We aimed to provide an unbiased estimate of the confounding effect of subcutaneous fat thickness on ultrasound echo intensity (EI) measures of muscle quality. The effect of fat thickness on EI was verified for an approximate range of 0 to 3 cm of fat using exogeneous layers of pork fat over the human tibialis anterior muscle. Sonograms were obtained (i) with focus constant across fat thickness conditions, and (ii) with focus position adjusted to the muscle region of interest (ROI) position for each fat thickness level. In agreement with our hypothesis, increasing fat between the probe and the ROI resulted in a decrease in EI. This overestimating effect of fat on muscle quality differs between sonograms with constant focus and sonograms with focus position adjusted to the vertical displacement in ROI position that occurs for different levels of fat thickness. Correcting equations to account for the overestimating effect of fat on muscle quality are provided for both focus conditions. This is the first study to systematically analyze the confounding effect of fat thickness as an independent factor and the provided equations can be used for improved accuracy in estimates of muscle quality in obese/overweight subjects/patients. Novelty: The independent confounding effect of subcutaneous fat thickness on ultrasound (US) estimates of muscle quality was quantified. US estimates of muscle quality depend on whether focus is adjusted to the muscle region of interest or not. Equations for correcting muscle quality estimates are provided.

It is unclear if applying larger or more symmetrical pedal forces leads to better performance in cycling. The aims of this study were to assess the relationship between pedal force production and performance in a cycling time trial and to evaluate the relationship between asymmetries in pedal force production and performance. Fifteen competitive cyclists/triathletes performed a 20 km cycling time trial on a cycle trainer while bilateral forces applied to the pedals were recorded along with total time. Total forces applied to the pedals were computed and converted into dominant and non-dominant forces using a leg preference inventory. Pedal force asymmetries ranged from 43% (in favour of the dominant limb) to 34% (in favour of the non-dominant limb). The relationship between total pedal force (averaged from both pedals) and performance time was small (r=-.32, effect size=.66) as well as the association between the asymmetry indices and performance time (r=.01, effect size=.06). In conclusion, applying large forces on the pedals and balancing pedal force application between the dominant and non-dominant limbs did not lead to better performance in this cycling time trial.

Lanferdini, FJ, Manganelli, BF, Lopez, P, Klein, KD, Cadore, EL, and Vaz, MA. Echo intensity reliability for the analysis of different muscle areas in athletes. J Strength Cond Res 33(12): 3353–3360, 2019—Skeletal muscles' echo intensity (EI) is used as a parameter to evaluate muscle damage and muscle quality after exercise or training. However, recent muscle EI studies have used regions of interest (ROIs) of different sizes for assessing muscle damage and muscle quality, which may lead to different results if the different ROIs from the same muscle are not reliable. Although a maximum rectangular ROI (RET-ROI), included in the muscles' anatomical cross-sectional area, can be used to represent the maximum muscle ROI (MAX-ROI), no studies were found that investigated the reliability of the evaluations of different ROIs for the EI of superficial vs. deep muscles of the thigh. In addition, no studies have evaluated different ROIs in cyclists, at different days and analyzed by different raters. The aim of this study was to evaluate the EI reliability of rectus femoris (RF) and vastus intermedius (VI) muscles of cyclists. Twenty cyclists visited the laboratory 4 times for the evaluation of RF and VI muscles transversal ultrasound images. Echo intensity was determined from grayscale mean values by 2 examiners who performed the analysis with 3 different ROIs: MAX-ROI, RET-ROI, and 1-cm² ROI (1CM-ROI). The between-ROI EI data reliability showed a strong correlation in both RF (r ≥ 0.79) and VI (r ≥ 0.87) muscles. Bland-Altman tests demonstrated high agreement among RF ROI muscle areas (p > 0.05), with no agreement between the VI areas (p < 0.05). Only the RF muscle MAX-ROI, RET-ROI, and 1CM-ROI areas are similar for EI analysis, with no similarities for the same VI muscle areas.

Purpose: This study aimed to determine whether triceps surae’s muscle architecture and Achilles tendon parameters are related to running metabolic cost (C) in trained long-distance runners.Methods: Seventeen trained male recreational long-distance runners (mean age = 34 years) participated in this study. C was measured during submaximal steady-state running (5 min) at 12 and 16 km h^–1 on a treadmill. Ultrasound was used to determine the gastrocnemius medialis (GM), gastrocnemius lateralis (GL), and soleus (SO) muscle architecture, including fascicle length (FL) and pennation angle (PA), and the Achilles tendon cross-sectional area (CSA), resting length and elongation as a function of plantar flexion torque during maximal voluntary plantar flexion. Achilles tendon mechanical (force, elongation, and stiffness) and material (stress, strain, and Young’s modulus) properties were determined. Stepwise multiple linear regressions were used to determine the relationship between independent variables (tendon resting length, CSA, force, elongation, stiffness, stress, strain, Young’s modulus, and FL and PA of triceps surae muscles) and C (J kg^–1m^–1) at 12 and 16 km h^–1.Results: SO PA and Achilles tendon CSA were negatively associated with C (r² = 0.69; p < 0.001) at 12 km h^–1, whereas SO PA was negatively and Achilles tendon stress was positively associated with C (r² = 0.63; p = 0.001) at 16 km h^–1, respectively. Our results presented a small power, and the multiple linear regression’s cause-effect relation was limited due to the low sample size.Conclusion: For a given muscle length, greater SO PA, probably related to short muscle fibers and to a large physiological cross-sectional area, may be beneficial to C. Larger Achilles tendon CSA may determine a better force distribution per tendon area, thereby reducing tendon stress and C at submaximal speeds (12 and 16 km h^–1). Furthermore, Achilles tendon morphological and mechanical properties (CSA, stress, and Young’s modulus) and triceps surae muscle architecture (GM PA, GM FL, SO PA, and SO FL) presented large correlations with C.

Purpose: The aim of this study was to verify whether physiological components [vertical jumps (Squat Jump – SJ and Countermovement Jump – CMJ), eccentric utilization ratio (EUR) of vertical jumps, running economy (RE), metabolic cost (C_MET), first and second ventilatory threshold (VT₁ and VT₂) maximal oxygen uptake (VO_2MAX)] can predict maximal endurance running performance. Methods: Twenty male runners performed maximal vertical jumps, submaximal running at constant speeds, and maximal incremental running test. Before, we measured anthropometric parameters (body mass and height) and registered the training history and volume. SJ and CMJ tests were evaluated prior to running tests. Initially, the oxygen uptake (VO₂) was collected at rest in the orthostatic position for 6 min. Soon after, a 10-min warm-up was performed on the treadmill at 10 km⋅h^–1, followed by two 5-min treadmill rectangular tests at 12 and 16 km⋅h^–1 monitored by a gas analyzer. After that, the runners performed a maximal incremental test, where the VT₁, VT₂, and VO_2MAX were evaluated, as well as the maximum running speed (vVO_2MAX). Thus, RE and C_MET were calculated with data obtained during rectangular running tests. Multivariate stepwise regression analyses were conducted to measure the relationship between independent variables (height and power of SJ and CMJ, EUR; RE and C_MET 12 and 16 km⋅h^–1_; VT₁, VT₂, and VO_2MAX), as predictors of maximal running performance (vVO_2MAX), with significance level at α = 0.05. Results: We found that VO_2MAX and RE at 16 km⋅h^–1 predict 81% of performance (vVO_2MAX) of endurance runners (p < 0.001). Conclusion: The main predictors of the maximal incremental running test performance were VO_2MAX and RE.