Physical and statistical shape modelling in craniomaxillofacial surgery: a personalised approach for outcome prediction

Orthognathic surgery involves repositioning of the jaw bones to restore face function and shape for patients who require an operation as a result of a syndrome, due to growth disturbances in childhood or after trauma. As part of the preoperative assessment, three-dimensional medical imaging and computer-assisted surgical planning help to improve outcomes, and save time and cost. Computer-assisted surgical planning involves visualisation and manipulation of the patient anatomy and can be used to aid objective diagnosis, patient communication, outcome evaluation, and surgical simulation. Despite the benefits, the adoption of three-dimensional tools has remained limited beyond specialised hospitals and traditional two-dimensional cephalometric analysis is still the gold standard. This thesis presents a multidisciplinary approach to innovative surgical simulation involving clinical patient data, medical image analysis, engineering principles, and state-of-the-art machine learning and computer vision algorithms. Two novel three-dimensional computational models were developed to overcome the limitations of current computer-assisted surgical planning tools. First, a physical modelling approach – based on a probabilistic finite element model – provided patient-specific simulations and, through training and validation, population-specific parameters. The probabilistic model was equally accurate compared to two commercial programs whilst giving additional information regarding uncertainties relating to the material properties and the mismatch in bone position between planning and surgery. Second, a statistical modelling approach was developed that presents a paradigm shift in its modelling formulation and use. Specifically, a 3D morphable model was constructed from 5,000 non-patient and orthognathic patient faces for fully-automated diagnosis and surgical planning. Contrary to traditional physical models that are limited to a finite number of tests, the statistical model employs machine learning algorithms to provide the surgeon with a goal-driven patient-specific surgical plan. The findings in this thesis provide markers for future translational research and may accelerate the adoption of the next generation surgical planning tools to further supplement the clinical decision-making process and ultimately to improve patients’ quality of life

Advanced Applications of Rapid Prototyping Technology in Modern Engineering

Rapid prototyping (RP) technology has been widely known and appreciated due to its flexible and customized manufacturing capabilities. The widely studied RP techniques include stereolithography apparatus (SLA), selective laser sintering (SLS), three-dimensional printing (3DP), fused deposition modeling (FDM), 3D plotting, solid ground curing (SGC), multiphase jet solidification (MJS), laminated object manufacturing (LOM). Different techniques are associated with different materials and/or processing principles and thus are devoted to specific applications. RP technology has no longer been only for prototype building rather has been extended for real industrial manufacturing solutions. Today, the RP technology has contributed to almost all engineering areas that include mechanical, materials, industrial, aerospace, electrical and most recently biomedical engineering. This book aims to present the advanced development of RP technologies in various engineering areas as the solutions to the real world engineering problems

User-led Innovation in the UK National Health Service

Healthcare services are delivered to patients using complex technology systems. Many innovative healthcare technologies are produced by industrial suppliers; however, healthcare staff are also active innovators of the technologies that they use in their own work. By assuming the role of user-innovators, they can create new technologies, procedures, processes and service-designs that improve and support healthcare provision. The focus of the research reported in this thesis is the phenomenon of user-led innovation of healthcare technology in the UK National Health Service (NHS). Exploratory research was carried out to develop a detailed understanding of user-led innovation within the NHS based on the perspectives of user-innovators. This thesis presents the results of the research in the form of four interpretive case studies, that contribute to an understanding of the enabling and inhibiting factors affecting user-led innovation. Each case presents an overview of the process of user-led innovation which was followed and the context in which it occurred. Several distinctive characteristics of user-led innovation are identified and a generic activity model of the user-led innovation process is described. Evaluation in user-led innovation processes is highlighted to have multiple purposes,beyond objective technology assessment. It is shown to support the on-going social-construction of user-developed technologies but also highlights the role of evaluation as a resource for exercising political influence within the innovation process. User led innovation is established as a theoretically useful and coherently defined mode of innovation, distinct from the lead user or open innovation paradigms. The major contribution of the thesis is an integrated model of healthcare technology systems that emphasises the role of protoinstitutions as critical products of user-led innovation. The thesis concludes that in order to maximise the benefit of user-led innovation in the NHS, innovation policy and practice should be broadened to recognise the role of proto-institutions as a valuable product of user-led innovation