CT Scanning

Since its introduction in 1972, X-ray computed tomography (CT) has evolved into an essential diagnostic imaging tool for a continually increasing variety of clinical applications. The goal of this book was not simply to summarize currently available CT imaging techniques but also to provide clinical perspectives, advances in hybrid technologies, new applications other than medicine and an outlook on future developments. Major experts in this growing field contributed to this book, which is geared to radiologists, orthopedic surgeons, engineers, and clinical and basic researchers. We believe that CT scanning is an effective and essential tools in treatment planning, basic understanding of physiology, and and tackling the ever-increasing challenge of diagnosis in our society

A situated method for modelling and analysing the efficiency of cognitive activity during the radiology reporting workflow using eye-tracking

The success of modern medical imaging systems has created a data overload problem, where an ever-increasing number of examinations, generate more images per study, which all need to be evaluated by radiologists or other reporting practitioners. This operational bottleneck hasthe potentialto create fatigue and burnout due to the high mental workload that is required to keep up with the demand. The focus of this problem centres around the cognitive complexity of the radiology reporting workflow, and the associated workstation interactions involved in diagnostic report generation. There has been a significant body of work evaluating the behaviour of radiologists using controlled laboratory-based techniques, but these non-naturalistic studies fail to address the highly context dependant nature of the radiology reporting workflow. For example, the early eye-tracking work of Charmody et al; the psychometric studies by Krupinksi et al; and also the workstation interaction evaluations of Moise et al; whilst highly principled, can be all be questioned on the grounds of ecological validity and authenticity. This thesis asserts that the only way to truly understand and resolve the radiology data overload problem, is by developing a situated method for observing the reporting workflow that can evaluate the behaviours of the reporting clinicians in relation to their authentic reporting context. To this end, this study has set out to develop a new approach for observing and analysing the cognitive activities of the reporters relative to the demands of their genuine working environment, and supported through the application of a Critical Realist’s perspective to naturalistic workplace observations. This goal was achieved through the development of four key project deliverables: • An in-depth exploratory study of the radiology overload problem based on an extensive literature review and situated observations of authentic reporting workflows. • A descriptive hierarchical activity modelof the reporting workflow that can be understood by both clinicians, application designers and researchers. • A generalised methodology and research protocolfor conducting situated observations of the radiology reporting workflow, using an analysis based on the process tracing of sequencesof Object Related Actions, captured with eye-tracking and multimodal recordings. • A set of case studies demonstrating the applicability of the research protocol involving 5 Radiology Consultants, 2 Radiology Registrars and one Reporting Radiographer at a single NHS Hospital within the UK. The final workflow evaluation of the case studies demonstrated that activities such as error correction, and the collection of supporting radiological information from previous studies is complex, time consuming and cognitively demanding. These types of activities are characterised by long, low utility actions that correspond to what Kahneman refers to as “Thinking Slow”. Also, the participants appeared to be self-optimising their workflow via a sparse use of complex functionality and system tools. From these observations, the author recommends that any intervention that can reduce the number and the duration of the object related actions used to produce radiology reports, will reduce cognitive load, increase overall efficiency, and go some way to alleviate the data overload problem. 4 This study establishes a new set of situated techniques that are able to capture and quantify the complex dynamicactivities that make up the radiology reporting workflow. Itis hoped that the ability to distil usefuland impactful insightsfrom the user’s workstation behaviours can be used as the basis for further development in the area of workflow analysis and redesign, which will ultimately improve the working lives of Radiologists and other Reporting Clinicians. Lastly, the generic nature of these techniques make them amenable for use within any type of complex sociotechnical human factors study related to the cognitive efficiency of the user

Opportunistic diagnosis of osteoporosis, fragile bone strength and vertebral fractures from routine CT scans; a review of approved technology systems and pathways to implementation

Osteoporosis causes bones to become weak, porous and fracture more easily. While a vertebral fracture is the archetypal fracture of osteoporosis, it is also the most difficult to diagnose clinically. Patients often suffer further spine or other fractures, deformity, height loss and pain before diagnosis. There were an estimated 520,000 fragility fractures in the United Kingdom (UK) in 2017 (costing £4.5 billion), a figure set to increase 30% by 2030. One way to improve both vertebral fracture identification and the diagnosis of osteoporosis is to assess a patient’s spine or hips during routine computed tomography (CT) scans. Patients attend routine CT for diagnosis and monitoring of various medical conditions, but the skeleton can be overlooked as radiologists concentrate on the primary reason for scanning. More than half a million CT scans done each year in the National Health Service (NHS) could potentially be screened for osteoporosis (increasing 5% annually). If CT-based screening became embedded in practice, then the technique could have a positive clinical impact in the identification of fragility fracture and/or low bone density. Several companies have developed software methods to diagnose osteoporosis/fragile bone strength and/or identify vertebral fractures in CT datasets, using various methods that include image processing, computational modelling, artificial intelligence and biomechanical engineering concepts. Technology to evaluate Hounsfield units is used to calculate bone density, but not necessarily bone strength. In this rapid evidence review, we summarise the current literature underpinning approved technologies for opportunistic screening of routine CT images to identify fractures, bone density or strength information. We highlight how other new software technologies have become embedded in NHS clinical practice (having overcome barriers to implementation) and highlight how the novel osteoporosis technologies could follow suit. We define the key unanswered questions where further research is needed to enable the adoption of these technologies for maximal patient benefit

Bodies of Seeing: A video ethnography of academic x-ray image interpretation training and professional vision in undergraduate radiology and radiography education

This thesis reports on a UK-based video ethnography of academic x-ray image interpretation training across two undergraduate courses in radiology and radiography. By studying the teaching and learning practices of the classroom, I initially explore the professional vision of x-ray image interpretation and how its relation to normal radiographic anatomy founds the practice of being ‘critical’. This criticality accomplishes a faculty of perceptual norms that is coded and organised and also, therefore, of a specific radiological vision. Professionals’ commitment to the cognitivist rhetoric of ‘looking at’/‘pattern recognition’ builds this critical perception, a perception that deepens in organisation when professionals endorse a ‘systematic approach’ that mediates matter-of-fact thoroughness and offers a helpful critical commentary towards the image. In what follows, I explore how x-ray image interpretation is constituted in case presentations. During training, x-ray images are treated with suspicion and as misleading and are aligned with a commitment to discursive contexts of ‘missed abnormality’, ‘interpretive risk’, and ‘technical error’. The image is subsequently constructed as ambiguous and that what is shown cannot be taken at face value. This interconnects with reenacting ideals around ‘seeing clearly’ that are explained through the teaching practices and material world of the academic setting and how, if misinterpretation is established, the ambiguity of the image is reduced by embodied gestures and technoscientific knowledge. By making this correction, the ambiguous image is reenacted and the misinterpretation of image content is explained. To conclude, I highlight how the professional vision of academic x-ray image interpretation prepares students for the workplace, shapes the classificatory interpretation of ab(normal) anatomy, manages ambiguity through embodied expectations and bodily norms, and cultivates body-machine relations

Surgical Data Science - from Concepts toward Clinical Translation

Recent developments in data science in general and machine learning in particular have transformed the way experts envision the future of surgery. Surgical Data Science (SDS) is a new research field that aims to improve the quality of interventional healthcare through the capture, organization, analysis and modeling of data. While an increasing number of data-driven approaches and clinical applications have been studied in the fields of radiological and clinical data science, translational success stories are still lacking in surgery. In this publication, we shed light on the underlying reasons and provide a roadmap for future advances in the field. Based on an international workshop involving leading researchers in the field of SDS, we review current practice, key achievements and initiatives as well as available standards and tools for a number of topics relevant to the field, namely (1) infrastructure for data acquisition, storage and access in the presence of regulatory constraints, (2) data annotation and sharing and (3) data analytics. We further complement this technical perspective with (4) a review of currently available SDS products and the translational progress from academia and (5) a roadmap for faster clinical translation and exploitation of the full potential of SDS, based on an international multi-round Delphi process

DEVELOPMENT OF MULTI-DIMENSIONAL X-RAY COMPUTED TOMOGRAPHY MEASUREMENTS OF LUNG TUMOURS

Metastatic disease is the most common cause of cancer-related deaths. Two established image analysis tools, the World Health Organization Handbook for Reporting Results for Cancer Treatment (2D measurement), and Response Evaluation Criteria in Solid Tumours (ID measurement), have been used to quantify metastatic tumour burden in vivo. Limitations of the ID and 2D measurements may be addressed using a 3D technique. The overall objective of this thesis was to determine the accuracy and reproducibility of a 3D measurement technique to be used as a potential imaging biomarker to quantify pulmonary metastases in vivo, using x-ray CT. We compared the accuracy and reproducibility of our 3D technique to the ID and 2D measurements using lung tumour phantoms of known dimensions and seven subjects with pulmonary metastases. Three­ dimensional measurements accurately quantified spherical and irregularly-shaped tumour phantoms (p\u3c0.05), and most observers measurement patient metastases with high intra- and inter-observer reproducibility ICC\u3e0.900