GABA-edited MEGA-PRESS at 3T: Does a measured MM background improve linear combination modeling?
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10 2024
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Source: Magn Reson Med. 92(4):1348-1362
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Alternative Title:Magn Reson Med
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Description:Purpose
The J-difference edited GABA signal is contaminated by other co-edited signals—the largest of which originates from co-edited macromolecules (MMs)—and is consequently often reported as “GABA+”. MM signals are broader and less well-characterized than the metabolites, and so are commonly approximated using a Gaussian model parameterization. Experimentally measured MM signals are a consensus-recommended alternative to parameterized modeling; however, they are relatively under-studied in the context of edited MRS.
Methods
To address this limitation in the literature, we have acquired GABA-edited MEGA-PRESS data with pre-inversion to null metabolite signals in 13 healthy controls. An experimental MM basis function was derived from the mean across subjects. We further derived a new parameterization of the MM signals from the experimental data, using multiple Gaussians to accurately represent their observed asymmetry. The previous single-Gaussian parameterization, mean experimental MM spectrum and new multi-Gaussian parameterization were compared in a three-way analysis of a public MEGA-PRESS dataset of 61 healthy participants.
Results
Both the experimental MMs and the multi-Gaussian parameterization exhibited reduced fit residuals compared to the single-Gaussian approach (p = 0.034 & p = 0.031, respectively), suggesting they better represent the underlying data than the single-Gaussian parameterization. Furthermore, both experimentally derived models estimated larger MM fractional contribution to the GABA+ signal for the experimental MMs (58%) and multi-Gaussian parameterization (58%), compared to the single-Gaussian approach (50%).
Conclusions
Our results indicate that single-Gaussian parameterization of edited MM signals is insufficient and that both experimentally derived GABA+ spectra and their parameterized replicas improve the modeling of GABA+ spectra.
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Pubmed ID:38818623
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Pubmed Central ID:PMC11262975
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Volume:92
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Issue:4
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Supporting Files:No Additional Files