Diffusion tensor imaging (DTI) of human lower leg muscles: correlation between DTI parameters and muscle power with different ankle positions

Abstract

Purpose To compare diffusion tensor imaging (DTI) parameters in healthy adult human lower leg muscles and to determine the correlation between DTI parameters and muscle power measurements among different types of muscle contraction. Materials and methods DTI measurements of the unilateral lower leg muscles having three different types of contraction (non-contraction state, isometric contraction, and soleus shortening) were obtained from 10 healthy adults using a 3-T MRI scanner. DTI parameters (λ1, λ2, λ3, mean diffusivity, and fractional anisotropy) were calculated. The values of the DTI parameters and correlation between the DTI parameters and muscle power measurements (maximum power and maximum amount of work) obtained from a dynamometer were statistically compared among the different types of contraction. Intra- and inter-class correlation coefficients were calculated for analysis of reproducibility. Results The λ1, λ2, λ3, and mean diffusivity of the soleus muscle are significantly lower in the non-contraction state as compared with isometric contraction and soleus shortening (p < 0.05). A positive correlation of the soleus muscle in the non-contraction state was seen between the maximum power and the λ1, λ2, and mean diffusivity. There was a positive correlation between the maximum amount of work and fractional anisotropy in the non-contraction state for the soleus muscle. A negative correlation for the tibialis anterior muscle in the non-contraction state was seen between the maximum amount of work and fractional anisotropy. Overall reproducibility of the DTI parameters was excellent. Conclusions DTI parameters were significantly changed depending on the ankle joint position and type of muscle contraction.

Advanced muscle imaging in adolescent elite rowers utilizing diffusion tensor imaging: Association of imaging findings with stroke typology

“…We assume this is mainly because the standard deviation of the training load in our study collective was relatively small and all athletes underwent the same training scheme in preparation of the rowing season. In contrast, a few studies have shown the dependency of DTI parameters to exercise intensity [ 30 ]. However, the impact of different training regimes on long-term DTI parameter changes has not yet been adequately investigated and could be of interest for future studies.…”

Diffusion tensor imaging of horizontal extraocular muscles in patients with concomitant and paralytic esotropia

“…Klupp et al [21] found in their study of paraspinal muscle that AD and MD value had significant positive correlation with the ratio of extension to flexion. Takao et al [23] found a positive correlation of the soleus muscle in the non-contraction state between the maximum power and the AD, λ2, and MD. However, The study of Yamauchi et al [24] showed that a lower rectus femoris AD value predicted greater peak knee extension torque, which may lead to the fact that the rectus femoris is a biarticular muscle and includes the highest proportion of fast fiber type.…”

Current State of Artificial Intelligence in Clinical Applications for Head and Neck MR Imaging

“…Prognosis prediction contributes to the optimization of treatment strategies, including the selection of initial therapy and the indication for adjuvant therapies, and the prediction is also considered useful to validate the treatment plan for each patient with head or neck cancer. Over the past few decades, imaging methods have been well developed and used together with advanced imaging techniques such as DWI and DCE, [99][100][101][102][103][104][105][106][107][108][109][110] or a high-dimensional analytical method such as a texture analysis or radiomics method 14,22,24,111,112 in various diseases as well as head and neck lesions. However, achieving accurate predictions is still challenging.…”