Test–retest reproducibility of human brain multi‐slice¹H FID‐MRSIdata at 9.4T after optimization of lipid regularization, macromolecular model, and spline baseline stiffness

Abstract

This study analyzes the effects of retrospective lipid suppression, a simulated macromolecular prior knowledge and different spline baseline stiffness values on 9.4T multi-slice proton FID-MRSI data spanning the whole cerebrum of human brain and the reproducibility of respective metabolite ratio to total creatine (/tCr) maps for 10 brain metabolites.Methods: Measurements were performed twice on 5 volunteers using a short TR and TE FID MRSI 2D sequence at 9.4T. The effects of retrospective lipid L2-regularization, macromolecular spectrum and different LCModel baseline flexibilities on SNR, FWHM, fitting residual, Cramér-Rao lower bound, and metabolite ratio maps were investigated. Intra-subject, inter-session coefficient of variation and the test-retest reproducibility of the mean metabolite ratios (/tCr) of each slice was calculated.Results: Transversal, sagittal, and coronal slices of many metabolite ratio maps correspond to the anatomically expected concentration relations in gray and white matter for the majority of the cerebrum when using a flexible baseline in LCModel fit. Results from the second measurements of the same subjects show that slice positioning and data quality correlate significantly to the first measurement.L2-regularization provided effective suppression of lipid-artifacts, but should be avoided if no artifacts are detected. Conclusion:Reproducible concentration ratio maps (/tCr) for 4 metabolites (total choline, N-acetylaspartate, glutamate, and myoinositol) spanning the majority of the cerebrum and 6 metabolites (N-acetylaspartylglutamate, γ-aminobutyric acid, glutathione, taurine, glutamine, and aspartate) covering 32 mm in the upper part of the brain were acquired at 9.4T using multi-slice FID MRSI with retrospective lipid suppression, a macromolecular spectrum and a flexible LCModel baseline.

Quantitative metabolic reference for healthy human cerebrum derived from group averaged 9.4T1H MRSI data

“…Metabolites with CRLBs that appear with a strong tissue contrast provide a hint that regions with an increase in CRLB are less likely to confidently fit a metabolite due to its lower regional concentration. For instance, NAAG is well documented to be almost exclusively located in the WM in MRSI studies (Bogner et al, 2012;Hangel et al, 2021;Henning et al, 2009;Nassirpour et al, 2016;Wright et al, 2022;Ziegs et al, 2023), and this is strongly supported in the present cohort by both the metabolite and CRLB maps.…”

“…without quantification: NAA, tCr, tCho, Glu, mI, and NAAG (Klauser et al, 2021). Compared to previous 9.4 T MRSI studies (Nassirpour, Chang, Avdievitch, et al, 2018;Nassirpour et al, 2016;Ziegs et al, 2023), this work shows a comparable quality across the cerebrum and maintained the standard of quantifying concentrations for 12 metabolites in vivo with voxel-specific T1-weighting corrections.…”

“…However, the quality of metabolite maps was not sufficient to derive quantitative metabolite maps in lower slices in the brain, which is also evidenced in a recent 9.4 T study (Ziegs et al, 2023) which assessed test-retest reproducibility and brain coverage of 1 H MRSI with an identical technical study design. This limitation has also been demonstrated in previous 7T whole-brain 1 H MRSI studies (Hangel et al, 2021;Klauser et al, 2021;Motyka et al, 2019).…”

“…The 1 H FID MRSI approach has been successfully translated to a 9.4 T human whole-body MRI scanner and enabled reliable data quality (Nassirpour et al, 2016). Furthermore, 9.4 T studies have investigated full brain reproducibility (Ziegs et al, 2023) and single slice quantitative analysis (Wright et al, 2022) of 1 H MRSI of the human brain at 9.4 T. This work melds previous 9.4 T 1 H FID MRSI efforts to provide group averaged metabolite distribution maps across the human cerebrum as metabolic reference. A respective dedicated data analysis pipeline has been developed and serves as a trail blazer toward the establishment of a metabolic atlas based on larger data sets in future.…”

“…Molecular imaging of the human brain using proton magnetic resonance spectroscopic imaging ( 1 H MRSI) offers a unique opportunity to explore metabolite distributions across the human brain as well as estimate concentrations of these metabolites in multiple brain regions. The development of 1 H MRSI capabilities is a continual process of technical development marked by reducing acquisition times(Bogner et al, 2020) while also improving image resolutions (Nassirpour et al, 2016), enhancing spectral resolutions, and providing reproducible and accurate results (Gasparovic et al, 2006; Hangel et al, 2021; Maudsley et al, 2009; Wright, Murali Manohar, et al, 2021; Ziegs et al, 2023). Improvements in 1 H MRSI have emphasized its value as a diagnostic tool for neurodegenerative diseases such as multiple sclerosis (Heckova et al, 2022), glioma (Gruber et al, 2017; Hangel et al, 2020; Laino et al, 2020), epilepsy (Pan et al, 2013), and more (Maudsley et al, 2020; Öz et al, 2014).…”