Michael O Harris-Love1,2,3,4, Tomas I Gonzales1, Qi Wei5, Catheeja Ismail1,6, Johannah Zabal4, Paula Woletz1, Loretta DiPietro4, Marc R Blackman2,6,7,8. 1. Muscle Morphology, Mechanics, and Performance Laboratory, Human Performance Research Unit, Clinical Research Center, Washington, DC, USA. 2. Research Service, Washington, DC, USA. 3. Geriatrics Service, Veterans Affairs Medical Center, Washington, DC, USA. 4. Department of Exercise and Nutritional Sciences, Milken Institute School of Public Health. 5. Department of Bioengineering, Volgenau School of Engineering, George Mason University, Fairfax, Virginia, USA. 6. Departments of Medicine, Washington, DC, USA. 7. Biochemistry and Molecular Medicine, School of Medicine and Health Sciences, George Washington University, Washington, DC, USA. 8. Departments of Medicine and Rehabilitation Medicine, Georgetown University School of Medicine, Washington, DC, USA.
Abstract
OBJECTIVES: Assessing aging muscle through estimates of muscle heterogeneity may overcome some of the limitations of grayscale analyses. The objectives of this study included determining statistical model parameters that characterize muscle echogenicity and are associated with strength in younger and older participants. METHODS: Thirty-three community-dwelling participants were assigned to younger and older groups. Quantitative B-mode ultrasound scanning of the rectus femoris and isometric grip strength testing were completed. Shape or dispersion parameters from negative binomial distribution, Nakagami, gamma, and gamma mixture models were fitted to the grayscale histograms. RESULTS: The mean ages ± SDs of the younger and older groups were 24.0 ± 2.3 and 65.1 ± 6.5 years, respectively. Statistical model shape and dispersion parameters for the grayscale histograms significantly differed between the younger and older participants (P = .002-.006). Among all of the statistical models considered, the gamma mixture model showed the best fit with the grayscale histograms (χ2 goodness of fit = 62), whereas the Nakagami distribution displayed the poorest fit (χ2 goodness of fit = 2595). Grayscale values were significantly associated with peak grip strength force in younger adult participants (R2 = 0.36; P < .008). However, the negative binomial dispersion parameter k (adjusted R2 = 0.70; P < .001) and gamma shape parameter α (adjusted R2 = 0.68; P < .01) showed the highest associations with peak grip strength force in older adult participants. CONCLUSIONS: The negative binomial dispersion parameter k and the gamma shape parameter α have clinical relevance for the assessment of age-related muscle changes. Statistical models of muscle heterogeneity may characterize the association between muscle tissue composition estimates and strength better than grayscale measures in samples of community-dwelling older adults. Published 2018. This article is a U.S. Government work and is in the public domain in the USA.
OBJECTIVES: Assessing aging muscle through estimates of muscle heterogeneity may overcome some of the limitations of grayscale analyses. The objectives of this study included determining statistical model parameters that characterize muscle echogenicity and are associated with strength in younger and older participants. METHODS: Thirty-three community-dwelling participants were assigned to younger and older groups. Quantitative B-mode ultrasound scanning of the rectus femoris and isometric grip strength testing were completed. Shape or dispersion parameters from negative binomial distribution, Nakagami, gamma, and gamma mixture models were fitted to the grayscale histograms. RESULTS: The mean ages ± SDs of the younger and older groups were 24.0 ± 2.3 and 65.1 ± 6.5 years, respectively. Statistical model shape and dispersion parameters for the grayscale histograms significantly differed between the younger and older participants (P = .002-.006). Among all of the statistical models considered, the gamma mixture model showed the best fit with the grayscale histograms (χ2 goodness of fit = 62), whereas the Nakagami distribution displayed the poorest fit (χ2 goodness of fit = 2595). Grayscale values were significantly associated with peak grip strength force in younger adult participants (R2 = 0.36; P < .008). However, the negative binomial dispersion parameter k (adjusted R2 = 0.70; P < .001) and gamma shape parameter α (adjusted R2 = 0.68; P < .01) showed the highest associations with peak grip strength force in older adult participants. CONCLUSIONS: The negative binomial dispersion parameter k and the gamma shape parameter α have clinical relevance for the assessment of age-related muscle changes. Statistical models of muscle heterogeneity may characterize the association between muscle tissue composition estimates and strength better than grayscale measures in samples of community-dwelling older adults. Published 2018. This article is a U.S. Government work and is in the public domain in the USA.
Authors: B H Goodpaster; C L Carlson; M Visser; D E Kelley; A Scherzinger; T B Harris; E Stamm; A B Newman Journal: J Appl Physiol (1985) Date: 2001-06
Authors: Rosaly Correa-de-Araujo; Michael O Harris-Love; Iva Miljkovic; Maren S Fragala; Brian W Anthony; Todd M Manini Journal: Front Physiol Date: 2017-02-15 Impact factor: 4.566