Determination of skeletal muscle architecture is important for accurately modeling muscle behavior. Current methods for 3D muscle architecture determination can be costly and time-consuming, making them prohibitive for clinical or modeling applications. Computational approaches such as Laplacian flow simulations can estimate muscle fascicle orientation based on muscle shape and aponeurosis location. The accuracy of this approach is unknown, however, since it has not been validated against other standards for muscle architecture determination. In this study, muscle architectures from the Laplacian approach were compared to those determined from diffusion tensor imaging in eight adult medial gastrocnemius muscles. The datasets were subdivided into training and validation sets, and computational fluid dynamics software was used to conduct Laplacian simulations. In training sets, inputs of muscle geometry, aponeurosis location, and geometric flow guides resulted in good agreement between methods. Application of the method to validation sets showed no significant differences in pennation angle (mean difference [Formula: see text] or fascicle length (mean difference 0.9 mm). Laplacian simulation was thus effective at predicting gastrocnemius muscle architectures in healthy volunteers using imaging-derived muscle shape and aponeurosis locations. This method may serve as a tool for determining muscle architecture in silico and as a complement to other approaches.
There are few comprehensive investigations of the changes in muscle architecture that accompany muscle contraction or change in muscle length in vivo. For this study, we measured changes in the three-dimensional architecture of the human medial gastrocnemius at the whole muscle level, the fascicle level and the fiber level using anatomical MRI and diffusion tensor imaging (DTI). Data were obtained from eight subjects under relaxed conditions at three muscle lengths. At the whole muscle level, a 5.1% increase in muscle belly length resulted in a reduction in both muscle width (mean change -2.5%) and depth (-4.8%). At the fascicle level, muscle architecture measurements obtained at 3,000 locations per muscle showed that for every millimeter increase in muscle-tendon length above the slack length, average fascicle length increased by 0.46 mm, pennation angle decreased by 0.27° (0.17° in the superficial part and 0.37° in the deep part), and fascicle curvature decreased by 0.18 m(-1) There was no evidence of systematic variation in architecture along the muscle's long axis at any muscle length. At the fiber level, analysis of the diffusion signal showed that passive lengthening of the muscle increased diffusion along fibers and decreased diffusion across fibers. Using these measurements across scales, we show that the complex shape changes that muscle fibers, whole muscles, and aponeuroses of the medial gastrocnemius undergo in vivo cannot be captured by simple geometrical models. This justifies the need for more complex models that link microstructural changes in muscle fibers to macroscopic changes in architecture.NEW & NOTEWORTHY Novel MRI and DTI techniques revealed changes in three-dimensional architecture of the human medial gastrocnemius during passive lengthening. Whole muscle belly width and depth decreased when the muscle lengthened. Fascicle length, pennation, and curvature changed uniformly or near uniformly along the muscle during passive lengthening. Diffusion of water molecules in muscle changes in the same direction as fascicle strains.
Ultrasound imaging is often used to measure muscle fascicle lengths and pennation angles in human muscles in vivo. Theoretically the most accurate measurements are made when the transducer is oriented so that the image plane aligns with muscle fascicles and, for measurements of pennation, when the image plane also intersects the aponeuroses perpendicularly. However this orientation is difficult to achieve and usually there is some degree of misalignment. Here, we used simulated ultrasound images based on three-dimensional models of the human medial gastrocnemius, derived from magnetic resonance and diffusion tensor images, to describe the relationship between transducer orientation and measurement errors. With the transducer oriented perpendicular to the surface of the leg, the error in measurement of fascicle lengths was about 0.4 mm per degree of misalignment of the ultrasound image with the muscle fascicles. If the transducer is then tipped by 20°, the error increases to 1.1 mm per degree of misalignment. For a given degree of misalignment of muscle fascicles with the image plane, the smallest absolute error in fascicle length measurements occurs when the transducer is held perpendicular to the surface of the leg. Misalignment of the transducer with the fascicles may cause fascicle length measurements to be underestimated or overestimated. Contrary to widely held beliefs, it is shown that pennation angles are always overestimated if the image is not perpendicular to the aponeurosis, even when the image is perfectly aligned with the fascicles. An analytical explanation is provided for this finding.
The length and pennation of muscle fascicles are frequently measured using ultrasonography. Conventional ultrasonography imaging methods only provide two-dimensional images of muscles, but muscles have complex three-dimensional arrangements. The most accurate measurements will be obtained when the ultrasound transducer is oriented so that endpoints of a fascicle lie on the ultrasound image plane and the image plane is oriented perpendicular to the aponeurosis, but little is known about how to find this optimal transducer orientation in the frequently-studied medial gastrocnemius muscle. In the current study, we determined the optimal transducer orientation at 9 sites in the medial gastrocnemius muscle of 8 human subjects by calculating the angle of misalignment between three-dimensional muscle fascicles, reconstructed from diffusion tensor images, and the plane of a virtual ultrasound image. The misalignment angle was calculated for a range of tilts and rotations of the ultrasound transducer relative to a reference orientation that was perpendicular to the skin and parallel to the tibia. With the transducer in the reference orientation, the misalignment was substantial (mean across sites and subjects of 6.5°, range 1.4 to 20.2°). However for all sites and subjects a near-optimal alignment (on average 2.6°, range 0.5° to 6.0°) could be achieved by maintaining 0° tilt and applying a small rotation (typically less than 10°). On the basis of these data we recommend that ultrasonographic measurements of medial gastrocnemius muscle fascicle architecture be obtained, at least for relaxed muscles under static conditions, with the transducer oriented perpendicular to the skin and nearly parallel to the tibia.
Personalisation of model parameters is likely to improve biomechanical model predictions and could allow models to be used for subject- or patient-specific applications. This study evaluates the effect of personalising physiological cross-sectional areas (PCSA) in a large-scale musculoskeletal model of the upper extremity. Muscle volumes obtained from MRI were used to scale PCSAs of five subjects, for whom the maximum forces they could exert in six different directions on a handle held by the hand were also recorded. The effect of PCSA scaling was evaluated by calculating the lowest maximum muscle stress (σmax, a constant for human skeletal muscle) required by the model to reproduce these forces. When the original cadaver-based PCSA-values were used, strongly different between-subject σmax-values were found (σmax=106.1±39.9 N cm(-2)). A relatively simple, uniform scaling routine reduced this variation substantially (σmax=69.4±9.4 N cm(-2)) and led to similar results to when a more detailed, muscle-specific scaling routine was used (σmax=71.2±10.8 N cm(-2)). Using subject-specific PCSA values to simulate an shoulder abduction task changed muscle force predictions for the subscapularis and the pectoralis major on average by 33% and 21%, respectively, but was <10% for all other muscles. The glenohumeral (GH) joint contact force changed less than 1.5% as a result of scaling. We conclude that individualisation of the model's strength can most easily be done by scaling PCSA with a single factor that can be derived from muscle volume data or, alternatively, from maximum force measurements. However, since PCSA scaling only marginally changed muscle and joint contact force predictions for submaximal tasks, the need for PCSA scaling remains debatable.
In vivo measurements of muscle architecture provide insight into inter-individual differences in muscle function and could be used to personalise musculoskeletal models. When muscle architecture is measured from ultrasound images, as is frequently done, it is assumed that fascicles are oriented in the image plane and, for some measurements, that the image plane is perpendicular to the aponeurosis at the intersection of fascicle and aponeurosis. This study presents an in vivo validation of these assumptions by comparing ultrasound image plane orientation to three-dimensional reconstructions of muscle fascicles and aponeuroses obtained with diffusion tensor imaging (DTI) and high-resolution anatomical MRI scans. It was found that muscle fascicles were oriented on average at 5.5±4.1° to the ultrasound image plane. On average, ultrasound yielded similar measurements of fascicle lengths to DTI (difference <3mm), suggesting that the measurements were unbiased. The absolute difference in length between any pair of measurements made with ultrasound and DTI was substantial (10mm or 20% of the mean), indicating that the measurements were imprecise. Pennation angles measured with ultrasound were significantly smaller than those measured with DTI (mean difference 6°). This difference was apparent only at the superficial insertion of the muscle fascicles so it was probably due to pressure on the skin applied by the ultrasound probes. It is concluded that ultrasound measurements of deep pennation angles and fascicle lengths in the medial gastrocnemius are unbiased but have a low precision and that superficial pennation angles are underestimated by approximately 10°. The low precision limits the use of ultrasound to personalise fascicle length in musculoskeletal models.
Musculoskeletal models are intended to be used to assist in prevention and treatments of musculoskeletal disorders. To capture important aspects of shoulder dysfunction, realistic simulation of clavicular and scapular movements is crucial. The range of motion of these bones is dependent on thoracic, clavicular and scapular anatomy and therefore different for each individual. Typically, patient or subject measurements will therefore not fit on a model that uses a cadaveric morphology. Up till now, this problem was solved by adjusting measured bone rotations such that they fit on the model, but this leads to adjustments of on average 3.98° and, in some cases, even more than 8°. Two novel methods are presented that decrease this discrepancy between experimental data and simulations. For one method, the model is scaled to fit the subject, leading to a 34 % better fit compared to the existing method. In the other method, the set of possible joint rotations is increased by allowing some variation on motion constraints, resulting in a 42 % better fit. This change in kinematics also affected the kinetics: muscle forces of some important scapular stabilizing muscles, as predicted by the Delft Shoulder and Elbow Model, were altered by maximally 17 %. The effect on the glenohumeral joint contact force was however marginal (1.3 %). The methods presented in this paper might lead to more realistic shoulder simulations and can therefore be considered a step towards (clinical) application, especially for applications that involve scapular imbalance.
Patient-specific biomechanical models including patient-specific finite-element (FE) models are considered potentially important tools for providing personalized healthcare to patients with musculoskeletal diseases. A multi-step procedure is often needed to generate a patient-specific FE model. As all involved steps are associated with certain levels of uncertainty, it is important to study how the uncertainties of individual components propagate to final simulation results. In this study, we considered a specific case of this problem where the uncertainties of the involved steps were known and the aim was to determine the uncertainty of the predicted strain distribution. The effects of uncertainties of three important components of patient-specific models, including bone density, musculoskeletal loads and the parameters of the material mapping relationship on the predicted strain distributions, were studied. It was found that the number of uncertain components and the level of their uncertainty determine the uncertainty of simulation results. The 'average' uncertainty values were found to be relatively small even for high levels of uncertainty in the components of the model. The 'maximum' uncertainty values were, however, quite high and occurred in the areas of the scapula that are of the greatest clinical relevance. In addition, the uncertainty of the simulation result was found to be dependent on the type of movement analysed, with abduction movements presenting consistently lower uncertainty values than flexion movements.
The parameters that describe the soft tissue structures are among the most important anatomical parameters for subject-specific biomechanical modelling. In this paper, we study one of the soft tissue parameters, namely muscle attachment sites. Two new methods are proposed for transformation of the muscle attachment sites of any reference scapula to any destination scapula based on four palpable bony landmarks. The proposed methods as well as one previously proposed method have been applied for transformation of muscle attachment sites of one reference scapula to seven other scapulae. The transformation errors are compared among the three methods. Both proposed methods yield significantly less (p < 0.05) prediction error as compared to the currently available method. Furthermore, we investigate whether there exists a reference scapula that performs significantly better than other scapulae when used for transformation of muscle attachment sites. Seven different scapulae were used as reference scapula and their resulting transformation errors were compared with each other. In the considered statistical population, no such a thing as an ideal scapula was found. There was, however, one outlier scapula that performed significantly worse than the other scapulae when used as a reference. The effect of perturbations in both muscle attachment sites and other muscle properties is studied by comparing muscle force predictions of a musculoskeletal model between perturbed and non-perturbed versions of the model. It is found that 10 mm variations in muscle attachments have more significant effect on muscle force predictions than 10% variations in any of the other four analysed muscle properties.
Musculoskeletal models have been developed to estimate internal loading on the human skeleton, which cannot directly be measured in vivo, from external measurements like kinematics and external forces. Such models of the shoulder and upper extremity have been used for a variety of purposes, ranging from understanding basic shoulder biomechanics to assisting in preoperative planning. In this review, we provide an overview of the most commonly used large-scale shoulder and upper extremity models and categorise the applications of these models according to the type of questions their users aimed to answer. We found that the most explored feature of a model is the possibility to predict the effect of a structural adaptation on functional outcome, for instance, to simulate a tendon transfer preoperatively. Recent studies have focused on minimising the mismatch in morphology between the model, often derived from cadaver studies, and the subject that is analysed. However, only a subset of the parameters that describe the model's geometry and, perhaps most importantly, the musculotendon properties can be obtained in vivo. Because most parameters are somehow interrelated, the others should be scaled to prevent inconsistencies in the model's structure, but it is not known exactly how. Although considerable effort is put into adding complexity to models, for example, by making them subject-specific, we have found little evidence of their superiority over current models. The current trend in development towards individualised, more complex models needs to be justified by demonstrating their ability to answer questions that cannot already be answered by existing models.
This paper aims to develop an EMG-driven model of the shoulder that can consider possible muscle co-contractions. A musculoskeletal shoulder model (the original model) is modified such that measured EMGs can be used as model-inputs (the EMG-driven model). The model is validated by using the in-vivo measured glenohumeral-joint reaction forces (GH-JRFs). Three patients carrying instrumented hemi-arthroplasty were asked to perform arm abduction and forward-flexion up to maximum possible elevation, during which motion data, EMG, and in-vivo GH-JRF were measured. The measured EMGs were normalized and together with analyzed motions served as model inputs to estimate the GH-JRF. All possible combinations of input EMGs ranging from a single signal to all EMG signals together were tested. The 'best solution' was defined as the combination of EMGs which yielded the closest match between the model and the experiments. Two types of inconsistencies between the original model and the measurements were observed including a general GH-JRF underestimation and a GH-JRF drop above 90° elevation. Both inconsistencies appeared to be related to co-contraction since inclusion of EMGs could significantly (p<.05) improve the predicted GH-JRF (up to 45%). The developed model has shown the potential to successfully take the existent muscle co-contractions of patients into account.