Altered mechanical loading is a widely suggested, but poorly understood potential cause of cartilage degeneration in osteoarthritis. In rodents, osteoarthritis is induced following destabilization of the medial meniscus (DMM). This study estimates knee kinematics and contact forces in rats with DMM to gain better insight into the specific mechanisms underlying disease development in this widely-used model. Unilateral knee surgery was performed in adult male Sprague-Dawley rats (n=5 with DMM, n=5 with sham surgery). Radio-opaque beads were implanted on their femur and tibia. 8 weeks following knee surgery, rat gait was recorded using the 3D²YMOX setup (Sanctorum et al. 2019, simultaneous acquisition of biplanar XRay videos and ground reaction forces). 10 trials (1 per rat) were calibrated and processed in XMALab (Knörlein et al. 2016). Hindlimb bony landmarks were labeled on the XRay videos using transfer learning (Deeplabcut, Mathis et al. 2019; Laurence-Chasen et al. 2020). A generic OpenSim musculoskeletal model of the rat hindlimb (Johnson et al. 2008) was adapted to include a 3-degree-of-freedom knee. Inverse kinematics, inverse dynamics, static optimization of muscle forces, and joint reaction analysis were performed. In rats with DMM, knee adduction was lower compared to sham surgery. Ground reaction forces were less variable with DMM, resulting in less variability in joint external moments. The mediolateral ground reaction force was lower, resulting in lower hip adduction moment, thus less force was produced by the rectus femoris. Rats with DMM tended to break rather than propel, resulting in lower hip flexion moment, thus less force was produced by the semimembranosus. These results are consistent with lower knee contact forces in the anteroposterior and axial directions. These preliminary data indicate no overloading of the knee joint in rats with DMM, compared with sham surgery. We are currently expanding our
Anterior cruciate ligament (acl) reconstruction is one of the most commonly performed procedures in orthopedics for acl injury. While literature suggest short-term good-to-excellent functional results, a significant number of long-term studies report unexplained early oa development, regardless type of reconstruction. The present study reports the feasibility analysis and development of a clinical protocol, integrating different methodologies, able to determine which acl reconstruction technique could have the best chance to prevent oa. It gives also clinicians an effective tool to minimize the incidence of early oa. A prospective clinical trial was defined to evaluate clinical outcome, biochemical changes in cartilage, biomechanical parameters and possible development of oa. The most common reconstruction techniques were selected for this study, including hamstring single-bundle, single-bundle with extraarticular tenodesis and anatomical double-bundle. Power analysis was performed in terms of changes at cartilage level measurable by mri with t2 mapping. A sample size of 42 patients with isolated traumatic acl injury were therefore identified, considering a possible 10% to follow-up. Subjects presenting skeletal immaturity, degenerative tear of acl, other potential risk factors of oa and previous knee surgery were excluded. Included patients were randomized and underwent one of the 3 specified reconstruction techniques. The patients were evaluated pre-operatively, intra-operatively and post-operatively at 4 and 18 months of follow-up. Clinical evaluation were performed at each time using subjective scores (koos) and generic health status (sf-12). The activity level were documented (marx) as well as objective function (ikdc). Preliminary results allow to verify kinematic patterns during active tasks, including level walking, stair descending and squatting using dynamic roentgen sterephotogrammetric analysis (rsa) methodology before and after the injured ligament reconstruction. Intra-operative kinematics was also available by using a dedicated navigation system, thus to verify knee laxity at the time of surgery. Additionally, non-invasive assessment was possible both before the reconstruction and during the whole follow-up period by using inertial sensors. Integrating 3d models with kinematic data, estimation of contact areas of stress patterns on cartilage was also possible. The presented integrate protocol allowed to acquired different types of information concerning clinical assessment, biochemical changes in cartilage and biomechanical parameters to identify which acl reconstruction could present the most chondroprotective behavior. Preliminary data showed all the potential of the proposed
Cell-based therapies offer a promising strategy to treat tendon injuries and diseases. Both mesenchymal stromal cells (MSCs) and pluripotent stem cells (PSCs) are good candidates for such applications due to their self-renewing and differentiation capacity. However, the translation of cell-based therapies from bench to bedside can be hindered by the use of animal-derived components in ancillary materials and by the lack of standardised media and protocols for in vitro tenogenic differentiation. To address this, we have optimized animal component-free (ACF)
Aim of this study was the development of a dynamic FE-framework to identify worst-case size combinations and kinematics in a virtual wear simulator setup covering five daily activities and high, dynamic loads. Two cruciate sacrificing knee designs (D1 & D2) were tested physically on a wear-testing machine prior the model development using a high demanding, daily activity protocol (HDA) [1]. A simplified FE-setup was generated, reduced to the 3D geometries of the assembly whereas the representation of the mechanical wear simulator conditions and the load transmission was achieved by joint elements. Inertial and other time-related effects of the physical situation were compensated by a system of spring- and damper elements. Using a time-series signal optimization approach on the anterior-posterior translation and the internal-external rotation results for each activity, 38 variable parameters were varied in between pre-defined limits in a semiautomatic
This study aims to create a novel computational
Developments in the field of additive manufacturing have allowed significant improvements in the design and production of scaffolds with biologically relevant features to treat bone defects. Unfortunately, the
In 2021 the bone grafting market was worth €2.72 billion globally. As allograft bone has a limited supply and risk of disease transmission, the demand for synthetic grafting substitutes (BGS) continues to grow while allograft bone grafts steadily decrease. Synthetic BGS are low in mechanical strength and bioactivity, inspiring the development of novel grafting materials, a traditionally laborious and expensive process. Here a novel BGS derived from sustainably grown coral was evaluated. Coral-derived scaffolds are a natural calcium carbonate bio-ceramic, which induces osteogenesis in bone marrow mesenchymal stem cells (MSCs), the cells responsible for maintaining bone homeostasis and orchestrating fracture repair. By 3D printing MSCs in coral-laden bioinks we utilise high throughput (HT) fabrication and evaluation of osteogenesis, overcoming the limitations of traditional screening methods. MSC and coral-laden GelXA (CELLINK) bioinks were 3D printed in square bottom 96 well plates using a CELLINK BIO X printer with pneumatic adapter Samples were non-destructively monitored during the culture period, evaluating both the sample and the culture media for metabolism (PrestoBlue), cytotoxicity (lactose dehydrogenase (LDH)) and osteogenic differentiation (alkaline phosphatase (ALP)). Endpoint, destructive assays used included qRT-PCR and SEM imaging. The inclusion of coral in the printed bioink was biocompatable with the MSCs, as reflected by maintained metabolism and low LDH release. The inclusion of coral induced osteogenic differentiation in the MSCs as seen by ALP secretion and increased RUNX2, collagen I and osteocalcin transcription. Sustainably grown coral was successfully incorporated into bioinks, reproducibly 3D printed, non-destructively monitored throughout culture and induced osteogenic differentiation in MSCs. This HT fabrication and monitoring
It is known that the gait dynamics of elderly substantially differs from that of young people. However, it has not been well studied how this age-related gait dynamics affects the knee biomechanics, e.g., cartilage mechanical response. In this study, we investigated how aging affects knee biomechanics in a female population using subject-specific computational models. Two female subjects (ages of 23 and 69) with no musculoskeletal disorders were recruited. Korea National Institute for Bioethics Policy Review Board approved the study. Participants walked at a self-selected speed (SWS), 110% of SWS, and 120% of SWS on 10 m flat ground. Three-dimensional marker trajectories and ground reaction forces (Motion Analysis, USA), and lower limbs’ muscle activities were measured (EMG, Noraxon USA). Knee cartilage and menisci geometries were obtained from subjects’ magnetic resonance images (3T, GE Health Care). An EMG-assisted musculoskeletal finite element modeling
While the COVID-19 pandemic highlighted the need for more accessible anatomy instruction tools, it is also well known that the time allocated to practical anatomy teaching has reduced in the past decades. Notably, the opportunity for anatomy students to learn osteology is not prioritised, nor is the ability of students to appreciate osteological variation. As a potential method of increasing accessibility to bone models, this study describes the process of developing 3D-printed replicas of human bones using a combination of structured light scanning (SLS) technology and 3D printing. Human bones were obtained from the Anatomy Lab at the University of Edinburgh and were digitised using SLS via an Einscan H scanner. The resulting data was then used to print multiple replicas of varying materials, colours, scales and resolutions on an Ultimaker S3 3D printer. To gather opinion on these models and their variables, surveys were completed by anatomy students and educators (n=57). Data was collected using a Likert scale response, as well as free-text answers to gather qualitative information. 3D scans of the scapula, atlas (C1 vertebrae) and femur were successfully obtained. Plastic replicas were produced with defined variables in 4 separate stations e.g. different colours, to obtain results from survey respondents. For colour, 87.7% of survey respondents preferred white models, with 7% preferring orange and 5.3% preferring blue. For material, 47.4% of respondents preferred PLA (Polylactic acid), while 33.3% preferred ABS (Acrylonitrile butadiene styrene), 12.3% preferred Pet-G (Polyethylene terephthalate glycol), 3.5% preferred Glassbend and 3.5% had no preference. Additional results based on scale and resolution were also collected. This initial study has demonstrated a proof-of-concept
Although 3D-printed porous dental implants may possess improved osseointegration potential, they must exhibit appropriate fatigue strength. Finite element analysis (FEA) has the potential to predict the fatigue life of implants and accelerate their development. This work aimed at developing and validating an FEA-based tool to predict the fatigue behavior of porous dental implants. Test samples mimicking dental implants were designed as 4.5 mm-diameter cylinders with a fully porous section around bone level. Three porosity levels (50%, 60% and 70%) and two unit cell types (Schwarz Primitive (SP) and Schwarz W (SW)) were combined to generate six designs that were split between calibration (60SP, 70SP, 60SW, 70SW) and validation (50SP, 50SW) sets. Twenty-eight samples per design were additively manufactured from titanium powder (Ti6Al4V). The samples were tested under bending compression loading (ISO 14801) monotonically (N=4/design) to determine ultimate load (F. ult. ) (Instron 5866) and cyclically at six load levels between 50% and 10% of F. ult. (N=4/design/load level) (DYNA5dent). Failure force results were fitted to F/F. ult. = a(N. f. ). b. (Eq1) with N. f. being the number of cycles to failure, to identify parameters a and b. The endurance limit (F. e. ) was evaluated at N. f. = 5M cycles. Finite element models were built to predict the yield load (F. yield. ) of each design. Combining a linear correlation between FEA-based F. yield. and experimental F. ult. with equation Eq1 enabled FEA-based prediction of F. e. . For all designs, F. e. was comprised between 10% (all four samples surviving) and 15% (at least one failure) of F. ult. The FEA-based tool predicted F. e. values of 11.7% and 12.0% of F. ult. for the validation sets of 50SP and 50SW, respectively. Thus, the developed FEA-based
A complete design-manufacturing process for delivering customized foot orthoses by means of digital technologies is presented. Moreover, this feasibility study aims to combine a semi-automatic modelling approach with the use of low-cost devices for 3D scanning and 3D printing. In clinical practice, traditional methods for manufacturing customized foot orthoses are completely manual, mainly based on plaster casting plus hand fabrication, and are widely used among practitioners. Therefore, results depend on skills and expertise of individual orthoptists and podiatrists that need considerable training and practice in order to obtain optimal functional devices. On the other side, novel approaches for design and manufacturing customized foot orthoses by means of digital technologies (generally based on 3D scanning, 3D modelling and 3D printing) are recently reported as a valid alternative method to overcome these limitations. This study has been carried out in an interdisciplinary approach between the staff of Design and Methods in Industrial Engineering and the staff of Podology with the aim to assess the feasibility of a novel user-friendly and cost-effective solution for delivering customized functional foot orthoses. More specifically, a Generative Design (GD)
Regulatory bodies impose stringent pre-market controls to certify the safety and compatibility of medical devices. However, internationally recognized standard tests may be expensive, time consuming and challenging for orthopedic implants because of many possible sizes and configurations. In addition, cost and time of standard testing may endanger the feasibility of custom-device production obtained through innovative manufacturing technologies like 3d printing. Modeling and simulation (M&S) tools could be used by manufactures and at point-of-care to improve design confidence and reliability, accelerate design cycles and processes, and optimize the amount of physical testing to be conducted. We propose an integrated cloud platform to perform in silico testing for orthopedic devices, assessing mechanical safety and electromagnetic compatibility, in line with recognized standards and regulatory guidelines. The . InSilicoTrials.com. platform contains two M&S tools for orthopedic devices: CONSELF and NuMRis. CONSELF (. conself.com. ) uses Salome-Meca 2017 to compute static implant stresses and strains on metallic orthopedic devices, following the requirements and considerations of ASTM F2996-20 for non-modular hip femoral stems and ASTM F3161-16 for total knee femoral components. Simulation results were consistent with those reported in the two standards. NuMRis (. numris.insilicomri.com. ) uses ANSYS HFSS and ANSYS Mechanical 2019R3 to compute radio-frequency energy absorption and induced heating in 1.5T and 3T MRI coils, replicating the ASTM F2182-19e2 Standard Test Method. Simulation results were validated against in vitro measurements. The integrated M&S
The human musculoskeletal system is a biological composite of hard and soft material phases organized into a complex 3D structure. The replication of mechanical properties in 3-dimensional space, so called ‘4D’ techniques, therefore promises next-generation of prosthetics and engineering structures for the musculoskeletal system. Approaches using in situ indentation of tissue correlated with micro computed tomography (μCT) are used here to provide a 4D data set that is representative of the native tissue at high fidelity. Multi-material 3D printing is exploited to realize the collected 4D data set by using materials with a wide range of mechanical properties and printing structures representative of native tissue. We demonstrate this correlative approach to reproduce bone structures and highlight a
Orbital floor (OF) fractures are commonly treated by implanting either bioinert titanium or polyethylene implants, or by autologous grafts. A personalized implant made of biodegradable and osteopromotive poly(trimethylene carbonate) loaded with hydroxyapatite (PTMC-HA) could be a suitable alternative for patients where a permanent implant could be detrimental. A
Introduction. A deep squat (DS) is a challenging motion at the level of the hip joint generating substantial reaction forces (HJRF). During DS, the hip flexion angle approximates the functional range of hip motion. In some hip morphologies this femoroacetabular conflict has been shown to occur as early as 80° of hip flexion. So far in-vivo HJRF measurements have been limited to instrumented hip implants in a limited number of older patients performing incomplete squats (< 50° hip flexion and < 80° knee flexion). Clearly, young adults have a different kinetical profile with hip and knee flexion ranges going well over 100 degrees. Since hip loading data on this subgroup of the population is lacking and performing invasive measurements would be unfeasible, this study aimed to report a personalised numerical model solution based on inverse dynamics to calculate realistic in silico HJRF values during DS. M&M. Fifty athletic males (18–25 years old) were prospectively recruited for motion and morphological analysis. DS motion capture (MoCap) acquisitions and MRI scans of the lower extremities with gait lab marker positions were obtained. The AnyBody Modelling System (v6.1.1) was used to implement a novel personalisation
Biomechanical interpretations of bone adaptation in biological reconstructions following bone tumors would be crucial for orthopedic oncologists, particularly if based on quantitative observations. This would help to plan for surgical treatments, rehabilitative programs and communication with the patients. In particular, outcomes of the Capanna technique, which combines bone allograft and vascularized fibula autograft, lead to stable and durable reconstructions [1, 2], and different remodeling patterns have been described [3] as a response to mechanical loading. However, there are several events that are not understood and require a biomechanical interpretation, as the evolution patterns can evolve towards conditions that threaten the strength of the reconstruction. We aimed to (i) analyze the biomechanical adaptation of a femoral reconstruction after Ewing sarcoma, in terms of morphological and densitometric evolution of bone from CT data, internal loads acting on the bone during movement, mechanical competence of the reconstruction, and (ii) relate in-progress bone resorption to the mechanical stimulus induced by different motor activities. Eight CT datasets of a patient (8 yrs at surgery using the Capanna technique) during 76-month follow-up were available. The evolution of bone morphology, density and moments of inertia was quantified. At the last control, the patient underwent gait analysis (walking, chair rise/sit, stair ascent/descent, squat). We created a multiscale musculoskeletal and finite element model from CT scans and motion analysis data at the end of follow-up, using state-of-the-art modeling
Using Python scripting it is possible to automate the pre-processing, solving and post-processing stages of finite element analysis using ABAQUS software. This is particularly useful when running multiple models parametrically. When the model involves a bony part, it is necessary to assign material properties based on the CT scan to represent bone heterogeneity, and unfortunately this cannot currently be done from within ABAQUS using software such as Bonemat [1]. To address this issue a Python package was written called ‘py_bonemat_abaqus’ to assign material properties from within ABAQUS. The purpose of this study was to compare the material assignments of py_bonemat_abaqus and Bonemat, to compare the processing speed, and to describe the
There is a critical need for safe innovation in total joint replacements to address the demands of an ageing yet increasingly active population. The development of robust implant designs requires consideration of uncertainties including patient related factors such as bone morphology but also activity related loads and the variability in the surgical procedure itself. Here we present an integrated framework considering these sources of variability and its application to assess the performance of the femoral component of a total hip replacement (THR). The framework offers four key features. To consider variability in bone properties, an automated
Summary. A retrospective study on 98 patients shows that FE-based bone strength from CT data (using validated FE models) is a suitable candidate to discriminate fractured versus controls within a clinical cohort. Introduction. Subject-specific Finite element models (FEM) from CT data are a promising tool to non-invasively assess the bone strength and the risk of fracture of bones in vivo in individual patients. The current clinical indicators, based on the epidemiological models like the FRAX tool, give limitation estimation of the risk of femoral neck fracture and they do not account for the mechanical determinants of the fracture. Aim of the present study is to prove the better predictive accuracy of individualised computer models based a CT-FEM protocol, with the accuracy of a widely used standard of care, the FRAX risk indicator. Patients and Methods. This retrospective cohort is individually-matched case control study composed by 98 Caucasian women who were at least 5 years post menopause. The case group consisted of 49 patients who had sustained a hip fracture (36 intra-capsular and 13 extra-capsular fractures) within the previous 90 days due to low-energy trauma. The CT datasets were segmented (using the ITK-Snap software) in order to extract the periosteal bone surface. Unstructured meshes (10-node tetrahedral elements) were generated using ANSYS mesh morphing software. Each CT dataset was calibrated using the European Spine Phantom. The inhomogeneous material properties were mapped from CT datasets into the FEM with the BoneMat_V3 software. Bone strength was evaluated in quasi-axial loading conditions, for a set of 12 different configurations sampling the cone of recorded in vivo hip joint reactions, and was defined as the minimum load inducing on the femoral neck surface an elastic principal strain value greater than a limit value. Results. There were no statistically significant difference between the fracture and the control groups for age, height and weight (p<0.05). All indices of areal bone mineral density (aBMD) and the volumetric mineral density (vBMD) between fractured and controls showed on average a lower value for fractured respect of the controls, with similar mean difference (14% for aBMD and 13% for the vBMD). FEM-predicted strength differed between fractured and non-fractured on average for 20%. To evaluate its ability to identify patients at risk of hip fracture, FEM-based strength was compared to the FRAX predictor by computing for each predictor the Receiver Operating Characteristic (ROC) curve, and the Area Under the Curve (AUC). The individualised risk predictor based on FEM bone strength was found to perform significantly better (AUC=0.76) than FRAX (AUC=0.66). When the FEM-based strength indicator was combined with available clinical information in a logistic regression, the resulting predictor achieved in this retrospective study an excellent accuracy (AUC=0.82). Discussion. This study confirms that individualised, CT- FEM, when generated using to the state-of-the-art protocols, can provide a predictor of the risk of hip fracture more accurate than those based on clinical data alone. In the integrated
The objective of this study was to develop a test for the rapid (within 25 minutes) intraoperative detection of bacteria from synovial fluid to diagnose periprosthetic joint infection (PJI). The 16s rDNA test combines a polymerase chain reaction (PCR) for amplification of 16s rDNA with a lateral flow immunoassay in one fully automated system. The synovial fluid of 77 patients undergoing joint aspiration or primary or revision total hip or knee surgery was prospectively collected. The cohort was divided into a proof-of-principle cohort (n = 17) and a validation cohort (n = 60). Using the proof-of-principle cohort, an optimal cut-off for the discrimination between PJI and non-PJI samples was determined. PJI was defined as detection of the same bacterial species in a minimum of two microbiological samples, positive histology, and presence of a sinus tract or intra-articular pus.Objectives
Methods