Influence of macromolecule baseline on 1 H MR spectroscopic imaging reproducibility

Purpose

Poorly characterized macromolecular (MM) and baseline artefacts are known to reduce metabolite quantitation accuracy in ¹H MR spectroscopic imaging (MRSI). Increasing echo time (TE) and improvements in MM analysis schemes have both been proposed as strategies to improve metabolite measurement reliability. In this study, the influence of TE and two MM analysis schemes on MRSI reproducibility are investigated.

Methods

An experimentally acquired baseline was collected using an inversion recovery sequence (TI = 750 ms) and incorporated into the analysis method. Intrasubject reproducibility of MRSI scans, acquired at 3 Tesla, was assessed using metabolite coefficients of variance (COVs) for both experimentally acquired and simulated MM analysis schemes. In addition, the reproducibility of TE = 35 ms, 80 ms, and 144 ms was evaluated.

Results

TE = 80 ms was the most reproducible for singlet metabolites with COVs < 6% for total N‐acetyl‐aspartate, total creatine, and total choline; however, moderate multiplet dephasing was observed. Analysis incorporating the experimental baseline achieved higher Glu and Glx reproducibility at TE = 35 ms, and showed improvements over the simulated baseline, with higher efficacy for poorer data.

Conclusion

Overall, TE = 80 ms yielded the most reproducible singlet metabolite estimates. However, combined use of a short TE sequence and the experimental baseline may be preferred as a compromise between accuracy, multiplet dephasing, and T2 bias on metabolite estimates. Magn Reson Med 77:34–43, 2017. © 2016 The Authors Magnetic Resonance in Medicine published by Wiley Periodicals, Inc. on behalf of International Society for Magnetic Resonance in Medicine.

Quantification method using the Morlet wavelet for magnetic resonance spectroscopic signals with macromolecular contamination

We study the Morlet wavelet transform on characterizing Magnetic Resonance Spectroscopic (MRS) signals acquired at short echo-time. These signals contain contributions from metabolites, water and a baseline which mainly originates from large molecules, known as macromolecules, and lipids. The baseline signal decays faster than the metabolite ones. Therefore, by making use of the time-scale representation of the wavelet, the two signals can be distinguished without any additional pre-processing. This is confirmed by the experimental results which show that the Morlet wavelet can correctly quantify the metabolite contributions even when a baseline is embedded in the MRS signals.

Influence of measured and simulated basis sets on metabolite concentration estimates

By quantification of brain metabolites, localized brain proton MRS can non-invasively provide biochemical information from distinct regions of the brain. Quantification of short-TE signals is usually based on a metabolite basis set. The basis set can be obtained by two approaches: (1) by measuring the signals of metabolites in aqueous solution; (2) by quantum-mechanically simulating the theoretical metabolite signals. The purpose of this study was to compare the effect of these two approaches on metabolite concentration estimates. Metabolite concentrations were quantified with the QUEST method, using both approaches. A comparison was performed with the aid of Monte Carlo studies, by using signals simulated from both basis sets. The best results were obtained when the basis set used for the fit was the same as that used to simulate the Monte Carlo signals. This comparison was also performed using in vivo short-TE signals acquired at 7 T from the central region of rat brains. The concentration estimates, with confidence intervals, obtained using both basis sets were in good agreement with values from the literature. The in vivo study showed that, in general, the differences between the estimates obtained with the two basis sets were not statistically significant or scientifically important. Consequently, a simulated basis set can be used in place of a measured basis set.