Use this URL to cite or link to this record in EThOS: http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.634101
Title: Mycardial applications of cardiovascular X-ray computed tomography
Author: Stirrup, James Elliott
Awarding Body: Imperial College London
Current Institution: Imperial College London
Date of Award: 2013
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Abstract:
This thesis evaluated the role of cardiovascular computed tomography (CCT) in assessing the left ventricular (LV) myocardium. The technical and clinical performance of single-slice CT for attenuation correction (CTAC) of SPECT myocardial perfusion scintigraphy (MPS) was evaluated. Early and delayed multi-slice CT (eCCT and dCCT respectively) myocardial enhancement patterns were validated against SPECT MPS (single-source CCT) and cardiovascular magnetic resonance imaging (CMR, dual-source CCT) for detection of chronic myocardial infarction (MI), as were CCT measures of segmental LV wall thickness and global and regional LV function. Impact of cardiac phase and reconstruction kernel on agreement with SPECT MPS was also measured. The following results were shown: CTAC showed no benefits on MPS report or reporter confidence when studied in a way that reflects clinical practice; dCCT best identifies segmental MI, showing good agreement and high specificity, negative predictive value and accuracy compared with SPECT MPS and CMR; choice of smooth or medium-smooth reconstruction kernel appears relatively unimportant; dual-energy dCCT may be more sensitive for segmental MI on CMR; CCT end-systolic wall thickness is a better predictor of myocardial scarring on MPS and CMR than end-diastolic wall thickness; CCT overestimates end-systolic and end-diastolic volumes on MPS but LV ejection fraction is equivalent; CCT shows no systematic differences in measures of global LV function when compared to CMR; measures of regional ventricular function on CCT show excellent and good agreement with MPS and CMR respectively; inter- and intraobserver agreement for dCCT myocardial enhancement patterns and regional LV function is excellent.
Supervisor: Underwood, Richard ; Anagnostopoulos, Constantinos Sponsor: Not available
Qualification Name: Thesis (M.D.) Qualification Level: Doctoral
EThOS ID: uk.bl.ethos.634101  DOI: Not available
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