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.

Building an index of well-being for children living in Ireland: conceptual, measurement and policy considerations

This study conceptualised and measured children’s well-being in Ireland and considered how such conceptualisations and approaches to the measurement of well-being might inform social policy for children and families living in Ireland. This research explored what is meant by children’s well-being and how it can be conceptualised and measured so as to reflect the multi-dimensionality of the concept. The study developed an index of well-being that was both theoretically and methodologically robust and could be meaningfully used to inform social policy developments for children and their families. For the first time, an index of well-being for children was developed using an explicitly articulated unifying theory of children’s well-being. Moreover, for the first time an index of wellbeing was developed for 13-year old children living in Ireland using data from Wave 2 of the national longitudinal study of children. The Structural Model of Child Well-being (SMCW), the theoretical framework that underpins the development of this study’s index, offers a comprehensive understanding of well-being. The SMCW builds on, and integrates, a range of already-established theories concerning children’s development, their agency, rights and capabilities into a unifying theory that explains well-being in its entirety. This conceptualisation of well-being moves beyond the narrow focus on child development adopted in some recent studies of children’s well-being and which perpetuate individualised and self-responsibilising conceptualisations of well-being. This study found that the SMCW can be meaningfully applied, both theoretically and operationally, to the construction of an index of well-being for children. While it was not the purpose of this study to validate the SMCW, in the process of developing the index, I concluded that there was a theoretical ‘fit’ between the conceptual orientation of the SMCW and the wider children’s well-being literature. The ‘nested’ structure of the SMCW facilitated the identification of domains, sub-domains and indicators of well-being reflecting typical conventions of index construction. The findings from the resulting index, in both its categorical and continuous forms, demonstrated how a comprehensive theory of well-being can be used to illustrate how children are faring and which children are experiencing poorer or better well-being. Furthermore, this study demonstrated how the SMCW and the resultant index can be meaningfully used to support the implementation and review of the national policy framework for children and young people in Ireland.