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PLOS One logoLink to PLOS One
. 2023 Jan 17;18(1):e0280202. doi: 10.1371/journal.pone.0280202

Usefulness of muscle ultrasound in appendicular skeletal muscle mass estimation for sarcopenia assessment

Seol-Hee Baek 1, Joo Hye Sung 1, Jin-Woo Park 1, Myeong Hun Son 1, Jung Hun Lee 1, Byung-Jo Kim 1,2,*
Editor: Emiliano Cè3
PMCID: PMC9844922  PMID: 36649288

Abstract

The measurement of skeletal muscle mass is essential for the diagnosis of sarcopenia. Muscle ultrasonography has emerged as a useful tool for evaluating sarcopenia because it can be used to assess muscle quality and quantity. This study investigated whether muscle ultrasonography is effective for estimating appendicular skeletal muscle mass (ASM) and screening for sarcopenia. This study prospectively enrolled 212 healthy volunteers aged 40–80 years. ASM was measured using the bioelectrical impedance analysis. Muscle thickness (MT) and echo-intensity (EI) were measured in four muscles (biceps brachii, BB; triceps brachii, TB; rectus femoris, RF; biceps femoris, BF) on the dominant hand. A hold-out cross-validation method was used to develop and validate the ASM prediction equation. In the model development group, the ASM prediction equations were deduced as follows: estimated ASM for men (kg) = 0.167 × weight (kg) + 0.228 × height (cm) + 0.143 × MT of BF (mm)– 0.822 × EI to MT ratio of BB– 28.187 (R2 = 0.830) and estimated ASM for women (kg) = 0.115 × weight + 0.215 × height (cm) + 0.139 × MT of RF–0.638 × EI to MT ratio of BB– 23.502 (R2 = 0.859). In the cross-validation group, the estimated ASM did not significantly differ from the measured ASM in both men (p = 0.775; intraclass correlation coefficient [ICC] = 0.948) and women (p = 0.516; ICC = 0.973). In addition, multiple logistic regression analysis revealed that the ratios of EI to MT in the BF and RF muscles in men and MT in the BB muscle in women could be valuable parameters for sarcopenia screening. Therefore, our study suggests that muscle ultrasound could be an effective tool for estimating ASM and screening sarcopenia.

Introduction

Sarcopenia is a skeletal muscle disorder characterized by progressive and generalized loss of muscle mass and strength and reduced functional physical performance [1]. This could be related to the increased risk of falls, frailty, and mortality. Recently, sarcopenia has been recognized as an independent disease condition with a dedicated International Classification of Disease-10 code and not just an age-related decline in muscle mass [2]. The European Working Group on Sarcopenia in Older People (EWGSOP) and the Asian Working Group for Sarcopenia (AWGS) recommended that the diagnosis of sarcopenia should be based on the combination of muscle mass, muscle strength, and physical performance [3, 4]. Therefore, measurement of muscle mass is an important part of sarcopenia diagnosis. The EWGSOP and AWGS suggested sarcopenia cut-off points for low muscle mass using appendicular skeletal muscle mass (ASM), which is a sum of the muscle mass in the limbs, or height-adjusted ASM (ASM/height2) [3, 4]. Muscle mass has been measured by several techniques, including dual-energy X-ray absorptiometry (DEXA), bioelectrical impedance analysis (BIA), computer tomography (CT), and magnetic resonance imaging (MRI). MRI and CT are considered the gold standards for the assessment of muscle mass because of their high accuracy. However, these techniques are not commonly used in clinical practice because of their high cost. In contrast, the DEXA and BIA techniques are widely used for the assessment of muscle mass because they are relatively inexpensive and easy to use.

Recently, ultrasound has been widely used as an effective neuroimaging tool for assessing the peripheral nerves and muscles. Muscle ultrasound can evaluate muscle thickness, cross-sectional area, muscle architecture, and muscle echo-intensity (EI). Therefore, muscle ultrasound may have the potential to evaluate both muscle quantity and quality. Although several studies have reported the possibility of muscle mass measurement using muscle ultrasound [5–9], it is still not approved as a neuroimaging tool for assessing muscle mass according to the EWGOP and AWGS recommendations [3, 4]. In addition, whether muscle EI is valuable for assessing muscle mass and further investigating sarcopenia is rarely reported.

This study aimed to investigate whether muscle ultrasound can be used as an effective tool for estimating ASM in terms of muscle quantity and quality. Since muscle mass begins to decline in middle-aged, and decreases gradually with age [10], we explored whether muscle ultrasonography could be used as a screening tool for sarcopenia in middle-aged and older individuals.

Materials and methods

Study population

Healthy volunteers aged 41–80 years were prospectively recruited between October 2020 and December 2021. We excluded participants with any objectively detected muscle weakness at the time of the study, any neurological disorder or musculoskeletal disease that could have caused muscle weakness within recent 3 months, or gait disturbance or muscle weakness as a sequela of a previous neurological disorder or musculoskeletal disease. A hold-out cross-validation method was used to develop and validate the ASM prediction equation. Thus, the entire dataset of our study was randomly divided into a model development group (training set) and a validation group (testing set). The ASM prediction equation using ultrasound parameters was then deduced from the model development group, and the accuracy of deducing the ASM equation was verified in the cross-validation group. The enrolled participants were randomly divided into a model development group (70%) and a cross-validation group (30%) using SPSS 25.0 (IBM Corp., Armonk, NY, USA). Written informed consent was obtained from all participants prior to inclusion. This study was approved by the Institutional Review Board of Korea at the University Anam Hospital (No. 2020AN0361) and performed in accordance with the Declaration of Helsinki.

Clinical assessment

We collected demographic and clinical information on the participants, including their age, sex, height, weight, and body mass index (BMI). To evaluate muscle strength, the handgrip strength of the dominant hand was measured using hand-held dynamometry (Jamar hand dynamometry, TEC Inc., Clifton, NJ, USA). To evaluate physical performance, gait speed was measured using gait analysis equipment (GAITRite®, CIR Systems Inc., NJ, USA). To measure muscle mass, body composition analysis was performed via BIA methods using InBody770 (InBody Co. LTD, Seoul, Korea). The InBody 770 machine had a total of 30 impedance measurements at six different frequencies (1 kHz, 5 kHz, 50 kHz, 250 kHz, 500 kHz, and 1000 kHz) for five body segments (right and left arms, right and left legs, and trunk). Body composition was estimated according to the developed prediction equations using tissue conductivity variables in combination with other covariates such as sex, weight, and height. In addition, the participants were instructed not to eat or exercise for at least three hours before the test and to maintain normal fluid intake the day before the test. Body composition data, including ASM data, were collected. Since muscle mass correlates with body size, muscle mass-adjusted body size is required to identify the optimal cut-off point for sarcopenia. The EWGSOP and AWGS 2019 consensus have proposed the cutoff point of sarcopenia using ASM normalized with the squared height [3, 4]. Thus, ASM index was calculated using the following equation: ASM index (kg/m2) = ASM (kg)/ height (m)2.

Muscle ultrasound

Muscle ultrasound was performed using a diagnostic ultrasound device (Aplio i700, Canon Medical Systems, Tochigi, Japan) with an 18-MHz linear probe and B-mode scanning, which was set with Gain 78, a penetrance depth of 3.5 cm, and a probe length of 5.5 cm. In this study, two representative muscles from the upper and lower extremities that are easy to assess using ultrasound were selected. Thus, the biceps brachii (BB) and triceps brachii (TB) in the upper extremity and the rectus femoris (RF) and biceps femoris (BF) in the extremity were chosen for study. MT and EI of these muscles were measured on the dominant hand side. The probe was placed perpendicular to the skin at minimal pressure to ensure accurate measurements. All participants were asked to be fully relaxed while lying in a supine position for the examination of the BB, TB, and RF muscles and in a prone position for the BF muscle. MT was measured in the short-axis view at the maximal vertical distance from the superficial to deep fascia layers. For the BB and TB muscles, the probe was placed between the acromion and cubital crease and scanned along the BB muscle to identify the thickest point of the BB muscle. Subsequently, the probe was laterally rotated 90° to identify the thickest point of the TB muscle. In addition, the probe was placed at the midpoint between the anterior superior iliac spine and the superior border of the patella for the RF muscle, and at the midpoint between the ischial tuberosity and fibular head for the BF muscle, followed by scanning along the RF and BF muscles to identify the thickest point of each muscle. To measure EI, regions of interest were drawn at each muscle that included maximum muscle tissue without the bone or surrounding fascia. The EI in the region of interest of each muscle was measured thrice and averaged for analysis. Fig 1 shows the methods used to measure ultrasonography parameters in each muscle.

Fig 1. Standard examination parameters.

Fig 1

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Muscle thickness and echo intensity of the four selected muscles (biceps brachii, triceps brachii, rectus femoris, and biceps femoris muscles) on the dominant hand side using a muscle ultrasound. The muscle thickness was measured in the short-axis view at the maximal vertical distance from the superficial to deep fascia layers. To measure echo intensity, regions of interest were drawn at each muscle that included maximum muscle tissue without bone or surrounding fascia.

Statistical analysis

Descriptive summaries are presented as frequencies and proportions for categorical variables and means and standard deviations for continuous variables. Pearson’s correlation analysis was performed to demonstrate the correlation between clinical parameters and ASM. To develop an ASM prediction equation, a multiple linear regression analysis was performed in the model development group, and a paired t-test was performed to investigate the agreement between the measured and estimated ASM. In addition, the Bland–Altman plot was used to compare the BIA-measured and estimated ASM. The prediction equation of ASM derived from the model development group was applied to the cross-validation group. A paired t-test and two-way random-effect intraclass correlation coefficient (ICC) were used to test the agreement between the measured and estimated ASM in the cross-validation group. In addition, a multivariate logistic regression model was used to identify the potential risk factors for sarcopenia. Low ASM group was defined as, based on AWGS 2019 consensus, ASM index of <7.0 kg/m2 for men and <5.7 kg/m2 for women by employing BIA methods [4]. Statistical comparisons between the normal and low ASM groups were performed using independent t-tests for continuous variables. The discriminative power of each parameter was assessed using the receiver operating characteristic curve and area under the curve (AUC). Statistical significance was set at p < 0.05. All statistical analyses were performed using SPSS 25.0 (IBM Corp., Armonk, NY, USA).

Results

Study participants

This study included 214 healthy volunteers (91 men, 123 women), of which two were excluded: one with inadequate data and another with a history of poliomyelitis. Thus, 212 participants (91 men and 121 women) were finally enrolled in this study. Men (n = 63 and 28) and women (n = 82 and 39) were included in the model development and cross-validation groups, respectively. Descriptive clinical data and ultrasound parameters for each group are summarized in Table 1. Pearson’s correlation analysis between the clinical parameters and ASM was performed. ASM was positively correlated with height, weight, BMI, and hand grip strength and negatively correlated with age. In addition, ASM was correlated with muscle thickness but negatively correlated with muscle EI. The results of the correlation analysis are summarized in Table 2.

Table 1. Demographic and clinical characteristics of the study participants.

Total (n = 212) Model development group Cross-validation group
Men (n = 61) Women (n = 90) Men (n = 30) Women (n = 31)
Mean ± SD Mean ± SD Mean ± SD Mean ± SD Mean ± SD
Age, years 59.47 ± 10.66 61.21 ± 11.40 57.88 ± 9.88 58.77 ± 12.40 61.35 ± 9.13
Height, cm 162.42 ± 8.38 169.53 ± 5.66 157.27 ± 5.79 169.58 ± 6.02 156.48 ± 4.98
Weight, kg 64.64 ± 11.22 72.10 ± 10.40 57.62 ± 7.19 73.63 ± 8.44 61.63 ± 9.77
BMI, kg/m 2 24.39 ± 3.03 25.04 ± 3.07 23.30 ± 2.63 25.56 ± 2.20 25.17 ± 3.74
Hand grip strength, kg 26.03 ± 8.68 33.36 ± 7.15 21.14 ± 4.84 32.67 ± 6.46 19.35 ± 6.85
Walking speed, cm/s 119.85 ± 18.47 119.12 ± 19.59 119.38 ± 18.28 121.52 ± 19.51 121.01 ± 16.30
ASM, kg 18.96 ± 4.55 23.10 ± 3.26 15.65 ± 2.05 23.61 ± 2.88 15.91 ± 2.26
ASM/Height 2 , kg/m 2 7.09 ± 1.09 8.01 ± 0.84 6.31 ± 0.55 8.18 ± 0.63 6.48 ± 0.70
Muscle thickness
    Biceps brachii, mm 13.89 ± 3.04 16.36 ± 2.41 11.85 ± 1.75 16.42 ± 2.96 12.53 ± 1.59
    Triceps brachii, mm 10.59 ± 3.51 12.48 ± 3.96 9.12 ± 2.39 12.42 ± 3.68 9.37 ± 2.58
    Rectus femoris, mm 11.26 ± 2.51 12.73 ± 2.49 10.23 ± 1.95 12.53 ± 2.27 10.10 ± 2.23
    Biceps femoris, mm 19.03 ± 4.53 21.34 ± 3.79 17.12 ± 3.88 22.03 ± 4.51 17.10 ± 4.09
Muscle echo intensity
    Biceps brachii 49.63 ± 2.50 48.84 ± 1.88 50.11 ± 2.96 48.39 ± 1.64 51.02 ± 1.62
    Triceps brachii 34.99 ± 8.42 31.36 ± 8.10 37.75 ± 7.50 30.81 ± 8.29 38.17 ± 7.50
    Rectus femoris 45.69 ± 3.96 45.37 ± 4.14 45.80 ± 3.63 45.52 ± 3.16 46.19 ± 5.16
    Biceps femoris 40.51 ± 5.85 41.20 ± 5.49 40.81 ± 5.51 36.79 ± 7.49 41.84 ± 4.39
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SD, standard deviation; BMI, body mass index; ASM, appendicular skeletal muscle mass.

Table 2. Correlation analysis between clinical parameters and appendicular skeletal muscle mass.

Total (n = 212) Men (n = 91) Women (n = 121)
r p-value r p-value r p-value
Age, years -0.184 0.007 -0.527 <0.001 -0.319 <0.001
Height, cm 0.889 <0.001 0.740 <0.001 0.751 <0.001
Weight, kg 0.859 <0.001 0.827 <0.001 0.741 <0.001
BMI, kg/m2 0.441 <0.001 0.547 <0.001 0.374 <0.001
Hand grip strength, kg 0.758 <0.001 0.470 <0.001 0.380 <0.001
Walking speed, cm/s -0.012 0.860 -0.062 0.562 0.018 0.848
Muscle thickness
    Biceps brachii, mm 0.718 <0.001 0.327 0.002 0.339 <0.001
    Triceps brachii, mm 0.525 <0.001 0.341 0.001 0.194 0.033
    Rectus femoris, mm 0.553 <0.001 0.361 <0.001 0.234 0.010
    Biceps femoris, mm 0.497 <0.001 0.393 <0.001 -0.027 0.765
Muscle echo intensity
    Biceps brachii -0.299 <0.001 -0.120 0.259 -0.010 0.912
    Triceps brachii -0.269 <0.001 0.145 0.169 0.057 0.535
    Rectus femoris -0.067 0.332 -0.075 0.478 0.013 0.886
    Biceps femoris -0.235 0.001 -0.395 <0.001 -0.055 0.549
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BMI, body mass index.

Development and validation of equation model for estimating ASM using muscle ultrasound parameters

Multiple linear regression was performed in the model development group to develop an equation for estimating the ASM using muscle ultrasound parameters. In the men group, weight, height, MT of the BF muscle, and the ratio of EI to MT of the BB muscle were predictors of ASM (Table 3 and S1 Table). The multiple linear regression model produced the following equation for estimated ASM in men:

Table 3. Regression models for predicting appendicular skeletal muscle mass in the men group.

r R2 Adjusted R2 SEE F Sig.
Model 1 0.880 0.775 0.767 1.573 99.657 <0.001
Model 2 0.905 0.818 0.809 1.426 85.497 <0.001
Model 3 0.909 0.827 0.814 1.404 66.780 <0.001
Model 4 0.911 0.830 0.818 1.390 66.446 <0.001
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SEE, standard error of the estimate.

Model 1: weight and height; Model 2: weight, height, and thickness of the biceps femoris; Model 3: weight, height, and echo intensity to muscle thickness ratio of the biceps brachii and rectus femoris; and Model 4: weight, height, thickness of the biceps femoris, and echo intensity to muscle thickness ratio of the biceps brachii.

Estimated ASM for men (kg) = 0.167 × weight (kg) + 0.228 × height (cm) + 0143 × BF thickness (mm) − 0.822 × ratio of EI to MT of BB − 28.187 (R2 = 0.830, adjusted R2 = 0.818).

In the women group, weight, height, MT of the RF muscle, and the ratio of EI to MT in the BB muscle were predictors of ASM (Table 4 and S2 Table). The multiple linear regression model produced the following equation for estimated ASM in women:

Table 4. Regression models for predicting appendicular skeletal muscle mass in the women group.

r R2 Adjusted R2 SEE F Sig.
Model 1 0.892 0.796 0.791 0.937 169.329 <0.001
Model 2 0.925 0.855 0.848 0.799 125.024 <0.001
Model 3 0.923 0.852 0.845 0.806 122.505 <0.001
Model 4 0.927 0.859 0.853 0.786 129.847 <0.001
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SEE, standard error of the estimate.

Model 1: weight and height; Model 2: weight, height, and thickness of the biceps brachii and rectus femoris; Model 3: weight, height, and echo intensity to muscle thickness ratio of the biceps brachii and rectus femoris; Model 4: weight, height, thickness of the rectus femoris, and echo intensity to muscle thickness ratio of the biceps brachii.

Estimated ASM for women (kg) = 0.115 × weight + 0.215 × height (cm) + 0.139 × RF thickness − 0.638 × ratio of EI to MT of BB – 23.502 (R2 = 0.859; adjusted R2 = 0.853; Fig 2B).

Fig 2. Relationship between the BIA-measured ASM and estimated ASM in the model development group.

Fig 2

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BIA, bioelectrical impedance analysis; ASM, appendicular skeletal muscle mass.

In the model development group, the estimated ASM did not significantly differ from the measured ASM in either group: men, p = 0.749; women, p = 0.548 (Fig 2), without a significant systematic error in the Bland–Altman plot (Fig 3). The developed ASM prediction equation was applied in the cross-validation group. The mean value of estimated ASM did not differ significantly from that of measured ASM in either men (23.61 kg vs 23.53 kg, p = 0.755; ICC = 0.948) or women (15.91 kg vs 15.99 kg, p = 0.516; ICC = 0.973) in the cross-validation group (Table 5).

Fig 3. Bland–Altman plot for the agreement between the BIA-measured ASM and estimated ASM in the model development group.

Fig 3

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BIA, bioelectrical impedance analysis; ASM, appendicular skeletal muscle mass.

Table 5. Intraclass correlation coefficient and standard error of estimated appendicular skeletal muscle mass in the cross-validation group.

ICC (95% CI) p-value Standard error (95% CI)
Men 0.948 (0.890–0.975) <0.001 0.077 (-0.421–0.574)
Women 0.973 (0.944–0.987) <0.001 0.124 (-0336–0.172)
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ASM, appendicular skeletal muscle mass; CI, confidence interval; ICC, intraclass correlation coefficient.

Cut-off value in ultrasound-derived parameters for sarcopenia risk screening

A low ASM index is essential for diagnosing sarcopenia. Among the study population, eight men and 13 women met the low ASM index criteria and were classified into the low ASM group. The low ASM group was older than the normal ASM group in men; however, no difference in age was observed between the two groups in women. Both men and women in the low ASM group exhibited weaker handgrip strength. Additionally, the low ASM group had a lower MT of the BB, TB, and RF muscles in men and the BB and TB muscles in women. However, there were no significant differences in the EI of any muscle between the two groups, except for the BF muscle in men. The clinical characteristics of the normal and low ASM groups are summarized in Table 6.

Table 6. Comparison between subjects in the normal and low ASM groups.

Men Women
ASM ≥ 7.0 ASM < 7.0 p-value ASM ≥ 5.7 ASM < 5.7 p-value
Number of patients 83 8 108 13
Age, years 59.27 ± 11.53 72.25 ± 5.82 0.002 58.77 ± 9.88 58.77 ± 9.24 0.933
Height, cm 170.03 ± 5.68 164.58 ± 3.85 0.010 157.67 ± 5.12 152.06 ± 6.94 0.008
Weight, kg 74.00 ± 8.92 58.06 ± 5.68 0.000 59.76 ± 7.76 49.37 ± 3.27 0.000
BMI, kg/m2 25.58 ± 2.63 21.41 ± 1.66 0.000 24.06 ± 3.04 21.44 ± 2.09 0.001
Hand grip strength, kg 33.87 ± 6.42 25.50 ± 7.54 0.003 20.88 ± 5.36 19.00 ± 6.12 0.395
Walking speed, cm/s 118.71 ± 19.05 132.44 ± 20.89 0.128 119.45 ± 17.46 122.75 ± 20.47 0.815
ASM, kg 23.83 ± 2.64 17.44 ± 1.36 0.000 16.08 ± 1.87 12.68 ± 1.27 0.000
ASM/Height2, kg/m2 8.22 ± 0.60 6.44 ± 0.53 0.000 6.46 ± 0.53 5.47 ± 0.16 0.000
Muscle thickness
    Biceps brachii, mm 16.57 ± 2.61 14.39 ± 1.21 0.005 12.15 ± 1.77 10.94 ± 0.75 0.008
    Triceps brachii, mm 12.76 ± 3.85 9.32 ± 2.18 0.011 9.34 ± 2.51 7.88 ± 1.05 0.024
    Rectus femoris, mm 12.91 ± 2.29 10.11 ± 2.27 0.004 10.30 ± 2.05 9.32 ± 1.56 0.085
    Biceps femoris, mm 21.80 ± 4.04 19.10 ± 3.09 0.051 17.26 ± 3.90 15.93 ± 4.03 0.252
Muscle echo intensity
    Biceps brachii 48.64 ± 1.81 49.15 ± 1.89 0.585 50.39 ±2.79 49.99 ± 1.88 0.359
    Triceps brachii 31.18 ± 8.41 31.14 ± 4.37 0.911 38.02 ± 7.19 36.51 ± 9.77 0.973
    Rectus femoris 45.32 ± 3.76 46.42 ± 4.63 0.231 45.95 ± 4.01 45.43 ± 4.55 0.586
    Biceps femoris 39.16 ± 6.39 45.82 ± 4.65 0.005 41.02 ± 5.28 41.52 ± 5.16 0.642
EI to MT ratio
    Biceps brachii 3.01 ± 0.54 3.43 ± 0.25 0.005 4.23 ± 0.65 4.59 ± 0.40 0.025
    Triceps brachii 2.75 ± 1.23 3.49 ± 0.91 0.077 4.38 ± 1.42 4.75 ± 1.45 0.148
    Rectus femoris 3.64 ± 0.80 4.81 ± 1.31 0.012 4.68 ± 1.23 5.05 ± 1.26 0.344
    Biceps femoris 1.89 ± 0.62 2.45 ± 0.42 0.005 2.54 ± 0.85 2.81 ± 0.92 0.255
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Descriptive summaries are presented as means ± standard deviations for continuous variables.

ASM, appendicular skeletal muscle mass; BMI, body mass index; EI, echo intensity; MT, muscle thickness.

Multivariate logistic regression analysis was performed to identify potential risk factors for sarcopenia (Table 7). In the men group, the EI to MT ratio of the RF muscle (odds ratio [OR] 3.536, 95% confidence interval [CI] 1.462–8.555; p = 0.005) and BF muscle (OR 3.2214, 95% CI 1.059–9.750; p = 0.039) were associated with low ASM. The EI to MT ratio of the RF and BF muscles for predicting the risk of low ASM had AUC of 0.770 (p = 0.012) and 0.803 (p = 0.005), respectively. The optimal cut-off points for predicting the risk of the low ASM group were an EI to MT ratio of ≥4.19 for RF and ≥2.14 for BF and BF. Using these cut-off values, a sensitivity of 75.0% and 87.5%, specificity of 75.9% and 73.5%, positive predictive value of 23.1% and 24.1%, and negative predictive value of 96.9% and 98.4% were obtained, respectively. In addition, the AUC of the combination of these two variables for predicting the risk of low ASM was 0.887 (p < 0.001). In the women group, the MT of the BB muscle (OR 0.644, 95% CI, 0.442–0.939; p = 0.022) was associated with low ASM. The MT of BB muscle for predicting the risk of low ASM had an AUC of 0.727 (p = 0.008), and the optimal cut-off value was BB ≤ 11.56 mm. Using this cut-off value, a sensitivity of 92.3%, specificity of 61.1%, positive predictive value of 22.2%, and negative predictive value of 98.4% were obtained.

Table 7. Univariate and multivariate logistic regression analyses.

Men group
Univariate logistic regression
OR (95% CI) p-value
Muscle thickness
    Biceps brachii 0.690 (0.498–0.956) 0.026
    Triceps brachii 0.700 (0.511–0.957) 0.026
    Rectus femoris 0.527 (0.342–0.812) 0.004
    Biceps femoris 0.846 (0.703–1.018) 0.076
Muscle echo intensity
    Biceps brachii 1.169 (0.779–1.754) 0.452
    Triceps brachii 0.999 (0.9136–1.093) 0.987
    Rectus femoris 1.097 (0.870–1.383) 0.433
    Biceps femoris 1.20 (1.058–1.526) 0.011
EI to MT ratio
    Biceps brachii 3.562 (1.034–12.274) 0.044
Triceps brachii 1.662 (0.891–3.099) 0.110
Rectus femoris 3.409 (1.496–7.766) 0.004
    Biceps femoris 2.955 (1.051–8.305) 0.040
Multivariate logistic regression (Forward stepwise)
OR (95% CI) p-value
EI to MT ratio
    Rectus femoris 3.536 (1.462–8.555) 0.005
    Biceps femoris 3.214 (1.059–9.750) 0.039
Women group
Univariate logistic regression
OR (95% CI) p-value
Muscle thickness
    Biceps brachii 0.644 (0.442–0.939) 0.022
    Triceps brachii 0.759 (0.578–0.996) 0.046
    Rectus femoris 0.781 (0.582–1.049) 0.100
    Biceps femoris 0.916 (0.789–1.063) 0.248
Muscle echo intensity
    Biceps brachii 0.952 (0.787–1.152) 0.614
    Triceps brachii 0.974 (0.902–1.050) 0.490
    Rectus femoris 0.969 (0.842–1.115) 0.657
    Biceps femoris 1.019 (0.911–1.140) 0.743
EI to MT ratio
    Biceps brachii 2.429 (0.963–6.129) 0.060
    Triceps brachii 1.194 (0.803–1.774) 0.382
    Rectus femoris 1.245 (0.817–1.897) 0.308
    Biceps femoris 1.375 (0.755–2.504) 0.298
Multivariate logistic regression (Forward stepwise)
OR (95% CI) p-value
Muscle thickness
    Biceps brachii 0.644 (0.442–0.939) 0.022
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OR, odds ratio; CI, confidence interval; EI, echo intensity; MT, muscle thickness.

Discussion

This study deduced ultrasound-driven estimation equations of the ASM using a multiple linear regression model. Additionally, the estimated ASM was not significantly different from the BIA-measured ASM in the men and women groups. Furthermore, our study showed that muscle ultrasound parameters, particularly the EI to MT ratio of the thigh muscles (BF and RF muscles) in the men group and the MT of the BB muscle in the women group, were associated with risk factors for low ASM.

Some studies have suggested that muscle ultrasonography may be a reliable tool for estimating the muscle mass. Abe et al. [11] developed a prediction equation for estimating lean body mass using MT that was measured by employing B-mode ultrasound. However, this study used the sum of the MT at nine sites (forearm, biceps, triceps, abdomen, subscapular, quadriceps, hamstrings, gastrocnemius, and tibialis anterior muscles) as the equation parameters. Thus, it is difficult and time-consuming to estimate the muscle mass. Takai et al. developed an estimation equation for whole-body fat-free mass using MT at four sites (anterior upper arm, anterior and posterior thigh, and posterior lower leg) measured using ultrasound and limb length [12]. Furthermore, some studies have reported that ASM can be predicted using a single ultrasound image of the forearm [6, 13]. Our study revealed that ASM can be effectively estimated by evaluating only two muscles in both men and women. This result suggests that muscle mass can be quickly and easily assessed using ultrasonography. In summary, muscle ultrasonography is a reliable and effective tool for estimating the muscle mass.

Some studies have reported that muscle ultrasonography could be used as a screening tool for sarcopenia. Rustani et al. suggested that RF thickness is a valuable parameter for sarcopenia screening [8]. Yamada et al. reported that quadriceps MT and thigh muscle volume can be indicators of sarcopenia diagnosis [14]. In addition, some studies suggested that the thickness of calf muscles, such as the tibialis anterior and gastrocnemius, can be a favorable parameter for sarcopenia screening [9, 15–17]. Some studies have also suggested that evaluation of arm muscles can help in screening for sarcopenia [6, 18, 19]. In this study, we found that muscle ultrasonography parameters, the EI to MT ratio of thigh muscles (RF and BF muscles) in men and MT of BB muscle in women, are associated with low ASM. These findings suggest that muscle ultrasonography is an easy and rapid screening method for sarcopenia. In addition, the results of this study imply that different muscles can be used as helpful parameters for sarcopenia screening according to sex. Further studies with a larger number of participants are needed to determine the appropriate muscle selection and optimal cut-off value.

Muscles (mainly contractile proteins) appear hypoechogenic, whereas adipocytes and fibrous tissue components appear hyperechogenic. Muscle EI is the degree of brightness of the acquired image and is affected by intramuscular fat infiltration and fibrotic changes, which are key factors in determining muscle function quality [20]. Therefore, muscle EI reflects the proportion of adipocytes and fibrous tissue in muscles [21, 22] and is considered a parameter that could reflect muscle quality. Some studies reported that muscle EI may be associated with muscle strength and functional status [23–25]. Previous research has reported that muscle EI is negatively correlated with MT in older adults [26]. Another study reported that changes in muscle EI were significantly associated with changes in BMI [27]. These findings imply that muscle EI has a more complicated relationship with MT and other demographic factors. However, few studies have reported an association between EI and muscle mass. This study showed no significant differences in the EI value of each muscle between the normal and low ASM groups, except for the BF muscle in men. However, the present study showed that the EI to MT ratio was significantly associated with the estimation of muscle mass. These findings imply that the EI to MT ratio may be a more helpful parameter for sarcopenia assessment than the EI alone. Further studies are required to clarify the clinical implications of EI in the muscles.

This study had some limitations. First, this study had a very small number of participants with low ASM to obtain a cut-off value for sarcopenia screening. This study was designed to assess the reliability and usefulness of muscle ultrasonography in measuring ASM in healthy volunteers. Outcomes of healthy volunteers who met the sarcopenia criteria were used to validate the results of this study. Therefore, further studies with a larger number of participants with low ASM are needed to clarify the optimal cut-off value for sarcopenia screening. Second, ultrasound is an operator-dependent technique that is affected by different device settings. Additionally, the EI value of the muscle may differ according to the ultrasound device used. Therefore, to overcome this limitation, this study was designed for using a single ultrasound device. Accordingly, the equation developed for estimating ASM from the present study has been limited to various ultrasound devices. Nevertheless, the results of this study support the idea that muscle ultrasound could be an effective tool for estimating muscle mass. Further studies using various ultrasound devices are needed to clarify the optimal cut-off value of muscle EI for sarcopenia screening according to different ultrasound device. Third, muscle ultrasound data from the distal parts of the arm and leg were not included in this study. Since this study was designed to investigate a simple and quick equation for estimating ASM using muscle ultrasound, only the representative muscles that are easy to access via muscle ultrasound were selected.

Conclusion

Muscle ultrasonography seems to be an effective tool for estimating muscle mass and screening for sarcopenia. Among the various parameters, MT and EI to MT ratio may be helpful indicators for assessing sarcopenia.

Supporting information

S1 Table. Multiple linear regression analysis (model 4) in men group.

(DOCX)

Click here for additional data file. (15.3KB, docx)
S2 Table. Multiple linear regression analysis (model 4) in women group.

(DOCX)

Click here for additional data file. (13.4KB, docx)

Acknowledgments

We would like to thank our colleagues in the Department of Neurology, Korea University Anam Hospital for their enthusiastic assistance. We also thank Kyoung-Sook Yang for providing statistical advice and analysis.

Data Availability

All relevant data are within the paper and its Supporting Information files.

Funding Statement

This work was supported by the Industrial Technology Innovation Program (No. 20008842), funded by the Ministry of Trade, Industry & Energy (MOTIE, Korea). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

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Decision Letter 0

Emiliano Cè

12 Sep 2022

PONE-D-22-16915Usefulness of muscle ultrasound in appendicular skeletal muscle mass estimation for sarcopenia assessmentPLOS ONE

Dear Dr. Kim,

Thank you for submitting your manuscript to PLOS ONE. After careful consideration, we feel that it has merit but does not fully meet PLOS ONE’s publication criteria as it currently stands. Therefore, we invite you to submit a revised version of the manuscript that addresses the points raised during the review process.

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Reviewer #1: Thanks to the authors for their good job. Sarcopenia is an important issue in aging societies and increasing comorbidities. This article could be a fine guide for the detection and management of sarcopenia. In this respect, I think it will contribute to the literature.

Reviewer #2: Dear Editor,

the manuscript entitled "Usefulness of muscle ultrasound in appendicular skeletal muscle mass estimation for

sarcopenia assessment" explore the use of ultrasound (US) as a simple, cheap, and non-invasive tool to assess sarcopenia.

To this purpose, 212 participants have been enrolled to the study.

I found the reading fluent and the english correct, however, I have some major concerns about the paper content.

1. Aiming to investigate whether muscle ultrasonography is an effective tool for estimating the appendicular skeletal muscle mass (ASM), the authors combined some parameters, among which some US measurements, into two equations (one for men and one for women). Then, they compared the estimated ASM to the one determined by a BIA analysis.

I found this approach questionable as BIA is not the gold standard for ASM assessment. Indeed, ASM is not a BIA direct measure but has to be derived by equation, therefore, its accuracy depends on which equation is adopted by the device. Moreover, other factors influence BIA measurements like hydration status, age, and body mass. About this latter, it has been found that BIA tends to underestimate ASM in overweight people. Even though the equations developed by the authors to estimate ASM took into account age, sex, and body mass, the measure used as reference value cannot be considered equal to the one determined by DXA or CT or MRI. In addition, ASM was estimated by authors feeding the equations with EI values determined during US measurements. Such index, however, has to be considered with cautions as its reliability is age-dependent (Strasser 2013) and it is influenced by several factors among which hydration status, probe position, and probe settings. Even though the reliability of the measure was good, the equations developed by the authors and used to estimate ASM, can be considered valid only in this specific study, with their specific US device, its settings and their operator. These equations on different laboratories may perform differently.

2. The other limit I found in the study relates to the US ability to discriminate lowASM people. Indeed, after having determined ASM on 212 participants, the authors found that 21 showed low ASM values and, by a ROC analysis, determined a cut-off value on the MT of some muscles. In my opinion the sample size of low ASM group was too poor to return a reliable value.

MINOR

1. In my opinion the introduction is too vague and should be improved, taking care in the terminology. The rationale is not clear and the paragraph dealing with sarcopenia should be delved more deeply. A complete definition of sarcopenia should be given: "Sarcopenia is a progressive, generalized, age-related loss of skeletal muscle mass [1]." is reductive. Notwithstanding the authors continued citing the association to loss of muscle strength and the reduction of physical activity, the offical definition of sarcopenia considers sarcopenia as concurrent reduction of skeletal muscle mass, muscle strength and functional physical performance. This latter is different from "physical activity".

"Historically, muscle mass has been measured using several imaging techniques, including dualenergy

X-ray absorptiometry, computed tomography, and magnetic resonance imaging." Which of these technique is considered the gold standard?

"Muscle ultrasound is a noninvasive, cost-effective, and easily accessible imaging technique for the evaluation of neuromuscular disorders [5]." I find this sentence unnecessary.

"This study aimed to investigate whether muscle ultrasonography is an effective tool for estimating the appendicular skeletal muscle mass (ASM) in terms of muscle quantity and quality." ASM should be introduced previously, in sarcopenia paragraph otherwise it is not clear why it represents a variable of interest. Moreover, given that the authors previously reported "muscle ultrasonography has been suggested as a valuable tool for assessing sarcopenia because it can assess both muscle quantity and quality" it is not clear which is the novelty of the present study. It seems this study aims to confirm something that is already known.

"In addition, we explored whether muscle ultrasonography can be used as a screening tool for sarcopenia in middle-aged and older individuals" please, explain why you chose such target of population. Is there any reason for involving middle-aged and old individuals?

"A hold-out cross-validation method was used to develop and validate the ASM prediction equation." Why did the authors have to validate an ASM prediction equation? The reader has to be previously be informed that US-derived ASM relies on prediction equation. Moreover, the authors should explain the reason why they proposed a different equation.

Please, do not use WEIGHT but BODY MASS

Please, provide an explanation about the test administered in Clinical assessment. Why did they test handgrip and gait speed, and analyzed body composition?

Pleae explain why ASM has been normalized to height.

Please, explain the criteria adopted to choose the muscles that have been measured (why BB, TB, RF ad BF)?

Please, explain why calf muscles have not been considered.

Please, it is recommended to provide all the information about US measurements: gain, frequency of the transducer beam, depth of penetrance, probe length.

As ROI appears only two times, I suggest to remove the acronymus.

In the statistical analysis, did the authors check for differences between DEVELOPMENT and cross-validation GROUP?

"Low ASM group was defined as, based on AWGS 2019 consensus, ASM index < 7.0 kg/m2 for men and < 5.7 kg/m2 for women." Please, provide a reference

Being sarcopenia a combination of muscle mass loss, low muscle strength and reduced functionality, did the authors investigate the correlation between functional parameters and ASM values?

Table 1 To make it more readable, I suggest to use only one column to show mean+/- SD and to thicken the column border of Model development goup and cross-validation group

Please, check that measure units are always present.

"The estimated ASM did not significantly differ from the measured ASM in either the men or the women groups (p = 0.749 and p = 0.548, respectively; Fig. 2)" Does this sentence relate to MODEL DEVELOPMENT group?

"without a significant systematic error in the Bland–Altman plot (p = 0.091 and p = 0.056, respectively; Fig. 3)." from which analysis, do these values derive?

Table 4. Differences in the measured and estimated appendicular skeletal muscle mass in the cross-validation group" I would appreciate a Bland_altman plot of these data.

About "Cut-off value in ultrasound-derived parameters for sarcopenia screening" I found questionable diagnosing sarcopenia on ASM alone. Similarly, I found questionable performing statistical analysis on samples with such diversity in size.

"Table 5. Comparison between subjects in the normal and low ASM groups." These results come from a statistical analysis that compared groups of different size (within male comparison: 83 vs 8 particpants; within female comparison: 108 vs 13 participants). There is no mention in statistical analysis paragraph about this comparison and, in any case, the size is so different that the results lose validity.

Please add references to:

"In addition, muscle ultrasonography has been suggested as a valuable tool for assessing sarcopenia because it can assess both muscle quantity and quality."

"Low ASM group was defined as, based on AWGS 2019 consensus, ASM index < 7.0 kg/m2 for men and < 5.7 kg/m2 for women"(reference is lacking)

**********

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Reviewer #2: No

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PLoS One. 2023 Jan 17;18(1):e0280202. doi: 10.1371/journal.pone.0280202.r002

Author response to Decision Letter 0

8 Nov 2022

On behalf of all the co-authors, I am very grateful to all the reviewers for their careful review, insightful comments, and constructive suggestions, which greatly helped to improve our manuscript. I have revised the manuscript to elaborate on and clarify the issues raised by the reviewers. I believe that the manuscript has substantially improved with the revision.

The attached file named "Response to Reviewers" are our responses to the reviewers' comments, including how and where the text has been modified. I have highlighted the changes to the manuscript by using the track changes mode in MS Word. I hope that you find our responses satisfactory and that the manuscript is now acceptable for publication.

Attachment

Submitted filename: response to reviewer.docx

Click here for additional data file. (41.7KB, docx)

Decision Letter 1

Emiliano Cè

6 Dec 2022

PONE-D-22-16915R1Usefulness of muscle ultrasound in appendicular skeletal muscle mass estimation for sarcopenia assessmentPLOS ONE

Dear Dr. Kim,

Thank you for submitting your manuscript to PLOS ONE. After careful consideration, we feel that it has merit but does not fully meet PLOS ONE’s publication criteria as it currently stands. Therefore, we invite you to submit a revised version of the manuscript that addresses the points raised during the review process.

==============================

ACADEMIC EDITOR: Two experts in the field reviewed your manuscript. They both found your new manuscript version decisively improved. Still Reviewer 2 has raised some minors issues that you should consider while revising the manuscript.==============================

Please submit your revised manuscript by Jan 20 2023 11:59PM. If you will need more time than this to complete your revisions, please reply to this message or contact the journal office at plosone@plos.org. When you're ready to submit your revision, log on to https://www.editorialmanager.com/pone/ and select the 'Submissions Needing Revision' folder to locate your manuscript file.

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If you would like to make changes to your financial disclosure, please include your updated statement in your cover letter. Guidelines for resubmitting your figure files are available below the reviewer comments at the end of this letter.

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PLOS ONE

Journal Requirements:

Please review your reference list to ensure that it is complete and correct. If you have cited papers that have been retracted, please include the rationale for doing so in the manuscript text, or remove these references and replace them with relevant current references. Any changes to the reference list should be mentioned in the rebuttal letter that accompanies your revised manuscript. If you need to cite a retracted article, indicate the article’s retracted status in the References list and also include a citation and full reference for the retraction notice.

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Reviewer's Responses to Questions

Comments to the Author

1. If the authors have adequately addressed your comments raised in a previous round of review and you feel that this manuscript is now acceptable for publication, you may indicate that here to bypass the “Comments to the Author” section, enter your conflict of interest statement in the “Confidential to Editor” section, and submit your "Accept" recommendation.

Reviewer #1: All comments have been addressed

Reviewer #2: (No Response)

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2. Is the manuscript technically sound, and do the data support the conclusions?

The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented.

Reviewer #1: Yes

Reviewer #2: Yes

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3. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #1: Yes

Reviewer #2: Yes

**********

4. Have the authors made all data underlying the findings in their manuscript fully available?

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Reviewer #1: Yes

Reviewer #2: Yes

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Reviewer #1: Yes

Reviewer #2: Yes

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6. Review Comments to the Author

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Reviewer #1: (No Response)

Reviewer #2: Dear Authors,

I appreciate your efforts in addressing most of my comments. I just have few minor concerns that I'd like to put to your attention.

In some comments I asked you to kindly explain your choices (comment 7, 8, 10, 11, and 12). You carefully addressed the comment in the Response section but, if I've seen correctly, you did not insert the explanation in the manuscript. My recommendations did not aim at receiving an explanation for myself rather providing more details to the readers by adding further explanantions in the text. Most of the times I had the answer so I was asking you to improve the manuscript by going deep insight for the readers.

Table 1 is almost ok. I personally do not appreciate decimals when they lose sense. For example: are two decimals essentials when the order of the measure unit is centimeters or millimeters? I understand that the table appears neater when every value is reported with two decimals but I wonder if the second decimals of a millimeter-based value has any sense.

In Conclusion I'd suggest a mitigation of the sentence "Muscle ultrasonography can be an effective tool for....." with something like "Muscle ultrasonography seems/appears be an effective tool for..."

**********

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Reviewer #1: No

Reviewer #2: No

​**********

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PLoS One. 2023 Jan 17;18(1):e0280202. doi: 10.1371/journal.pone.0280202.r004

Author response to Decision Letter 1

9 Dec 2022

Reviewers' comments

Reviewer #1: (No Response)

Reviewer #2: Dear Authors,

I appreciate your efforts in addressing most of my comments. I just have few minor concerns that I'd like to put to your attention.

Comments (1)

In some comments I asked you to kindly explain your choices (comment 7, 8, 10, 11, and 12). You carefully addressed the comment in the Response section but, if I've seen correctly, you did not insert the explanation in the manuscript. My recommendations did not aim at receiving an explanation for myself rather providing more details to the readers by adding further explanations in the text. Most of the times I had the answer so I was asking you to improve the manuscript by going deep insight for the readers.

Response (1)

We appreciate your careful reading of this manuscript and valuable comments on this research. We revised the manuscript, as you recommended.

1) About your previous comment #7, we modified the following sentence to clarify the purpose of our study and to explain why we included only healthy volunteers aged 41 – 80 years.

(Line 70-73) Since muscle mass begins to decline in middle-aged, and decreases gradually with age [10], we explored whether muscle ultrasonography could be used as a screening tool for sarcopenia in middle-aged and older individuals.

2) About comment #8, we added the following sentences to describe a more detailed hold-out cross-validation method in the revised manuscript.

(Line 82-86) the entire dataset of our study was randomly divided into a model development group (training set) and a validation group (testing set). The ASM prediction equation using ultrasound parameters was then deduced from the model development group, and the accuracy of deducing the ASM equation was verified in the cross-validation group.

3) About comment #10-12, we modified the manuscript to clarify the methods of this study as follows:

(Line 95-100) To evaluate muscle strength, the handgrip strength of the dominant hand was measured using hand-held dynamometry (Jamar hand dynamometry, TEC Inc., Clifton, NJ, USA). To evaluate physical performance, gait speed was measured using gait analysis equipment (GAITRite®, CIR Systems Inc., NJ, USA). To measure muscle mass, body composition analysis was performed via BIA methods using InBody770 (InBody Co. LTD, Seoul, Korea).

(Line 107-110) Since muscle mass correlates with body size, muscle mass-adjusted body size is required to identify the optimal cut-off point for sarcopenia. The EWGSOP and AWGS 2019 consensus have proposed the cutoff point of sarcopenia using ASM normalized with the squared height [3, 4].

(Line 116-123) In this study, two representative muscles from the upper and lower extremities that are easy to assess using ultrasound were selected. Thus, the biceps brachii (BB) and triceps brachii (TB) in the upper extremity and the rectus femoris (RF) and biceps femoris (BF) in the extremity were chosen for study. MT and EI of these muscles were measured on the dominant hand side.

Comments (2)

Table 1 is almost ok. I personally do not appreciate decimals when they lose sense. For example: are two decimals’ essentials when the order of the measure unit is centimeters or millimeters? I understand that the table appears neater when every value is reported with two decimals but I wonder if the second decimals of a millimeter-based value have any sense.

Response (2)

In Table 1, all variables were presented as two decimals. Although two decimals may not be essential when the order of the measuring unit is centimeters or millimeters, we presented the two decimals for a unified representation.

Comments (3)

In Conclusion I'd suggest a mitigation of the sentence "Muscle ultrasonography can be an effective tool for....." with something like "Muscle ultrasonography seems/appears be an effective tool for..."

Response (3)

We modified the sentence in Conclusion, as you recommended,

(Line 344) Muscle ultrasonography seems to be an effective tool for estimating muscle mass and screening for sarcopenia.

Attachment

Submitted filename: response to reviewers_final.docx

Click here for additional data file. (26.3KB, docx)

Decision Letter 2

Emiliano Cè

19 Dec 2022

PONE-D-22-16915R2Usefulness of muscle ultrasound in appendicular skeletal muscle mass estimation for sarcopenia assessmentPLOS ONE

Dear Dr. Kim,

Thank you for submitting your manuscript to PLOS ONE. After careful consideration, we feel that it has merit but does not fully meet PLOS ONE’s publication criteria as it currently stands. Therefore, we invite you to submit a revised version of the manuscript that addresses the points raised during the review process.

==============================

ACADEMIC EDITOR: Dear Authors, your manuscript has been revised by an expert in the field that found some minor issues.

Please submit your revised manuscript by Feb 02 2023 11:59PM. If you will need more time than this to complete your revisions, please reply to this message or contact the journal office at plosone@plos.org. When you're ready to submit your revision, log on to https://www.editorialmanager.com/pone/ and select the 'Submissions Needing Revision' folder to locate your manuscript file.

Please include the following items when submitting your revised manuscript:

  • A rebuttal letter that responds to each point raised by the academic editor and reviewer(s). You should upload this letter as a separate file labeled 'Response to Reviewers'.

  • A marked-up copy of your manuscript that highlights changes made to the original version. You should upload this as a separate file labeled 'Revised Manuscript with Track Changes'.

  • An unmarked version of your revised paper without tracked changes. You should upload this as a separate file labeled 'Manuscript'.

If you would like to make changes to your financial disclosure, please include your updated statement in your cover letter. Guidelines for resubmitting your figure files are available below the reviewer comments at the end of this letter.

If applicable, we recommend that you deposit your laboratory protocols in protocols.io to enhance the reproducibility of your results. Protocols.io assigns your protocol its own identifier (DOI) so that it can be cited independently in the future. For instructions see: https://journals.plos.org/plosone/s/submission-guidelines#loc-laboratory-protocols. Additionally, PLOS ONE offers an option for publishing peer-reviewed Lab Protocol articles, which describe protocols hosted on protocols.io. Read more information on sharing protocols at https://plos.org/protocols?utm_medium=editorial-email&utm_source=authorletters&utm_campaign=protocols.

We look forward to receiving your revised manuscript.

Kind regards,

Emiliano Cè

Academic Editor

PLOS ONE

Journal Requirements:

Please review your reference list to ensure that it is complete and correct. If you have cited papers that have been retracted, please include the rationale for doing so in the manuscript text, or remove these references and replace them with relevant current references. Any changes to the reference list should be mentioned in the rebuttal letter that accompanies your revised manuscript. If you need to cite a retracted article, indicate the article’s retracted status in the References list and also include a citation and full reference for the retraction notice.

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Reviewers' comments:

[NOTE: If reviewer comments were submitted as an attachment file, they will be attached to this email and accessible via the submission site. Please log into your account, locate the manuscript record, and check for the action link "View Attachments". If this link does not appear, there are no attachment files.]

While revising your submission, please upload your figure files to the Preflight Analysis and Conversion Engine (PACE) digital diagnostic tool, https://pacev2.apexcovantage.com/. PACE helps ensure that figures meet PLOS requirements. To use PACE, you must first register as a user. Registration is free. Then, login and navigate to the UPLOAD tab, where you will find detailed instructions on how to use the tool. If you encounter any issues or have any questions when using PACE, please email PLOS at figures@plos.org. Please note that Supporting Information files do not need this step.

PLoS One. 2023 Jan 17;18(1):e0280202. doi: 10.1371/journal.pone.0280202.r006

Author response to Decision Letter 2

20 Dec 2022

We carefully checked all reference lists and found the #27 article did not correctly include the publication information. So, the information of reference #27 was updated in the revised manuscript as follows:

(Line 455-458) 27. Monjo H, Fukumoto Y, Asai T, Ohshima K, Kubo H, Tajitsu H, et al. Changes in Muscle Thickness and Echo Intensity in Chronic Stroke Survivors: A 2-Year Longitudinal Study. J Clin Neurol. 2022;18(3):308-14. https://doi.org/10.3988/jcn.2022.18.3.308 PMID: 35196746

In addition, this manuscript (PONE-D-22-16915R3) added 1 more reference (Reference #10) to provide further explanations as the reviewer’s recommendation, compared to the previously revised manuscript (PONE-D-22-16915R1). Therefore, the final version of the revised manuscript (PONE-D-22-16915R3) included a total of 27 references. We have reviewed all reference list to ensure that it is complete and correct.

Attachment

Submitted filename: response to reviewers.docx

Click here for additional data file. (17.2KB, docx)

Decision Letter 3

Emiliano Cè

22 Dec 2022

Usefulness of muscle ultrasound in appendicular skeletal muscle mass estimation for sarcopenia assessment

PONE-D-22-16915R3

Dear Dr. Kim,

We’re pleased to inform you that your manuscript has been judged scientifically suitable for publication and will be formally accepted for publication once it meets all outstanding technical requirements.

Within one week, you’ll receive an e-mail detailing the required amendments. When these have been addressed, you’ll receive a formal acceptance letter and your manuscript will be scheduled for publication.

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Kind regards,

Emiliano Cè

Academic Editor

PLOS ONE

Additional Editor Comments (optional):

Reviewers' comments:

Acceptance letter

Emiliano Cè

5 Jan 2023

PONE-D-22-16915R3

Usefulness of muscle ultrasound in appendicular skeletal muscle mass estimation for sarcopenia assessment

Dear Dr. Kim:

I'm pleased to inform you that your manuscript has been deemed suitable for publication in PLOS ONE. Congratulations! Your manuscript is now with our production department.

If your institution or institutions have a press office, please let them know about your upcoming paper now to help maximize its impact. If they'll be preparing press materials, please inform our press team within the next 48 hours. Your manuscript will remain under strict press embargo until 2 pm Eastern Time on the date of publication. For more information please contact onepress@plos.org.

If we can help with anything else, please email us at plosone@plos.org.

Thank you for submitting your work to PLOS ONE and supporting open access.

Kind regards,

PLOS ONE Editorial Office Staff

on behalf of

Professor Emiliano Cè

Academic Editor

PLOS ONE

Associated Data

    This section collects any data citations, data availability statements, or supplementary materials included in this article.

    Supplementary Materials

    S1 Table. Multiple linear regression analysis (model 4) in men group.

    (DOCX)

    Click here for additional data file. (15.3KB, docx)
    S2 Table. Multiple linear regression analysis (model 4) in women group.

    (DOCX)

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    Attachment

    Submitted filename: response to reviewer.docx

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    Attachment

    Submitted filename: response to reviewers_final.docx

    Click here for additional data file. (26.3KB, docx)
    Attachment

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    Data Availability Statement

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