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Abstract #4191

High SNR Efficiency Diffusion-Prepared Imaging with Amplitude Navigation

Philip Kenneth Lee1, Xuetong Zhou1,2, and Brian Andrew Hargreaves1,2,3
1Radiology, Stanford University, Stanford, CA, United States, 2Bioengineering, Stanford University, Stanford, CA, United States, 3Electrical Engineering, Stanford University, Stanford, CA, United States

Synopsis

Keywords: Diffusion Reconstruction, Image Reconstruction

Motivation: To improve the SNR efficiency of diffusion-prepared imaging by avoiding the use of a stabilizer gradient and its 2× signal penalty.

Goal(s): Demonstrate that shot-to-shot motion-induced phases can be modelled as image-based amplitude variations in reconstruction.

Approach: Monte Carlo simulations showed that eliminating the stabilizer gradient increases the number of excitations required to obtain accurate ADC estimates. Diffusion-prepared acquisitions with and without stabilizer gradients were performed in the brain and reconstructed with different retrospective NEX.

Results: Eliminating the stabilizer gradient improved SNR at the cost of an increased minimum scan time, and diffusion contrast sensitivity to B1 inhomogeneity.

Impact: Replacing the stabilizer gradient with use of a signal amplitude correction in diffusion-prepared imaging can reliably improve the SNR efficiency in cases where motion-induced and eddy-current-induced phase is controlled.

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