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.

Analysis of liver viscosity behavior as a function of multifrequency magnetic resonance elastography (MMRE) postprocessing.

PURPOSE: To analyze the relevance of the viscosity measurement as a liver diagnostic marker. MATERIALS AND METHODS: To determine the level of fibrosis, a Fibroscan test was performed on 40 subjects (10 healthy volunteers and 30 patients). Subsequently, multifrequency magnetic resonance elastography (MMRE) tests were made with a pneumatic driver at 60, 70, and 80 Hz. Phase images were analyzed with two different postprocessing methods, without (Method 1) and with (Method 2) the inversion algorithm (IA), using rheological models (Voigt, springpot) in order to characterize the viscoelastic properties (viscosity: η and elasticity: µ). RESULTS: MRE cartography of the viscous tendency (G″MRE_M2 ) measured within the region of interest (ROI) of the liver increased as a function of the level of fibrosis. Similar results were also obtained for the viscosity (ηmodels_M1 ) calculated with a postprocessing without IA. However, the viscosity (ηmodels_M2 ) remained constant with the stage of fibrosis when the postprocessing was composed of an IA. The experimental (µMRE_M1 and G'MRE_M2 ) and rheological (µmodels_M2 and µmodels_M1 ) elasticities always increased with the level of fibrosis regardless of the postprocessing method. CONCLUSION: The variation of the liver viscosity parameter as a function of postprocessing revealed that this parameter should be further investigated to demonstrate its relevance in clinical practice.

Non-destructive Characterization of Skeletal Muscle Extracellular Matrix Morphology by Combining Optical Coherence Tomography (OCT) Imaging with Tissue Clearing.

Histology is an essential step to visualize and analyze the microstructure of any biological tissue; however, histological processing is often irreversible, and histological samples are unable to be imaged or tested further. In this work, a novel non-destructive protocol is proposed for morphological analysis of skeletal muscles, combining Optical Coherence Tomography (OCT) imaging with Tissue Clearing. Imaging combining OCT and Propylene Glycol (PG) as a tissue-clearing agent, was performed on rat tail and extensor digitorum longus (EDL) muscle. The results show that the extracellular matrix morphology of skeletal muscles, including muscular fibers and the whole microstructure architecture were clearly identified. PG improved OCT imaging as measured by image quality metric Contrast Per Pixel CPP (increases by 3.9%), Naturalness Image Quality Evaluator NIQE (decreases by 23%), and Volume of Interest VOI size (higher for CPP and lower for NIQE values). The tendon microstructure was observed with less precision, as collagen fibers could not be clearly detected. The reversibility of the optical effects of the PG on the immersed tissue (in a Phosphate-Buffered Saline solution) was studied comparing native and rehydrated OCT image acquisition from a single EDL sample. Optical properties and microstructure visibility (CPP and NIQE) have been recovered to 99% of the native sample values. Moreover, clearing process caused shrinkage of the tissue recovered to 86% of the original width. Future work will aim to employ the proposed experimental protocol to identify the local mechanical properties of biological tissues.

Reinforcement learning coupled with finite element modeling for facial motion learning.

BACKGROUND AND OBJECTIVE: Facial palsy patients or patients with facial transplantation have abnormal facial motion due to altered facial muscle functions and nerve damage. Computer-aided system and physics-based models have been developed to provide objective and quantitative information. However, the predictive capacity of these solutions is still limited to explore the facial motion patterns with emerging properties. The present study aims to couple the reinforcement learning and the finite element modeling for facial motion learning and prediction. METHODS: A novel modeling workflow for learning facial motion was developed. A physically-based model of the face within the Artisynth modeling platform was used. Information exchange protocol was proposed to link reinforcement learning and rigid multi-bodies dynamics outcomes. Two reinforcement learning algorithms (deep deterministic policy gradient (DDPG) and Twin-delayed DDPG (TD3)) were used and implemented to drive the simulations of symmetry-oriented and smile movements. Numerical outcomes were compared to experimental observations (Bosphorus database) for evaluation and validation purposes. RESULTS: As result, after more than 100 episodes of exploring the environment, the agent starts to learn from previous trials and can find the optimal policy after more than 300 episodes of training. Regarding the symmetry-oriented motion, the muscle excitations predicted by the trained agent help to increase the value of reward from R = -2.06 to R = -0.23, which counts for ∼89% improvement of the symmetry value of the face. For smile-oriented motion, two points at the edge of the mouth move up 0.35 cm, which is within the range of movements estimated from the Bosphorus database (0.4 ± 0.32 cm). CONCLUSIONS: The present study explored the muscle excitation patterns by coupling reinforcement learning with a detailed finite element model of the face. We developed, for the first time, a novel coupling scheme to integrate the finite element simulation into the reinforcement learning process for facial motion learning. As perspectives, this present workflow will be applied for facial palsy and facial transplantation patients to guide and optimize the functional rehabilitation program.

Fast 3D Face Reconstruction from a Single Image Using Different Deep Learning Approaches for Facial Palsy Patients.

The 3D reconstruction of an accurate face model is essential for delivering reliable feedback for clinical decision support. Medical imaging and specific depth sensors are accurate but not suitable for an easy-to-use and portable tool. The recent development of deep learning (DL) models opens new challenges for 3D shape reconstruction from a single image. However, the 3D face shape reconstruction of facial palsy patients is still a challenge, and this has not been investigated. The contribution of the present study is to apply these state-of-the-art methods to reconstruct the 3D face shape models of facial palsy patients in natural and mimic postures from one single image. Three different methods (3D Basel Morphable model and two 3D Deep Pre-trained models) were applied to the dataset of two healthy subjects and two facial palsy patients. The reconstructed outcomes were compared to the 3D shapes reconstructed using Kinect-driven and MRI-based information. As a result, the best mean error of the reconstructed face according to the Kinect-driven reconstructed shape is 1.5±1.1 mm. The best error range is 1.9±1.4 mm when compared to the MRI-based shapes. Before using the procedure to reconstruct the 3D faces of patients with facial palsy or other facial disorders, several ideas for increasing the accuracy of the reconstruction can be discussed based on the results. This present study opens new avenues for the fast reconstruction of the 3D face shapes of facial palsy patients from a single image. As perspectives, the best DL method will be implemented into our computer-aided decision support system for facial disorders.

A simple and effective 1D-element discrete-based method for computational bone remodeling.

In-silico models applied to bone remodeling are widely used to investigate bone mechanics, bone diseases, bone-implant interactions, and also the effect of treatments of bone pathologies. This article proposes a new methodology to solve the bone remodeling problem using one-dimensional (1D) elements to discretize trabecular structures more efficiently for 2D and 3D domains. An Euler integration scheme is coupled with the momentum equations to obtain the evolution of material density at each step. For the simulations, the equations were solved by using the finite element method, and two benchmark tests were solved varying mesh parameters. Proximal femur and calcaneus bone were selected as study cases given the vast research available on the topology of these bones, and compared with the anatomical features of trabecular bone reported in the literature. The presented methodology has proven to be efficient in optimizing topologies of lattice structures; It can predict the trend of formation patterns of the main trabecular groups from two different cancellous bones (femur and calcaneus) using domains set up by discrete elements as a starting point. Preliminary results confirm that the proposed approach is suitable and useful in bone remodeling problems leading to a considerable computational cost reduction. Characteristics similar to those encountered in topological optimization algorithms were identified in the benchmark tests as well, showing the viability of the proposed approach in other applications such as bio-inspired design.

Computer-aided decision system for the clubfeet deformities.

A computer-aided decision system (CADS) based on ontology in pediatric orthopedics was developed to assess, without assumptions performed, the abnormalities of the musculoskeletal system of lower limbs. The CADS consists of four components. The first component is a diagnosis-based ontology, called Ontologie du Système Musculosquelettique des Membres Inférieurs (OSMMI). The second component is a database for collecting clinical observations, e.g., the birth classification of the clubfeet deformities. The third component uses statistical methods (principal component analysis and decision tree) for constructing an approach to evaluate new issues. The last component is an interactive module for managing the interaction between patients, experts, and the due CADS. Our system has been validated clinically with the real patient data obtained from the Infant Surgery Service in the hospital of Robert Debré in Paris. Our CADS is a good solution to compare the studies of the clubfeet deformities before and after the treatment using a universally scoring system. The assessment, conservative treatment, and monitoring were set up. Our system was developed to allow a better assessment for improving the knowledge and thus the evaluation and treatment of the musculoskeletal pathologies, e.g., the clubfeet deformities.

Morphogenesis of the human palma arch using three-dimensional geometric modeling.

The hand goes through complex morphological modifications during embryogenesis. The goal of this study was to use geometric modeling to study the morphometric modifications of the palmar arch. Five embryos were used for the study (sizes: 15, 17, 23, 30, and 44 mm). After digitalization of histologic sections (Sony DXC-930P 3CCD camera, Leica Qwin) and segmentation of the metacarpal cartilaginous matrices (Winsurf 4.3 software), geometric modeling and calculations were performed using MSC.Patran 2005r2 software. Correlations (r > 0.99) were found between embryo size and metacarpal volume, metacarpal surface, and the surface of the modeled palmar arch. The growth of the palmar arch is nonhomothetic. Significant reduction (P = 0.05) in the divergence of the 2nd, 3rd, 4th, and 5th metacarpals was observed. Deepening of the palmar arch is correlated with embryo size and age (r > 0.99). Geometric modeling allows 3D rendering of histologic sections and thus quantitative description of the morphogenesis. The results of this study support the hypothesis that opposition of the thumb in correlation with deepening of the palmar arch appears early in embryological development. It constitutes a specific morphological characteristic that appears very early in the human phylum. The fact that the human thumb is naturally in opposition in the resting position is a consequence of this morphogenesis. The thumb's resting position has received little attention in clinical settings and should be considered as the reference position for biomechanical analysis of the thumb column.

Enhanced facial expression recognition using 3D point sets and geometric deep learning.

Facial expression recognition plays an essential role in human conversation and human-computer interaction. Previous research studies have recognized facial expressions mainly based on 2D image processing requiring sensitive feature engineering and conventional machine learning approaches. The purpose of the present study was to recognize facial expressions by applying a new class of deep learning called geometric deep learning directly on 3D point cloud data. Two databases (Bosphorus and SIAT-3DFE) were used. The Bosphorus database includes sixty-five subjects with seven basic expressions (i.e., anger, disgust, fearness, happiness, sadness, surprise, and neutral). The SIAT-3DFE database has 150 subjects and 4 basic facial expressions (neutral, happiness, sadness, and surprise). First, preprocessing procedures such as face center cropping, data augmentation, and point cloud denoising were applied on 3D face scans. Then, a geometric deep learning model called PointNet++ was applied. A hyperparameter tuning process was performed to find the optimal model parameters. Finally, the developed model was evaluated using the recognition rate and confusion matrix. The facial expression recognition accuracy on the Bosphorus database was 69.01% for 7 expressions and could reach 85.85% when recognizing five specific expressions (anger, disgust, happiness, surprise, and neutral). The recognition rate was 78.70% with the SIAT-3DFE database. The present study suggested that 3D point cloud could be directly processed for facial expression recognition by using geometric deep learning approach. In perspectives, the developed model will be applied for facial palsy patients to guide and optimize the functional rehabilitation program.

Kinect-driven Patient-specific Head, Skull, and Muscle Network Modelling for Facial Palsy Patients.

BACKGROUND AND OBJECTIVE: Facial palsy negatively affects both professional and personal life qualities of involved patients. Classical facial rehabilitation strategies can recover facial mimics into their normal and symmetrical movements and appearances. However, there is a lack of objective, quantitative, and in-vivo facial texture and muscle activation bio-feedbacks for personalizing rehabilitation programs and diagnosing recovering progresses. Consequently, this study proposed a novel patient-specific modelling method for generating a full patient specific head model from a visual sensor and then computing the facial texture and muscle activation in real-time for further clinical decision making. METHODS: The modeling workflow includes (1) Kinect-to-head, (2) head-to-skull, and (3) muscle network definition & generation processes. In the Kinect-to-head process, subject-specific data acquired from a new user in neutral mimic were used for generating his/her geometrical head model with facial texture. In particular, a template head model was deformed to optimally fit with high-definition facial points acquired by the Kinect sensor. Moreover, the facial texture was also merged from his/her facial images in left, right, and center points of view. In the head-to-skull process, a generic skull model was deformed so that its shape was statistically fitted with his/her geometrical head model. In the muscle network definition & generation process, a muscle network was defined from the head and skull models for computing muscle strains during facial movements. Muscle insertion points and muscle attachment points were defined as vertex positions on the head model and the skull model respectively based on the standard facial anatomy. Three healthy subjects and two facial palsy patients were selected for validating the proposed method. In neutral positions, magnetic resonance imaging (MRI)-based head and skull models were compared with Kinect-based head and skull models. In mimic positions, infrared depth-based head models in smiling and [u]-pronouncing mimics were compared with appropriate animated Kinect-driven head models. The Hausdorff distance metric was used for these comparisons. Moreover, computed muscle lengths and strains in the tested facial mimics were validated with reported values in literature. RESULTS: With the current hardware configuration, the patient-specific head model with skull and muscle network could be fast generated within 17.16±0.37s and animated in real-time with the framerate of 40 fps. In neutral positions, the best mean error was 1.91 mm for the head models and 3.21 mm for the skull models. On facial regions, the best mean errors were 1.53 mm and 2.82 mm for head and skull models respectively. On muscle insertion/attachment point regions, the best mean errors were 1.09 mm and 2.16 mm for head and skull models respectively. In mimic positions, these errors were 2.02 mm in smiling mimics and 2.00 mm in [u]-pronouncing mimics for the head models on facial regions. All above error values were computed on a one-time validation procedure. Facial muscles exhibited muscle shortening and muscle elongating for smiling and pronunciation of sound [u] respectively. Extracted muscle features (i.e. muscle length and strain) are in agreement with experimental and literature data. CONCLUSIONS: This study proposed a novel modeling method for fast generating and animating patient-specific biomechanical head model with facial texture and muscle activation bio-feedbacks. The Kinect-driven muscle strains could be applied for further real-time muscle-oriented facial paralysis grading and other facial analysis applications.

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

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

Real-time computer vision system for tracking simultaneously subject-specific rigid head and non-rigid facial mimic movements using a contactless sensor and system of systems approach.

BACKGROUND AND OBJECTIVE: Head and facial mimic animations play important roles in various fields such as human-machine interactions, internet communications, multimedia applications, and facial mimic analysis. Numerous studies have been trying to simulate these animations. However, they hardly achieved all requirements of full rigid head and non-rigid facial mimic animations in a subject-specific manner with real-time framerates. Consequently, this present study aimed to develop a real-time computer vision system for tracking simultaneously rigid head and non-rigid facial mimic movements. METHODS: Our system was developed using the system of systems approach. A data acquisition sub-system was implemented using a contactless Kinect sensor. A subject-specific model generation sub-system was designed to create the geometrical model from the Kinect sensor without texture information. A subject-specific texture generation sub-system was designed for enhancing the reality of the generated model with texture information. A head animation sub-system with graphical user interfaces was also developed. Model accuracy and system performances were analyzed. RESULTS: The comparison with MRI-based model shows a very good accuracy level (distance deviation of ~1 mm in neutral position and an error range of [2-3 mm] for different facial mimic positions) for the generated model from our system. Moreover, the system speed can be optimized to reach a high framerate (up to 60 fps) during different head and facial mimic animations. CONCLUSIONS: This study presents a novel computer vision system for tracking simultaneously subject-specific rigid head and non-rigid facial mimic movements in real time. In perspectives, serious game technology will be integrated into this system towards a full computer-aided decision support system for facial rehabilitation.

Comparison of patient-specific computational models vs. clinical follow-up, for adjacent segment disc degeneration and bone remodelling after spinal fusion.

Spinal fusion is a standard surgical treatment for patients suffering from low back pain attributed to disc degeneration. However, results are somewhat variable and unpredictable. With fusion the kinematic behaviour of the spine is altered. Fusion and/or stabilizing implants carrying considerable load and prevent rotation of the fused segments. Associated with these changes, a risk for accelerated disc degeneration at the adjacent levels to fusion has been demonstrated. However, there is yet no method to predict the effect of fusion surgery on the adjacent tissue levels, i.e. bone and disc. The aim of this study was to develop a coupled and patient-specific mechanoregulated model to predict disc generation and changes in bone density after spinal fusion and to validate the results relative to patient follow-up data. To do so, a multiscale disc mechanoregulation adaptation framework was developed and coupled with a previously developed bone remodelling algorithm. This made it possible to determine extra cellular matrix changes in the intervertebral disc and bone density changes simultaneously based on changes in loading due to fusion surgery. It was shown that for 10 cases the predicted change in bone density and degeneration grade conforms reasonable well to clinical follow-up data. This approach helps us to understand the effect of surgical intervention on the adjacent tissue remodelling. Thereby, providing the first insight for a spine surgeon as to which patient could potentially be treated successfully by spinal fusion and in which patient has a high risk for adjacent tissue changes.

MRI-based finite element modeling of facial mimics: a case study on the paired zygomaticus major muscles.

Finite element simulation of facial mimics provides objective indicators about soft tissue functions for improving diagnosis, treatment and follow-up of facial disorders. There is a lack of in vivo experimental data for model development and validation. In this study, the contribution of the paired Zygomaticus Major (ZM) muscle contraction on the facial mimics was investigated using in vivo experimental data derived from MRI. Maximal relative differences of 7.7% and 37% were noted between MRI-based measurements and numerical outcomes for ZM and skin deformation behaviors respectively. This study opens a new direction to simulate facial mimics with in vivo data.

Rehabilitation-Oriented Serious Game Development and Evaluation Guidelines for Musculoskeletal Disorders.

BACKGROUND: The progress in information and communication technology (ICT) led to the development of a new rehabilitation technique called "serious game for functional rehabilitation." Previous works have shown that serious games can be used for general health and specific disease management. However, there is still lack of consensus on development and evaluation guidelines. It is important to note that the game performance depends on the designed scenario. OBJECTIVE: The objective of this work was to develop specific game scenarios and evaluate them with a panel of musculoskeletal patients to propose game development and evaluation guidelines. METHODS: A two-stage workflow was proposed using determinant framework. The development guideline includes the selection of three-dimensional (3D) computer graphics technologies and tools, the modeling of physical aspects, the design of rehabilitation scenarios, and the implementation of the proposed scenarios. The evaluation guideline consists of the definition of evaluation metrics, the execution of the evaluation campaign, the analysis of user results and feedbacks, and the improvement of the designed game. RESULTS: The case study for musculoskeletal disorders on the healthy control and patient groups showed the usefulness of these guidelines and associated games. All participants enjoyed the 2 developed games (football and object manipulation), and found them challenging and amusing. In particular, some healthy subjects increased their score when enhancing the level of difficulty. Furthermore, there were no risks and accidents associated with the execution of these games. CONCLUSIONS: It is expected that with the proven effectiveness of the proposed guidelines and associated games, this new rehabilitation game may be translated into clinical routine practice for the benefit of patients with musculoskeletal disorders.

Exploring various orientation measurement approaches applied to a serious game system for functional rehabilitation.

Serious games have been established as a complementary tool for conventional rehabilitation. This trend proved to be beneficial for both experts and patients since the first are able to assign and monitor virtual reality games for their patients to be executed at home, and the latter are greatly motivated by the challenges of these games rather than the repeatable and boring rehabilitation movements. In a previous work, we proposed a serious game for lower limb rehabilitation of the musculoskeletal system using the Microsoft KinectTM camera and a virtual environment. However, this system suffers from inaccurate kinematic measurement due to various external sources. Therefore, this paper explores various kinematic measurement technics to improve the accuracy of our system. Six real time orientation measurement algorithms were assessed and compared, using multiple types of sensors. The results obtained showed a better performance for our system. In fact, this study reinforced a clearer view on a low cost, real time portable system to be implemented at home.

Identification process based on shear wave propagation within a phantom using finite element modelling and magnetic resonance elastography.

Magnetic resonance elastography (MRE), based on shear wave propagation generated by a specific driver, is a non-invasive exam performed in clinical practice to improve the liver diagnosis. The purpose was to develop a finite element (FE) identification method for the mechanical characterisation of phantom mimicking soft tissues investigated with MRE technique. Thus, a 3D FE phantom model, composed of the realistic MRE liver boundary conditions, was developed to simulate the shear wave propagation with the software ABAQUS. The assumptions of homogeneity and elasticity were applied to the FE phantom model. Different ranges of mesh size, density and Poisson's ratio were tested in order to develop the most representative FE phantom model. The simulated wave displacement was visualised with a dynamic implicit analysis. Subsequently, an identification process was performed with a cost function and an optimisation loop provided the optimal elastic properties of the phantom. The present identification process was validated on a phantom model, and the perspective will be to apply this method on abdominal tissues for the set-up of new clinical MRE protocols that could be applied for the follow-up of the effects of treatments.

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.

Spatial distribution of acoustic and elastic properties of human femoral cortical bone.

The purpose of this study is to quantify the spatial distribution of acoustic velocities and elastic properties (elastic constants) on Human femoral cortical bone. Four cross sections (average thickness of 2.09+/-0.27 mm) have been cut transversally between 40% and 70% of the total length and between them parallelepiped samples in each quadrant have been cut. Ultrasonic technique in transmission with immersion focused transducers at 5 MHz and contact transducers 2.25 MHz were used on the cross sections and parallelepiped samples, respectively. The first technique allows relative spatial distribution of velocities to be obtained, meanwhile the second technique allows the direct assessment of elastic constants. For both techniques, bulk velocities were found to be lower at the posterior side with an increase along the length (from 40% to 70% total length) (p < 0.05). Densities and elastic constants show equivalent pattern of variation. These variations are mainly due the cortical porosity related to vascularisation environment. The spatial distribution of velocities exhibits significant radial variation from the endosteal to the periosteal region. This is in agreement with variation of the porosity at that location. Same range of velocities was obtained with both techniques. The range of longitudinal velocities values varies from 3548 to 3967 m/s and between 18.5 and 33.1 GPa for the bulk velocities and axial elastic constants, respectively. Our results are within the range with those found in the literature. However, it must be noted that the range of acoustic and elastic properties variation is concerning the same bone. So, our new results show the ability of the technique to quantify accurately local variation of acoustic and elastic properties (within the section and along the length) of human cortical bone. Furthermore, our immersion technique could be used to assess the spatial distribution of the elastic constants with the knowledge of spatial distribution of densities.

Transmission scanning acoustic imaging of human cortical bone and relation with the microstructure.

OBJECTIVE: To investigate and compare the spatial distribution of velocity with that of the microstructural properties (dimension of the haversian canal, percentage of porosity) on cross section of cortical bone. DESIGN: Experimental investigations permitted to quantify variation of acoustic properties related with that of the microstructural properties. BACKGROUND: Transmission ultrasonic techniques have been used in vitro and in vivo to assess the elastic and acoustic properties of Human bone, but few investigated the relationship between their variation with that of the microstructure. METHODS: Two scanning techniques (in transmission with a focused transducer at 5 MHz and an environmental scanning electronic microscope at 20 KV) enabled to obtain the spatial distribution of relative acoustic velocities and the microstructural properties (pore size and porosity). RESULTS: Increase of the velocities is related with the decrease of pore size and porosity. Around the periphery of the sections, the velocities were found to be significantly lower in the posterior side with a significant increase along the length. Radial variations are correlated to the spatial distribution of the microstructure where the endocortical region is more porous compared to the periosteal region. CONCLUSION: Significant alterations of the microstructural properties of the cortical bone reflect small variation of velocity suggesting that the velocities are not so sensitive to microstructural changes. RELEVANCE: These results are of importance for the clinicians and researchers to get a better understanding (advantages and limitation) of the use of ultrasound technique to assess material and structural properties of cortical bone. Our study suggested that velocity could be an index of porosity. Then it would be of interest to improve the clinical assessment of bone quality by describing bone both by a mineralization index and a microstructural index.