MR diffusion kurtosis imaging for neural tissue characterization

Abstract

In conventional diffusion tensor imaging (DTI), water diffusion distribution is described as a 2nd-order three-dimensional (3D) diffusivity tensor. It assumes that diffusion occurs in a free and unrestricted environment with a Gaussian distribution of diffusion displacement, and consequently that diffusion weighted (DW) signal decays with diffusion factor (b-value) monoexponentially. In biological tissue, complex cellular microstructures make water diffusion a highly hindered or restricted process. Non-monoexponential decays are experimentally observed in both white matter and gray matter. As a result, DTI quantitation is b-value dependent and DTI fails to fully utilize the diffusion measurements that are inherent to tissue microstructure. Diffusion kurtosis imaging (DKI) characterizes restricted diffusion and can be readily implemented on most clinical scanners. It provides a higher-order description of water diffusion process by a 2nd-order 3D diffusivity tensor as in conventional DTI together with a 4th-order 3D kurtosis tensor. Because kurtosis is a measure of the deviation of the diffusion displacement profile from a Gaussian distribution, DKI analyses quantify the degree of diffusion restriction or tissue complexity without any biophysical assumption. In this work, the theory of diffusion kurtosis and DKI including the directional kurtosis analysis is revisited. Several recent rodent DKI studies from our group are summarized, and DKI and DTI compared for their efficacy in detecting neural tissue alterations. They demonstrate that DKI offers a more comprehensive approach than DTI in describing the complex water diffusion process in vivo. By estimating both diffusivity and kurtosis, it may provide improved sensitivity and specificity in MR diffusion characterization of neural tissues.

Diffusion Kurtosis Imaging Detects Acute Microstructural Changes in White and Gray Matter after Alcohol Intoxication in Rat

“…This may be largely due to two reasons which have already interpretation in previous studies. On the one hand, a decrease in MK may associated with degenerative processes leading to neuronal shrinkage [9,10,24,25]. On the other hand, it may induced by changes in axonal and myelin density [26].…”

Microstructures of Learning: Novel methods and approaches for assessing structural and functional changes underlying knowledge acquisition in the brain

“…Diffusion tensor MRI, diffusional kurtosis imaging (DKI) (Jensen and Helpern, 2010;Wu and Cheung, 2010), and q-space diffusion MRI (King et al, 1994;Assaf et al, 2002;Cohen and Assaf, 2002) are techniques that use statistical tools to model and extract features of the molecular displacement probability distribution, or diffusion propagator. DT-MRI yields the average diffusion tensor, while DKI and related methods yield the intra-voxel variance of diffusion coefficients or tensors, in addition to the average.…”

Interimager Variability in ADC Measurement of the Human Brain

“…In addition to the instruments themselves, coil systems, 12 scanning parameters, 15,22 and age of subjects 18,19 elicit variations in ADC values. An animal study demonstrated that the diffusion time for the b-value affects the values of diffusion parameters, including the ADC.…”

“…An animal study demonstrated that the diffusion time for the b-value affects the values of diffusion parameters, including the ADC. 22 Although we fixed the b-value at 1,000 s/mm 2 , diffusion times were dependent on tuning by the vendors. Because our study focused on the role of ADC values in the clinical setting, we used identical coil systems and parameters, except FOV, to those used in routine clinical studies performed with the 12 MR imagers.…”