Relevance of time-dependence for clinically viable diffusion imaging of the spinal cord.
Relevance of time-dependence for clinically viable diffusion imaging of the spinal cord.
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DOI:
10.1002/mrm.27463
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发表时间:
2019-03
影响因子:
3.3
通讯作者:
Gandini Wheeler-Kingshott CAM
中科院分区:
文献类型:
--
作者:
Grussu F;Ianuş A;Tur C;Prados F;Schneider T;Kaden E;Ourselin S;Drobnjak I;Zhang H;Alexander DC;Gandini Wheeler-Kingshott CAM
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. 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. 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. 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.
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影响因子:
3.3
作者:
Clark, CA;Hedehus, M;Moseley, ME
通讯作者:
Moseley, ME
影响因子:
2.4
作者:
Einstein, A
通讯作者:
Einstein, A
影响因子:
3.3
作者:
Figley, C. R.;Stroman, P. W.
通讯作者:
Stroman, P. W.
影响因子:
10.6
作者:
Hall, Matt G.;Alexander, Daniel C.
通讯作者:
Alexander, Daniel C.
DOI:
10.1016/j.nicl.2017.05.010
发表时间:
2017
期刊:
NeuroImage. Clinical
影响因子:
--
作者:
By S;Xu J;Box BA;Bagnato FR;Smith SA
通讯作者:
Smith SA