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High Tibial Osteotomy (HTO) surgery is performed as a treatment for people who have osteoarthritis (OA) affecting one side of their knee. It realigns the joint to redistribute joint loading and relieve pain. It is used by some clinicians as a valuable joint preserving intervention for patients who are too young for a total knee replacement. It is also occasionally used in asymptomatic patients to prevent further mal-alignment of the knee. To prolong the life of the joint, the angle of joint alignment correction must be sufficient to reduce loads on the medial compartment, whilst not excessively loading the lateral compartment. In current clinical practice, the angle of correction is estimated from standing static x-rays. However, dynamic gait measurements, in particular the knee adduction moment, are reported to be more highly related to clinical outcome than measures of static knee alignment. The proposed research aims to develop a method to quantify the optimum correction angle, based on a patients preoperative gait biomechanics. If new methods of calculating the correction angle can be found that improve longevity of the joint, the procedure as a service may be adopted more widely. This proposal also aims to evaluate associated changes in the forces acting through the joint using models that consider the effects of muscle forces on the joint. A patient specific dynamic model from the University of Florida will be employed in this research. This model was developed to predict the changes in knee adduction moment following HTO surgery using pre-operative gait data and the angles of correction measured from standard long leg x-rays. This research will test whether optimised models, calibrated to each patient, can predict post-surgery knee adduction moments using HTO surgical parameters. This will be the first implementation of this software using pre and post-operative patient data. This software will be adapted to determine the changes in tibial geometry required to produce the optimum post-operative knee adduction moment. The ability to calculate the optimum angles of correction based on a patient's pre-operative gait will form the basis of a new clinical tool. As part of the proposed research, open-source software (OpenSim) will be employed to investigate changes in joint reaction forces following HTO surgery. A model will be adapted for this purpose. This will be the first implementation of a musculoskeletal model to investigate changes in joint reaction forces for patients undergoing HTO and will provide a basis for further development. Joint reaction forces calculated pre-operatively and how they change post-operatively will be compared to a healthy cohort. This will provide information on the changes in loading in the knee and thus the efficacy of HTO surgery in restoring normal knee joint loading. The end product of this research will be a new tool for bespoke surgical planning and outcome measures detailing the efficacy of HTO surgery. It will enhance the biomechanical understanding of HTO realignment and demonstrate the usefulness of dynamic measurements and musculoskeletal modelling.

The Bionics+ NetworkPlus will represent the spectrum of research, clinical and industrial communities across bionic technologies within the EPSRC Grand Challenge theme of Frontiers of Physical Intervention. It will invigorate and support a cohesive, open and active network with the mission of creating a mutually supportive environment. It will lead to the co-creation of user-centred bionic solutions that are fit for purpose. These advances will have a global impact, consolidating the world-leading position of the UK. The founding tranche will focus on ambitious and transformative research, new collaborative and translational activities, and the formulation of a longer-term strategy. Within this context, as a community, we will explore and identify areas of opportunity and value, driven by Bionics users' needs, complementary to existing activity and strengths. The network will instigate and support early-stage research in these priority areas, alongside providing an outward-facing representation and engagement of the UK Bionics community. Further, we aim to contribute in an advisory capacity to public bodies, UK industry and government policy. At the time of the application, we have obtained a positive commitment from circa 70 groups including bionic users, academic partners from universities in England, Scotland, Wales and Northern Ireland and a few international partners; partners in medical devices, orthotics and prosthetics industry, both large corporates and small-medium size companies; and many clinicians, surgeons and aligned health experts from relevant NHS clinics and the private sector.

The ability to predict weather offers the potential to provide valuable information that can be used in planning health services. For example, imagine a hospital planning system that was able to predict fluctuations in demand for different services as a consequence of predictions of meteorological events such as the early February cold spell in 2009. Such a tool would result in a substantial benefit to both the NHS and health outcomes. Specifically, appropriate use of meteorological intelligence would help to:1. Improve health by reducing morbidity and mortality rates, and generally improving health outcomes.2. Improve access to services by better predicting hospital pressures due to weather events, thus allowing for hospital mangers to anticipate and better prepare for such fluctuations. This research will explore and quantify the relationship between weather patterns and extreme weather events, and their impact on various health conditions, such a heart attacks, stroke, asthma, and fractures. For example, it is thought that a sudden surge in cold temperature can cause blood to thicken slightly and blood pressure to increase, which can trigger a heart attack or stroke in vulnerable patients. There are many other reported (observed) trends such as thunderstorm-related asthma. A thunderstorm in South East England, for example, saw 640 patients presenting with severe asthma to hospital, ten times the usual number. By linking weather and health in this way, we can help save lives or minimise the risk of morbidity by creating an early warning system that can ensure at-risk patients are well informed and have sufficient medication and advice. Furthermore, this research will utilise computer simulation techniques and statistical models and apply their use to create a novel hospital operational capacity support tool (MetSim) that will utilise meteorological forecasts alongside NHS hospital data to provide information to hospitals on expected levels of emergency admissions and to alert them of sudden surges in demand and daily fluctuations. By forecasting demand in this manner, MetSim will allow hospital managers to understand more closely resulting resource needs over the short-term planning horizon and assist in planning decisions such as cancellation of elective admissions. Given that the provision of hospital resources is a matter of considerable public and political concern and has been the subject of widespread debate, this research will help the NHS more effectively and efficiently plan and manage their health services.A further benefit of MetSim is that it can act as a public health warning system. Health-weather correlations could be used by regional Strategic Health Authorities or Primary Care Trusts to alert at-risk populations. This could have significant public health benefits by ensuring such people are better informed about the forthcoming risks and have sufficient medication and appropriate medical advice. Treating patients for the health conditions evaluated in this research (to include heart disease, stroke, acute bronchitis, fractures and pneumonia) accounts for a significant proportion of the NHS budget. For example, stroke and heart disease incidence in the UK is amongst the highest in the world and these two conditions alone cost the NHS an estimated 18.3 billion annually. Using MetSim to prevent hospital admissions or improving health outcomes for even a small percentage of these patients could result in significant costs savings to NHS Trusts.This novel and valuable research involves a collaborative team of specialists in Operational Research and Statistics, with co-operation and support of the Met Office, Southampton University Hospital NHS Trust, and the Cardiff and Vale NHS Trust. The level of support, commitment and excitement about this research from these three organisations is such that between them they have pledged 60,000 towards the costs of the overall project.

Brain diseases such as tumours, head injury, epilepsy, multiple sclerosis and dementias have considerable personal, social and economic costs for the sufferers and their carers. While magnetic resonance imaging (MRI) has revolutionised the management of many brain conditions in the last 40 years, there is a need for better tools for quantifying the brain's supply of energy in terms of blood flow and vascular function and it use of energy in terms of metabolic function. For example, in the case of the most common forms of brain tumour, glioma, we lack detailed information about the heterogeneity of tissue function that could help guide better treatments such as more targeted and individualised combined radiotherapy and drug programmes. Understanding more about the tumour microenvironment will also promote the development of more effective treatments. For high-grade gliomas, particularly glioblastoma, the prognosis remains poor, highlighting an urgent clinical need. Recently, we at Cardiff University Brain Research Imaging Centre (CUBRIC), and others, have developed MRI-based tools (termed dual calibrated fMRI) to map across the human brain, with a spatial resolution of a few millimetres, the amount of oxygen that the brain is consuming (known as CMRO2) along with measures of the efficiency of blood supply. CMRO2 reflects neural activity and can be altered with disease such as tumour where there is cell proliferation and energy metabolism is changed. Knowing also the functional properties of brain blood vessels and the oxygen status of brain tissue is important for understanding whether blood supply is sufficient or the vasculature is abnormal as is often seen in tumours where vessels proliferate. Our newly developed methods have shown promise in revealing abnormalities of brain tissue energy consumption in multiple sclerosis and epilepsy. In epilepsy they may offer an alternative to the use of radiation-based PET scans in the evaluation of patients for brain surgery by identifying areas in the brain with abnormally low metabolism. However, to produce a wider clinical impact it is necessary to advance the MRI and data analysis further, such that they could then be taken forward for commercial development and routine clinical use, initially within clinical trials. Two-thirds of the proposed project will address engineering and physical science challenges to (i) speed up data acquisition to about 10 mins, a clinically feasible time, by optimising the MRI data acquisition and analysis, (ii) widen the range of tissue pathology that we can reliably measure through collection of additional MRI information and detailed biophysical modelling of tissue properties and (iii) implement efficient artificial intelligence (neural network) based data analysis that can rapidly feed the images to the clinician at the MRI scanner. The remaining one-third of the project will demonstrate the feasibility of the method and its value in application to brain tumour (glioma). We aim to show that we can map the heterogeneity of tumour tissue that can reveal the type of tumour, where it is actively growing, where it is and is not responding to treatment and where radiotherapy may be damaging healthy tissue, all helping to guide treatment decisions for maximum efficacy. Central to the success of our proposal are our partnerships with industry and the NHS. Siemens will contribute the expertise of its onsite scientist at CUBRIC for the development of the MRI technology. The Velindre Cancer Centre, South Wales' principal centre for oncology, will partner on the clinical pilot studies and help to evaluate imaging for future patient benefit. Our partners will help us to bring the methods to the point within this project, if successful, of commercial development for healthcare benefit and larger scale clinical trials to demonstrate how the methods may be used in clinical practice for diagnosis, treatment planning and monitoring.