White Matter microstructural property decoding from gradient echo data using realistic white matter models

White Matter microstructural property decoding from gradient echo data using realistic white matter models

Publication date: Jun 23, 2020

The multi-echo gradient echo (ME-GRE) magnetic resonance signal evolution in white matter has a strong dependence on the orientation of myelinated axons in respect to the main static field. Although analytical solutions, based on the Hollow Cylinder Model have been able to predict some of the behaviour the hollow cylinder model, it has been shown that realistic models of white matter offer a better description of the signal behaviout observed. In this work, we present a pipeline to (i) generate realistic 2D white matter models with its microstructure based on real axon but with arbitrary fiber volume fraction (FVF) and g-ratio. We (ii) simulate their interaction with the static magnetic field to be able to simulate their MR signal. For the first time, we (iii) demonstrate that realistic 2D models can be used to simulate an MR signal that provides a good approximation of the signal obtained from a real 3D white matter model obtained using electron microscopy. We then (iv) demonstrate in silico that 2D WM models can be used to predict microstructural parameters in a robust way if multi-echo multi-orientation data is available and the main fiber orientation in each pixel is known using DTI. A Deep Learning Network was trained and characterized in its ability to recover the desired microstructural parameters such as FVF, g-ratio, free and bound water transverse relaxation and magnetic susceptibility. Finally, the network was trained to recover these micro-structural parameters from an ex-vivo dataset acquired in 9-orientations in respect to the magnetic field and 12 echo times. We demonstrate that this is an overdetermined problem and that as few as 3 orientations can already provide comparable results for some of the decoded metrics. [Highlights] – A pipeline to generate realistic white matter models of arbitrary fiber volume fraction and g-ratio is presented; – We present a methodology to simulated the gradient echo signal from segmented 2D and 3D models of white matter, which takes into account the interaction of the static magnetic field with the anisotropic susceptibility of the myelin phospholipids; – Deep Learning Networks can be used to decode microstructural white matter parameters from the signal of multi-echo multi-orientation data;

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Concepts Keywords
Algorithm Experimental protocol
Anisotropic Makesour network
Axon Learning networks
Axons Chemical exchange
Brain Sufficient experimental protocol
Canine Parallel imaging artifactsinto
Central Nervous System Inmagnetic resonance imaging
Christian Reducewater diffusivity protocol
Deep Learning Invasive imaging methodsthat
Deep Neural Network Branches of biology
Demyelination Neuroscience
Diamagnetic Organ systems
DTI Glial cells
DWI Myelin
Echo Times Axon
Electric Insulator White matter
Electron Microscopy Oligodendrocyte
Evolution Brain
Fiber Demyelinating disease
Frequency Corpus callosum
Glial Reducewater diffusivity protocol
Gradient Neural network
GRE 1 Algorithm
Heidelberg DWI protocol
Histology Simulation
Hydrophobic Sufficient experimental protocol
Imation MRI
Infor
Isotropic
Licht
Lipid
Magnetic Field
Magnetic Susceptibility
Magnetization
Magnitude
Mannheim
Mat
Microstructure
Models 1
MRI
Myelin
Myelin Sheath
Myelinated
Netherlands
Neurodegenerative Disorders
Nijmegen
Perturbation
Phospholipids
Pipeline
Pixel
Ppm
Proton
Resonance
Scalar
Spin
Spinal Cord
Square Root
Symmetry
Tensor
Unmyelinated
Vertebrate
Vivo
Volume Fraction
Walsum
White
White Matter

Semantics

Type Source Name
drug DRUGBANK Flunarizine
drug DRUGBANK Tropicamide
drug DRUGBANK Water
drug DRUGBANK Omega-3 fatty acids
drug DRUGBANK Ilex paraguariensis leaf
disease MESH demyelination
disease MESH neurodegenerative disorders
drug DRUGBANK Coenzyme M
disease MESH diagnosis
disease MESH separated
drug DRUGBANK Formaldehyde
drug DRUGBANK Medical air
disease MESH visual
drug DRUGBANK Aspartame
drug DRUGBANK Iron
drug DRUGBANK Trestolone
disease MESH tic

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