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Experimental demonstration of diffusion limitations on resolution and SNR in MR microscopy (2301.00727v2)

Published 2 Jan 2023 in physics.med-ph and physics.bio-ph

Abstract: Magnetic resonance microscopy images at cellular resolution (< 10 microns) are limited by diffusion. SNR and spatial resolution suffer from the dephasing of transverse magnetization caused by diffusion of spins in strong gradients. Such effects may be reduced by using phase encoding instead of frequency encoding readout gradients. Demonstration of the benefits of phase encoding are lacking, and the conditions in which it is preferred are not clearly established. We quantify when phase encoding outperforms a readout gradient with emphasis on the detrimental effects of diffusion on SNR and resolution. A 15.2T MRI scanner, with 1 T/m gradients, and micro solenoid RF coils < 1 mm in diameter, were used to quantify diffusion effects on resolution and SNR of frequency and phase encoded acquisitions. Frequency and phase encoding resolution and SNR per square root time were calculated and measured for images at the diffusion limited resolution. The point-spread-function was measured for phase and frequency encoding using additional constant time gradients with voxels 3-15 microns. The effect of diffusion during the readout gradient on SNR was experimentally demonstrated. The achieved resolutions of frequency and phase encoded acquisitions were measured via the point-spread-function. SNR per square root time and actual resolution were calculated for a wide range of gradient amplitudes, diffusion coefficients, and relaxation properties. The results provide a practical guide on how to choose between phase and frequency encoding. Images of excised rat spinal cord at 10 x 10 microns in-plane demonstrate benefits of phase encoding in the form of higher measured resolution and SNR vs the same image acquired with a conventional readout. We demonstrate the extent to which phase encoding outperforms readout gradients in SNR and resolution over a wide range of voxel sizes, sample, and hardware properties.

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