3D‐multi‐echo radial imaging of 23Na (3D‐MERINA) for time‐efficient multi‐parameter tissue compartment mapping

12:53 pm 15 Dec 2017

First published: 28 July 2017


The work was supported by a research collaboration agreement with Siemens Healthcare. Grant sponsor: Jon Cleary is funded by a University of Melbourne McKenzie Fellowship. Bradford Moffat is supported by the Australian National Imaging Facility (NIF).

Yasmin Blunck,
Sonal Josan,
Syeda Warda Taqdees,
Bradford A. Moffat,
Roger J. Ordidge,
Jon O. Cleary,
Leigh A. Johnston


This work demonstrates a 3D radial multi-echo acquisition scheme for time-efficient sodium (23Na) MR-signal acquisition and analysis. Echo reconstructions were used to produce signal-to-noise ratio (SNR)-enhanced 23Na-images and parameter maps of the biexponential observed transverse relaxation time ( ) decay.

A custom-built sequence for radial multi-echo acquisition was proposed for acquisition of a series of 3D volumetric 23Na-images. Measurements acquired in a phantom and in vivo human brains were analyzed for SNR enhancement and multi-component estimation.

Rapid gradient refocused imaging acquired 38 echoes within a repetition time of 160 ms. Signal averaging of multi-echo time (TE) measurements showed an average brain tissue SNR enhancement of 34% compared to single-TE images across subjects. Phantom and in vivo measurements detected distinguishable signal decay characteristics for fluid and solid media. Mapping results were investigated in phantom and in vivo experiments for sequence timing optimization and signal decay analysis. The mapping results were consistent with previously reported values and facilitated fluid-signal discrimination.

The proposed method offers an efficient 23Na-imaging scheme that extends existing 23Na-MRI sequences by acquiring signal decay information with no increase in time or specific absorption rate. The resultant SNR-enhanced 23Na-images and estimated signal decay characteristics offer great potential for detailed investigation of tissue compartment characterization and clinical application. Magn Reson Med, 2017. © 2017 International Society for Magnetic Resonance in Medicine.

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