Yoko Ikoma

The ordered subset expectation maximization with a point spread function (OSEM-PSF) was developed to improve the spatial resolution of reconstructed positron emission tomography (PET) images and has been reported to improve the contrast of hot spots in PET studies for oncology. However, in neuroreceptor imaging, the regional radioactivity concentration changes dynamically during the scan, and the effects of the PSF may differ among various radioligands or quantification methods. In this study, we investigated the effects of the PSF on quantification in PET studies with [¹¹C]FLB 457 of dopamine D₂ receptors, using both phantom and human data acquired by the Siemens Biograph 16 imaging platform. In the phantom studies, we evaluated the hot contrast recovery coefficient (HCRC) for variously sized hot spheres and the linearity between the measured and true radioactivities in OSEM-PSF images. Next, in the human studies with [¹¹C]FLB 457, radioactivity concentrations and binding potentials for the cerebral cortex and thalamus were compared between images reconstructed with and without PSF. In the phantom studies, the OSEM-PSF images showed a better HCRC compared to images without PSF, and they showed a good linear correlation with true radioactivity. In the human studies, the radioactivity concentration increased especially in small regions with high accumulation of [¹¹C]FLB 457 when the PSF was included. However, little difference in the binding potentials was observed for the target regions between both types of reconstructed images. In conclusion, PSF-based reconstruction reduced the spill-over phenomena in small hot regions; however, it caused no increase in the binding potentials in the [¹¹C]FLB 457 studies.

Positron emission tomography (PET) with ¹⁸F-FE-PE2I is useful for investigating the function of dopamine transporter, and kinetics of ¹⁸F-FE-PE2I could be described by standard two-tissue compartment model (2CM) using plasma input function. In this study, we investigated the feasibility of semi-quantitative methods for estimating binding potential (BPND) and transporter occupancy to shorten the scan period and to reduce the effect of statistical noise on quantitative outcomes using computer simulation and human PET studies with ¹⁸F-FE-PE2I. In the simulations, time-activity curves (TACs) for the putamen with a wide range of BPND were generated. In these TACs, BPNDs were estimated by standardized uptake value ratio (SUVR) using various integration intervals and the simplified reference tissue model (SRTM) with the cerebellum as reference region, and reduction of BPND assuming transporter occupancy by antipsychotics was calculated from BPND obtained from TACs with various BPND values. These estimates were evaluated by comparison with those of 2CM. In human studies with normal volunteers, BPNDs were estimated in the caudate and putamen using SUVR and SRTM with the cerebellar reference region, and compared with BPND by standard 2CM. In the simulations, BPND estimated by SUVR with late time frames and SRTM showed linear correlation with those by 2CM, although the estimates by SUVR were overestimated and affected by the cerebral blood flow as BPND became higher. As for transporter occupancy, SRTM showed higher linearity with 2CM and less effect of statistical noise than the SUVR method. In human studies, BPND by SRTM and SUVR with late time frames showed good correlation with BPND by 2CM. Although SRTM is more reliable than the SUVR method for BPND and occupancy estimation, SUVR using late time frames has the potential to provide practical indices of BPND and occupancy with a shorter scan period.

P-glycoprotein (P-gp) is a membrane protein that functions as an adenosine triphosphate-dependent efflux pump for xenobiotics at the blood-brain barrier (BBB). Polymorphisms of MDR1 gene have been reported to be associated with the expression level of P-gp. (11)C-Verapamil is considered to be one of the suitable radioligands for evaluating P-gp functions. However, the metabolites of verapamil might complicate the quantitative analysis because of their possible brain penetration. In the present study, we investigated the P-gp functional differences at the BBB between the haplotypes (1236TT, 2677TT, 3435TT vs. 1236CC, 2677GG, 3435CC) of the MDR1 gene with different quantitative analyses of (11)C-verapamil. Thirty-three healthy male volunteers were enrolled in this study after identification of the haplotypes of the MDR1 gene. Brain PET scans with (11)C-verapamil were performed for 16 min. Integration plot analysis, which yields brain uptake clearance, was performed with the first 3-min data. Integration plot analysis was then compared with several other quantitative analyses with 16-min data (1-input, 1-tissue compartment model, and the area under the curve ratio (AUC(ratio)) between brain and plasma). In the integration plot, there was no difference in the absolute values of brain uptake clearance (CL(uptake)) between the haplotypes; CL(uptake) of (11)C-verapamil for the haplotypes (1236TT, 2677TT, 3435TT vs. 1236CC, 2677GG, 3435CC) were 0.053 +/- 0.011 and 0.051 +/- 0.011 mL/g/min, respectively. CL(uptake) of (11)C-verapamil in the integration plot was significantly correlated with K1 and DV(K1/k2) (DV is distribution volume; K1 and k2 are plasma and tissue rate constants) in the 1-input, 1-tissue compartment model and the AUC(ratio). On the basis of the several quantitative analyses of (11)C-verapamil, the assumption that the function of P-gp at the BBB is different between the haplotypes (3 single nucleotide polymorphisms: C1236T, G2677T, and C3435T) of MDR1 gene was not supported.

P-glycoprotein in the blood-brain barrier (BBB) has been found to be associated with several types of neurologic damage. (11)C-Verapamil has been used for in vivo imaging of P-glycoprotein function in the BBB by PET, but metabolites in plasma complicate the quantitative analysis of human studies. In this study, we validated the quantification methods of (11)C-verapamil transfer from plasma to the brain in humans. The transfer rate constant from plasma to the brain, K(1), was estimated by nonlinear least squares (NLS) with a 2-input compartment model, including the permeation of the main metabolite in plasma at the BBB, and with a 1-input compartment model using only 15-min data that contained little metabolite in plasma. K(1) was also estimated by graphical analysis of an integration plot that uses only early-time data, before the appearance of metabolites, and the estimated K(1) was compared with that obtained by the NLS method. In the simulation study, the reliability of parameter estimates in the graphical analysis method was investigated for various values of rate constants, time ranges of parameter estimations, and noise levels. (11)C-Verapamil in plasma gradually converted to its metabolites, and about 45% of the radioactivity in the plasma specimen was associated with (11)C-verapamil metabolites at 30 min after injection. Although K(1) estimated from graphical analysis was slightly smaller than that by NLS, there was strong correlation among the K(1) values obtained by these 3 methods. In the simulation study, for graphical analysis, the differences between the true and mean of K(1) estimates became larger and the coefficient of variation (COV) of K(1) estimates became smaller as the end time of linear regression became later. The COV of graphical analysis was almost equal to that of NLS with the 1-input compartment model. The transfer of (11)C-verapamil from plasma to the brain was able to be quantitatively estimated by graphical analysis because this method can provide K(1) from the data of the initial few minutes without considering the effect of the metabolites in plasma.

Quantification of the receptor binding potential (BP) in human brain has been performed with positron emission tomography. In this quantitative analysis, the uncertainty in estimated kinetic parameters depends on the SNR. Evaluation of the reliability of parameter estimates is important for the optimization of scan protocol and quantitative analysis methods. However, estimating the reliability is not easy for human data because the true noise level is not precisely known. In this study, we have evaluated a method for estimating the reliability of kinetic parameters with a bootstrap approach for both simulated and human data, and applied this method to evaluating the influence of scan time on the error in BP estimated from PET [¹¹C]raclopride studies. As a result, it was possible to deduce the reliability of kinetic parameter estimates in region-of-interest analysis of human data using the replicated data generated by bootstrap method. In [¹¹C]raclopride studies, the mean estimated BP value did not change when the scan time decreased from 90 to 15 min. However, the uncertainty in BP estimates became larger as the scan time became shorter. With the bootstrap method, it is possible to easily assess the reliability of parameter estimates using only the measured data, and this method can be applied to optimizing scan protocol.