A robust framework for characterising diffusion metrics of the median and ulnar nerves: Exploiting state‐of‐the‐art tracking methods

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).