  Correction of main and transmit magnetic field (B0 and B1) inhomogeneity effects in multicomponent‐driven equilibrium single‐pulse observation of T1 and T2 , 2011, Magnetic resonance in medicine.

[67]  G. Dehaene-Lambertz,et al.  Multi-parametric evaluation of the white matter maturation , 2014, Brain Structure and Function.

[68]  C. Raine,et al.  Axon diameter and myelin thickness—unusual relationships in dorsal root ganglia , 1973, The Anatomical record.

[69]  H. Kinney,et al.  Sequence of Central Nervous System Myelination in Human Infancy. II. Patterns of Myelination in Autopsied Infants , 1988, Journal of neuropathology and experimental neurology.

[70]  Arthur W. Toga,et al.  Human brain white matter atlas: Identification and assignment of common anatomical structures in superficial white matter , 2008, NeuroImage.

[71]  Jennifer S. W. Campbell,et al.  Combined NODDI and qMT for full-brain g-ratio mapping with complex subvoxel microstructure , 2013 .

[72]  J. Thiessen,et al.  Quantitative MRI and ultrastructural examination of the cuprizone mouse model of demyelination , 2013, NMR in biomedicine.

[73]  Fredrik Ullén,et al.  Is activity regulation of late myelination a plastic mechanism in the human nervous system? , 2009, Neuron glia biology.

[74]  D. Norman,et al.  Normal maturation of the neonatal and infant brain: MR imaging at 1.5 T. , 1988, Radiology.

[75]  T. Hare,et al.  Changes in cerebral functional organization during cognitive development , 2005, Current Opinion in Neurobiology.

[76]  A. MacKay,et al.  In vivo visualization of myelin water in brain by magnetic resonance , 1994, Magnetic resonance in medicine.

[77]  R K Taira,et al.  MR evaluation of early myelination patterns in normal and developmentally delayed infants. , 1988, AJR. American journal of roentgenology.

[78]  Brian B. Avants,et al.  Symmetric diffeomorphic image registration with cross-correlation: Evaluating automated labeling of elderly and neurodegenerative brain , 2008, Medical Image Anal..

[79]  Lawrence L. Wald,et al.  Surface based analysis of diffusion orientation for identifying architectonic domains in the in vivo human cortex , 2013, NeuroImage.

[80]  D. Whitteridge,et al.  Conduction velocity and myelin thickness in regenerating nerve fibres , 1946, The Journal of physiology.

[81]  J. Dubois,et al.  Diffusion tensor imaging of brain development. , 2006, Seminars in fetal & neonatal medicine.

[82]  L. Goldman,et al.  Computation of impulse conduction in myelinated fibers; theoretical basis of the velocity-diameter relation. , 1968, Biophysical journal.

[83]  Andrew L. Alexander,et al.  Longitudinal processing speed impairments in males with autism and the effects of white matter microstructure , 2014, Neuropsychologia.

[84]  Jonathan O'Muircheartaigh,et al.  Breastfeeding and early white matter development: A cross-sectional study , 2013, NeuroImage.

[85]  R. Fields,et al.  White matter in learning, cognition and psychiatric disorders , 2008, Trends in Neurosciences.

[86]  Daniel C. Alexander,et al.  NODDI: Practical in vivo neurite orientation dispersion and density imaging of the human brain , 2012, NeuroImage.

[87]  Peter J. Brophy,et al.  Mechanisms of axon ensheathment and myelin growth , 2005, Nature Reviews Neuroscience.

[88]  J. Dobbing,et al.  Quantitative growth and development of human brain , 1973, Archives of disease in childhood.

[89]  A. Meyer-Lindenberg,et al.  The evolution of complexity in human brain development: an EEG study. , 1996, Electroencephalography and clinical neurophysiology.

[90]  Dost Öngür,et al.  Probing myelin and axon abnormalities separately in psychiatric disorders using MRI techniques , 2013, Front. Integr. Neurosci..

[91]  J. B. HURSHl CONDUCTION VELOCITY AND DIAMETER OF NERVE FIBERS , 2004 .

[92]  D. Necchi,et al.  Axonal abnormalities in cerebellar Purkinje cells of the Ts65Dn mouse , 2008, Brain Research.

[93]  David H. Miller,et al.  Quantitative magnetic resonance of postmortem multiple sclerosis brain before and after fixation , 2008, Magnetic resonance in medicine.

[94]  C. Lebel,et al.  Longitudinal Development of Human Brain Wiring Continues from Childhood into Adulthood , 2011, The Journal of Neuroscience.

[95]  G Rees Cosgrove,et al.  Advances in myelin imaging with potential clinical application to pediatric imaging. , 2013, Neurosurgical focus.

[96]  A. Mackay,et al.  In vivo measurement of T2 distributions and water contents in normal human brain , 1997, Magnetic resonance in medicine.

[97]  Stephen M Smith,et al.  Fast robust automated brain extraction , 2002, Human brain mapping.

[98]  Sean C L Deoni,et al.  Quantitative Relaxometry of the Brain , 2010, Topics in magnetic resonance imaging : TMRI.

[99]  C. Lebel,et al.  Diffusion tensor imaging of white matter tract evolution over the lifespan , 2012, NeuroImage.

[100]  R. Fields,et al.  Myelination: An Overlooked Mechanism of Synaptic Plasticity? , 2005, The Neuroscientist : a review journal bringing neurobiology, neurology and psychiatry.