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. 2024 Jun 7:18:1389111.
doi: 10.3389/fnins.2024.1389111. eCollection 2024.

Mapping intracellular NAD content in entire human brain using phosphorus-31 MR spectroscopic imaging at 7 Tesla

Rong Guo  1   2 , Shaolin Yang  3   4 , Hannes M Wiesner  5 , Yudu Li  1 , Yibo Zhao  1   6 , Zhi-Pei Liang  1   6 , Wei Chen  5 , Xiao-Hong Zhu  5
Affiliations

Mapping intracellular NAD content in entire human brain using phosphorus-31 MR spectroscopic imaging at 7 Tesla

Rong Guo et al. Front Neurosci. .

Abstract

Introduction: Nicotinamide adenine dinucleotide (NAD) is a crucial molecule in cellular metabolism and signaling. Mapping intracellular NAD content of human brain has long been of interest. However, the sub-millimolar level of cerebral NAD concentration poses significant challenges for in vivo measurement and imaging.

Methods: In this study, we demonstrated the feasibility of non-invasively mapping NAD contents in entire human brain by employing a phosphorus-31 magnetic resonance spectroscopic imaging (31P-MRSI)-based NAD assay at ultrahigh field (7 Tesla), in combination with a probabilistic subspace-based processing method.

Results: The processing method achieved about a 10-fold reduction in noise over raw measurements, resulting in remarkably reduced estimation errors of NAD. Quantified NAD levels, observed at approximately 0.4 mM, exhibited good reproducibility within repeated scans on the same subject and good consistency across subjects in group data (2.3 cc nominal resolution). One set of higher-resolution data (1.0 cc nominal resolution) unveiled potential for assessing tissue metabolic heterogeneity, showing similar NAD distributions in white and gray matter. Preliminary analysis of age dependence suggested that the NAD level decreases with age.

Discussion: These results illustrate favorable outcomes of our first attempt to use ultrahigh field 31P-MRSI and advanced processing techniques to generate a whole-brain map of low-concentration intracellular NAD content in the human brain.

Keywords: brain metabolites; nicotinamide adenine dinucleotide; phosphorus-31 magnetic resonance spectroscopic imaging; subspace modeling; ultrahigh field.

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Conflict of interest statement

RG is currently an employee of Siemens Medical Solutions USA, Inc. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Figures

Figure 1
Figure 1
Representative spectra, SNR maps, and metabolite maps (signal intensities after spectral fitting, including PCr, αATP, GPC, and NAD) of results (from one 2.3 cc data) using different processing methods: (A) raw in vivo 31P-MRSI data without denoising; (B) 31P-MRSI data using basic low-rank denoising; (C) 31P-MRSI data using the probabilistic subspace-based denoising method. Spectra were displayed on the same horizontal scale. The displayed spectra were from the single voxel labeled on the SNR maps and they were displayed in absolute mode.
Figure 2
Figure 2
A representative set of human brain metabolite maps (signal intensities after spectral fitting) obtained using the proposed method, including PCr, αATP, γATP, βATP, Pi, GPE, GPC, PE, PC, and NAD. Nominal spatial resolution was 2.3 cc, acquisition time was 51 min.
Figure 3
Figure 3
Computational simulation of 31P-MRSI for comparison of different methods: (A) ground truth (generated by averaging eight 31P-MRSI data); (B) raw data without denoising; (C) basic low-rank denoising; (D) probabilistic subspace-based denoising method. NAD maps (signal intensities after spectral fitting) were displayed on the left and the localized spectra of selected point (as labeled on the NAD maps) were displayed on the right. The spectra were displayed in absolute mode.
Figure 4
Figure 4
(A) Quantified whole-brain NAD concentration maps (in mM, overlaid on anatomical MRI images) of seven subjects (the subject 7 was scanned twice, labeled as Sub. 7a and Sub. 7b). (B) Boxplots of the NAD concentrations of these seven subjects with the mean and standard deviations. Red lines indicate the median while blue boxes cover the 25%–75% percentiles. (C) Spectra of the same selected voxel (as labeled on the NAD maps) from Sub. 7a and Sub. 7b datasets. (D) R2-plot of the NAD concentrations from Sub. 7a and Sub. 7b datasets, with the Pearson’s correlation coefficient as 0.72 and the coefficient of variation as 6.1%. Red dot line is the identical line. For all these scans, nominal spatial resolution was 2.3 cc, acquisition time was 51 min. The spectra were displayed in absolute mode.
Figure 5
Figure 5
SNR analysis of one high-resolution “1.0-cc data” (age 22, male), including representative spectra, SNR maps, and SNR boxplots of results using different processing methods: (A) raw in vivo 31P-MRSI data without denoising; (B) 31P-MRSI data using basic low-rank denoising; (C) 31P-MRSI data using the probabilistic subspace-based denoising method. The displayed spectra were from the single voxel labeled on the SNR maps. The spectra were displayed in absolute mode.
Figure 6
Figure 6
Resulting metabolite maps (signal intensities after spectral fitting, including PCr, αATP, GPC, and NAD) of one high-resolution 31P-MRSI data (age 22, male). Nominal spatial resolution was 1.0 cc, acquisition time was 21 min.
Figure 7
Figure 7
Regression analysis of the metabolite signal intensities over the gray matter fraction (in percentage), including PCr, GPC, NAD, αATP, γATP, and βATP. Red lines are linear regression curves.
Figure 8
Figure 8
Correlation between the average brain NAD levels and age. The red line is the linear regression curve.
Figure 9
Figure 9
Representative spectrum (averaged from 9 adjacent voxels as indicated in the anatomical image, displayed in absolute mode) (A) with its spectral fitting (B) and residue (C). Zoom-in region shows the spectral range covering the NADH/NAD+ and UDPG signals.
Figure 10
Figure 10
Comparison of the spectra and NAD estimates from (A) large-voxel data by averaging 24 voxels from the raw 31P-MRSI data; (B) large-voxel data by averaging 24 voxels from the denoised 31P-MRSI data. The spectra were from six representative large voxels indicated by black box in the NAD maps, and they were displayed in absolute mode.
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Grants and funding

The author(s) declare that financial support was received for the research, authorship, and/or publication of this article. This work was supported, in part, by the National Institutes of Health grants (U01EB026978, R01CA240953, R01NS133006, and P41EB027061). The data collection at the University of Pittsburgh was also supported by the endowment of the Charles F. Reynolds III and Ellen G. Detlefsen Endowed Chair in Geriatric Psychiatry.

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