A robust framework for characterising diffusion metrics of the median and ulnar nerves: Exploiting state-of-the-art...

Diffusion-weighted imaging has been used to quantify peripheral nerve properties; however, traditional post-processing techniques have several limitations. Advanced neuroimaging techniques, which overcome many of these limitations, have not been applied to peripheral nerves. Here, we use state-of-the-art diffusion analysis tools to reconstruct the median and ulnar nerves and quantify their diffusion properties. Diffusion-weighted MRI scans were obtained from eight healthy adult subjects. Constrained spherical deconvolution was combined with probabilistic fibre tracking to compute track-weighted fibre orientation distribution (TW-FOD). The tensor was computed and used along with the tracks to estimate TW apparent diffusion coefficient (TW-ADC), TW fractional anisotropy (TW-FA), TW axial diffusivity (TW-AD), and TW radial diffusivity (TW-RD). Variability of TW measurements was used to estimate power size information. The population intersession mean (± SD) measurements for the median nerve were TW-FOD 1.30 (±0.17), TW-ADC 1.16 (±0.13) × 10^-3  mm² /s, TW-FA 0.60 (±0.05), TW-AD 2.05 (±0.16) × 10^-3  mm² /s, and TW-RD 0.72 (±0.12) × 10^-3  mm² /s. The corresponding measurements for the ulnar nerve were TW-FOD 1.25 (±0.14), TW-ADC 1.13 (±0.10) × 10^-3  mm² /s, TW-FA 0.56 (±0.06), TW-AD 1.93 (±0.01) × 10^-3  mm² /s, and TW-RD 0.74 (±0.12) × 10^-3  mm² /s. Based on these measurements, a sample size of 37 would be sufficient to detect a 10% difference in any of the measured TW metrics. A sample size of 20 would be large enough to detect within-subject differences as small as 2.9% (TW-AD, ulnar nerve) and between-subject differences as small as 3.8% (TW-AD, ulnar nerve).