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

Biomechanical analysis of complications following T10-Pelvis spinal fusion: A population based computational study

Proximal junctional kyphosis (PJK) and proximal junctional failure (PJF) are challenging complications of long fusion constructs for the treatment of adult spinal deformity. The objective of this study is to understand the biomechanical stresses proximal to the upper instrumentation of a T10-pelvis fusion in a large patient cohort. The pre-fusion models were subject-specific thoracolumbar spine models that incorporate the height, weight, spine curvature, and muscle morphology of 250 individuals from the Framingham Heart Study Multidetector CT Study. To create post-fusion models, the subject-specific models were further modified to eliminate motion between the intervertebral joints from T10 to the pelvis. OpenSim analysis tools were used to calculate the medial lateral shear force, anterior posterior shear force, and compressive force on the T9 vertebra during the static postures. Differences between pre-fusion and post-fusion T9 biomechanics were consistent between increased segmental mobility and unchanged segmental mobility conditions. For all static postures, compression decreased (p < 0. 0005). Anterior-posterior shear force significantly increased (p < 0. 0005) during axial twist and significantly increased (p < 0. 0005) during trunk flexion. Medial lateral shear force significantly increased (p < 0. 0005) during axial twist. This computational study provided the first use of subject-specific models to investigate the biomechanics of long spinal fusions. Patients undergoing T10-Pelvis fusion were predicted to have increased shear forces and decreased compressive force at the T9 vertebra, independent of change in segmental mobility. The computational model shows potential for the investigation of spinal fusion biomechanics to reduce the risk of PJK or PJF.

Using inertial measurement units to estimate spine joint kinematics and kinetics during walking and running

Optical motion capture (OMC) is considered the best available method for measuring spine kinematics, yet inertial measurement units (IMU) have the potential to collect data outside the laboratory. When combined with musculoskeletal modeling, IMU technology may be used to estimate spinal loads in real-world settings. To date, IMUs have not been validated for estimates of spinal movement and loading during both walking and running. Using OpenSim Thoracolumbar Spine and Ribcage models, we compare IMU and OMC estimates of lumbosacral (L5/S1) and thoracolumbar (T12/L1) joint angles, moments, and reaction forces during gait across six speeds for five participants. For comparisons, time series are ensemble averaged over strides. Comparisons between IMU and OMC ensemble averages have low normalized root mean squared errors (< 0.3 for 81% of comparisons) and high, positive cross-correlations (> 0.5 for 91% of comparisons), suggesting signals are similar in magnitude and trend. As expected, joint moments and reaction forces are higher during running than walking for IMU and OMC. Relative to OMC, IMU overestimates joint moments and underestimates joint reaction forces by 20.9% and 15.7%, respectively. The results suggest using a combination of IMU technology and musculoskeletal modeling is a valid means for estimating spinal movement and loading.

Effect of personalized spinal profile on its biomechanical response in an EMG-assisted optimization musculoskeletal model of the trunk

Recent developments in musculoskeletal (MS) modeling have been geared towards model customization. Personalization of the spine profile could affect estimates of spinal loading and stability, particularly in the upright standing posture where large inter-subject variations in the lumbar lordosis have been reported. This study investigates the biomechanical consequences of changes in the spinal profile. In 31 participants (healthy and with back pain), (1) the spine external profile was measured, (2) submaximal contractions were recorded in a dynamometer to calibrate the EMG-driven MS model and finally (3) static lifting in the upright standing challenging spine stability while altering load position and magnitude were considered. EMG signals of 12 trunk muscles and angular kinematics of 17 segments were recorded. For each participant, the MS model was constructed using either a generic or a personalized spinal profile and 17 biomechanical outcomes were computed, including individual muscle forces, ratios of muscle group forces, spinal loading and stability parameters. According to the ANOVA results and corresponding effect sizes, personalizing the spine profile induced medium and large effects on about half MS model outcomes related to the trunk muscle forces and negligible to small effects on spinal loading and stability as more aggregate outcomes. These effects are explained by personalized spine profiles that were a little more in extension as well as more pronounced spine curvatures (lordosis and kyphosis). These findings suggest that spine profile personalization should be considered in MS spine modeling as it may impact muscle force prediction and spinal loading.

Validity of evaluating spinal kinetics without participant-specific kinematics

Musculoskeletal models are commonly used to estimate in vivo spinal loads under various loading conditions. Typically, participant-specific measured kinematics (PSMK) are coupled with participant-specific models, but obtaining PSMK data can be costly and infeasible in large studies or clinical practice. Thus, we evaluated two alternative methods to estimate spinal loads without PSMK: 1) ensemble average kinematics (EAK) based on kinematics from all participants; and 2) using separately measured individual kinematics (SMIK) from multiple other participants as inputs, then averaging the resulting loads. This study compares the dynamic spine loading patterns and peak loads in older adults performing five lifting tasks using PSMK, EAK and SMIK. Median root mean square errors of EAK and SMIK methods versus PSMK ranged from 18 to 72% body weight for compressive loads and from 2 to 25% body weight for shear loads, with median cross-correlations ranging from 0.931 to 0.991. The root mean square errors and cross-correlations between repeated PSMK trials fell within similar ranges. Compressive peak loads evaluated by EAK and SMIK were not different than PSMK in 12 of 15 cases, while by comparison repeated PSMK trials were not different in 13 of 15 cases. Overall, the resulting spine loading magnitudes and profiles using EAK or SMIK were not notably different than using a PSMK approach, and differences were not greater than between two PSMK trials. Thus, these findings indicate that these approaches may be used to make reasonable estimates of dynamic spinal loading without direct measurement of participant kinematics.

EMG Validation of a Subject-Specific Thoracolumbar Spine Musculoskeletal Model During Dynamic Activities in Older Adults

Musculoskeletal models can uniquely estimate in vivo demands and injury risk. In this study, we aimed to compare muscle activations from subject-specific thoracolumbar spine OpenSim models with recorded muscle activity from electromyography (EMG) during five dynamic tasks. Specifically, 11 older adults (mean = 65 years, SD = 9) lifted a crate weighted to 10% of their body mass in axial rotation, 2-handed sagittal lift, 1-handed sagittal lift, and lateral bending, and simulated a window opening task. EMG measurements of back and abdominal muscles were directly compared to equivalent model-predicted activity for temporal similarity via maximum absolute normalized cross-correlation (MANCC) coefficients and for magnitude differences via root-mean-square errors (RMSE), across all combinations of participants, dynamic tasks, and muscle groups. We found that across most of the tasks the model reasonably predicted temporal behavior of back extensor muscles (median MANCC = 0.92 ± 0.07) but moderate temporal similarity was observed for abdominal muscles (median MANCC = 0.60 ± 0.20). Activation magnitude was comparable to previous modeling studies, and median RMSE was 0.18 ± 0.08 for back extensor muscles. Overall, these results indicate that our thoracolumbar spine model can be used to estimate subject-specific in vivo muscular activations for these dynamic lifting tasks.

Three-dimensional spinal shape changes during daily activities

MOTIVATION

Intuitive assessment of spinal motion poses a tremendous challenge to both physicians and computer modelers. On the one side, medically detailed analyses of spinal shapes, such as computer tomography or X-ray images, are usually subject to static boundary constraints, thereby omitting dynamic information. On the other side, complex computer simulations often lack proper calibration aside from few control points, particularly regarding the three-dimensional arrangement of the spinal column and its idiomotion.

PURPOSE

Here, we investigate whether the full three-dimensional changes in spinal shape over time can be concisely detected and depicted. Further, we assess which parts of the spine undergo significant changes during various daily activities.

METHODS

We utilize a set of previously published motion capture data from the spinous processes (sacrum up to vertebra C7) of 17 healthy individuals performing the daily tasks of standing, walking, stair climbing, sitting down, and lifting. These three-dimensional, time-dependent marker positions were approximated by a Bézier curve at each time instant. The curves' characteristics, i.e.curvature and torsion, were calculated and juxtaposed for each individual and each activity over time. A statistical parametric mapping revealed significant changes in spinal shape.

RESULTS

We found the individual spinal shape characteristics being recognizably preserved during all activities. The walking task did not significantly alter the spinal curvature, while sitting and forward bending significantly altered the lumber and whole spine curvature, respectively. Torsion did not show any significant alterations.

CONCLUSION

Based on these results, we suggest that individualized dynamic information on spinal shapes can improve (i) the evaluation of (healthy) motion characteristics, (ii) the detection of pathologies, and (iii) individualized computer simulation models.

Deep Learning for Multi-Tissue Segmentation and Fully Automatic Personalized Biomechanical Models from BACPAC Clinical Lumbar Spine MRI

STUDY DESIGN

In vivo retrospective study of fully automatic quantitative imaging feature extraction from clinically acquired lumbar spine magnetic resonance imaging (MRI).

OBJECTIVE

To demonstrate the feasibility of substituting automatic for human-demarcated segmentation of major anatomic structures in clinical lumbar spine MRI to generate quantitative image-based features and biomechanical models.

SETTING

Previous studies have demonstrated the viability of automatic segmentation applied to medical images; however, the feasibility of these networks to segment clinically acquired images has not yet been demonstrated, as they largely rely on specialized sequences or strict quality of imaging data to achieve good performance.

METHODS

Convolutional neural networks were trained to demarcate vertebral bodies, intervertebral disc, and paraspinous muscles from sagittal and axial T1-weighted MRIs. Intervertebral disc height, muscle cross-sectional area, and subject-specific musculoskeletal models of tissue loading in the lumbar spine were then computed from these segmentations and compared against those computed from human-demarcated masks.

RESULTS

Segmentation masks, as well as the morphological metrics and biomechanical models computed from those masks, were highly similar between human- and computer-generated methods. Segmentations were similar, with Dice similarity coefficients of 0.77 or greater across networks, and morphological metrics and biomechanical models were similar, with Pearson R correlation coefficients of 0.69 or greater when significant.

CONCLUSIONS

This study demonstrates the feasibility of substituting computer-generated for human-generated segmentations of major anatomic structures in lumbar spine MRI to compute quantitative image-based morphological metrics and subject-specific musculoskeletal models of tissue loading quickly, efficiently, and at scale without interrupting routine clinical care.

Dependence of trunk muscle size and position on age, height, and weight in a multi-ethnic cohort of middle-aged and older men and women

Trunk muscle size and location relative to the spine are key factors affecting their capacity to assist in trunk movement, strength, and function. There remains limited information on how age, weight and height affect these measurements across multiple spinal levels, and prior studies had limited samples in terms of size and ethnicity. In this study, we measured trunk muscles in coronal plane slices at T4 - L4 of CT scans acquired in 507 participants, aged 40-90 years, from the community-based Framingham Heart Study. Mixed-effects linear regressions, stratified by sex, determined the contributions of age, height and weight, to muscle cross-sectional area (CSA), the distance from the vertebral body centroid (CD), and the in-plane angle of the line between the vertebral body and the muscle centroids (CA). Muscle CSA decreased with higher age by an average of -0.8% per year, but weight (average 0.8% per kg) and height (average -0.05% per cm) had mixed results, with both positive and negative effects depending on muscle group and level. Muscle CD increased with weight by an average of 0.3% per kg, but had mixed effects for age (average 0.8% per year) and height (average 0.1% per cm). Muscle CA had mixed associations with age (average 0.05% per year), weight (average 0.01% per kg) and height (average -0.05% per cm). A prediction program created with these results provides a simple approach for estimating probable values for trunk muscle size and position in the absence of medical imaging.

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.

Validation of an EMG submaximal method to calibrate a novel dynamic EMG-driven musculoskeletal model of the trunk: Effects on model estimates

BACKGROUND

Multijoint EMG-assisted optimization models are reliable tools to predict muscle forces as they account for inter- and intra-individual variations in activation. However, the conventional method of normalizing EMG signals using maximum voluntary contractions (MVCs) is problematic and introduces major limitations. The sub-maximal voluntary contraction (SVC) approaches have been proposed as a remedy, but their performance against the MVC approach needs further validation particularly during dynamic tasks.

METHODS

To compare model outcomes between MVC and SVC approaches, nineteen healthy subjects performed a dynamic lifting task with two loading conditions.

RESULTS

Results demonstrated that these two approaches produced highly correlated results with relatively small absolute and relative differences (<10 %) when considering highly-aggregated model outcomes (e.g. compression forces, stability indices). Larger differences were, however, observed in estimated muscle forces. Although some model outcomes, e.g. force of abdominal muscles, were statistically different, their effect sizes remained mostly small (η_G² ≤ 0.13) and in a few cases moderate (η_G² ≤ 0.165).

CONCLUSION

The findings highlight that the MVC calibration approach can reliably be replaced by the SVC approach when the true MVC exertion is not accessible due to pain, kinesiophobia and/or the lack of proper training.

Effects of geometric individualisation of a human spine model on load sharing: neuro-musculoskeletal simulation reveals significant differences in ligament and muscle contribution

In spine research, two possibilities to generate models exist: generic (population-based) models representing the average human and subject-specific representations of individuals. Despite the increasing interest in subject specificity, individualisation of spine models remains challenging. Neuro-musculoskeletal (NMS) models enable the analysis and prediction of dynamic motions by incorporating active muscles attaching to bones that are connected using articulating joints under the assumption of rigid body dynamics. In this study, we used forward-dynamic simulations to compare a generic NMS multibody model of the thoracolumbar spine including fully articulated vertebrae, detailed musculature, passive ligaments and linear intervertebral disc (IVD) models with an individualised model to assess the contribution of individual biological structures. Individualisation was achieved by integrating skeletal geometry from computed tomography and custom-selected muscle and ligament paths. Both models underwent a gravitational settling process and a forward flexion-to-extension movement. The model-specific load distribution in an equilibrated upright position and local stiffness in the L4/5 functional spinal unit (FSU) is compared. Load sharing between occurring internal forces generated by individual biological structures and their contribution to the FSU stiffness was computed. The main finding of our simulations is an apparent shift in load sharing with individualisation from an equally distributed element contribution of IVD, ligaments and muscles in the generic spine model to a predominant muscle contribution in the individualised model depending on the analysed spine level.

Using static postures to estimate spinal loading during dynamic lifts with participant-specific thoracolumbar musculoskeletal models

Static biomechanical simulations are sometimes used to estimate in vivo kinetic demands because they can be solved efficiently, but this ignores any potential inertial effects. To date, comparisons between static and dynamic analyses of spinal demands have been limited to lumbar joint differences in young males performing sagittal lifts. Here we compare static and dynamic vertebral compressive and shear force estimates during axial, lateral, and sagittal lifting tasks across all thoracic and lumbar vertebrae in older men and women. Participant-specific thoracolumbar full-body musculoskeletal models estimated vertebral forces from recorded kinematics both with and without consideration of dynamic effects, at an identified frame of peak vertebral loading. Static analyses under-predicted dynamic compressive and resultant shear forces, by an average of about 16% for all three lifts across the thoracic and lumbar spine but were highly correlated with dynamic forces (average r² > .95). The study outcomes have the potential to enable standard clinical and occupational estimates using static analyses.

A computational method for estimating trunk muscle activations during gait using lower extremity muscle synergies

One of the surgical treatments for pelvic sarcoma is the restoration of hip function with a custom pelvic prosthesis after cancerous tumor removal. The orthopedic oncologist and orthopedic implant company must make numerous often subjective decisions regarding the design of the pelvic surgery and custom pelvic prosthesis. Using personalized musculoskeletal computer models to predict post-surgery walking function and custom pelvic prosthesis loading is an emerging method for making surgical and custom prosthesis design decisions in a more objective manner. Such predictions would necessitate the estimation of forces generated by muscles spanning the lower trunk and all joints of the lower extremities. However, estimating trunk and leg muscle forces simultaneously during walking based on electromyography (EMG) data remains challenging due to the limited number of EMG channels typically used for measurement of leg muscle activity. This study developed a computational method for estimating unmeasured trunk muscle activations during walking using lower extremity muscle synergies. To facilitate the calibration of an EMG-driven model and the estimation of leg muscle activations, EMG data were collected from each leg. Using non-negative matrix factorization, muscle synergies were extracted from activations of leg muscles. On the basis of previous studies, it was hypothesized that the time-varying synergy activations were shared between the trunk and leg muscles. The synergy weights required to reconstruct the trunk muscle activations were determined through optimization. The accuracy of the synergy-based method was dependent on the number of synergies and optimization formulation. With seven synergies and an increased level of activation minimization, the estimated activations of the erector spinae were strongly correlated with their measured activity. This study created a custom full-body model by combining two existing musculoskeletal models. The model was further modified and heavily personalized to represent various aspects of the pelvic sarcoma patient, all of which contributed to the estimation of trunk muscle activations. This proposed method can facilitate the prediction of post-surgery walking function and pelvic prosthesis loading, as well as provide objective evaluations for surgical and prosthesis design decisions.

Construction of the Adjusted Scoliosis 3D Finite Element Model and Biomechanical Analysis under Gravity

OBJECTIVE

Adolescent idiopathic scoliosis (AIS) is a three-dimensional structural deformity of the spine caused by the disruption of the biomechanical balance of the spine. However, the current biomechanical modeling and analysis methods of scoliosis cannot really describe the real state of the spine. This study aims to propose a high-precision biomechanical modeling and analysis method that can reflect the spinal state under gravity and provide a theoretical basis for therapeutics.

METHODS

Combining CT and X-ray images of AIS patients, this study constructed an adjusted three-dimensional model and FE model of the spine corresponding to the patient's gravity position, including vertebral bodies, intervertebral discs, ribs, costal cartilage, ligaments, and facet cartilage. Then, the displacement and stress of the spine under gravity were analyzed.

RESULTS

A model of the T1-Sacrum with 1.7 million meshes was constructed. After adding the gravity condition, the maximum displacement point was at T1 of thoracic vertebra (20.4 mm). The analysis indicates that the stress on the lower surface of the vertebral body in thoracolumbar scoliosis tended to be locally concentrated, especially on the concave side of the primary curvature's vertebral body (the maximum stress on the lower surface of T9 is 32.33 MPa) and the convex side of the compensatory curvature's vertebral body (the maximum stress on the lower surface of L5 is 41.97 MPa).

CONCLUSION

This study provides a high-precision modeling and analysis method for scoliosis with full consideration of gravity. The reliability of the method was verified based on patient data. This model can be used to analyze the biomechanical characteristics of patients in the treatment plan design stage.

Augmenting the Cobb angle: Three-dimensional analysis of whole spine shapes using Bézier curves

BACKGROUND AND OBJECTIVE

The identification and classification of pathological spinal deformities poses a major challenge to any diagnostician. First, available medical images are usually two-dimensional projections, obscuring elaborated spatial information. Second, several measurement techniques with different thresholds for certain clinical syndromes make it difficult to classify measured results. Here, a method is presented to augment and standardize the analysis of spinal shapes in three dimensions.

METHODS

Regarding the first limitation, (semi-)automatic, three-dimensional segmentation techniques of medical images have already been developed. To overcome the second, we propose here a representation of the whole spine by a Bézier curve using the vertebral centers as control points. After normalization, a differential-geometric approach yields information on curvature and torsion at each spinal level as well as in between.

RESULTS

Based on literature data and multi-body simulations, we show how these quantities alter with individual posture and during motion. Robustness with respect to missing data is investigated. Approaches towards the identification of spinal disorders are motivated.

CONCLUSION

Our results emphasize the need for individualizable identification and classification of spinal deformities and give an outlook on how it might be achieved. The presented methodology constitutes the first fully three-dimensional analysis of spinal shapes, i.e. without the requirement of certain physiological planes (e.g. the sagittal plane) or landmarks (e.g. the apex vertebra).

Evaluation of Load-To-Strength Ratios in Metastatic Vertebrae and Comparison With Age- and Sex-Matched Healthy Individuals

Vertebrae containing osteolytic and osteosclerotic bone metastases undergo pathologic vertebral fracture (PVF) when the lesioned vertebrae fail to carry daily loads. We hypothesize that task-specific spinal loading patterns amplify the risk of PVF, with a higher degree of risk in osteolytic than in osteosclerotic vertebrae. To test this hypothesis, we obtained clinical CT images of 11 cadaveric spines with bone metastases, estimated the individual vertebral strength from the CT data, and created spine-specific musculoskeletal models from the CT data. We established a musculoskeletal model for each spine to compute vertebral loading for natural standing, natural standing + weights, forward flexion + weights, and lateral bending + weights and derived the individual vertebral load-to-strength ratio (LSR). For each activity, we compared the metastatic spines' predicted LSRs with the normative LSRs generated from a population-based sample of 250 men and women of comparable ages. Bone metastases classification significantly affected the CT-estimated vertebral strength (Kruskal-Wallis, p < 0.0001). Post-test analysis showed that the estimated vertebral strength of osteosclerotic and mixed metastases vertebrae was significantly higher than that of osteolytic vertebrae (p = 0.0016 and p = 0.0003) or vertebrae without radiographic evidence of bone metastasis (p = 0.0010 and p = 0.0003). Compared with the median (50%) LSRs of the normative dataset, osteolytic vertebrae had higher median (50%) LSRs under natural standing (p = 0.0375), natural standing + weights (p = 0.0118), and lateral bending + weights (p = 0.0111). Surprisingly, vertebrae showing minimal radiographic evidence of bone metastasis presented significantly higher median (50%) LSRs under natural standing (p < 0.0001) and lateral bending + weights (p = 0.0009) than the normative dataset. Osteosclerotic vertebrae had lower median (50%) LSRs under natural standing (p < 0.0001), natural standing + weights (p = 0.0005), forward flexion + weights (p < 0.0001), and lateral bending + weights (p = 0.0002), a trend shared by vertebrae with mixed lesions. This study is the first to apply musculoskeletal modeling to estimate individual vertebral loading in pathologic spines and highlights the role of task-specific loading in augmenting PVF risk associated with specific bone metastatic types. Our finding of high LSRs in vertebrae without radiologically observed bone metastasis highlights that patients with metastatic spine disease could be at an increased risk of vertebral fractures even at levels where lesions have not been identified radiologically.

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.

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.

Computational modelling of the scoliotic spine: A literature review

Scoliosis is a deformity of the spine that in severe cases requires surgical treatment. There is still disagreement among clinicians as to what the aim of such treatment is as well as the optimal surgical technique. Numerical models can aid clinical decision-making by estimating the outcome of a given surgical intervention. This paper provided some background information on the modelling of the healthy spine and a review of the literature on scoliotic spine models, their validation, and their application. An overview of the methods and techniques used to construct scoliotic finite element and multibody models was given as well as the boundary conditions used in the simulations. The current limitations of the models were discussed as well as how such limitations are addressed in non-scoliotic spine models. Finally, future directions for the numerical modelling of scoliosis were addressed.

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.

Load Distribution in the Lumbar Spine During Modeled Compression Depends on Lordosis

Excessive or incorrect loading of lumbar spinal structures is commonly assumed as one of the factors to accelerate degenerative processes, which may lead to lower back pain. Accordingly, the mechanics of the spine under medical conditions, such as scoliosis or spondylolisthesis, is well-investigated. Treatments via both conventional therapy and surgical methods alike aim at restoring a "healthy" (or at least pain-free) load distribution. Yet, surprisingly little is known about the inter-subject variability of load bearings within a "healthy" lumbar spine. Hence, we utilized computer tomography data from 28 trauma-room patients, whose lumbar spines showed no visible sign of degeneration, to construct simplified multi-body simulation models. The subject-specific geometries, measured by the corresponding lumbar lordosis (LL) between the endplates of vertebra L1 and the sacrum, served as ceteris paribus condition in a standardized forward dynamic compression procedure. Further, the influence of stimulating muscles from the M. multifidus group was assessed. For the range of available LL from 28 to 66°, changes in compressive and shear forces, bending moments, as well as facet joint forces between adjacent vertebrae were calculated. While compressive forces tended to decrease with increasing LL, facet forces were tendentiously increasing. Shear forces decreased between more cranial vertebrae and increased between more caudal ones, while bending moments remained constant. Our results suggest that there exist significant, LL-dependent variations in the loading of "healthy" spinal structures, which should be considered when striving for individually appropriate therapeutic measures.

Estimation and assessment of sagittal spinal curvature and thoracic muscle morphometry in different postures

Spine models are typically developed from supine clinical imaging data, and hence clearly do not fully reflect postures that replicate subjects' clinical symptoms. Our objectives were to develop a method to: (i) estimate the subject-specific sagittal curvature of the whole spine in different postures from limited imaging data, (ii) obtain muscle lines-of-action in different postures and analyze the effect of posture on muscle fascicle length, and (iii) correct for cosine between the magnetic resonance imaging (MRI) scan plane and dominant fiber line-of-action for muscle parameters (cross-sectional area (CSA) and position). The thoracic spines of six healthy volunteers were scanned in four postures (supine, standing, flexion, and sitting) in an upright MRI. Geometry of the sagittal spine was approximated with a circular spline. A pipeline was developed to estimate spine geometry in different postures and was validated. The lines-of-action for two muscles, erector spinae (ES) and transversospinalis (TS) were obtained for every posture and hence muscle fascicle lengths were computed. A correction factor based on published literature was then computed and applied to the muscle parameters. The maximum registration error between the estimated spine geometry and MRI data was small (average RMSE∼1.2%). The muscle fascicle length increased (up to 20%) in flexion when compared to erect postures. The correction factor reduced muscle parameters (∼5% for ES and ∼25% for TS) when compared to raw MRI data. The proposed pipeline is a preliminary step in subject-specific modeling. Direction cosines of muscles could be used while improving the inputs of spine models.

Patterns of Load-to-Strength Ratios Along the Spine in a Population-Based Cohort to Evaluate the Contribution of Spinal Loading to Vertebral Fractures

Vertebral fractures (VFx) are common among older adults. Epidemiological studies report high occurrence of VFx at mid-thoracic and thoracolumbar regions of the spine; however, reasons for this observation remain poorly understood. Prior reports of high ratios of spinal loading to vertebral strength in the thoracolumbar region suggest a possible biomechanical explanation. However, no studies have evaluated load-to-strength ratios (LSRs) throughout the spine for a large number of activities in a sizeable cohort. Thus, we performed a cross-sectional study in a sample of adult men and women from a population-based cohort to: 1) determine which activities cause the largest vertebral LSRs, and 2) examine patterns of LSRs along the spine for these high-load activities. We used subject-specific musculoskeletal models of the trunk to determine vertebral compressive loads for 109 activities in 250 individuals (aged 41 to 90 years, 50% women) from the Framingham Heart Study. Vertebral compressive strengths from T₄ to L₄ were calculated from computed tomography-based vertebral size and bone density measurements. We determined which activities caused maximum LSRs at each of these spinal levels. We identified nine activities that accounted for >95% of the maximum LSRs overall and at least 89.6% at each spinal level. The activity with the highest LSR varied by spinal level, and three distinct spinal regions could be identified by the activity producing maximum LSRs: lateral bending with a weight in one hand (upper thoracic), holding weights with elbows flexed (lower thoracic), and forward flexion with weight (lumbar). This study highlights the need to consider a range of lifting, holding, and non-symmetric activities when evaluating vertebral LSRs. Moreover, we identified key activities that produce higher loading in multiple regions of the spine. These results provide the first guidance on what activities to consider when evaluating vertebral load-to-strength ratios in future studies, including those examining dynamic motions and the biomechanics of VFx. © 2020 American Society for Bone and Mineral Research (ASBMR).

Comparison of different lifting analysis tools in estimating lower spinal loads - Evaluation of NIOSH criterion

Excessive loads on the human spine is recognized as a risk factor for back injuries/pain. Various lifting analysis tools such as musculoskeletal models, regression equations and NIOSH (National Institute for Occupational Safety and Health) lifting equation (NLE) have been proposed to evaluate and mitigate associated risks during manual material handling activities. Present study aims to compare predicted spinal loads from 5 different lifting analysis tools as well as to critically evaluate the NIOSH recommended weight limit (RWL). Spinal loads were estimated under different symmetric/asymmetric lifting tasks in which hand-load mass at each task was set based on RWL from NLE. Estimated intradiscal pressures (IDPs) of various tools were also compared with in vivo measurements. We compared RWL by NLE versus our estimations of RWL calculated from our regression equations using biomechanical criteria (compression <3400 N with/without shear <1000, 1250 or 1500 N). Our regression equations followed by OpenSim, AnyBody, simple polynomial and 3DSSPP satisfactorily predicted L4-L5 IDPs. Lifting analysis tools estimated comparable spinal compression forces (mean Pearson's r = 0.80; standard deviation of relative difference = 26%) while in shear, differences were greater (mean Pearson's r = 0.68; standard deviation of relative difference = 56%). NLE estimations of RWL were conservative in comparison with our estimations for lean individuals (BMI < 25 kg/m²) when compression <3400 N and shear <1250 N were considered as the biomechanical criteria. For heavier individuals, however, NLE estimations of RWL generated spinal compression >3400 N (NIOSH biomechanical safety threshold) as well as shear >1000 N. Although RWLs estimated by NLE was body weight independent, body weight substantially altered RWLs estimated from our regression equations. For improved estimation of the risk of injury, more accurate failure criteria for spinal segments are essential.

Development of a multiscale model of the human lumbar spine for investigation of tissue loads in people with and without a transtibial amputation during sit-to-stand

Quantification of lumbar spine load transfer is important for understanding low back pain, especially among persons with a lower limb amputation. Computational modeling provides a helpful solution for obtaining estimates of in vivo loads. A multiscale model was constructed by combining musculoskeletal and finite element (FE) models of the lumbar spine to determine tissue loading during daily activities. Three-dimensional kinematic and ground reaction force data were collected from participants with ([Formula: see text]) and without ([Formula: see text]) a unilateral transtibial amputation (TTA) during 5 sit-to-stand trials. We estimated tissue-level load transfer from the multiscale model by controlling the FE model with intervertebral kinematics and muscle forces predicted by the musculoskeletal model. Annulus fibrosis stress, intradiscal pressure (IDP), and facet contact forces were calculated using the FE model. Differences in whole-body kinematics, muscle forces, and tissue-level loads were found between participant groups. Notably, participants with TTA had greater axial rotation toward their intact limb ([Formula: see text]), greater abdominal muscle activity ([Formula: see text]), and greater overall tissue loading throughout sit-to-stand ([Formula: see text]) compared to able-bodied participants. Both normalized (to upright standing) and absolute estimates of L4-L5 IDP were close to in vivo values reported in the literature. The multiscale model can be used to estimate the distribution of loads within different lumbar spine tissue structures and can be adapted for use with different activities, populations, and spinal geometries.

Between-session reliability of subject-specific musculoskeletal models of the spine derived from optoelectronic motion capture data

This study evaluated the between-session reliability of creating subject-specific musculoskeletal models with optoelectronic motion capture data, and using them to estimate spine loading. Nineteen healthy participants aged 24-74 years underwent the same set of measurements on two separate occasions. Retroreflective markers were placed on anatomical regions, including C7, T1, T4, T5, T8, T9, T12 and L1 spinous processes, pelvis, upper and lower limbs, and head. We created full-body musculoskeletal models with detailed thoracolumbar spines, and scaled these to create subject-specific models for each individual and each session. Models were scaled from distances between markers, and spine curvature was adjusted according to marker-estimated measurements. Using these models, we estimated vertebral compressive loading for five different standardized postures: neutral standing, 45˚ trunk flexion, 15˚ trunk extension, 20˚ lateral bend to the right, and 45˚ axial rotation to the right. Intraclass correlation coefficients (ICCs) and standard error of measurement were calculated as measures of between-session reliability and measurement error, respectively. Spine curvature measures showed excellent reliability (ICC = 0.79-0.91) and body scaling segments showed fair to excellent reliability (ICC = 0.46-0.95). We found that musculoskeletal models showed mostly excellent between-session reliability to estimate spine loading, with 91% of ICC values > 0.75 for all activities. This information is a necessary precursor for using motion capture data to estimate spine loading from subject-specific musculoskeletal models, and suggests that marker data will deliver reproducible subject-specific models and estimates of spine loading.

Validity of flexicurve and motion capture for measurements of thoracic kyphosis vs standing radiographic measurements

Thoracic kyphosis varies among healthy adults and typically increases with age. Excessive kyphosis (hyperkyphosis) is associated with negative health. Spinal alignment also affects spine loading, with implications for conditions such as vertebral fractures and back pain. Valid measurements of kyphosis are necessary for clinical and research assessment of age-related posture changes, and to support improved biomechanical understating of spine conditions. Independent validation of non-radiographic techniques, however, remains limited. The goal of this study was to compare standing radiographic kyphosis measurements with non-radiographic measurements and predictions of thoracic kyphosis using flexicurve and motion analysis markers, in order to determine their validity. Thirteen non-radiographic measures of thoracic kyphosis were obtained in each of 40 adult subjects who also underwent standing radiographs of the thoracic spine. Measures included estimates derived by fitting of polynomials or circles to the non-radiographic data, as well as predictions calculated using previously published methods. Intra-class correlations (ICC) and root-mean square errors (RMSEs) were calculated between radiographic and non-radiographic measures to determine validity. Most non-radiographic estimates of kyphosis show similar, weak to moderate levels of validity when compared to radiographic measurements, and RMSEs ranging from 8.0° to 20.8°. Unbiased estimates of radiographic measurements with moderate to good ICCs were identified, however, based on marker measurements, and new prediction equations were created with similar validity that also account for age and body habitus. Clinical significance: These non-radiographic measurements of thoracic kyphosis can be applied to clinical practice or to clinical studies with recognition of specific limitations.

Effects of Long-Duration Spaceflight on Vertebral Strength and Risk of Spine Fracture

Although the negative impact of long-duration spaceflight on spine BMD has been reported, its impact on vertebral strength and risk of vertebral fracture remains unknown. This study examined 17 crewmembers with long-duration service on the International Space Station in whom computed tomography (CT) scans of the lumbar spine (L₁ and L₂ ) were collected preflight, immediately postflight and 1 to 4 years after return to Earth. We assessed vertebral strength via CT-based finite element analysis (CT-FEA) and spinal loading during different activities via subject-specific musculoskeletal models. Six months of spaceflight reduced vertebral strength by 6.1% (-2.3%, -8.7%) (median [interquartile range]) compared to preflight (p < 0.05), with 65% of subjects experiencing deficits of greater than 5%, and strengths were not recovered up to 4 years after the mission. This decline in vertebral strength exceeded (p < 0.05) the 2.2% (-1.3%, -6.0%) decline in lumbar spine DXA-BMD. Further, the subject-specific changes in vertebral strength were not correlated with the changes in DXA-BMD. Although spinal loading increased slightly postflight, the ratio of vertebral compressive load to vertebral strength for typical daily activities remained well below a value of 1.0, indicating a low risk of vertebral fracture despite the loss in vertebral strength. However, for more strenuous activity, the postflight load-to-strength ratios ranged from 0.3 to 0.7, indicating a moderate risk of vertebral fracture in some individuals. Our findings suggest persistent deficits in vertebral strength following long-duration spaceflight, and although risk of vertebral fracture remains low for typical activities, the risk of vertebral fracture is notable in some crewmembers for strenuous exercise requiring maximal effort. © 2019 American Society for Bone and Mineral Research.

Moment-rotation behavior of intervertebral joints in flexion-extension, lateral bending, and axial rotation at all levels of the human spine: A structured review and meta-regression analysis

Spinal intervertebral joints are complex structures allowing motion in multiple directions, and many experimental studies have reported moment-rotation response. However, experimental methods, reporting of results, and levels of the spine tested vary widely, and a comprehensive assessment of moment-rotation response across all levels of the spine is lacking. This review aims to characterize moment-rotation response in a consistent manner for all levels of the human spine. A literature search was conducted in PubMed for moment versus rotation data from mechanical testing of intact human cadaveric intervertebral joint specimens in flexion-extension, lateral bending, and axial rotation. A total of 45 studies were included, providing data from testing of an estimated 1,648 intervertebral joints from 518 human cadavers. We used mixed-effects regression analysis to create 75 regression models of moment-rotation response (25 intervertebral joints × 3 directions). We found that a cubic polynomial model provides a good representation of the moment-rotation behavior of most intervertebral joints, and that compressive loading increases rotational stiffness throughout the spine in all directions. The results allow for the direct evaluation of intervertebral ranges of motion across the whole of the spine for given loading conditions. The random-effects outcomes, representing standard deviations of the model coefficients across the dataset, can aid understanding of normal variations in moment-rotation responses. Overall these results fill a large gap, providing the first realistic and comprehensive representations of moment-rotation behavior at all levels of the spine, with broad implications for surgical planning, medical device design, computational modeling, and understanding of spine biomechanics.

Spine loading during laboratory-simulated fireground operations - inter-individual variation and method of load quantification

Spine loading data are needed to design low-back health-preserving ergonomic interventions for firefighters. Study objectives were to quantify spine loads during simulated fireground operations using simple (polynomial) and advanced (EMG-assisted musculoskeletal model) methods and to describe the variation in spine loads between performers (N = 20). Spine compression forces differed by as much as 5.5 times bodyweight between individuals performing identical tasks. Anteroposterior and mediolateral shear forces varied by as much 3.2 and 2.1 times bodyweight between individuals performing the same tasks, respectively. Large variations in spine load magnitudes were documented regardless of whether simple or advanced quantification methods were used. Results suggest that low-back loading demands on the fireground would vary widely depending on the physical characteristics of individual firefighters, movement strategies employed, and tasks performed. Thus, personalised ergonomic interventions are warranted to regulate spine loading and load tolerance in firefighters. Practitioner summary: Even when performing the same work, the associated spine loading demands will vary widely across people due to differences in their body sizes, shapes, and movement strategies. Therefore, personalised interventions are needed to regulate spine loading and load tolerance in workers (e.g. obesity prevention, physical capacity-building exercise, and movement [re]training).

Musculoskeletal full-body models including a detailed thoracolumbar spine for children and adolescents aged 6-18 years

Currently available musculoskeletal inverse-dynamics thoracolumbar spine models are entirely based on data from adults and might therefore not be applicable for simulations in children and adolescents. In addition, these models lack lower extremities, which are required for comprehensive evaluations of functional activities or therapeutic exercises. We therefore created OpenSim-based musculoskeletal full-body models including a detailed thoracolumbar spine for children and adolescents aged 6-18 years and validated by comparing model predictions to in vivo data. After combining our recently developed adult thoracolumbar spine model with a lower extremity model, children and adolescent models were created for each year of age by adjusting segmental length and mass distribution, center of mass positions and moments of inertia of the major body segments as well as sagittal pelvis and spine alignment based on literature data. Similarly, muscle strength properties were adjusted based on CT-derived cross-sectional area measurements. Simulations were conducted from in vivo studies reported in the literature involving children and adolescents evaluating maximum trunk muscle strength (MTMS), lumbar disc compressibility (LDC), intradiscal pressure (IDP) and trunk muscle activity (MA). Model predictions correlated highly with in vivo data (MTMS: r ≥ 0.82, p ≤ 0.03; LDC: r = 0.77, p < 0.001; IDP: r ≥ 0.78, p < 0.001; MA: r ≥ 0.90, p < 0.001), indicating suitability for the reasonably accurate prediction of maximal trunk muscle strength, segmental loading and trunk muscle activity in children and adolescents. When aiming at investigating children or adolescents with pathologies such as idiopathic scoliosis, our models can serve as a basis for the creation of deformed spine models and for comparative purposes.

Optimal Estimation of Anthropometric Parameters for Quantifying Multisegment Trunk Kinetics

Kinetics assessment of the human head-arms-trunk (HAT) complex via a multisegment model is a useful tool for objective clinical evaluation of several pathological conditions. Inaccuracies in body segment parameters (BSPs) are a major source of uncertainty in the estimation of the joint moments associated with the multisegment HAT. Given the large intersubject variability, there is currently no comprehensive database for the estimation of BSPs for the HAT. We propose a nonlinear, multistep, optimization-based, noninvasive method for estimating individual-specific BSPs and calculating joint moments in a multisegment HAT model. Eleven nondisabled individuals participated in a trunk-bending experiment and their body motion was recorded using cameras and a force plate. A seven-segment model of the HAT was reconstructed for each participant. An initial guess of the BSPs was obtained by individual-specific scaling of the BSPs calculated from the male visible human (MVH) images. The intersegmental moments were calculated using both bottom-up and top-down inverse dynamics approaches. Our proposed method adjusted the scaled BSPs and center of pressure (COP) offsets to estimate optimal individual-specific BSPs that minimize the difference between the moments obtained by top-down and bottom-up inverse dynamics approaches. Our results indicate that the proposed method reduced the error in the net joint moment estimation (defined as the difference between the net joint moment calculated via bottom-up and top-down approaches) by 79.3% (median among participants). Our proposed method enables an optimized estimation of individual-specific BSPs and, consequently, a less erroneous assessment of the three-dimensional (3D) kinetics of a multisegment HAT model.

Estimating apparent maximum muscle stress of trunk extensor muscles in older adults using subject-specific musculoskeletal models

Maximum muscle stress (MMS) is a critical parameter in musculoskeletal modeling, defining the maximum force that a muscle of given size can produce. However, a wide range of MMS values have been reported in literature, and few studies have estimated MMS in trunk muscles. Due to widespread use of musculoskeletal models in studies of the spine and trunk, there is a need to determine reasonable magnitude and range of trunk MMS. We measured trunk extension strength in 49 participants over 65 years of age, surveyed participants about low back pain, and acquired quantitative computed tomography (QCT) scans of their lumbar spines. Trunk muscle morphology was assessed from QCT scans and used to create a subject-specific musculoskeletal model for each participant. Model-predicted extension strength was computed using a trunk muscle MMS of 100 N/cm² . The MMS of each subject-specific model was then adjusted until the measured strength matched the model-predicted strength (±20 N). We found that measured trunk extension strength was significantly higher in men. With the initial constant MMS value, the musculoskeletal model generally over-predicted trunk extension strength. By adjusting MMS on a subject-specific basis, we found apparent MMS values ranging from 40 to 130 N/cm² , with an average of 75.5 N/cm² for both men and women. Subjects with low back pain had lower apparent MMS than subjects with no back pain. This work incorporates a unique approach to estimate subject-specific trunk MMS values via musculoskeletal modeling and provides a useful insight into MMS variation. © 2017 Orthopaedic Research Society. Published by Wiley Periodicals, Inc. J Orthop Res 36:498-505, 2018.