Tien Tuan Dao

Estimation of accuracy of patient-specific musculoskeletal modelling: case study on a post polio residual paralysis subject

For patients with patterns ranging out of anthropometric standard values, patient-specific musculoskeletal modelling becomes crucial for clinical diagnosis and follow-up. However, patient-specific modelling using imaging techniques and motion capture systems is mainly subject to experimental errors. The aim of this study was to quantify these experimental errors when performing a patient-specific musculoskeletal model. CT scan data were used to personalise the geometrical model and its inertial properties for a post polio residual paralysis subject. After having performed a gait-based experimental protocol, kinematics data were measured using a VICON motion capture system with six infrared cameras. The musculoskeletal model was computed using a direct/inverse algorithm (LifeMod software). A first source of errors was identified in the segmentation procedure in relation to the calculation of personalised inertial parameters. The second source of errors was subject related, as it depended on the reproducibility of performing the same type of gait. The impact of kinematics, kinetics and muscle forces resulting from the musculoskeletal modelling was quantified using relative errors and the absolute root mean square error. Concerning the segmentation procedure, we found that the kinematics results were not sensitive to the errors (relative error < 1%). However, a strong influence was noted on the kinetics results (deviation up to 71%). Furthermore, the reproducibility error showed a significant influence (relative mean error varying from 5 to 30%). The present paper demonstrates that in patient-specific musculoskeletal modelling variations due to experimental errors derived from imaging techniques and motion capture need to be both identified and quantified. Therefore, the paper can be used as a guideline.

On the Relative Relevance of Subject-Specific Geometries and Degeneration-Specific Mechanical Properties for the Study of Cell Death in Human Intervertebral Disk Models

Capturing patient- or condition-specific intervertebral disk (IVD) properties in finite element models is outmost important in order to explore how biomechanical and biophysical processes may interact in spine diseases. However, disk degenerative changes are often modeled through equations similar to those employed for healthy organs, which might not be valid. As for the simulated effects of degenerative changes, they likely depend on specific disk geometries. Accordingly, we explored the ability of continuum tissue models to simulate disk degenerative changes. We further used the results in order to assess the interplay between these simulated changes and particular IVD morphologies, in relation to disk cell nutrition, a potentially important factor in disk tissue regulation. A protocol to derive patient-specific computational models from clinical images was applied to different spine specimens. In vitro, IVD creep tests were used to optimize poro-hyperelastic input material parameters in these models, in function of the IVD degeneration grade. The use of condition-specific tissue model parameters in the specimen-specific geometrical models was validated against independent kinematic measurements in vitro. Then, models were coupled to a transport-cell viability model in order to assess the respective effects of tissue degeneration and disk geometry on cell viability. While classic disk poro-mechanical models failed in representing known degenerative changes, additional simulation of tissue damage allowed model validation and gave degeneration-dependent material properties related to osmotic pressure and water loss, and to increased fibrosis. Surprisingly, nutrition-induced cell death was independent of the grade-dependent material properties, but was favored by increased diffusion distances in large IVDs. Our results suggest that in situ geometrical screening of IVD morphology might help to anticipate particular mechanisms of disk degeneration.

Musculoskeletal Simulation for Assessment of Effect of Movement-Based Structure-Modifying Treatment Strategies

The better understanding of the complex mechanism between neural motor control and its resulting joint kinematics and muscle forces allows a better elucidation of the mechanisms behind body growth, aging progression, and disease development. This study aimed at investigating the impact of movement-based structure-modifying treatment strategies on joint kinematics, muscle forces, and muscle synergies of the gait with instrumented implant. A patient-specific musculoskeletal model was used to quantitatively assess the deviations of joint and muscle behaviors between the normal gait and 4 gait modifications (bouncy, medial thrust, midcrouch, and mtp (i.e., gait with forefoot strike)). Moreover, muscle synergy analysis was performed using EMG-based nonnegative matrix factorization. Large variation of 19 degrees and 190 N was found for knee flexion/extension and lower limb muscle forces, respectively. EMG-based muscle synergy analysis revealed that the activation levels of the vastus lateralis and tibialis anterior are dominant for the midcrouch gait. In addition, an important contribution of semimembranosus to the medial thrust and midcrouch gaits was also observed. In fact, such useful information could allow a better understanding of the joint function and muscle synergy strategies leading to deeper knowledge of joint and muscle mechanisms related to neural voluntary motor commands.

Knowledge-based personalized search engine for the Web-based Human Musculoskeletal System Resources (HMSR) in biomechanics

Human musculoskeletal system resources of the human body are valuable for the learning and medical purposes. Internet-based information from conventional search engines such as Google or Yahoo cannot response to the need of useful, accurate, reliable and good-quality human musculoskeletal resources related to medical processes, pathological knowledge and practical expertise. In this present work, an advanced knowledge-based personalized search engine was developed. Our search engine was based on a client-server multi-layer multi-agent architecture and the principle of semantic web services to acquire dynamically accurate and reliable HMSR information by a semantic processing and visualization approach. A security-enhanced mechanism was applied to protect the medical information. A multi-agent crawler was implemented to develop a content-based database of HMSR information. A new semantic-based PageRank score with related mathematical formulas were also defined and implemented. As the results, semantic web service descriptions were presented in OWL, WSDL and OWL-S formats. Operational scenarios with related web-based interfaces for personal computers and mobile devices were presented and analyzed. Functional comparison between our knowledge-based search engine, a conventional search engine and a semantic search engine showed the originality and the robustness of our knowledge-based personalized search engine. In fact, our knowledge-based personalized search engine allows different users such as orthopedic patient and experts or healthcare system managers or medical students to access remotely into useful, accurate, reliable and good-quality HMSR information for their learning and medical purposes.

A New Multi-Sensor Fusion Scheme to Improve the Accuracy of Knee Flexion Kinematics for Functional Rehabilitation Movements

Exergames have been proposed as a potential tool to improve the current practice of musculoskeletal rehabilitation. Inertial or optical motion capture sensors are commonly used to track the subject’s movements. However, the use of these motion capture tools suffers from the lack of accuracy in estimating joint angles, which could lead to wrong data interpretation. In this study, we proposed a real time quaternion-based fusion scheme, based on the extended Kalman filter, between inertial and visual motion capture sensors, to improve the estimation accuracy of joint angles. The fusion outcome was compared to angles measured using a goniometer. The fusion output shows a better estimation, when compared to inertial measurement units and Kinect outputs. We noted a smaller error (3.96°) compared to the one obtained using inertial sensors (5.04°). The proposed multi-sensor fusion system is therefore accurate enough to be applied, in future works, to our serious game for musculoskeletal rehabilitation.

ASSESSMENT OF PARAMETER UNCERTAINTY IN RIGID MUSCULOSKELETAL SIMULATION USING A PROBABILISTIC APPROACH

Experimental investigation coupled with numerical simulations is commonly used for solving multi-physical problems. In the field of biomechanics, in which the aim is to understand the mechanics of living system, the main difficulties are to provide experimental data reflecting the multi-physical behavior of the system of interest. These experimental data are used as input data for numerical simulations to quantify output responses through physical and/or biological laws expressed by constitutive mathematical equations. However, uncertainties on the experimentally available data exist from factors such as human variability and differences in protocols parameters and techniques. Thus, the true values of these data could never be experimentally measured. The objective of this study was to develop a modeling workflow to assess and account for the parameter uncertainty in rigid musculoskeletal simulation. A generic musculoskeletal model was used. Data uncertainties of the right thigh mass, physiological cross-sectional area (pCSA) and muscle tension coefficient of the rectus femoris were accounted to estimate their effect on the joint moment and muscle force computing, respectively. A guideline was developed to fuse data from multiple sources into a sample variation space leading to establish input data distribution. Uncertainty propagation was performed using Monte Carlo and most probable point methods. A high degree of sensitivity of 0.98 was noted for the effect of thigh mass uncertainty on the hip joint moment using inverse dynamics method. A strong deviation of rectus femoris muscle force (around 260 N) was found under effect of pCSA and muscle tension coefficient on the force estimation using static optimization method. Accounting parameter uncertainty into rigid musculoskeletal simulation plays an essential role in the evaluation of the confidence in the model outputs. Thus, simulation outcome may be computed and represented in a more reliable manner with a global range of plausible values.

Quantitative analysis of annulus fibrosus and nucleus pulposus derived from T2 mapping, diffusion-weighted and diffusion tensor MR imaging

Quantitative information on annulus fibrosus (AF) and nucleus pulposus (NP) is of interest in early diagnosis of degenerated intervertebral disc (IVD) disease. In this present study, we developed a practical framework to analyse and visualise three feature maps of the IVD: the T2 relaxation time, the apparent diffusion coefficient and the anisotropy. They are derived from advanced Magnetic Resonance Imaging sequences such as T2 mapping, diffusion-weighted and diffusion tensor sequences. These features were quantified using regression analysis with least squares and signal intensity-based direction-oriented methods. Based on these maps, a threshold-based geometrical computing procedure was developed to compute the geometrical repartition maps. As a first case study, in vivo features of AF and NP regions of the L4/5 IVD were analysed and visualised. Practical relevance of our developed framework for a clinical purpose is discussed. In fact, our framework allows useful information of IVD to be quantified and...

ESTIMATION OF MUSCLE FORCE DERIVED FROM IN VIVO MR ELASTOGRAPHY TESTS: A PRELIMINARY STUDY

The objective is to estimate the vastus medialis (VM) muscle force from multifrequency magnetic resonance elastography (MMRE) tests and two different rheological models (Voigt and springpot). Healthy participants (N = 13) underwent multifrequency (70, 90 and 110 Hz) magnetic resonance elastography MMRE tests. Thus, in vivo experimental elastic (μ) properties of the VM in passive and active (20% MVC) conditions were characterized. Moreover, the muscle viscosity (η) was determined with Voigt and springpot rheological models, in both muscle states. Subsequently, the VM muscle forces were calculated with a generic musculoskeletal model (OpenSIM) where the active and passive shear moduli (μ) were implemented. The viscosity measured with the two rheological models increased when the muscle is contracted. During the stance and the swing phases, the VM tensile forces decrease and the VM force was lower with the springpot model. It can be noted that during the swing phase, the muscle forces estimated from springpot model showed a higher standard deviation compared to the Voigt model. This last result may indicate a strong sensitivity of the muscle force to the change of active and passive contractile components in the swing phase of gait. This study provides for the first time an estimation of the muscle tensile forces for lower limb, during human motion, from in vivo experimental muscle mechanical properties. The assessment of individualized muscle forces during motion is valuable for finite element models, increasing the patient specific parameters. This novel muscle database will be of use for the clinician to better elucidate the muscle pathophysiology and to better monitor the effects of the muscle disease.

Estimation of Patient Specific Lumbar Spine Muscle Forces Using Multi-physical Musculoskeletal Model and Dynamic MRI

Trunk muscle forces are of great interest in the diagnosis and treatment of low back pain diseases. Musculoskeletal modeling is often used to estimate muscle forces using optimization principle. Available parameterized multibody lumbar spine models used generic geometries and literature-based values leading to inaccurate muscle architecture and muscle forces not reliable for a specific case. In this present study, a multi-physical musculoskeletal model of the lumbar spine was developed from medical imaging to estimate patient specific trunk muscle forces with lumbar spine range of motions derived from dynamic MRI data in supine position. As results, a 3D patient specific musculoskeletal model was developed with 126 muscle fascicles. Maximal estimated forces of all muscle groups range from 3 to 40 N for hyperlordosis motion. The higher muscle forces were estimated in iliocostalis lumborum pars lumborum. This study has demonstrated that patient specific modeling is essential for clinical analysis of lumbar spine.

Computer-aided decision system to diagnose pathologies concerning the musculo-skeletal system of the lower limbs

In this abstract, a computer-aided decision system (CADS) based on ontology in pediatric orthopaedics is developed to diagnose pathologies concerning the musculo-skeletal system of the lower limbs. The period 2000–2010 was declared the ‘decade of bones and joints’. Studing the impact of the pathologies concerning the musculo-skeletal system of the lower limbs is a challenge. The diagnosis decision and rehabilitation treatment depend on the geographical conditions and also the knowledge of the experts. Our system is developed in order to allow equality in the diagnosis, decision and treatment.