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Time‐integrated activity coefficient estimation for radionuclide therapy using PET and a pharmacokinetic model: A simulation study on the effect of sampling schedule and noise
Author(s) -
Hardiansyah Deni,
Guo Wei,
Kletting Peter,
Mottaghy Felix M.,
Glatting Gerhard
Publication year - 2016
Publication title -
medical physics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.473
H-Index - 180
eISSN - 2473-4209
pISSN - 0094-2405
DOI - 10.1118/1.4961012
Subject(s) - physiologically based pharmacokinetic modelling , radionuclide therapy , bayesian probability , mathematics , nuclear medicine , population , statistics , dosimetry , standard deviation , pharmacokinetics , medicine , environmental health
Purpose: The aim of this study was to investigate the accuracy of PET‐based treatment planning for predicting the time‐integrated activity coefficients (TIACs). Methods: The parameters of a physiologically based pharmacokinetic (PBPK) model were fitted to the biokinetic data of 15 patients to derive assumed true parameters and were used to construct true mathematical patient phantoms (MPPs). Biokinetics of 150 MBq 68 Ga‐DOTATATE‐PET was simulated with different noise levels [fractional standard deviation (FSD) 10%, 1%, 0.1%, and 0.01%], and seven combinations of measurements at 30 min, 1 h, and 4 h p.i. PBPK model parameters were fitted to the simulated noisy PET data using population‐based Bayesian parameters to construct predicted MPPs. Therapy simulations were performed as 30 min infusion of 90 Y‐DOTATATE of 3.3 GBq in both true and predicted MPPs. Prediction accuracy was then calculated as relative variability v organ between TIACs from both MPPs. Results: Large variability values of one time‐point protocols [e.g., FSD = 1%, 240 min p.i., v kidneys = (9 ± 6)%, and v tumor = (27 ± 26)%] show inaccurate prediction. Accurate TIAC prediction of the kidneys was obtained for the case of two measurements (1 and 4 h p.i.), e.g., FSD = 1%, v kidneys = (7 ± 3)%, and v tumor = (22 ± 10)%, or three measurements, e.g., FSD = 1%, v kidneys = (7 ± 3)%, and v tumor = (22 ± 9)%. Conclusions: 68 Ga‐DOTATATE‐PET measurements could possibly be used to predict the TIACs of 90 Y‐DOTATATE when using a PBPK model and population‐based Bayesian parameters. The two time‐point measurement at 1 and 4 h p.i. with a noise up to FSD = 1% allows an accurate prediction of the TIACs in kidneys.