Musculotendinous structure as a functional unit (i.e., muscle–tendon unit [MTU]) of the lower limbs usually shortens immediately after being lengthened in human movements, such as running and jumping. This combination of lengthening and shortening actions is called the stretch-shortening cycle (SSC). It is well known that the storage and the subsequent release of elastic energy in the SSC enhance the mechanical efficiency and power output of the MTU (1,2), and thus the performance in the SSC can be influenced by the MTU elasticity. The MTU elasticity in SSC exercises is suggested to depend on neuromuscular factors and intrinsic stiffness of MTU (3). Regarding the latter, to date, much attention has been paid to the functional roles of the MTU and tendon stiffness of knee extensors (e.g., the vastus lateralis [VL]) and plantar flexors (e.g., the medial gastrocnemius) in sprinting and running (4–6). In contrast, it is unclear whether and how muscle stiffness plays a role in SSC exercises, such as running and sprinting. An advanced understanding of the role of muscle stiffness in sprint and running can provide us with a basis for developing more effective training programs.
Muscle stiffness is dependent on the fiber type composition of the muscle. Animal studies have shown that type I muscle fibers are stiffer than type II fibers under passive (resting) (7,8) and active (contracting) (9,10) conditions. Compared with untrained individuals, the VL of sprinters shows a high percentage of type II fibers, whereas the VL of long-distance runners is composed of a high percentage of type I fibers (11–13). Therefore, it can be expected that the VL of sprinters and long-distance runners exhibit remarkably different stiffness under both passive and active conditions; compliant and stiff for sprinters and long-distance runners, respectively. On the other hand, trained endurance athletes have an enhanced store of fat (lipids) in the VL (14), and thereby their endurance performance can be improved through increased oxidative energy metabolism. Fat tissues are more compliant than muscles (15). Taking these findings together, it is unclear whether the VL of trained long-distance runners is stiffer than those of sprinters and untrained individuals, and to what extent the VL muscle stiffness is related to the performance of these athletes.
Previously, in vivo human muscle (not MTU) stiffness under passive and active conditions has been studied using the alpha method (16,17) or with B-mode ultrasonography (18). However, careful attention should be paid when interpreting muscle stiffness assessed using these methods. For example, tissues other than muscles and tendons of interest are not taken into consideration in the two methods. Additionally, in theory, muscle size strongly influences the stiffness of the assessed muscle. Thus, techniques that address these concerns should be considered (19). Alternatively, ultrasound shear wave elastography (SWE) is a noninvasive technique that can be used to quantify the stiffness of individual muscles under passive and active conditions. Briefly, SWE generates shear waves using focused pushing beams (i.e., acoustic radiation force) within the tissue and then measures the shear wave propagation speed using ultrafast ultrasound imaging. Shear wave speed can be used as a noninvasive proxy for tissue stiffness because of its relation to the elastic moduli, such as Young’s modulus and shear modulus, that is, the stiffer the tissue, the faster the shear wave propagates (20).
Taking advantage of SWE, we firstly compared the VL muscle stiffness between sprinters, long-distance runners, and untrained individuals. We hypothesized that the muscles of sprinters are compliant under both passive and active conditions, whereas the muscles of long-distance runners are stiffer during contraction but not at rest. The latter is because the relatively high intramuscular fat concentration in lower-limb muscles of long-distance runners would mask a potential effect of muscle fiber type composition under passive conditions, whereas under active conditions the effect of intramuscular fat would be minimal or negligible because muscles during contraction are far stiffer than those at rest. The second aim was to determine how muscle stiffness is associated with the athletic performance of sprinters and long-distance runners. Due to the nonrigidity of the tendon, elastic energy can be stored when the MTU is lengthened. In this way, the MTU performance can be enhanced in SSC exercises (1,21,22). From a mechanical point of view, stiffer muscles would be more favorable to effectively use the tendon elasticity (i.e., to store more elastic energy) in SSC exercises, regardless of sprinting or running because the tendon is much stiffer than the muscle (23). Therefore, we hypothesized that muscle shear wave speed, at least under active conditions, is positively associated with sprinting/running performance in both sprinters and long-distance runners.
METHODS
Subjects
This study included 22 male sprinters (SPR group), 22 male long-distance runners (LDR group), and 19 healthy untrained control male subjects (CON group) as participants. The necessary sample size was calculated in advance using the data of our preliminary results (n = 6 in each group; total = 18). A priori power analysis with an assumed type 1 error of 0.05 and a statistical power of 0.80 was conducted to find statistically significant differences in VL shear wave speed under passive and active conditions between the groups and to find a statistically significant correlation between VL shear wave speed and sprint or running performance in the SPR and LDR groups, respectively. The critical sample sizes were estimated to be at least 16. Thus, approximately 20 subjects were recruited to account for possible attrition in each group. The inclusion criteria for the SPR and LDR groups were (i) current participation in competitive 100- or 5000-m races and (ii) at least 3 yr of continuous sprint or running training. The best time of official 100- and 5000-m races within 3 months from the experiment ranged from 10.66 to 11.58 s (11.07 ± 0.29 s) for the SPR group and from 854.8 to 939.9 s (893.9 ± 24.1 s) for the LDR group. According to International Association of Athletics Federation Scoring Tables of Athletics, there was no significant difference in performance level between the SPR and LDR groups. None of the subjects had a recent history (within the last 6 months) of lower-limb musculoskeletal injuries or joint pain. All subjects provided written informed consent before participation. This study was approved by the ethics committee of National Institute of Fitness and Sports in Kanoya (H29-8-28) and performed in accordance with the Declaration of Helsinki.
Experimental Setup and SWE Measurement
The subjects were seated on a dynamometer (Biodex System 4; Biodex Medical System, USA) with the hip and knee flexed at 80° and 90° (anatomical position = 0°), respectively. They were tightly secured to the seat of the dynamometer with nonelastic straps, and the lever arm of the dynamometer was attached 3 to 4 cm above the lateral malleolus of the right leg. The rotation axis of the knee was aligned with the axis of the motor. The shear wave speed of the VL was measured using an ultrasound SWE scanner (Aixplorer; Supersonic Imagine, France), coupled with a linear array probe, in “SWE” mode (musculoskeletal preset, persistence = off, smoothing = 5). For VL shear wave speed measurements, the ultrasound probe was positioned at 50% level of the thigh length (measured from the greater trochanter to the popliteal crease). First, the shear wave speed of the passive VL was measured. The subjects were instructed to completely relax their leg throughout the measurements. Then, after a warm-up consisting of several submaximal and maximal voluntary isometric contractions (MVC) of the knee extensors, each subject performed two or three MVC at 90° knee angle. The highest torque was used to determine the target torque level (i.e., 50% MVC) during shear wave speed measurement of the active VL. The relative torque level (% MVC) rather than the absolute torque (N·m) was used so that the active VL shear wave speed could be measured under conditions in which the muscle contraction intensity was the same across all subjects regardless of the muscle size. The contraction intensity of 50% MVC was chosen according to the results of our preliminary experiments, which aimed to define the maximal contraction intensity that can be developed without saturation of SWE measurement (i.e., 16.3 m·s−1) for all subjects. The subjects maintained 50% MVC torque for approximately 7 to 8 s. A line representing the target level was displayed on a computer screen along with the actual torque output, which ensured real-time feedback on the contraction intensity. Two trials were performed in both passive and active conditions, respectively. In each trial, SWE measurements were performed three times (i.e., three images were acquired). The images were acquired after ensuring that the color map (Fig. 1) was stable for a few seconds. Throughout the scanning, care was taken not to press and deform the muscle. The mean shear wave speed (expressed in meters per second) was calculated over the largest region of interest (ROI) from which we excluded the aponeurosis and subcutaneous adipose tissues while referring the B-mode images. The values of three measurements in each trial were averaged, and the average of the two trials was used for further analyses. All measurements and analyses of SWE data were performed by experienced examiners (>4 yr of practice). The coefficients of variation (CV) were 1.8% ± 1.9% and 4.5% ± 3.3%, with an intraclass correlation coefficient of 0.987 (P < 0.001) and 0.924 (P < 0.001) for shear wave speed in passive and active conditions, respectively.
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FIGURE 1: Typical examples of ultrasound SWE measurements of the VL at rest (left) and during knee extension at 50% MVC (right). The colored region represents the shear wave speed map with the scale below the images. The rectangle drawn in solid black is the region of interest for the determination of shear wave speed.
Echo intensity measurement
To evaluate the relative amount of contractile (and noncontractile) materials within the VL (24), the echo intensity of the ultrasound image was assessed. Transverse B-mode images of the VL at 90° knee angle were obtained using the same ultrasound device (in “B” mode) and probe as the SWE measurement. The probe was positioned perpendicular to the longitudinal axis of the VL at 50% level of the thigh length. Gain and depth were adjusted to 80% and 5 cm, respectively. Focus area was increased to maximum. These settings were kept consistent across all subjects. Other ultrasound settings were unchanged from the preset. A generous amount of water-soluble gel was applied between the skin and the probe to enhance ultrasound coupling and avoid deformation of the skin and subcutaneous tissues caused by excess compression. Three consecutive images were obtained. The B-mode images were analyzed using ImageJ software (National Institutes of Health, USA). Echo intensity was assessed using computer-aided gray-scale analysis with histogram function. For each image, an ROI that included as much of the VL as possible but avoided the surrounding fascia and aponeurosis was selected. The mean echo intensity of the selected ROI was expressed as a value between 0 (black) and 255 (white). The CV was 0.2% ± 0.3%, with an ICC of 1.000 (P < 0.001). The average of the three values was used for further analyses.
Statistics
The normality of the data was confirmed using the Kolmogorov–Smirnov test. For each parameter, a one-way ANOVA was used to compare the values between groups. When a significant main effect for a group was observed, the post hoc Bonferroni test was applied to determine statistical significance. Furthermore, an effect size was reported with a P value to determine the magnitude of the differences. Correlations between muscle shear wave speed and performance (i.e., season-best time of official 100- and 5000-m races for the SPR and LDR groups, respectively) were investigated using Pearson product–moment correlation. The level of significance was accepted at P < 0.05. All statistical analyses were performed with statistical software (SPSS Statistics 25; IBM Japan). Data are expressed as means and SD.
RESULTS
Table, Supplemental Digital Content 1 shows physical characteristics and maximal voluntary knee extension torque in three groups (https://links.lww.com/MSS/B604). Body height and weight were greater in the SPR group than in the LDR and CON groups, and were smaller in the LDR group than in the CON group. The knee extension MVC torque in the SPR group was significantly greater than that in the LDR group. The contraction intensity of the knee extensors (% MVC) during SWE measurements did not differ between the three groups (SPR, 49.5% ± 1.4% MVC; LDR, 50.0% ± 1.3% MVC; CON, 50.0% ± 1.5% MVC).
Figure 2 shows the passive and active VL shear wave speed in the three groups (SPR, 2.69 ± 0.30 m·s−1; LDR, 2.91 ± 0.21 m·s−1; CON, 2.93 ± 0.20 m·s−1 for passive condition; SPR, 10.63 ± 1.16 m·s−1; LDR, 11.15 ± 0.68 m·s−1; CON, 10.11 ± 0.98 m·s−1 for active condition). One-way ANOVA revealed a significant main effect of group for passive (P = 0.032, η2 = 0.012) and active (P < 0.001, η2 = 0. 091) VL shear wave speed. According to post hoc tests, the passive VL shear wave speed in the SPR group was significantly lower than that in the LDR group (P = 0.029, d = 0.87), and the active VL shear wave speed in the LDR group was significantly higher than that in the SPR (P = 0.010, d = 0.56) and CON (P < 0.001, d = 1.28) groups. Figure 3 shows the VL echo intensity. One-way ANOVA demonstrated a significant main effect of group (P < 0.001,η2 = 0.794). Post hoc tests revealed that the echo intensity in the SPR group was significantly lower than that in the LDR (P < 0.001, d = 1.74) and CON (P < 0.001, d = 1.71) groups.
FIGURE 2: Passive (A) and active (B) muscle shear wave speed of the VL in SPR, LDR, and CON. The values are mean ± SD. *Significant difference.
FIGURE 3: Muscle echo intensity of the VL in SPR, LDR, and CON. The values are mean ± SD. *Significant difference.
Table 1 shows the correlation coefficients between the passive VL shear wave speed, active VL shear wave speed, and VL echo intensity in the SPR, LDR, and CON groups, and in all subjects pooled (n = 63). A significantly positive correlation (r = 0.364, P = 0.003) was observed only between active VL shear wave speed and VL echo intensity in all subjects pooled, but not between any other pairs.
TABLE 1: Correlation coefficients between passive VL shear wave speed, active VL shear wave speed, and VL echo intensity in SPR, LDR, CON, and all subjects pooled.
In the SPR group, the 100-m race time was negatively correlated to the passive VL shear wave speed (r = −0.470, P = 0.027; Fig. 4), positively correlated to the active VL shear wave speed (r = 0.468, P = 0.028; Fig. 4), but not correlated to echo intensity (r = −0.303, P = 0.170). In the LDR group, the 5000-m race time was positively correlated to the passive VL shear wave speed (r = 0.423, P = 0.049; Fig. 5) but not correlated to the active VL shear wave speed (r = 0.237, P = 0.301; Fig. 5) or echo intensity (r = 0.102, P = 0.653).
FIGURE 4: Relationship between the 100-m race time and muscle shear wave speed of the passive (A) or active (B) VL in sprinters.
FIGURE 5: Relationship between the 5000-m race time and muscle shear wave speed of the passive (A) or active (B) VL in LDR.
DISCUSSION
We found, using ultrasound SWE, that both passive and active VL shear wave speeds are high in long-distance runners and low in sprinters. This is partly in agreement with our first hypothesis, although significant differences between the CON group and the SPR or LDR group were not always observed. With respect to the association with performance, we found that high passive VL shear wave speed is associated with superior sprint performance but with inferior long-distance running performance, and that high active VL shear wave speed is associated with inferior sprint performance but is not associated with running performance. These findings, especially the latter, are contrary to our second hypothesis. These results have implications for how the stiffness of leg muscles plays a functional role in human locomotion at various speeds.
Between-group difference in muscle stiffness
Type I muscle fibers are reported to be stiffer than type II fibers under both passive (7,8) and active (9,10) conditions. Although the VL muscle fiber composition was not experimentally tested in the present study, it is likely that the VL of the LDR and SPR groups contains a relatively higher percentage of type I and II muscle fibers, respectively, as previously demonstrated for the VL (11–13). This between-group difference in muscle fiber type composition might be involved in the difference in VL shear wave speed observed in the present study. On the other hand, although muscles are composed primarily of contractile materials, there is a growing body of evidence indicating that noncontractile connective tissues (consisting mainly of collagen) such as perimysium and epimysium strongly affect muscle stiffness under passive conditions (25,26). Thus, the differences in passive muscle stiffness between the SPR and LDR groups obtained in the present study might be due primarily to the amount of noncontractile connective tissues depending on the muscle fiber type composition rather than the muscle fiber type per se.
In the present study, the muscle echo intensity of the VL was higher in the LDR group than in the SPR group (Fig. 3). As enhanced muscle echo intensity is reported to be associated with increasing intramuscular fat (27), the present result is in line with previous findings indicating that the concentration of intramuscular fat is higher in leg muscles of trained endurance athletes than in untrained individuals (14) and sprinters (28). However, considering that fat is more compliant than muscle (15), the result on muscle echo intensity seems to be discrepant with the present finding that passive muscle shear wave speed was higher in the LDR group than in the SPR group (Fig. 2A). This might be due to the effect of tissues other than intramuscular fat on the muscle echo intensity and the passive muscle shear wave speed. Higher values of muscle echo intensity also represent more intramuscular connective tissues and less contractile material (29). Mechanical stress induced by cyclic strain influences the mechanical properties of collagenous tissues (30). Additionally, it has been suggested that the number rather than the intensity of SSC is important for the adaptation of the mechanical properties of muscles and tendons (31,32). Thus, it is reasonably likely that the concentration of intramuscular connective tissue within the VL is higher in long-distance runners, who habitually experience a large number of SSC during running, than in untrained individuals and sprinters. Considering these together with the present result, although the VL of long-distance runners contains relatively higher amounts of both connective tissue with high stiffness and fat with low stiffness, the effect of intramuscular fat concentration on passive muscle shear wave speed would be small.
The active VL shear wave speed (although submaximal at 50% MVC level) and its variation between groups were more than 10 times higher than the passive VL shear wave speed. Additionally, there were no significant correlations between passive and active VL shear wave speed for any of the three groups, either individually or for the whole population. These results indicate that tissues other than the aforementioned connective tissue and fat, specifically attached cross-bridges, should be primarily involved to determine the active VL shear wave speed. Thus, it can be presumed that the variation in muscle fiber type composition strongly contributed to the variation in the active VL shear wave speed between the groups. It is well known that, when an active muscle/muscle fiber is stretched, the force it exerts is enhanced above the isometric force at the corresponding length. Studies with in situ muscles (33) and single-skinned fibers (34) have compared force responses in short-range stretch experiments between fast and slow muscles/muscle fibers. They have shown a greater increase in force in slow muscles than in fast muscles, meaning that slow muscles/muscle fibers are stiffer than fast muscles/muscle fibers. The increased stiffness in slow muscles would be due to the slower cross-bridge kinetics (10,35). Not all muscle fibers were recruited at the moderate contraction intensity used in the present study (i.e., 50% MVC). Thus, it is likely that slow muscle fibers were primarily recruited in the LDR group, whereas fast and slow fibers were recruited in the SPR group because the VL of the LDR group contains a higher percentage of slow fibers (11–13). Such a difference in the muscle fiber type recruited between the SPR and LDR groups should not disappear at a higher contraction intensity (e.g., 80% MVC or more). Therefore, the between-group difference in the active VL shear wave speed observed in the present study would be found even if the VL shear wave speed is measured at a higher contraction intensity. In contrast, when the active VL shear wave speed is measured at a lower contraction intensity (e.g., 20% MVC), the between-group difference might not be observed as only slow fibers should be activated for all groups regardless of the muscle fiber type composition. We confirmed these speculations in an additional experiment (n = 3). The active VL shear wave speed overall linearly increased with increasing isometric knee extension torque (although the contraction intensity was limited up to 68%, 82%, and 96% MVC for each subject, respectively). There were apparent between-subject differences in active VL shear wave speed at moderate- to high-intensity contractions but not at low-intensity contractions (<30% MVC) (see Figure, Supplemental Digital Content 2, relationship between VL shear wave speed and knee extension torque level obtained from the three subjects, https://links.lww.com/MSS/B605). This quasilinear relationship was previously reported for other muscles such as the abductor digiti minimi (36). Taken together, it can be concluded that the between-group difference in the active VL shear wave speed is observed even when the active VL shear wave speed is measured at 100% MVC. Unfortunately, however, the VL shear wave speed data at 100% MVC are not available because of the upper limit of measurement range of the elastography scanner used in the present study as mentioned above. Further studies are required to systematically clarify the effect of contraction intensity on the between-group difference in active muscle shear wave speed.
Relationship between muscle stiffness and sprint/running performance
We found that higher passive muscle shear wave speed was weakly to moderately, but significantly, related to superior sprint performance (seasonal best time of official 100-m races). This finding is in line with a recent study reporting a negative correlation in sprinters between passive ankle joint stiffness during dorsiflexion and the 100-m race time (37), and further corroborates the importance of the passive musculoskeletal flexibility in sprinting. High passive muscle stiffness can help in quickly repositioning the limb during the aerial (swing) phase in fast locomotion (i.e., sprinting), as can be observed in hopping toads (38). In contrast to the SPR group, in the LDR group, higher passive muscle stiffness was related to inferior long-distance running performance. Low passive muscle stiffness can reduce the metabolic energy cost during antagonist contraction (i.e., while knee flexors are active in the case of the present study), leading to high performance in slow, long-lasting locomotion (i.e., long-distance running). Although these underlying mechanisms for the relationships between muscle stiffness and performance are still under speculation and factors other than VL stiffness influence sprint/running performance, the present results suggest that passive and active muscle stiffness may play different roles in sprinting and long-distance running.
In the SPR group, the active VL shear wave speed showed a significantly positive correlation with the 100-m race time, meaning that higher active muscle stiffness is related to inferior sprint performance. This result is opposite to our hypothesis. Although the reasons for the discrepancy between the hypothesis and the result are unknown, active muscle stiffness, which is balanced against tendon stiffness under active conditions, might be involved. To the best of our knowledge, only a few studies have attempted to identify the relationship between tendon stiffness and sprint performance (5,6,39). Among them, two studies demonstrated that the VL tendon was stiffer in inferior sprinters than in superior sprinters (5,6). It seems conceivable that the VL of sprinters with stiffer VL tendon should be stiffer during contraction to be able to store more elastic energy in the VL tendon at the first part of the contact (stance) phase during sprinting. Taken together, although the range of functions provided by muscle stiffness is not yet elucidated, it can be concluded that the spring-like function within the muscle may be simple but have so far undiscovered roles in locomotion. Future works should explore this possibility and gain insight into the functional roles of MTU stiffness in human locomotion while considering both muscle and tendon stiffness.
Limitations
Besides the contraction intensity as discussed above, the present study has some other limitations. First, we measured the VL shear wave speed in a sitting position, which does not correspond to the knee joint angles during the contact phase in sprinting or running. Second, the target muscle was limited to the VL. With regard to tendon stiffness, there were between-group differences as well as association with performance for the VL tendon but not for the plantar flexor tendon (5,39). It remains unclear whether such site specificity exists in muscle stiffness. Third, the SWE system used in the present study does not directly quantify the muscle stiffness but quantifies the shear wave speed. In most studies, shear modulus (expressed in kilopascals) is reported as a measure of stiffness. Shear modulus (G) is calculated using the equation G = ρv2, where ρ is the tissue density and v is the tissue shear wave speed. Although some assumptions are needed for obtaining the shear modulus from the shear wave speed, the tissue density is a matter of concern especially when comparing between groups or between individuals as in the case of the present study, because intramuscular compositions such as fat and connective tissue could differ between groups and between individuals. Namely, the between-group and -individual differences in muscle shear wave speed observed in the present study may not reflect those in muscle stiffness. However, this would be unlikely because the individual variation in muscle density (4% of CV, n = 54; [40]) is smaller compared with that in muscle shear wave speed (9% and 11% of CV for passive and active conditions, respectively, n = 63; the present study) and because the muscle shear wave speed has a square effect on the muscle shear modulus as the above equation shows. Nevertheless, it is unknown whether the former reason holds true in each of the SPR and LDR groups and for the comparison between the SPR and LDR groups. Further studies are required to examine these concerns.
CONCLUSIONS
We provided evidence that the muscles of sprinters and long-distance runners exhibit characteristic stiffness that can be beneficial to their athletic performance. Specifically, the VL muscle is stiffer in long-distance runners than in sprinters under both passive and active conditions. With respect to the association with performance, a high passive VL shear wave speed (i.e., stiffer VL at rest) is associated with superior sprint performance but with inferior long-distance running performance. A high active VL shear wave speed (i.e., stiffer VL during contraction) is associated with inferior sprint performance but not to running performance. These results have important implications for understanding the roles of muscle stiffness in human locomotion at various speeds. Furthermore, we propose that passive and active muscle stiffness may play different roles in human locomotion, depending on locomotion speeds.
The authors appreciate the time and effort expended by the volunteer subjects. This work was supported by JSPS KAKENHI grant JP16H03233 (to NM).
Author Contributions: N. M., K. H., K. I., and T. H. conceived and designed of research. N. M., K. H., and K. I. performed the experiments. N. M. and K. H. analyzed the data. N. M., K. H., K. I., and T. H. interpreted data. N. M. drafted manuscript. K. H., K. I., and T. H. edited and revised the article. All authors approved the final version of the article.
Conflict of Interest: The authors declare no conflict of interest. The results of this study are presented clearly, honestly, and without fabrication, falsification, or inappropriate data manipulation. The results of the present study do not constitute endorsement by the American College of Sports Medicine.
REFERENCES
1. Cavagna GA. Storage and utilization of elastic energy in skeletal muscle.
Exerc Sport Sci Rev. 1977;5:89–129.
2. Komi PV, Bosco C. Utilization of stored elastic energy in leg extensor muscles by men and women.
Med Sci Sports. 1978;10(4):261–5.
3. Bobbert MF. Dependence of human squat jump performance on the series elastic compliance of the triceps surae: a simulation study.
J Exp Biol. 2001;204(Pt 3):533–42.
4. Hobara H, Inoue K, Muraoka T, Omuro K, Sakamoto M, Kanosue K. Leg stiffness adjustment for a range of hopping frequencies in humans.
J Biomech. 2010;43(3):506–11.
5. Kubo K, Kanehisa H, Kawakami Y, Fukunaga T. Elasticity of tendon structures of the lower limbs in sprinters.
Acta Physiol Scand. 2000;168(2):327–35.
6. Stafilidis S, Arampatzis A. Muscle–tendon unit mechanical and morphological properties and sprint performance.
J Sports Sci. 2007;25(9):1035–46.
7. Kovanen V, Suominen H, Heikkinen E. Mechanical properties of fast and slow skeletal muscle with special reference to collagen and endurance training.
J Biomech. 1984;17(10):725–35.
8. Mutungi G, Ranatunga KW. The viscous, viscoelastic and elastic characteristics of resting fast and slow mammalian (rat) muscle fibres.
J Physiol. 1996;496(Pt 3):827–36.
9. Goubel F, Marini JF. Fibre type transition and stiffness modification of soleus muscle of trained rats.
Pflugers Arch. 1987;410(3):321–5.
10. Mutungi G, Ranatunga KW. The effects of ramp stretches on active contractions in intact mammalian fast and slow muscle fibres.
J Muscle Res Cell Motil. 2001;22(2):175–84.
11. Andersen JL, Klitgaard H, Saltin B. Myosin heavy chain isoforms in single fibres from m. vastus lateralis of sprinters: influence of training.
Acta Physiol Scand. 1994;151(2):135–42.
12. Gollnick PD, Armstrong RB, Saubert CW 4th, Piehl K, Saltin B. Enzyme activity and fiber composition in skeletal muscle of untrained and trained men.
J Appl Physiol. 1972;33(3):312–9.
13. Thorstensson A, Larsson L, Tesch P, Karlsson J. Muscle strength and fiber composition in athletes and sedentary men.
Med Sci Sports. 1977;9(1):26–30.
14. Goodpaster BH, He J, Watkins S, Kelley DE. Skeletal muscle lipid content and insulin resistance: evidence for a paradox in endurance-trained athletes.
J Clin Endocrinol Metab. 2001;86(12):5755–61.
15. Chakouch MK, Charleux F, Bensamoun SF. Quantifying the elastic property of nine thigh muscles using magnetic resonance
elastography.
PLoS One. 2015;10(11):e0142958.
16. Foure A, Nordez A, Cornu C. In vivo assessment of both active and passive parts of the plantarflexors series elastic component stiffness using the alpha method: a reliability study.
Int J Sports Med. 2010;31(1):51–7.
17. Hauraix H, Foure A, Dorel S, Cornu C, Nordez A. Muscle and tendon stiffness assessment using the alpha method and ultrafast ultrasound.
Eur J Appl Physiol. 2015;115(7):1393–400.
18. Kubo K. Active muscle stiffness in the human medial gastrocnemius muscle in vivo.
J Appl Physiol. 2014;117(9):1020–6.
19. Miyamoto N, Hirata K. Muscle elasticity under active conditions in humans: a methodological comparison.
Transl Sports Med. 2019;2(3):138–45.
20. Bercoff J, Tanter M, Fink M. Supersonic shear imaging: a new technique for soft tissue elasticity mapping.
IEEE Trans Ultrason Ferroelectr Freq Control. 2004;51(4):396–409.
21. Alexander RM, Bennet-Clark HC. Storage of elastic strain energy in muscle and other tissues.
Nature. 1977;265(5590):114–7.
22. Roberts TJ, Marsh RL, Weyand PG, Taylor CR. Muscular force in running turkeys: the economy of minimizing work.
Science. 1997;275(5303):1113–5.
23. Stolov WC, Weilepp TG Jr. Passive length–tension relationship of intact muscle, epimysium, and tendon in normal and denervated gastrocnemius of the rat.
Arch Phys Med Rehabil. 1966;47(9):612–20.
24. Young HJ, Jenkins NT, Zhao Q, McCully KK. Measurement of intramuscular fat by muscle echo intensity.
Muscle Nerve. 2015;52(6):963–71.
25. Gajdosik RL. Passive extensibility of skeletal muscle: review of the literature with clinical implications.
Clin Biomech (Bristol, Avon). 2001;16(2):87–101.
26. Gillies AR, Lieber RL. Structure and function of the skeletal muscle extracellular matrix.
Muscle Nerve. 2011;44(3):318–31.
27. Reimers K, Reimers CD, Wagner S, Paetzke I, Pongratz DE. Skeletal muscle sonography: a correlative study of echogenicity and morphology.
J Ultrasound Med. 1993;12(2):73–7.
28. Tamura Y, Watada H, Igarashi Y, et al. Short-term effects of dietary fat on intramyocellular lipid in sprinters and endurance runners.
Metabolism. 2008;57(3):373–9.
29. Pillen S, Tak RO, Zwarts MJ, et al. Skeletal muscle ultrasound: correlation between fibrous tissue and echo intensity.
Ultrasound Med Biol. 2009;35(3):443–6.
30. Yamamoto E, Kogawa D, Tokura S, Hayashi K. Effects of the frequency and duration of cyclic stress on the mechanical properties of cultured collagen fascicles from the rabbit patellar tendon.
J Biomech Eng. 2005;127(7):1168–75.
31. Foure A, Nordez A, McNair P, Cornu C. Effects of plyometric training on both active and passive parts of the plantarflexors series elastic component stiffness of muscle–tendon complex.
Eur J Appl Physiol. 2011;111:539–48.
32. Grosset JF, Piscione J, Lambertz D, Perot C. Paired changes in electromechanical delay and musculo-tendinous stiffness after endurance or plyometric training.
Eur J Appl Physiol. 2009;105(1):131–9.
33. Walmsley B, Proske U. Comparison of stiffness of soleus and medial gastrocnemius muscles in cats.
J Neurophysiol. 1981;46(2):250–9.
34. Malamud JG, Godt RE, Nichols TR. Relationship between short-range stiffness and yielding in type-identified, chemically skinned muscle fibers from the cat triceps surae muscles.
J Neurophysiol. 1996;76(4):2280–9.
35. Ramsey KA, Bakker AJ, Pinniger GJ. Fiber-type dependence of stretch-induced force enhancement in rat skeletal muscle.
Muscle Nerve. 2010;42(5):769–77.
36. Ates F, Hug F, Bouillard K, et al. Muscle shear elastic modulus is linearly related to muscle torque over the entire range of isometric contraction intensity.
J Electromyogr Kinesiol. 2015;25(4):703–8.
37. Takahashi C, Suga T. Ueno Het al. Potential relationship between passive plantar flexor stiffness and sprint performance in sprinters.
Phys Ther Sport. 2018;32:54–8.
38. Schnyer A, Gallardo M, Cox S, Gillis G. Indirect evidence for elastic energy playing a role in limb recovery during toad hopping.
Biol Lett. 2014;10(7):20140418.
39. Kubo K, Ikebukuro T, Yata H, Tomita M, Okada M. Morphological and mechanical properties of muscle and tendon in highly trained sprinters.
J Appl Biomech. 2011;27(4):336–44.
40. Ward SR, Lieber RL. Density and hydration of fresh and fixed human skeletal muscle.
J Biomech. 2005;38(11):2317–20.
