Age-related alterations in axonal microstructure in the corpus callosum measured by high-gradient diffusion MRI

ABSTRACT Cerebral white matter exhibits age‐related degenerative changes during the course of normal aging, including decreases in axon density and alterations in axonal structure. Noninvasive approaches to measure these microstructural alterations throughout the lifespan would be invaluable for understanding the substrate and regional variability of age‐related white matter degeneration. Recent advances in diffusion magnetic resonance imaging (MRI) have leveraged high gradient strengths to increase sensitivity toward axonal size and density in the living human brain. Here, we examined the relationship between age and indices of axon diameter and packing density using high‐gradient strength diffusion MRI in 36 healthy adults (aged 22–72) in well‐defined central white matter tracts in the brain. A recently validated method for inferring the effective axonal compartment size and packing density from diffusion MRI measurements acquired with 300mT/m maximum gradient strength was applied to the in vivo human brain to obtain indices of axon diameter and density in the corpus callosum, its sub‐regions, and adjacent anterior and posterior fibers in the forceps minor and forceps major. The relationships between the axonal metrics, corpus callosum area and regional gray matter volume were also explored. Results revealed a significant increase in axon diameter index with advancing age in the whole corpus callosum. Similar analyses in sub‐regions of the corpus callosum showed that age‐related alterations in axon diameter index and axon density were most pronounced in the genu of the corpus callosum and relatively absent in the splenium, in keeping with findings from previous histological studies. The significance of these correlations was mirrored in the forceps minor and forceps major, consistent with previously reported decreases in FA in the forceps minor but not in the forceps major with age. Alterations in the axonal imaging metrics paralleled decreases in corpus callosum area and regional gray matter volume with age. Among older adults, results from cognitive testing suggested an association between larger effective compartment size in the corpus callosum, particularly within the genu of the corpus callosum, and lower scores on the Montreal Cognitive Assessment, largely driven by deficits in short‐term memory. The current study suggests that high‐gradient diffusion MRI may be sensitive to the axonal substrate of age‐related white matter degeneration reflected in traditional DTI metrics and provides further evidence for regionally selective alterations in white matter microstructure with advancing age. HIGHLIGHTSDiffusion MRI reveals age‐related microstructural alterations in the corpus callosum.Axon diameter index increases with advancing age in the whole corpus callosum.Age‐related microstructural alterations are more pronounced in the genu than splenium.Larger axon diameter index is associated with poorer performance on cognitive testing.

[1]  Robin M Heidemann,et al.  Generalized autocalibrating partially parallel acquisitions (GRAPPA) , 2002, Magnetic resonance in medicine.

[2]  M. Ptito,et al.  Contrast and stability of the axon diameter index from microstructure imaging with diffusion MRI , 2012, Magnetic resonance in medicine.

[3]  M. O’Sullivan,et al.  Activate your online subscription , 2001, Neurology.

[4]  P. V. van Zijl,et al.  Evaluation of restricted diffusion in cylinders. Phosphocreatine in rabbit leg muscle. , 1994, Journal of magnetic resonance. Series B.

[5]  Scott A. Huettel,et al.  Diffusion tensor imaging of adult age differences in cerebral white matter: relation to response time , 2004, NeuroImage.

[6]  Stamatios N. Sotiropoulos,et al.  Incorporating outlier detection and replacement into a non-parametric framework for movement and distortion correction of diffusion MR images , 2016, NeuroImage.

[7]  P. Basser,et al.  In vivo measurement of axon diameter distribution in the corpus callosum of rat brain. , 2009, Brain : a journal of neurology.

[8]  Fang-Cheng Yeh,et al.  Generalized ${ q}$-Sampling Imaging , 2010, IEEE Transactions on Medical Imaging.

[9]  Stefan Skare,et al.  How to correct susceptibility distortions in spin-echo echo-planar images: application to diffusion tensor imaging , 2003, NeuroImage.

[10]  L. Wald,et al.  A 64‐channel 3T array coil for accelerated brain MRI , 2013, Magnetic resonance in medicine.

[11]  J. Polimeni,et al.  Blipped‐controlled aliasing in parallel imaging for simultaneous multislice echo planar imaging with reduced g‐factor penalty , 2012, Magnetic resonance in medicine.

[12]  E. Sullivan,et al.  Corpus callosal microstructural integrity influences interhemispheric processing: a diffusion tensor imaging study. , 2005, Cerebral cortex.

[13]  Agnieszka Z. Burzynska,et al.  Diffusion tensor imaging of cerebral white matter integrity in cognitive aging. , 2012, Biochimica et biophysica acta.

[14]  Anastasia Yendiki,et al.  Longitudinal Changes in White Matter Tract Integrity across the Adult Lifespan and Its Relation to Cortical Thinning , 2016, PloS one.

[15]  Kathryn L. West,et al.  Evaluating g-ratio weighted changes in the corpus callosum as a function of age and sex , 2017, NeuroImage.

[16]  Stephan P. Swinnen,et al.  Bimanual motor deficits in older adults predicted by diffusion tensor imaging metrics of corpus callosum subregions , 2013, Brain Structure and Function.

[17]  Bruce R. Rosen,et al.  MGH–USC Human Connectome Project datasets with ultra-high b-value diffusion MRI , 2016, NeuroImage.

[18]  Dmitry S. Novikov,et al.  Mesoscopic structure of neuronal tracts from time-dependent diffusion , 2015, NeuroImage.

[19]  H. Johansen-Berg,et al.  Accelerated Changes in White Matter Microstructure during Aging: A Longitudinal Diffusion Tensor Imaging Study , 2014, The Journal of Neuroscience.

[20]  Faith M. Gunning-Dixon,et al.  Aging, sexual dimorphism, and hemispheric asymmetry of the cerebral cortex: replicability of regional differences in volume , 2004, Neurobiology of Aging.

[21]  Nikos Makris,et al.  Automatically parcellating the human cerebral cortex. , 2004, Cerebral cortex.

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

[23]  D. Tuch Q‐ball imaging , 2004, Magnetic resonance in medicine.

[24]  A. Pfefferbaum,et al.  Increased brain white matter diffusivity in normal adult aging: Relationship to anisotropy and partial voluming , 2003, Magnetic resonance in medicine.

[25]  A. Dale,et al.  One-Year Brain Atrophy Evident in Healthy Aging , 2009, The Journal of Neuroscience.

[26]  Julien Cohen-Adad,et al.  The Human Connectome Project and beyond: Initial applications of 300mT/m gradients , 2013, NeuroImage.

[27]  Tim B. Dyrby,et al.  Orientationally invariant indices of axon diameter and density from diffusion MRI , 2010, NeuroImage.

[28]  D. Madden,et al.  Disconnected aging: Cerebral white matter integrity and age-related differences in cognition , 2014, Neuroscience.

[29]  Lars T Westlye,et al.  Mild Cognitive Impairment is Associated With White Matter Integrity Changes in Late-Myelinating Regions Within the Corpus Callosum , 2016, American journal of Alzheimer's disease and other dementias.

[30]  Edith V. Sullivan,et al.  Equivalent disruption of regional white matter microstructure in ageing healthy men and women , 2001, Neuroreport.

[31]  Bruce R. Rosen,et al.  Investigating the Capability to Resolve Complex White Matter Structures with High b-Value Diffusion Magnetic Resonance Imaging on the MGH-USC Connectom Scanner , 2014, Brain Connect..

[32]  Joseph A. Helpern,et al.  Characterizing microstructure of living tissues with time-dependent diffusion , 2012, 1210.3014.

[33]  Arthur W. Toga,et al.  Stereotaxic white matter atlas based on diffusion tensor imaging in an ICBM template , 2008, NeuroImage.

[34]  F. Aboitiz,et al.  Age-related changes in fibre composition of the human corpus callosum: sex differences. , 1996, Neuroreport.

[35]  Edith V. Sullivan,et al.  Frontal circuitry degradation marks healthy adult aging: Evidence from diffusion tensor imaging , 2005, NeuroImage.

[36]  Andrew R. Bender,et al.  White matter and memory in healthy adults: Coupled changes over two years , 2016, NeuroImage.

[37]  J. Helpern,et al.  MRI quantification of non‐Gaussian water diffusion by kurtosis analysis , 2010, NMR in biomedicine.

[38]  Mark W. Woolrich,et al.  Advances in functional and structural MR image analysis and implementation as FSL , 2004, NeuroImage.

[39]  Ruth A. Carper,et al.  Atrophy of the Corpus Callosum in Alzheimer's Disease Versus Healthy Aging , 1996, Journal of the American Geriatrics Society.

[40]  Derek K. Jones,et al.  Including diffusion time dependence in the extra-axonal space improves in vivo estimates of axonal diameter and density in human white matter , 2016, NeuroImage.

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

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

[43]  Stephen M. Smith,et al.  Multiplexed Echo Planar Imaging for Sub-Second Whole Brain FMRI and Fast Diffusion Imaging , 2010, PloS one.

[44]  M. Filippi,et al.  Microstructural changes and atrophy in brain white matter tracts with aging , 2012, Neurobiology of Aging.

[45]  Richard S. Frackowiak,et al.  Regional specificity of MRI contrast parameter changes in normal ageing revealed by voxel-based quantification (VBQ) , 2011, NeuroImage.

[46]  Walter Schneider,et al.  Validation of diffusion MRI estimates of compartment size and volume fraction in a biomimetic brain phantom using a human MRI scanner with 300 mT/m maximum gradient strength , 2018, NeuroImage.

[47]  Christian Beaulieu,et al.  Diffusion anisotropy in subcortical white matter and cortical gray matter: Changes with aging and the role of CSF‐suppression , 2004, Journal of magnetic resonance imaging : JMRI.

[48]  Stamatios N. Sotiropoulos,et al.  An integrated approach to correction for off-resonance effects and subject movement in diffusion MR imaging , 2016, NeuroImage.

[49]  A. Pfefferbaum,et al.  Diffusion tensor imaging and aging , 2006, Neuroscience & Biobehavioral Reviews.

[50]  Mark E Bastin,et al.  Ageing and brain white matter structure in 3,513 UK Biobank participants , 2016, Nature Communications.

[51]  A. Scheibel,et al.  Morphometry of the Sylvian fissure and the corpus callosum, with emphasis on sex differences. , 1992, Brain : a journal of neurology.

[52]  Carl-Fredrik Westin,et al.  Resolution limit of cylinder diameter estimation by diffusion MRI: The impact of gradient waveform and orientation dispersion , 2017, NMR in biomedicine.

[53]  T. Kemper,et al.  Neuroanatomical and neuropathological changes during aging and dementia. , 1994 .

[54]  Anders M. Dale,et al.  Frontal connections and cognitive changes in normal aging rhesus monkeys: A DTI study , 2007, Neurobiology of Aging.

[55]  B. Wandell,et al.  Lifespan maturation and degeneration of human brain white matter , 2014, Nature Communications.

[56]  Markus H. Sneve,et al.  Brain Events Underlying Episodic Memory Changes in Aging: A Longitudinal Investigation of Structural and Functional Connectivity. , 2016, Cerebral cortex.

[57]  M E Shenton,et al.  Lifespan Trajectories of White Matter Changes in Rhesus Monkeys , 2019, Cerebral cortex.

[58]  David H. Salat,et al.  Re-examining age-related differences in white matter microstructure with free-water corrected diffusion tensor imaging , 2018, Neurobiology of Aging.

[59]  A. Dale,et al.  Cortical Surface-Based Analysis II: Inflation, Flattening, and a Surface-Based Coordinate System , 1999, NeuroImage.

[60]  Hauke R. Heekeren,et al.  Age-related differences in white matter microstructure: Region-specific patterns of diffusivity , 2010, NeuroImage.

[61]  Wang Zhan,et al.  Patterns of age-related water diffusion changes in human brain by concordance and discordance analysis , 2010, Neurobiology of Aging.

[62]  Takayuki Obata,et al.  Age-related degeneration of corpus callosum measured with diffusion tensor imaging , 2006, NeuroImage.

[63]  Haruyasu Yamada,et al.  Normal aging in the central nervous system: quantitative MR diffusion-tensor analysis , 2002, Neurobiology of Aging.

[64]  A. Pfefferbaum,et al.  Quantitative fiber tracking of lateral and interhemispheric white matter systems in normal aging: Relations to timed performance , 2010, Neurobiology of Aging.

[65]  Anders M. Dale,et al.  Cortical Surface-Based Analysis I. Segmentation and Surface Reconstruction , 1999, NeuroImage.

[66]  Kawin Setsompop,et al.  Ultra-fast MRI of the human brain with simultaneous multi-slice imaging. , 2013, Journal of magnetic resonance.

[67]  M. Moseley Diffusion tensor imaging and aging – a review , 2002, NMR in biomedicine.

[68]  Jennifer A McNab,et al.  Characterization of Axonal Disease in Patients with Multiple Sclerosis Using High-Gradient-Diffusion MR Imaging. , 2016, Radiology.

[69]  A. Scheibel,et al.  Fiber composition of the human corpus callosum , 1992, Brain Research.

[70]  D. Alexander A general framework for experiment design in diffusion MRI and its application in measuring direct tissue‐microstructure features , 2008, Magnetic resonance in medicine.

[71]  Danielle van Westen,et al.  Diffusion tensor imaging and tractography of the white matter in normal aging: The rate-of-change differs between segments within tracts. , 2018, Magnetic resonance imaging.

[72]  Andrew R. Bender,et al.  Differential aging of cerebral white matter in middle-aged and older adults: A seven-year follow-up , 2016, NeuroImage.

[73]  D. Head,et al.  Differential vulnerability of anterior white matter in nondemented aging with minimal acceleration in dementia of the Alzheimer type: evidence from diffusion tensor imaging. , 2004, Cerebral cortex.

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

[75]  Faith M. Gunning-Dixon,et al.  Aging of cerebral white matter: a review of MRI findings , 2009, International journal of geriatric psychiatry.

[76]  A. Lundervold,et al.  Fractional anisotropy shows differential reduction in frontal-subcortical fiber bundles—A longitudinal MRI study of 76 middle-aged and older adults , 2015, Front. Aging Neurosci..

[77]  Jianfeng Qiu,et al.  Age‐related changes in fiber tracts in healthy adult brains: A generalized q‐sampling and connectometry study , 2018, Journal of magnetic resonance imaging : JMRI.

[78]  Zhe Zhang,et al.  Subcortical White Matter Changes with Normal Aging Detected by Multi-Shot High Resolution Diffusion Tensor Imaging , 2016, PloS one.

[79]  Julien Cohen-Adad,et al.  Pushing the limits of in vivo diffusion MRI for the Human Connectome Project , 2013, NeuroImage.

[80]  R. Peeters,et al.  Age-related microstructural differences quantified using myelin water imaging and advanced diffusion MRI , 2015, Neurobiology of Aging.

[81]  Christian Beaulieu,et al.  Age-related regional variations of the corpus callosum identified by diffusion tensor tractography , 2010, NeuroImage.

[82]  N. Raz,et al.  Aging white matter and cognition: Differential effects of regional variations in diffusion properties on memory, executive functions, and speed , 2009, Neuropsychologia.

[83]  Markus H. Sneve,et al.  Relationship between structural and functional connectivity change across the adult lifespan: A longitudinal investigation , 2017 .

[84]  P. Reuter-Lorenz,et al.  Differential Effects of Aging on the Functions of the Corpus Callosum , 2000, Developmental neuropsychology.

[85]  Joseph A. Helpern,et al.  White matter characterization with diffusional kurtosis imaging , 2011, NeuroImage.

[86]  Stephen M. Smith,et al.  Age-related changes in grey and white matter structure throughout adulthood , 2010, NeuroImage.

[87]  Caterina Mainero,et al.  A surface‐based technique for mapping homotopic interhemispheric connectivity: Development, characterization, and clinical application , 2016, Human brain mapping.

[88]  J. Cummings,et al.  The Montreal Cognitive Assessment, MoCA: A Brief Screening Tool For Mild Cognitive Impairment , 2005, Journal of the American Geriatrics Society.

[89]  A. Pfefferbaum,et al.  Selective age-related degradation of anterior callosal fiber bundles quantified in vivo with fiber tracking. , 2006, Cerebral cortex.

[90]  D. Barazany,et al.  AxCaliber 3D , 2010 .

[91]  Dan Wang,et al.  Application of super‐resolution track‐density technique: Earlier detection of aging‐related subtle alterations than morphological changes in corpus callosum from normal population? , 2019, Journal of magnetic resonance imaging : JMRI.

[92]  J. H. Howard,et al.  Age‐related differences in multiple measures of white matter integrity: A diffusion tensor imaging study of healthy aging , 2009, Human brain mapping.

[93]  Anders M. Fjell,et al.  White matter integrity as a marker for cognitive plasticity in aging , 2016, Neurobiology of Aging.

[94]  Jens Frahm,et al.  Topography of the human corpus callosum revisited—Comprehensive fiber tractography using diffusion tensor magnetic resonance imaging , 2006, NeuroImage.

[95]  A. Dale,et al.  Age‐Related Changes in Prefrontal White Matter Measured by Diffusion Tensor Imaging , 2005, Annals of the New York Academy of Sciences.

[96]  Jung-Lung Hsu,et al.  Gender differences and age-related white matter changes of the human brain: A diffusion tensor imaging study , 2008, NeuroImage.

[97]  Jelle Veraart,et al.  In vivo observation and biophysical interpretation of time-dependent diffusion in human white matter , 2016, NeuroImage.

[98]  Bruce Fischl,et al.  FreeSurfer , 2012, NeuroImage.

[99]  Julien Cohen-Adad,et al.  The impact of gradient strength on in vivo diffusion MRI estimates of axon diameter , 2015, NeuroImage.

[100]  I. V. D. van der Ham,et al.  How does the corpus callosum mediate interhemispheric transfer? A review. , 2011, Behavioural brain research.

[101]  M S Buchsbaum,et al.  Regional and global changes in cerebral diffusion with normal aging. , 2001, AJNR. American journal of neuroradiology.

[102]  Dmitry S. Novikov,et al.  What dominates the time dependence of diffusion transverse to axons: Intra- or extra-axonal water? , 2017, NeuroImage.

[103]  Itamar Ronen,et al.  Differentiating between axonal damage and demyelination in healthy aging by combining diffusion-tensor imaging and diffusion-weighted spectroscopy in the human corpus callosum at 7 T , 2016, Neurobiology of Aging.

[104]  Mark Jenkinson,et al.  Evaluating fibre orientation dispersion in white matter: Comparison of diffusion MRI, histology and polarized light imaging , 2017, NeuroImage.

[105]  Markus Nilsson,et al.  Investigating tissue microstructure using diffusion MRI : How does the resolution limit of the axon diameter relate to the maximal gradient strength ? , 2011 .

[106]  K. Lim,et al.  Age‐related decline in brain white matter anisotropy measured with spatially corrected echo‐planar diffusion tensor imaging , 2000, Magnetic resonance in medicine.

[107]  Roberto Cabeza,et al.  Assessing the effects of age on long white matter tracts using diffusion tensor tractography , 2009, NeuroImage.

[108]  P. Moes,et al.  Interhemispheric transfer time differences related to aging and gender , 1996, Neuropsychologia.

[109]  M. Thiebaut de Schotten,et al.  Atlasing the frontal lobe connections and their variability due to age and education: a spherical deconvolution tractography study , 2015, Brain Structure and Function.

[110]  Yaniv Assaf,et al.  Composite hindered and restricted model of diffusion (CHARMED) MR imaging of the human brain , 2005, NeuroImage.

[111]  Julien Cohen-Adad,et al.  Improving diffusion MRI using simultaneous multi-slice echo planar imaging , 2012, NeuroImage.

[112]  André J. W. van der Kouwe,et al.  Brain morphometry with multiecho MPRAGE , 2008, NeuroImage.