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Evaluation of tracer kinetic models for analysis of [18F]FDDNP studies.

Yaqub M, Boellaard R, van Berckel BN, Tolboom N, Luurtsema G, Dijkstra AA, Lubberink M, Windhorst AD, Scheltens P, Lammertsma AA - Mol Imaging Biol (2009)

Bottom Line: Indirect BP(ND) using 2T1M correlated better with SRTM then direct BP(ND).Fairly constant volume of distribution of metabolites was found across brain and across subjects, which was strongly related to bias in BP(ND) obtained from SRTM as seen in simulations.Furthermore, in simulations, SRTM showed constant bias with best precision if metabolites entered brain.

View Article: PubMed Central - PubMed

Affiliation: Department of Nuclear Medicine & PET Research, VU University Medical Centre, P.O. Box 7057, 1007 MB, Amsterdam, The Netherlands. Maqsood.Yaqub@VUmc.nl

ABSTRACT

Purpose: Different pharmacokinetic methods for [18F]FDDNP studies were evaluated using both simulations and clinical data.

Procedures: Methods included two-tissue reversible plasma (2T4k), simplified reference tissue input (SRTM), and a modified 2T4k models. The latter included an additional compartment for metabolites (2T1M). For plasma input models, binding potential, BP(ND), was obtained both directly (=k (3)/k (4)) and indirectly (using volume of distribution ratios).

Results: For clinical data, 2T1M was preferred over 2T4k according to Akaike criterion. Indirect BP(ND) using 2T1M correlated better with SRTM then direct BP(ND). Fairly constant volume of distribution of metabolites was found across brain and across subjects, which was strongly related to bias in BP(ND) obtained from SRTM as seen in simulations. Furthermore, in simulations, SRTM showed constant bias with best precision if metabolites entered brain.

Conclusions: SRTM is the method of choice for quantitative analysis of [18F]FDDNP even if it is unclear whether labeled metabolites enter the brain.

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Schematic diagram of the model that includes a tissue metabolite compartment. BBB represents the blood–brain barrier; PParent and PMet are tracer plasma radioactivity concentrations (Bq ml−1) of parent and labeled metabolites, respectively; T is the radioactivity concentration in tissue, F+NSParent that of free and non-specifically bound parent in tissue, SParent that of bound parent in tissue; and F+NSMet that of labeled metabolites in tissue (Bq ml−1); K1 (ml·cm−3·min−1) and k2 (min−1) are rate constants, describing exchange of parent between plasma and tissue; k3 and k4 are rate constants (min−1), describing exchange of parent between free and bound compartments; K1m (ml·cm−3·min−1) and k2m (min−1) are rate constants, describing exchange of labeled metabolites between plasma and tissue.
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Fig1: Schematic diagram of the model that includes a tissue metabolite compartment. BBB represents the blood–brain barrier; PParent and PMet are tracer plasma radioactivity concentrations (Bq ml−1) of parent and labeled metabolites, respectively; T is the radioactivity concentration in tissue, F+NSParent that of free and non-specifically bound parent in tissue, SParent that of bound parent in tissue; and F+NSMet that of labeled metabolites in tissue (Bq ml−1); K1 (ml·cm−3·min−1) and k2 (min−1) are rate constants, describing exchange of parent between plasma and tissue; k3 and k4 are rate constants (min−1), describing exchange of parent between free and bound compartments; K1m (ml·cm−3·min−1) and k2m (min−1) are rate constants, describing exchange of labeled metabolites between plasma and tissue.

Mentions: Based on the possibility of metabolites entering the brain [27, 28], also a modified 2T4k model was used. This model included an additional (parallel) single-tissue compartment for labeled metabolites (2T1M, Fig. 1). The metabolite input curve was based only on polar metabolites and ignores the minor fraction of other metabolites. The direct binding potential for this model was defined as k3/k4 (Fig. 1), and the volumes of distributions, VT and VTm, were defined as and K1m/k2m, respectively. Similar to 2T4ki, the binding potential was also estimated indirectly using the volume of distribution ratios with the cerebellum as reference region . All 2T1M fits were repeated after fixing VTm to the cerebellum value (=2T1Mfvtm). This model was also used to estimate binding potential both directly and indirectly using DVR − 1 . The indirect methods for estimating BPND using 2T1M and 2T1Mfvtm will be indicated by 2T1Mi and , respectively.Fig. 1


Evaluation of tracer kinetic models for analysis of [18F]FDDNP studies.

Yaqub M, Boellaard R, van Berckel BN, Tolboom N, Luurtsema G, Dijkstra AA, Lubberink M, Windhorst AD, Scheltens P, Lammertsma AA - Mol Imaging Biol (2009)

Schematic diagram of the model that includes a tissue metabolite compartment. BBB represents the blood–brain barrier; PParent and PMet are tracer plasma radioactivity concentrations (Bq ml−1) of parent and labeled metabolites, respectively; T is the radioactivity concentration in tissue, F+NSParent that of free and non-specifically bound parent in tissue, SParent that of bound parent in tissue; and F+NSMet that of labeled metabolites in tissue (Bq ml−1); K1 (ml·cm−3·min−1) and k2 (min−1) are rate constants, describing exchange of parent between plasma and tissue; k3 and k4 are rate constants (min−1), describing exchange of parent between free and bound compartments; K1m (ml·cm−3·min−1) and k2m (min−1) are rate constants, describing exchange of labeled metabolites between plasma and tissue.
© Copyright Policy
Related In: Results  -  Collection

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getmorefigures.php?uid=PMC2719728&req=5

Fig1: Schematic diagram of the model that includes a tissue metabolite compartment. BBB represents the blood–brain barrier; PParent and PMet are tracer plasma radioactivity concentrations (Bq ml−1) of parent and labeled metabolites, respectively; T is the radioactivity concentration in tissue, F+NSParent that of free and non-specifically bound parent in tissue, SParent that of bound parent in tissue; and F+NSMet that of labeled metabolites in tissue (Bq ml−1); K1 (ml·cm−3·min−1) and k2 (min−1) are rate constants, describing exchange of parent between plasma and tissue; k3 and k4 are rate constants (min−1), describing exchange of parent between free and bound compartments; K1m (ml·cm−3·min−1) and k2m (min−1) are rate constants, describing exchange of labeled metabolites between plasma and tissue.
Mentions: Based on the possibility of metabolites entering the brain [27, 28], also a modified 2T4k model was used. This model included an additional (parallel) single-tissue compartment for labeled metabolites (2T1M, Fig. 1). The metabolite input curve was based only on polar metabolites and ignores the minor fraction of other metabolites. The direct binding potential for this model was defined as k3/k4 (Fig. 1), and the volumes of distributions, VT and VTm, were defined as and K1m/k2m, respectively. Similar to 2T4ki, the binding potential was also estimated indirectly using the volume of distribution ratios with the cerebellum as reference region . All 2T1M fits were repeated after fixing VTm to the cerebellum value (=2T1Mfvtm). This model was also used to estimate binding potential both directly and indirectly using DVR − 1 . The indirect methods for estimating BPND using 2T1M and 2T1Mfvtm will be indicated by 2T1Mi and , respectively.Fig. 1

Bottom Line: Indirect BP(ND) using 2T1M correlated better with SRTM then direct BP(ND).Fairly constant volume of distribution of metabolites was found across brain and across subjects, which was strongly related to bias in BP(ND) obtained from SRTM as seen in simulations.Furthermore, in simulations, SRTM showed constant bias with best precision if metabolites entered brain.

View Article: PubMed Central - PubMed

Affiliation: Department of Nuclear Medicine & PET Research, VU University Medical Centre, P.O. Box 7057, 1007 MB, Amsterdam, The Netherlands. Maqsood.Yaqub@VUmc.nl

ABSTRACT

Purpose: Different pharmacokinetic methods for [18F]FDDNP studies were evaluated using both simulations and clinical data.

Procedures: Methods included two-tissue reversible plasma (2T4k), simplified reference tissue input (SRTM), and a modified 2T4k models. The latter included an additional compartment for metabolites (2T1M). For plasma input models, binding potential, BP(ND), was obtained both directly (=k (3)/k (4)) and indirectly (using volume of distribution ratios).

Results: For clinical data, 2T1M was preferred over 2T4k according to Akaike criterion. Indirect BP(ND) using 2T1M correlated better with SRTM then direct BP(ND). Fairly constant volume of distribution of metabolites was found across brain and across subjects, which was strongly related to bias in BP(ND) obtained from SRTM as seen in simulations. Furthermore, in simulations, SRTM showed constant bias with best precision if metabolites entered brain.

Conclusions: SRTM is the method of choice for quantitative analysis of [18F]FDDNP even if it is unclear whether labeled metabolites enter the brain.

Show MeSH