Kinetic Modeling without Accounting for the Vascular Component Impairs the Quantification of [11C]PBR28 Brain PET Data

• Published in: Journal of cerebral blood flow and metabolism Vol. 34; no. 6; pp. 1060 - 1069
• Main Authors: Rizzo, Gaia, Veronese, Mattia, Tonietto, Matteo, Zanotti-Fregonara, Paolo, Turkheimer, Federico E, Bertoldo, Alessandra
• Format: Journal Article
• Language: English
• Published: London, England SAGE Publications 01.06.2014; Sage Publications Ltd; Nature Publishing Group
• Subjects: Acetamides - pharmacokinetics; Acetamides - pharmacology; Carbon Isotopes - pharmacokinetics; Carbon Isotopes - pharmacology; Cerebrovascular Circulation - drug effects; Cerebrovascular Circulation - physiology; Humans; Kinetics; Models, Cardiovascular; Nerve Tissue Proteins - biosynthesis; Original; Positron-Emission Tomography; Pyridines - pharmacokinetics; Pyridines - pharmacology; Receptors, GABA - biosynthesis; RNA, Messenger - biosynthesis; [1C]PBR28; TSPO; neuroinflammation; PK11195; microglia; kinetic modeling
• DOI: 10.1038/jcbfm.2014.55
• ISSN: 0271-678X

The positron emission tomography radioligand [11C]PBR28 targets translocator protein (18 kDa) (TSPO) and is a potential marker of neuroinflammation. [11C]PBR28 binding is commonly quantified using a two-tissue compartment model and an arterial input function. Previous studies with [11C]HRJ-PK11195 demonstrated a slow irreversible binding component to the TSPO proteins localized in the endothelium of brain vessels, such as venous sinuses and arteries. However, the impact of this component on the quantification of [11C]PBR28 data has never been investigated. In this work we propose a novel kinetic model for [11C]PBR28. This model hypothesizes the existence of an additional irreversible component from the blood to the endothelium. The model was tested on a data set of 19 healthy subjects. A simulation was also performed to quantify the error generated by the standard two-tissue compartmental model when the presence of the irreversible component is not taken into account. Our results show that when the vascular component is included in the model the estimates that include the vascular component (2TCM-1K) are more than three-fold smaller, have a higher time stability and are better correlated to brain mRNA TSPO expression than those that do not include the model (2TCM).