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Single-time-point estimation of absorbed doses in PRRT using a non-linear mixed-effects model
INTRODUCTION: Estimation of accurate time-integrated activity coefficients (TIACs) and radiation absorbed doses (ADs) is desirable for treatment planning in peptide-receptor radionuclide therapy (PRRT). This study aimed to investigate the accuracy of a simplified dosimetry using a physiologically-ba...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10082376/ https://www.ncbi.nlm.nih.gov/pubmed/35961809 http://dx.doi.org/10.1016/j.zemedi.2022.06.004 |
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author | Hardiansyah, Deni Riana, Ade Beer, Ambros J. Glatting, Gerhard |
author_facet | Hardiansyah, Deni Riana, Ade Beer, Ambros J. Glatting, Gerhard |
author_sort | Hardiansyah, Deni |
collection | PubMed |
description | INTRODUCTION: Estimation of accurate time-integrated activity coefficients (TIACs) and radiation absorbed doses (ADs) is desirable for treatment planning in peptide-receptor radionuclide therapy (PRRT). This study aimed to investigate the accuracy of a simplified dosimetry using a physiologically-based pharmacokinetic (PBPK) model, a nonlinear mixed effect (NLME) model, and single-time-point imaging to calculate the TIACs and ADs of (90)Y-DOTATATE in various organs of dosimetric interest and tumors. MATERIALS & METHODS: Biokinetic data of (111)In-DOTATATE in tumors, kidneys, liver, spleen, and whole body were obtained from eight patients using planar scintigraphic imaging at T1 = (2.9 ± 0.6), T2 = (4.6 ± 0.4), T3 = (22.8 ± 1.6), T4 = (46.7 ± 1.7) and T5 = (70.9 ± 1.0) h post injection. Serum activity concentration was measured at 5 and 15 min; 0.5, 1, 2, and 4 h; and 1, 2, and 3 d p.i.. A published PBPK model for PRRT, NLME, and a single-time-point imaging datum at different time points were used to calculate TIACs in tumors, kidneys, liver, spleen, whole body, and serum. Relative deviations (RDs) (median [min, max]) between the calculated TIACs from single-time-point imaging were compared to the TIACs calculated from the all-time-points fit. The root mean square error (RMSE) of the difference between the computed ADs from the single-time-point imaging and reference ADs from the all-time point fittings were analyzed. A joint root mean square error [Formula: see text] of the ADs was calculated with the RSME from both the tumor and kidneys to sort the time points concerning accurate results for the kidneys and tumor dosimetry. The calculations of TIACs and ADs from the single-time-point dosimetry were repeated using the sum of exponentials (SOE) approach introduced in the literature. The RDs and the RSME of the PBPK approach in our study were compared to the SOE approach. RESULTS: Using the PBPK and NLME models and the biokinetic measurements resulted in a good fit based on visual inspection of the fitted curves and the coefficient of variation CV of the fitted parameters (<50%). T4 was identified being the time point with a relatively low median and range of TIACs RDs, i.e., 5 [1, 21]% and 2 [−15, 21]% for kidneys and tumors, respectively. T4 was found to be the time point with the lowest joint root mean square error [Formula: see text] of the ADs. Based on the RD and RMSE, our results show a similar performance as the SOE and NLME model approach. SUMMARY: In this study, we introduced a simplified calculation of TIACs/ADs using a PBPK model, an NLME model, and a single-time-point measurement. Our results suggest a single measurement might be used to calculate TIACs/ADs in the kidneys and tumors during PRRT. |
format | Online Article Text |
id | pubmed-10082376 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Elsevier |
record_format | MEDLINE/PubMed |
spelling | pubmed-100823762023-04-09 Single-time-point estimation of absorbed doses in PRRT using a non-linear mixed-effects model Hardiansyah, Deni Riana, Ade Beer, Ambros J. Glatting, Gerhard Z Med Phys Original Paper INTRODUCTION: Estimation of accurate time-integrated activity coefficients (TIACs) and radiation absorbed doses (ADs) is desirable for treatment planning in peptide-receptor radionuclide therapy (PRRT). This study aimed to investigate the accuracy of a simplified dosimetry using a physiologically-based pharmacokinetic (PBPK) model, a nonlinear mixed effect (NLME) model, and single-time-point imaging to calculate the TIACs and ADs of (90)Y-DOTATATE in various organs of dosimetric interest and tumors. MATERIALS & METHODS: Biokinetic data of (111)In-DOTATATE in tumors, kidneys, liver, spleen, and whole body were obtained from eight patients using planar scintigraphic imaging at T1 = (2.9 ± 0.6), T2 = (4.6 ± 0.4), T3 = (22.8 ± 1.6), T4 = (46.7 ± 1.7) and T5 = (70.9 ± 1.0) h post injection. Serum activity concentration was measured at 5 and 15 min; 0.5, 1, 2, and 4 h; and 1, 2, and 3 d p.i.. A published PBPK model for PRRT, NLME, and a single-time-point imaging datum at different time points were used to calculate TIACs in tumors, kidneys, liver, spleen, whole body, and serum. Relative deviations (RDs) (median [min, max]) between the calculated TIACs from single-time-point imaging were compared to the TIACs calculated from the all-time-points fit. The root mean square error (RMSE) of the difference between the computed ADs from the single-time-point imaging and reference ADs from the all-time point fittings were analyzed. A joint root mean square error [Formula: see text] of the ADs was calculated with the RSME from both the tumor and kidneys to sort the time points concerning accurate results for the kidneys and tumor dosimetry. The calculations of TIACs and ADs from the single-time-point dosimetry were repeated using the sum of exponentials (SOE) approach introduced in the literature. The RDs and the RSME of the PBPK approach in our study were compared to the SOE approach. RESULTS: Using the PBPK and NLME models and the biokinetic measurements resulted in a good fit based on visual inspection of the fitted curves and the coefficient of variation CV of the fitted parameters (<50%). T4 was identified being the time point with a relatively low median and range of TIACs RDs, i.e., 5 [1, 21]% and 2 [−15, 21]% for kidneys and tumors, respectively. T4 was found to be the time point with the lowest joint root mean square error [Formula: see text] of the ADs. Based on the RD and RMSE, our results show a similar performance as the SOE and NLME model approach. SUMMARY: In this study, we introduced a simplified calculation of TIACs/ADs using a PBPK model, an NLME model, and a single-time-point measurement. Our results suggest a single measurement might be used to calculate TIACs/ADs in the kidneys and tumors during PRRT. Elsevier 2022-08-10 /pmc/articles/PMC10082376/ /pubmed/35961809 http://dx.doi.org/10.1016/j.zemedi.2022.06.004 Text en © 2022 Published by Elsevier GmbH on behalf of DGMP, ÖGMP and SSRMP. https://creativecommons.org/licenses/by-nc-nd/4.0/This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Original Paper Hardiansyah, Deni Riana, Ade Beer, Ambros J. Glatting, Gerhard Single-time-point estimation of absorbed doses in PRRT using a non-linear mixed-effects model |
title | Single-time-point estimation of absorbed doses in PRRT using a non-linear mixed-effects model |
title_full | Single-time-point estimation of absorbed doses in PRRT using a non-linear mixed-effects model |
title_fullStr | Single-time-point estimation of absorbed doses in PRRT using a non-linear mixed-effects model |
title_full_unstemmed | Single-time-point estimation of absorbed doses in PRRT using a non-linear mixed-effects model |
title_short | Single-time-point estimation of absorbed doses in PRRT using a non-linear mixed-effects model |
title_sort | single-time-point estimation of absorbed doses in prrt using a non-linear mixed-effects model |
topic | Original Paper |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10082376/ https://www.ncbi.nlm.nih.gov/pubmed/35961809 http://dx.doi.org/10.1016/j.zemedi.2022.06.004 |
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