Imaging laminar structures in the gray matter with diffusion MRI

The cortical layers define the architecture of the gray matter and its neuroanatomical regions and are essential for brain function. Abnormalities in cortical layer development, growth patterns, organization, or size can affect brain physiology and cognition. Unfortunately, while large population studies are underway that will greatly increase our knowledge about these processes, current non-invasive techniques for characterizing the cortical layers remain inadequate. For decades, high-resolution T1 and T2 Weighted Magnetic Resonance Imaging (MRI) have been the method-of-choice for gray matter and layer characterization. In the past few years, however, diffusion MRI has shown increasing promise for its unique insights into the fine structure of the cortex. Several different methods, including surface analysis, connectivity exploration, and sub-voxel component modeling, are now capable of exploring the diffusion characteristics of the cortex. In this review, we will discuss current advances in the application of diffusion imaging for cortical characterization and its unique features, with a particular emphasis on its spatial resolution, arguably its greatest limitation. In addition, we will explore the relationship between the diffusion MRI signal and the cellular components of the cortex, as visualized by histology. While the obstacles facing the widespread application of cortical diffusion imaging remain daunting, the information it can reveal may prove invaluable. Within the next few years, we predict a surge in the application of this technique and a concomitant expansion of our knowledge of cortical layers.

[1]  Christopher D. Kroenke,et al.  Determination of Axonal and Dendritic Orientation Distributions Within the Developing Cerebral Cortex by Diffusion Tensor Imaging , 2012, IEEE Transactions on Medical Imaging.

[2]  O. Sporns Networks of the Brain , 2010 .

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

[4]  David R. Haynor,et al.  Anatomically Informed Metrics for Connectivity-Based Cortical Parcellation From Diffusion MRI , 2015, IEEE Journal of Biomedical and Health Informatics.

[5]  Lazaros C. Triarhou,et al.  A Proposed Number System for the 107 Cortical Areas of Economo and Koskinas, and Brodmann Area Correlations , 2007, Stereotactic and Functional Neurosurgery.

[6]  宮田 淳,et al.  精神科領域の用語解説 Surface-based analysis , 2015 .

[7]  M. Jenkinson,et al.  In vivo identification of human cortical areas using high-resolution MRI: An approach to cerebral structure–function correlation , 2003, Proceedings of the National Academy of Sciences of the United States of America.

[8]  Timothy E. J. Behrens,et al.  Measuring macroscopic brain connections in vivo , 2015, Nature Neuroscience.

[9]  David L. Thomas,et al.  Using High Angular Resolution Diffusion Imaging Data to Discriminate Cortical Regions , 2013, PloS one.

[10]  P. Basser Inferring microstructural features and the physiological state of tissues from diffusion‐weighted images , 1995, NMR in biomedicine.

[11]  R. Turner,et al.  Layer-Specific Intracortical Connectivity Revealed with Diffusion MRI , 2012, Cerebral cortex.

[12]  Alan Connelly,et al.  Robust determination of the fibre orientation distribution in diffusion MRI: Non-negativity constrained super-resolved spherical deconvolution , 2007, NeuroImage.

[13]  A. Anwander,et al.  Validation of tractography: Comparison with manganese tracing , 2015, Human brain mapping.

[14]  Keith Heberlein,et al.  Imaging human connectomes at the macroscale , 2013, Nature Methods.

[15]  E Courchesne,et al.  In vivo myeloarchitectonic analysis of human striate and extrastriate cortex using magnetic resonance imaging. , 1992, Cerebral cortex.

[16]  Lauren L. Cloutman,et al.  Connectivity-based structural and functional parcellation of the human cortex using diffusion imaging and tractography , 2012, Front. Neuroanat..

[17]  P. Basser,et al.  MR diffusion tensor spectroscopy and imaging. , 1994, Biophysical journal.

[18]  Mark W. Woolrich,et al.  Probabilistic diffusion tractography with multiple fibre orientations: What can we gain? , 2007, NeuroImage.

[19]  Mara Cercignani,et al.  Twenty‐five pitfalls in the analysis of diffusion MRI data , 2010, NMR in biomedicine.

[20]  L. Garey Brodmann's localisation in the cerebral cortex , 1999 .

[21]  Alan C. Evans,et al.  Mapping anatomical connectivity patterns of human cerebral cortex using in vivo diffusion tensor imaging tractography. , 2009, Cerebral cortex.

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

[23]  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.

[24]  Nico S. Gorbach,et al.  Hierarchical Information-Based Clustering for Connectivity-Based Cortex Parcellation , 2011, Front. Neuroinform..

[25]  Desmond J. Higham,et al.  Connectivity-based parcellation of human cortex using diffusion MRI: Establishing reproducibility, validity and observer independence in BA 44/45 and SMA/pre-SMA , 2007, NeuroImage.

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

[27]  S S Kollias,et al.  Preliminary Experience with Visualization of Intracortical Fibers by Focused High-Resolution Diffusion Tensor Imaging , 2008, American Journal of Neuroradiology.

[28]  M. Catani,et al.  Monkey to human comparative anatomy of the frontal lobe association tracts , 2012, Cortex.

[29]  Alfred Anwander,et al.  A hierarchical method for whole‐brain connectivity‐based parcellation , 2014, Human brain mapping.

[30]  W. Baaré,et al.  An ex vivo imaging pipeline for producing high‐quality and high‐resolution diffusion‐weighted imaging datasets , 2011, Human brain mapping.

[31]  Tim B. Dyrby,et al.  Comparison of diffusion tractography and manganese tracing , 2011 .

[32]  Yaniv Assaf,et al.  Micro-structural assessment of short term plasticity dynamics , 2013, NeuroImage.

[33]  Jeong-Won Jeong,et al.  Surface‐based laminar analysis of diffusion abnormalities in cortical and white matter layers in neocortical epilepsy , 2013, Epilepsia.

[34]  P. Hagmann,et al.  Mapping complex tissue architecture with diffusion spectrum magnetic resonance imaging , 2005, Magnetic resonance in medicine.

[35]  Jesper Andersson,et al.  A multi-modal parcellation of human cerebral cortex , 2016, Nature.

[36]  Robert Turner,et al.  Diffusion imaging in humans at 7T using readout‐segmented EPI and GRAPPA , 2010, Magnetic resonance in medicine.

[37]  T. Chenevert,et al.  Anisotropic diffusion in human white matter: demonstration with MR techniques in vivo. , 1990, Radiology.

[38]  J. Kucharczyk,et al.  Anisotropy in diffusion‐weighted MRI , 1991, Magnetic resonance in medicine.

[39]  J. Grafman,et al.  Imaging cortical anatomy by high‐resolution MR at 3.0T: Detection of the stripe of Gennari in visual area 17 , 2002, Magnetic resonance in medicine.

[40]  P. Basser,et al.  Toward a quantitative assessment of diffusion anisotropy , 1996, Magnetic resonance in medicine.

[41]  Olaf Sporns,et al.  From simple graphs to the connectome: Networks in neuroimaging , 2012, NeuroImage.

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

[43]  David G. Norris,et al.  Diffusion tensor characteristics of gyrencephaly using high resolution diffusion MRI in vivo at 7T , 2015, NeuroImage.

[44]  Susumu Mori,et al.  Probing region-specific microstructure of human cortical areas using high angular and spatial resolution diffusion MRI , 2015, NeuroImage.

[45]  Xia Li,et al.  Tests of cortical parcellation based on white matter connectivity using diffusion tensor imaging , 2017, NeuroImage.

[46]  Timothy Edward John Behrens,et al.  Non-invasive mapping of connections between human thalamus and cortex using diffusion imaging , 2003, Nature Neuroscience.

[47]  A. Song,et al.  Cortical Depth Dependence of the Diffusion Anisotropy in the Human Cortical Gray Matter In Vivo , 2014, PloS one.

[48]  H. Barbas,et al.  Cortical structure predicts the pattern of corticocortical connections. , 1997, Cerebral cortex.

[49]  Christoph Palm,et al.  A novel approach to the human connectome: Ultra-high resolution mapping of fiber tracts in the brain , 2011, NeuroImage.

[50]  Hui Zhang,et al.  Detailed laminar characteristics of the human neocortex revealed by NODDI , 2013 .

[51]  A. Schleicher,et al.  High‐resolution MRI reflects myeloarchitecture and cytoarchitecture of human cerebral cortex , 2005, Human brain mapping.

[52]  Claus C Hilgetag,et al.  Bridging Cytoarchitectonics and Connectomics in Human Cerebral Cortex , 2015, The Journal of Neuroscience.

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

[54]  Yu Zhang,et al.  The Human Brainnetome Atlas: A New Brain Atlas Based on Connectional Architecture , 2016, Cerebral cortex.

[55]  Daniel C Alexander,et al.  High angular resolution diffusion imaging with stimulated echoes: compensation and correction in experiment design and analysis , 2014, NMR in biomedicine.

[56]  P. Basser,et al.  A simplified method to measure the diffusion tensor from seven MR images , 1998, Magnetic resonance in medicine.

[57]  J. Frank,et al.  The contribution of gliosis to diffusion tensor anisotropy and tractography following traumatic brain injury: validation in the rat using Fourier analysis of stained tissue sections. , 2011, Brain : a journal of neurology.

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

[59]  M. Budde,et al.  Quantification of anisotropy and fiber orientation in human brain histological sections , 2012, Front. Integr. Neurosci..

[60]  A. Anwander,et al.  Connectivity-Based Parcellation of Broca's Area. , 2006, Cerebral cortex.

[61]  M. Descoteaux High Angular Resolution Diffusion Imaging (HARDI) , 2015 .

[62]  Derek K. Jones Diffusion MRI: Theory, methods, and applications , 2011 .

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

[64]  Stephan E Maier,et al.  Developmental changes and injury induced disruption of the radial organization of the cortex in the immature rat brain revealed by in vivo diffusion tensor MRI. , 2007, Cerebral cortex.

[65]  Cornelis H. Slump,et al.  Layer-specific diffusion weighted imaging in human primary visual cortex in vitro , 2013, Cortex.

[66]  O. Sporns,et al.  Mapping the Structural Core of Human Cerebral Cortex , 2008, PLoS biology.

[67]  D. V. van Essen,et al.  Mapping Human Cortical Areas In Vivo Based on Myelin Content as Revealed by T1- and T2-Weighted MRI , 2011, The Journal of Neuroscience.

[68]  Jelliffe Vergleichende Lokalisationslehre der Grosshirnrinde , 1910 .

[69]  P. Thiran,et al.  Mapping Human Whole-Brain Structural Networks with Diffusion MRI , 2007, PloS one.

[70]  A. van Cappellen van Walsum,et al.  Recent advancements in diffusion MRI for investigating cortical development after preterm birth—potential and pitfalls , 2015, Front. Hum. Neurosci..

[71]  Jeremy D. Schmahmann,et al.  Diffusion spectrum magnetic resonance imaging (DSI) tractography of crossing fibers , 2008, NeuroImage.