Multiple‐echo diffusion tensor acquisition technique (MEDITATE) on a 3T clinical scanner

Abstract

This paper describes the concepts and implementation of an MRI method, Multiple Echo Diffusion Tensor Acquisition Technique (MEDITATE), which is capable of acquiring apparent diffusion tensor maps in two scans on a 3T clinical scanner. In each MEDITATE scan, a set of RF-pulses generates multiple echoes whose amplitudes are diffusion-weighted in both magnitude and direction by a pattern of diffusion gradients. As a result, two scans acquired with different diffusion weighting strengths suffice for accurate estimation of diffusion tensor imaging (DTI)-parameters. The MEDITATE variation presented here expands previous MEDITATE approaches to adapt to the clinical scanner platform, such as exploiting longitudinal magnetization storage to reduce T2-weighting. Fully segmented multi-shot Cartesian encoding is used for image encoding. MEDITATE was tested on isotropic (agar gel), anisotropic diffusion phantoms (asparagus), and in vivo skeletal muscle in healthy volunteers with cardiac-gating. Comparisons of accuracy were performed with standard twice-refocused spin echo (TRSE) DTI in each case and good quantitative agreement was found between diffusion eigenvalues, mean diffusivity, and fractional anisotropy derived from TRSE-DTI and from the MEDITATE sequence. Orientation patterns were correctly reproduced in both isotropic and anisotropic phantoms, and approximately so for in vivo imaging. This illustrates that the MEDITATE method of compressed diffusion encoding is feasible on the clinical scanner platform. With future development and employment of appropriate view-sharing image encoding this technique may be used in clinical applications requiring time-sensitive acquisition of DTI parameters such as dynamical DTI in muscle.

Spatially resolved kinetics of skeletal muscle exercise response and recovery with multiple echo diffusion tensor imaging (MEDITI): a feasibility study

“…Prior work has explored the diffusion-weighting pattern’s capturing of dynamic diffusion tensor behavior [24,27]; the current study focused upon spatially-resolved dynamic imaging. In this implementation, each of the 11 echoes in each MEDITI echo train was measured with a 5-petal Single TrAjectory radial (STAR) k-space acquisition [30].…”

“…Recently, a new approach for compressing the required directional encodings has been demonstrated [24], titled “multiple echo diffusion tensor acquisition technique (MEDITATE)” and based on prior work in preclinical scanners [25,26], A single-voxel variant (SV-MEDITATE) has been applied to measure dynamic anisotropic diffusion exercise response in normal calf muscle [27] and thigh muscles in controls and dermatomyositis patients [28]. However, to produce a spatially-resolved variant of MEDITATE, k-space acquisition and reconstruction must be chosen to (a) include self-navigation of phase errors and (b) achieve sufficient temporal resolution to capture post-exercise recovery.…”

Dynamic diffusion-tensor measurements in muscle tissue using the single-line multiple-echo diffusion-tensor acquisition technique at 3T

“…As a result, two scans acquired with different diffusion‐weighting strengths suffice to isolate the diffusion weighting from T 1 , T 2 and proton‐density effects and to estimate DTI parameters accurately. As described in previous work , the full b matrix is calculated from the difference of b matrices in the two scans, including both the diffusion gradients and the imaging gradients used for spatial localization. The diffusion gradients were optimized to minimize the condition number , a scalar metric quantifying the diffusion sampling quality; an optimal condition number of 4.42 was found.…”

“…Input diffusion parameters D ( t ) were calculated according to a short‐time expansion using male human calf‐muscle parameters (fiber size 61 μ m, membrane permeability 20 μ m/s, D 0 1.52 μ m 2 /ms; these parameter choices induce an FA of 0.4 at the diffusion time of t = 1 s) ). For the simulation, echo amplitudes were generated and fitted for each time point using the sequence parameters and signal equations . These simulations were repeated for different SNR levels with Rician noise added to the echo amplitudes, using 400 samples for each time point at each SNR level.…”

“…In this work, we demonstrate the feasibility of in vivo dynamic diffusion‐tensor measurements in human skeletal muscle. To this end, we first extend the previous MEDITATE method to a single line volume acquisition (Fig. ) and verify the volume selection.…”