Lessons About Neurodevelopment From Anatomical Magnetic Resonance Imaging

The arrival of magnetic resonance imaging (MRI) has offered major advances in our understanding of both normal and abnormal neurodevelopment. This review is a broad overview of the key findings that anatomical MRI research has provided in regard to the normal developing brain and presents key issues and consideration in pediatric imaging. Volumetric MRI studies, using various methods, have reliably found that gray-matter volume increases and peaks in late childhood, followed by a slow but continued loss, whereas white matter increases rapidly until age 10 years with continued development well beyond adolescence. The introduction of analysis techniques, such as voxel-based morphometry, cortical thickness measures, and cortical pattern mapping, have begun to answer more regionally specific questions. Pediatric neuroimaging studies carry specific requirements, given not only the high degree of variability between individuals, ages, and sexes but also issues of behavioral compliance, MR signal, and postprocessing methodologies such as appropriate normalization. Considerations in future pediatric imaging studies are presented. Ultimately, the promise of computational analysis of structural MRI data is to understand how changes in cerebral morphology relate to acquisition and enhancement of skills and behaviors in typical and atypical development.

[1]  P. Yakovlev,et al.  The myelogenetic cycles of regional maturation of the brain , 1967 .

[2]  G. Nellhaus Head circumference from birth to eighteen years. Practical composite international and interracial graphs. , 1968, Pediatrics.

[3]  F. Gilles,et al.  Gyral development of the human brain , 1977, Transactions of the American Neurological Association.

[4]  A. Dekaban,et al.  Changes in brain weights during the span of human life: Relation of brain weights to body heights and body weights , 1978, Annals of neurology.

[5]  P. Huttenlocher Synaptic density in human frontal cortex - developmental changes and effects of aging. , 1979, Brain research.

[6]  E. Terasawa,et al.  HYPOTHALAMIC CONTROL OF PUBERTY IN THE FEMALE RHESUS MACAQUE1234 , 1983 .

[7]  S. DeKosky,et al.  Gonadal steroids influence axon sprouting in the hippocampal dentate gyrus: A sexually dimorphic response , 1986, Experimental Neurology.

[8]  T. H. Newton,et al.  MRI of normal brain maturation. , 1986, AJNR. American journal of neuroradiology.

[9]  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.

[10]  P S Goldman-Rakic,et al.  Androgen binding and metabolism in the cerebral cortex of the developing rhesus monkey. , 1988, Endocrinology.

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

[12]  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.

[13]  Professor Dr. Jacob Valk,et al.  Magnetic Resonance of Myelin, Myelination, and Myelin Disorders , 1989, Springer Berlin Heidelberg.

[14]  D. Kennedy,et al.  Magnetic resonance imaging–based brain morphometry: Development and application to normal subjects , 1989, Annals of neurology.

[15]  C. Léránth,et al.  African green monkeys have sexually dimorphic and estrogen-sensitive hypothalamic neuronal membranes , 1990, Brain Research Bulletin.

[16]  G. Press,et al.  Methods for measuring brain morphologic features on magnetic resonance images. Validation and normal aging. , 1990, Archives of neurology.

[17]  M. Torrens Co-Planar Stereotaxic Atlas of the Human Brain—3-Dimensional Proportional System: An Approach to Cerebral Imaging, J. Talairach, P. Tournoux. Georg Thieme Verlag, New York (1988), 122 pp., 130 figs. DM 268 , 1990 .

[18]  小野 道夫,et al.  Atlas of the Cerebral Sulci , 1990 .

[19]  M Ashtari,et al.  Computerized volume measurement of brain structure. , 1990, Investigative radiology.

[20]  G. Bruyn Atlas of the Cerebral Sulci, M. Ono, S. Kubik, Chad D. Abernathey (Eds.). Georg Thieme Verlag, Stuttgart, New York (1990), 232, DM 298 , 1990 .

[21]  R. Melcangi,et al.  Androgen metabolism in the brain , 1991, The Journal of Steroid Biochemistry and Molecular Biology.

[22]  K Hayakawa,et al.  Normal brain maturation in MRI. , 1991, European journal of radiology.

[23]  T. Jernigan,et al.  Maturation of human cerebrum observed in vivo during adolescence. , 1991, Brain : a journal of neurology.

[24]  C. Woolley,et al.  Steroid hormones as mediators of neural plasticity , 1991, The Journal of Steroid Biochemistry and Molecular Biology.

[25]  Terry M. Peters,et al.  3D statistical neuroanatomical models from 305 MRI volumes , 1993, 1993 IEEE Conference Record Nuclear Science Symposium and Medical Imaging Conference.

[26]  K. Slifer,et al.  Behavior analysis of motion control for pediatric neuroimaging. , 1993, Journal of applied behavior analysis.

[27]  D. Kennedy,et al.  The young adult human brain: an MRI-based morphometric analysis. , 1994, Cerebral cortex.

[28]  D. Mathalon,et al.  A quantitative magnetic resonance imaging study of changes in brain morphology from infancy to late adulthood. , 1994, Archives of neurology.

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

[30]  K. Slifer,et al.  Behavioral Training of Motion Control in Young Children Undergoing Radiation Treatment Without Sedation , 1994, Journal of pediatric oncology nursing : official journal of the Association of Pediatric Oncology Nurses.

[31]  J. Valk,et al.  Myelin and White Matter , 1995 .

[32]  PhD Marjo S. van der Knaap MD,et al.  Magnetic Resonance of Myelin, Myelination, and Myelin Disorders , 1995, Springer Berlin Heidelberg.

[33]  D. Kennedy,et al.  The human brain age 7-11 years: a volumetric analysis based on magnetic resonance images. , 1996, Cerebral cortex.

[34]  K. Slifer A video system to help children cooperate with motion control for radiation treatment without sedation. , 1996, Journal of pediatric oncology nursing : official journal of the Association of Pediatric Oncology Nurses.

[35]  Alan C. Evans,et al.  In vivo morphometry of the intrasulcal gray matter in the human cingulate, paracingulate, and superior‐rostral sulci: Hemispheric asymmetries, gender differences and probability maps , 1996, The Journal of comparative neurology.

[36]  Giorgio Zamboni,et al.  [Normal pubertal development]. , 1996, La Pediatria medica e chirurgica : Medical and surgical pediatrics.

[37]  A. Reiss,et al.  Brain development, gender and IQ in children. A volumetric imaging study. , 1996, Brain : a journal of neurology.

[38]  P. Basser,et al.  Diffusion tensor MR imaging of the human brain. , 1996, Radiology.

[39]  K Amunts,et al.  Quantitative analysis of sulci in the human cerebral cortex: Development, regional heterogeneity, gender difference, asymmetry, intersubject variability and cortical architecture , 1997, Human brain mapping.

[40]  B. Pakkenberg,et al.  Neocortical neuron number in humans: Effect of sex and age , 1997, The Journal of comparative neurology.

[41]  J. Rapoport,et al.  Variability of human brain structure size: ages 4–20 years , 1997, Psychiatry Research: Neuroimaging.

[42]  T. Takeya,et al.  Volumetric quantification of brain development using MRI , 1997, Neuroradiology.

[43]  S. Maier,et al.  Microstructural Development of Human Newborn Cerebral White Matter Assessed in Vivo by Diffusion Tensor Magnetic Resonance Imaging , 1998, Pediatric Research.

[44]  K. Wallen,et al.  Sexual maturation in male rhesus monkeys: importance of neonatal testosterone exposure and social rank. , 1998, The Journal of endocrinology.

[45]  A. Snyder,et al.  Normal brain in human newborns: apparent diffusion coefficient and diffusion anisotropy measured by using diffusion tensor MR imaging. , 1998, Radiology.

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

[47]  Alan C. Evans,et al.  Structural maturation of neural pathways in children and adolescents: in vivo study. , 1999, Science.

[48]  J. Gabrieli,et al.  Myelination and organization of the frontal white matter in children: a diffusion tensor MRI study. , 1999, Neuroreport.

[49]  F. Aboitiz,et al.  Hemispheric differences in variability of fissural patterns in parasylvian and cingulate regions of human brains , 1999, The Journal of comparative neurology.

[50]  R. A. Zimmerman,et al.  Changes in brain water diffusion during childhood , 1999, Neuroradiology.

[51]  I. Aharon,et al.  Three‐dimensional mapping of cortical thickness using Laplace's Equation , 2000, Human brain mapping.

[52]  Jean Meunier,et al.  Average Brain Models: A Convergence Study , 2000, Comput. Vis. Image Underst..

[53]  Karl J. Friston,et al.  Voxel-Based Morphometry—The Methods , 2000, NeuroImage.

[54]  Alan C. Evans,et al.  Growth patterns in the developing brain detected by using continuum mechanical tensor maps , 2000, Nature.

[55]  J. Townsend,et al.  Normal brain development and aging: quantitative analysis at in vivo MR imaging in healthy volunteers. , 2000, Radiology.

[56]  Michael I. Miller,et al.  Bayesian Construction of Geometrically Based Cortical Thickness Metrics , 2000, NeuroImage.

[57]  A M Dale,et al.  Measuring the thickness of the human cerebral cortex from magnetic resonance images. , 2000, Proceedings of the National Academy of Sciences of the United States of America.

[58]  O. Muzik,et al.  Statistical Parametric Mapping: Assessment of Application in Children , 2000, NeuroImage.

[59]  M. Rivkin,et al.  Developmental neuroimaging of children using magnetic resonance techniques. , 2000, Mental retardation and developmental disabilities research reviews.

[60]  A. Toga,et al.  Mapping cortical asymmetry and complexity patterns in normal children , 2001, Psychiatry Research: Neuroimaging.

[61]  D. Sparks,et al.  Quantitative assessment of possible age-related change in synaptic numbers in the human frontal cortex , 2001, Neurobiology of Aging.

[62]  Karl J. Friston,et al.  Cerebral Asymmetry and the Effects of Sex and Handedness on Brain Structure: A Voxel-Based Morphometric Analysis of 465 Normal Adult Human Brains , 2001, NeuroImage.

[63]  R. Gur,et al.  Age-related volumetric changes of brain gray and white matter in healthy infants and children. , 2001, Cerebral cortex.

[64]  Alan C. Evans,et al.  Measurement of Cortical Thickness Using an Automated 3-D Algorithm: A Validation Study , 2001, NeuroImage.

[65]  A. Toga,et al.  Mapping Continued Brain Growth and Gray Matter Density Reduction in Dorsal Frontal Cortex: Inverse Relationships during Postadolescent Brain Maturation , 2001, The Journal of Neuroscience.

[66]  M. Keshavan,et al.  Sex differences in brain maturation during childhood and adolescence. , 2001, Cerebral cortex.

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

[68]  J. Shimony,et al.  Normal brain maturation during childhood: developmental trends characterized with diffusion-tensor MR imaging. , 2001, Radiology.

[69]  C. Beaulieu,et al.  The basis of anisotropic water diffusion in the nervous system – a technical review , 2002, NMR in biomedicine.

[70]  Alan C. Evans,et al.  Developmental trajectories of brain volume abnormalities in children and adolescents with attention-deficit/hyperactivity disorder. , 2002, JAMA.

[71]  Abraham Z. Snyder,et al.  The Feasibility of a Common Stereotactic Space for Children and Adults in fMRI Studies of Development , 2002, NeuroImage.

[72]  S. Dehaene,et al.  Functional Neuroimaging of Speech Perception in Infants , 2002, Science.

[73]  T. Jernigan,et al.  Development of cortical and subcortical brain structures in childhood and adolescence: a structural MRI study , 2002, Developmental medicine and child neurology.

[74]  A. Toga,et al.  Mapping sulcal pattern asymmetry and local cortical surface gray matter distribution in vivo: maturation in perisylvian cortices. , 2002, Cerebral cortex.

[75]  J. Provenzale,et al.  Evaluation of normal age-related changes in anisotropy during infancy and childhood as shown by diffusion tensor imaging. , 2002, AJR. American journal of roentgenology.

[76]  Marko Wilke,et al.  Assessment of spatial normalization of whole‐brain magnetic resonance images in children , 2002, Human brain mapping.

[77]  Marko Wilke,et al.  Correlation of white matter diffusivity and anisotropy with age during childhood and adolescence: a cross-sectional diffusion-tensor MR imaging study. , 2002, Radiology.

[78]  M Wilke,et al.  Normative pediatric brain data for spatial normalization and segmentation differs from standard adult data , 2003, Magnetic resonance in medicine.

[79]  P. Levitt Structural and functional maturation of the developing primate brain. , 2003, The Journal of pediatrics.

[80]  B. Pakkenberg,et al.  Marked loss of myelinated nerve fibers in the human brain with age , 2003, The Journal of comparative neurology.

[81]  J. Petrella,et al.  Developmental aspects of language processing: fMRI of verbal fluency in children and adults , 2003, Human brain mapping.

[82]  J. Giedd Structural Magnetic Resonance Imaging of the Adolescent Brain , 2004, Annals of the New York Academy of Sciences.

[83]  John H. Gilmore,et al.  3 Tesla magnetic resonance imaging of the brain in newborns , 2004, Psychiatry Research: Neuroimaging.

[84]  J. Valk,et al.  MR imaging of the various stages of normal myelination during the first year of life , 2004, Neuroradiology.

[85]  Thomas F. Nugent,et al.  Dynamic mapping of human cortical development during childhood through early adulthood. , 2004, Proceedings of the National Academy of Sciences of the United States of America.

[86]  A. Toga,et al.  Mapping Changes in the Human Cortex throughout the Span of Life , 2004, The Neuroscientist : a review journal bringing neurobiology, neurology and psychiatry.

[87]  Suzanne E. Welcome,et al.  Longitudinal Mapping of Cortical Thickness and Brain Growth in Normal Children , 2022 .

[88]  Karl J. Friston,et al.  Unified segmentation , 2005, NeuroImage.

[89]  V. Menon,et al.  White matter development during childhood and adolescence: a cross-sectional diffusion tensor imaging study. , 2005, Cerebral cortex.

[90]  H. Engeland,et al.  Variability in spatial normalization of pediatric and adult brain images , 2005, Clinical Neurophysiology.

[91]  J. Giedd,et al.  Brain development in children and adolescents: Insights from anatomical magnetic resonance imaging , 2006, Neuroscience & Biobehavioral Reviews.

[92]  Hangyi Jiang,et al.  Pediatric diffusion tensor imaging: Normal database and observation of the white matter maturation in early childhood , 2006, NeuroImage.

[93]  A. Toga,et al.  Mapping brain maturation , 2006, Trends in Neurosciences.

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

[95]  K. Lim,et al.  Advances in white matter imaging: A review of in vivo magnetic resonance methodologies and their applicability to the study of development and aging , 2006, Neuroscience & Biobehavioral Reviews.

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

[97]  J. Allsop,et al.  Quantification of Deep Gray Matter in Preterm Infants at Term-Equivalent Age Using Manual Volumetry of 3-Tesla Magnetic Resonance Images , 2007, Pediatrics.

[98]  J. Allsop,et al.  Quantification of Deep Gray Matter in Preterm Infants at Term-Equivalent Age Using Manual Volumetry of 3-Tesla Magnetic Resonance Images , 2007, Pediatrics.

[99]  Brain Development Cooperative Group,et al.  The NIH MRI study of normal brain development (Objective-2): Newborns, infants, toddlers, and preschoolers , 2007, NeuroImage.

[100]  Hamid Abrishami Moghaddam,et al.  A neonatal atlas template for spatial normalization of whole-brain magnetic resonance images of newborns: Preliminary results , 2007, NeuroImage.

[101]  Judith Rumsey,et al.  The NIH MRI study of normal brain development: Performance of a population based sample of healthy children aged 6 to 18 years on a neuropsychological battery , 2007, Journal of the International Neuropsychological Society.

[102]  M. Ditchfield,et al.  Reviewing the process of preparing children for MRI , 2008, Pediatric Radiology.

[103]  Li Yao,et al.  Brain development in Chinese children and adolescents: a structural MRI study , 2007, Neuroreport.

[104]  K. Kaga,et al.  Myelination progression in language-correlated regions in brain of normal children determined by quantitative MRI assessment. , 2008, International journal of pediatric otorhinolaryngology.

[105]  Scott Holland,et al.  Infant brain probability templates for MRI segmentation and normalization , 2008, NeuroImage.

[106]  Scott Holland,et al.  Template-O-Matic: A toolbox for creating customized pediatric templates , 2008, NeuroImage.

[107]  Rebecca C. Knickmeyer,et al.  A Structural MRI Study of Human Brain Development from Birth to 2 Years , 2008, The Journal of Neuroscience.

[108]  et al.,et al.  The Effect of Template Choice on Morphometric Analysis of Pediatric Brain Data ☆ , 2022 .

[109]  Xue Hua,et al.  Detecting brain growth patterns in normal children using tensor‐based morphometry , 2009, Human brain mapping.

[110]  Orit A Glenn,et al.  Normal development of the fetal brain by MRI. , 2009, Seminars in perinatology.

[111]  M. Spencer-Smith,et al.  Childhood brain insult: can age at insult help us predict outcome? , 2009, Brain : a journal of neurology.