Diagnostic ultrasound estimates of muscle mass and muscle quality discriminate between women with and without sarcopenia

Introduction: Age-related changes in muscle mass and muscle tissue composition contribute to diminished strength in older adults. The objectives of this study are to examine if an assessment method using mobile diagnostic ultrasound augments well-known determinants of lean body mass (LBM) to aid sarcopenia staging, and if a sonographic measure of muscle quality is associated with muscle performance.Methods: Twenty community-dwelling female subjects participated in the study (age = 43.4 ±20.9 years; BMI: 23.8, interquartile range: 8.5). Dual energy X-ray absorptiometry (DXA) and diagnostic ultrasound morphometry were used to estimate LBM. Muscle tissue quality was estimated via the echogenicity using grayscale histogram analysis. Peak force was measured with grip dynamometry and scaled for body size. Bivariate and multiple regression analyses were used to determine the association of the predictor variables with appendicular lean mass (aLM/ht2), and examine the relationship between scaled peak force values and muscle echogenicity. The sarcopenia LBM cut point value of 6.75 kg/m2 determined participant assignment into the Normal LBM and Low LBM subgroups.Results: The selected LBM predictor variables were body mass index (BMI), ultrasound morphometry, and age. Although BMI exhibited a significant positive relationship with aLM/ht2 (adj. R2 = .61, p \u3c .001), the strength of association improved with the addition of ultrasound morphometry and age as predictor variables (adj. R2 = .85, p \u3c .001). Scaled peak force was associated with age and echogenicity (adj. R2 = .53, p \u3c .001), but not LBM. The Low LBM subgroup of women (n = 10) had higher scaled peak force, lower BMI, and lower echogenicity values in comparison to the Normal LBM subgroup (n = 10; p \u3c .05).Conclusions: Diagnostic ultrasound morphometry values are associated with LBM, and improve the BMI predictive model for aLM/ht2 in women. In addition, ultrasound proxy measures of muscle quality are more strongly associated with strength than muscle mass within the study sample

Diagnostic ultrasound estimates of muscle mass and muscle quality discriminate between women with and without sarcopenia

Introduction: Age-related changes in muscle mass and muscle tissue composition contribute to diminished strength in older adults. The objectives of this study are to examine if an assessment method using mobile diagnostic ultrasound augments well-known determinants of lean body mass (LBM) to aid sarcopenia staging, and if a sonographic measure of muscle quality is associated with muscle performance.Methods: Twenty community-dwelling female subjects participated in the study (age = 43.4 ±20.9 years; BMI: 23.8, interquartile range: 8.5). Dual energy X-ray absorptiometry (DXA) and diagnostic ultrasound morphometry were used to estimate LBM. Muscle tissue quality was estimated via the echogenicity using grayscale histogram analysis. Peak force was measured with grip dynamometry and scaled for body size. Bivariate and multiple regression analyses were used to determine the association of the predictor variables with appendicular lean mass (aLM/ht2), and examine the relationship between scaled peak force values and muscle echogenicity. The sarcopenia LBM cut point value of 6.75 kg/m2 determined participant assignment into the Normal LBM and Low LBM subgroups.Results: The selected LBM predictor variables were body mass index (BMI), ultrasound morphometry, and age. Although BMI exhibited a significant positive relationship with aLM/ht2 (adj. R2 = .61, p \u3c .001), the strength of association improved with the addition of ultrasound morphometry and age as predictor variables (adj. R2 = .85, p \u3c .001). Scaled peak force was associated with age and echogenicity (adj. R2 = .53, p \u3c .001), but not LBM. The Low LBM subgroup of women (n = 10) had higher scaled peak force, lower BMI, and lower echogenicity values in comparison to the Normal LBM subgroup (n = 10; p \u3c .05).Conclusions: Diagnostic ultrasound morphometry values are associated with LBM, and improve the BMI predictive model for aLM/ht2 in women. In addition, ultrasound proxy measures of muscle quality are more strongly associated with strength than muscle mass within the study sample

Interrater reliability of quantitative ultrasound using force feedback among examiners with varied levels of experience

Background. Quantitative ultrasound measures are influenced by multiple external factors including examiner scanning force. Force feedback may foster the acquisition of reliable morphometry measures under a variety of scanning conditions. The purpose of this study was to determine the reliability of force-feedback image acquisition and morphometry over a range of examiner-generated forces using a muscle tissuemimicking ultrasound phantom. Methods. Sixty material thickness measures were acquired from a muscle tissue mimicking phantom using B-mode ultrasound scanning by six examiners with varied experience levels (i.e., experienced, intermediate, and novice). Estimates of interrater reliability and measurement error with force feedback scanning were determined for the examiners. In addition, criterion-based reliability was determined using material deformation values across a range of examiner scanning forces (1–10 Newtons) via automated and manually acquired image capture methods using force feedback. Results. All examiners demonstrated acceptable interrater reliability (intraclass correlation coefficient, ICC = .98, p \u3c .001) for material thickness measures obtained using force feedback. Individual examiners exhibited acceptable reliability with the criterion-based reference measures (ICC \u3e .90, p \u3c .001), independent of their level of experience. The measurement error among all examiners was 1.5%–2.9% across all applied stress conditions. Conclusion. Manual image capture with force feedback may aid the reliability of morphometry measures across a range of examiner scanning forces, and allow for consistent performance among examiners with differing levels of experience

Statistical modeling of musculoskeletal ultrasound images reveals correlates of age-related muscle performance

Background: Musculoskeletal ultrasound (MUS) is an inexpensive method to assess age-related changes in muscle tissue composition. Statistical modeling of MUS image data is relatively unexplored and may reveal correlates of muscle function and quality. The primary objective of this study was to determine how well several statistical models fit MUS image data. The secondary objective was to assess the association between model parameters and muscle performance in young and older adults. Methods: Seventeen young (age = 24 yrs. ± 2) and seventeen older (age = 65 yrs. ± 7) adults enrolled in the study. Ultrasound scans of the rectus femoris muscle were obtained using B-mode MUS with a 13-6 MHz linear array transducer. For each scan, grayscale data were extracted from a region encompassing the muscle, and parameters for the normal, Poisson, and negative binomial distributions were estimated. Theoretical data were generated from parameter estimates, and R2 values were computed to assess agreement between grayscale and theoretical data. A one-way ANOVA was used to test for differences between each statistical model and F-tests were performed to compare goodness-of-fit. Muscle performance was measured with a hand dynamometer, and correlation analysis was conducted to determine the association between hand grip strength and parameter estimates. Results: Mean R2 values were similar between the negative binomial (R2 = 0.93 ± 0.06) and normal (R2 = 0.84 ± 0.10) distributions (p = 0.141) and both demonstrated good agreement with grayscale data. The Poisson distribution had poor agreement (R2 = -0.34 ± 0.60) was dissimilar to the other models (p \u3c 0.001), and was excluded from further analysis. Fit between grayscale and theoretical data was statistically better using the negative binomial distribution compared to the normal distribution for all ultrasound scans (mean F253,253: 2.70 ± 1.10, p: \u3c 0.0001). Hand grip strength was strongly associated with negative binomial dispersion parameter estimates in older (R2 = 0.80), but not young (R2 = 0.17), adults. Mean grayscale values were moderately associated with hand grip strength in both young (R2 = 0.39) and older (R2 = 0.39) adults. Conclusions: MUS data are best modeled by the negative binomial distribution, and dispersion parameter estimates could be used to assess loss of muscle quality with age. Future work is needed to determine whether dispersion parameter estimates are associated with measures of muscle quality attained using other imaging modalities and to explore if our findings generalize to other muscle groups

Interrater reliability of quantitative ultrasound using force feedback among examiners with varied levels of experience

Background. Quantitative ultrasound measures are influenced by multiple external factors including examiner scanning force. Force feedback may foster the acquisition of reliable morphometry measures under a variety of scanning conditions. The purpose of this study was to determine the reliability of force-feedback image acquisition and morphometry over a range of examiner-generated forces using a muscle tissue-mimicking ultrasound phantom. Methods. Sixty material thickness measures were acquired from a muscle tissue mimicking phantom using B-mode ultrasound scanning by six examiners with varied experience levels (i.e., experienced, intermediate, and novice). Estimates of interrater reliability and measurement error with force feedback scanning were determined for the examiners. In addition, criterion-based reliability was determined using material deformation values across a range of examiner scanning forces (1–10 Newtons) via automated and manually acquired image capture methods using force feedback. Results. All examiners demonstrated acceptable interrater reliability (intraclass correlation coefficient, ICC = .98, p < .001) for material thickness measures obtained using force feedback. Individual examiners exhibited acceptable reliability with the criterion-based reference measures (ICC > .90, p < .001), independent of their level of experience. The measurement error among all examiners was 1.5%–2.9% across all applied stress conditions. Conclusion. Manual image capture with force feedback may aid the reliability of morphometry measures across a range of examiner scanning forces, and allow for consistent performance among examiners with differing levels of experience