Relevance of time‐dependence for clinically viable diffusion imaging of the spinal cord - Grussu, Francesco; Ianuş, Andrada; Tur, Carmen; Prados, Ferran; Schneider, Torben; Kaden, Enrico; Ourselin, Sébastien; Drobnjak, Ivana; Zhang, Hui; Alexander, Daniel C.; Gandini Wheeler‐Kingshott, Claudia A. M. (Magnetic resonance in medicine, 2019)
Purpose Time‐dependence is a key feature of the diffusion‐weighted (DW) signal, knowledge of which informs biophysical modelling. Here, we study time‐dependence in the human spinal cord, as its axonal structure is specific and different from the brain. Methods We run Monte Carlo simulations using a synthetic model of spinal cord white matter (WM) (large axons), and of brain WM (smaller axons). Furthermore, we study clinically feasible multi‐shell DW scans of the cervical spinal cord (b = 0; b = 711 s mm−2; b = 2855 s mm−2), obtained using three diffusion times (Δ of 29, 52 and 76 ms) from three volunteers. Results Both intra‐/extra‐axonal perpendicular diffusivities and kurtosis excess show time‐dependence in our synthetic spinal cord model. This time‐dependence is reflected mostly in the intra‐axonal perpendicular DW signal, which also exhibits strong decay, unlike our brain model. Time‐dependence of the total DW signal appears detectable in the presence of noise in our synthetic spinal cord model, but not in the brain. In WM in vivo, we observe time‐dependent macroscopic and microscopic diffusivities and diffusion kurtosis, NODDI and two‐compartment SMT metrics. Accounting for large axon calibers improves fitting of multi‐compartment models to a minor extent. Conclusions Time‐dependence of clinically viable DW MRI metrics can be detected in vivo in spinal cord WM, thus providing new opportunities for the non‐invasive estimation of microstructural properties. The time‐dependence of the perpendicular DW signal may feature strong intra‐axonal contributions due to large spinal axon caliber. Hence, a popular model known as “stick” (zero‐radius cylinder) may be sub‐optimal to describe signals from the largest spinal axons.