A musculoskeletal model of the lumbar spine using ArtiSynth – development and validation

Muscle Strength Identification Based on Isokinetic Testing and Spine Musculoskeletal Modeling

Subject-specific spinal musculoskeletal modeling can help understand the spinal loading mechanism during human locomotion. However, existing literature lacks methods to identify the maximum isometric strength of individual spinal muscles. In this study, a muscle strength identification method combining isokinetic testing and musculoskeletal simulations was proposed, and the influence of muscle synergy and intra-abdominal pressure (IAP) on identified spinal muscle strength was further discussed. A multibody dynamic model of the spinal musculoskeletal system was established and controlled by a feedback controller. Muscle strength parameters were adjusted based on the measured isokinetic moments, and muscle synergy vectors and the IAP piston model were further introduced. The results of five healthy subjects showed that the proposed method successfully identified the subject-specific spinal flexor/extensor strength. Considering the synergistic activations of antagonist muscles improved the correlation between the simulated and measured spinal moments, and the introduction of IAP slightly increased the identified spinal extensor strength. The established method is beneficial for understanding spinal loading distributions for athletes and patients with sarcopenia.

An Enhanced Spine Model Validated for Simulating Dynamic Lifting Tasks in OpenSim

A fully articulated thoracolumbar spine model had been previously developed in OpenSim and had been extensively validated against experimental data during various static tasks. In the present study, we enhanced this detailed musculoskeletal model by adding the role of passive structures and adding kinematic constraints to make it suitable for dynamic tasks. We validated the spinal forces estimated by this enhanced model during nine dynamic lifting/lowering tasks. Moreover, we recently developed and evaluated five approaches in OpenSim to model the external loads applied to the hands during lifting/lowering tasks, and in the present study, we assessed which approach results in more accurate spinal forces. Regardless of the external load modeling approach, the maximum forces predicted by our enhanced spine model across all tasks, as well as the pattern of estimated spinal forces within each task, showed strong correlations (r-values and cross-correlation coefficients > 0.9) with experimental data. Given the biofidelity of our enhanced model, its accessibility via the open-source OpenSim software, and the extent to which this model has been validated, we recommend it for applications requiring estimation of spinal forces during lifting/lowering tasks using multibody-based models and inverse dynamic analyses.

Muscle-driven forward dynamic active hybrid model of the lumbosacral spine: combined FEM and multibody simulation

Most spine models belong to either the musculoskeletal multibody (MB) or finite element (FE) method. Recently, coupling of MB and FE models has increasingly been used to combine advantages of both methods. Active hybrid FE-MB models, still rarely used in spine research, avoid the interface and convergence problems associated with model coupling. They provide the inherent ability to account for the full interplay of passive and active mechanisms for spinal stability. In this paper, we developed and validated a novel muscle-driven forward dynamic active hybrid FE-MB model of the lumbosacral spine (LSS) in ArtiSynth to simultaneously calculate muscle activation patterns, vertebral movements, and internal mechanical loads. The model consisted of the rigid vertebrae L1-S1 interconnected with hyperelastic fiber-reinforced FE intervertebral discs, ligaments, facet joints, and force actuators representing the muscles. Morphological muscle data were implemented via a semi-automated registration procedure. Four auxiliary bodies were utilized to describe non-linear muscle paths by wrapping and attaching the anterior abdominal muscles. This included an abdominal plate whose kinematics was optimized using motion capture data from upper body movements. Intra-abdominal pressure was calculated from the forces of the abdominal muscles compressing the abdominal cavity. For the muscle-driven approach, forward dynamics assisted data tracking was used to predict muscle activation patterns that generate spinal postures and balance the spine without prescribing accurate spinal kinematics. During calibration, the maximum specific muscle tension and spinal rhythms resulting from the model dynamics were evaluated. To validate the model, load cases were simulated from -10° extension to +30° flexion with weights up to 20 kg in both hands. The biomechanical model responses were compared with in vivo literature data of intradiscal pressures, intra-abdominal pressures, and muscle activities. The results demonstrated high agreement with this data and highlight the advantages of active hybrid modeling for the LSS. Overall, this new self-contained tool provides a robust and efficient estimation of LSS biomechanical responses under in vivo similar loads, for example, to improve pain treatment by spinal stabilization therapies.

Multibody Models of the Thoracolumbar Spine: A Review on Applications, Limitations, and Challenges

Numerical models of the musculoskeletal system as investigative tools are an integral part of biomechanical and clinical research. While finite element modeling is primarily suitable for the examination of deformation states and internal stresses in flexible bodies, multibody modeling is based on the assumption of rigid bodies, that are connected via joints and flexible elements. This simplification allows the consideration of biomechanical systems from a holistic perspective and thus takes into account multiple influencing factors of mechanical loads. Being the source of major health issues worldwide, the human spine is subject to a variety of studies using these models to investigate and understand healthy and pathological biomechanics of the upper body. In this review, we summarize the current state-of-the-art literature on multibody models of the thoracolumbar spine and identify limitations and challenges related to current modeling approaches.

Evaluation of spinal force normalization techniques

Division normalization is commonly used in biomechanics studies to remove the effect of anthropometric differences (e.g., body weight) on kinetic variables, facilitating comparison across a population. In spine biomechanics, spinal forces are commonly divided by the body weight or the intervertebral load during a standing posture. However, it has been suggested that offset and power curve normalization are more appropriate than division normalization for normalizing kinetic variables such as ground reaction forces during walking and running. The present study investigated, for the first time, the effectiveness of four techniques for normalizing spinal forces to remove the effect of body weight. Spinal forces at all lumbar levels were estimated using a detailed OpenSim musculoskeletal model of the spine for 11 scaled models (50-100 kg) and during 13 trunk flexion tasks. Pearson correlations of raw and normalized forces against body weight were used to assess the effectiveness of each normalization technique. Body weight and standing division normalization could only successfully normalize L₄L₅ spinal forces in three tasks, and L₅S₁ loads in five and three tasks, respectively; however, offset and power curve normalization techniques were successful across all lumbar spine levels and all tasks. Offset normalization successfully removed the effect of body weight and maintained the influence of flexion angle on spinal forces. Thus, we recommend offset normalization to account for anthropometric differences in studies of spinal forces.

Computational lumbar spine models: A literature review

BACKGROUND

Computational spine models of various types have been employed to understand spine function, assess the risk that different activities pose to the spine, and evaluate techniques to prevent injury. The areas in which these models are applied has expanded greatly, potentially beyond the appropriate scope of each, given their capabilities. A comprehensive understanding of the components of these models provides insight into their current capabilities and limitations.

METHODS

The objective of this review was to provide a critical assessment of the different characteristics of model elements employed across the spectrum of lumbar spine modeling and in newer combined methodologies to help better evaluate existing studies and delineate areas for future research and refinement.

FINDINGS

A total of 155 studies met selection criteria and were included in this review. Most current studies use either highly detailed Finite Element models or simpler Musculoskeletal models driven with in vivo data. Many models feature significant geometric or loading simplifications that limit their realism and validity. Frequently, studies only create a single model and thus can't account for the impact of subject variability. The lack of model representation for certain subject cohorts leaves significant gaps in spine knowledge. Combining features from both types of modeling could result in more accurate and predictive models.

INTERPRETATION

Development of integrated models combining elements from different model types in a framework that enables the evaluation of larger populations of subjects could address existing voids and enable more realistic representation of the biomechanics of the lumbar spine.

Biomechanical Properties of Paraspinal Muscles Influence Spinal Loading—A Musculoskeletal Simulation Study

Paraspinal muscles are vital to the functioning of the spine. Changes in muscle physiological cross-sectional area significantly affect spinal loading, but the importance of other muscle biomechanical properties remains unclear. This study explored the changes in spinal loading due to variation in five muscle biomechanical properties: passive stiffness, slack sarcomere length (SSL), in situ sarcomere length, specific tension, and pennation angle. An enhanced version of a musculoskeletal simulation model of the thoracolumbar spine with 210 muscle fascicles was used for this study and its predictions were validated for several tasks and multiple postures. Ranges of physiologically realistic values were selected for all five muscle parameters and their influence on L4-L5 intradiscal pressure (IDP) was investigated in standing and 36° flexion. We observed large changes in IDP due to changes in passive stiffness, SSL, in situ sarcomere length, and specific tension, often with interesting interplays between the parameters. For example, for upright standing, a change in stiffness value from one tenth to 10 times the baseline value increased the IDP only by 91% for the baseline model but by 945% when SSL was 0.4 μm shorter. Shorter SSL values and higher stiffnesses led to the largest increases in IDP. More changes were evident in flexion, as sarcomere lengths were longer in that posture and thus the passive curve is more influential. Our results highlight the importance of the muscle force-length curve and the parameters associated with it and motivate further experimental studies on in vivo measurement of those properties.

EMG optimization in OpenSim: A model for estimating lower back kinetics in gait

Participant-specific musculoskeletal models are needed to accurately estimate lower back internal kinetic demands and injury risk. In this study we developed the framework for incorporating an electromyography optimization (EMGopt) approach within OpenSim (https://simtk.org/projects/emg_opt_tool) and evaluated lower back demands estimated from the model during gait. Kinematic, external kinetic, and EMG data were recorded from six participants as they performed walking and carrying tasks on a treadmill. For evaluation, predicted lumbar vertebral joint forces were compared to those from a generic static optimization approach (SOpt) and to previous studies. Further, model-estimated muscle activations were compared to recorded EMG, and model sensitivity to day-to-day EMG variability was evaluated. Results showed the vertebral joint forces from the model were qualitatively similar in pattern and magnitude to literature reports. Compared to SOpt, the EMGopt approach predicted larger joint loads (p<.01) with muscle activations better matching individual participant EMG patterns. L5/S1 vertebral joint forces from EMGopt were sensitive to the expected variability of recorded EMG, but the magnitude of these differences (±4%) did not impact between-task comparisons. Despite limitations inherent to such models, the proposed musculoskeletal model and EMGopt approach appears well-suited for evaluating internal lower back demands during gait tasks.

Subject-Specific Alignment and Mass Distribution in Musculoskeletal Models of the Lumbar Spine

Musculoskeletal modeling is a well-established method in spine biomechanics and generally employed for investigations concerning both the healthy and the pathological spine. It commonly involves inverse kinematics and optimization of muscle activity and provides detailed insight into joint loading. The aim of the present work was to develop and validate a procedure for the automatized generation of semi-subject-specific multi-rigid body models with an articulated lumbar spine. Individualization of the models was achieved with a novel approach incorporating information from annotated EOS images. The size and alignment of bony structures, as well as specific body weight distribution along the spine segments, were accurately reproduced in the 3D models. To ensure the pipeline’s robustness, models based on 145 EOS images of subjects with various weight distributions and spinopelvic parameters were generated. For validation, we performed kinematics-dependent and segment-dependent comparisons of the average joint loads obtained for our cohort with the outcome of various published in vivo and in situ studies. Overall, our results agreed well with literature data. The here described method is a promising tool for studying a variety of clinical questions, ranging from the evaluation of the effects of alignment variation on joint loading to the assessment of possible pathomechanisms involved in adjacent segment disease.

Credibility assessment of patient-specific biomechanical models to investigate proximal junctional failure in clinical cases with adult spine deformity using ASME V&V40 standard

Computational models are increasingly used to assess spine biomechanics and support surgical planning. However, varying levels of model verification and validation, along with characterization of uncertainty effects limit the level of confidence in their predictive potential. The objective was to assess the credibility of an adult spine deformity instrumentation model for proximal junction failure (PJF) analysis using the ASME V&V40:2018 framework. To assess model applicability, the surgery, erected posture, and flexion movement of actual clinical cases were simulated. The loads corresponding to PJF indicators for a group of asymptomatic patients and a group of PJF patients were compared. Model consistency was demonstrated by finding PJF indicators significantly higher for the simulated PJF vs. asymptomatic patients. A detailed sensitivity analysis and uncertainty quantification were performed to further establish the model credibility.

The effect of vertebral level on biomechanical properties of the lumbar paraspinal muscles in a rat model

INTRODUCTION

Passive mechanical properties of the paraspinal muscles are important to the biomechanical functioning of the spine. In most computational models, the same biomechanical properties are assumed for each paraspinal muscle group, while cross-sectional area or fatty infiltration in these muscles have been reported to differ between the vertebral levels. Two important properties for musculoskeletal modeling are the slack sarcomere length and the tangent modulus. This study aimed to investigate the effect of vertebral level on these biomechanical properties of paraspinal muscles in a rat model.

METHODS

The left paraspinal muscles of 13 Sprague-Dawley rats were exposed under anesthesia. Six muscle biopsies were collected from each rat: three from multifidus (one per each of the L1, L3, and L5 levels) and similarly three from longissimus. Each biopsy was cut into two halves. From one half, two to three single muscle fibers and two to six muscle fiber bundles (14 ± 7 fibers surrounded in their connective tissue) were extracted and mechanically tested in a passive state. From the resulting stress-strain data, tangent modulus was calculated as the slope of the tangent at 30% strain and slack sarcomere length (beyond which passive force starts to develop) was recorded. The other half of each biopsy, which represented the muscle at the fascicle level, was snap frozen, sectioned, stained for Collagen I and its area fraction was measured. To evaluate the effect of spinal level on these biomechanical properties of multifidus and longissimus, one-way repeated measures ANOVA (p < 0.05) was performed for tangent modulus and slack sarcomere length, while for collagen I content linear mixed-models analysis was adopted.

RESULTS

In total, 192 fibers and 262 fiber bundles were mechanically tested. For both muscle groups, no significant difference in tangent modulus of the single fibers was detected between the three spinal levels (p = 0.9 for multifidus and p = 0.08 for longissimus). Similarly, the tangent modulus values for the fiber bundles were not significantly different between the three spinal levels (p = 0.13 for multifidus and p = 0.49 for longissimus). In both muscle groups, the slack sarcomere lengths were not different among the spinal levels except for multifidus fibers (p = 0.02). Collagen I area fraction in muscle fascicles averaged 6.8% for multifidus and 5.3% for longissimus and was not different between the spinal levels.

DISCUSSION

The results of this study highlighted that the tangent modulus, slack sarcomere length, and collagen I content of the lumbar paraspinal muscles are independent of spinal level. This finding provides the basis for the assumption of similar mechanical properties along a paraspinal muscle group.

Preliminary investigation of spinal level and postural effects on thoracic muscle morphology with upright open MRI

OBJECTIVE

Spinal-muscle morphological differences between weight-bearing and supine postures have potential diagnostic, prognostic, and therapeutic applications. While the focus to date has been on cervical and lumbar regions, recent findings have associated spinal deformity with smaller paraspinal musculature in the thoracic region. We aim to quantitatively investigate the morphology of trapezius (TZ), erector spinae (ES) and transversospinalis (TS) muscles in upright postures with open upright MRI and also determine the effect of level and posture on the morphological measures.

METHODS

Six healthy volunteers (age 26 ± 6 years) were imaged (0.5 T MROpen, Paramed, Genoa, Italy) in four postures (supine, standing, standing with 30° flexion, and sitting). Two regions of the thorax, middle (T4-T5), and lower (T8-T9), were scanned separately for each posture. 2D muscle parameters such as cross-sectional area (CSA) and position (radius and angle) with respect to the vertebral body centroid were measured for the three muscles. Effect of spinal level and posture on muscle parameters was examined using 2-way repeated measures ANOVA separately for T4-T5 and T8-T9 regions.

RESULTS

The TZ CSA was smaller (40%, P = .0027) at T9 than at T8. The ES CSA was larger at T5 than at T4 (12%, P = .0048) and at T9 than at T8 (10%, P = .0018). TS CSA showed opposite trends at the two spinal regions with it being smaller (16%, P = .0047) at T5 than at T4 and larger (11%, P = .0009) at T9 than at T8. At T4-T5, the TZ CSA increased (up to 23%), and the ES and TS CSA decreased (up to 10%) in upright postures compared to supine.

CONCLUSION

Geometrical parameters that describe muscle morphology in the thorax change with level and posture. The increase in TZ CSA in upright postures could result from greater activation while upright. The decrease in ES CSA in flexed positions likely represents passive stretching compared to neutral posture.

An Enhanced Planar Linked Segment Model for Predicting Lumbar Spine Loads during Symmetric Lifting Tasks

The present technical note aimed at enriching the planar linked segment model originally proposed by Chaffin with the prediction of the moment arm and of the orientation of the line of action of the back extensor muscles during symmetric lifting tasks. The prediction equations proposed by van Dieen and de Looze for their single equivalent muscle model were used for such a purpose. Their prediction was based on the thorax-to-pelvis flexion angle as computed from 3D video-based motion capture. In order to make these prediction equations compliant with a two-dimensional analysis, the planar angle formed by the segment joining L5/S1 to the shoulder with the longitudinal axis of the pelvis was introduced. This newly computed planar trunk flexion angle was used to feed van Dieen and de Looze’s equations, comparing the results with the original model. A full-body Plug-in-Gait model relative to 10 subjects performing manual lifting activities using a stoop and a squat technique was used for model validation. A strong association was found between the proposed planar trunk flexion angle and that used by van Dieen and de Looze (r = 0.970). A strong association and a high level of agreement were found between the back extensor muscle moment arm (r = 0.965; bias < 0.001 m; upper limit of agreement (LOA) = 0.002 m; lower LOA < 0.001 m) and the orientation of the line of action (r = 0.970; bias = 2.8°; upper LOA = 5.3°; lower LOA = 0.2°) as computed using the two methods. For both the considered variables, the prediction error fell within the model sensitivity.