A new model for separation between brain dopamine and serotonin transporters in 123I-beta-CIT SPECT measurements: normal values and sex and age dependence.
123I-beta-CIT is a radioactive ligand for single-photon emission computed tomography (SPECT) imaging of the pre-synaptic (transporter) re-uptake sites for dopamine (DAT) and serotonin (5HTT), and it is widely used to visualize monoamine turnover. Since 123I-beta-CIT uptake occurs at 5HTT and DAT sites in conjunction with the presence of freely soluble 123I-beta-CIT in brain tissue, adequate separation of these three components is necessary. However, only partial separation is possible with current methods. Two main strategies have previously been used for 123I-beta-CIT component separation, based on the following considerations: (1) the faster uptake rate for 5HTT compared with DAT enables temporal separation by performing 5HTT imaging at 1-2 h and DAT imaging at 20-24 h; (2) blocking the 5HTT re-uptake with citalopram renders 123I-beta-CIT imaging DAT (non-5HTT) specific. In a new analytical model, we combined these two approaches with methods to isolate the passively dissolved 123I-beta-CIT in brain tissue from the monoamine transporter uptake, and to correct the 5HTT and DAT values for concomitant uptake. The new analytical model was used to study brain 5HTT and DAT in 23 normal subjects, with the aim of clarifying the effect of age and sex. A significant correlation between 5HTT and DAT values was found only in the thalamus, indicating successful component separation. Negative correlations between age and DAT were found for basal ganglia, thalami, brain stem and temporal lobes, but not for the frontal, parietal or occipital regions. No correlation with age was found for 5HTT. We found no sex difference for 5HTT or DAT.
Ryding
Erik
E
Department of Clinical Neurophysiology, University Hospital, 221 85, Lund, Sweden. erik@ryding.net
Lindström
Mats
M
Brådvik
Björn
B
Grabowski
Martin
M
Bosson
Peter
P
Träskman-Bendz
Lil
L
Rosén
Ingmar
I
D000328:Adult; D000367:Age Factors; D000368:Aged; D000375:Aging / Q000378:metabolism; D000465:Algorithms; D001921:Brain / Q000000981:diagnostic imaging* / Q000378:metabolism*; D003042:Cocaine / Q000031:analogs & derivatives* / Q000493:pharmacokinetics*; D003198:Computer Simulation; D050483:Dopamine Plasma Membrane Transport Proteins; D005260:Female; D006801:Humans; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D008297:Male; D008562:Membrane Glycoproteins / Q000378:metabolism*; D026901:Membrane Transport Proteins / Q000378:metabolism*; D008875:Middle Aged; D008954:Models, Biological; D009419:Nerve Tissue Proteins / Q000378:metabolism*; D019275:Radiopharmaceuticals / Q000493:pharmacokinetics; D050486:Serotonin Plasma Membrane Transport Proteins; D012737:Sex Factors; D014018:Tissue Distribution; D015899:Tomography, Emission-Computed, Single-Photon / Q000379:methods
D050483:Dopamine Plasma Membrane Transport Proteins; D008562:Membrane Glycoproteins; D026901:Membrane Transport Proteins; D009419:Nerve Tissue Proteins; D019275:Radiopharmaceuticals; C493214:SLC6A3 protein, human; C493230:SLC6A4 protein, human; D050486:Serotonin Plasma Membrane Transport Proteins; C069723:2beta-carbomethoxy-3beta-(4-iodophenyl)tropane; D003042:Cocaine