# Fatigue Effects on the Lower Leg Muscle Architecture Using Diffusion Tensor MRI
## 4 Discussion
The PCSA estimated revealed much smaller values when compared with the existing literature (although the SOL and TA PCSAs were similar to those assessed in cadavers). We could attribute this to the estimated fiber length, which may have been overestimated (both before and after exercise). Moreover, some of the differences found may be partially explained by the fact that cadaveric tissue is subjected to specific protection procedures before experimental studies and the effects of those actions are still not well understood. Moreover, rigor mortis can produce a slow contraction in the skeletal muscle [49], with consequent effects on the fiber architecture. To test our second hypothesis, namely, the shape of the muscle was the same within our group of subjects, we considered the inter-subject variability by measuring the CV of the ratio between V\({}_{\text{m}}\) and the product of ACSA\({}_{\text{max}}\) and L\({}_{\text{m}}\) (shape factor p), as well as the ratio between V\({}_{\text{m}}\) and either the ACSA\({}_{\text{max}}\) or L\({}_{\text{m}}\) for the four muscles. We found that, similar to [PERSON] et al. [15], the lowest inter-subject variability occurred for the ratio between V\({}_{\text{m}}\) and the product of ACSA\({}_{\text{max}}\) and L\({}_{\text{m}}\), demonstrating that the shape of each muscle seemed to be similar across the examined subjects. Other limitations regarding this study must be reported. Regarding the use of DTI to assess the changes in the muscle architecture immediately after exercise, an important issue should be raised: the transverse relaxation time in muscles is short. This means that the signal-to-noise ratio was limited, thus increasing the number of averages needed to minimize the noise, thereby extending the acquisition time [22]. By increasing the acquisition time, the effect of the exercise may be partially lost due to a fast recovery period. This may explain some of our results since no significant changes were observed in most of the muscle's architecture. Moreover, it might be a limitation of this study that proton density and diffusion tensor imaging for 3D measurements of the leg muscles' architectural parameters does not entirely show a very high intraclass correlation coefficient for all muscle architectural parameters [21], and thus, we should be careful when interpreting the results. Additionally, the small sample size and the fact that the participants were only female subjects may also decrease the external validity of this study, making it difficult to extrapolate the results to other populations. The relationship between the structure and function of muscles is critical to understanding the physiological basis of force production and movement, especially in adaptive conditions, such as training, detraining, disease, age and immobilization, where the architecture of the muscle can undergo changes [50; 51; 52; 53]. This relationship is usually studied through musculoskeletal models, where the anatomical and architectural parameters of the muscles are usually simplified and/or adapted from cadaveric databases, most of them with a small sample size [18]. Structural and functional parameters provided by PD and DTI, such as the trace of the diffusion tensor, allow for the non-invasive and in vivo measurement of critical parameters for the elaboration of those models, such as muscle volume, fiber length and PCSA. Adding these architectural parameters in the elaboration of those models may help us to accurately assemble subject-specific simulations to study human movement. This combination of advanced imaging techniques with computation methods will allow for the creation of more individualized models, and subsequently, estimation of muscle forces during specific movement patterns.