Diffusion tensor imaging (DTI) is increasingly applied to study skeletal muscle physiology, anatomy, and pathology. The reason for this growing interest is that DTI offers unique, noninvasive, and potentially diagnostically relevant imaging readouts of skeletal muscle structure that are difficult or impossible to obtain otherwise. DTI has been shown to be feasible within most skeletal muscles. DTI parameters are highly sensitive to patient-specific properties such as age, body mass index (BMI), and gender, but also to more transient factors such as exercise, rest, pressure, temperature, and relative joint position. However, when designing a DTI study one should not only be aware of sensitivity to the above-mentioned factors but also the fact that the DTI parameters are dependent on several acquisition parameters such as echo time, b-value, and diffusion mixing time. The purpose of this review is to provide an overview of DTI studies covering the technical, demographic, and clinical aspects of DTI in skeletal muscles. First we will focus on the critical aspects of the acquisition protocol. Second, we will cover the reported normal variance in skeletal muscle diffusion parameters, and finally we provide an overview of clinical studies and reported parameter changes due to several (patho-)physiological conditions.

A feasible method for DTI measurements of the upper legs was developed that fully included frequently injured muscles, such as hamstrings, in one single imaging session. This study also revealed changes in DTI parameters that over time were not revealed by qualitative T2-weighted MR imaging with fat suppression.

The mechanical functions of muscles are generating force and actuating movement by shortening or lengthening under load. These functions are influenced, in part, by the internal arrangement of muscle fibers with respect to the muscle’s mechanical line of action. This property is known as muscle architecture. In this review, we describe the use of diffusion-tensor (DT-) MRI muscle fiber tracking for studying muscle architecture. In the first section, the importance of skeletal muscle architecture to function is discussed. Also, traditional and complementary methods for assessing muscle architecture (brightness-mode ultrasound imaging and cadaver analysis) are presented. Next, DT-MRI is introduced and the structural basis for the reduced and anisotropic diffusion of water in muscle is discussed. The third section discusses issues related to the acquisition of skeletal muscle DT-MRI data and presents recommendations for optimal strategies. The fourth section discusses methods for pre-processing DT-MRI data, the available approaches for calculating the diffusion tensor and seeding and propagating fiber tracts, and analyzing the tracking results to measure structural properties pertinent to muscle biomechanics. Lastly, examples of how DT-MRI fiber tracking has been used to provide new insights into how muscle function are presented and important future research directions are highlighted.

The aim of the present study was to evaluate a fast clinical protocol to enable diffusion tensor imaging of the human forearm and assess the reproducibility of six diffusion tensor imaging parameters, i.e., the tensor eigenvalues (l 1 , l 2 , and l 3 ), mean diffusivity, fractional anisotropy, and ellipsoid eccentricity. The right forearms of 10 healthy volunteers were scanned twice, with a 1-week interval. Reproducibility of the diffusion tensor imaging parameters was interpreted using Bland-Altman plots, coefficient of repeatability, repeatability index, and the intraclass correlation coefficient. Analysis was done for three regions of interest: the whole muscle volume, flexor digitorum profundus, and extensor digitorum. The Bland-Altman analysis showed that there is good agreement between the two measurements. Based on the intraclass correlation coefficients, agreement was substantial (0.59 < intraclass correlation coefficient < 0.92) for all six parameters of the whole muscle volume and flexor digitorum profundus but only fair (0.18 < intraclass correlation coefficient < 0.64) for the extensor digitorum. Using a 7 min 40 sec scan protocol, which was well tolerated by the volunteers, the reproducibility of diffusion tensor imaging parameters was demonstrated. However, repeatability varies, depending on the region of interest and diffusion tensor imaging parameters. This should be taken into account when a longitudinal study is designed. Magn Reson Med 64:1182-1190,

Musculoskeletal (dys‐)function relies for a large part on muscle architecture which can be obtained using Diffusion‐Tensor MRI (DT‐MRI) and fiber tractography. However, reconstructed tracts often continue along the tendon or aponeurosis when using conventional methods, thus overestimating fascicle lengths. In this study, we propose a new method for semiautomatic segmentation of tendinous tissue using tract density (TD). We investigated the feasibility and repeatability of this method to quantify the mean fascicle length per muscle. Additionally, we examined whether the method facilitates measuring changes in fascicle length of lower leg muscles with different foot positions. Five healthy subjects underwent two DT‐MRI scans of the right lower leg, with the foot in 15° dorsiflexion, neutral, and 30° plantarflexion positions. Repeatability of fascicle length measurements was assessed using Bland–Altman analysis. Changes in fascicle lengths between the foot positions were tested using a repeated multivariate analysis of variance (MANOVA). Bland–Altman analysis showed good agreement between repeated measurements. The coefficients of variation in neutral position were 8.3, 16.7, 11.2, and 10.4% for soleus (SOL), fibularis longus (FL), extensor digitorum longus (EDL), and tibialis anterior (TA), respectively. The plantarflexors (SOL and FL) showed significant increase in fascicle length from plantarflexion to dorsiflexion, whereas the dorsiflexors (EDL and TA) exhibited a significant decrease. The use of a tract density for semiautomatic segmentation of tendinous structures provides more accurate estimates of the mean fascicle length than traditional fiber tractography methods. The method shows moderate to good repeatability and allows for quantification of changes in fascicle lengths due to passive stretch.