Browsing by Author "Evans, P."

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    Developing focal construct technology for in vivo diagnosis of osteoporosis
    (IOP, 2019-03-18) Greenwood, Charlene; Rogers, Keith; Wilson, M.; Lyburn, Iain Douglas; Evans, P.; Prokopiou, Danae
    Osteoporosis is a prevalent bone disease around the world, characterised by low bone mineral density and increased fracture risk. Currently, the gold standard for identifying osteoporosis and increased fracture risk is through quantification of bone mineral density (BMD), using dual energy X-ray absorption (DEXA). However, the use of BMD to diagnose osteoporosis is not without limitation and arguably the risk of osteoporotic fracture should be determined collectively by bone mass, architecture and physicochemistry of the mineral composite building blocks. Rather than depending exclusively on the 'mass' of bone, our previous research investigated predicting the risk of fracture using 'bone quality'. The work highlighted that the material properties of OP tissue differ significantly to that of 'normal' bone and for the first time reported the clinical value of new biomarkers (obtained from X-ray scatter signatures) for fracture risk prediction. Thus, in order to improve fracture prediction models, diagnostic tools need to be developed which not only measure bone mineral density, but also bone quality. This pilot study builds on our previous work and aims to develop a new technology, Focal Construct Technology (FCT), which is hoped can measure XRD signatures in vivo. Our previous work was performed entirely with interrogating probes applied in transmission mode. This has some disadvantages that would be overcome were reflection mode employed. This study involves the creation of unique, high impact data with the potential to form the basis of a new generation of medical diagnostic instrumentation. A systematic series of conventional reflection mode ex vivo experiments were performed in which bone specimens were examined through increasing thicknesses of overlaying muscle/fat/skin. Further, we applied FCT to these geometries. This had not previously been attempted and required some initial modelling to ensure correct topologies of the hollow beams. The results from this study suggest it may be possible to obtain the parameters in vivo with the same precision as those obtained within the laboratory when using FCT.
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    Diffraction enhanced kinetic depth X-ray imaging
    (2013-12-04) Dicken, Anthony; Rogers, Keith; Evans, P.
    An increasing number of fields would benefit from a single analytical probe that can characterise bulk objects that vary in morphology and/or material composition. These fields include security screening, medicine and material science. In this study the X-ray region is shown to be an effective probe for the characterisation of materials. The most prominent analytical techniques that utilise X-radiation are reviewed. The study then focuses on methods of amalgamating the three dimensional power of kinetic depth X-ray (KDFX) imaging with the materials discrimination of angular dispersive X-ray diffraction (ADXRD), thus providing KDEX with a much needed material specific counterpart. A knowledge of the sample position is essential for the correct interpretation of diffraction signatures. Two different sensor geometries (i.e. circumferential and linear) that are able to collect end interpret multiple unknown material diffraction patterns and attribute them to their respective loci within an inspection volume are investigated. The circumferential and linear detector geometries are hypothesised, simulated and then tested in an experimental setting with the later demonstrating a greater ability at discerning between mixed diffraction patterns produced by differing materials. Factors known to confound the linear diffraction method such as sample thickness and radiation energy have been explored and quantified with a possible means of mitigation being identified (i.e. via increasing the sample to detector distance). A series of diffraction patterns (following the linear diffraction appoach) were obtained from a single phantom object that was simultaneously interrogated via KDEX imaging. Areas containing diffraction signatures matched from a threat library have been highlighted in the KDEX imagery via colour encoding and match index is inferred by intensity. This union is the first example of its kind and is called diffraction enhanced KDEX imagery. Finally an additional source of information obtained from object disparity is explored as an alternative means of calculating sample loci. This offers a greater level of integration between these two complimentary techniques as object disparity could be used to reinforce the results produced by the linear diffraction geometry.