Effects of fat on MR-measured metabolite signal strengths: implications for in vivo MRS studies of the human brain

Abstract

Recent MRS studies have indicated that a higher body mass index (BMI) is associated with lower brain metabolite levels. Generally, individuals with higher BMIs have more body fat deposits than individuals with normal BMIs. This single-voxel spectroscopy (SVS) study investigated possible effects of fat on MR-measured metabolite signal areas, which may at least partly explain the observed associations of BMI with MR-measured brain metabolite levels in vivo. SVS data were acquired at 4 T from a phantom containing N-acetylaspartate, glutamate and creatine, as well as from three healthy male adults. Back fat obtained from pig was used to assess the effects of fat on metabolite signals. With the same voxel size and placement, the phantom was first scanned without fat (baseline), and then with 0.7-cm- and 1.4-cm-thick fat layers placed on it. Each participant was also scanned first without fat and then with two 0.7-cm fat layers, one placed beneath the occiput and the other on the forehead. Two spectra were acquired per participant from the anterior cingulate and the parieto-occipital cortices. The metabolite resonance and corresponding water peak areas were then fitted and metabolite to water signal ratios were used for analyses. In both phantom and in vivo experiments, the metabolite-to-water ratios decreased in the presence of fat relative to baseline metabolite-to-water ratios. The reduced metabolite signals in the presence of fat reported here are reminiscent of the negative correlations observed between BMI and MR-measured metabolite levels. These apparent physical effects of fat have potentially far-reaching consequences for the accuracy of MR measurements of brain metabolite levels and their interpretation, particularly when large fat stores exist around the skull, such as in individuals with higher BMI.

Keywords: MRS; body fat; body mass index; dielectric effects; metabolite concentration; radiofrequency absorption.

Figure 1

Sagittal T1-weighted (top) and axial T2-weighted (bottom) images showing the positions of the fat layers on the head and the VOIs in the brain from one in vivo experiment. Left panel: ACC (with and without fat layers), Right panel: POC (with and without fat layers).

Figure 2

In vivo spectra of human brain fitted with the SITOOLS software. Top spectrum illustrates a typical good baseline fit between 1.8 and 4.2 ppm. Any peak areas above the baseline are fit by the spectral model, including macromolecules. The bottom spectrum illustrates a typical good model fit. The black line represents the acquired data, the green line the sum of spectral and baseline model used.

Figure 3

NAA, Glu and Cr spectra of phantom (panel A: spectra are not on the same vertical scale) and plots of metabolite/H₂O ratios from acquired data against fat thickness. Panel B: NAA/H₂O and CR/H₂O ratios estimated using Gaussian formula; panel C: NAA/H₂O, Glu/ H₂O and CR/H₂O ratios obtained from software fitting. Notice the slight spectral line broadening of the middle and bottom spectra acquired in the presence of fat when compared with the top spectrum (baseline).

Figure 4

In vivo brain metabolite spectra for the POC voxel (panel A: spectra are not on the same vertical scale). Plots of NAA/H₂O, Glu/ H₂O, CR/H₂O and Cho/H₂O ratios against fat thickness for one participant in ACC (Panel B) and POC (Panel C). (Note: In Panel B, the values for ACC Glu/H₂O and Cr/H₂O were very similar in one of the participants (participant 2), but for the purpose of clarity, they are shown separated by decreasing the Glu/ H₂O values slightly.