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• W3037847603 abstract "Abstract In sarcopenic obesity, the importance of evaluating muscle and fat mass is unquestionable. There exist diverse quantification methods for assessing muscle and fat mass by imaging techniques; thus these methods must be standardized for clinical practice. This study developed a quantification software for the body composition imaging using abdominal magnetic resonance (MR) images and compared the difference between sarcopenic obesity and healthy controls for clinical application. Thirty patients with sarcopenic obesity and 30 healthy controls participated. The quantification software was developed based on an ImageJ multiplatform and the processing steps are as follows: execution, setting, confirmation, and extraction. The variation in the muscle area (MA), subcutaneous fat area (SA), and visceral fat area (VA) was analyzed with an independent two sample T-test. There were significant differences in SA (p < 0.001) and VA (p = 0.011), whereas there was no difference in MA (p = 0.421). Regarding the ratios, there were significant differences in MA/SA (p < 0.001), MA/VA (p = 0.002), and MA/(SA + VA) (p < 0.001). Overall, intraclass correlation coefficients were higher than 0.9, indicating excellent reliability. This study developed customized sarcopenia-software for assessing body composition using abdominal MR images. The clinical findings demonstrate that the quantitative body composition areas and ratios can assist in the differential diagnosis of sarcopenic obesity or sarcopenia." @default.
• W3037847603 created "2020-07-02" @default.
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• W3037847603 date "2020-06-26" @default.
• W3037847603 modified "2023-09-26" @default.
• W3037847603 title "Development of quantification software for evaluating body composition contents and its clinical application in sarcopenic obesity" @default.
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• W3037847603 doi "https://doi.org/10.1038/s41598-020-67461-0" @default.
• W3037847603 hasPubMedCentralId "https://www.ncbi.nlm.nih.gov/pmc/articles/7320181" @default.
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