Signal-to-Noise Ratio Enhancement of Single-Voxel In Vivo 31P and 1H Magnetic Resonance Spectroscopy in Mice Brain Data Using Low-Rank Denoising

Yeong-Jae Jeon; Shin-Eui Park; Keun-A Chang; Hyeon-Man Baek

doi:10.3390/metabo12121191

Signal-to-Noise Ratio Enhancement of Single-Voxel In Vivo ³¹P and ¹H Magnetic Resonance Spectroscopy in Mice Brain Data Using Low-Rank Denoising

Metabolites. 2022 Nov 29;12(12):1191. doi: 10.3390/metabo12121191.

Authors

Yeong-Jae Jeon^{1

2}, Shin-Eui Park², Keun-A Chang^{1

3}, Hyeon-Man Baek^{1

4}

Affiliations

¹ Department of Health Sciences and Technology, Gachon Advanced Institute for Health Sciences and Technology, Gachon University, Incheon 21999, Republic of Korea.
² Department of Biomedical Science, Lee Gil Ya Cancer and Diabetes Institute, Gachon University, Incheon 21999, Republic of Korea.
³ Department of Basic Neuroscience, Neuroscience Research Institute, Gachon University, Incheon 21999, Republic of Korea.
⁴ Department of Molecular Medicine, Lee Gil Ya Cancer and Diabetes Institute, Gachon University, Incheon 21999, Republic of Korea.

Abstract

Magnetic resonance spectroscopy (MRS) is a noninvasive technique for measuring metabolite concentration. It can be used for preclinical small animal brain studies using rodents to provide information about neurodegenerative diseases and metabolic disorders. However, data acquisition from small volumes in a limited scan time is technically challenging due to its inherently low sensitivity. To mitigate this problem, this study investigated the feasibility of a low-rank denoising method in enhancing the quality of single voxel multinuclei (³¹P and ¹H) MRS data at 9.4 T. Performance was evaluated using in vivo MRS data from a normal mouse brain (³¹P and ¹H) and stroke mouse model (¹H) by comparison with signal-to-noise ratios (SNRs), Cramer-Rao lower bounds (CRLBs), and metabolite concentrations of a linear combination of model analysis results. In ³¹P MRS data, low-rank denoising resulted in improved SNRs and reduced metabolite quantification uncertainty compared with the original data. In ¹H MRS data, the method also improved the SNRs, CRLBs, but it performed better for ³¹P MRS data with relatively simpler patterns compared to the ¹H MRS data. Therefore, we suggest that the low-rank denoising method can improve spectra SNR and metabolite quantification uncertainty in single-voxel in vivo ³¹P and ¹H MRS data, and it might be more effective for ³¹P MRS data. The main contribution of this study is that we demonstrated the effectiveness of the low-rank denoising method on small-volume single-voxel MRS data. We anticipate that our results will be useful for the precise quantification of low-concentration metabolites, further reducing data acquisition voxel size, and scan time in preclinical MRS studies.

Keywords: 1H MRS; 31P MRS; denoising; mouse brain; single voxel; stroke.

Grants and funding

This study was supported by the Bio & Medical Technology Development Program of the National Research Foundation (NRF) & funded by the Republic of Korea government (MSIT) (grant No. 2020M3A9E4104384) and the Gachon University research fund of 2022 (GCU-202106270001) and Basic Science Research Capacity Enhancement Project through Republic of Korea Basic Science Institute (National research Facilities and Equipment Center), grant funded by the Ministry of Education. (grant No. 2021R1A6C101A432).