Kinetic modelling of [(11)C]PBR28 for 18 kDa translocator protein PET data: A validation study of vascular modelling in the brain using XBD173 and tissue analysis

Mattia Veronese, Tiago Reis Marques, Peter S Bloomfield, Gaia Rizzo, Nisha Singh, Deborah Jones, Erjon Agushi, Dominic Mosses, Alessandra Bertoldo, Oliver Howes, Federico Roncaroli, Federico E Turkheimer

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Abstract

The 18 kDa translocator protein (TSPO) is a marker of microglia activation in the central nervous system and represents the main target of radiotracers for the in vivo quantification of neuroinflammation with positron emission tomography (PET). TSPO PET is methodologically challenging given the heterogeneous distribution of TSPO in blood and brain. Our previous studies with the TSPO tracers [(11)C]PBR28 and [(11)C]PK11195 demonstrated that a model accounting for TSPO binding to the endothelium improves the quantification of PET data. Here, we performed a validation of the kinetic model with the additional endothelial compartment through a displacement study. Seven subjects with schizophrenia, all high-affinity binders, underwent two [(11)C]PBR28 PET scans before and after oral administration of 90 mg of the TSPO ligand XBD173. The addition of the endothelial component provided a signal compartmentalization much more consistent with the underlying biology, as only in this model, the blocking study produced the expected reduction in the tracer concentration of the specific tissue compartment, whereas the non-displaceable compartment remained unchanged. In addition, we also studied TSPO expression in vessels using 3D reconstructions of histological data of frontal lobe and cerebellum, demonstrating that TSPO positive vessels account for 30% of the vascular volume in cortical and white matter.

Original languageEnglish
JournalJournal of cerebral blood flow and metabolism : official journal of the International Society of Cerebral Blood Flow and Metabolism
Early online date5 Jun 2017
DOIs
Publication statusE-pub ahead of print - 5 Jun 2017

Keywords

  • Journal Article

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