Quantification of dopamine transporter binding using [18F]FP- β-CIT and positron emission tomography

Maqsood Yaqub*, Ronald Boellaard, Bart N.M. Van Berckel, Mirthe M. Ponsen, Mark Lubberink, Albert D. Windhorst, Henk W. Berendse, Adriaan A. Lammertsma

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

Abstract

The purpose of this study was to compare different kinetic and semi-quantitative methods for analysing human [18F]FP-β-CIT studies: plasma input models, simplified (SRTM) and full (FRTM) reference tissue models, standard uptake values (SUV) and SUV ratios (SUVr). Both simulations and clinical evaluations were performed to determine the effects of noise, scan duration and blood volume on Akaike model selection, and on precision and accuracy of estimated parameters. For typical noise levels (COV∼2.5%) and scan durations (<90 mins), simulations provided poor fits (Akaike criterion) in case of reversible plasma input models showing a relatively high number of outliers compared with the two-tissue irreversible model. Reference tissue models provided more reliable fits, which were nearly independent of noise and scan duration. For clinical data, two tissue irreversible and reversible plasma input models fitted striatum curves equally well (Akaike criterion). BP with plasma input models were less precise and contained more outliers than BP obtained with SRTM or FRTM. Among all methods tested, SRTM showed the highest contrast between patients and controls. When differentiating between patients and controls, SUVr performed almost equally well as SRTM, although contrast between striatum and background was lower. In conclusion, SRTM provided BP estimates with the highest precision and accuracy. Moreover, SRTM provided good contrast between patients and controls, and between striatum and background. SRTM is therefore the method of choice for quantitative [18F]FP- β-CIT studies. SUVr might be an alternative for larger clinical trials.

Original languageEnglish
Pages (from-to)1397-1406
Number of pages10
JournalJournal of Cerebral Blood Flow and Metabolism
Volume27
Issue number7
DOIs
Publication statusPublished - 27 Jul 2007

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