Towards a unified analysis of brain maturation and aging across the entire lifespan: A MRI analysis

There is no consensus in literature about lifespan brain maturation and senescence, mainly because previous lifespan studies have been performed on restricted age periods and/or with a limited number of scans, making results instable and their comparison very difficult. Moreover, the use of nonharmonized tools and different volumetric measurements lead to a great discrepancy in reported results. Thanks to the new paradigm of BigData sharing in neuroimaging and the last advances in image processing enabling to process baby as well as elderly scans with the same tool, new insights on brain maturation and aging can be obtained. This study presents brain volume trajectory over the entire lifespan using the largest age range to date (from few months of life to elderly) and one of the largest number of subjects (N = 2,944). First, we found that white matter trajectory based on absolute and normalized volumes follows an inverted U‐shape with a maturation peak around middle life. Second, we found that from 1 to 8–10 y there is an absolute gray matter (GM) increase related to body growth followed by a GM decrease. However, when normalized volumes were considered, GM continuously decreases all along the life. Finally, we found that this observation holds for almost all the considered subcortical structures except for amygdala which is rather stable and hippocampus which exhibits an inverted U‐shape with a longer maturation period. By revealing the entire brain trajectory picture, a consensus can be drawn since most of the previously discussed discrepancies can be explained. Hum Brain Mapp 38:5501–5518, 2017. © 2017 Wiley Periodicals, Inc.

[1]  M. Styner,et al.  Longitudinal development of cortical and subcortical gray matter from birth to 2 years. , 2012, Cerebral cortex.

[2]  D. Louis Collins,et al.  Volumetric analysis of medial temporal lobe structures in brain development from childhood to adolescence , 2013, NeuroImage.

[3]  J. Simpkins,et al.  Neuroprotective effects of estrogens: potential mechanisms of action , 2000, International Journal of Developmental Neuroscience.

[4]  Kathrine Skak Madsen,et al.  Postnatal brain development: structural imaging of dynamic neurodevelopmental processes. , 2011, Progress in brain research.

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

[6]  D. Louis Collins,et al.  Nonlocal Intracranial Cavity Extraction , 2014, Int. J. Biomed. Imaging.

[7]  C. Jack,et al.  Medial temporal atrophy on MRI in normal aging and very mild Alzheimer's disease , 1997, Neurology.

[8]  Pierrick Coupé,et al.  volBrain: An Online MRI Brain Volumetry System , 2015, Front. Neuroinform..

[9]  Daniel Rueckert,et al.  Regional growth and atlasing of the developing human brain , 2016, NeuroImage.

[10]  Anders M. Fjell,et al.  Heterogeneity in Subcortical Brain Development: A Structural Magnetic Resonance Imaging Study of Brain Maturation from 8 to 30 Years , 2009, The Journal of Neuroscience.

[11]  A. Dale,et al.  Structural growth trajectories and rates of change in the first 3 months of infant brain development. , 2014, JAMA neurology.

[12]  R. Gur,et al.  Gender differences in age effect on brain atrophy measured by magnetic resonance imaging. , 1991, Proceedings of the National Academy of Sciences of the United States of America.

[13]  Krzysztof J. Gorgolewski,et al.  Making big data open: data sharing in neuroimaging , 2014, Nature Neuroscience.

[14]  A. Dale,et al.  Critical ages in the life course of the adult brain: nonlinear subcortical aging , 2013, Neurobiology of Aging.

[15]  Eveline A. Crone,et al.  Structural brain development between childhood and adulthood: Convergence across four longitudinal samples , 2016, NeuroImage.

[16]  José V. Manjón,et al.  Improved estimates of partial volume coefficients from noisy brain MRI using spatial context , 2010, NeuroImage.

[17]  Yasuhiro Kawasaki,et al.  Male-specific volume expansion of the human hippocampus during adolescence. , 2004, Cerebral cortex.

[18]  Daniel Rueckert,et al.  Automatic Whole Brain MRI Segmentation of the Developing Neonatal Brain , 2014, IEEE Transactions on Medical Imaging.

[19]  D. Louis Collins,et al.  Patch-based segmentation using expert priors: Application to hippocampus and ventricle segmentation , 2011, NeuroImage.

[20]  Guido Gerig,et al.  User-guided 3D active contour segmentation of anatomical structures: Significantly improved efficiency and reliability , 2006, NeuroImage.

[21]  Suzanne E. Welcome,et al.  Mapping cortical change across the human life span , 2003, Nature Neuroscience.

[22]  G. Ratcliff,et al.  Sex differences in brain aging: a quantitative magnetic resonance imaging study. , 1998, Archives of neurology.

[23]  Simon Duchesne,et al.  Normative data for subcortical regional volumes over the lifetime of the adult human brain , 2016, NeuroImage.

[24]  C. Woolley,et al.  Quantitative analysis of pre‐ and postsynaptic sex differences in the nucleus accumbens , 2009, The Journal of comparative neurology.

[25]  Alan C. Evans,et al.  Total and regional brain volumes in a population-based normative sample from 4 to 18 years: the NIH MRI Study of Normal Brain Development. , 2012, Cerebral cortex.

[26]  Arno Klein,et al.  A reproducible evaluation of ANTs similarity metric performance in brain image registration , 2011, NeuroImage.

[27]  Anders M. Dale,et al.  Consistent neuroanatomical age-related volume differences across multiple samples , 2011, Neurobiology of Aging.

[28]  J. Becker,et al.  Sex differences in drug abuse , 2008, Frontiers in Neuroendocrinology.

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

[30]  Torsten Rohlfing,et al.  Variation in longitudinal trajectories of regional brain volumes of healthy men and women (ages 10 to 85years) measured with atlas-based parcellation of MRI , 2013, NeuroImage.

[31]  Joseph E LeDoux,et al.  Contributions of the Amygdala to Emotion Processing: From Animal Models to Human Behavior , 2005, Neuron.

[32]  P. Huttenlocher,et al.  Regional differences in synaptogenesis in human cerebral cortex , 1997, The Journal of comparative neurology.

[33]  L. Jäncke,et al.  Brain structural trajectories over the adult lifespan , 2012, Human brain mapping.

[34]  Yaozong Gao,et al.  Segmentation of neonatal brain MR images using patch-driven level sets , 2014, NeuroImage.

[35]  Margaret A. Sheridan,et al.  A Review of Adversity, The Amygdala and the Hippocampus: A Consideration of Developmental Timing , 2009, Front. Hum. Neurosci..

[36]  A. Dale,et al.  Through Thick and Thin: a Need to Reconcile Contradictory Results on Trajectories in Human Cortical Development , 2016, Cerebral cortex.

[37]  A. Dale,et al.  High consistency of regional cortical thinning in aging across multiple samples. , 2009, Cerebral cortex.

[38]  Brian B. Avants,et al.  N4ITK: Improved N3 Bias Correction , 2010, IEEE Transactions on Medical Imaging.

[39]  D. Louis Collins,et al.  A new method for structural volume analysis of longitudinal brain MRI data and its application in studying the growth trajectories of anatomical brain structures in childhood , 2013, NeuroImage.

[40]  R. Kahn,et al.  Human brain changes across the life span: A review of 56 longitudinal magnetic resonance imaging studies , 2012, Human brain mapping.

[41]  J. Rapoport,et al.  Structural MRI of Pediatric Brain Development: What Have We Learned and Where Are We Going? , 2010, Neuron.

[42]  Karl J. Friston,et al.  A Voxel-Based Morphometric Study of Ageing in 465 Normal Adult Human Brains , 2001, NeuroImage.

[43]  Simon Vogrin,et al.  Cerebral cortex: An MRI-based study of volume and variance with age and sex , 2006, Journal of Clinical Neuroscience.

[44]  Pierrick Coupé,et al.  Author manuscript, published in "Journal of Magnetic Resonance Imaging 2010;31(1):192-203" DOI: 10.1002/jmri.22003 Adaptive Non-Local Means Denoising of MR Images with Spatially Varying Noise Levels , 2010 .

[45]  F. Gage,et al.  Neurogenesis in the adult human hippocampus , 1998, Nature Medicine.

[46]  A. Connelly,et al.  Developmental changes in cerebral grey and white matter volume from infancy to adulthood , 2010, International Journal of Developmental Neuroscience.

[47]  Hagen B. Huttner,et al.  Dynamics of Hippocampal Neurogenesis in Adult Humans , 2013, Cell.

[48]  Alan C. Evans,et al.  Trajectories of cortical thickness maturation in normal brain development — The importance of quality control procedures , 2016, NeuroImage.

[49]  A. Dale,et al.  What is normal in normal aging? Effects of aging, amyloid and Alzheimer's disease on the cerebral cortex and the hippocampus , 2014, Progress in Neurobiology.

[50]  F. Gage,et al.  Functional neurogenesis in the adult hippocampus , 2002, Nature.

[51]  R. Pearson,et al.  The Human Nervous System. Basic Elements of Structure and Function , 1967, The Yale Journal of Biology and Medicine.

[52]  Olivier Potvin,et al.  Freesurfer cortical normative data for adults using Desikan-Killiany-Tourville and ex vivo protocols , 2017, NeuroImage.

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

[54]  Paul M. Thompson,et al.  Sexual dimorphism of brain developmental trajectories during childhood and adolescence , 2007, NeuroImage.

[55]  Terry L. Jernigan,et al.  The Basics of Brain Development , 2010, Neuropsychology Review.

[56]  Rebecca C. Knickmeyer,et al.  Regional Gray Matter Growth, Sexual Dimorphism, and Cerebral Asymmetry in the Neonatal Brain , 2007, The Journal of Neuroscience.

[57]  Rhoshel K. Lenroot,et al.  Sex differences in the adolescent brain , 2010, Brain and Cognition.

[58]  Murat Yücel,et al.  Brain development during adolescence: A mixed‐longitudinal investigation of cortical thickness, surface area, and volume , 2016, Human brain mapping.

[59]  Armin Raznahan,et al.  How Does Your Cortex Grow? , 2011, The Journal of Neuroscience.

[60]  Nick C Fox,et al.  Presymptomatic hippocampal atrophy in Alzheimer's disease. A longitudinal MRI study. , 1996, Brain : a journal of neurology.