- Main
Spectral fitting strategy to overcome the overlap between 2-hydroxyglutarate and lipid resonances at 2.25 ppm.
Published Web Location
https://doi.org/10.1002/mrm.28829Abstract
PURPOSE: 1 H MRS provides a noninvasive tool for identifying mutations in isocitrate dehydrogenase (IDH). Quantification of the prominent 2-hydroxyglutarate (2HG) resonance at 2.25 ppm is often confounded by the lipid resonance at the same frequency in tumors with elevated lipids. We propose a new spectral fitting approach to separate these overlapped signals, therefore, improving 2HG evaluation. METHODS: TE 97 ms PRESS was acquired at 3T from 42 glioma patients. New lipid basis sets were created, in which the small lipid 2.25-ppm signal strength was preset with reference to the lipid signal at 0.9 ppm, incorporating published fat relaxation data. LCModel fitting using the new lipid bases (Fitting method 2) was conducted along with fitting using the LCModel built-in lipid basis set (Fitting method 1), in which the lipid 2.25-ppm signal is assessed with reference to the lipid 1.3-ppm signal. In-house basis spectra of low-molecular-weight metabolites were used in both fitting methods. RESULTS: Fitting method 2 showed marked improvement in identifying IDH mutational status compared with Fitting method 1. 2HG estimates from Fitting method 2 were overall smaller than those from Fitting method 1, which was because of differential assignment of the signal at 2.25 ppm to lipids. In receiver operating characteristic analysis, Fitting method 2 provided a complete distinction between IDH mutation and wild-type whereas Fitting method 1 did not. CONCLUSION: The data suggest that 1 H MR spectral fitting using the new lipid basis set provides a robust fitting strategy that improves 2HG evaluation in brain tumors with elevated lipids.
Many UC-authored scholarly publications are freely available on this site because of the UC's open access policies. Let us know how this access is important for you.
Main Content
Enter the password to open this PDF file:
-
-
-
-
-
-
-
-
-
-
-
-
-
-