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Title: Improving quantification of PET/CT biomarkers for evaluation of disease progression and treatment effectiveness in pulmonary fibrosis
Author: Holman, B.
ISNI:       0000 0004 7230 7482
Awarding Body: UCL (University College London)
Current Institution: University College London (University of London)
Date of Award: 2016
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Idiopathic pulmonary fibrosis (IPF) is a progressive disease of unknown aetiology and with a high mortality rate. Treatment options are currently limited and the mean survival following diagnosis is 3 yrs. Recently, dynamic and static PET/CT has been used to image the IPF lung with the aim of improving the understanding of the disease mechanisms, monitoring disease progression and evaluating treatment effectiveness. Quantitative imaging of PET tracer uptake in the lung tissue of patients with any diffuse pulmonary disease is highly challenging due to the effects of breathing and the large pulmonary blood component. In this work, three main sources of error on PET image quantitation in the lung have been assessed and addressed. Firstly, the effect of air and blood within the lung tissue on PET parameter accuracy has been characterised and methods developed to reduce the uncertainties. Secondly, analysis of the effect of density variations in the lung, due to the respiratory cycle, has been determined and suggestions given for minimising the errors induced. Thirdly, methods for calculating the blood tracer uptake and volume within the lung have been established and used to assess the effect on quantitation in the lungs of IPF and control patients. Finally, a feasibility study has been performed using an improved PET analysis methodology to determine if more robust parameter estimates can be derived in the lung tissue of patients with diffuse lung diseases. Specifically, the new methodology was applied to patients with IPF who had undergone dynamic PET/CT studies with 18F-FDG and 18F-FMISO.
Supervisor: Thielemans, K. ; Hutton, B. Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available