Phenotypical changes of osteocytes in osteoarthritis

This thesis focuses on the role of a bone cell, osteocytes in the progression of osteoarthritis. The biological relevance of this study has opened doors to new possibilities of understanding the pathogenesis of osteoarthritis

Correlating flow induced shear stress and chondrocytes activity in micro-porous scaffold using computational fluid dynamic and rapid prototyping

Flow induced shear stress plays an important role in regulating cell growth and distribution in scaffolds. This study sought to correlate wall shear stress and chondrocytes activity for engineering design of micro-porous osteochondral grafts based on the hypothesis that it is possible to capture and discriminate between the transmitted force and cell response at the inner irregularities. Unlike common tissue engineering therapies with perfusion bioreactors in which flow-mediated stress is the controlling parameter, this work assigned the associated stress as a function of porosity to influence in vitro proliferation of chondrocytes. D-optimality criterion was used to accommodate three pore characteristics for appraisal in a mixed level fractional design of experiment (DOE); namely, pore size (4 levels), distribution pattern (2 levels) and density (3 levels). Micro-porous scaffolds (n=12) were fabricated according to the DOE using rapid prototyping of an acrylic-based bio-photopolymer. Computational fluid dynamics (CFD) models were created correspondingly and used on an idealized boundary condition with a Newtonian fluid domain to simulate the dynamic microenvironment inside the pores. In vitro condition was reproduced for the 3D printed constructs seeded by high pellet densities of human chondrocytes and cultured for 72 hours. The results showed that cell proliferation was significantly different in the constructs (p<0.05). Inlet fluid velocity of 3×10-2mms-1 and average shear stress of 5.65×10-2 Pa corresponded with increased cell proliferation for scaffolds with smaller pores in hexagonal pattern and lower densities. Although the analytical solution of a Poiseuille flow inside the pores was found insufficient for the description of the flow profile probably due to the outside flow induced turbulence, it showed that the shear stress would increase with cell growth and decrease with pore size. This correlation demonstrated the basis for determining the relation between the induced stress and chondrocyte activity to optimize microfabrication of engineered cartilaginous constructs

A stimulatory effect of Ca3ZrSi2O9 bioceramics on cementogenic/osteogenic differentiation of periodontal ligament cells

The regeneration of periodontal tissues to cure periodontitis remains a medical challenge. Therefore, it is of great importance to develop a novel biomaterial that could induce cementogenesis and osteogenesis in periodontal tissue engineering. Calcium silicate (Ca–Si) based ceramics have been found to be potential bioactive materials due to their osteostimulatory effect. Recently, it is reported that zirconium modified calcium-silicate-based (Ca3ZrSi2O9) ceramics stimulate cell proliferation and osteogenic differentiation of osteoblasts. However, it is unknown whether Ca3ZrSi2O9 ceramics possess specific cementogenic stimulation for human periodontal ligament cells (hPDLCs) in periodontal tissue regeneration in vitro. The purpose of this study was to investigate whether Ca3ZrSi2O9 ceramic disks and their ionic extracts could stimulate cell growth and cementogenic/osteogenic differentiation of hPDLCs; the possible molecular mechanism involved in this process was also explored by investigating the Wnt/β-catenin signalling pathway of hPDLCs. Our results showed that Ca3ZrSi2O9 ceramic disks supported cell adhesion, proliferation and significantly up-regulated relative alkaline phosphatase (ALP) activity, cementogenic/osteogenic gene expression (CEMP1, CAP, ALP and OPN) and Wnt/β-catenin signalling pathway-related genes (AXIN2 and CTNNB) for hPDLCs, compared to that of β-tricalcium phosphate (β-TCP) bioceramic disks and blank controls. The ionic extracts from Ca3ZrSi2O9 powders also significantly enhanced relative ALP activity, cementogenic/osteogenic and Wnt/β-catenin-related gene expression of hPDLCs. The present results demonstrate that Ca3ZrSi2O9 ceramics are capable of stimulating cementogenic/osteogenic differentiation of hPDLCs possibly via activation of the Wnt/β-catenin signalling pathway, suggesting that Ca3ZrSi2O9 ceramics have the potential to be used for periodontal tissue regeneration

Kinematic model of the human leg using DH parameters

Robotic-assisted surgical procedures have recently increased in popularity in clinical environments. Applications of clinically approved surgical robots range from minimally invasive surgery to open joint replacements. In hip and knee orthopaedic procedures, access to leg joint cavities require constant manipulation of the patient’s leg to a high degree of accuracy to reduce surgical injuries. This study develops a nine degree of freedom serial kinematic model of the human leg, using the well known Denavit Hartenberg Parameters, for robotic-assisted leg manipulation during orthopaedic leg surgery. The proposed model is validated through human cadaver experiments with an optical tracking system used as ground-truth to measure the leg pose. The knee and foot workspace for the model determines the pose of the leg and in comparing it to cadaver leg position. The positional error relative to the cadaver leg was found to be 0.43mm and 0.4mm respectively, with a maximum uncertainty of 3.51mm in the foot position. It demonstrates that the proposed model provides an accurate representation of the human leg motion for automated leg manipulation during orthopaedic surgery.</p

Correction to: The effects of gender, age, and videogame experience on performance and experiences with a surgical robotic arm: an exploratory study with general public (Journal of Robotic Surgery, (2022), 16, 3, (621-629), 10.1007/s11701-021-01287-4)

The original version of this article unfortunately contained a mistake. One author name was missing. Missing author name and affiliation should be Jeremy Opie Wellcome/EPSRC Centre for Interventional and Surgical Sciences (WEISS), University College London (UCL), London, UK And author group should be Selen Türkay · Kate Letheren · Jeremy Opie · Ross Crawford · Jonathan Roberts · Anjali Tumkur Jaiprakash.</p

The effects of gender, age, and videogame experience on performance and experiences with a surgical robotic arm : an exploratory study with general public

Robotic surgery is increasing in prevalence, thanks to its potential benefits for patients (e.g., reduced blood loss) and surgeons (e.g., ergonomics). It is important to know what inherent characteristics of potential surgeons may facilitate robotic surgery training and performance. Findings from previous studies indicate videogames can be inexpensive tools that help improve hand–eye coordination, coordination of 3-D movements with 2-D images, and spatial orientation. In the context of robotic-assisted knee arthroscopy using a MAKO robotic arm, this study explored performance and subjective experiences of novices (N = 104) with a fake bone shaving task at a public event. Participants’ performance was measured based on how much of the bone they successfully shaved. Findings showed that duration of videogame play per week was negatively related to performance with the robotic arm. Male and female participants performed similarly on the bone shaving task, and reported similar difficulty with and enjoyment of the task. However, female participants who played videogames performed better than those who did not play videogames. Participants who were younger than 11 had the worst performance and the most difficulty with the robotic arm. Overall, the findings indicate that the effect of videogame experience on the performance with the robotic arm may differ based on gender and age. This has implications on the length of training for surgeons of different gender using videogames and other emerging technologies.</p

Bayesian CNN for segmentation uncertainty inference on 4D ultrasound images of the femoral cartilage for guidance in robotic knee arthroscopy

Ultrasound (US) imaging is a complex imaging modality, where the tissues are typically characterised by an inhomogeneous image intensity and by a variable image definition at the boundaries that depends on the direction of the incident sound wave. For this reason, conventional image segmentation approaches where the regions of interest are represented by exact masks are inherently inefficient for US images. To solve this issue, we present the first application of a Bayesian convolutional neural network (CNN) based on Monte Carlo dropout on US imaging. This approach is particularly relevant for quantitative applications since differently from traditional CNNs, it enables to infer for each image pixel not only the probability of being part of the target but also the algorithm confidence (i.e. uncertainty) in assigning that probability. In this work, this technique has been applied on US images of the femoral cartilage in the framework of a new application, where high-refresh-rate volumetric US is used for guidance in minimally invasive robotic surgery for the knee. Two options were explored, where the Bayesian CNN was trained with the femoral cartilage contoured either on US, or on magnetic resonance imaging (MRI) and then projected onto the corresponding US volume. To evaluate the segmentation performance, we propose a novel approach where a probabilistic ground-truth annotation was generated combining the femoral cartilage contours from registered US and MRI volumes. Both cases produced a significantly better segmentation performance when compared against traditional CNNs, achieving a dice score coefficient increase of about 6% and 8%, respectively