An analytical model for estimating water exchange rate in white matter using diffusion MRI.
Substantial effort is being expended on using micro-structural modeling of the white matter, with the goal of relating diffusion weighted magnetic resonance imaging (DWMRI) to the underlying structure of the tissue, such as axonal density. However, one of the important parameters affecting diffusion is the water exchange rate between the intra- and extra-axonal space, which has not been fully investigated and is a crucial marker of brain injury such as multiple sclerosis (MS), stroke, and traumatic brain injury (TBI). To our knowledge, there is no diffusion analytical model which includes the Water eXchange Rate (WXR) without the requirement of short gradient pulse (SGP) approximation. We therefore propose a new analytical model by deriving the diffusion signal for a permeable cylinder, assuming a clinically feasible pulse gradient spin echo (PGSE) sequence. Simulations based on Markov Random Walk confirm that the exchange parameter included in our model has a linear correlation (R2>0.88) with the actual WXR. Moreover, increasing WXR causes the estimated values of diameter and volume fraction of the cylinders to increase and decrease, respectively, which is consistent with our findings from histology measurements in tissues near TBI regions. This model was also applied to the diffusion signal acquired from ex vivo brains of 14 male (10 TBI and 4 normal) rats using hybrid diffusion imaging. The estimated values of axon diameter and axonal volume fraction are in agreement with their corresponding histological measurements in normal brains, with 0.96 intra-class correlation coefficient value resulting from consistency analysis. Moreover, a significant increase (p = 0.001) in WXR and diameter and decrease in axonal volume fraction in the TBI boundary were detected in the TBI rats compared with the normal rats.
School of Electrical and Computer Engineering, University of Tehran, Tehran, Iran; Department of Neurology, Henry Ford Health System, Detroit, Michigan, United States of America.
Esmaeil
E
Davoodi-Bojd
Department of Neurology, Henry Ford Health System, Detroit, Michigan, United States of America; Department of Physics, Oakland University, Rochester, Michigan, United States of America.
Michael
M
Chopp
School of Electrical and Computer Engineering, University of Tehran, Tehran, Iran; Image Analysis Laboratory, Department of Radiology, Henry Ford Hospital, Detroit, Michigan, United States of America.
Hamid
H
Soltanian-Zadeh
Department of Physics, Oakland University, Rochester, Michigan, United States of America.
Shiyang
S
Wang
Department of Neurology, Henry Ford Health System, Detroit, Michigan, United States of America.
Guangliang
G
Ding
Department of Neurology, Henry Ford Health System, Detroit, Michigan, United States of America; Department of Physics, Oakland University, Rochester, Michigan, United States of America.
Quan
Q
Jiang
D000818:Animals; D001369:Axons / Q000648:ultrastructure*; D038524:Diffusion Magnetic Resonance Imaging / Q000379:methods*; D008297:Male; D008390:Markov Chains; D008954:Models, Biological; D056004:Molecular Dynamics Simulation; D051381:Rats; D014867:Water / Q000032:analysis* / Q000378:metabolism; D066127:White Matter / Q000737:chemistry* / Q000378:metabolism
D014867:Water