Feasibility and implications of using subject‐specific macromolecular spectra to model short echo time magnetic resonance spectroscopy data

Abstract

Expert consensus recommends linear-combination modeling (LCM) of 1 H MR spectra with sequence-specific simulated metabolite basis function and experimentally derived macromolecular (MM) basis functions. Measured MM basis functions are usually derived from metabolite-nulled spectra averaged across a small cohort. The use of subject-specific instead of cohort-averaged measured MM basis functions has not been studied widely. Furthermore, measured MM basis functions are not widely available to non-expert users, who commonly rely on parameterized MM signals internally simulated by LCM software. To investigate the impact of the choice of MM modeling, this study, therefore, compares metabolite level estimates between different MM modeling strategies (cohort-mean measured; subject-specific measured; parameterized) in a lifespan cohort and characterizes its impact on metabolite-age associations. 100 conventional (TE = 30 ms) and metabolite-nulled (TI = 650 ms) PRESS datasets, acquired from the medial parietal lobe in a lifespan cohort (20-70 years of age), were analyzed in Osprey. Short-TE spectra were modeled in Osprey using six different strategies to consider the MM baseline. Fully tissue-and relaxation-corrected metabolite levels were compared between MM strategies.Model performance was evaluated by model residuals, the Akaike information criterion (AIC), and the impact on metabolite-age associations. The choice of MM strategy had a significant impact on the mean metabolite level estimates and no major impact on variance. Correlation analysis revealed moderate-to-strong agreement between different MM strategies (r > 0.6). The lowest relative model residuals and AIC values

Metabolite T1relaxation times differ across the adult lifespan

“…We present a novel analysis of a large publicly available cross-sectional dataset (data available on https://www.nitrc.org/projects/mm_mrs/) that was acquired previously [16][17][18] from 102 healthy volunteers to characterize the MM and metabolite spectra in aging. Metabolite residual subtraction for MM spectra is implemented in the open-source MRS processing toolbox Osprey according to consensus-recommended 28 methods.…”

“…The data analyzed in this study are publicly available on www.nitrc.org and were previously published [16][17][18] . All acquisitions were performed on a 3T MRI scanner (Ingenia CX, Philips Healthcare, The Netherlands) on 102 healthy volunteers after approval from the local institutional review board (Shandong University School of Medicine).…”

“…Metabolite spectra were also acquired (TR/TE: 2000/30 ms) using PRESS localization and VAPOR 21 water suppression. Further acquisition details are reported in references [16][17][18] .…”

sLASER and PRESS Perform Similarly at Revealing Metabolite-Age Correlations

“…Water reference spectra were acquired without water suppression. The PRESS data in this manuscript have been previously analyzed in two studies (32,33). Quantification Spectra were processed and modeled using the Osprey software v2.4 (34), following consensus recommendation for linear combination model fitting (35).…”

“…Metabolites included in the (32). Briefly, individualsubject 'clean' MM spectra were modeled with a flexible spline of 0.1 ppm knot spacing and the overall mean 'clean' MM spectra were generated and employed as the MM basis functions (33).…”