Automated Reference Region Extraction and Population-Based Input Function for Brain [11C]TMSX PET Image Analyses. Issue 1 (January 2015)

• Record Type: Journal Article
• Authors: Rissanen, Eero; Tuisku, Jouni; Luoto, Pauliina; Arponen, Eveliina; Johansson, Jarkko; Oikonen, Vesa; Parkkola, Riitta; Airas, Laura; Rinne, Juha O
• Is Part Of: Journal of cerebral blood flow & metabolism. Volume 35:Issue 1(2015)
• Page Start: 157
• Page End: 165
• Publication Date: 2015-01
• Subjects: A2AR -- input function -- PET -- supervised clustering -- [11C]TMSX; Cerebral circulation -- Periodicals; Brain -- Metabolism -- Periodicals; Brain -- Blood-vessels -- Periodicals; Cerebrovascular disease -- Periodicals; 612.824
• DOI: 10.1038/jcbfm.2014.194
• Languages: English
• ISSNs: 0271-678X

Abstract

[ 11 C]TMSX ([7- N -methyl- 11 C]-(E)-8-(3, 4, 5-trimethoxystyryl)-1, 3, 7-trimethylxanthine) is a selective adenosine A2A receptor (A2A R) radioligand. In the central nervous system (CNS), A2A R are linked to dopamine D2 receptor function in striatum, but they are also important modulators of inflammation. The golden standard for kinetic modeling of brain [ 11 C]TMSX positron emission tomography (PET) is to obtain arterial input function via arterial blood sampling. However, this method is laborious, prone to errors and unpleasant for study subjects. The aim of this work was to evaluate alternative input function acquisition methods for brain [ 11 C]TMSX PET imaging. First, a noninvasive, automated method for the extraction of gray matter reference region using supervised clustering (SCgm) was developed. Second, a method for obtaining a population-based arterial input function (PBIF) was implemented. These methods were created using data from 28 study subjects (7 healthy controls, 12 multiple sclerosis patients, and 9 patients with Parkinson's disease). The results with PBIF correlated well with original plasma input, and the SCgm yielded similar results compared with cerebellum as a reference region. The clustering method for extracting reference region and the population-based approach for acquiring input for dynamic [ 11 C]TMSX brain PET image analyses appear to be feasible and robust methods, that can be applied in patients with CNS pathology.