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Sifting through the surfeit of neuroinflammation tracers

Overview of attention for article published in Cerebrovascular and Brain Metabolism Reviews, December 2017
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Title
Sifting through the surfeit of neuroinflammation tracers
Published in
Cerebrovascular and Brain Metabolism Reviews, December 2017
DOI 10.1177/0271678x17748786
Pubmed ID
Authors

Paul Cumming, Bjorn Burgher, Omkar Patkar, Michael Breakspear, Neil Vasdev, Paul Thomas, Guo-Jun Liu, Richard Banati

Abstract

The first phase of molecular brain imaging of microglial activation in neuroinflammatory conditions began some 20 years ago with the introduction of [11C]-( R)-PK11195, the prototype isoquinoline ligand for translocator protein (18 kDa) (TSPO). Investigations by positron emission tomography (PET) revealed microgliosis in numerous brain diseases, despite the rather low specific binding signal imparted by [11C]-( R)-PK11195. There has since been enormous expansion of the repertoire of TSPO tracers, many with higher specific binding, albeit complicated by allelic dependence of the affinity. However, the specificity of TSPO PET for revealing microglial activation not been fully established, and it has been difficult to judge the relative merits of the competing tracers and analysis methods with respect to their sensitivity for detecting microglial activation. We therefore present a systematic comparison of 13 TSPO PET and single photon computed tomography (SPECT) tracers belonging to five structural classes, each of which has been investigated by compartmental analysis in healthy human brain relative to a metabolite-corrected arterial input. We emphasize the need to establish the non-displaceable binding component for each ligand and conclude with five recommendations for a standard approach to define the cellular distribution of TSPO signals, and to characterize the properties of candidate TSPO tracers.

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Geographical breakdown

Country Count As %
Unknown 82 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 23 28%
Student > Ph. D. Student 17 21%
Student > Bachelor 8 10%
Student > Master 8 10%
Professor > Associate Professor 4 5%
Other 5 6%
Unknown 17 21%
Readers by discipline Count As %
Medicine and Dentistry 15 18%
Neuroscience 15 18%
Chemistry 8 10%
Agricultural and Biological Sciences 4 5%
Psychology 4 5%
Other 17 21%
Unknown 19 23%