Loading…

Morlet wavelet analysis of Magnetic Resonance Spectroscopic signals with macromolecular contamination

We apply theMorlet wavelet transform to characterizing Magnetic Resonance Spectroscopy (MRS) signals acquired at short echo-time. These signals usually contain contributions from metabolites, water and a baseline which mainly originates from large molecules, known as macromolecules, and lipids. The...

Full description

Saved in:
Bibliographic Details
Main Authors: Suvichakorn, A., Ratiney, H., Bucur, A., Cavassila, S., Antoine, J.-P.
Format: Conference Proceeding
Language:English
Subjects:
Online Access:Request full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:We apply theMorlet wavelet transform to characterizing Magnetic Resonance Spectroscopy (MRS) signals acquired at short echo-time. These signals usually contain contributions from metabolites, water and a baseline which mainly originates from large molecules, known as macromolecules, and lipids. The baseline accommodation is one of the major obstructions in in vivo short echo-time MRS quantification as its shape and intensity are not known a priori. In this paper, the simulated signal of the N-acetylaspartate (NAA) metabolite is used as a test signal to be recovered after adding the in vivo macromolecular signal. The in vivo macromolecule MRS signal was acquired on a horizontal 4.7T Biospec system. By optimizing the inversion time, which represents the delay between the inversion pulse and the first pulse of the PRESS sequence, the metabolites are nullified while the others are maintained. The metabolite-nullified signal from a volume-of-interest centralized in the hippocampus of a healthy mouse, which was a combination of residual water, baseline and noise, was added to the signal of NAA. The amplitude of the metabolite is also varied to visualize the sensitivity of the wavelet transform at different ratios between the intensity of the macromolecular and the metabolite signals. Compared to the simulated signal of NAA, the signal decays much faster. The time-scale representation of the wavelet can therefore distinguish the two signals without any additional pre-processing. The amplitude of the metabolite is also correctly derived although at earlier time it still has an effect of the baseline.
ISSN:1558-2809
2832-4242
DOI:10.1109/IST.2008.4659993