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PET Methodology

Federico Turkheimer

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Funding source

Medical Research Council (MRC)
In the next five years we want to progress the set of technologies that PET Methodology has built at Hammersmith for the field in the past 20 years with the aim of increasing PET accuracy and expand its applications to provide ever more useful end-points for diagnostic use, clinical research and drug development. We will support the introduction of new tracers in the Unit (e.g. 11C-Ro-154513, 11CCUMI, 11C-CNS-5161, 11C-MePPEP) developing tailored quantitative methodologies. We will employ novel modeling approaches (e.g. generalized reference region models) to simplify,without loss of precision, the use of PET in research and drug development. To support the imaging work in Neurodegeneration, we will expand our methodological toolbox on imaging inflammation developing quantification methods for the new generation of high affinity TSPO radiotracers such as 11C-PBR28 and 18F-FEPPA. We will be also looking at translational models of senescence to identify aging microglia phenotypes and their markers. To support the work in Psychiatric disorders, we will develop methodologies able to quantify the dynamics of large neuronal ensembles from fMRI time-courses looking both at local and regional determinants using concepts from network analysis and statistical physics. We will then use these endpoints in combined fMRI/PET study designs to measure the relationship between receptor densities/endogenous neurotransmitters levels (e.g. using dopaminergic tracers such as 18F-FDOPA, 11C-Raclopride, 11C-FLB457 or cannabinoid tracers such as 11C-CB1) and neuronal dynamics. In Cancer, we will work on two paths. On one side we will research novel quantification methodologies for radiotracers used in clinical studies at the Unit (18FFluorothymidine, 18F- AH111585 e 18CCholine) to model their complex and heterogeneous kinetic behavior in tumor cells. In parallel, we will be developing computer aided strategies able to use features of functional (PET) and structural (CT) images to automatically detect tumors in functional or multimodal studies. Our work on Genomics will continue with focus on the epigenetics of brain disorders (Huntington‘s and Parkinson‘s disease, Schizophrenia and bipolar disorders) using computational models applied to microarray data for exploration and guide for further genomic (ChIP-Seq) studies.

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