期刊
NMR IN BIOMEDICINE
卷 34, 期 5, 页码 -出版社
WILEY
DOI: 10.1002/nbm.4393
关键词
brain macromolecules; fitting; metabolite quantification; mobile lipids; parameterization; proton magnetic resonance spectroscopy; quantification; spectral analysis
资金
- Swiss National Science Foundation [320030-175,984, 310030_173222/1]
- Horizon 2020/CDS-QUAMRI Grant [634541]
- Horizon 2020/SYNAPLAST Grant [679927]
- US National Institutes of Health [P41-P41EB015909, R01 MH109159, P41-EB027061, P30-NS076408]
- Austrian Science Fund (FWF) [P 30701-B27]
- Ministry of Education, Youth and Sports of the Czech Republic [CZ.02.1.01/0.0/0.0/16_013/0001775]
- Swiss National Science Foundation (SNF) [310030_173222] Funding Source: Swiss National Science Foundation (SNF)
This paper provides an overview and recommendations on handling mobile macromolecule (MM) signals in proton MR spectra of the brain, as well as a list of open issues in the field. It highlights the importance of separating MM signals from metabolites for accurate determination of metabolite concentrations and their potential as biomarkers in specific diseases.
Proton MR spectra of the brain, especially those measured at short and intermediate echo times, contain signals from mobile macromolecules (MM). A description of the main MM is provided in this consensus paper. These broad peaks of MM underlie the narrower peaks of metabolites and often complicate their quantification but they also may have potential importance as biomarkers in specific diseases. Thus, separation of broad MM signals from low molecular weight metabolites enables accurate determination of metabolite concentrations and is of primary interest in many studies. Other studies attempt to understand the origin of the MM spectrum, to decompose it into individual spectral regions or peaks and to use the components of the MM spectrum as markers of various physiological or pathological conditions in biomedical research or clinical practice. The aim of this consensus paper is to provide an overview and some recommendations on how to handle the MM signals in different types of studies together with a list of open issues in the field, which are all summarized at the end of the paper.
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