Evaluation of 135- and 150-degree sliding hip screws

Sliding hip screws are routinely used to repair Garden III femoral neck factures. This research seeks to better understand the influence of the hip screw angle on the performance of the fixation. The mechanics of fractured femurs repaired with 135- and 150-degree sliding fixation devices are explored using experimental, finite element, and analytical modeling. The experimental study involves testing of both intact and fixated femurs; the finite element work centers on two-dimensional models of intact and fixated femurs; and the analytical modeling explores the forces, moments and stresses in the fixation. The analytical model predicts that the screw will serve as a hinge point leading to compressive contact forces across the fracture faces below the screw. The peak stresses I the screw are seen to be a function of the installation position of the screw on the fracture plane. Screw are seen to have lower stresses when they are installed low on the fracture plane, especially in the case of the 150-degree screw. The experimental and finite element results both predict that the 150-degree fixation will be stiffer than the 135-degree fixation. The finite element calculations are verified by comparison with the experimental results

X-ray based machine vision system for distal locking of intramedullary nails

In surgical procedures for femoral shaft fracture treatment, current techniques for locking the distal end of intramedullary nails, using two screws, rely heavily on the use of two-dimensional X-ray images to guide three-dimensional bone drilling processes. Therefore, a large number of X-ray images are required, as the surgeon uses his/her skills and experience to locate the distal hole axes on the intramedullary nail. The long-term effects of X-ray radiation and their relation to different types of cancer still remain uncertain. Therefore, there is a need to develop a surgical technique that can limit the use of X-rays during the distal locking procedure. A Robotic-Assisted Orthopaedic Surgery System has been developed at Loughborough University named Loughborough Orthopaedic Assistant System (LOAS) to assist orthopaedic surgeons during distal-locking of intramedullary nails. It uses a calibration frame and a C-arm X-ray unit. The system simplifies the current approach as it uses only two near-orthogonal X-ray images to determine the drilling trajectory of the distal-locking holes, thereby considerably reducing irradiation to both the surgeon and patient. The LOAS differs from existing computer-assisted orthopaedic surgery systems, as it eliminates the need for optical tracking equipment which tends to clutter the operating theatre environment and requires care in maintaining the line of sight. Additionally use of optical tracking equipment makes such systems an expensive method for surgical guidance in distal-locking of intramedullary nails. This study is specifically concerned with the improvements of the existing system. [Continues.

Enhancing Total Hip Replacement Complications Diagnosis: A Deep Learning Approach with Clinical Knowledge Integration

The increased rate of Total Hip Replacement (THR) for relieving hip pain and improving the quality of life has been accompanied by a rise in associated post-operative complications, which are evaluated and monitored mainly through clinical assessment of the X-ray images. The current clinical practice depends on the manual identification of important regions and the analysis of different features in arthroplasty X-ray images which can lead to subjectivity, prone to human error and delay diagnosis. Deep Learning (DL) based techniques showed outstanding outcomes across various image analysis tasks. However, the success of these networks is subjected to the availability of a very large, accurately annotated and well-balanced dataset - a constraint that is considered a main challenge for many medical image analysis tasks including THR. This thesis focuses on automating the analysis of THR X-ray images to aid in the diagnosis and treatment planning of various THR complications. THR X-ray images including post-operation images and after Peri-Prosthetic Femur Fracture (PFF) images of a wide range of implants and various positioning and orientations, are collected to this end. Different Convolutional Neural Network (CNN) architectures are explored for PFF classification to observe how these networks perform in the presence of class imbalance and a limited number of data and with complex image patterns, either using full X-ray images or Region of Interest (ROI) images. This demonstrates that typical CNN-based methods succeeded in detecting PFF with DenseNet achieving an F1 score of 95%, while exhibiting low performance in the classification of PFF types, achieving an F1 score of 54% with GoogleNet, Resnet and DenseNet. This lower performance is attributed to the increased complexity of the task and the imbalanced distribution of the classes. To this end, the incorporation of THR medical knowledge with DL model is investigated. The segmentation of the femoral implant component and the detection of important landmarks are formulated as simultaneous tasks within multi-task CNN that combines segmentation maps of implant with the regression of shape parameters derived from the Statistical Shape Model (SSM). Compared to the state-of-the-art, this integrated approach improves the estimation of the implant shape by a 6% dice score, making the segmentation realistic and allowing automatic detection of the important landmarks which can help in detecting many THR complications. For PFF diagnosis, the incorporation of the clinical process of interpreting THR X-ray images with CNN is developed. For this purpose, the process of clinical interpretation of PFF X-ray images is defined and the method is designed accordingly. Four feature extraction components are trained to construct features from distinctive regions of the X-ray image that are defined automatically. The extracted features are fused to classify the X-ray image into a specific fracture type. The developed approach improved PFF diagnosis by approximately 8% AUC score compared to state-of-the-art methods, signifying notable clinical advancement. Finally, the virtual pre-operative planning of bone fracture reduction surgery is explored which is important to reduce surgery time and minimize potential risks. The main obstacle toward the planning task is to define the matching between fragments. Therefore, 3D puzzle-solving method is formulated by introducing a new fragment representation and feature extraction method that improves the matching between fragments. The initial evaluation of the method demonstrates promising performance for the virtual reassembly of broken objects

1st EFORT European Consensus: Medical & Scientific Research Requirements for the Clinical Introduction of Artificial Joint Arthroplasty Devices

Innovations in Orthopaedics and Traumatology have contributed to the achievement of a high-quality level of care in musculoskeletal disorders and injuries over the past decades. The applications of new implants as well as diagnostic and therapeutic techniques in addition to implementation of clinical research, have significantly improved patient outcomes, reduced complication rates and length of hospital stay in many areas. However, the regulatory framework is extensive, and there is a lack of understanding and clarity in daily practice what the meaning of clinical & pre‐clinical evidence as required by the MDR is. Thus, understanding and clarity are of utmost importance for introduction of new implants and implant-related instrumentation in combination with surgical technique to ensure a safe use of implants and treatment of patients. Therefore EFORT launched IPSI, The Implant and Patient Safety Initiative, which starting from an inaugural workshop in 2021 issued a set of recommendations, notably through a subsequent Delphi Process involving the National Member Societies of EFORT, European Specialty Societies as well as International Experts. These recommendations provide surgeons, researchers, implant manufacturers as well as patients and health authorities with a consensus of the development, implementation, and dissemination of innovation in the field of arthroplasty. The intended key outcomes of this 1st EFORT European Consensus on “Medical & Scientific Research Requirements for the Clinical Introduction of Artificial Joint Arthroplasty Devices”are consented, practical pathways to maintain innovation and optimisation of orthopaedic products and workflows within the boundaries of MDR 2017/745. Open Access practical guidelines based on adequate, state of the art pre-clinical and clinical evaluation methodologies for the introduction of joint replacements and implant-related instrumentation shall provide hands-on orientation for orthopaedic surgeons, research institutes and laboratories, orthopaedic device manufacturers, Notified Bodies but also for National Institutes and authorities, patient representatives and further stakeholders. We would like to acknowledge and thank the Scientific Committee members, all International Expert Delegates, the Delegates from European National & Specialty Societies and the Editorial Team for their outstanding contributions and support during this EFORT European Consensus

Improved human soft tissue thigh surrogates for superior assessment of sports personal protective equipment

Human surrogates are representations of living humans, commonly adopted to better understand human response to impacts. Though surrogates have been widely used in automotive, defence and medical industries with varying levels of biofidelity, their primary application in the sporting goods industry has been through primitive rigid anvils used in assessing personal protective equipment (PPE) effectiveness. In sports, absence from competition is an important severity measure and soft tissue injuries such as contusions and lacerations are serious concerns. Consequently, impact surrogates for the sporting goods industry need a more subtle description of the relevant soft tissues to assess impact severity and mitigation accurately to indicate the likelihood of injury. The fundamental aim for this research study was to establish a method to enable the development of superior, complementary, increasingly complex synthetic and computational impact surrogates for improved assessment of sports personal protective equipment. With a particular focus on the thigh segment, research was conducted to evaluate incremental increases in surrogate complexity. Throughout this study, empirical assessment of synthetic surrogates and computational evaluation using finite element (FE) models were employed to further knowledge on design features influencing soft tissue surrogates in a cost and time efficient manner. To develop a more representative human impact surrogate, the tissue structures considered, geometries and materials were identified as key components influencing the mechanical response of surrogates. As a design tool, FE models were used to evaluate the changes in impact response elicited with different soft tissue layer configurations. The study showed the importance of skin, adipose, muscle and bone tissue structures and indicated up to 15.4% difference in maximum soft tissue displacement caused by failure to represent the skin layer. FE models were further used in this capacity in a shape evaluation study from which it was determined that a full-scale anatomically contoured thigh was necessary to show the full diversity of impact response phenomena exhibited. This was particularly pertinent in PPE evaluations where simple surrogate shapes significantly underestimated the magnitudes of displacements exhibited (up to 155% difference) when rigid shell PPE was simulated under impact conditions. Synthetic PDMS silicone simulants were then fabricated for each of the organic soft tissues to match their dynamic responses. The developed simulants exhibited a superior representation of the tissues when compared to previous single material soft tissue simulant, Silastic 3483, which showed 324%, 11,140% and -15.8% greater differences than the PDMS when compared to previously reported target organic tissue datasets for relaxed muscle, skin and adipose tissues respectively. The impact response of these PDMS surrogates were compared in FE models with previously used single material simulants in representative knee and cricket ball sports impact events. The models were each validated through experimental tests and the PDMS simulants were shown to exhibit significantly closer responses to organic tissue predictions across all impact conditions and evaluation metrics considered. An anatomically contoured synthetic thigh surrogate was fabricated using the PDMS soft tissue simulants through a novel multi-stage moulding process. The surrogate was experimentally tested under representative sports impact conditions and showed a good comparison with FE model predictions with a maximum difference in impactor displacements and peak accelerations of +6.86% and +12.5% respectively at velocities between 2 - 4 m.s-1. The value of increased biofidelity in the anatomical synthetic and virtual surrogate thighs has been proven through the incremental adoption of important surrogate elements (tissue structures, material and geometries). The predictive capabilities of each surrogate have been demonstrated through their parallel developments and staged comparisons with idealised organic tissue responses. This increase in biofidelity is introduced at modestly higher cost compared to Silastic 3483, but, given the benefits of a more representative human impact response for PPE evaluations, this is shown to be worthwhile