Evaluation of a morphing based method to estimate muscle attachment sites of the lower extremity

Multibody dynamics-based musculoskeletal modeling for gait analysis: a systematic review

Beyond qualitative assessment, gait analysis involves the quantitative evaluation of various parameters such as joint kinematics, spatiotemporal metrics, external forces, and muscle activation patterns and forces. Utilizing multibody dynamics-based musculoskeletal (MSK) modeling provides a time and cost-effective non-invasive tool for the prediction of internal joint and muscle forces. Recent advancements in the development of biofidelic MSK models have facilitated their integration into clinical decision-making processes, including quantitative diagnostics, functional assessment of prosthesis and implants, and devising data-driven gait rehabilitation protocols. Through an extensive search and meta-analysis of over 116 studies, this PRISMA-based systematic review provides a comprehensive overview of different existing multibody MSK modeling platforms, including generic templates, methods for personalization to individual subjects, and the solutions used to address statically indeterminate problems. Additionally, it summarizes post-processing techniques and the practical applications of MSK modeling tools. In the field of biomechanics, MSK modeling provides an indispensable tool for simulating and understanding human movement dynamics. However, limitations which remain elusive include the absence of MSK modeling templates based on female anatomy underscores the need for further advancements in this area.

Kinematic-kinetic compliant acetabular cup positioning based on preoperative motion tracking and musculoskeletal modeling for total hip arthroplasty

The invention of the surgical robot enabled accurate component implantation during total hip arthroplasty (THA). However, a preoperative surgical planning methodology is still lacking to determine the acetabular cup alignment considering the patient-specific hip functions during daily activities such as walking. To simultaneously avoid implant edgeloading and impingement, this study established a kinematic-kinetic compliant (KKC) acetabular cup positioning method based on preoperative gait kinematics measurement and musculoskeletal modeling. Computed tomography images around the hip joint and their biomechanical data during gait, including motion tracking and foot-ground reaction forces, were collected. Using the reconstructed pelvic and femur geometries, the patient-specific hip muscle insertions were located in the lower limb musculoskeletal model via point cloud registration. The designed cup orientation has to be within the patient-specific safe zone to prevent implant impingement, and the optimized value selected based on the time-dependent hip joint reaction force to minimize the risk of edgeloading. As a validation of the proposed musculoskeletal model, the predicted lower limb muscle activations for seven patients were correlated with their surface electromyographic measurements, and the computed hip contact force was also in quantitative agreement with data from the literature. However, the designed cup orientations were not always within the well-known Lewinnek safe zone, highlighting the importance of KKC surgical planning based on patient-specific biomechanical evaluations.

Prediction of knee biomechanics with different tibial component malrotations after total knee arthroplasty: conventional machine learning vs. deep learning

The precise alignment of tibiofemoral components in total knee arthroplasty is a crucial factor in enhancing the longevity and functionality of the knee. However, it is a substantial challenge to quickly predict the biomechanical response to malrotation of tibiofemoral components after total knee arthroplasty using musculoskeletal multibody dynamics models. The objective of the present study was to conduct a comparative analysis between a deep learning method and four conventional machine learning methods for predicting knee biomechanics with different tibial component malrotation during a walking gait after total knee arthroplasty. First, the knee contact forces and kinematics with different tibial component malrotation in the range of ±5° in the three directions of anterior/posterior slope, internal/external rotation, and varus/valgus rotation during a walking gait after total knee arthroplasty were calculated based on the developed musculoskeletal multibody dynamics model. Subsequently, deep learning and four conventional machine learning methods were developed using the above 343 sets of biomechanical data as the dataset. Finally, the results predicted by the deep learning method were compared to the results predicted by four conventional machine learning methods. The findings indicated that the deep learning method was more accurate than four conventional machine learning methods in predicting knee contact forces and kinematics with different tibial component malrotation during a walking gait after total knee arthroplasty. The deep learning method developed in this study enabled quickly determine the biomechanical response with different tibial component malrotation during a walking gait after total knee arthroplasty. The proposed method offered surgeons and surgical robots the ability to establish a calibration safety zone, which was essential for achieving precise alignment in both preoperative surgical planning and intraoperative robotic-assisted surgical navigation.

How mechanics of individual muscle-tendon units define knee and ankle joint function in health and cerebral palsy-a narrative review

This study reviews the relationship between muscle-tendon biomechanics and joint function, with a particular focus on how cerebral palsy (CP) affects this relationship. In healthy individuals, muscle size is a critical determinant of strength, with muscle volume, cross-sectional area, and moment arm correlating with knee and ankle joint torque for different isometric/isokinetic contractions. However, in CP, impaired muscle growth contributes to joint pathophysiology even though only a limited number of studies have investigated the impact of deficits in muscle size on pathological joint function. As muscles are the primary factors determining joint torque, in this review two main approaches used for muscle force quantification are discussed. The direct quantification of individual muscle forces from their relevant tendons through intraoperative approaches holds a high potential for characterizing healthy and diseased muscles but poses challenges due to the invasive nature of the technique. On the other hand, musculoskeletal models, using an inverse dynamic approach, can predict muscle forces, but rely on several assumptions and have inherent limitations. Neither technique has become established in routine clinical practice. Nevertheless, identifying the relative contribution of each muscle to the overall joint moment would be key for diagnosis and formulating efficient treatment strategies for patients with CP. This review emphasizes the necessity of implementing the intraoperative approach into general surgical practice, particularly for joint correction operations in diverse patient groups. Obtaining in vivo data directly would enhance musculoskeletal models, providing more accurate force estimations. This integrated approach can improve the clinicians' decision-making process and advance treatment strategies by predicting changes at the muscle and joint levels before interventions, thus, holding the potential to significantly enhance clinical outcomes.

The novel magnesium-titanium hybrid cannulated screws for the treatment of vertical femoral neck fractures: Biomechanical evaluation

Background

Conventional cannulated screws are commonly used for internal fixation in the treatment of vertical femoral neck fractures. However, the noticeably high rates of undesirable outcomes such as nonunion, malunion, avascular necrosis, and fixation failure still troubled the patients and surgeons. It is urgent to develop new cannulated screws to improve the above clinical problems. The purpose of this study was to design a novel magnesium-titanium hybrid cannulated screw and to further evaluate its biomechanical performance for the treatment of vertical femoral neck fractures.

Methods

A novel magnesium-titanium hybrid cannulated screw was designed, and the conventional titanium cannulated screw was also modeled. The finite element models for vertical femoral neck fractures with magnesium-titanium hybrid cannulated screws and conventional cannulated screws were respectively established. The hip joint contact force during walking gait calculated by a subject-specific musculoskeletal multibody dynamics model, was used as loads and boundary conditions for both finite element models. The stress and displacement distributions of the cannulated screws and the femur, the micromotion of the fracture surfaces of the femoral neck, and the overall stiffness were calculated and analyzed using finite element models. The biomechanical performance of the Magnesium-Titanium hybrid cannulated screws was evaluated.

Results

The maximum stresses of the magnesium-titanium hybrid cannulated screws and the conventional cannulated screws were 451.5 ​MPa and 476.8 ​MPa, respectively. The maximum stresses of the femur with the above different cannulated screws were 140.3 ​MPa and 164.8 ​MPa, respectively. The maximum displacement of the femur with the hybrid cannulated screws was 6.260 ​mm, lower than the femur with the conventional cannulated screws, which was 7.125 ​mm. The tangential micromotions in the two orthogonal directions at the fracture surface of the femoral neck with the magnesium-titanium hybrid cannulated screws were comparable to those with the conventional cannulated screws. The overall stiffness of the magnesium-titanium hybrid cannulated screw system was 490.17 ​N/mm, higher than that of the conventional cannulated screw system, which was 433.92 ​N/mm.

Conclusion

The magnesium-titanium hybrid cannulated screw had superior mechanical strength and fixation stability for the treatment of the vertical femoral neck fractures, compared with those of the conventional cannulated screw, indicating that the magnesium-titanium hybrid cannulated screw has great potential as a new fixation strategy in future clinical applications.The translational potential of this article: This study highlights an innovative design of the magnesium-titanium hybrid cannulated screw for the treatment of vertical femoral neck fractures. The novel magnesium-titanium hybrid cannulated screw not only to provide sufficient mechanical strength and fixation stability but also to contribute to the promotion of fracture healing, which could provide a better treatment for the vertical femoral neck fractures, beneficially reducing the incidence of nonunion and reoperation rates.

Conformity design can change the effect of tibial component malrotation on knee biomechanics after total knee arthroplasty

BACKGROUND

Component alignment is essential to improve knee function and survival in total knee arthroplasty. However, it is still unclear whether the conformity design of tibiofemoral component can mitigate abnormal knee biomechanics caused by component malrotation. The purpose of this study was to investigate whether the sagittal/coronal conformity design of the tibial component could change the effect of the tibial component malrotation on knee biomechanics in total knee arthroplasty.

METHODS

A developed patient-specific musculoskeletal multi-body dynamics model of total knee arthroplasty was used to investigate the effects of the sagittal/coronal conformity of the tibial component on knee contact forces and kinematics caused by tibial component malrotation during the walking gait.

FINDINGS

Medial and lateral contact forces, internal-external rotation, and anterior-posterior translation were significantly affected by tibial component malrotation after total knee arthroplasty during the walking gait. The lower sagittal conformity of the tibial component can mitigate the abnormal internal-external rotation caused by tibial component malrotation in total knee arthroplasty, the higher coronal conformity of the tibial component can mitigate the abnormal medial-lateral translation caused by tibial component malrotation in total knee arthroplasty.

INTERPRETATION

This study highlights the importance of the tibiofemoral conformity designs on knee biomechanics caused by component malrotation in total knee arthroplasty. The optimization of the tibiofemoral conformity designs should be thoroughly considered in the design of new implants and in the planning of surgical procedures.

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

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

Multi-level personalization of neuromusculoskeletal models to estimate physiologically plausible knee joint contact forces in children

Neuromusculoskeletal models are a powerful tool to investigate the internal biomechanics of an individual. However, commonly used neuromusculoskeletal models are generated via linear scaling of generic templates derived from elderly adult anatomies and poorly represent a child, let alone children with a neuromuscular disorder whose musculoskeletal structures and muscle activation patterns are profoundly altered. Model personalization can capture abnormalities and appropriately describe the underlying (altered) biomechanics of an individual. In this work, we explored the effect of six different levels of neuromusculoskeletal model personalization on estimates of muscle forces and knee joint contact forces to tease out the importance of model personalization for normal and abnormal musculoskeletal structures and muscle activation patterns. For six children, with and without cerebral palsy, generic scaled models were developed and progressively personalized by (1) tuning and calibrating musculotendon units' parameters, (2) implementing an electromyogram-assisted approach to synthesize muscle activations, and (3) replacing generic anatomies with image-based bony geometries, and physiologically and physically plausible muscle kinematics. Biomechanical simulations of gait were performed in the OpenSim and CEINMS software on ten overground walking trials per participant. A mixed-ANOVA test, with Bonferroni corrections, was conducted to compare all models' estimates. The model with the highest level of personalization produced the most physiologically plausible estimates. Model personalization is crucial to produce physiologically plausible estimates of internal biomechanical quantities. In particular, personalization of musculoskeletal anatomy and muscle activation patterns had the largest effect overall. Increased research efforts are needed to ease the creation of personalized neuromusculoskeletal models.

Glenohumeral joint reconstruction using statistical shape modeling

Evaluation of the bony anatomy of the glenohumeral joint is frequently required for surgical planning and subject-specific computational modeling and simulation. The three-dimensional geometry of bones is traditionally obtained by segmenting medical image datasets, but this can be time-consuming and may not be practical in the clinical setting. The aims of this study were twofold. Firstly, to develop and validate a statistical shape modeling approach to rapidly reconstruct the complete scapular and humeral geometries using discrete morphometric measurements that can be quickly and easily measured directly from CT, and secondly, to assess the effectiveness of statistical shape modeling in reconstruction of the entire humerus using just the landmarks in the immediate vicinity of the glenohumeral joint. The most representative shape prediction models presented in this study achieved complete scapular and humeral geometry prediction from seven or fewer morphometric measurements and yielded a mean surface root mean square (RMS) error under 2 mm. Reconstruction of the entire humerus was achieved using information of only proximal humerus bony landmarks and yielding mean surface RMS errors under 3 mm. The proposed statistical shape modeling facilitates rapid generation of 3D anatomical models of the shoulder, which may be useful in rapid development of personalized musculoskeletal models.

Patient-specific musculoskeletal models as a framework for comparing ACL function in unicompartmental versus bicruciate retaining arthroplasty

Unicompartmental knee arthroplasty has been shown to provide superior functional outcomes compared to total knee arthroplasty and have motivated development of advanced implant designs including bicruciate retaining knee arthroplasty. However, few validated frameworks are available to directly compare the effect of implant design and surgical techniques on ligament function and joint kinematics. In the present study, the subject-specific lower extremity models were developed based on musculoskeletal modeling framework using force-dependent kinematics method, and validated against in vivo telemetric data. The experiment data of two subjects who underwent TKA were obtained from the SimTK "Grand Challenge Competition" repository, and integrated into the subject-specific lower extremity model. Five walking gait trials and three different knee implant models for each subject were used as partial inputs for the model to predict knee biomechanics for unicompartmental, bicruciate retaining, and total knee arthroplasty. The results showed no significant differences in the tibiofemoral contact forces or angular kinematic parameters between three groups. However, unicompartmental knee arthroplasty demonstrated significantly more posterior tibial location between 0% and 40% of the gait cycle (p < 0.017). Significant differences in range of tibiofemoral anterior/posterior translation and medial/lateral translation were also observed between unicompartmental and bicruciate retaining arthroplasty (p < 0.017). Peak values of anterior cruciate ligament forces differed between unicompartmental and bicruciate retaining arthroplasty from 10% to 30% of the gait cycle. Findings of this study indicate that unicompartmental and bicruciate retaining arthroplasty do not have identical biomechanics and point to the complementary role of anterior cruciate ligament and articular geometry in guiding knee function. Further, the patient-specific musculoskeletal model developed provides a reliable framework for assessing new implant designs, and effect of surgical techniques on knee biomechanics following arthroplasty.

Automated muscle elongation measurement during reverse shoulder arthroplasty planning

BACKGROUND

Adequate deltoid and rotator cuff elongation in reverse shoulder arthroplasty is crucial to maximize postoperative functional outcomes and to avoid complications. Measurements of deltoid and rotator cuff elongation during preoperative planning can support surgeons in selecting a suitable implant design and position. Therefore, this study presented and evaluated a fully automated method for measuring deltoid and rotator cuff elongation.

METHODS

Complete scapular and humeral models were extracted from computed tomography scans of 40 subjects. First, a statistical shape model of the complete humerus was created and evaluated to identify the muscle attachment points. Next, a muscle wrapping algorithm was developed to identify the muscle paths and to compute muscle lengths and elongations after reverse shoulder arthroplasty implantation. The accuracy of the muscle attachment points and the muscle elongation measurements was evaluated for the 40 subjects by use of both complete and artificially created partial humeral models. Additionally, the muscle elongation measurements were evaluated for a set of 50 arthritic shoulder joints. Finally, a sensitivity analysis was performed to evaluate the impact of implant positioning on deltoid and rotator cuff elongation.

RESULTS

For the complete humeral models, all muscle attachment points were identified with a median error < 3.5 mm. For the partial humeral models, the errors on the deltoid attachment point largely increased. Furthermore, all muscle elongation measurements showed an error < 1 mm for 75% of the subjects for both the complete and partial humeral models. For the arthritic shoulder joints, the errors on the muscle elongation measurements were <2 mm for 75% of the subjects. Finally, the sensitivity analysis showed that muscle elongations were affected by implant positioning.

DISCUSSION

This study presents an automated method for accurately measuring muscle elongations during preoperative planning of shoulder arthroplasty. The results show that the accuracy in measuring muscle elongations is higher than the accuracy in indicating the muscle attachment points. Hence, muscle elongation measurements are insensitive to the observed errors on the muscle attachment points. Related to this finding, muscle elongations can be accurately measured for both a complete humeral model and a partial humeral model. Because the presented method also showed accurate results for arthritic shoulder joints, it can be used during preoperative shoulder arthroplasty planning, in which typically only the proximal humerus is present in the scan and in which bone arthropathy can be present. As the muscle elongations are sensitive to implant positioning, surgeons can use the muscle elongation measurements to refine their surgical plan.

Effect of Ligament Properties on Nonlinear Dynamics and Wear Prediction of Knee Prostheses

Although wear is known as the primary cause of long-time failure of total knee arthroplasty (TKA), it can be vital in short- and midterm TKA failure due to laxity. One of the reasons leading to joint laxity and instability is ligamentous insufficiency. This study, therefore, aims to investigate the effects of insufficient ligaments-related knee laxity on both nonlinear dynamics and wear of TKA. The study hypothesizes (a) ligamentous insufficiency can increase TKA damage; (b) stiffness reduction of each of the posterior cruciate ligament (PCL) and medial-lateral collateral ligaments (MCL-LCL) can differently contribute to TKA damage. A forward dynamics methodology is developed and the ligament behavior is simulated employing an asymmetric nonlinear elastic model. External loads and moment, due to the presence of all soft tissues, e.g., muscles and hip joint reaction forces, applied to the femoral bone are determined using a musculoskeletal approach linked to the developed model. A mesh density analysis is performed and comparing outcomes with that available in the literature allows for the assessment of our approach. From the results acquired, reduced PCL stiffness leads to an increase in linear wear rates and results in the maximum damage in TKAs. However, the maximum linear wear rates on both condyles occur once the stiffness of all ligaments is reduced. Moreover, the worn area of the tibia surface increases with the reduction in MCL-LCL stiffness on the medial condyle. The joint with insufficient PCL also shows a considerable increase in ligament forces right after toe-off.

Leveraging subject-specific musculoskeletal modeling to assess effect of anterior cruciate ligament retaining total knee arthroplasty during walking gait

Bi-cruciate retaining total knee arthroplasty has several potential advantages including improved anteroposterior knee stability compared to contemporary posterior cruciate-retaining total knee arthroplasty. However, few studies have explored whether there is significant differences of knee biomechanics following bi-cruciate retaining total knee arthroplasty compared to posterior cruciate-retaining total knee arthroplasty. In the present study, subject-specific lower extremity musculoskeletal multi-body dynamics models for bi-cruciate retaining, bi-cruciate retaining without anterior cruciate ligament, and posterior cruciate-retaining total knee arthroplasty were developed based on the musculoskeletal modeling framework using force-dependent kinematics method and validated against in vivo telemetric data. The experiment data of two subjects who underwent total knee arthroplasty were obtained for the SimTK “Grand Challenge Competition” repository, and integrated into the musculoskeletal model. Five walking gait trials for each subject were used as partial inputs for the model to predict the knee biomechanics for bi-cruciate retaining, bi-cruciate retaining without anterior cruciate ligament, and posterior cruciate-retaining total knee arthroplasty. The results revealed significantly greater range of anterior/posterior tibiofemoral translation, and significantly more posterior tibial location during the early phase of gait and more anterior tibial location during the late phase of gait were found in bi-cruciate retaining total knee arthroplasty without anterior cruciate ligament when compared to the bi-cruciate retaining total knee arthroplasty. No significant differences in tibiofemoral contact forces, rotations, translations, and ligament forces between bi-cruciate retaining and posterior cruciate-retaining total knee arthroplasty during normal walking gait, albeit slight differences in range of tibiofemoral internal/external rotation and anterior/posterior translation were observed. The present study revealed that anterior cruciate ligament retention has a positive effect on restoring normal knee kinematics in bi-cruciate retaining total knee arthroplasty. Preservation of anterior cruciate ligament in total knee arthroplasty and knee implant designs interplay each other and both contribute to restoring normal knee kinematics in different types of total knee arthroplasty. Further evaluation of more demanding activities and subject data from patients with bi-cruciate retaining and posterior cruciate-retaining total knee arthroplasty via musculoskeletal modeling may better highlight the role of the anterior cruciate ligament and its stabilizing influence.

Development and Evaluation of a Subject-Specific Lower Limb Model With an Eleven-Degrees-of-Freedom Natural Knee Model Using Magnetic Resonance and Biplanar X-Ray Imaging During a Quasi-Static Lunge

Musculoskeletal (MS) models can be used to study the muscle, ligament, and joint mechanics of natural knees. However, models that both capture subject-specific geometry and contain a detailed joint model do not currently exist. This study aims to first develop magnetic resonance image (MRI)-based subject-specific models with a detailed natural knee joint capable of simultaneously estimating in vivo ligament, muscle, tibiofemoral (TF), and patellofemoral (PF) joint contact forces and secondary joint kinematics. Then, to evaluate the models, the predicted secondary joint kinematics were compared to in vivo joint kinematics extracted from biplanar X-ray images (acquired using slot scanning technology) during a quasi-static lunge. To construct the models, bone, ligament, and cartilage structures were segmented from MRI scans of four subjects. The models were then used to simulate lunges based on motion capture and force place data. Accurate estimates of TF secondary joint kinematics and PF translations were found: translations were predicted with a mean difference (MD) and standard error (SE) of 2.13 ± 0.22 mm between all trials and measures, while rotations had a MD ± SE of 8.57 ± 0.63 deg. Ligament and contact forces were also reported. The presented modeling workflow and the resulting knee joint model have potential to aid in the understanding of subject-specific biomechanics and simulating the effects of surgical treatment and/or external devices on functional knee mechanics on an individual level.

Automated Generation of Three-Dimensional Complex Muscle Geometries for Use in Personalised Musculoskeletal Models

The geometrical representation of muscles in computational models of the musculoskeletal system typically consists of a series of line segments. These muscle anatomies are based on measurements from a limited number of cadaveric studies that recently have been used as atlases for creating subject-specific models from medical images, so potentially restricting the options for personalisation and assessment of muscle geometrical models. To overcome this methodological limitation, we propose a novel, completely automated technique that, from a surface geometry of a skeletal muscle and its attachment areas, can generate an arbitrary number of lines of action (fibres) composed by a user-defined number of straight-line segments. These fibres can be included in standard musculoskeletal models and used in biomechanical simulations. This methodology was applied to the surfaces of four muscles surrounding the hip joint (iliacus, psoas, gluteus maximus and gluteus medius), segmented on magnetic resonance imaging scans from a cadaveric dataset, for which highly discretised muscle representations were created and used to simulate functional tasks. The fibres’ moment arms were validated against measurements and models of the same muscles from the literature with promising outcomes. The proposed approach is expected to improve the anatomical representation of skeletal muscles in personalised biomechanical models and finite element applications.

Insert conformity variation affects kinematics and wear performance of total knee replacements

BACKGROUND

The insert conformity is a critical factor for successful total knee replacement which must be considered in design of the implant. However, the effects of conformity on knee kinematics and wear under physiological environment are often neglected in previous studies. The present study involved evaluating the biomechanics and wear performance with regard to different insert conformity in total knee replacement.

METHODS

Different tibial inserts with different sagittal and coronal conformity levels were created and analyzed using a previously developed wear prediction framework, coupling a patient-specific musculoskeletal multibody dynamics simulation, finite element and wear analysis. The contact mechanics, kinematics, and wear performance were compared during 10 million cycles of wear simulation.

FINDINGS

The findings revealed that the knee kinematics was affected by sagittal conformity design variables, which further influenced the wear of insert bearing surface. Additionally, kinematics and wear of artificial knee joint were much more sensitive to sagittal than coronal conformity of tibial insert. The lower sagittal conformity designs had lower wear rates, worn area and contact area. In turn, the wear of insert bearing surface also changed insert conformity, and further impacted on knee kinematics.

INTERPRETATION

The present study indicated that the sagittal conformity design of insert surface played a crucial role to improve contact mechanics and kinematics performance and minimize wear of total knee replacement. The optimization of insert conformity should be considered carefully in implant design and surgical procedures.

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

OBJECTIVE

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

METHODS

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

RESULTS

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

CONCLUSION

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

SIGNIFICANCE

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

Three-dimensional temporomandibular joint muscle attachment morphometry and its impacts on musculoskeletal modeling

In musculoskeletal models of the human temporomandibular joint (TMJ), muscles are typically represented by force vectors that connect approximate muscle origin and insertion centroids (centroid-to-centroid force vectors). This simplification assumes equivalent moment arms and muscle lengths for all fibers within a muscle even with complex geometry and may result in inaccurate estimations of muscle force and joint loading. The objectives of this study were to quantify the three-dimensional (3D) human TMJ muscle attachment morphometry and examine its impact on TMJ mechanics. 3D muscle attachment surfaces of temporalis, masseter, lateral pterygoid, and medial pterygoid muscles of human cadaveric heads were generated by co-registering measured attachment boundaries with underlying skull models created from cone-beam computerized tomography (CBCT) images. A bounding box technique was used to quantify 3D muscle attachment size, shape, location, and orientation. Musculoskeletal models of the mandible were then developed and validated to assess the impact of 3D muscle attachment morphometry on joint loading during jaw maximal open-close. The 3D morphometry revealed that muscle lengths and moment arms of temporalis and masseter muscles varied substantially among muscle fibers. The values calculated from the centroid-to-centroid model were significantly different from those calculated using the 'Distributed model', which considered crucial 3D muscle attachment morphometry. Consequently, joint loading was underestimated by more than 50% in the centroid-to-centroid model. Therefore, it is necessary to consider 3D muscle attachment morphometry, especially for muscles with broad attachments, in TMJ musculoskeletal models to precisely quantify the joint mechanical environment critical for understanding TMJ function and mechanobiology.

Feasibility of A-mode ultrasound based intraoperative registration in computer-aided orthopedic surgery: A simulation and experimental study

PURPOSE

A fast and accurate intraoperative registration method is important for Computer-Aided Orthopedic Surgery (CAOS). A-mode ultrasound (US) is able to acquire bone surface data in a non-invasive manner. To utilize A-mode US in CAOS, a suitable registration algorithm is necessary with a small number of registration points and the presence of measurement errors. Therefore, we investigated the effects of (1) the number of registration points and (2) the Ultrasound Point Localization Error (UPLE) on the overall registration accuracy.

METHODS

We proposed a new registration method (ICP-PS), including the Iterative Closest Points (ICP) algorithm and a Perturbation Search algorithm. This method enables to avoid getting stuck in the local minimum of ICP iterations and to find the adjacent global minimum. This registration method was subsequently validated in a numerical simulation and a cadaveric experiment using a 3D-tracked A-mode US system.

RESULTS

The results showed that ICP-PS outperformed the standard ICP algorithm. The registration accuracy improved with the addition of ultrasound registration points. In the numerical simulation, for 25 sample points with zero UPLE, the averaged registration error of ICP-PS reached 0.25 mm, while 1.71 mm for ICP, decreasing by 85.38%. In the cadaver experiment, using 25 registration points, ICP-PS achieved an RMSE of 2.81 mm relative to 5.84 mm for the ICP, decreasing by 51.88%.

CONCLUSIONS

The simulation approach provided a well-defined framework for estimating the necessary number of ultrasound registration points and acceptable level of UPLE for a given required level of accuracy for intraoperative registration in CAOS. ICP-PS method is suitable for A-mode US based intraoperative registration. This study would facilitate the application of A-mode US probe in registering the point cloud to a known shape model, which also has the potential for accurately estimating bone position and orientation for skeletal motion tracking and surgical navigation.

Workflow assessing the effect of gait alterations on stresses in the medial tibial cartilage - combined musculoskeletal modelling and finite element analysis

Knee osteoarthritis (KOA) is most common in the medial tibial compartment. We present a novel method to study the effect of gait modifications and lateral wedge insoles (LWIs) on the stresses in the medial tibial cartilage by combining musculoskeletal (MS) modelling with finite element (FE) analysis. Subject's gait was recorded in a gait laboratory, walking normally, with 5° and 10° LWIs, toes inward ('Toe in'), and toes outward ('Toe out wide'). A full lower extremity MRI and a detailed knee MRI were taken. Bones and most soft tissues were segmented from images, and the generic bone architecture of the MS model was morphed into the segmented bones. The output forces from the MS model were then used as an input in the FE model of the subject's knee. During stance, LWIs failed to reduce medial peak pressures apart from Insole 10° during the second peak. Toe in reduced peak pressures by -11% during the first peak but increased them by 12% during the second. Toe out wide reduced peak pressures by -15% during the first and increased them by 7% during the second. The results show that the work flow can assess the effect of interventions on an individual level. In the future, this method can be applied to patients with KOA.

Subject-specific shoulder muscle attachment region prediction using statistical shape models: A validity study

Subject-specific musculoskeletal models can predict accurate joint and muscle biomechanics thereby helping clinicians and surgeons. Current modeling strategies do not incorporate accurate subject-specific muscle parameters. This study reports a statistical shape model (SSM) based method to predict subject-specific muscle attachment regions on shoulder bones and illustrates the concurrent validity of the predictions. Augmented SSMs of scapula and humerus bones were built using bone meshes and five muscle attachment (origin/insertion) regions which play important role in the shoulder motion and function. Muscle attachments included Subscapularis, Supraspinatus, Infraspinatus, Teres Major and Teres Minor on both the bones. The regions were represented by subset of vertices on the bone meshes and were tracked using vertex identifiers. Subject-specific muscle attachment regions were predicted using external set of bones not used in building the SSMs. Validity of predictions was determined by visual inspection and also by using four similarity measures between predicted and manually segmented regions. Excellent concurrent validity was found indicating the higher accuracy of predictions. This method can be effectively employed in modeling pipelines or in automatic segmentation of medical images. Further validations are warranted on all the muscles of the shoulder complex.

Development of a biomechanical model of the wrist joint for patient-specific model guided surgical therapy planning: Part 1

An enhanced musculoskeletal biomechanical model of the wrist joint is presented in this article. The developed computational model features the two forearm bones radius and ulna, the eight wrist bones, the five metacarpal bones, and a soft tissue apparatus. Validation of the model was based on information taken from the literature as well as own experimental passive in vitro motion analysis of eight cadaver specimens. The computational model is based on the multi-body simulation software AnyBody. A comprehensive ligamentous apparatus was implemented allowing the investigation of ligament function. The model can easily patient specific personalized on the basis of image information. The model enables simulation of individual wrist motion and predicts trends correctly in the case of changing kinematics. Therefore, patient-specific multi-body simulation models are potentially valuable tools for surgeons in pre- and intraoperative planning of implant placement and orientation.

Non-linear scaling of a musculoskeletal model of the lower limb using statistical shape models

Accurate muscle geometry for musculoskeletal models is important to enable accurate subject-specific simulations. Commonly, linear scaling is used to obtain individualised muscle geometry. More advanced methods include non-linear scaling using segmented bone surfaces and manual or semi-automatic digitisation of muscle paths from medical images. In this study, a new scaling method combining non-linear scaling with reconstructions of bone surfaces using statistical shape modelling is presented. Statistical Shape Models (SSMs) of femur and tibia/fibula were used to reconstruct bone surfaces of nine subjects. Reference models were created by morphing manually digitised muscle paths to mean shapes of the SSMs using non-linear transformations and inter-subject variability was calculated. Subject-specific models of muscle attachment and via points were created from three reference models. The accuracy was evaluated by calculating the differences between the scaled and manually digitised models. The points defining the muscle paths showed large inter-subject variability at the thigh and shank – up to 26 mm; this was found to limit the accuracy of all studied scaling methods. Errors for the subject-specific muscle point reconstructions of the thigh could be decreased by 9% to 20% by using the non-linear scaling compared to a typical linear scaling method. We conclude that the proposed non-linear scaling method is more accurate than linear scaling methods. Thus, when combined with the ability to reconstruct bone surfaces from incomplete or scattered geometry data using statistical shape models our proposed method is an alternative to linear scaling methods.

Subject-specific musculoskeletal loading of the tibia: Computational load estimation

The systematic development of subject-specific computer models for the analysis of personalized treatments is currently a reality. In fact, many advances have recently been developed for creating virtual finite element-based models. These models accurately recreate subject-specific geometries and material properties from recent techniques based on quantitative image analysis. However, to determine the subject-specific forces, we need a full gait analysis, typically in combination with an inverse dynamics simulation study. In this work, we aim to determine the subject-specific forces from the computer tomography images used to evaluate bone density. In fact, we propose a methodology that combines these images with bone remodelling simulations and artificial neural networks. To test the capability of this novel technique, we quantify the personalized forces for five subject-specific tibias using our technique and a gait analysis. We compare both results, finding that similar vertical loads are estimated by both methods and that the dominant part of the load can be reliably computed. Therefore, we can conclude that the numerical-based technique proposed in this work has great potential for estimating the main forces that define the mechanical behaviour of subject-specific bone.

Subject-specific geometrical detail rather than cost function formulation affects hip loading calculation

This study assessed the relative importance of introducing an increasing level of medical image-based subject-specific detail in bone and muscle geometry in the musculoskeletal model, on calculated hip contact forces during gait. These forces were compared to introducing minimization of hip contact forces in the optimization criterion. With an increasing level of subject-specific detail, specifically MRI-based geometry and wrapping surfaces representing the hip capsule, hip contact forces decreased and were more comparable to contact forces measured using instrumented prostheses (average difference of 0.69 BW at the first peak compared to 1.04 BW for the generic model). Inclusion of subject-specific wrapping surfaces in the model had a greater effect than altering the cost function definition.

Intra-Articular Knee Contact Force Estimation During Walking Using Force-Reaction Elements and Subject-Specific Joint Model2

Joint contact forces measured with instrumented knee implants have not only revealed general patterns of joint loading but also showed individual variations that could be due to differences in anatomy and joint kinematics. Musculoskeletal human models for dynamic simulation have been utilized to understand body kinetics including joint moments, muscle tension, and knee contact forces. The objectives of this study were to develop a knee contact model which can predict knee contact forces using an inverse dynamics-based optimization solver and to investigate the effect of joint constraints on knee contact force prediction. A knee contact model was developed to include 32 reaction force elements on the surface of a tibial insert of a total knee replacement (TKR), which was embedded in a full-body musculoskeletal model. Various external measurements including motion data and external force data during walking trials of a subject with an instrumented knee implant were provided from the Sixth Grand Challenge Competition to Predict in vivo Knee Loads. Knee contact forces in the medial and lateral portions of the instrumented knee implant were also provided for the same walking trials. A knee contact model with a hinge joint and normal alignment could predict knee contact forces with root mean square errors (RMSEs) of 165 N and 288 N for the medial and lateral portions of the knee, respectively, and coefficients of determination (R2) of 0.70 and −0.63. When the degrees-of-freedom (DOF) of the knee and locations of leg markers were adjusted to account for the valgus lower-limb alignment of the subject, RMSE values improved to 144 N and 179 N, and R2 values improved to 0.77 and 0.37, respectively. The proposed knee contact model with subject-specific joint model could predict in vivo knee contact forces with reasonable accuracy. This model may contribute to the development and improvement of knee arthroplasty.

Prediction of hip joint load and translation using musculoskeletal modelling with force-dependent kinematics and experimental validation

Musculoskeletal lower limb models are widely used to predict the resultant contact force in the hip joint as a non-invasive alternative to instrumented implants. Previous musculoskeletal models based on rigid body assumptions treated the hip joint as an ideal sphere with only three rotational degrees of freedom. An musculoskeletal model that considered force-dependent kinematics with three additional translational degrees of freedom was developed and validated in this study by comparing it with a previous experimental measurement. A 32-mm femoral head against a polyethylene cup was considered in the musculoskeletal model for calculating the contact forces. The changes in the main modelling parameters were found to have little influence on the hip joint forces (relative deviation of peak value < 10 BW%, mean trial deviation < 20 BW%). The centre of the hip joint translation was more sensitive to the changes in the main modelling parameters, especially muscle recruitment type (relative deviation of peak value < 20%, mean trial deviation < 0.02 mm). The predicted hip contact forces showed consistent profiles, compared with the experimental measurements, except in the lateral–medial direction. The ratio-average analysis, based on the Bland–Altman’s plots, showed better limits of agreement in climbing stairs (mean limits of agreement: −2.0 to 6.3 in walking, mean limits of agreement: −0.5 to 3.1 in climbing stairs). Better agreement of the predicted hip contact forces was also found during the stance phase. The force-dependent kinematics approach underestimated the maximum hip contact force by a mean value of 6.68 ± 1.75% BW compared with the experimental measurements. The predicted maximum translations of the hip joint centres were 0.125 ± 0.03 mm in level walking and 0.123 ± 0.005 mm in climbing stairs.

A Subject-Specific Musculoskeletal Modeling Framework to Predict In Vivo Mechanics of Total Knee Arthroplasty

Musculoskeletal (MS) models should be able to integrate patient-specific MS architecture and undergo thorough validation prior to their introduction into clinical practice. We present a methodology to develop subject-specific models able to simultaneously predict muscle, ligament, and knee joint contact forces along with secondary knee kinematics. The MS architecture of a generic cadaver-based model was scaled using an advanced morphing technique to the subject-specific morphology of a patient implanted with an instrumented total knee arthroplasty (TKA) available in the fifth “grand challenge competition to predict in vivo knee loads” dataset. We implemented two separate knee models, one employing traditional hinge constraints, which was solved using an inverse dynamics technique, and another one using an 11-degree-of-freedom (DOF) representation of the tibiofemoral (TF) and patellofemoral (PF) joints, which was solved using a combined inverse dynamic and quasi-static analysis, called force-dependent kinematics (FDK). TF joint forces for one gait and one right-turn trial and secondary knee kinematics for one unloaded leg-swing trial were predicted and evaluated using experimental data available in the grand challenge dataset. Total compressive TF contact forces were predicted by both hinge and FDK knee models with a root-mean-square error (RMSE) and a coefficient of determination (R2) smaller than 0.3 body weight (BW) and equal to 0.9 in the gait trial simulation and smaller than 0.4 BW and larger than 0.8 in the right-turn trial simulation, respectively. Total, medial, and lateral TF joint contact force predictions were highly similar, regardless of the type of knee model used. Medial (respectively lateral) TF forces were over- (respectively, under-) predicted with a magnitude error of M < 0.2 (respectively > −0.4) in the gait trial, and under- (respectively, over-) predicted with a magnitude error of M > −0.4 (respectively < 0.3) in the right-turn trial. Secondary knee kinematics from the unloaded leg-swing trial were overall better approximated using the FDK model (average Sprague and Geers' combined error C = 0.06) than when using a hinged knee model (C = 0.34). The proposed modeling approach allows detailed subject-specific scaling and personalization and does not contain any nonphysiological parameters. This modeling framework has potential applications in aiding the clinical decision-making in orthopedics procedures and as a tool for virtual implant design.