Axons morphometry in the human spinal cord

&NA; Due to the technical challenges of large‐scale microscopy and analysis, to date only limited knowledge has been made available about axon morphometry (diameter, shape, myelin thickness, volume fraction), thereby limiting our understanding of neuronal microstructure and slowing down research on neurodegenerative pathologies. This study addresses this knowledge gap by establishing a state‐of‐the‐art acquisition and analysis framework for mapping axon morphometry, and providing the first comprehensive mapping of axon morphometry in the human spinal cord. We dissected, fixed and stained a human spinal cord with osmium tetroxide, and used a scanning electron microscope to image the entirety of 23 axial slices, covering C1 to L5 spinal levels. An automatic method based on deep learning was then used to segment each axon and myelin sheath to produce maps of axon morphometry. These maps were then registered to a standard spinal cord magnetic resonance imaging (MRI) template. Between 500,000 (lumbar) and 1 million (cervical) myelinated axons were segmented at each level of this human spinal cord. Morphometric features show a large disparity between tracts, but high right‐left symmetry. Our results suggest a modality‐based organization of the dorsal column in the human, as it has been observed in the rat. The generated axon morphometry template is publicly available at https://osf.io/8k7jr/ and could be used as a reference for quantitative MRI studies. The proposed framework for axon morphometry mapping could be extended to other parts of the central or peripheral nervous system that exhibit coherently‐oriented axons. Graphical abstract Figure. No caption available. Highlights3D atlas of the human spinal cord white matter microstructureMetrics include axon diameter, axon density, myelin density and g‐ratioThe atlas has been constructed from high resolution electron microscopyThe atlas is registered to an existing spinal cord MRI template (PAM50) as part of SCTThe atlas is publicly available at https://osf.io/8k7jr/

[1]  M. A. Biedenbach,et al.  Pyramidal tract of the cat: axon size and morphology , 2004, Experimental Brain Research.

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

[3]  G. Knott,et al.  Serial Section Scanning Electron Microscopy of Adult Brain Tissue Using Focused Ion Beam Milling , 2008, The Journal of Neuroscience.

[4]  Robert Plonsey,et al.  Bioelectricity: A Quantitative Approach Duke University’s First MOOC , 2013 .

[5]  Erik Bélanger,et al.  Automated method for the segmentation and morphometry of nerve fibers in large-scale CARS images of spinal cord tissue. , 2014, Biomedical optics express.

[6]  G. Paxinos,et al.  The Spinal Cord: A Christopher and Dana Reeve Foundation Text and Atlas , 2009 .

[7]  Julien Cohen-Adad,et al.  AxonDeepSeg: automatic axon and myelin segmentation from microscopy data using convolutional neural networks , 2017, Scientific Reports.

[8]  Julien Cohen-Adad,et al.  g-Ratio weighted imaging of the human spinal cord in vivo , 2017, NeuroImage.

[9]  M. Helmstaedter,et al.  Large-volume en-bloc staining for electron microscopy-based connectomics , 2015, Nature Communications.

[10]  A. M. Lassek THE HUMAN PYRAMIDAL TRACT: XI. CORRELATION OF THE BABINSKI SIGN AND THE PYRAMIDAL SYNDROME , 1945 .

[11]  Torben Schneider,et al.  A framework for optimal whole-sample histological quantification of neurite orientation dispersion in the human spinal cord , 2016, Journal of Neuroscience Methods.

[12]  Jan Voogd,et al.  The human central nervous system : a synopsis and atlas , 1978 .

[13]  L. A. Kenna Eccentricity in Ellipses , 1959 .

[14]  P. Sterling,et al.  Why Do Axons Differ in Caliber? , 2012, The Journal of Neuroscience.

[15]  Julien Cohen-Adad,et al.  Quantitative MRI of the Spinal Cord , 2014 .

[16]  Julien Cohen-Adad,et al.  SCT: Spinal Cord Toolbox, an open-source software for processing spinal cord MRI data , 2017, NeuroImage.

[17]  H. Ralston,et al.  Non-myelinated axons are rare in the medullary pyramids of the macaque monkey , 1987, Neuroscience Letters.

[18]  Alejandra Sierra,et al.  Automated 3D Axonal Morphometry of White Matter , 2018 .

[19]  H. Johansen-Berg,et al.  Unraveling the secrets of white matter – Bridging the gap between cellular, animal and human imaging studies , 2014, Neuroscience.

[20]  Julien Cohen-Adad,et al.  Microstructural imaging in the spinal cord and validation strategies , 2018, NeuroImage.

[21]  Verhaart Wj The pyramidal tract. Its structure and functions in man and animals. , 1962 .

[22]  Hiroki R Ueda,et al.  Whole-body and Whole-Organ Clearing and Imaging Techniques with Single-Cell Resolution: Toward Organism-Level Systems Biology in Mammals. , 2016, Cell chemical biology.

[23]  Wenqin Luo,et al.  Modality-Based Organization of Ascending Somatosensory Axons in the Direct Dorsal Column Pathway , 2013, The Journal of Neuroscience.

[24]  Julien Cohen-Adad,et al.  Axon and Myelin Morphology in Animal and Human Spinal Cord , 2017, Front. Neuroanat..

[25]  P. Sterling,et al.  How the Optic Nerve Allocates Space, Energy Capacity, and Information , 2009, The Journal of Neuroscience.

[26]  Johannes E. Schindelin,et al.  Fiji: an open-source platform for biological-image analysis , 2012, Nature Methods.

[27]  David E. Comings,et al.  Principles and techniques of electron microscopy: Biological applications , 1971 .

[28]  R. N. Lemon,et al.  Axon diameters and conduction velocities in the macaque pyramidal tract , 2014, Journal of neurophysiology.

[29]  W. Verhaart The pyramidal tract. Its structure and functions in man and animals. , 1962, World Neurology.

[30]  Linda G. Shapiro,et al.  Computer and Robot Vision , 1991 .

[31]  Julien Cohen-Adad,et al.  In vivo mapping of human spinal cord microstructure at 300mT/m , 2015, NeuroImage.

[32]  A. Veicsteinas,et al.  Time and frequency domain analysis of electromyogram and sound myogram in the elderly , 2004, European Journal of Applied Physiology and Occupational Physiology.

[33]  H. Gray Anatomy, Descriptive and Surgical , 1858, Glasgow Medical Journal.

[34]  W. Denk,et al.  Staining and embedding the whole mouse brain for electron microscopy , 2012, Nature Methods.

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

[36]  R. Ordidge,et al.  High field MRI correlates of myelin content and axonal density in multiple sclerosis , 2003, Journal of Neurology.

[37]  W. Demyer Number of axons and myelin sheaths in adult human medullary pyramids , 1959, Neurology.

[38]  S. Standring Gray's Anatomy: The Anatomical Basis of Clinical Practice , 2015 .

[39]  Julien Cohen-Adad,et al.  Test-retest reliability of myelin imaging in the human spinal cord: Measurement errors versus region- and aging-induced variations , 2018, PloS one.

[40]  A. M. Lassek,et al.  A comparative fiber and numerical analysis of the pyramidal tract , 1940 .

[41]  Ullrich Köthe,et al.  Ilastik: Interactive learning and segmentation toolkit , 2011, 2011 IEEE International Symposium on Biomedical Imaging: From Nano to Macro.

[42]  Julien Cohen-Adad,et al.  White matter atlas of the human spinal cord with estimation of partial volume effect , 2015, NeuroImage.

[43]  Julien Cohen-Adad,et al.  PAM50: Unbiased multimodal template of the brainstem and spinal cord aligned with the ICBM152 space , 2018, NeuroImage.

[44]  Stephan Saalfeld,et al.  Globally optimal stitching of tiled 3D microscopic image acquisitions , 2009, Bioinform..

[45]  W. Denk,et al.  High-resolution whole-brain staining for electron microscopic circuit reconstruction , 2015, Nature Methods.

[46]  Julien Cohen-Adad,et al.  AxonSeg: Open Source Software for Axon and Myelin Segmentation and Morphometric Analysis , 2016, Front. Neuroinform..

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

[48]  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.