Use this URL to cite or link to this record in EThOS: https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.819030
Title: Evaluating the opportunities for image guidance as a surgical decision-support technology to improve the quality and safety of surgery
Author: Dilley, James
ISNI:       0000 0004 9356 9844
Awarding Body: Imperial College London
Current Institution: Imperial College London
Date of Award: 2019
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Abstract:
Image guidance has been developed to improve and augment the visual input to the surgeon before and during surgical procedure. Despite much interest and research it is not yet commonplace in operating theatres or surgical workflow. This thesis sought to understand the current landscape and provide evidence for future direction and integration of image guidance systems. An initial systematic review demonstrated how existing clinical image guidance systems focused their reported outcomes on traditional clinical measures, commonly neglecting to report on areas that image guidance were designed to improve, namely user interaction as well as patient acceptability and economic impact Within a simulated environment it was shown that image guidance allows the surgeon to perform a laparoscopic cholecystectomy more accurately. However, it was surgeons using a low-barrier image guidance system based on preoperative images rather than perfectly registered intraoperative system that experienced better surgical outcomes. A second study demonstrated that surgeon’s behaviour is unaltered between the simulated and real robotic environments. This validated the simulated robotic environment as a platform in which image guidance can be developed as well as the use of eye metrics as an objective measure of surgeon behaviour. The second part of the thesis explored image guidance in the preoperative workflow setting. After initially confirming the importance of imaging to surgeons in planning and predicting complications, two studies were performed. The first of these demonstrated that surgeons using an image guidance platform were more accurately able to predict the surgical procedures and complexity required to achieve their surgical aim. The second found that as the complexity of the cases increases, those using the image guidance system were more accurate in identifying the anatomy that was affected or involved. Importantly in both of these studies the surgeon’s mental workload was reduced. This thesis has demonstrated that image guidance can improve surgical outcomes and benefit the surgeon. Improving publication focus, leveraging the simulated environment and expanding use of image guidance into the preoperative workflow are key components towards realizing its translation as a surgical decision-support technology to improve the quality and safety of surgery.
Supervisor: Mayer, Erik ; Darzi, Ara ; Pratt, Philip Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID: uk.bl.ethos.819030  DOI:
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