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

Fetus descent simulation with the active uterine contraction during the vaginal delivery: MRI-based evaluation and uncertainty quantification

Finite element models ranging from single to multiscale models have been widely used to gain valuable insights into the physiological delivery process and associated complication scenarios. However, the fetus descent simulation with the active uterine contraction is still challenging for validation and uncertainty quantification issues. The present study performed a fetus descent simulation using the active uterine contraction. Then, simulation outcomes were evaluated using theoretical and in vivo MRI childbirth data. Moreover, parameter uncertainty and propagation were also performed. A maternal pelvis model was developed. The active uterine contraction was modeled using a transversely isotropic Mooney-Rivlin material. Displacement trajectories were compared between simulation, theoretical and in vivo MRI childbirth data. Monte Carlo (M.C) and Polynomial Chaos Expansion (PCE) methods were applied to quantify uncertain parameters and their propagations. Obtained results showed that fetal descent behavior is consistent with the MRI-based observation as well as the theoretical trajectory (curve of Carus). The head downward vertical displacement ranges from 0 to approximately 47 mm. A reduction of 50% in uterine size was observed during the simulation. Three high-sensitive parameters (C 1 , C 2 , Ca 0 ) were also identified. Our study suggested that the use of the active uterine contraction is essential for simulating vaginal delivery but the global parameter sensitivity, parameter uncertainty, and outcome evaluation should be carefully performed. As a perspective, the developed approach could be extrapolated for patient-specific modeling and associated delivery complication simulations to identify risks and potential therapeutic solutions.

Reliability of MyotonPro in measuring the biomechanical properties of the quadriceps femoris muscle in people with different levels and types of motor preparation

The aim of this research was to evaluate the reliability of the measurements of biomechanical parameters of the muscles of athletes representing different disciplines as well as untrained people. Ninety-four young, healthy male individuals participated in the study and were divided into five subgroups: footballers (n = 25), volleyballers (n = 14), handballers (n = 19), MMA fighters (n = 16), and undrained group (n = 20). All of the participants underwent measurements of stiffness (S), muscle tone (T) and elasticity (E) by two independent measurers using MyotonPro equipment. Analysis was conducted on two different parts of the quadriceps femoris: rectus femoris (RF) and vastus medialis (VM. Consequently, the comprehensive analysis comprised 564 measurements (94 participants * 3 parameters = 282 * 2 measurers = 564). The results proves high reliability of the myotonometry (Pearson's CC over 0.8208-0.8871 for different parameters, ICC from to 0.74 to 0.99 for different muscles and parameters) excluding only stiffness for the VM which was characterized withlow ICC of 0.08 and relatively highest between the examined parameters MAE% of 8.7% which still remains low value. The most significant differences between the parameters in examined groups were observed between MMA fighters and volleyballers in terms of muscle tone and elasticity of the VM (correlation of 0.14842 and 0.15083 respecitively). These results confirm the usability of myotonometry in measuring the biomechanical properties of the muscles in different sports groups and confirm the independence of the results obtained from the person performing the measurement.

Exploring the muscle architecture effect on the mechanical behaviour of mouse rotator cuff muscles

Incorporating detailed muscle architecture aspects into computational models can enable researchers to gain deeper insights into the complexity of muscle function, movement, and performance. In this study, we employed histological, multiphoton image processing, and finite element method techniques to characterise the mechanical dependency on the architectural behaviour of supraspinatus and infraspinatus mouse muscles. While mechanical tests revealed a stiffer passive behaviour in the supraspinatus muscle, the collagen content was found to be two times higher in the infraspinatus. This effect was unveiled by analysing the alignment of fibres during muscle stretch with the 3D models and the parameters obtained in the fitting. Therefore, a strong dependence of muscle behaviour, both active and passive, was found on fibre orientation rather than collagen content.

Optimal fibre length and maximum isometric force are the most influential parameters when modelling muscular adaptations to unloading using Hill-type muscle models

Introduction: Spaceflight is associated with severe muscular adaptations with substantial inter-individual variability. A Hill-type muscle model is a common method to replicate muscle physiology in musculoskeletal simulations, but little is known about how the underlying parameters should be adjusted to model adaptations to unloading. The aim of this study was to determine how Hill-type muscle model parameters should be adjusted to model disuse muscular adaptations. Methods: Isokinetic dynamometer data were taken from a bed rest campaign and used to perform tracking simulations at two knee extension angular velocities (30°·s-1 and 180°·s-1). The activation and contraction dynamics were solved using an optimal control approach and direct collocation method. A Monte Carlo sampling technique was used to perturb muscle model parameters within physiological boundaries to create a range of theoretical and feasible parameters to model muscle adaptations. Results: Optimal fibre length could not be shortened by more than 67% and 61% for the knee flexors and non-knee muscles, respectively. Discussion: The Hill-type muscle model successfully replicated muscular adaptations due to unloading, and recreated salient features of muscle behaviour associated with spaceflight, such as altered force-length behaviour. Future researchers should carefully adjust the optimal fibre lengths of their muscle-models when trying to model adaptations to unloading, particularly muscles that primarily operate on the ascending and descending limbs of the force-length relationship.

Influence of muscle length on the three-dimensional architecture and aponeurosis dimensions of rabbit calf muscles

The function of a muscle is highly dependent on its architecture, which is characterized by the length, pennation, and curvature of the fascicles, and the geometry of the aponeuroses. During in vivo function, muscles regularly undergo changes in length, thereby altering their architecture. During passive muscle lengthening, fascicle length (FL) generally increases and the angle of fascicle pennation (FP) and the fascicle curvature (FC) decrease, while the aponeuroses increase in length but decrease in width. Muscles are differently structured, making their change during muscle lengthening complex and multifaceted. To obtain comprehensive data on architectural changes in muscles during passive length, the present study determined the three-dimensional fascicle geometry of rabbit M. gastrocnemius medialis (GM), M. gastrocnemius lateralis (GL), and M. plantaris (PLA). For this purpose, the left and right legs of three rabbits were histologically fixed at targeted ankle joint angles of 95° (short muscle length [SML]) and 60° (long muscle length [LML]), respectively, and the fascicles were tracked by manual three-dimensional digitization. In a second set of experiments, the GM aponeurosis dimensions of ten legs from five rabbits were determined at varying muscle lengths via optical marker tracking. The GM consisted of a uni-pennated compartment, whereas the GL and PLA contained multiple compartments of differently pennated fascicles. In the LML compared to the SML, the GM, GL, and PLA had on average a 41%, 29%, and 41% increased fascicle length, and a 30%, 25%, and 33% decrease in fascicle pennation and a 32%, 11%, and 35% decrease in fascicle curvature, respectively. Architectural properties were also differentiated among the different compartments of the PLA and GL, allowing for a more detailed description of their fascicle structure and changes. It was shown that the compartments change differently with muscle length. It was also shown that for each degree of ankle joint angle reduction, the proximal GM aponeurosis length increased by 0.11%, the aponeurosis width decreased by 0.22%, and the area was decreased by 0.20%. The data provided improve our understanding of muscles and can be used to develop and validate muscle models.

A Biomechanical Simulation of Forearm Flexion Using the Finite Element Approach

Upper limb movement is vital in daily life. A biomechanical simulation of the forearm with consideration of the physiological characteristics of the muscles is instrumental in gaining deeper insights into the upper limb motion mechanisms. In this study, we established a finite element model of the forearm, including the radius, biceps brachii, and tendons. We simulated the motion of the forearm resulting from the contraction of the biceps brachii by using a Hill-type transversely isotropic hyperelastic muscle model. We adjusted the contraction velocity of the biceps brachii muscle in the simulation and found that a slower muscle contraction velocity facilitated forearm flexion. Then, we changed the percentage of fast-twitch fibers, the maximum muscle strength, and the neural excitation values of the biceps brachii muscle to investigate the forearm flexion of elderly individuals. Our results indicated that reduced fast-twitch fiber percentage, maximum muscle strength, and neural excitation contributed to the decline in forearm motion capability in elderly individuals. Additionally, there is a threshold for neural excitation, below which, motion capability sharply declines. Our model aids in understanding the role of the biceps brachii in forearm flexion and identifying the causes of upper limb movement disorders, which is able to provide guidance for enhancing upper limb performance.

Modeling of active skeletal muscles: a 3D continuum approach incorporating multiple muscle interactions

Skeletal muscles have a highly organized hierarchical structure, whose main function is to generate forces for movement and stability. To understand the complex heterogeneous behaviors of muscles, computational modeling has advanced as a non-invasive approach to evaluate relevant mechanical quantities. Aiming to improve musculoskeletal predictions, this paper presents a framework for modeling 3D deformable muscles that includes continuum constitutive representation, parametric determination, model validation, fiber distribution estimation, and integration of multiple muscles into a system level for joint motion simulation. The passive and active muscle properties were modeled based on the strain energy approach with Hill-type hyperelastic constitutive laws. A parametric study was conducted to validate the model using experimental datasets of passive and active rabbit leg muscles. The active muscle model with calibrated material parameters was then implemented to simulate knee bending during a squat with multiple quadriceps muscles. A computational fluid dynamics (CFD) fiber simulation approach was utilized to estimate the fiber arrangements for each muscle, and a cohesive contact approach was applied to simulate the interactions among muscles. The single muscle simulation results showed that both passive and active muscle elongation responses matched the range of the testing data. The dynamic simulation of knee flexion and extension showed the predictive capability of the model for estimating the active quadriceps responses, which indicates that the presented modeling pipeline is effective and stable for simulating multiple muscle configurations. This work provided an effective framework of a 3D continuum muscle model for complex muscle behavior simulation, which will facilitate additional computational and experimental studies of skeletal muscle mechanics. This study will offer valuable insight into the future development of multiscale neuromuscular models and applications of these models to a wide variety of relevant areas such as biomechanics and clinical research.

Linking cortex and contraction-Integrating models along the corticomuscular pathway

Computational models of the neuromusculoskeletal system provide a deterministic approach to investigate input-output relationships in the human motor system. Neuromusculoskeletal models are typically used to estimate muscle activations and forces that are consistent with observed motion under healthy and pathological conditions. However, many movement pathologies originate in the brain, including stroke, cerebral palsy, and Parkinson's disease, while most neuromusculoskeletal models deal exclusively with the peripheral nervous system and do not incorporate models of the motor cortex, cerebellum, or spinal cord. An integrated understanding of motor control is necessary to reveal underlying neural-input and motor-output relationships. To facilitate the development of integrated corticomuscular motor pathway models, we provide an overview of the neuromusculoskeletal modelling landscape with a focus on integrating computational models of the motor cortex, spinal cord circuitry, α-motoneurons  and skeletal muscle in regard to their role in generating voluntary muscle contraction. Further, we highlight the challenges and opportunities associated with an integrated corticomuscular pathway model, such as challenges in defining neuron connectivities, modelling standardisation, and opportunities in applying models to study emergent behaviour. Integrated corticomuscular pathway models have applications in brain-machine-interaction, education, and our understanding of neurological disease.

Nondestructive ultrasound evaluation of microstructure-related material parameters of skeletal muscle: An in silico and in vitro study

Direct and nondestructive assessment of material properties of skeletal muscle in vivo shall advance our understanding of intact muscle mechanics and facilitate personalized interventions. However, this is challenged by intricate hierarchical microstructure of the skeletal muscle. We have previously regarded the skeletal muscle as a composite of myofibers and extracellular matrix (ECM), formulated shear wave propagation in the undeformed muscle using the acoustoelastic theory, and preliminarily demonstrated that ultrasound-based shear wave elastography (SWE) could estimate microstructure-related material parameters (MRMPs): myofiber stiffness μ_f, ECM stiffness μ_m, and myofiber volume ratio V_f. The proposed method warrants further validation but is hampered by the lack of ground truth values of MRMPs. In this study, we presented analytical and experimental validations of the proposed method using finite-element (FE) simulations and 3D-printed hydrogel phantoms, respectively. Three combinations of different physiologically relevant MRMPs were used in the FE simulations where shear wave propagations in the corresponding composite media were simulated. Two 3D-printed hydrogel phantoms with the MRMPs close to those of a real skeletal muscle (i.e., μ_f=2.02kPa, μ_m=52.42kPa, and V_f=0.675,0.832) for ultrasound imaging were fabricated by an alginate-based hydrogel printing protocol that we modified and optimized from the freeform reversible embedding of suspended hydrogels (FRESH) method in literature. Average percent errors of (μ_f,μ_m,V_f) estimates were found to be (2.7%,7.3%,2.4%)in silico and (3.0%,8.0%,9.9%)in vitro. This quantitative study corroborated the potential of our proposed theoretical model along with ultrasound SWE for uncovering microstructural characteristics of the skeletal muscle in an entirely nondestructive way.

A biophysically guided constitutive law of the musculotendon-complex: modelling and numerical implementation in Abaqus

BACKGROUND AND OBJECTIVE

Many biomedical, clinical, and industrial applications may benefit from musculoskeletal simulations. Three-dimensional macroscopic muscle models (3D models) can more accurately represent muscle architecture than their 1D (line-segment) counterparts. Nevertheless, 3D models remain underutilised in academic, clinical, and commercial environments. Among the reasons for this is a lack of modelling and simulation standardisation, verification, and validation. Here, we strive towards a solution by providing an open-access, characterised, constitutive relation (CR) for 3D musculotendon models.

METHODS

The musculotendon complex is modelled following the state-of-the-art active stress approach and is treated as hyperelastic, transversely isotropic, and nearly incompressible. Furthermore, force-length and -velocity relationships are incorporated, and muscle activation is derived from motor-unit information. The CR was implemented within the commercial finite-element software package Abaqus as a user-subroutine. A masticatory system model with left and right masseters was used to demonstrate active and passive movement.

RESULTS

The CR was characterised by various experimental data sets and was able to capture a wide variety of passive and active behaviours. Furthermore, the masticatory simulations revealed that joint movement was sensitive to the muscle's in-fibre passive response.

CONCLUSIONS

This user-material provides a "plug and play" template for 3D neuro-musculoskeletal finite element modelling. We hope that this reduces modelling effort, fosters exchange, and contributes to the standardisation of such models.

Electroactive functional microenvironments from bioactive polymers: A new strategy to address cancer

The present work reports on a new approach based on electroactive microenvironments to mitigate skeletal muscle cancer. For that, piezoelectric films based on poly(vinylidene fluoride) have been applied to evaluate the influence of mechano- and/or electrical stimuli on rhabdomyosarcoma (RMS) proliferation. Human embryonal rhabdomyosarcoma (RD) cells were cultured on PVDF pristine films with different surface charge (non-poled, poled+ and poled-) and magnetic composites (10% and 20% Fe₃O₄, and 20% CFO filler content) to allow magneto-mechanical and magnetoelectrical stimulation films. Electrospun PVDF pristine (oriented and randomly) and magnetic (10% Fe₃O₄) fiber mats were also evaluated to take into consideration the morphology effect on cell response. It was found that the mechanical stimuli enhance RMS proliferation whereas the mechano-electrical decreases it. It was also verified that the RD cells proliferate better on randomly oriented fibers, whereas myoblast cells do it better in oriented ones. The obtained results confirm that electroactive microenvironments can be used to develop novel and effective approaches to deal with RMS cancer, that can be extrapolated to others cancer types.

Recurrent neural network to predict hyperelastic constitutive behaviors of the skeletal muscle

Hyperelastic constitutive laws have been commonly used to model the passive behavior of the human skeletal muscle. Despite many efforts, the use of accurate finite element formulations of hyperelastic constitutive laws is still time-consuming for a real-time medical simulation system. The objective of the present study was to develop a deep learning model to predict the hyperelastic constitutive behaviors of the skeletal muscle toward a fast estimation of the muscle tissue stress.A finite element (FE) model of the right psoas muscle was developed. Neo-Hookean and Mooney-Rivlin laws were used. A tensile test was performed with an applied body force. A learning database was built from this model using an automatic probabilistic generation process. A long-short term memory (LSTM) neural network was implemented to predict the stress evolution of the skeletal muscle tissue. A hyperparameter tuning process was conducted. Root mean square error (RMSE) and associated relative error was quantified to evaluate the precision of the predictive capacity of the developed deep learning model. Pearson correlation coefficients (R) was also computed.The nodal displacements and the maximal stresses range from 70 to 227 mm and from 2.79 to 5.61 MPa for Neo-Hookean and Monney-Rivlin laws, respectively. Regarding the LSTM predictions, the RMSE ranges from 224.3 ± 3.9 Pa (8%) to 227.5 [Formula: see text] 5.7 Pa (4%) for Neo-Hookean and Monney-Rivlin laws, respectively. Pearson correlation coefficients (R) of 0.78 [Formula: see text] 0.02 and 0.77 [Formula: see text] 0.02 were obtained for Neo-Hookean and Monney-Rivlin laws, respectively.The present study showed that, for the first time, the use of a deep learning model can reproduce the time-series behaviors of the complex FE formulations for skeletal muscle modeling. In particular, the use of a LSTM neural network leads to a fast and accurate surrogate model for the in silico prediction of the hyperelastic constitutive behaviors of the skeletal muscle. As perspectives, the developed deep learning model will be integrated into a real-time medical simulation of the skeletal muscle for prosthetic socket design and childbirth simulator.

HyperMSM: A new MSM variant for efficient simulation of dynamic soft-tissue deformations

BACKGROUND AND OBJECTIVE

Fast, accurate, and stable simulation of soft tissue deformation is a challenging task. Mass-Spring Model (MSM) is one of the popular methods used for this purpose for its simple implementation and potential to provide fast dynamic simulations. However, accurately simulating a non-linear material within the mass-spring framework is still challenging. The objective of the present study is to develop and evaluate a new efficient hyperelastic Mass-Spring Model formulation to simulate the Neo-Hookean deformable material, called HyperMSM.

METHODS

Our novel HyperMSM formulation is applicable for both tetrahedral and hexahedral mesh configurations and is compatible with the original projective dynamics solver. In particular, the proposed MSM variant includes springs with variable rest-lengths and a volume conservation constraint. Two applications (transtibial residual limb and the skeletal muscle) were conducted.

RESULTS

Compared to finite element simulations, obtained results show RMSE ranges of [2.8%-5.2%] and [0.46%-5.4%] for stress-strain and volumetric responses respectively for strains ranging from -50% to +100%. The displacement error range in our transtibial residual limb simulation is around [0.01mm-0.7 mm]. The RMSE range of relative nodal displacements for the skeletal psoas muscle model is [0.4%-1.7%].

CONCLUSIONS

Our novel HyperMSM formulation allows hyperelastic behavior of soft tissues to be described accurately and efficiently within the mass-spring framework. As perspectives, our formulation will be enhanced with electric behavior toward a multi-physical soft tissue mass-spring modeling framework. Then, the coupling with an augmented reality environment will be performed.

Operation Safety of a 2-DoF Planar Mechanism for Arm Rehabilitation

The operation safety of rehabilitation devices must be addressed early in the development process and before being tested on people. In this paper, the operation safety of a 2-DoF (degrees of freedom) planar mechanism for arm rehabilitation is addressed. Then, the safety and efficiency of the device operation is assessed through the Transmission Index (TI) distribution in its workspace. Furthermore, the produced stresses on the human arm are assessed via the FEM (finite element method) when the rehabilitation device reaches five critical positions within its workspace. The TI distribution showed that the proposed design has a proper behaviour from a force transmission point of view, avoiding any singular configuration that might cause a control failure and subsequent risk for the user and supporting the user’s motion with a good efficiency throughout its operational workspace. The FEM analysis showed that Nurse operation is safe for the human arm since a negligible maximum stress of 6.55 × 103 N/m2 is achieved by the human arm when the device is located on the evaluated critical positions.

Quantification of the demands of cricket bowling and the relationship to injury risk: a systematic review

BACKGROUND

Bowling in cricket is a complex sporting movement which, despite being well characterised, still produces a significant number of injuries each year. Fast bowlers are more likely to be injured than any other playing role. Frequency, duration, intensity and volume of bowling, which have been generalised as measurements of workload, are thought to be risk factors for injuries. Injury rates of fast bowlers have not reduced in recent years despite the implementation of various workload monitoring practices.

OBJECTIVE

To identify the variables used to quantify frequency, intensity, time and volume of bowling; and evaluate relationships between these variables and injury risk.

METHODS

Six online databases were systematically searched for studies on fast bowling that included terms related to workload. Population characteristics, variables relating to demand and their relationship to standardised definitions of physical activity were extracted from all included studies.

RESULTS

Bowling workload is typically quantified through measures of frequency, duration, or indirect intensity, with few studies reporting on bowling volume.

CONCLUSIONS

When reported on, volume was often described using imprecise or insufficient measures of intensity. There is a need to develop more appropriate measures of intensity during bowling and improve the quality of evidence to inform on bowling programme management practices.

Inverse identification of hyperelastic constitutive parameters of skeletal muscles via optimization of AI techniques

Studies on the deformation characteristics and stress distribution in loaded skeletal muscles are of increasing importance. Reliable prediction of hyperelastic material parameters requires an inverse process, which possesses challenges. This work proposes two inverse procedures to identify the hyperelastic material parameters of skeletal muscles. The first one integrates nonlinear finite element method (FEM), random forest (RF) model, and Bayesian optimization (BO) algorithm. The other one integrates FEM, RF and hybrid Grid Search (GS), and Random Search (RS) algorithm. FEM models are first established to simulate nonlinear deformation of skeletal muscles subject to compression based on nonlinear mechanics principals. A dataset of nonlinear relationship between the nominal stress and principal stretch of skeletal muscles is created using our FEM models and the nonlinear relationship is learned through RF model. The BO, hybrid GS and RS algorithms are used to adjust the major model parameters in RF. Then the optimized RF is utilized to predict hyperelastic material parameters of skeletal muscles, with the help of uniaxial compression experiments. Intensive studies also have been carried out to compare the RF-BO approach with RF-Search approach, and the comparison results show that RF-BO approach is an effective and accurate approach to identify the hyperelastic material parameters of skeletal muscles. The present RF-BO model can be further extended for the predictions of constitutive parameters of other types of nonlinear soft materials.

Directional Dependence of Experimental Trunk Stiffness: Role of Muscle-Stiffness Variation of Nonneural Origin

Trunk stiffness is an important parameter for trunk stability analysis and needs to be evaluated accurately. Discrepancies regarding the dependence of trunk stiffness on the direction of movement in the sagittal plane suggest inherent sources of error that require explanation. In contrast to the common assumption that the muscle stiffness remains constant prior to the induction of a reflex during position perturbations, it is postulated that muscle-stiffness changes of nonneural origin occur and alter the experimental trunk stiffness, causing it to depend on the sagittal direction. This is confirmed through reinterpretation of existing test data for a healthy subject, numerical simulation, and sensitivity analysis using a biomechanical model. The trunk stiffness is determined through a static approach (in forward and backward directions) and compared with the model stiffness for assumed scenarios involving deactivated muscles. The difference in stiffness between the opposite directions reaches 17.5% without a preload and decreases when a moderate vertical preload is applied. The increased muscle activation induced by preloads or electrical stimuli explains the apparent discrepancies observed in previous studies. The experimental stiffness invariably remains between low and high model-stiffness estimates based on extreme scenarios of the postulated losses of muscle activation, thereby confirming our hypothesis.

The Politics of Chronic LBP: Can We Rely on a Proxy-Vote? Linking Multifidus Intra-Myo-Cellular Lipid (IMCL) Fatty Infiltration With Arthrogenic Muscle Inhibition (AMI)-induced Chronic Nonspecific Low Back Pain

STUDY DESIGN

Retrospective review of the literature.

OBJECTIVE

To update recent trends in the use of magnetic resonance spectroscopy (MRS) analysis for CLBP.

SUMMARY OF BACKGROUND DATA

The lumbar multifidus (MF) muscle has drawn sustained interest for some time, particularly related to its structure, role in spinal stability, and its association and clinical significance with CLBP. Additionally, the presence of MF-arthrogenic muscle inhibition (AMI) and its relation to induced CLBP, through depleted lumbar stabilization, has gained increased recognition. In contrast, the differential diagnostic use of MRS analysis has suggested specific links between the presence of MF myo-cellular lipid (MCL) infiltration and CLBP patients.

METHODS

Review of the literature related to CLBP with the keywords MCL, MRS analysis, and MF-AMI.

RESULTS

No articles discussed CLBP using the three key concepts in a single context. The use of MRS analysis has the capacity to distinguish between Extra-MCL (EMCL) and intra-MCL (IMCL) infiltration within the lumbar MF. It is suggested that EMCLs are more likely to be associated with age-related change, while the IMCLs appear more likely to be associated with the presence of CLBP. The increased recognition of MF-AMI as a primary cause of CLBP, and the potential that AMI parallels the presence of IMCLs, facilitates possible use of MRS as a means to quantify the basis of lumbar MF-AMI CLBP, and that proportional IMCL changes in the MF could serve as a 'proxy' to indicate the effectiveness of interventions directed at MF activation.

CONCLUSIONS

It may be possible for IMCLs to serve as a 'proxy' prognostic marker of lumbar MF-AMI in CLBP patients. Further, if this assertion were correct, then reductions in IMCLs could potentially quantify recovery and the efficacy of rehabilitation management strategies directed at lumbar MF activation.Level of Evidence: 5.

Surface-based modeling of muscles: Functional simulation of the shoulder

Musculoskeletal simulations are an essential tool for studying functional implications of pathologies and of potential surgical outcomes, e.g., for the complex shoulder anatomy. Most shoulder models rely on line-segment approximation of muscles with potential limitations. Comprehensive shoulder models based on continuum-mechanics are scarce due to their complexity in both modeling and computation. In this paper, we present a surface-based modeling approach for muscles, which simplifies the modeling process and is efficient for computation. We propose to use surface geometries for modeling muscles, and devise an automatic approach to generate such models, given the locations of the origin and insertion of tendons. The surfaces are expressed as higher-order tensor B-splines, which ensure smoothness of the geometrical representation. They are simulated as membrane elements within a finite element simulation. This is demonstrated on a comprehensive model of the upper limb, where muscle activations needed to perform desired motions are obtained by using inverse dynamics. In synthetic examples, we demonstrate our proposed surface elements both to be easy to customize (e.g., with spatially varying material properties) and to be substantially (up to 12 times) faster in simulation compared to their volumetric counterpart. With our presented automatic approach of muscle wrapping around bones, the humeral head is exemplified to be wrapped physiologically consistently with surface elements. Our functional simulation is shown to successfully replicate a tracked shoulder motion during activities of daily living. We demonstrate surface-based models to be a numerically stable and computationally efficient compromise between line-segment and volumetric models, enabling anatomical correctness, subject-specific customization, and fast simulations, for a comprehensive simulation of musculoskeletal motion.

A Systematic Review of Real-Time Medical Simulations with Soft-Tissue Deformation: Computational Approaches, Interaction Devices, System Architectures, and Clinical Validations

Simulating deformations of soft tissues is a complex engineering task, and it is even more difficult when facing the constraint between computation speed and system accuracy. However, literature lacks of a holistic review of all necessary aspects (computational approaches, interaction devices, system architectures, and clinical validations) for developing an effective system of soft-tissue simulations. This paper summarizes and analyses recent achievements of resolving these issues to estimate general trends and weakness for future developments. A systematic review process was conducted using the PRISMA protocol with three reliable scientific search engines (ScienceDirect, PubMed, and IEEE). Fifty-five relevant papers were finally selected and included into the review process, and a quality assessment procedure was also performed on them. The computational approaches were categorized into mesh, meshfree, and hybrid approaches. The interaction devices concerned about combination between virtual surgical instruments and force-feedback devices, 3D scanners, biomechanical sensors, human interface devices, 3D viewers, and 2D/3D optical cameras. System architectures were analysed based on the concepts of system execution schemes and system frameworks. In particular, system execution schemes included distribution-based, multithread-based, and multimodel-based executions. System frameworks are grouped into the input and output interaction frameworks, the graphic interaction frameworks, the modelling frameworks, and the hybrid frameworks. Clinical validation procedures are ordered as three levels: geometrical validation, model behavior validation, and user acceptability/safety validation. The present review paper provides useful information to characterize how real-time medical simulation systems with soft-tissue deformations have been developed. By clearly analysing advantages and drawbacks in each system development aspect, this review can be used as a reference guideline for developing systems of soft-tissue simulations.

An inverse model of the mechanical response of passive skeletal muscle: Implications for microstructure

The constitutive response of passive skeletal muscle is important for many human body modelling applications, but modelling the tension-compression asymmetry and the anisotropy observed in ex-vivo samples is challenging. Existing microstructural models do not capture the full three-dimensional response while models suitable for application in finite element environments mostly have a limited microstructural basis and cannot capture the observed Poisson's ratios. The aim of this paper is to derive an inverse model based on the microstructure of a skeletal muscle that can predict its passive mechanical response. The model parameters and predictions were derived and assessed by comparison with published experimental stress-strain response and Poisson's ratio data. Results show a close match for both predicted stress-strain response for fibre and cross-fibre direction deformations and similar Poisson's ratio values. Some microstructural observations which strengthen our understanding of the role of the collagen network and intramuscular pressure are also provided.

Microstructural analysis of skeletal muscle force generation during aging

Human aging results in a progressive decline in the active force generation capability of skeletal muscle. While many factors related to the changes of morphological and structural properties in muscle fibers and the extracellular matrix (ECM) have been considered as possible reasons for causing age-related force reduction, it is still not fully understood why the decrease in force generation under eccentric contraction (lengthening) is much less than that under concentric contraction (shortening). Biomechanically, it was observed that connective tissues (endomysium) stiffen as ages, and the volume ratio of connective tissues exhibits an age-related increase. However, limited skeletal muscle models take into account the microstructural characteristics as well as the volume fraction of tissue material. This study aims to provide a numerical investigation in which the muscle fibers and the ECM are explicitly represented to allow quantitative assessment of the age-related force reduction mechanism. To this end, a fiber-level honeycomb-like microstructure is constructed and modeled by a pixel-based Reproducing Kernel Particle Method (RKPM), which allows modeling of smooth transition in biomaterial properties across material interfaces. The numerical investigation reveals that the increased stiffness of the passive materials of muscle tissue reduces the force generation capability under concentric contraction while maintains the force generation capability under eccentric contraction. The proposed RKPM microscopic model provides effective means for the cellular-scale numerical investigation of skeletal muscle physiology. NOVELTY STATEMENT: A cellular-scale honeycomb-like microstructural muscle model constructed from a histological cross-sectional image of muscle is employed to study the causal relations between age-associated microstructural changes and age-related force loss using Reproducing Kernel Particle Method (RKPM). The employed RKPM offers an effective means for modeling biological materials based on pixel points in the medical images and allow modeling of smooth transition in the material properties across interfaces. The proposed microstructure-informed muscle model enables quantitative evaluation on how cellular-scale compositions contribute to muscle functionality and explain differences in age-related force changes during concentric, isometric and eccentric contractions.