A fractional motion diffusion model for a twice‐refocused spin‐echo pulse sequence

Abstract

The purpose of this study was to develop an analytical expression for a fractional motion (FM) diffusion model to characterize diffusion-induced signal attenuation in a twice-refocused spin-echo (TRSE) sequence that is resilient to eddy currents, and to demonstrate its applicability to human brain imaging in vivo. Based on the FM theory, which provides a unified statistical description for Langevin motions, the diffusion-weighted (DW) MR signal was measured with a TRSE sequence that balances the concomitant gradients. The analytical expression was fitted to a set of DW images acquired with 14 b-values (0-4000 s/mm ) from a total of 10 healthy human subjects at 3 T, yielding three FM parameter maps based on anomalous diffusion coefficient D , diffusion increment variance φ, and diffusion correlation ψ, respectively. These parameters were used to characterize different brain regions in gray matter (GM), white matter (WM), and cerebrospinal fluid. The analytical expression for the TRSE-based FM model accurately described diffusion signal attenuation in healthy brain tissues at high b-values. TRSE's robustness against eddy currents was illustrated by comparing results from an expression for a conventional Stejskal-Tanner sequence. The TRSE-based FM model also produced consistent GM-WM contrast (p < 0.01) across all brain regions studied, whereas the consistency was not observed with the Stejskal-Tanner-based FM model. This new analytical expression is expected to enable further investigations to probe tissue structures by exploiting anomalous diffusion properties without being hindered by eddy-current perturbations at high b-values.

Quartile histogram assessment of glioma malignancy using high b‐value diffusion MRI with a continuous‐time random‐walk model

“…In a homogeneous medium, α and β values approach 1, corresponding to Gaussian diffusion. As the degree of spatiotemporal diffusion heterogeneity increases, α and β values decrease accordingly 15,55 . The spatiotemporal diffusion heterogeneities can be a reflection of the underlying structural heterogeneity, which is related to glioma grade.…”

“…As the degree of spatiotemporal diffusion heterogeneity increases, α and β values decrease accordingly. 15,55 The spatiotemporal diffusion heterogeneities can be a reflection of the underlying structural heterogeneity, which is related to glioma grade. High-grade gliomas are known to be more heterogeneous than their low-grade counterparts because of the presence of necrosis, cyst and hemorrhage.…”

Diffusion in Sephadex Gel Structures: Time Dependency Revealed by Multi-Sequence Acquisition over a Broad Diffusion Time Range

“…E α is a single-parameter Mittag–Leffler function [ 8 ]. For other diffusion gradient waveforms, expressions analogous to Equation (7) can be derived in reference of the methods described in [ 24 , 25 ].…”

Diffusion MRI of cancer: From low to high b‐values

“…Pulse sequences resilient to eddy currents, such as twice-refocused spin echo, can be used for high b-value DWI to reduce image distortion. [114][115][116] Various commercial softwares are also available to reduce the distortion after image acquisition.…”

“…As the b-value increases, diffusion gradient becomes stronger and/or TE becomes longer, both of which exacerbate image distortion. Pulse sequences resilient to eddy currents, such as twice-refocused spin echo, can be used for high b-value DWI to reduce image distortion 114–116 . Various commercial software is also available to reduce the distortion after image acquisition.…”