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1H-MRS technique and spectroscopic imaging LCModel based adolescent obese metabolic syndrome research

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Abstract

Hydrogen proton magnetic resonance spectroscopy (1H-MRS) was widely used in the auxiliary diagnosis of clinical diseases. However, in the previous study on hippocampal metabolites, the relative ratio of magnetic resonance spectroscopic data common area blow the crest or crest height was used for semi-quantitative or relative quantitative analysis. Although it was convenient to observe the change trend for this method, it could not accurately reflect the specific changes of various metabolites concentrations. So it had a certain limitation. Based on Linear Combination of Model Spectra (LCmodel) processing technology this paper introduced the spectroscopic imaging technology into the analysis procedures. The absolute concentration of brain metabolites was quantitatively detected in the hippocampus of adolescent obese metabolic syndrome. The results showed that the levels of NAA, Cho and MI in bilateral hippocampuses of adolescent metabolic syndrome were significantly decreased, especially in right hippocampus. The application of LCmodel software brought great convenience to realize the absolute quantification of metabolites in vivo.

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Acknowledgments

The research was founded within the project No.13YJC890032 entitled: “Psychological Evaluation of Cognitive Function and 1H-MRS Study of Frontal Lobe and Hippocampus Metabolism before and after the Aerobic Exercise Intervention among Obese Adolescents” being one of Youth Project supported by Humanities and Social Sciences Research Fund of Ministry of Education of the People’s Republic of China (MOE of PRC, 2013). Meanwhile, the research was founded by the General Project of Xinjiang Ethnic Sports Culture Research Center (No.XJEDU040613C03). Moreover, the research was founded by key discipline of Xinjiang Uighur Autonomous Region, Sports Humanistic Sociology.

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Sun, J., Chen, P. & Bi, C. 1H-MRS technique and spectroscopic imaging LCModel based adolescent obese metabolic syndrome research. Multimed Tools Appl 76, 19491–19505 (2017). https://doi.org/10.1007/s11042-015-3191-3

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  • DOI: https://doi.org/10.1007/s11042-015-3191-3

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