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Imaging of the brain serotonin transporters (SERT) with super(18)F-labelled fluoromethyl-McN5652 and PET in humans
Purpose: [ super(11)C]DASB is currently the most frequently used highly selective radiotracer for visualization and quantification of central SERT. Its use, however, is hampered by the short half-life of super(11)C, the moderate cortical test-retest reliability, and the lack of quantifying endogenou...
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Published in: | European journal of nuclear medicine and molecular imaging 2012-06, Vol.39 (6), p.1001-1011 |
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Main Authors: | , , , , , , , , , , , , , , , , |
Format: | Article |
Language: | English |
Subjects: | |
Online Access: | Get full text |
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Summary: | Purpose: [ super(11)C]DASB is currently the most frequently used highly selective radiotracer for visualization and quantification of central SERT. Its use, however, is hampered by the short half-life of super(11)C, the moderate cortical test-retest reliability, and the lack of quantifying endogenous serotonin. Labelling with super(18)F allows in principle longer acquisition times for kinetic analysis in brain tissue and may provide higher sensitivity. The aim of our study was to firstly use the new highly SERT-selective super(18)F-labelled fluoromethyl analogue of (+)-McN5652 ((+)-[ super(18)F]FMe-McN5652) in humans and to evaluate its potential for SERT quantification. Methods: The PET data from five healthy volunteers (three men, two women, age 39 plus or minus 10 years) coregistered with individual MRI scans were semiquantitatively assessed by volume-of-interest analysis using the software package PMOD. Rate constants and total distribution volumes (V sub(T)) were calculated using a two-tissue compartment model and arterial input function measurements were corrected for metabolite/plasma data. Standardized uptake region-to-cerebellum ratios as a measure of specific radiotracer accumulation were compared with those of a [ super(11)C]DASB PET dataset from 21 healthy subjects (10 men, 11 women, age 38 plus or minus 8 years). Results: The two-tissue compartment model provided adequate fits to the data. Estimates of total distribution volume (V sub(T)) demonstrated good identifiability based on the coefficients of variation (COV) for the volumes of interest in SERT-rich and cortical areas (COV V sub(T) |
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ISSN: | 1619-7070 1619-7089 |
DOI: | 10.1007/s00259-012-2078-z |