The success of cementless orthopaedic implants relies on bony ingrowth and active bone remodelling. Much research effort is invested to develop implants with controllable surface roughness and internal porous architectures that encourage these biological processes. Evaluation of these implants requires long-term and costly animal studies, which do not always yield the desired outcome requiring iteration. The aim of our study is to develop a cost-effective method to prescreen design parameters prior to animal trials to streamline implant development and reduce live animal testing burden. Ex vivo porcine cancellous bone cylinders (n=6, Ø20×12mm) were extracted from porcine knee joints with a computer-numerically-controlled milling machine under sterile conditions within 4 hours of animal sacrifice. The bone discs were implanted with Ø6×12mm additive manufactured porous titanium implants and were then cultured for 21days. Half underwent static culture in medium (DMEM, 10% FBS, 1% antibiotics) at 37°C and 5% CO2. The rest were cultured in novel high-throughput stacked configuration in a bioreactor that simulated physiological conditions after surgery: the fluid flow and cyclic compression force were set at 10ml/min and 10–150 N (1Hz,5000 cycles/day) respectively. Stains were administered at days 7 and 14. Samples were evaluated with widefield microscopy, scanning electron microscopy (SEM) and with histology. More bone remodelling was observed on the samples cultured within the bioreactor: widefield imaging showed more remodelling at the boundaries between the implant-bone interface, while SEM revealed immature bone tissue integration within the pores of the implant. Histological analysis confirmed these results, with many more trabecular struts with new osteoid formation on the samples cultured dynamically compared to static ones. Ex vivo bone can be used to analyse new implant technologies with lower cost and ethical impact than animal trial. Physiological conditions (load and fluid flow) promoted bone ingrowth and remodelling.
Knee alignment affects both the development and surgical treatment of knee osteoarthritis. Automating femorotibial angle (FTA) and hip-knee-ankle angle (HKA) measurement from radiographs could improve reliability and save time. Further, if the gold-standard HKA from full-limb radiographs could be accurately predicted from knee-only radiographs then the need for more expensive equipment and radiation exposure could be reduced. The aim of this research is to assess if deep learning methods can predict FTA and HKA angle from posteroanterior (PA) knee radiographs. Convolutional neural networks with densely connected final layers were trained to analyse PA knee radiographs from the Osteoarthritis Initiative (OAI) database with corresponding angle measurements. The FTA dataset with 6149 radiographs and HKA dataset with 2351 radiographs were split into training, validation and test datasets in a 70:15:15 ratio. Separate models were learnt for the prediction of FTA and HKA, which were trained using mean squared error as a loss function. Heat maps were used to identify the anatomical features within each image that most contributed to the predicted angles.Abstract
Objectives
Methods
In other medical fields, smart implantable devices are enabling decentralised monitoring of patients and early detection of disease. Despite research-focused smart orthopaedic implants dating back to the 1980s, such implants have not been adopted into regular clinical practice. The hardware footprint and commercial cost of components for sensing, powering, processing, and communicating are too large for mass-market use. However, a low-cost, minimal-modification solution that could detect loosening and infection would have considerable benefits for both patients and healthcare providers. This proof-of-concept study aimed to determine if loosening/infection data could be monitored with only two components inside an implant: a single-element sensor and simple communication element. The sensor and coil were embedded onto a representative cemented total knee replacement. The implant was then cemented onto synthetic bone using polymethylmethacrylate (PMMA). Wireless measurements for loosening and infection were then made across different thicknesses of porcine tissue to characterise the sensor's accuracy for a range of implantation depths. Loosening was simulated by taking measurements before and after compromising the implant-cement interface, with fluid influx simulated with phosphate-buffered saline solution. Elevated temperature was used as a proxy for infection, with the sensor calibrated wirelessly through 5 mm of porcine tissue across a temperature range of 26–40°C.Introduction & Aims
Methods
Bone is a hierarchically structured hard tissue that consists of approximately 70 wt% low-crystallinity hydroxyapatite. Intricate tubular channels, such as Haversian canals, Volkman's canals, and canaliculi are a preserved feature of bone microstructure. These structures provide pathways for vasculature and facilitate cell-to-cell communication processes, together supporting viability of cellular components and aiding in remodeling processes. Unfortunately, many commercial bone augmentation materials consist of highly crystalline phases that are absent of the structuring present within the native tissue they are replacing. This work reports on a the development of a novel bone augmentation material that is able to generate biologically analogous tubular calcium phosphate mineral structures from hydrogel-based spheres that can be packed into defects similar to those encountered in vivo. Calcium loaded spheres were made by adding 5 wt% agar powder to 1 M calcium nitrate solutions, before heating the mixture to 80–90 oC and feeding droplets of gel into a reservoir of liquid nitrogen. Deposition of tubular mineral was initiated by exposure to ammonium phosphate solutions at concentrations between 500 mM and 1 M, and was characterized by micro-XRF mapping, XRD and SEM techniques. For an ex vivo model, human bone tissue was collected from patients undergoing elective knee replacement surgery. The United Kingdom National Research Ethics Service (East of Scotland Research Ethics Service) provided ethical approval (11/ES/1044). The augmented defect of the model was characterised by micro-XRF mapping and micro-CT techniques.Background
Experimental
Persistent low back and leg pain is a common and highly disabling musculoskeletal condition. Many patients seek the opinion of a neurosurgeon with a view to surgical intervention. Few data are available which document the experiences of patients at these consultations. To investigate the experiences of patients seeking a neurosurgical opinion for back and leg pain.Background
Aims
