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Background  P-glycoprotein [Pgp] dysfunction may be involved in neurodegenerative diseases, such as Alzheimer's disease, and in drug resistant epilepsy. Positron emission tomography using the Pgp substrate tracer ( R )-[ 11 C]verapamil enables  in vivo  quantification of Pgp function at the human blood-brain barrier. Knowledge of test-retest variability is important for assessing changes over time or after treatment with disease-modifying drugs. The purpose of this study was to assess reproducibility of several tracer kinetic models used for analysis of ( R )-[ 11 C]verapamil data.    Methods  Dynamic ( R )-[ 11 C]verapamil scans with arterial sampling were performed twice on the same day in 13 healthy controls. Data were reconstructed using both filtered back projection [FBP] and partial volume corrected ordered subset expectation maximization [PVC OSEM]. All data were analysed using single-tissue and two-tissue compartment models. Global and regional test-retest variability was determined for various outcome measures.    Results  Analysis using the Akaike information criterion showed that a constrained two-tissue compartment model provided the best fits to the data. Global test-retest variability of the volume of distribution was comparable for single-tissue (6%) and constrained two-tissue (9%) compartment models. Using a single-tissue compartment model covering the first 10 min of data yielded acceptable global test-retest variability (9%) for the outcome measure  K  1 . Test-retest variability of binding potential derived from the constrained two-tissue compartment model was less robust, but still acceptable (22%). Test-retest variability was comparable for PVC OSEM and FBP reconstructed data.    Conclusion  The model of choice for analysing ( R )-[ 11 C]verapamil data is a constrained two-tissue compartment model.

Reproducibility of quantitative (R)-[11C]verapamil studies