Use this URL to cite or link to this record in EThOS: http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.439962
Title: Predicting the response of large and locally advanced breast cancers to neoadjuvant chemotherapy using 2-Deoxy-2-[18F]-Fluoro-D-Glucose positron emission tomography
Author: McDermott, Garry M.
Awarding Body: University of Aberdeen
Current Institution: University of Aberdeen
Date of Award: 2006
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Abstract:
Introduction: The purpose of this thesis was to compare 2-deoxy-2-[18F]-fluoro-D-glucose positron emission tomography (FDG-PET) images of large and locally advanced breast cancers, which were acquired during Anthracycline-based neoadjuvant chemotherapy. The aim was to determine the effectiveness of FDG-PET for predicting the pathological response of tumours. Method: PET images were acquired before the first and second cycles, at the midpoint and at the endpoint of neoadjuvant chemotherapy. The tumour images were quantified using a range of methods including: volume delineations, standardised uptake values, the simplified kinetic method, fractal analysis and textual analysis. Receiver-operator characteristic (ROC) analysis was used to determine the discrimination between tumours demonstrating a high pathological response (i.e. those with greater than 90% reduction in viable tumour cells) and low pathological response. Also, factor analysis was performed on the image quantifications with discriminative ability to determine whether there are underlying tumour responsiveness factors common to them. Results: Pathological tumour response could only be discriminated for tumours with a high initial image contrast (tumour to background ratio >5). For this group, a number of different image quantifications (including standardised uptake values, tumour volume and fractal dimension) produced similar response discrimination throughout chemotherapy. Factor analysis revealed two underlying factors. One factor, which was based in changes in response predictors over the first cycle of chemotherapy, had a higher response discrimination than any of the individual predictors (ROC area = 0.92, sensitivity = 100%, specificity = 74%). Conclusion: FDG-PET is efficacious for predicting the pathologic response of most primary breast tumours during a neoadjuvant chemotherapy regimen. If a tumour has sufficient image contrast on a pre-therapy PET scan, a high proportion of tumours with low pathological response can be identified. Therefore, FDG-PET may allow clinicians to tailor chemotherapy to an individual patients needs.
Supervisor: Not available Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID: uk.bl.ethos.439962  DOI: Not available
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