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Towards a representative reference for MRI-based human axon radius assessment using light microscopy.
- Source :
-
NeuroImage [Neuroimage] 2022 Apr 01; Vol. 249, pp. 118906. Date of Electronic Publication: 2022 Jan 13. - Publication Year :
- 2022
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Abstract
- Non-invasive assessment of axon radii via MRI bears great potential for clinical and neuroscience research as it is a main determinant of the neuronal conduction velocity. However, there is a lack of representative histological reference data at the scale of the cross-section of MRI voxels for validating the MRI-visible, effective radius (r <subscript>eff</subscript> ). Because the current gold standard stems from neuroanatomical studies designed to estimate the bulk-determined arithmetic mean radius (r <subscript>arith</subscript> ) on small ensembles of axons, it is unsuited to estimate the tail-weighted r <subscript>eff</subscript> . We propose CNN-based segmentation on high-resolution, large-scale light microscopy (lsLM) data to generate a representative reference for r <subscript>eff</subscript> . In a human corpus callosum, we assessed estimation accuracy and bias of r <subscript>arith</subscript> and r <subscript>eff</subscript> . Furthermore, we investigated whether mapping anatomy-related variation of r <subscript>arith</subscript> and r <subscript>eff</subscript> is confounded by low-frequency variation of the image intensity, e.g., due to staining heterogeneity. Finally, we analyzed the error due to outstandingly large axons in r <subscript>eff</subscript> . Compared to r <subscript>arith</subscript> , r <subscript>eff</subscript> was estimated with higher accuracy (maximum normalized-root-mean-square-error of r <subscript>eff</subscript> : 8.5 %; r <subscript>arith</subscript> : 19.5 %) and lower bias (maximum absolute normalized-mean-bias-error of r <subscript>eff</subscript> : 4.8 %; r <subscript>arith</subscript> : 13.4 %). While r <subscript>arith</subscript> was confounded by variation of the image intensity, variation of r <subscript>eff</subscript> seemed anatomy-related. The largest axons contributed between 0.8 % and 2.9 % to r <subscript>eff</subscript> . In conclusion, the proposed method is a step towards representatively estimating r <subscript>eff</subscript> at MRI voxel resolution. Further investigations are required to assess generalization to other brains and brain areas with different axon radii distributions.<br />Competing Interests: Declaration of Competing Interest The Max Planck Institute for Human Cognitive and Brain Sciences has an institutional research agreement with Siemens Healthcare. NW was a speaker at an event organized by Siemens Healthcare and was reimbursed for the travel expenses.<br /> (Copyright © 2022. Published by Elsevier Inc.)
Details
- Language :
- English
- ISSN :
- 1095-9572
- Volume :
- 249
- Database :
- MEDLINE
- Journal :
- NeuroImage
- Publication Type :
- Academic Journal
- Accession number :
- 35032659
- Full Text :
- https://doi.org/10.1016/j.neuroimage.2022.118906