Statistical considerations in the kinetic analysis of PET-FDG brain tumour studies

Dynamic positron emission tomography (PET) imaging can be used to track the distribution of injected radio-labelled molecules over time in vivo. This is a powerful technique, which provides researchers and clinicians the opportunity to study the status of healthy and pathological tissue by examining how it processes substances of interest. Widely used tracers include 18F-uorodeoxyglucose, an analog of glucose, which is used as the radiotracer in over ninety percent of PET scans. This radiotracer provides a way of quantifying the distribution of glucose utilisation in vivo. The interpretation of PET time-course data is complicated because the measured signal is a combination of vascular delivery and tissue retention effects. If the arterial time-course is known, the tissue time-course can typically be expressed in terms of a linear convolution between the arterial time-course and the tissue residue function. As the residue represents the amount of tracer remaining in the tissue, this can be thought of as a survival function; these functions been examined in great detail by the statistics community. Kinetic analysis of PET data is concerned with estimation of the residue and associated functionals such as ow, ux and volume of distribution. This thesis presents a Markov chain formulation of blood tissue exchange and explores how this relates to established compartmental forms. A nonparametric approach to the estimation of the residue is examined and the improvement in this model relative to compartmental model is evaluated using simulations and cross-validation techniques. The reference distribution of the test statistics, generated in comparing the models, is also studied. We explore these models further with simulated studies and an FDG-PET dataset from subjects with gliomas, which has previously been analysed with compartmental modelling. We also consider the performance of a recently proposed mixture modelling technique in this study.

Simulation chamber studies of the atmospheric degradation of naphthalene, 1-nitronaphthalene and phthaldialdehyde

A detailed series of simulation chamber experiments has been performed on the atmospheric degradation pathways of the primary air pollutant naphthalene and two of its photooxidation products, phthaldialdehyde and 1-nitronaphthalene. The measured yields of secondary organic aerosol (SOA) arising from the photooxidation of naphthalene varied from 6-20%, depending on the concentrations of naphthalene and nitrogen oxides as well as relative humidity. A range of carbonyls, nitro-compounds, phenols and carboxylic acids were identified among the gas- and particle-phase products. On-line analysis of the chemical composition of naphthalene SOA was performed using aerosol time-of-flight mass spectrometry (ATOFMS) for the first time. The results indicate that enhanced formation of carboxylic acids may contribute to the observed increase in SOA yields at higher relative humidity. The photolysis of phthaldialdehyde and 1-nitronaphthalene was investigated using natural light at the European Photoreactor (EUPHORE) in Valencia, Spain. The photolysis rate coefficients were measured directly and used to confirm that photolysis is the major atmospheric loss process for these compounds. For phthaldialdehyde, the main gas-phase products were phthalide and phthalic anhydride. SOA yields in the range 2-11% were observed, with phthalic acid and dihydroxyphthalic acid identified among the particle phase products. The photolysis of 1-nitronaphthalene yielded nitric oxide and a naphthoxy radical which reacted to form several products. SOA yields in the range 57-71% were observed, with 1,4-naphthoquinone, 1-naphthol and 1,4-naphthalenediol identified in the particle phase. On-line analysis of the SOA generated in an indoor chamber using ATOFMS provided evidence for the formation of high-molecular-weight products. Further investigations revealed that these products are oxygenated polycyclic compounds most likely produced from the dimerization of naphthoxy radicals. These results of this work indicate that naphthalene is a potentially large source of SOA in urban areas and should be included in atmospheric models. The kinetic and mechanistic information could be combined with existing literature data to produce an overall degradation mechanism for naphthalene suitable for inclusion in photochemical models that are used to predict the effect of emissions on air quality.