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Abstract #1838

Effect of FID-MRSI backward linear prediction with autoregressive algorithm on metabolite estimates for compensation of acquisition delay

Alessio Siviglia1,2, Brayan Alves1,2, Jessie Mosso1,2, Cristina Cudalbu1,2, and Bernard Lanz1,2
1CIBM Center for Biomedical Imaging, Lausanne, Switzerland, 2Animal Imaging and Technology, EPFL, Lausanne, Switzerland

Synopsis

Keywords: Spectroscopy, Spectroscopy, MRSI, Acquisition Delay, FID-MRSI, Ultra-high field, Preclinical, Rat

Motivation: 1H Free-Induction Decay (FID) MRSI is limited by the acquisition delay (AD) between the RF excitation pulse and the FID signal. N initial data points are thus lost.

Goal(s): Our goal was to evaluate the consistency of the Backward Linear Prediction (BLP) auto-regressive reconstruction method to recover the lost FID data points.

Approach: In-vivo rat data were used to investigate the impact of the BLP methodology in a cut-and-recover approach; further Monte-Carlo simulations were used to identify the method validity limit.

Results: In-vivo and Monte-Carlo results highlighted the consistency of the BLP methodology for realistic FID reconstruction ranges.

Impact: Focusing on metabolites of interest, no significant variations of brain map concentrations have been detected between original FID acquisitions and BLP reconstruction outcomes between AD=1.3ms and AD=0.708ms. Moreover, Monte Carlo simulations showed good quantification reliability until AD=2.7 ms.

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Keywords