Use this URL to cite or link to this record in EThOS: http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.679686
Title: The development of a validated preoperative staging system for rectal cancer using MRI
Author: Taylor, Fiona
ISNI:       0000 0004 5371 9385
Awarding Body: Imperial College London
Current Institution: Imperial College London
Date of Award: 2015
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Abstract:
Rectal cancer is a common and complex form of colorectal malignancy which is the second largest cause of cancer death in the United Kingdom. The need for an accurate method of staging as a guide to selecting treatment has become increasingly important with the recent advances in options for preoperative therapy. It is now clearly understood that there are a number of prognostic features that can predict a poor outlook. These include; local tumour extent, involved circumferential resection margin, involved lymph nodes and extramural venous invasion. Traditionally these factors have been noted on histopathology of the resected specimen by which time the opportunity to institute preoperative therapy has been lost. Identification of these factors prior to surgery would be of paramount importance in potentially improving the outcome for these selected patients. MRI has now been shown to be proficient at identifying many of these features. The MERCURY study (Magnetic Resonance Imaging and Rectal Cancer European Equivalence Study) recruited 679 patients from 11 different centres, prior to surgery (in 2002-2003) and was able to demonstrate the ability of MRI to predict margin involvement and local extent of tumour invasion. Data has been collected on the 5 year outcome of 374 patients consenting to follow up in the MERCURY study. This thesis explores the relationship of the distance to the circumferential resection margin, the prognostic significance of predicted involvement of the margin and the ability of MRI to identify patients with early tumours, good prognosis tumours and those with poor prognostic features. The aim is to investigate the significance of these factors in predicting the long term outcome of these patients.
Supervisor: Brown, Gina ; Tekkis, Paris Sponsor: Not available
Qualification Name: Thesis (M.D.) Qualification Level: Doctoral
EThOS ID: uk.bl.ethos.679686  DOI: Not available
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