Prediction of the Clinical SUV Ratio in Amyloid PET Imaging Using a Biomathematic Modeling Approach Toward the Efficient Development of a Radioligand.

Our study aimed to develop a method to mathematically predict the kinetic parameters (influx rate constant), (efflux rate constant), and BP (nondisplaceable binding potential) of amyloid PET tracers and obtain SUV ratios (SUVRs) from predicted time-activity curves of target and reference regions. We investigated 10 clinically applied amyloid PET radioligands: C-Pittsburgh compound B, C-BF-227, C-AZD2184, C-SB-13, F-FACT, F-florbetapir, F-florbetaben, F-flutemetamol, F-FDDNP, and F-AZD4694. For each tracer, time-activity curves of both target and reference regions were generated using a simplified 1-tissue-compartment model, with an arterial plasma input function and the predicted kinetic parameters. , , and BP were derived from the lipophilicity (log), apparent volume, free fraction in plasma, free fraction in tissue, dissociation constant, and density of amyloid β using biomathematic modeling. Density was fixed at 3 nM to represent healthy control conditions and 50 nM to represent severe Alzheimer disease (AD). Predicted SUVRs for the healthy and AD groups were then obtained by dividing the integrated time-activity curve of the target region by that of the reference region. To validate the presented method, the predicted , , BP, and SUVR for the healthy and AD groups were compared with the respective clinically observed values. The correlation between predicted and clinical kinetic parameters had an value of 0.73 for in the healthy group, 0.71 for in the AD group, 0.81 for in the healthy group, 0.85 for in the AD group, and 0.63 for BP in the AD group. The regression relationship between the predicted SUVR () and the clinical SUVR () for the healthy and the AD groups was = 2.73 - 2.11 ( = 0.72). The proposed method showed a good correlation between predicted and clinical SUVR for the 10 clinically applied amyloid tracers.