Pharmacokinetic Assessment of the Uptake of 16β-¹⁸F-Fluoro-5α-Dihydrotestosterone (FDHT) in Prostate Tumors as Measured by PET

Patients

Patients were selected prospectively under the auspices of the Memorial Sloan-Kettering Cancer Center Institutional Review Board (protocol 00-095). All who agreed to participate in the study signed informed consent forms. The study cohort consisted of 13 patients who then underwent dynamic ¹⁸F-FDHT PET over a selected metastatic tumor site, located in either the pelvis or the abdomen. Because satisfactory region-of-interest (ROI)–based blood time–activity data (i.e., input functions) could not, in general, be obtained from these images, arterial input data were extracted from a larger cohort of 25 patients, who underwent dynamic ¹⁸F-FDHT PET of the heart. Data from ROIs placed over the aorta in these patients were averaged to generate a population-based input function used in the pharmacokinetic modeling.

For the 13 patients recruited into the first cohort, there were a total of thirty ¹⁸F-FDHT scans obtained, consisting of 3 patients for whom a single ¹⁸F-FDHT baseline scan only was obtained, 3 patients for whom 1 pre- and 1 posttherapy ¹⁸F-FDHT scan were obtained, and 7 patients for whom a baseline scan followed by 2 posttherapy scans were obtained.

Radiochemical Synthesis of ¹⁸F-FDHT

¹⁸F-FDHT was synthesized as previously described (5). The total radiochemistry synthesis time was approximately 100 min, and the radiochemical yield to end of bombardment was nearly 30%. Chemical and radiochemical quality assurance (QA) was performed by radio–thin-layer chromatography and reversed-phase high-performance liquid chromatography (HPLC) by coelution with a fully characterized nonradioactive standard. Additional QA included confirmation of color, appearance, radioactive half-life, pH, sterility, and apyrogenicity. All QA results were in full accordance with the approved specifications. The radiochemical purity was greater than 99%.

To maintain the chemical stability of the ¹⁸F-FDHT compound, the final product was formulated in a 5% ethanol solution, precluding the use of a bolus injection because of the burning sensation at the injection site associated with the intravenous administration of alcohol. As a consequence, injections were manually performed using a lead-shielded syringe for 40 s to 2 min, and the rate was reduced based on patient feedback.

Binding Studies with ¹⁸F-FDHT

Displacement studies were performed with ¹⁸F-FDHT and CWR22-rv1 cells with FDHT and DHT as competitors. Briefly, triplicate samples of cells were mixed with 20,000 counts per minute of ¹⁸F-FDHT and increasing amounts of cold competitor (1 pM to 1 μM). The solutions were then shaken on an orbital shaker at ambient temperature, and after 60 min the cells were isolated and washed with ice-cold Tris-buffered saline using a M-24T cell harvester (Brandel). All of the isolated cell samples were counted, with appropriate standards of total activity and blank controls, and the specific uptake of ¹⁸F-FDHT determined. These data were plotted against the concentration of the cold competitor to give sigmoidal displacement curves (Fig. 1). The inhibitory concentration of 50% was determined using a 1-site model and a least-squares curve-fitting routine (Origin; OriginLab). The r² of the curve fit was 0.99.

• Download figure
• Open in new tab
• Download powerpoint

FIGURE 1. 

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

A sample of ¹⁸F-FDHT drug product was evaporated to remove the ethanol and mixed with a 10% suspension of rat liver homogenate in phenazine methosulfate for 30 min at 37°C. At the end of this period, the solution was diluted to 40% acetonitrile and the precipitated proteins pelleted by centrifugation. The metabolized ¹⁸F-FDHT supernatant was then purified by reversed-phase HPLC (C₁₈ Ultrasphere column [Beckman]; 5 μm, 250 × 4.6 mm) using an gradient elution of 40% acetonitrile/10 mM phosphoric acid up to 90% acetonitrile/10 mM phosphoric acid over 10 min at a flow rate of 1 mL/min. Under these conditions, ¹⁸F-FDHT elutes at around 8 min, and the main metabolite elutes at 4 min. The purified metabolite was then used in a displacement binding study as described above.

PET

Each patient underwent at least 1 whole-body ¹⁸F-FDG PET/CT scan that was followed within 1–7 d by dynamic and whole-body ¹⁸F-FDHT PET scans. The initial ¹⁸F-FDG PET/CT scan was used to identify one or more lesions to be followed in the subsequent dynamic ¹⁸F-FDHT scans. A subset of the patients received up to 2 additional sets of scans, approximately 4 and 12 wk later during their course of treatment.

All studies were performed on either a Discovery LS or an Advance PET scanner (GE Healthcare). Before the ¹⁸F-FDG scans, patients were required to fast for at least 6 h and a blood sample was obtained to measure the serum glucose level. No fasting was required for the ¹⁸F-FDHT scan. For all ¹⁸F-FDHT scans, each patient had 1 peripheral intravenous line placed into each arm, 1 for injection and 1 for blood sampling. Scanning in all cases was performed in 2-dimensional mode (septa-in).

The dynamic ¹⁸F-FDHT PET emission scan was initiated coincident with the start of the injection. The first 2 patients underwent a dynamic scan of 55 min. Analysis of this dynamic imaging data, along with plasma metabolite analysis, showed little to no change in activity levels in the tumor occurring beyond 20 min after injection and almost complete metabolism of the compound. The protocol was, therefore, modified for patients 3–13, reducing the duration of the dynamic PET scan to 30 min. After the dynamic scan, patients were allowed to dismount from the table to rest for approximately 10 min. Patients were encouraged to urinate before the acquisition of a whole-body PET scan, which was used to determine overall biodistribution and to explore other potential metastatic sites. The whole-body scan was obtained from the skull base to the pelvic floor. All images were reconstructed using both filtered backprojection (FBP) and iterative reconstruction.

The 25 patients from the second cohort underwent an almost identical scan procedure, except that the 30-min dynamic scan was obtained over the chest to include the heart rather than over a metastatic index lesion. ROI data were derived from the aorta of these patients and were used to generate a population average input function for ¹⁸F-FDHT.

Radiometabolite Analysis of ¹⁸F-FDHT

Patients who underwent ¹⁸F-FDHT scans had blood samples drawn to determine the clearance of ¹⁸F-FDHT and the rate of metabolite formation. Blood samples were drawn at all or some of the following time points after injection with ¹⁸F-FDHT: 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 15, 20, 25, 30, 40, and 50 min. Patients who underwent 30-min dynamic scans did not have the 40- and 50-min blood samples drawn, but whenever possible a blood sample was drawn at a late time point after the whole-body PET scan was obtained. The activities in whole blood, plasma, 30-kDa filtered plasma, and acetonitrile-precipitated plasma were determined. In addition, the relative amounts of ¹⁸F-FDHT and ¹⁸F-FDHT metabolites in the plasma were determined by HPLC.

Aliquots of whole blood were transferred to preweighed tubes. Portions of the blood samples were centrifuged and aliquots of plasma transferred into preweighed tubes. The remaining plasma samples underwent ultrafiltration using 30-kDa spin filters (Centricon YM-30; Millipore), and aliquots of the filtrate were transferred to preweighed tubes. ¹⁸F activity in all samples was assayed in a γ-counter (LKB Wallac 1282; Compugamma) calibrated for ¹⁸F, corrected for decay to the time of injection, and expressed as a percentage of the injected dose per gram.

The counted plasma samples were mixed with 0.45 mL of acetonitrile containing unlabeled FDHT (0.05 mg/mL) as a reference compound. After centrifugation at 2,000g for 5 min, the precipitated proteins were also counted in a γ-counter. The protein-free supernatant was analyzed by reversed-phase C₁₈ HPLC. The Shimadzu HPLC system consisted of 2 LC10AT pumps and a SCL10A controller coupled to a SPD-10A ultraviolet detector and a Packard Radiometric 625TR flow detector (500 μL/cell, with bismuth germanate crystals) in series. The reversed-phase C₁₈ column (Ultrasphere [Beckman]; 5 μm, 250 × 4.6 mm) was eluted, applying a gradient from 40% acetonitrile/10 mM phosphoric acid to 90% acetonitrile/10 mM phosphoric acid over 10 min at a flow rate of 1 mL/min. Under these conditions, ¹⁸F-FDHT elutes at around 8 min and the main metabolized product at 4 min. The data were expressed as a percentage of the total activity in plasma.

ROI Analysis

One nuclear medicine reader analyzed the ROIs in this investigation. The tumor was identified by displaying the ¹⁸F-FDG PET/CT scan alongside the whole-body ¹⁸F-FDHT and regional dynamic ¹⁸F-FDHT scans. Separate ROIs circumscribing a homogeneous region well within the borders of the index tumor were drawn on images from a summed frame, iteratively reconstructed, covering the last 15 min of the ¹⁸F-FDHT PET emission data. ROIs were also generated for the descending aorta (3 studies in 2 patients) or iliac arteries (20 studies in 9 patients) using summed frames covering the first 2 min after ¹⁸F-FDHT injection. All ROIs were applied to FBP-reconstructed images to generate curves of mean activity concentration versus time. FBP images were used here to avoid problems associated with spatially variant convergence rates encountered with iterative reconstruction methods. Multiple ROIs were weighted (by their fractional volume) and summed for structures extending over several adjacent images.

Because of the relatively large diameter of the descending aorta, we chose the 3 curves, so derived, as the reference against which to judge the accuracy of the iliac artery–derived curves and the venous blood samples. A comparison of the blood time–activity curves both within and among studies suggested that data from the venous blood samples and from ROIs drawn over the iliac arteries likely do not accurately represent the true blood–activity time course at early times after ¹⁸F-FDHT injection. Only time–activity curves generated from ROIs drawn over the descending aorta showed the expected first-pass peak (Fig. 2). At late times (>15 min) all curves tended to plateau, with the aorta-derived and venous blood–derived data reaching approximately the same activity concentration level.

• Download figure
• Open in new tab
• Download powerpoint

FIGURE 2. 

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

The descending aorta was within the field of view for only 2 patients in the first cohort; therefore, it was decided to use data from a second separate cohort of patients for which dynamic PET scans of ¹⁸F-FDHT were obtained over the heart. These data were used to establish a population-based blood time–activity curve. Curves derived from ROIs drawn over the aorta from this cohort of 25 patients were converted to standardized uptake values (SUVs = tissue activity per kg divided by injected activity per kg of body weight) and averaged. Individual radiolabeled metabolite and parent ¹⁸F-FDHT input functions were calculated for each patient by first scaling the population-based blood time–activity curve so that it matched the venous blood sample activity level at late times and then multiplying the result by a population-based metabolite-fraction time–activity curve derived from the original cohort. The parent ¹⁸F-FDHT input function could then be calculated by subtracting this metabolite input function from the scaled population-based blood time–activity curve (Fig. 2).

Pharmacokinetic Modeling

A series of linear compartmental pharmacokinetic models of increasing complexity were tested on the tumor tissue data and compared using the Bayesian information criterion (BIC) as formulated by Schwartz (7). The definition of BIC is given aswhere n is the number of data points, RSS the residual sum of squares from the estimated model, and k the number of free parameters used in the model fit.

The BIC provide a statistical metric with which to compare the results of different model fits to the data. The model yielding the lowest BIC value is judged to be of sufficient dimension (i.e., have enough parameters) to describe the data. The BIC increase as a function of the residual sum of squares of the fitted data, but they also increase as the number of model parameters used to fit the data is increased. In this way, the introduction of more than a requisite number of compartments is penalized. Hence, lower BIC imply either fewer explanatory variables, better fit, or both.

The patient data were fitted to 4 different compartmental models that were then compared using the BIC metric. These models are diagrammed in Figure 3. The first and simplest of these models, model 1, consisted of an instantaneously equilibrating space (often also referred to as a fractional blood volume), followed by a unidirectional trap, thus requiring just 2 parameters. The instantaneously equilibrating space was assumed to contain both parent ¹⁸F-FDHT and its metabolites, whereas the trap was assumed to contain only parent ¹⁸F-FDHT. The exclusion of the metabolites from the final compartment was justified on the basis of our in vitro studies demonstrating that the radiolabeled metabolites of ¹⁸F-FDHT do not bind to CWR22-rv1 cells.

• Download figure
• Open in new tab
• Download powerpoint

FIGURE 3. 

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

The next 2 models (2a and 2b) are similar to the first model except for the addition of a reversible space between the instantaneously equilibrating space and the trap. The 2 variants differed in their exclusion (2a) and allowance (2b) of metabolites into this intermediate space. When allowed, the metabolites were forced to enter and exit this space using rate constants constrained to equal that of the parent ¹⁸F-FDHT; thus, each of the 2 variants required 4 parameters. We chose to equate these rate constants under the assumption that the associated space represents a region of disrupted vasculature into which radiolabeled molecules bound to plasma proteins were leaking. For the most complex model tried, model 3, an additional reversible space preceding the unidirectional trap was added, requiring a total of 6 parameters. In this model, metabolites were allowed to enter the first reversible space (again using rate constants constrained to equal that of ¹⁸F-FDHT) but not allowed to enter the second.

In each of these models, we have assumed that the entirety of the parent ¹⁸F-FDHT in the blood is equally available for uptake into the tumor, whether it is bound to plasma proteins or to steroid hormone–binding globulin or other constituents of the blood or free in the plasma. Therefore, our input functions are based on whole-blood activity concentrations.

The ¹⁸F time–activity data for each lesion in each patient PET study was independently fitted by each of the described model variants using the SAAM II software package (University of Washington). Parameter values were adjusted to minimize the sum of the weighted squared differences between the model estimate and the corresponding measured values. The weight for each PET time point was chosen to be the inverse of the duration of its frame. The parent ¹⁸F-FDHT and metabolite input functions applied to the models were the individually scaled population-based curves as described above. BIC values for each of the fits were calculated by SAAM II.

Clinical Image Data

Thirteen patients were studied in this protocol. Most of the metastatic sites were in bone. A summary of the patient scans and treatment regimens is provided in Table 1. A detailed description of these scans is beyond the scope of this article. However, in brief, several of these patients exhibited concordant PET lesion detection by ¹⁸F-FDHT and ¹⁸F-FDG PET, with patient 12 showing ¹⁸F-FDG positivity and ¹⁸F-FDHT negativity and patient 4 exhibiting only abnormal ¹⁸F-FDHT uptake. Two of the patients (12 and 13) did not demonstrate ¹⁸F-FDHT uptake in any tumors and were, thus, excluded from further analysis. Some of the patients demonstrated mixed findings between the SUVs measured for corresponding lesions, with high SUV on ¹⁸F-FDG and low SUV on ¹⁸F-FDHT scans, or vice versa. Most patients with positive ¹⁸F-FDHT baseline scan findings exhibited uptake on posttherapy scans at reduced levels. However, there were instances of increased uptake on the follow-up ¹⁸F-FDHT PET scans, for example, patient 1. One patient (patient 10) had multiple positive lesions on the baseline ¹⁸F-FDG scan and a negative baseline ¹⁸F-FDHT scan result but new abnormal ¹⁸F-FDHT uptake in these regions on the later PET scans. Although several of the patients had some soft-tissue areas of abnormal ¹⁸F-FDG uptake without corresponding ¹⁸F-FDHT uptake, patient 7 showed abnormal ¹⁸F-FDG and ¹⁸F-FDHT uptake in lymph nodes in the left neck and retroperitoneum, with increasing ¹⁸F-FDHT uptake on subsequent scans.

From this patient cohort in Table 1, the following values are observed: the average age of the patients was 66.7 y, with a range of 49–79 y. The median prostate-specific antigen value was 94.65, with a minimum of 0.49 and a maximum of 885.05. The average Gleason score for these patients was 7, with a range of 5–10. The Karnofsky performance status (KPS) values were either 80 (6 patients) or 90 (7 patients). Nine patients had bone disease, 8 had visceral or lymph node lesions, and 4 had both bone and visceral or lymph node disease.

Metabolite Analysis

There was no free ¹⁸F-FDHT, as determined by size-exclusion filtration of serum samples. Recovery of ¹⁸F activity from the acetonitrile-precipitated serum samples was around 89% and showed no trend with increasing metabolite levels. A series of HPLC chromatograms for 1 patient study is shown in Figure 4. The earliest samples, obtained at 1 min after injection, show the activity eluting at 7.6 min as ¹⁸F-FDHT. Later serum samples show increasing amounts of a metabolite eluting at 4 min. The serum count data and HPLC analysis data were combined to give a time–activity curve for total blood activity and ¹⁸F-FDHT and radiolabeled metabolite levels (Fig. 5)

• Download figure
• Open in new tab
• Download powerpoint

FIGURE 4. 

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

• Download figure
• Open in new tab
• Download powerpoint

FIGURE 5. 

Time course of ¹⁸F-FDHT and metabolite levels in serial patient sera. %ID/L = percentage injected dose per liter.

Compartmental Analysis

Twenty-six tumor time–activity datasets were fitted by each of the 4 compartmental models proposed. All datasets fit well to model 1; for 16 of the datasets, the BIC found model 1 to be of the most appropriate dimension. By these criteria, model 2a was most appropriate for 7 cases, and model 2b was best in 2 cases. However, in both of the cases for model 2b, the distribution volumes for the metabolites were found to be quite high (28% and 67%), possibly inconsistent with our in vitro findings that the metabolites do not enter or bind to the cell membrane. The most complex model, model 3, was best by the BIC for only 1 dataset. In this case, the unidirectional rate constant k_trap went to zero.

As can be seen from the results shown in Table 2, the pattern of the model selection does not appear to correlate with individual tumors; that is, repeated studies of the same tumor yielded different models judged as the most appropriate. In the few cases in which either model 2b or model 3 was judged best, the BIC value was not substantially better (i.e., lower) than its values for models 1 and 2a, suggesting perhaps that their seeming superiority might be due to random correlations in the noise. Thus, we present parameter values for only models 1 and 2a in Table 2, leaving the description of models 2b and 3 results to the “Discussion” section. Also in Table 2 are the estimation of the fraction of the measured tumor tissue activity that is bound to AR at 30 min after injection and SUV at that time for models 1 and 2a. The correlation between the k_trap term and the 30-min SUV of model 1 is shown in Figure 6, suggesting the possibility of using a simplified imaging protocol that does not involve blood sampling or modeling.

• Download figure
• Open in new tab
• Download powerpoint

FIGURE 6. 

Scattergram showing relationship between k_trap parameter values calculated in model 1 with 30-min SUV. These data are fitted with line forced through origin. SUV_bw = SUV normalized by body weight.

Sample results of the compartmental modeling are presented in Figure 7A, which shows the fits for model 1 to the measured tumor time–activity data for ¹⁸F-FDHT in patient 1. This patient underwent 1 pre- and 2 posttherapy ¹⁸F-FDHT scans, and for all of these scans model 1 was selected by the BIC. The results consistently show what might be interpreted as a progressive reduction in AR concentration (or a reduction in AR-expressing viable cells) in response to therapy, but alternative interpretations cannot be ruled out on the basis of these data alone.

• Download figure
• Open in new tab
• Download powerpoint

FIGURE 7. 

(A) Tumor time vs. activity concentration data for 3 studies (1 pretherapy and 2 posttherapy) of patient 1 fitted with model 1. (B) 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.