1. Single-time-point dosimetry using model selection and the Bayesian fitting method: A proof of concept.
- Author
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Patrianesha BB, Peters SMB, Hardiansyah D, Ritawidya R, Privé BM, Nagarajah J, Konijnenberg MW, and Glatting G
- Abstract
Purpose: This study aimed to determine the effect of model selection on simplified dosimetry for the kidneys using Bayesian fitting (BF) and single-time-point (STP) imaging., Methods: Kidney biokinetics data of [
177 Lu]Lu-PSMA-617 from mHSPC were collected using SPECT/CT after injection of (3.1 ± 0.1) GBq at time points T1(2.3 ± 0.5), T2(23.8 ± 2.0), T3(47.7 ± 2.2), T4(71.8 ± 2.2), and T5(167.4 ± 1.9) h post-injection. Eleven functions with various parameterizations and a combination of shared and individual parameters were used for model selection. Model averaging of functions with an Akaike weight of >10 % was used to calculate the reference TIAC (TIACREF ). STP BF method (STP-BF) was performed to determine the STP TIACs (TIACSTP-BF ). The STP-BF performance was assessed by calculating the root-mean-square error (RMSE) of relative deviation between TIACSTP-BF and TIACREF . In addition, the STP-BF performance was compared to the Hänscheid Method., Results: The function [Formula: see text] with shared parameter λ2 was selected as the best function (Akaike weight of 57.91 %). STP-BF using the best function resulted in RMSEs of 20.3 %, 9.1 %, 8.4 %, 13.6 %, and 19.3 % at T1, T2, T3, T4, and T5, respectively. The RMSEs of STP-Hänscheid were 22.4 %, 14.6 %, and 21.9 % at T2, T3, and T4, respectively., Conclusion: A model selection was presented to determine the fit function for calculating TIACs in STP-BF. This study shows that the STP dosimetry using BF and model selection performed better than the frequently used STP Hänscheid method., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Associazione Italiana di Fisica Medica e Sanitaria. Published by Elsevier Ltd. All rights reserved.)- Published
- 2024
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