Novel [11C]CO2 radiolabelling methodologies for PET neuroimaging

Student thesis: Doctoral ThesisDoctor of Philosophy


PET is a non-invasive molecular imaging technique that is increasingly being used for medical imaging and drug development. Carbon-11 (11C; half-life 20.4 min) is one of the most commonly used radionuclides for PET molecular imaging. 11C is usually produced in the form of [11C]CO2 and converted into more reactive secondary precursors such as [11C]methyl iodide and [11C]carbon monoxide for radiolabelling. Although such secondary precursors are undoubtedly useful, given the short half-life of 11C, it would be advantageous to use [11C]CO2 directly from the cyclotron without additional time-consuming processing. Therefore, the development of radiochemical methods to efficiently radiolabel compounds directly with [11C]CO2 for applications in PET neuroimaging is an important goal and is the focus of this thesis.
This work includes the development of novel radiolabelling methodology utilising [11C]CO2 for the radiolabelling of molecules based on urea and carbamate scaffolds. These functional groups are found in a plethora of biologically active molecules and pharmaceuticals. As proof of concept, the utility of the developed radiochemistry methods were applied to the synthesis of novel GABA and glutamate radiotracers.
GABA and glutamate are major excitatory and inhibitory neurotransmitters in the brain. Although implicated in many diseases, the in vivo function of these neurotransmitter system is poorly understood. Their dysfunction are implicated in pathologies such as addiction, Alzheimer’s disease, Parkinson’s disease and autism. Monitoring the expression of the receptors in vivo and in vitro would enable better understanding of these diseases, their progression and treatment. The research described in this thesis unveils new methods to radiolabel novel molecules for these targets with 11C thereby enabling more opportunities to study them in vitro using autoradiography and in vivo using PET molecular imaging.
Date of Award2015
Original languageEnglish
Awarding Institution
  • King's College London
SupervisorTony Gee (Supervisor) & Gregory Mullen (Supervisor)

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