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 on the scale of the cross-section of MRI voxels for validating the MRI-visible, effective radius (reff). Because the current gold standard stems from neuroanatomical studies designed to estimate the frequency-weighted arithmetic mean radius (rarith) on small ensembles of axons, it is unsuited to estimate the tail-weighted reff. We propose CNN-based segmentation on high-resolution, large-scale light microscopy (lsLM) data to generate a representative reference for reff. In a human corpus callosum, we assessed estimation accuracy and bias of rarith and reff. Furthermore, we investigated whether mapping anatomy-related variation of rarith and reff is confounded by low-frequency variation of the image intensity, e.g., due to staining heterogeneity. Finally, we analyzed the potential error due to outstandingly large axons in reff. Compared to rarith, reff was estimated with higher accuracy (normalized-root-mean-square-error of reff: 7.2 %; rarith: 21.5 %) and lower bias (normalized-mean-bias-error of reff: −1.7 %; rarith: 16 %). While rarith was confounded by variation of the image intensity, variation of reff seemed anatomy-related. The largest axons contributed between 0.9 % and 3 % to reff. In conclusion, the proposed method accurately estimates reff at MRI voxel resolution across a human corpus callosum sample. Further investigations are required to assess generalization to brain areas with different axon radii ensembles.
Competing Interest Statement
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.
List of Symbols and Acronyms
- r
- individual axon radius
- r
- axon radii ensemble
- reference axon radii ensemble
- EM-based axon radii ensemble obtained through annotation of SEM
- lsLM-based axon radii ensemble for large axons obtained through annotation of SlsLM,large
- estimated axon radii ensemble
- estimated axon radii ensemble with erroneous radii in axon radii range rng
- small
- axons with r < 0.3 µm
- medium-sized
- axons with 0.3 µm ≤ r < 1.8 µm
- large
- axons with r ≥ 1.8 µm
- rarith
- arithmetic mean radius
- reference arithmetic mean radius
- estimated arithmetic mean radius
- reff
- effective radius
- reference effective radius
- estimated effective radius
- estimated effective radius based on an axon radii ensemble with erroneous radii in axon radii range rng
- SEM
- EM subsection
- SlsLM
- small lsLM subsection
- SlsLM,large
- large lsLM subsection
- CNN
- convolutional neural network
- EM
- electron microscopy
- lsLM
- high-resoution, large-scale light microscopy
- NMBE
- normalized-mean-bias-error
- NRMSE
- normalized-root-mean-square-error