Image-based musculoskeletal modeling: Applications, advances, and future opportunities

How reliable are femoropelvic kinematics during deep squats? The influence of subject-specific skeletal modelling on measurement variability

BACKGROUND

Biplanar radiography displays promising results in the production of subject-specific (S.specific) biomechanical models. However, the focus has predominantly centred on methodological investigations in gait analysis. Exploring the influence of such models on the analysis of high range of motion tasks linked to hip pathologies is warranted. The aim of this study is to investigate the effect of S.Specific modelling techniques on the reliability of deep squats kinematics in comparison to generic modelling.

METHODS

8 able-bodied male participants attended 5 motion capture sessions conducted by 3 observers and performed 5 deep squats in each. Prior to each session a biplanar scan was acquired with the reflective-markers attached. Inverse kinematics of pelvis and thigh segments were calculated based on S.specific and Generic model definition. Agreement between the two models femoropelvic orientation in standing was assessed with Bland-Altman plots and paired t- tests. Inter-trial, inter-session, inter-observer variability and observer/trial difference and ratio were calculated for squat kinematic data derived from the two modelling approaches.

RESULTS

Compared to the Generic model, the S.Specific model produced a calibration trial that is significantly offset into more posterior pelvis tilt (-2.8±2.7), hip extension (-2.2±3.8), hip abduction (-1.2±3.6) and external rotation (-13.8±11.4). The S.specific model produced significantly different squat kinematics in the sagittal plane of the pelvis (entire squat cycle) and hip (between 40 % and 60 % of the squat cycle). Variability analysis indicated that the error magnitude between the two models was comparable (difference<2°). The S.specific model exhibited a lower variability in the observer/trial ratio in the sagittal pelvis and hip, the frontal hip, but showed a higher variability in the transverse hip.

SIGNIFICANCE

S.specific modelling appears to introduce a calibration offset that primarily translates into an effect in the sagittal plane kinematics. However, the clinical added value of S.specific modelling in terms of reducing experimental sources of kinematic variability was limited.

Integration of Febio as an Instructional Tool in the Undergraduate Biomechanics Curriculum

Computer simulations play an important role in a range of biomedical engineering applications. Thus, it is important that biomedical engineering students engage with modeling in their undergraduate education and establish an understanding of its practice. In addition, computational tools enhance active learning and complement standard pedagogical approaches to promote student understanding of course content. Herein, we describe the development and implementation of learning modules for computational modeling and simulation (CM&S) within an undergraduate biomechanics course. We developed four CM&S learning modules that targeted predefined course goals and learning outcomes within the febio studio software. For each module, students were guided through CM&S tutorials and tasked to construct and analyze more advanced models to assess learning and competency and evaluate module effectiveness. Results showed that students demonstrated an increased interest in CM&S through module progression and that modules promoted the understanding of course content. In addition, students exhibited increased understanding and competency in finite element model development and simulation software use. Lastly, it was evident that students recognized the importance of coupling theory, experiments, and modeling and understood the importance of CM&S in biomedical engineering and its broad application. Our findings suggest that integrating well-designed CM&S modules into undergraduate biomedical engineering education holds much promise in supporting student learning experiences and introducing students to modern engineering tools relevant to professional development.

Impact of model geometry and joint center locations on inverse kinematic/dynamic predictions: A comparative study of sexually dimorphic models

This work illustrates the sensitivity of demographically characteristic body segment inertial properties and subject-specific customization on model performance. One characteristic demographic, gender, and one subject-specific characteristic, hip joint center location, were represented with musculoskeletal modeling to evaluate how design decisions may alter model outputs. Generic sexually dimorphic musculoskeletal models were developed from the commonly used Rajagopal model using male and female data adapted by Dumas et al. Hip joint centers of these models were adjusted based on functional joint center testing. The kinematics and dynamics of 40 gait cycles from four subjects are predicted using these models. Two-way analysis of variance (ANOVA) was performed on the continuous time series data using statistical parametric mapping (SPM) to assess changes in kinematics/dynamics due to either choice in model (Rajagopal vs Dumas) or whether joint center adjustment was performed. The SPM based two-way ANOVA of the inverse dynamics found that differences in the Rajagopal and Dumas models resulted in significant differences in sagittal plane moments during swing (0.115 ± 0.032 Nm/kg difference in mean hip flexion moment during initial swing and a 0.077 ± 0.041 Nm/kg difference in mean hip extension moment during terminal swing), and differences between the models with and without hip joint center adjustment resulted in significant differences in hip flexion and abduction moments during stance (0.217 ± 0.055 Nm/kg increased mean hip abductive moment). By comparing the outputs of these differently constructed models with each other, the study finds that dynamic predictions of stance are sensitive to positioning of joint centers, and dynamic predictions of swing are more sensitive to segment mass/inertial properties.

Muscle-Tendon Unit Length Measurement Using 3D Ultrasound in Passive Conditions: OpenSim Validation and Development of Personalized Models

This study investigated the validity of using OpenSim to measure muscle-tendon unit (MTU) length of the bi-articular lower limb muscles in several postures (shortened, lengthened, a combination of shortened and lengthened involving both joints, neutral and standing) using 3D freehand ultrasound (US), and to propose new personalized models. MTU length was measured on 14 participants and 6 bi-articular muscles (semimembranosus SM, semitendinosus ST, biceps femoris BF, rectus femoris RF, gastrocnemius medialis GM and gastrocnemius lateralis GL), considering 5 to 6 postures. MTU length was computed using OpenSim with three different models: OS (the generic OpenSim scaled model), OS + INSER (OS with personalized 3D US MTU insertions), OS + INSER + PATH (OS with personalized 3D US MTU insertions and path obtained from one posture). Significant differences in MTU length were found between OS and 3D US models for RF, GM and GL (from - 6.3 to 10.9%). Non-significant effects were reported for the hamstrings, notably for the ST (- 1.5%) and BF (- 1.9%), while the SM just crossed the alpha level (- 3.4%, p = 0.049). The OS + INSER model reduced the magnitude of bias by an average of 4% for RF, GM and GL. The OS + INSER + PATH model showed the smallest biases in length estimates, which made them negligible and non-significant for all the MTU (i.e. ≤ 2.2%). A 3D US pipeline was developed and validated to estimate the MTU length from a limited number of measurements. This opens up new perspectives for personalizing musculoskeletal models using low-cost user-friendly devices.

A Systems Approach to Biomechanics, Mechanobiology, and Biotransport

The human body represents a collection of interacting systems that range in scale from nanometers to meters. Investigations from a systems perspective focus on how the parts work together to enact changes across spatial scales, and further our understanding of how systems function and fail. Here, we highlight systems approaches presented at the 2022 Summer Biomechanics, Bio-engineering, and Biotransport Conference in the areas of solid mechanics; fluid mechanics; tissue and cellular engineering; biotransport; and design, dynamics, and rehabilitation; and biomechanics education. Systems approaches are yielding new insights into human biology by leveraging state-of-the-art tools, which could ultimately lead to more informed design of therapies and medical devices for preventing and treating disease as well as rehabilitating patients using strategies that are uniquely optimized for each patient. Educational approaches can also be designed to foster a foundation of systems-level thinking.

Forty-Six Years of Technological Innovation in Musculoskeletal Medicine: An Analysis of a Patent Database (1973 to 2018)

BACKGROUND

Technological innovation in orthopaedics is key to advancing patient care. As emerging technologies near maturity, clinicians must be able to objectively assess where and when these technologies can be implemented. Patent databases are an underappreciated resource for quantifying innovation, especially within orthopaedic surgery. This study used a patent database to assess patent activity and relative growth of technologies in musculoskeletal medicine and orthopaedics over a period of 46 years.

METHODS

A total of 121,471 patent records were indexed from Lens.org , a patent database. These patents were grouped into subspecialty clusters and technology clusters using patent codes. Five-year (2014 to 2018), 10-year (2009 to 2018), and 30-year (1989 to 2018) compound annual growth rates were calculated and compared for each cluster.

RESULTS

Annual patent activity increased from one patent in 1973 to 4,866 patents in 2018. Of the eight subspecialty clusters, the largest number of patents were related to 'Inflammation' (n = 63,128; 40.57%). The 'Elbow', 'Shoulder', and 'Knee' clusters experienced increased annual patent activity since 2000. Of the 12 technological clusters, the largest number of patents were related to 'Drugs' (n = 55,324; 39.75%). The 'Custom/patient-specific instrumentation, 'Computer Modeling', 'Robotics', and 'Navigation' clusters saw growth in the average annual patent activity since 2000.

DISCUSSION

Innovation, as measured by patent activity in musculoskeletal medicine and orthopaedics, has seen notable growth since 1973. The 'Robotics' cluster seems poised to experience exponential growth in industry investment and technological developments over the next 5 to 10 years. The 'Diagnostics', 'Computer Modeling', 'Navigation', and 'Design and Manufacturing' clusters demonstrate potential for exponential growth in industry investment and technological developments within the next 10 to 20 years.

American Society of Biomechanics Journal of Biomechanics Award 2022: Computer models do not accurately predict human muscle passive muscle force and fiber length: Evaluating subject-specific modeling impact on musculoskeletal model predictions

Musculoskeletal models are valuable for studying and understanding the human body in a variety of clinical applications that include surgical planning, injury prevention, and prosthetic design. Subject-specific models have proven to be more accurate and useful compared to generic models. Nevertheless, it is important to validate all models when possible. To this end, gracilis muscle-tendon parameters were directly measured intraoperatively and used to test model predictions. The aim of this study was to evaluate the benefits and limitations of systematically incorporating subject-specific variables into muscle models used to predict passive force and fiber length. The results showed that incorporating subject-specific values generally reduced errors, although significant errors still existed. Optimization of the modeling parameter "tendon slack length" was explored in two cases: minimizing fiber length error and minimizing passive force error. The results showed that using all subject-specific values yielded the most favorable outcome in both models and optimization cases. However, the trade-off between fiber length error and passive force error will depend on the specific circumstances and research objectives due to significant individual errors. Notably, individual fiber length and passive force errors were as high as 20% and 37% respectively. Finally, the modeling parameter "tendon slack length" did not correlate with any real-world anatomical length.

In vivo imaging of skeletal muscle form and function: 50 years of insight

Skeletal muscle form and function has fascinated scientists for centuries. Our understanding of muscle function has long been driven by advancements in imaging techniques. For example, the sliding filament theory of muscle, which is now widely leveraged in biomechanics research, stemmed from observations made possible by scanning electron microscopy. Over the last 50 years, advancing in medical imaging, combined with ingenuity and creativity of biomechanists, have provide a wealth of new and important insights into in vivo human muscle function. Incorporation of in vivo imaging has also advanced computational modeling and allowed our research to have an impact in many clinical populations. While this review does not provide a comprehensive or meta-analysis of the all the in vivo muscle imaging work over the last five decades, it provides a narrative about the past, present, and future of in vivo muscle imaging.

Increasing Step Frequency Reduces Patellofemoral Joint Stress and Patellar Tendon Force Impulse More at Low Running Speed

PURPOSE

Patellofemoral pain syndrome and patellar tendinopathy are important running-related overuse injuries. This study investigated the interaction of running speed and step frequency alterations on peak and cumulative patellofemoral joint stress (PFJS) and patellar tendon force (PTF) parameters.

METHODS

Twelve healthy individuals completed an incremental running speed protocol on a treadmill at habitual, increased and decreased step frequency. Peak PFJS and PTF, peak rate of PFJS and PTF development, and PFJS and PTF impulse per kilometer (km) were calculated using musculoskeletal modeling.

RESULTS

With increasing running speed, peak PFJS ( P < 0.001) and PTF ( P < 0.001) and peak rate of PFJS ( P < 0.001) and PTF ( P < 0.001) development increased, whereas PFJS ( P < 0.001) and PTF ( P < 0.001) impulse per km decreased. While increasing step frequency by 10%, the peak PFJS ( P < 0.001) and PTF ( P < 0.001) and the PFJS ( P < 0.001) and PTF ( P < 0.001) impulse per kilometer decreased. No significant effect of step frequency alteration was found for the peak rate of PFJS ( P = 0.008) and PTF ( P = 0.213) development. A significant interaction effect was found for PFJS ( P < 0.001) and PTF ( P < 0.001) impulse per km, suggesting that step frequency alteration was more effective at low running speed.

CONCLUSIONS

The effectiveness of step frequency alteration on PFJS and PTF impulse per km is dependent on the running speed. With regard to peak PFJS and PTF, step frequency alteration is equally effective at low and high running speeds. Step frequency alteration was not effective for peak rate of PFJS and PTF development. These findings can assist the optimization of patellofemoral joint and patellar tendon load management strategies.

A review of the efforts to develop muscle and musculoskeletal models for biomechanics in the last 50 years

Both the Hill and the Huxley muscle models had already been described by the time the International Society of Biomechanics was founded 50 years ago, but had seen little use before the 1970s due to the lack of computing. As computers and computational methods became available in the 1970s, the field of musculoskeletal modeling developed and Hill type muscle models were adopted by biomechanists due to their relative computational simplicity as compared to Huxley type muscle models. Muscle forces computed by Hill type muscle models provide good agreement in conditions similar to the initial studies, i.e. for small muscles contracting under steady and controlled conditions. However, more recent validation studies have identified that Hill type muscle models are least accurate for natural in vivo locomotor behaviours at submaximal activations, fast speeds and for larger muscles, and thus need to be improved for their use in understanding human movements. Developments in muscle modelling have tackled these shortcomings. However, over the last 50 years musculoskeletal simulations have been largely based on traditional Hill type muscle models or even simplifications of this model that neglected the interaction of the muscle with a compliant tendon. The introduction of direct collocation in musculoskeletal simulations about 15 years ago along with further improvements in computational power and numerical methods enabled the use of more complex muscle models in simulations of whole-body movement. Whereas Hill type models are still the norm, we may finally be ready to adopt more complex muscle models into musculoskeletal simulations of human movement.

Intra-operator Repeatability of Manual Segmentations of the Hip Muscles on Clinical Magnetic Resonance Images

The manual segmentation of muscles on magnetic resonance images is the gold standard procedure to reconstruct muscle volumes from medical imaging data and extract critical information for clinical and research purposes. (Semi)automatic methods have been proposed to expedite the otherwise lengthy process. These, however, rely on manual segmentations. Nonetheless, the repeatability of manual muscle volume segmentations performed on clinical MRI data has not been thoroughly assessed. When conducted, volumetric assessments often disregard the hip muscles. Therefore, one trained operator performed repeated manual segmentations (n = 3) of the iliopsoas (n = 34) and gluteus medius (n = 40) muscles on coronal T1-weighted MRI scans, acquired on 1.5 T scanners on a clinical population of patients elected for hip replacement surgery. Reconstructed muscle volumes were divided in sub-volumes and compared in terms of volume variance (normalized variance of volumes - nVV), shape (Jaccard Index-JI) and surface similarity (maximal Hausdorff distance-HD), to quantify intra-operator repeatability. One-way repeated measures ANOVA (or equivalent) tests with Bonferroni corrections for multiple comparisons were conducted to assess statistical significance. For both muscles, repeated manual segmentations were highly similar to one another (nVV: 2-6%, JI > 0.78, HD < 15 mm). However, shape and surface similarity were significantly lower when muscle extremities were included in the segmentations (e.g., iliopsoas: HD -12.06 to 14.42 mm, P < 0.05). Our findings show that the manual segmentation of hip muscle volumes on clinical MRI scans provides repeatable results over time. Nonetheless, extreme care should be taken in the segmentation of muscle extremities.

A handbook for beginners in skeletal muscle diffusion tensor imaging: physical basis and technical adjustments

Magnetic resonance imaging (MRI) of skeletal muscle is routinely performed using morphological sequences to acquire anatomical information. Recently, there is an increasing interest in applying advanced MRI techniques that provide pathophysiologic information for skeletal muscle evaluation to complement standard morphologic information. Among these advanced techniques, diffusion tensor imaging (DTI) has emerged as a potential tool to explore muscle microstructure. DTI can noninvasively assess the movement of water molecules in well-organized tissues with anisotropic diffusion, such as skeletal muscle. The acquisition of DTI studies for skeletal muscle assessment requires specific technical adjustments. Besides, knowledge of DTI physical basis and skeletal muscle physiopathology facilitates the evaluation of this advanced sequence and both image and parameter interpretation. Parameters derived from DTI provide a quantitative assessment of muscle microstructure with potential to become imaging biomarkers of normal and pathological skeletal muscle. KEY POINTS: • Diffusion tensor imaging (DTI) allows to evaluate the three-dimensional movement of water molecules inside biological tissues. • The skeletal muscle structure makes it suitable for being evaluated with DTI. • Several technical adjustments have to be considered for obtaining robust and reproducible DTI studies for skeletal muscle assessment, minimizing potential artifacts.

OpenColab project: OpenSim in Google colaboratory to explore biomechanics on the web

OpenSim is an open-source biomechanical package with a variety of applications. It is available for many users with bindings in MATLAB, Python, and Java via its application programming interfaces (APIs). Although the developers described well the OpenSim installation on different operating systems (Windows, Mac, and Linux), it is time-consuming and complex since each operating system requires a different configuration. This project aims to demystify the development of neuro-musculoskeletal modeling in OpenSim with zero configuration on any operating system for installation (thus cross-platform), easy to share models while accessing free graphical processing units (GPUs) on a web-based platform of Google Colab. To achieve this, OpenColab was developed where OpenSim source code was used to build a Conda package that can be installed on the Google Colab with only one block of code in less than 7 min. To use OpenColab, one requires a connection to the internet and a Gmail account. Moreover, OpenColab accesses vast libraries of machine learning methods available within free Google products, e.g. TensorFlow. Next, we performed an inverse problem in biomechanics and compared OpenColab results with OpenSim graphical user interface (GUI) for validation. The outcomes of OpenColab and GUI matched well (r≥0.82). OpenColab takes advantage of the zero-configuration of cloud-based platforms, accesses GPUs, and enables users to share and reproduce modeling approaches for further validation, innovative online training, and research applications. Step-by-step installation processes and examples are available at: https://simtk.org/projects/opencolab.

Validation of a Patient-Specific Musculoskeletal Model for Lumbar Load Estimation Generated by an Automated Pipeline From Whole Body CT

Background: Chronic back pain is a major health problem worldwide. Although its causes can be diverse, biomechanical factors leading to spinal degeneration are considered a central issue. Numerical biomechanical models can identify critical factors and, thus, help predict impending spinal degeneration. However, spinal biomechanics are subject to significant interindividual variations. Therefore, in order to achieve meaningful findings on potential pathologies, predictive models have to take into account individual characteristics. To make these highly individualized models suitable for systematic studies on spinal biomechanics and clinical practice, the automation of data processing and modeling itself is inevitable. The purpose of this study was to validate an automatically generated patient-specific musculoskeletal model of the spine simulating static loading tasks.

Methods: CT imaging data from two patients with non-degenerative spines were processed using an automated deep learning-based segmentation pipeline. In a semi-automated process with minimal user interaction, we generated patient-specific musculoskeletal models and simulated various static loading tasks. To validate the model, calculated vertebral loadings of the lumbar spine and muscle forces were compared with in vivo data from the literature. Finally, results from both models were compared to assess the potential of our process for interindividual analysis.

Results: Calculated vertebral loads and muscle activation overall stood in close correlation with data from the literature. Compression forces normalized to upright standing deviated by a maximum of 16% for flexion and 33% for lifting tasks. Interindividual comparison of compression, as well as lateral and anterior–posterior shear forces, could be linked plausibly to individual spinal alignment and bodyweight.

Conclusion: We developed a method to generate patient-specific musculoskeletal models of the lumbar spine. The models were able to calculate loads of the lumbar spine for static activities with respect to individual biomechanical properties, such as spinal alignment, bodyweight distribution, and ligament and muscle insertion points. The process is automated to a large extent, which makes it suitable for systematic investigation of spinal biomechanics in large datasets.

A Pilot Study of Radiomics Models Combining Multi-Probe and Multi-Modality Images of 68Ga-NOTA-PRGD2 and 18F-FDG PET/CT for Differentiating Benign and Malignant Pulmonary Space-Occupying Lesions

Background

This is a pilot study of radiomics based on ⁶⁸Ga-NOTA-PRGD2 [NOTA-PEG4-E[c(RGDfK)]2)] and ¹⁸F-FDG PET/CT to (i) evaluate the diagnostic efficacy of radiomics features of ⁶⁸Ga-NOTA-PRGD2 PET in the differential diagnosis of benign and malignant pulmonary space-occupying lesions and (ii) compare the diagnostic efficacy of multi-modality and multi-probe images.

Methods

We utilized a dataset of 48 patients who participated in ⁶⁸Ga-NOTA-PRGD2 PET/CT and ¹⁸F-FDG PET/CT clinical trials to extract image features and evaluate their diagnostic efficacy in the differentiation of benign and malignant lesions by the Mann-Whitney U test. After feature selection with sequential forward selection, random forest models were developed with tenfold cross-validation. The diagnostic performance of models based on different image features was visualized by receiver operating characteristic (ROC) curves and compared by permutation tests.

Results

Fourteen of the ⁶⁸Ga-NOTA-PRGD2 PET features between benign and malignant pulmonary space-occupying lesions had significant differences (P<0.05, Mann-Whitney U test). Eighteen of the ⁶⁸Ga-NOTA-PRGD2 PET features demonstrated higher AUC values than all CT features in the differential diagnosis of pulmonary lesions. The AUC value (0.908) ​​of the three-modal feature model was significantly higher (P<0.05, permutation test) than those of the single- and dual-modal models.

Conclusion

⁶⁸Ga-NOTA-PRGD2 PET features have better diagnostic capacity than CT features for pulmonary space-occupying lesions. The combination of multi-modality and multi-probe images can improve the diagnostic efficiency of models. Our preliminary clinical hypothesis of using radiomics based on ⁶⁸Ga-NOTA-PRGD2 PET images and multimodal images as a diagnostic tool warrants further validation in a larger multicenter sample size.

Uncertainty in Muscle–Tendon Parameters can Greatly Influence the Accuracy of Knee Contact Force Estimates of Musculoskeletal Models

Understanding the sources of error is critical before models of the musculoskeletal system can be usefully translated. Using in vivo measured tibiofemoral forces, the impact of uncertainty in muscle–tendon parameters on the accuracy of knee contact force estimates of a generic musculoskeletal model was investigated following a probabilistic approach. Population variability was introduced to the routine musculoskeletal modeling framework by perturbing input parameters of the lower limb muscles around their baseline values. Using ground reaction force and skin marker trajectory data collected from six subjects performing body-weight squat, the knee contact force was calculated for the perturbed models. The combined impact of input uncertainties resulted in a considerable variation in the knee contact force estimates (up to 2.1 BW change in the predicted force), especially at larger knee flexion angles, hence explaining up to 70% of the simulation error. Although individual muscle groups exhibited different contributions to the overall error, variation in the maximum isometric force and pathway of the muscles showed the highest impacts on the model outcomes. Importantly, this study highlights parameters that should be personalized in order to achieve the best possible predictions when using generic musculoskeletal models for activities involving deep knee flexion.

Regional variation in lateral and medial gastrocnemius muscle fibre lengths obtained from diffusion tensor imaging

Assessment of regional muscle architecture is primarily done through the study of animals, human cadavers, or using b-mode ultrasound imaging. However, there remain several limitations to how well such measurements represent in vivo human whole muscle architecture. In this study, we developed an approach using diffusion tensor imaging and magnetic resonance imaging to quantify muscle fibre lengths in different muscle regions along a muscle's length and width. We first tested the between-day reliability of regional measurements of fibre lengths in the medial (MG) and lateral gastrocnemius (LG) and found good reliability for these measurements (intraclass correlation coefficient [ICC] = 0.79 and ICC = 0.84, respectively). We then applied this approach to a group of 32 participants including males (n = 18), females (n = 14), young (24 ± 4 years) and older (70 ± 2 years) adults. We assessed the differences in regional muscle fibre lengths between different muscle regions and between individuals. Additionally, we compared regional muscle fibre lengths between sexes, age groups, and muscles. We found substantial variability in fibre lengths between different regions within the same muscle and between the MG and the LG across individuals. At the group level, we found no difference in mean muscle fibre length between males and females, nor between young and older adults, or between the MG and the LG. The high variability in muscle fibre lengths between different regions within the same muscle, possibly expands the functional versatility of the muscle for different task requirements. The high variability between individuals supports the use of subject-specific measurements of muscle fibre lengths when evaluating muscle function.

MRI classification using semantic random forest with auto-context model

BACKGROUND

It is challenging to differentiate air and bone on MR images of conventional sequences due to their low contrast. We propose to combine semantic feature extraction under auto-context manner into random forest to improve reasonability of the MRI segmentation for MRI-based radiotherapy treatment planning or PET attention correction.

METHODS

We applied a semantic classification random forest (SCRF) method which consists of a training stage and a segmentation stage. In the training stage, patch-based MRI features were extracted from registered MRI-CT training images, and the most informative elements were selected via feature selection to train an initial random forest. The rest sequence of random forests was trained by a combination of MRI feature and semantic feature under an auto-context manner. During segmentation, the MRI patches were first fed into these random forests to derive patch-based segmentation. By using patch fusion, the final end-to-end segmentation was obtained.

RESULTS

The Dice similarity coefficient (DSC) for air, bone and soft tissue classes obtained via proposed method were 0.976±0.007, 0.819±0.050 and 0.932±0.031, compared to 0.916±0.099, 0.673±0.151 and 0.830±0.083 with random forest (RF), and 0.942±0.086, 0.791±0.046 and 0.917±0.033 with U-Net. SCRF also outperformed the competing methods in sensitivity and specificity for all three structure types.

CONCLUSIONS

The proposed method accurately segmented bone, air and soft tissue. It is promising in facilitating advanced MR application in diagnosis and therapy.

Automatic detection of attachment sites for knee ligaments and tendons on CT images

PURPOSE

The diseases and injuries of the knee joint are the most common orthopedic disorders. Personalized knee models can be helpful in the process of early intervention and lasting treatment techniques development. Fully automatic reconstruction of knee joint anatomical structures from medical images (CT, MRI, ultrasound) remains a challenge. For this reason, most of state-of-the-art knee joint models contain simplifications such as representation of muscles and ligaments as line segments connecting two points which replace attachment areas. The paper presents algorithms for automatic detection of such points on knee CT images.

METHODS

This paper presents three approaches to automatic detection of ligaments and tendons attachment sites on the patients CT images: qualitative anatomical descriptions, analysis of bones curvature, and quantitative anatomical descriptions. Combinations of these approaches result in new automatic detection algorithms. Each algorithm exploits anatomical peculiarities of each attachment site, e.g., bone curvature and number of other attachments in a neighborhood of the site.

RESULTS

The experimental dataset consisted of 26 anonymized CT sequences containing right and left knee joints in different resolutions. The proposed algorithms take into account bone surface curvatures and spatial differences in locations of medial and lateral parts of both knees. The algorithms for detection of quadriceps femoris, popliteus, biceps femoris tendons, and lateral collateral and medial collateral ligaments attachment sites are provided, as well as examples of their application. Two algorithms are validated by comparison with known statistics of ligaments lengths and also using ground truth annotations for anatomical landmarks approved by clinical experts.

CONCLUSIONS

The algorithms simplify generation of patient-specific knee joint models demanded in personalized biomechanical models. The algorithms in the current implementation have two important limitations. First, the correctness of the produced results depends on the bones segmentation quality. Second, the presented algorithms detect a point of the attachment site, which is not necessarily its center. Therefore, manual correction of the attachment site location may be required for attachments with relatively large area.

Classifying muscle parameters with artificial neural networks and simulated lateral pinch data

Objective

Hill-type muscle models are widely employed in simulations of human movement. Yet, the parameters underlying these models are difficult or impossible to measure in vivo. Prior studies demonstrate that Hill-type muscle parameters are encoded within dynamometric data. But, a generalizable approach for estimating these parameters from dynamometric data has not been realized. We aimed to leverage musculoskeletal models and artificial neural networks to classify one Hill-type muscle parameter (maximum isometric force) from easily measurable dynamometric data (simulated lateral pinch force). We tested two neural networks (feedforward and long short-term memory) to identify if accounting for dynamic behavior improved accuracy.

Methods

We generated four datasets via forward dynamics, each with increasing complexity from adjustments to more muscles. Simulations were grouped and evaluated to show how varying the maximum isometric force of thumb muscles affects lateral pinch force. Both neural networks classified these groups from lateral pinch force alone.

Results

Both neural networks achieved accuracies above 80% for datasets which varied only the flexor pollicis longus and/or the abductor pollicis longus. The inclusion of muscles with redundant functions dropped model accuracies to below 30%. While both neural networks were consistently more accurate than random guess, the long short-term memory model was not consistently more accurate than the feedforward model.

Conclusion

Our investigations demonstrate that artificial neural networks provide an inexpensive, data-driven approach for approximating Hill-type muscle-tendon parameters from easily measurable data. However, muscles of redundant function or of little impact to force production make parameter classification more challenging.

SENSITIVITY OF MODEL-PREDICTED MUSCLE FORCES OF PATIENTS WITH CEREBRAL PALSY TO VARIATIONS IN MUSCLE-TENDON PARAMETERS

Computational musculoskeletal modeling and simulation platforms are efficient tools to gain insight into the muscular coordination of patients with motor disabilities such as cerebral palsy (CP). Muscle force predictions from simulation programs are influenced by the architectural and contractile properties of muscle-tendon units. In this study, we aimed to evaluate the sensitivity of major lower limb muscle forces in patients with CP to changes in muscle-tendon parameters. Open-access datasets of children with CP ([Formula: see text]) and healthy children ([Formula: see text]) were considered. Monte Carlo analysis was executed to specify how sensitive the muscle forces to perturbations between [Formula: see text]% and [Formula: see text]% of the nominal value of the maximum isometric muscle force, optimal muscle fiber length, muscle pennation angle, tendon slack length, and maximum contraction velocity of muscle. The sensitivity analysis revealed that muscle forces of CP patients and healthy individuals were most sensitive to perturbations in the tendon slack length ([Formula: see text]), while forces of CP patients were more sensitive to tendon slack length when compared to the healthy group ([Formula: see text]). Muscle forces of patients and healthy individuals were insensitive to the other four parameters ([Formula: see text]), except for the gracilis and sartorius muscles in which the proportion of optimal muscle fiber length to tendon slack length is higher than 1; forces of these two muscles were also sensitive to the optimal muscle fiber length. The results of this study are expected to contribute to our understanding of which parameters should be personalized when conducting musculoskeletal modeling and simulation of patients with CP.

Effects of Oral Drugs on Coronary Microvascular Function in Patients Without Significant Stenosis of Epicardial Coronary Arteries: A Systematic Review and Meta-Analysis of Coronary Flow Reserve

Objective: This study aims to investigate the impact of cardiovascular medications on the coronary flow reserve (CFR) in patients without obstructive coronary artery disease (CAD).

Methods: We searched PubMed, EMBASE, and Cochrane databases from inception to 15 November 2019. Studies were included if they reported CFR from baseline to follow-up after oral drug therapy of patients without obstructive CAD. Data was pooled using random-effects modeling. The primary outcome was change in CFR from baseline to follow-up after oral drug therapy.

Results: A total of 46 studies including 845 subjects were included in this study. Relative to baseline, the CFR was improved by angiotensin-converting enzymes (ACEIs), aldosterone receptor antagonists (ARBs) [standard mean difference (SMD): 1.12; 95% CI: 0.77–1.47], and statins treatments (SMD: 0.61; 95%CI: 0.36–0.85). Six to 12 months of calcium channel blocker (CCB) treatments improved CFR (SMD: 1.04; 95% CI: 0.51–1.58). Beta-blocker (SMD: 0.24; 95% CI: −0.39–0.88) and ranolazine treatment (SMD: 0.31; 95% CI: −0.39–1.01) were not associated with improved CFR.

Conclusions: Therapy with ACEIs, ARBs, and statins was associated with improved CFR in patients with confirmed or suspicious CMD. CCBs also improved CFR among patients followed for 6–12 months. Beta-blocker and ranolazine had no impact on CFR.

Predicting longitudinal changes in joint contact forces in a juvenile population: scaled generic versus subject-specific musculoskeletal models

Subject-specific musculoskeletal model use in clinical settings is limited due to development-associated time and effort burdens together with potential medical imaging unavailability. As an alternative, this study investigated consistency in estimating longitudinal changes in joint contact forces (JCF) between scaled generic and subject-specific models. For 11 children, joint kinematics and JCF were calculated using subject-specific and scaled generic models. JCF changes estimated by both models were strongly correlated for the hip and knee although JCF estimates varied between models. Findings suggest that within specified limits of accuracy, scaled generic models are sensitive enough to detect JCF changes consistent with subject-specific models.

Role of the Extracellular Matrix in Loss of Muscle Force With Age and Unloading Using Magnetic Resonance Imaging, Biochemical Analysis, and Computational Models

The focus of this review is the application of advanced MRI to study the effect of aging and disuse related remodeling of the extracellular matrix (ECM) on force transmission in the human musculoskeletal system. Structural MRI includes (i) ultra-low echo times (UTE) maps to visualize and quantify the connective tissue, (ii) diffusion tensor imaging (DTI) modeling to estimate changes in muscle and ECM microstructure, and (iii) magnetization transfer contrast imaging to quantify the macromolecular fraction in muscle. Functional MRI includes dynamic acquisitions during contraction cycles enabling computation of the strain tensor to monitor muscle deformation. Further, shear strain extracted from the strain tensor may be a potential surrogate marker of lateral transmission of force. Biochemical and histological analysis of muscle biopsy samples can provide "gold-standard" validation of some of the MR findings. The review summarizes biochemical studies of ECM adaptations with age and with disuse. A brief summary of animal models is included as they provide experimental confirmation of longitudinal and lateral force transmission pathways. Computational muscle models enable exploration of force generation and force pathways and elucidate the link between structural adaptations and functional consequences. MR image findings integrated in a computational model can explain and predict subject specific functional changes to structural adaptations. Future work includes development and validation of MRI biomarkers using biochemical analysis of muscle tissue as a reference standard and potential translation of the imaging markers to the clinic to noninvasively monitor musculoskeletal disease conditions and changes consequent to rehabilitative interventions.

A multivariate statistical strategy to adjust musculoskeletal models

In musculoskeletal modelling, adjusting model parameters is challenging. This paper proposes a multivariate statistical methodology to adjust muscle force-generating parameters optimally. Dynamic residuals are minimized as muscle force-generating parameters are varied (maximal isometric force, optimal fiber length, tendon slack length and pennation angle).First, a sensitivity and a Pareto analyses are carried out in order to sort out and screen the set of parameters having the greatest influence regarding the dynamic residuals. These parameters are then used to create a response surface following a Design of Experiments (DoE) approach. Finally, this surface is used to determine the optimum levels of the design variables (muscle force-generating parameters). The proposed methodology is illustrated by the adjustment of a three-dimensional musculoskeletal model of a sheep forelimb. After adjustment, the reserve actuator values of the elbow and wrist joints were reduced, on average, by 18%, and 16%, respectively. These results demonstrate that the use of multivariate statistical strategies is an effective way to adjust model parameters optimally while reducing dynamic inconsistencies. This study constitutes a step towards a more robust methodology in musculoskeletal modelling, focusing on muscular parameter tuning.

Increasing level of neuromusculoskeletal model personalisation to investigate joint contact forces in cerebral palsy: A twin case study

BACKGROUND

Cerebral palsy is a complex neuromuscular disorder that affects the sufferers in multiple different ways. Neuromusculoskeletal models are promising tools that can be used to plan patient-specific treatments for cerebral palsy. However, current neuromusculoskeletal models are typically scaled from generic adult templates that poorly represent paediatric populations. Furthermore, muscle activations are commonly computed via optimisation methods, which may not reproduce co-contraction observed in cerebral palsy. Alternatively, calibrated EMG-informed approaches within OpenSim can capture pathology-related muscle activation abnormalities, possibly enabling more feasible estimations of muscle and joint contact forces.

METHODS

Two identical twin brothers, aged 13, one with unilateral cerebral palsy and the other typically developing, were enrolled in the study. Four neuromusculoskeletal models with increasing subject-specificity were built in OpenSim and CEINMS combining literature findings, experimental motion capture, EMG and MR data for both participants. The physiological and biomechanical validity of each model was assessed by quantifying its ability to track experimental joint moments and muscle excitations.

FINDINGS

All developed models accurately tracked external joint moments; however EMG-informed models better tracked muscle excitations compared to neural solutions generated by static optimisation. Calibrating muscle-tendon unit parameters with EMG data allowed for more physiologically plausible joint contact forces estimates. Further scaling the maximal isometric force of muscles with MR-derived muscle volumes did not affect model predictions.

INTERPRETATION

Given their ability to identify atypical joint contact forces profiles and accurately reproduce experimental data, calibrated EMG-informed models should be preferred over generic models using optimisation methods in informing the management of cerebral palsy.

Automated postoperative muscle assessment of hip arthroplasty patients using multimodal imaging joint segmentation

BACKGROUND AND OBJECTIVE

In patients treated with hip arthroplasty, the muscular condition and presence of inflammatory reactions are assessed using magnetic resonance imaging (MRI). As MRI lacks contrast for bony structures, computed tomography (CT) is preferred for clinical evaluation of bone tissue and orthopaedic surgical planning. Combining the complementary information of MRI and CT could improve current clinical practice for diagnosis, monitoring and treatment planning. In particular, the different contrast of these modalities could help better quantify the presence of fatty infiltration to characterise muscular condition and assess implant failure. In this work, we combine CT and MRI for joint bone and muscle segmentation and we propose a novel Intramuscular Fat Fraction estimation method for the quantification of muscle atrophy.

METHODS

Our multimodal framework is able to segment healthy and pathological musculoskeletal structures as well as implants, and develops into three steps. First, input images are pre-processed to improve the low quality of clinically acquired images and to reduce the noise associated with metal artefact. Subsequently, CT and MRI are non-linearly aligned using a novel approach which imposes rigidity constraints on bony structures to ensure realistic deformation. Finally, taking advantage of a multimodal atlas we created for this task, a multi-atlas based segmentation delineates pelvic bones, abductor muscles and implants on both modalities jointly. From the obtained segmentation, a multimodal estimation of the Intramuscular Fat Fraction can be automatically derived.

RESULTS

Evaluation of the segmentation in a leave-one-out cross-validation study on 22 hip sides resulted in an average Dice score of 0.90 for skeletal and 0.84 for muscular structures. Our multimodal Intramuscular Fat Fraction was benchmarked on 27 different cases against a standard radiological score, showing stronger association than a single modality approach in a one-way ANOVA F-test analysis.

CONCLUSIONS

The proposed framework represents a promising tool to support image analysis in hip arthroplasty, being robust to the presence of implants and associated image artefacts. By allowing for the automated extraction of a muscle atrophy imaging biomarker, it could quantitatively inform the decision-making process about patient's management.

Accuracy and kinematics consistency of marker-based scaling approaches on a lower limb model: a comparative study with imagery data

Medical images are not typically included in protocol of motion laboratories. Thus, accurate scaling of musculoskeletal models from optoelectronic data are important for any biomechanical analysis. The aim of the current study was to identify a scaling method based on optoelectronic data, inspired from literature, which could offer the best trade-off between accurate geometrical parameters (segment lengths, orientation of joint axes, marker coordinates) and consistent inverse kinematics outputs (kinematic error, joint angles). The methods were applied on 26 subjects and assessed with medical imagery building EOS-based models, considered as a reference. The main contribution of this paper is to show that the marker-based scaling followed by an optimisation of orientation joint axes and markers local coordinates, gives the most consistent scaling and joint angles with EOS-based models. Thus, when a non-invasive mean with an optoelectronic system is considered, a marker-based scaling is preliminary needed to get accurate segment lengths and to optimise joint axes and marker local coordinates to reduce kinematic errors.AbbrevationsAJCAnkle joint centreCKEcumulative kinematic errorDoFdegree of freedomEBEOS-basedHBheight-basedHJChip joint centreKJCknee joint centreMBmarker-basedMSMmusculoskeletal modelsSPMstatistical parametric mappingSTAsoft tissue artifactEB_a.m∗EOS-based with optimised joint axes, and all model markers coordinatesMB_a.m∗marker-based with optimised joint axes, and all model markers coordinatesMB_l.a.mmarker-based with optimised segment lengths, joint axes, and selected model markers coordinatesASISanterior superior illiac spinePSISposterior superior illiac spine.

A discrete element model to predict anatomy of the psoas muscle and path of the tendon: Design implications for total hip arthroplasty

BACKGROUND

The accurate estimation of a muscle's line of action is a fundamental requirement in computational modelling. We present a novel anatomical muscle wrapping technique and demonstrate its clinical use on the evaluation of the Psoas muscle mechanics in hip arthroplasty.

METHODS

A volume preserving, spring model to parameterize muscle anatomy changes during motion is presented. Validation was performed by a CT scan of a cadaver model in multiple positions. The predicted psoas musculotendinous path was compared with the actual imaging findings. In a second stage, psoas kinetics were compared between a conventional versus a resurfacing hip arthroplasty during gait.

FINDINGS

Anatomy prediction error was found to be 2.12 mm on average (SD 1.34 mm). When applied to psoas mechanics during walking, the muscle was found to wrap predominantly around the femoral head providing a biomechanically efficient and nearly constant moment arm for flexion during the entire gait cycle. However, this advantage was found to be lost in small diameter hip arthroplasty designs resulting in an important mechanical disadvantage. The moment arm for flexion, was on average 36% (SD 0.03%) lower in the small diameter conventional hip arthroplasty as compared to the large diameter head of the hip resurfacing and this difference was highly significant. (p < 0.001).

INTERPRETATION

Despite the shortcomings of an "in silico" and cadaveric study, our findings are in accordance with previous clinical and gait studies. Furthermore, the findings are strongly in favour of large diameter implant designs, warranting their further development and optimisation.

A preclinical PET detector constructed with a monolithic scintillator ring

This paper presents a unique preclinical positron emission tomography (PET) detector constructed with a monolithic scintillator ring (MSR) and two rings of silicon photomultipliers (SiPM). The inner diameter, outer diameter and length of the MSR were 48.5 mm, 58.5 mm, and 25.1 mm, respectively. The two SiPM rings, constructed with 46 SiPMs, were air-coupled to the two ends of the MSR detector. The center of gravity (COG) and artificial neural network (ANN) methods were adapted to decode the positions of the gamma interactions in the circumferential (θ) and axial (Z) directions, respectively. Collimating systems, consisting of a tungsten collimator and a high-precision displacement and rotating platform, were constructed to assess the decoding accuracies of the MSR detector in both θ and Z directions. The average intrinsic full-width half maximums (FWHMs) and mean absolute errors (MAEs) of the decoding accuracies were 0.94 mm and 0.33 mm in the circumferential direction, 2.45 mm and 1.08 mm in the axial direction. An energy resolution of 10.7% was measured at 511 keV. The scintillating photons generated by a pair of coincidence gamma photons overlap with each other, and cause circumferential parallax errors in the lines of response (LOR). The experimental results show that the average FWHM errors in the θ direction increased slightly from 0.94 mm to 1.14 mm when Δθ of the two single events was larger than 70°. The imaging performance of the MSR detector was also initially assessed with a Derenzo phantom filled with 18F-FDG. The rods with a diameter larger than 1.2 mm can be resolved. The energy resolutions were 12.3% at 511 keV (single events), and 11.4% at 1022 keV (coincidence events). We concluded that it is feasible to construct the high-performance preclinical PET scanners using one or multiple MSR detectors.

Improving Musculoskeletal Model Scaling Using an Anatomical Atlas: The Importance of Gender and Anthropometric Similarity to Quantify Joint Reaction Forces

OBJECTIVE

The accuracy of a musculoskeletal model relies heavily on the implementation of the underlying anatomical dataset. Linear scaling of a generic model, despite being time and cost efficient, produces substantial errors as it does not account for gender differences and inter-individual anatomical variations. The hypothesis of this study is that linear scaling to a musculoskeletal model with gender and anthropometric similarity to the individual subject produces similar results to the ones that can be obtained from a subject-specific model.

METHODS

A lower limb musculoskeletal anatomical atlas was developed consisting of ten datasets derived from magnetic resonance imaging of healthy subjects and an additional generic dataset from the literature. Predicted muscle activation and joint reaction force were compared with electromyography and literature data. Regressions based on gender and anthropometry were used to identify the use of atlas.

RESULTS

Primary predictors of differences for the joint reaction force predictions were mass difference for the ankle (p < 0.001) and length difference for the knee and hip (p ≤ 0.017). Gender difference accounted for an additional 3% of the variance (p ≤ 0.039). Joint reaction force differences at the ankle, knee, and hip were reduced by between 50% and 67% (p = 0.005) when using a musculoskeletal model with the same gender and similar anthropometry in comparison with a generic model.

CONCLUSION

Linear scaling with gender and anthropometric similarity can improve joint reaction force predictions in comparison with a scaled generic model.

SIGNIFICANCE

The presented scaling approach and atlas can improve the fidelity and utility of musculoskeletal models for subject-specific applications.

Musculoskeletal models with generic and subject-specific geometry estimate different joint biomechanics in dysplastic hips

Optimizing the geometric complexity of musculoskeletal models is important for reliable yet feasible estimation of joint biomechanics. This study investigated the effects of subject-specific model geometry on hip joint reaction forces (JRFs) and muscle forces in patients with developmental dysplasia of the hip (DDH) and healthy controls. For nine DDH and nine control subjects, three models were created with increasingly subject-specific pelvis geometry, hip joint center locations and muscle attachments. Hip JRFs and muscle forces during a gait cycle were compared among the models. For DDH subjects, resultant JRFs from highly specific models including subject-specific pelvis geometry, joint locations and muscle attachments were not significantly different compared to models using generic geometry in early stance, but were significantly higher in late stance (p = 0.03). Estimates from moderately specific models using CT-informed scaling of generic pelvis geometry were not significantly different from low specificity models using generic geometry scaled with skin markers. For controls, resultant JRFs in early stance from highly specific models were significantly lower than moderate and low specificity models (p ≤ 0.02) with no significant differences in late stance. Inter-model JRF differences were larger for DDH subjects than controls. Inter-model differences for JRF components and muscle forces were similar to resultant JRFs. Incorporating subject-specific pelvis geometry significantly affects JRF and muscle force estimates in both DDH and control groups, which may be especially important for reliable estimation of pathomechanics in dysplastic hips.

Individualization of Musculoskeletal Model for Analyzing Pelvic Floor Muscles Activity Based on Gait Motion Features

Stress urinary incontinence (SUI) is a typical quality of life disease in women. The strengthening of the pelvic floor muscle (PFM) is considered effective to prevent this. Specifically, PFM activity is affected by individual pelvic shape and posture. Therefore, it is necessary to analyze muscle activity by considering the individual differences. In this study, individual pelvic alignment was estimated from the feature values of natural gait via multiple regression analysis. In addition, individual pelvic feature points were derived from X-ray images and used to deform the standard model to obtain individual pelvic shapes. Results indicate that the residual averages of the estimated feature angles were less than 2° in most cases. Subsequently, measurements of the pelvis were obtained via MRI to evaluate the estimated pelvis shape. The results indicate that individual adaptation leads to muscle attachment positions, which are important in the muscle activity analysis, and closer to the true MRI value when compared to that of the standard pelvic model.

A Systematic Review of Continuum Modeling of Skeletal Muscles: Current Trends, Limitations, and Recommendations

Finite elasticity theory has been commonly used to model skeletal muscle. A very large range of heterogeneous constitutive laws has been proposed. In this review, the most widely used continuum models of skeletal muscles were synthetized and discussed. Trends and limitations of these laws were highlighted to propose new recommendations for future researches. A systematic review process was performed using two reliable search engines as PubMed and ScienceDirect. 40 representative studies (13 passive muscle materials and 27 active muscle materials) were included into this review. Note that exclusion criteria include tendon models, analytical models, 1D geometrical models, supplement papers, and indexed conference papers. Trends of current skeletal muscle modeling relate to 3D accurate muscle representation, parameter identification in passive muscle modeling, and the integration of coupled biophysical phenomena. Parameter identification for active materials, assumed fiber distribution, data assumption, and model validation are current drawbacks. New recommendations deal with the incorporation of multimodal data derived from medical imaging, the integration of more biophysical phenomena, and model reproducibility. Accounting for data uncertainty in skeletal muscle modeling will be also a challenging issue. This review provides, for the first time, a holistic view of current continuum models of skeletal muscles to identify potential gaps of current models according to the physiology of skeletal muscle. This opens new avenues for improving skeletal muscle modeling in the framework of in silico medicine.

Diffusion-Tensor Imaging Versus Digitization in Reconstructing the Masseter Architecture

Accurate characterization of the craniomaxillofacial (CMF) skeleton using finite element (FE) modeling requires representation of complex geometries, heterogeneous material distributions, and physiological loading. Musculature in CMF FE models are often modeled with simple link elements that do not account for fiber bundles (FBs) and their differential activation. Magnetic resonance (MR) diffusion-tensor imaging (DTI) enables reconstruction of the three-dimensional (3D) FB arrangement within a muscle. However, 3D quantitative validation of DTI-generated FBs is limited. This study compares 3D FB arrangement in terms of pennation angle (PA) and fiber bundle length (FBL) generated through DTI in a human masseter to manual digitization. CT, MR-proton density, and MR-DTI images were acquired from a single cadaveric specimen. Bone and masseter surfaces were reconstructed from CT and MR-proton density images, respectively. PA and FBL were estimated from FBs reconstructed from MR-DTI images using a streamline tracking (STT) algorithm (n = 193) and FBs identified through manual digitization (n = 181) and compared using the Mann–Whitney test. DTI-derived PAs did not differ from the digitized data (p = 0.411), suggesting that MR-DTI can be used to simulate FB orientation and the directionality of transmitted forces. Conversely, a significant difference was observed in FBL (p < 0.01) which may have resulted due to the tractography stopping criterion leading to early tract termination and greater length variability. Overall, this study demonstrated that DTI can yield muscle FB orientation data suitable to representative directionality of physiologic muscle loading in patient-specific CMF FE modeling.

Measurement of large strain properties in calf muscles in vivo using magnetic resonance elastography and spatial modulation of magnetization

It is important to measure the large deformation properties of skeletal muscle in vivo in order to understand and model movement and the force-producing capabilities of muscle. As muscle properties are non-linear, an understanding of how the deformation state affects the measured shear moduli is also useful for clinical applications of magnetic resonance elastography (MRE) to muscle disorders. MRE has so far only been used to measure the linear viscoelastic (small strain) properties of muscles. This study aims to measure the shear moduli of human calf muscles under varying degrees of strain using MRE. Nine healthy adults (four males; age range, 25-38 years) were recruited, and the storage modulus G' was measured at three ankle angle positions: P0 (neutral), P15 (15° plantarflexed) and P30 (30° plantarflexed). Spatial modulation of magnetization (SPAMM) was used to measure the strain in the calf associated with the ankle rotations between P0 to P15 and P0 to P30. SPAMM results showed that, with plantarflexion, there was a shortening of the medial gastrocnemius and soleus muscles, which resulted in an expansion of both muscles in the transverse direction. Strains for each ankle rotation were in the range 3-9% (in compression). MRE results showed that this shortening during plantarflexion resulted in a mean decrease in G' in the medial gastrocnemius (p = 0.013, linear mixed model), but not in the soleus (p = 0.47). This study showed that MRE is a viable technique for the measurement of large strain deformation properties in vivo in soft tissues by inducing physiological strain within the muscle during imaging.

An Efficient Modelling-Simulation-Analysis Workflow to Investigate Stump-Socket Interaction Using Patient-Specific, Three-Dimensional, Continuum-Mechanical, Finite Element Residual Limb Models

The lack of an efficient modelling-simulation-analysis workflow for creating and utilising detailed subject-specific computational models is one of the key reasons why simulation-based approaches for analysing socket-stump interaction have not yet been successfully established. Herein, we propose a novel and efficient modelling-simulation-analysis workflow that uses commercial software for generating a detailed subject-specific, three-dimensional finite element model of an entire residual limb from Diffusion Tensor MRI images in <20 min. Moreover, to complete the modelling-simulation-analysis workflow, the generated subject-specific residual limb model is used within an implicit dynamic FE simulation of bipedal stance to predict the potential sites of deep tissue injury. For this purpose, a nonlinear hyperelastic, transversely isotropic skeletal muscle constitutive law containing a deep tissue injury model was implemented in LS-DYNA. To demonstrate the feasibility of the entire modelling-simulation-analysis workflow and the fact that detailed, anatomically realistic, multi-muscle models are superior to state-of-the-art, fused-muscle models, an implicit dynamic FE analysis of 2-h bipedal stance is carried out. By analysing the potential volume of damaged muscle tissue after donning an optimally-fitted and a misfitted socket, i.e., a socket whose volume was isotropically shrunk by 10%, we were able to highlight the differences between the detailed individual- and fused-muscle models. The results of the bipedal stance simulation showed that peak stresses in the fused-muscle model were four times lower when compared to the multi-muscle model. The peak interface stress in the individual-muscle model, at the end of bipedal stance analysis, was 2.63 times lower than that in the deep tissues of the stump. At the end of the bipedal stance analysis using the misfitted socket, the fused-muscle model predicted that 7.65% of the residual limb volume was injured, while the detailed-model predicted 16.03%. The proposed approach is not only limited to modelling residual limbs but also has applications in predicting the impact of plastic surgery, for detailed forward-dynamics simulations of normal musculoskeletal systems.

Sensitivity analysis of the estimated muscle forces during gait with respect to the musculoskeletal model parameters and dynamic simulation techniques

The purpose of the current study was to investigate the robustness of dynamic simulation results in the presence of uncertainties resulting from application of a scaled-generic musculoskeletal model instead of a subject-specific model as well as the effect of the choice of simulation method on the obtained muscle forces. The performed sensitivity analysis consisted of the following multibody parameter modifications: maximum isometric muscle forces, number of muscles, the hip joint centre location, segment masses as well as different dynamic simulation methods, namely static optimization with three different criteria and a computed muscle control algorithm (hybrid approach combining forward and inverse dynamics). Twenty-four different models and fifty-five resultant dynamic simulation data sets were analysed. The effects of model perturbation on the magnitude and profile of muscle forces were compared. It has been shown that estimated muscle forces are very sensitive to model parameters. The greatest impact was observed in the case of the force magnitude of the muscles generating high forces during gait (regardless of the modification introduced). However, the force profiles of those muscles were preserved. Relatively large differences in muscle forces were observed for different simulation techniques, which included both magnitude and profile of muscle forces. Personalization of model parameters would affect the resultant muscle forces and seems to be necessary to improve general accuracy of the estimated parameters. However, personalization alone will not ensure high accuracy due to the still unresolved muscle force sharing problem.

Interlaboratory comparison of femur surface reconstruction from CT data compared to reference optical 3D scan

BACKGROUND

The present study contrasts the accuracy of different reconstructed models with distinctive segmentation methods performed by various experts. Seven research groups reconstructed nine 3D models of one human femur based on an acquired CT image using their own computational methods. As a reference model for accuracy assessment, a 3D surface scan of the human femur was created using an optical measuring system. Prior to comparison, the femur was divided into four areas; "neck and greater trochanter", "proximal metaphysis", "diaphysis", and "distal metaphysis". The deviation analysis was carried out in GEOMAGIC studio v.2013 software.

RESULTS

The results revealed that the highest deviation errors occurred in "neck and greater trochanter" area and "proximal metaphysis" area with RMSE of 0.84 and 0.83 mm respectively.

CONCLUSION

In conclusion, this study shows that the average deviation of reconstructed models prepared by experts with various methods, skills and software from the surface 3D scan is lower than 0.79 mm, which is not a significant discrepancy.

Dynamic MRI to quantify musculoskeletal motion: A systematic review of concurrent validity and reliability, and perspectives for evaluation of musculoskeletal disorders

Purpose

To report evidence for the concurrent validity and reliability of dynamic MRI techniques to evaluate in vivo joint and muscle mechanics, and to propose recommendations for their use in the assessment of normal and impaired musculoskeletal function.

Materials and methods

The search was conducted on articles published in Web of science, PubMed, Scopus, Academic search Premier, and Cochrane Library between 1990 and August 2017. Studies that reported the concurrent validity and/or reliability of dynamic MRI techniques for in vivo evaluation of joint or muscle mechanics were included after assessment by two independent reviewers. Selected articles were assessed using an adapted quality assessment tool and a data extraction process. Results for concurrent validity and reliability were categorized as poor, moderate, or excellent.

Results

Twenty articles fulfilled the inclusion criteria with a mean quality assessment score of 66% (±10.4%). Concurrent validity and/or reliability of eight dynamic MRI techniques were reported, with the knee being the most evaluated joint (seven studies). Moderate to excellent concurrent validity and reliability were reported for seven out of eight dynamic MRI techniques. Cine phase contrast and real-time MRI appeared to be the most valid and reliable techniques to evaluate joint motion, and spin tag for muscle motion.

Conclusion

Dynamic MRI techniques are promising for the in vivo evaluation of musculoskeletal mechanics; however results should be evaluated with caution since validity and reliability have not been determined for all joints and muscles, nor for many pathological conditions.

nmsBuilder: Freeware to create subject-specific musculoskeletal models for OpenSim

BACKGROUND AND OBJECTIVE

Musculoskeletal modeling and simulations of movement have been increasingly used in orthopedic and neurological scenarios, with increased attention to subject-specific applications. In general, musculoskeletal modeling applications have been facilitated by the development of dedicated software tools; however, subject-specific studies have been limited also by time-consuming modeling workflows and high skilled expertise required. In addition, no reference tools exist to standardize the process of musculoskeletal model creation and make it more efficient. Here we present a freely available software application, nmsBuilder 2.0, to create musculoskeletal models in the file format of OpenSim, a widely-used open-source platform for musculoskeletal modeling and simulation. nmsBuilder 2.0 is the result of a major refactoring of a previous implementation that moved a first step toward an efficient workflow for subject-specific model creation.

METHODS

nmsBuilder includes a graphical user interface that provides access to all functionalities, based on a framework for computer-aided medicine written in C++. The operations implemented can be used in a workflow to create OpenSim musculoskeletal models from 3D surfaces. A first step includes data processing to create supporting objects necessary to create models, e.g. surfaces, anatomical landmarks, reference systems; and a second step includes the creation of OpenSim objects, e.g. bodies, joints, muscles, and the corresponding model.

RESULTS

We present a case study using nmsBuilder 2.0: the creation of an MRI-based musculoskeletal model of the lower limb. The model included four rigid bodies, five degrees of freedom and 43 musculotendon actuators, and was created from 3D surfaces of the segmented images of a healthy subject through the modeling workflow implemented in the software application.

CONCLUSIONS

We have presented nmsBuilder 2.0 for the creation of musculoskeletal OpenSim models from image-based data, and made it freely available via nmsbuilder.org. This application provides an efficient workflow for model creation and helps standardize the process. We hope this would help promote personalized applications in musculoskeletal biomechanics, including larger sample size studies, and might also represent a basis for future developments for specific applications.

Incorporation of CT-based measurements of trunk anatomy into subject-specific musculoskeletal models of the spine influences vertebral loading predictions

We created subject-specific musculoskeletal models of the thoracolumbar spine by incorporating spine curvature and muscle morphology measurements from computed tomography (CT) scans to determine the degree to which vertebral compressive and shear loading estimates are sensitive to variations in trunk anatomy. We measured spine curvature and trunk muscle morphology using spine CT scans of 125 men, and then created four different thoracolumbar spine models for each person: (i) height and weight adjusted (Ht/Wt models); (ii) height, weight, and spine curvature adjusted (+C models); (iii) height, weight, and muscle morphology adjusted (+M models); and (iv) height, weight, spine curvature, and muscle morphology adjusted (+CM models). We determined vertebral compressive and shear loading at three regions of the spine (T8, T12, and L3) for four different activities. Vertebral compressive loads predicted by the subject-specific CT-based musculoskeletal models were between 54% lower to 45% higher from those estimated using musculoskeletal models adjusted only for subject height and weight. The impact of subject-specific information on vertebral loading estimates varied with the activity and spinal region. Vertebral loading estimates were more sensitive to incorporation of subject-specific spinal curvature than subject-specific muscle morphology. Our results indicate that individual variations in spine curvature and trunk muscle morphology can have a major impact on estimated vertebral compressive and shear loads, and thus should be accounted for when estimating subject-specific vertebral loading. © 2017 Orthopaedic Research Society. Published by Wiley Periodicals, Inc. J Orthop Res 35:2164-2173, 2017.

A scaling method to individualise muscle force capacities in musculoskeletal models of the hand and wrist using isometric strength measurements

Because the force-generating capacities of muscles are currently estimated using anatomical data obtained from cadaver specimens, hand musculoskeletal models provide only a limited representation of the specific features of individual subjects. A scaling method is proposed to individualise muscle capacities using dynamometric measurements and electromyography. For each subject, a strength profile was first defined by measuring net moments during eight maximum isometric contractions about the wrist and metacarpophalangeal joints. The capacities of the five muscle groups were then determined by adjusting several parameters of an initial musculoskeletal model using an optimisation procedure which minimised the differences between measured moments and model estimates. Sixteen volunteers, including three particular participants (one climber, one boxer and one arthritic patient), were recruited. Compared with the initial literature-based model, the estimated subject-specific capacities were on average five times higher for the wrist muscles and twice as high for the finger muscles. The adjustments for particular subjects were consistent with their expected specific characteristics, e.g. high finger flexor capacities for the climber. Using the subject-specific capacities, the model estimates were markedly modified. The proposed protocol and scaling procedure can capture the specific characteristics of the participants and improved the representation of their capacities in the musculoskeletal model.

RIGID MUSCULOSKELETAL MODELS OF THE HUMAN BODY SYSTEMS: A REVIEW

Advancing the knowledge of the biomechanics of the human body is essential to improve the clinical decision-makings of musculoskeletal disorders in the framework of in silico medicine. An impressive number of research projects focused on the development of rigid-body musculoskeletal models have been conducted over the world thanks to the new research directives. However, the application of these models in clinical practices remains a challenging issue. The objective of this review paper was to present the most current rigid-body musculoskeletal models of the human body systems and to analyze their trends and weaknesses for clinical applications. Then, recommendations were proposed for future researches toward fully clinical decision support. A systematic review process was performed. Well-selected studies related to the most current rigid-body 3D musculoskeletal models for each body system component (jaw, cervical spine, upper limbs, lumbar spine, and lower limbs) were summarized and explored. Trends in rigid musculoskeletal modeling are highlighted as personalization, new imaging techniques for specific joint kinematics, and computational efficiency. Weaknesses are highlighted as modeling assumptions, use of generic model, lack of modeling consensus, model validation, and parameter and model uncertainties. Future directions related to joint and muscle modeling, neuro-musculoskeletal modeling, model validation, data and model uncertainty quantification are recommended.