Time-integrated activity coefficient estimation for radionuclide therapy using PET and a pharmacokinetic model

• Verfasst von: Hardiansyah, Deni [VerfasserIn]
• Verfasst von: Glatting, Gerhard [VerfasserIn]
• Titel: Time-integrated activity coefficient estimation for radionuclide therapy using PET and a pharmacokinetic model
• Titelzusatz: A simulation study on the effect of sampling schedule and noise
• Verf.angabe: Deni Hardiansyah, Wei Guo, Peter Kletting, Felix M. Mottaghy, Gerhard Glatting
• E-Jahr: 2016
• Jahr: 19 August 2016
• Umfang: 10 S.
• Fussnoten: Gesehen am 06.08.2019
• Titel Quelle: Enthalten in: Medical physics
• Ort Quelle: Hoboken, NJ : Wiley, 1974
• Jahr Quelle: 2016
• Band/Heft Quelle: 43(2016), 9, Seite 5145-5154
• ISSN Quelle: 2473-4209
• ISSN Quelle: 1522-8541
• DOI: doi:10.1118/1.4961012
• Datenträger: Online-Ressource
• Sprache: eng
• Sach-SW: Bayes methods
• Sach-SW: Bayesian parameter
• Sach-SW: Biological material
• Sach-SW: Biomedical modeling
• Sach-SW: Cancer
• Sach-SW: Computer modeling
• Sach-SW: Dose-volume analysis
• Sach-SW: dosimetry
• Sach-SW: e.g. blood
• Sach-SW: Haemocytometers
• Sach-SW: kidney
• Sach-SW: Kidneys
• Sach-SW: Liver
• Sach-SW: Measuring half-life of a radioactive substance
• Sach-SW: Medical imaging
• Sach-SW: Medical treatment planning
• Sach-SW: Optimization
• Sach-SW: PBPK model
• Sach-SW: Peptides
• Sach-SW: PET
• Sach-SW: phantoms
• Sach-SW: positron emission tomography
• Sach-SW: Positron emission tomography (PET)
• Sach-SW: PRRT
• Sach-SW: radiation therapy
• Sach-SW: Radiation therapy
• Sach-SW: radioisotopes
• Sach-SW: Scintigraphy
• Sach-SW: TIAC
• Sach-SW: Tissue response
• Sach-SW: tumours
• Sach-SW: urine
• K10plus-PPN: 1670649822

Abstract

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 68Ga-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 90Y-DOTATATE of 3.3 GBq in both true and predicted MPPs. Prediction accuracy was then calculated as relative variability vorgan between TIACs from both MPPs. Results: Large variability values of one time-point protocols [e.g., FSD = 1%, 240 min p.i., vkidneys = (9 ± 6)%, and vtumor = (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%, vkidneys = (7 ± 3)%, and vtumor = (22 ± 10)%, or three measurements, e.g., FSD = 1%, vkidneys = (7 ± 3)%, and vtumor = (22 ± 9)%. Conclusions: 68Ga-DOTATATE-PET measurements could possibly be used to predict the TIACs of 90Y-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.