Influence of muscle depth and thickness on ultrasound echo intensity of the vastus lateralis

Abstract

Background

Ultrasonography is used to evaluate muscle quality (i.e. echo intensity [EI]), but an attenuation of ultrasound waves occurs in deeper tissues, potentially affecting these measures.

Purpose

To determine whether muscle thickness (MT) affects EI and if EI varies between the superficial and deep portions of the muscle.

Materials and Methods

MT, EI, subcutaneous adipose tissue thickness (SAT), tissue depth (DIS_DEEP), and EI of the overall (EI_FULL) as well as deep (EI_DEEP) and superficial (EI_SUPF) portions of the vastus lateralis (VL) were assessed in 33 resistance-trained males using ultrasonography. The difference (EI_DIFF) between EI_SUPF and EI_DEEP was calculated. Mean differences between EI_FULL, EI_SUPF, and EI_DEEP were analyzed using a repeated-measures analysis of variance (ANOVA). Relationships between measures of muscle depth/ thickness and EI were examined using Pearson’s r.

Results

EI_SUPF was greater than EI_DEEP (P < 0.001) and EI_FULL (P < 0.001). MT was negatively correlated with EI_FULL (P < 0.001) and positively correlated with EI_DIFF (P < 0.001). SAT was not correlated with any EI measure, but DIS_DEEP was positively correlated with EI_DIFF (P < 0.001).

Conclusion

EI of the VL is heterogeneous, as the deeper portion produces lower values than the superficial portion. Thicker muscles present lower EI but have greater discrepancies in EI between the superficial and deep portions. Although SAT was not correlated with EI, DIS_DEEP was related to EI_DIFF, demonstrating that the combination of MT and SAT should be considered when evaluating muscle quality. Future research is necessary to determine if changes in EI following resistance training are driven by increases in MT.

Keywords

Echogenicity ultrasonography cross-sectional area tissue composition attenuation

Introduction

Ultrasonographic imaging of skeletal muscle has become an increasingly popular method of examining muscle morphological characteristics in response to exercise and nutritional interventions, muscle damage, edema, aging, and disease (1 –9). While quantification of muscle size and architecture are common in several investigations, recent focus has been given to the examination of muscle echo intensity (EI). EI refers to the reflectance of ultrasound waves off of a structure of interest and is quantified via grayscale density analysis of individual pixels within an ultrasound image (10). Darker structures in an ultrasound image are indicative of a tissue with less reflectivity and correspond with lower EI values, whereas the opposite is true for brighter structures (11). Although skeletal muscle is relatively hypoechoic in nature, intramuscular components can affect muscle echogenicity (10,11). It has been suggested that muscles with a greater proportion of contractile tissue have lower EI values due to the hypoechoic nature of contractile elements (10). EI is thought to be a non-invasive surrogate measure of muscle quality, as increased EI is associated with infiltration of intramuscular fat, collagen, and fibrous and connective tissue (10,12 –14). Although numerous investigations have demonstrated that muscle EI is related to functional ability, strength, and power (3,6,13 –19), studies using EI as a proxy of muscle quality after resistance training have generated inconsistent results (4,6,13,20 –23), leading researchers to question the true physiological interpretation of muscle EI (24).

Recently, the examination of regional differences in intramuscular EI has become popular (4,14,25 –27), as different types of exercise training may induce non-homogenous muscular adaptations (4,5,28). Studies have shown that EI values vary between muscles (3,4,6,14,25,26,29), along the length of an individual muscle (4,14,26), and even within the same ultrasound image of a muscle (25). While differences in EI may be due to variations in fiber orientation, muscle architecture, and intramuscular adipose and fibrous tissue content, it is possible that tissue depth alone may influence ultrasound-derived EI values.

On most ultrasound devices, visualization of superficial tissues is relatively easy, whereas the reflection and absorption of ultrasound waves by the superficial tissue layers make deeper tissues more difficult to visualize (10,30). Differences in acoustic impedance between tissues result in an attenuation of the ultrasound beam, causing deeper structures to have a more distorted appearance than superficial structures. In line with this notion, previous research has demonstrated that the amount of subcutaneous adipose tissue adjacent to the muscle affects muscle EI (14). Specifically, Young et al. (14) observed that EI values increase when the subcutaneous adipose tissue adjacent to the muscle is compressed. As such, correcting for subcutaneous adipose tissue thickness in the examination of EI has become increasingly popular, and studies have demonstrated that EI corrected for subcutaneous adipose tissue thickness values are more predictive of physical performance (31,32) and body composition (12,14,32) than raw EI values. Nevertheless, increased muscle thickness may also result in an attenuation of the ultrasound beam within the deeper portions of an individual muscle, therefore affecting intramuscular EI values.

The aim of the present study was to examine the heterogeneity of EI between the superficial and deep portions of the vastus lateralis (VL). A secondary aim was to determine whether muscle depth influenced muscle EI or the differences in EI between the superficial and deep portions of the VL.

Material and Methods

Experimental design

Participants reported to the Human Performance Laboratory on two occasions. During visit 1, participants were informed of all study procedures, risks, and benefits and completed a written informed consent form. To establish participant eligibility, potential participants filled out a physical activity readiness questionnaire (PAR-Q+) and medical history and physical activity questionnaire (MHAQ). Eligible participants were instructed to return to the laboratory for their testing day. Participants were instructed to refrain from vigorous lower-body exercise for at least 72 h, alcohol and caffeine for 24 h, and food and flavored beverages for 4 h before the scheduled testing time. On the day of testing, each participant underwent an assessment of hydration status to ensure euhydration, followed by anthropometric testing, body composition assessment, and ultrasonography assessment. This investigation was approved by the University of Central Florida Institutional Review Board for human subjects (approval number: BIO-18-14303; 21 September 2018) and all procedures were in accordance with the ethical standards of the 1964 Helsinki Declaration and its later amendments.

Participants

Thirty-five recreationally active males aged 18–35 years were recruited, and each participant provided their written informed consent to participate. Participants were required to be resistance-trained, which was defined as participating in at least three sessions of resistance training per week for the previous year or more, as confirmed by the MHAQ. Participants were also required to be non-smokers, free from previous use of any performance-enhancing drugs, and free of any physical limitations, chronic diseases, or injuries, and deemed healthy (as determined by the MHAQ and PAR-Q+).

Procedures

Assessment of hydration status

In order to participate in the testing day assessments, participants were required to arrive euhydrated. To determine hydration status, each participant provided a urine sample in a container. Urine samples were assessed via refractometry by placing a small drop of urine on a digital refractometer (Human Urine Refractometer, MISCO Refractometer, Cleveland, OH, USA). Participants were required to have a urine specific gravity of ≤1.020 to continue with the testing day procedures.

Anthropometric and body composition assessments

Participants removed their footwear, socks, jewelry, and removed all loose clothing before anthropometric and body composition assessment. Body mass and height were measured using a Health-O-Meter Professional scale (Patient Weighing Scale, Model 500 KL, Pelstar, Alsip, IL, USA) to the nearest 0.1 kg and 0.1 cm, respectively. Multi-frequency bioelectrical impedance analysis (BIA) (InBody770, InBody, Cerritos, CA, USA) was used to determine body composition (percentage of body fat), as previously described (33).

Ultrasound assessments

Before testing, all participants were instructed to wear shorts to the laboratory to avoid compression of the upper leg musculature and to expose the upper portion of the thigh. The ultrasound imaging techniques utilized in this investigation have been previously described (3,6,7,15,27,34,35). Briefly, participants were instructed to lay down on an examination table in the supine position with legs fully extended for 15 min (6,7,27,35). Then, each participant was instructed to lay on their non-dominant lateral recumbent side (determined via self-report) for ultrasound image capture of the VL muscle in the dominant leg. Participants’ legs were positioned stacked on top of one another, and a foam pad was placed between their ankles. A goniometer was used to position the knees of each participant at 10° of knee flexion. Upon attaining this positioning, ultrasound images of the VL in the dominant limb were captured.

Anatomical features of interest for determining the location of ultrasound image capture were identified, and ultrasound images were captured at 50% of the distance from the greater trochanter to the lateral border of the patella (6,21). To ensure consistent image capture, a semi-permanent marker was used to draw a line along the surface of the skin at the aforementioned location. An experienced ultrasound technician obtained ultrasound images using a B-mode, 12-MHz linear probe (General Electric LOGIQ e, Wauwatosa, WI, USA), which was coated with transmission gel (AquasonicVR 100, Parker Laboratories, Fairfield, NJ, USA) to provide acoustic contact without depressing the dermal layer of the skin (6,7). Ultrasound settings remained fixed for each participant (gain = 50 dB; dynamic range = 72; depth = 5 cm) to minimize instrumentation bias, to optimize spatial resolution, and to ensure EI consistency. Three consecutive still images were captured with the probe oriented in the sagittal plane, parallel to the long axis of the VL (35). The same experienced ultrasound technician completed all ultrasound images and image analysis.

Ultrasound images were analyzed offline using an image analysis software (ImageJ, National Institutes of Health, USA, version 1.52p). A known distance in each ultrasound image was used to calibrate the image analysis software. Raw EI, muscle thickness (MT), and subcutaneous adipose tissue thickness (SAT) were assessed in the still images using the following procedures (32,35):

EI: In each image, the outline of the VL muscle was identified and traced using the polygon function tool, including as much of the VL muscle as possible without including surrounding connective tissue, bone, SAT, or fascia (7). The vertical borders of the muscle were limited by the size of the probe, so the left and right sides of the polygon consisted of perfectly vertical lines that aligned with the edges of the image, whereas the superficial and deep sides of the polygon corresponded to the muscle-aponeurosis interfaces (35). EI of the traced polygon (EI_FULL) was determined using the brightness standard histogram function in the image analysis software. The standard histogram function allows for quantification of the grayscale of each individual pixel in the region of interest (ROI), and values were expressed as a number in the range of 0–255 AU (0 = black; 255 = white) (6,7,10). The grayscale values for each individual pixel were projected on a histogram plot, and EI was quantified as the mean of all grayscale values (Fig. 1a).

Fig. 1.

An example of a still ultrasound image of the VL in the longitudinal plane. (a) EI was determined by manually tracing the border of the VL, excluding the surrounding fascia using the polygon function in ImageJ software (National Institutes of Health, Bethesda, MD, USA). An example of the corresponding grayscale histogram is provided. (b) MT was measured as the perpendicular distance between the deep border of the superficial aponeurosis and the superficial border of the deep aponeurosis. (c) SAT was measured as the perpendicular distance between the superficial border of the superficial aponeurosis and the deep border of the epithelium and was determined from the average of the left, mid-line, and right SAT values. (d) To examine EI heterogeneity, the VL in each image was divided into two compartments of equal vertical depth. The MT value was divided into equal halves, and the line tool was used to demarcate the superficial (SUPF) and deep (DEEP) portions of the muscle. EI of each compartment was quantified. (e) The perpendicular distance from the superficial border of the epithelium (i.e. top of the image) to the deep border of the superficial aponeurosis (DIS_SUPF) and superficial border of the deep aponeurosis (DIS_DEEP) of the VL were measured using the line tool. EI, echo intensity; MT, muscle thickness; SAT, subcutaneous adipose tissue thickness; VL, vastus lateralis.

MT: MT is defined as the perpendicular distance from the deep border of the superficial aponeurosis to the superficial border of the deep aponeurosis and was quantified using the straight-line tool in ImageJ at 50% of the horizontal distance of the image length (7) (Fig. 1b).

SAT: SAT was determined as the perpendicular distance between the superficial border of the superficial aponeurosis and the deep border of the epithelium (14). Quantification of SAT was determined as the average of three values: adjacent to the left, mid-line, and right portions of the image. SAT was quantified using the line tool in the image analysis software (Fig. 1c) (12,14).

To examine EI heterogeneity, the VL in each image was divided into two compartments of equal vertical length/depth. To determine the midpoint of the muscle, the MT value was divided into equal halves, and the line tool was used to demarcate the superficial (SUPF) and deep (DEEP) portions of the muscle (Fig. 1d). The EI of each compartment was then quantified using the polygon tool in ImageJ and methodology described above (EI_SUPF; EI_DEEP). The difference between EI_SUPF and EI_DEEP (EI_DIFF) was calculated as:

{EI}_{DIFF} = {EI}_{SUPF} {- EI}_{DEEP}

To determine the influence of tissue depth on EI, the perpendicular distance from the superficial border of the epithelium (i.e. top of the image) to the deep border of the superficial aponeurosis (DIS_SUPF) and superficial border of the deep aponeurosis (DIS_DEEP) of the VL were measured using the line tool in ImageJ (Fig. 1e).

The average values (of each of the three images) for each variable were used for further analysis. Inter-day reliability for the sonographer in the quantification of EI_FULL, MT, and SAT of the VL after 15 min of rest in the supine position have been previously reported (32,35).

Statistical analyses

Precision and reliability values for EI_FULL, EI_SUPF, EI_DEEP, EI_DIFF, MT, SAT, DIS_SUPF, and DIS_DEEP between the three images captured were calculated using the coefficient of variation (CV), intraclass correlation coefficient model “3,1” (ICC_3,1), standard error of measurement (SEM), and minimal difference (MD). Before statistical analysis, data were assessed for normality and sphericity. If the assumption of sphericity was violated, a Greenhouse-Geisser correction was applied. Mean differences between EI_FULL, EI_SUPF, and EI_DEEP were analyzed using a repeated-measures analysis of variance (ANOVA). In the event of a significant main effect, Bonferroni adjusted post-hoc tests were used for pairwise comparisons. Muscle depth effects were further analyzed using partial eta squared ( $η_{p}^{2}$ ). Interpretations of η_p² were evaluated in accordance with Cohen (36) at the following levels: small = 0.01–0.058; medium = 0.059–0.137; and large = >0.138. Comparisons of EI between sections were further analyzed using 95% confidence intervals (CI) and Cohen’s d. Magnitudes of the standardized effects were interpreted at thresholds corresponding to: very small = <0.01; small = 0.2; medium = 0.5; large = 0.8; very large = 1.2; and huge = 2.0 (37).

To determine the relationship between muscle depth and EI, associations between muscle morphological characteristics were examined using Pearson’s r. Correlation magnitudes were quantified using the following descriptors: trivial = 0.00–0.10; small = 0.11–0.30; moderate = 0.31–0.50; large = 0.51–0.70; very large = 0.71–0.90; and almost perfect = 0.91–1.00 (38). Statistical software (Statistical Package for the Social Sciences [SPSS] V.26.0, Chicago, IL, USA) was used for all analyses. Significance was set at P ≤ 0.05. All data are reported as mean ± standard deviation, unless otherwise noted.

Results

Characteristics of participants

Thirty-three participants were included in the analysis (age = 23.1 ± 2.1 years; height = 1.79 ± 0.08 m; body mass = 88.1 ± 13.2 kg; body fat percentage = 18.3 ± 5.7%), as one participant did not complete all of the required testing procedures and ultrasound images from another participant were removed from the analysis because the VL muscle could not fit into the still image at a depth of 5 cm.

Ultrasound assessments

A majority of ultrasound morphological variables exhibited normality; therefore, comparisons of the mean difference in EI between regions and relationships between morphological variables were assessed using parametric analyses.

Precision and reliability values for ultrasound variables are listed in Table 1.

Table 1.

Reliability and precision values for ultrasound variables.

	ICC_3,1	CV	SEM	MD
EI_FULL	0.939	6.043%	2.742 AU	7.600 AU
EI_SUPF	0.925	5.412%	2.870 AU	7.956 AU
EI_DEEP	0.944	8.059%	3.123 AU	8.658 AU
EI_DIFF	0.924	*	2.397 AU	6.645 AU
MT	0.987	1.910%	0.048 cm	0.134 cm
SAT	0.994	5.256%	0.032 cm	0.089 cm
DIS_SUPF	0.988	3.255%	0.044 cm	0.123 cm
DIS_DEEP	0.989	1.627%	0.059 cm	0.164 cm

*CV could not be calculated because of the inclusion of both positive and negative data points.

CV, coefficient of variation; DIS_DEEP, distance from the superficial border of the epithelium to the superficial border of the deep aponeurosis; DIS_SUPF, distance from the superficial border of the epithelium to the deep border of the superficial aponeurosis; EI_DEEP, echo intensity of the deep portion of the VL; EI_DIFF, difference between EI_SUPF and EI_DEEP; EI_FULL, echo intensity of the entire area of the VL; EI_SUPF, echo intensity of the superficial portion of the VL; ICC_3,1, intraclass correlation coefficient using model “3,1”; MD, minimal difference; MT, muscle thickness; SAT, subcutaneous adipose tissue thickness; SEM, standard error of measurement; VL, vastus lateralis.

A significant main effect was observed for EI (F_{2, 64} = 47.844, η_p² = 0.599, P < 0.001). EI_SUPF (52.88 ± 10.19 AU) was significantly greater than EI_FULL (47.72 ± 10.87 AU; P < 0.001; d = 1.22, very large; 95% CI = 3.29–7.02 AU) and EI_DEEP (42.75 ± 12.98 AU; P < 0.001; d = 1.21, very large; 95% CI = 6.43–13.83 AU). EI_FULL was significantly greater than EI_DEEP (P < 0.001; d = 1.19, large; 95% CI = 3.14–6.82 AU) (Fig. 2).

Fig. 2.

Comparison of EI values in the superficial (EI_SUPF) and deep (EI_DEEP) portions of the VL, as well as the overall (EI_FULL) VL. Dots represent individual data points. Lines and error bars represent the mean and standard deviation of the sample. *P < 0.001. EI, echo intensity; VL, vastus lateralis.

Associations between muscle morphological characteristics are presented in Table 2. EI_FULL was significantly correlated with both EI_SUPF and EI_DEEP, and EI_SUPF was correlated with EI_DEEP (all P < 0.001). EI_DIFF was significantly negatively correlated with EI_FULL (P = 0.042) and EI_DEEP (P < 0.001) but was not significantly associated with EI_SUPF (P = 0.846). MT was significantly negatively correlated with all raw EI measures (EI_FULL [P < 0.001], EI_SUPF [P = 0.044], and EI_DEEP [P < 0.001]). DIS_DEEP was significantly negatively correlated with EI_DEEP (P = 0.014), but was not significantly correlated with EI_SUPF (P = 0.701) or EI_FULL (P = 0.096). EI_DIFF was significantly positively correlated with MT (P < 0.001) and DIS_DEEP (P < 0.001). SAT was not significantly associated with any EI measure.

Table 2.

Relationships between muscle morphological characteristics.

	EI_SUPF	EI_DEEP	EI_DIFF	MT	SAT	DIS_SUPF	DIS_DEEP
EI_FULL	0.921	0.954	−0.356	−0.590	0.183	0.205	−0.295
	<0.001*	<0.001*	0.042^†	<0.001*	0.309	0.253	0.096
EI_SUPF		0.762	0.035	−0.352	0.257	0.274	−0.069
		<0.001*	0.846	0.044^†	0.149	0.123	0.701
EI_DEEP			−0.620<0.001*	−0.709<0.001*	0.1250.488	0.1500.406	−0.4230.014^†
EI_DIFF				0.668<0.001*	0.1180.512	0.1010.577	0.568<0.001*
MT					−0.0150.933	−0.0520.774	0.703<0.001*
SAT						0.996<0.001*	0.697<0.001*
DIS_SUPF							0.673<0.001*

Data is presented as Pearson’s r values with P values underneath.

*P < 0.001.

^†P < 0.05.

DIS_DEEP, perpendicular distance from the epithelium to the superficial border of the deep aponeurosis; DIS_SUPF, perpendicular distance from the epithelium to the deep border of the superficial aponeurosis; EI, echo intensity; EI_DEEP, EI of the deep half of the VL; EI_DIFF, difference between EI_SUPF and EI_DEEP; EI_FULL, EI of the entire VL muscle in the still ultrasound image; EI_SUPF, EI of the superficial half of the VL; MT, muscle thickness of the VL; SAT, subcutaneous adipose tissue thickness adjacent to the VL; VL, vastus lateralis.

Discussion

The primary findings of this investigation suggest that EI of the VL differs based on tissue depth. EI values were lower in the deep portion (EI_DEEP) compared to the superficial portion (EI_SUPF) of the muscle, although EI values at different depths were all significantly correlated with one another. EI_DIFF was positively correlated with MT and DIS_DEEP, indicating that the difference in EI values between the deep and superficial portions increased as tissue thickness and maximal tissue distance from the ultrasound probe increased. Furthermore, EI_FULL was significantly negatively correlated with MT, indicating that thicker muscles tended to appear darker in color.

This investigation demonstrates that EI values within ultrasound images of the VL are heterogeneous, as the deeper portion of the muscle produces lower values than the superficial portion (very large effect size). These findings are consistent with the notion that the absorption or reflection of ultrasound waves by superficial tissues results in an attenuation of the ultrasound beam, which limits the visualization of deeper structures and causes them to appear darker in color (10,30). In alignment with our findings, previous research has reported lower EI in the deeper knee extensor muscles (ex: vastus intermedius) compared to the superficial muscles (ex: rectus femoris, vastus lateralis) in young individuals (26,39). In addition, Li et al. (40) reported significantly lower EI in the deeper forearm flexor muscles compared to the superficial muscles in young participants. To our knowledge, only one other investigation has examined EI variability between superficial and deep regions of a muscle within an ultrasound image (25); however, in contrast to our findings, Caresio et al. (25) observed greater EI in the deeper portion of the tibialis anterior than the superficial portion. Different muscle fiber arrangements between the VL (unipennate muscle) and the tibialis anterior (circumpennate muscle) may explain these opposing results, as EI heterogeneity within an individual image may be influenced by muscle architecture, independent of muscle depth (25,27). The present study also examined larger ROIs within the image of the VL than Caresio et al. (25) did in the tibialis anterior, and EI reliability improves when larger regions are examined (25,41). Notably, the values for EI_DEEP were less than EI_FULL, and both were less than EI_SUPF in our study, whereas Caresio et al. reported lower EI of both the superficial and deep portions than EI of the full muscle, indicating that regions of the muscle with higher EI were not included in either the superficial or deep regions selected by Caresio et al. (25). Although EI_SUPF, EI_DEEP, and EI_FULL measures were significantly correlated with one another in the present study, they were all significantly different, indicating that the size and location of the ROI may have profound impacts on EI. Discrepancies between studies may also be a result of different scanning planes used, as we examined the VL in the longitudinal plane, whereas Caresio et al. (25) examined the tibialis anterior in the transverse plane. Although EI values obtained in longitudinal and transverse ultrasound images are strongly related, they are not interchangeable, as each result in visualization of different intramuscular structures (35). The orientation of the probe in the longitudinal plane in the present study may have resulted in greater reflections in the superficial portion of the muscle due to hyperechoic fascia and connective tissue striations between fascicles, reducing the strength of the waves penetrating the deeper portion of the muscle and producing darker deep potion.

Although intramuscular EI variability may be due to regional differences in fiber architecture or composition (i.e. contractile tissue, glycogen, intramuscular adipose tissue, fibrous tissue, collagen, and connective tissue content) (10,26,42,43), we observed that EI_FULL was negatively correlated with MT, indicating that thicker VL muscles appear darker. These findings align with other studies reporting negative correlations between MT and EI (9,13,26,35,44,45). As unaccustomed bouts of resistance training often result in concurrent increases in muscle quality (i.e. decreased intramuscular fat and connective tissue, decreased EI) and hypertrophy (i.e. increased MT) (6,46,47), it is possible that the inverse relationship between MT and EI may have been facilitated by training-induced adaptations. Nevertheless, we report that the difference in EI between the deep and superficial portions of the VL (EI_DIFF) is amplified with increasing MT, demonstrating that thicker muscles have greater disparities in EI between the deep and superficial portions, despite having lower EI values overall. These results indicate that the attenuation of ultrasound waves in the deeper portion of the muscle may contribute to lower EI in thicker muscles. Thus, it is possible that improvements in EI secondary to resistance training programs are largely a result of increased MT; however, future research in this area is warranted.

Despite significant negative relationships between MT and EI, we observed no significant correlations between SAT and EI. Studies using computed tomography and magnetic resonance imaging demonstrate that increasing adiposity is related to the accumulation of intramuscular fat and connective tissue suggestive of decreased muscle quality (48 –50); thus, it may be expected that increases in SAT mirror increases in EI. However, studies using ultrasonography show that raw EI values do not accurately predict body composition (35,44,51 –53), likely because of the influence of increasing SAT on the attenuation of ultrasound waves (14). Young et al. (14) demonstrated that raw EI values increase when the SAT adjacent to the muscle is compressed, and as a result of these findings, correcting for SAT in the examination of EI is now a common practice (12,26,31,32). Although SAT was not related to EI in the current study, DIS_DEEP was negatively correlated with EI_DEEP and positively correlated with EI_DIFF. Thus, muscles infiltrating deeper in the images as a result of large MT and/or SAT had darker deeper potions compared to muscles that were located more superficially. These findings demonstrate that the combination of MT and SAT should be taken into consideration when evaluating muscle quality, as MT appears to directly affect EI, and correcting for SAT does not fully account for differences in tissue depth. Although increasing SAT was associated with greater overall tissue depth (DIS_DEEP), our findings show that MT may have a larger effect on EI than SAT. Furthermore, the attenuation of the ultrasound beam appears to be more pronounced in deeper regions of the muscle, as DIS_DEEP was only significant associated with EI_DEEP but was not with other EI measures. Future research is necessary to determine appropriate methods for EI quantification after correcting for MT and SAT.

The primary aim of this investigation was attained, but several limitations should be acknowledged when interpreting its results. We recruited a relatively homogenous sample of participants; thus, these findings may be limited to healthy, young, resistance-trained males. We examined only the VL muscle in the dominant limb, and future research is necessary to determine if similar findings are observed in other muscles. Although ultrasound settings were standardized for all participants in the present study, our results may not be generalizable when using other ultrasound systems or settings. Paris et al. (54) recently reported that ultrasound imaging depth affects EI of the rectus femoris, as lower image resolution (i.e. greater depth) resulted in higher EI values. It is possible that our findings are a consequence of the relatively shallow imaging depth used, in combination with a high-frequency probe. Since high-frequency probes are most beneficial for examining superficial tissues (11), it is possible that the image quality of deeper tissues may have been compromised resulting in lower EI values. Future research is necessary to determine if similar findings are observed using other ultrasound systems and settings. Furthermore, the use of EI as a measure of muscle quality has been cautioned as EI seems to be influenced by a myriad of factors independent of muscle composition (24). Nevertheless, EI provides useful information about muscle that is absent from other ultrasound-derived measures of morphology. EI remains an important measure of muscle quality, as larger muscles do not necessarily indicate higher-quality muscles. This investigation supports the notion that EI is influenced by confounding factors; however, future research is necessary to determine ways to adjust EI to account for these variables, specifically MT and DIS_DEEP.

In conclusion, our data suggest that EI of the VL is heterogeneous based on tissue depth. The deeper portion of the muscle produced lower EI values than the superficial portion. EI and EI_DIFF paralleled increases in MT, indicating that thicker muscles tend to be darker in color overall but have greater discrepancies in EI between the superficial and deep portions of the muscle. Although SAT was not significantly correlated with EI, DIS_DEEP was significantly related to EI_DIFF, demonstrating that the combination of MT and SAT affects EI. Future research is necessary to determine how to account for both SAT and MT in EI quantification.

Footnotes

Author's note

Tal Belity is also affiliated with Department of Clinical Biochemistry and Pharmacology, Faculty of Health Sciences, Ben-Gurion University of the Negev, Beer-Sheva, Israel.

Declaration of conflicting interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) received no financial support for the research, authorship, and/or publication of this article.

ORCID iD

Alyssa N Varanoske

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