A time-dependent diffusion MRI signature of axon caliber variations and beading

Hong-Hsi Lee,Els Fieremans,Dmitry S Novikov,Sung-Lyoung Kim,Antonios Papaioannou

doi:10.1038/s42003-020-1050-x

Hong-Hsi Lee, Els Fieremans + Show 3 more

Open Access

https://doi.org/10.1038/s42003-020-1050-x

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Abstract

MRI provides a unique non-invasive window into the brain, yet is limited to millimeter resolution, orders of magnitude coarser than cell dimensions. Here, we show that diffusion MRI is sensitive to the micrometer-scale variations in axon caliber or pathological beading, by identifying a signature power-law diffusion time-dependence of the along-fiber diffusion coefficient. We observe this signature in human brain white matter and identify its origins by Monte Carlo simulations in realistic substrates from 3-dimensional electron microscopy of mouse corpus callosum. Simulations reveal that the time-dependence originates from axon caliber variation, rather than from mitochondria or axonal undulations. We report a decreased amplitude of time-dependence in multiple sclerosis lesions, illustrating the potential sensitivity of our method to axonal beading in a plethora of neurodegenerative disorders. This specificity to microstructure offers an exciting possibility of bridging across scales to image cellular-level pathology with a clinically feasible MRI technique.

Highlights

MRI provides a unique non-invasive window into the brain, yet is limited to millimeter resolution, orders of magnitude coarser than cell dimensions
How adequate is the picture of featureless sticks? In this work, we show that the diffusion inside the intra-axonal space (IAS) along axons is nonGaussian at clinically employed diffusion times t ~ 10–100 ms and identify the dominant geometric features for this non-Gaussianity, which can be quantified with a Diffusion magnetic resonance imaging (dMRI) measurement
To verify the power law (1) and attribute it to axon caliber variation, we evaluate the effect of axon shape on diffusion by developing, for the first time to our knowledge, a full three-dimensional (3d) Monte Carlo (MC) simulations of dMRI in a realistic microgeometry based on 3d electron microscopy (EM) segmentation[23] of mouse brain corpus callosum (CC)

Summary

Introduction

MRI provides a unique non-invasive window into the brain, yet is limited to millimeter resolution, orders of magnitude coarser than cell dimensions. Intra-axonal diffusion has been described[5] as occurring within infinitely narrow featureless impermeable tubes—dubbed “sticks”—inside which diffusion is effectively one-dimensional and Gaussian, completely determined by a constant diffusion coefficient This simplified viewpoint—a cornerstone ingredient of the so-called WM Standard Model4—has been the basis for WM dMRI modeling over more than a decade, approximating the net intra-axonal space (IAS) within an MRI voxel as a collection of these sticks. Selecting models becomes feasible by testing their unique functional forms in the domain where the dependence on experimental parameters clearly reveals their assumptions[12] Borrowing this methodology from the physical sciences, the assumptions of the existence of sticks (i.e., of the locally one-dimensional (1d) water diffusion) and of negligible exchange between sticks and extra-axonal water on the time scale of clinical dMRI have bpeffieffin validated in vivo in human brain WM by observing the 1= b dMRI signal scaling (ideal stick response) at very strong diffusion weighting b ~ 10 ms/μm[2 11,13]. We focus on varying the diffusion time t rather than on increasing the dMRI wave vector q

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