Use this URL to cite or link to this record in EThOS: https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.785116
Title: Evaluating and optimising direct digital chest radiography
Author: Violaki, Konstantina
ISNI:       0000 0004 7970 6590
Awarding Body: UCL (University College London)
Current Institution: University College London (University of London)
Date of Award: 2019
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Abstract:
The purpose of this study is to evaluate and optimise the patient doses in chest radiography using direct digital X-ray systems. Such imaging systems were first introduced at Barts Health NHS Trust in 2012. The wide dynamic range of such systems is more tolerant to sub-optimal practice and can affect patient doses. A large database of digital chest X-ray examinations performed in 2014 at the Royal London Hospital has been used to compile a large-scale patient dose audit to evaluate and optimise chest radiography. Findings from this study suggest that there is no noticeable degradation in performance by the use of DR imaging systems, but that this is most likely attributed to the wide selection of available protocols and variable user-input. Patient data were extracted from the DICOM header along with the exposure parameters used, which were filtered to compile patient dose descriptive statistics based on the quantity of Dose Area Product (DAP). The DAP analysis showed variation in the choice of exposure settings and techniques, and that radiographers do not necessarily follow the standardised protocol settings. An anthropomorphic phantom was used to simulate the most commonly selected exposure settings in the patient dose audit, to control variation and investigate their effect on image quality. 6 regions of interest were examined to obtain the optimum Contrast-to-Noise Ratio (CNR) and Figure of Merit (FOM). A patient simulator tool was subsequently designed and manufactured to automate the process for image quality optimisation and assess the optimum CNR. The tool was experimentally tested for healthy patients as well as patients suffering from underlying chest conditions by simulating appropriate 3D printed models and was validated subjectively by a consultant radiologist. Findings suggested that doses can be reduced by a factor of 4 compared to current protocol settings for medium-sized patients. The test tool serves as a feedback control mechanism to minimise user input and optimise direct digital radiography by controlling the exposure using CNR rather than detector dose.
Supervisor: Not available Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID: uk.bl.ethos.785116  DOI: Not available
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