Pharmacokinetic assessment of the uptake of 16beta-18F-fluoro-5alpha-dihydrotestosterone (FDHT) in prostate tumors as measured by PET

Abstract

The aim of this study was to develop a clinically applicable noninvasive method to quantify changes in androgen receptor (AR) levels based on (18)F-16beta-fluoro-5alpha-dihydrotestosterone ((18)F-FDHT) PET in prostate cancer patients undergoing therapy.

Methods: Thirteen patients underwent dynamic (18)F-FDHT PET over a selected tumor. Concurrent venous blood samples were acquired for blood metabolite analysis. A second cohort of 25 patients injected with (18)F-FDHT underwent dynamic PET of the heart. These data were used to generate a population-based input function, essential for pharmacokinetic modeling. Linear compartmental pharmacokinetic models of increasing complexity were tested on the tumor tissue data. Four suitable models were applied and compared using the Bayesian information criterion (BIC). Model 1 consisted of an instantaneously equilibrating space, followed by a unidirectional trap. Models 2a and 2b contained a reversible space between the instantaneously equilibrating space and the trap, into which metabolites were excluded (2a) or allowed (2b). Model 3 built on model 2b with the addition of a second reversible space preceding the unidirectional trap and from which metabolites were excluded.

Results: The half-life of the (18)F-FDHT in blood was between 6 and 7 min. As a consequence, the uptake of (18)F-FDHT in prostate cancer lesions reached a plateau within 20 min as the blood-borne activity was consumed. Radiolabeled metabolites were shown not to bind to ARs in in vitro studies with CWR22 cells. Model 1 produced reasonable and robust fits for all datasets and was judged best by the BIC for 16 of 26 tumor scans. Models 2a, 2b, and 3 were judged best in 7, 2, and 1 cases, respectively.

Conclusion: Our study explores the clinical potential of using (18)F-FDHT PET to estimate free AR concentration. This process involved the estimation of a net uptake parameter such as the k(trap) of model 1 that could serve as a surrogate measure of AR expression in metastatic prostate cancer. Our initial studies suggest that a simple body mass-normalized standardized uptake value correlates reasonably well to model-based k(trap) estimates, which we surmise may be proportional to AR expression. Validation studies to test this hypothesis are underway.

FIGURE 1

Displacement binding of ¹⁸F-FDHT and final ¹⁸F-FDHT metabolite to CWR22-rv1 cells by DHT.

FIGURE 2

Time activity curves in SUV units for the blood samples (total, ¹⁸F-FDHT and metabolites) and the PET derived data from iliac artery and aorta. SUV_bw = SUV normalized by body weight.

FIGURE 3

Four compartmental models used to fit ¹⁸F-FDHT data to the tumor uptake profiles. V*FDHT = volume times FDHT concentration; V*metab = volume times metabolite concentration.

FIGURE 4

Series of HPLC elution profiles showing progressive decrease in ¹⁸F-FDHT (retention time, 6.7 minutes) and increase in metabolites (retention time, 4.0 minutes)

FIGURE 5

Time course of ¹⁸F-FDHT and metabolite levels in serial patient sera.

FIGURE 6

Scattergram showing relationship between the k_trap parameter values calculated in Model 1 with the 30 minute SUV value. These data are fitted with a line forced through the origin.

FIGURE 7

(A) Tumor time versus activity concentration data for the three studies (1 pre-therapy and two post-therapy) of patient 1 fitted with model 1. (B) The same 3 datasets as in A, this time fitted by model 2a. Time-course of modeled reversible compartment for each of these is also shown. SUV_bw = SUV normalized by body weight; Rev cmpt = reversible compartment.