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使用非线性混合效应模型单次点估计 PRRT 中的吸收剂量。

Single-time-point estimation of absorbed doses in PRRT using a non-linear mixed-effects model.

机构信息

Medical Physics and Biophysics, Physics Department, Faculty of Mathematics and Natural Sciences, Universitas Indonesia, Depok, Indonesia.

Department of Nuclear Medicine, Ulm University, Ulm, Germany.

出版信息

Z Med Phys. 2023 Feb;33(1):70-81. doi: 10.1016/j.zemedi.2022.06.004. Epub 2022 Aug 10.

DOI:10.1016/j.zemedi.2022.06.004
PMID:35961809
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC10082376/
Abstract

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 Y-DOTATATE in various organs of dosimetric interest and tumors.

MATERIALS & METHODS: Biokinetic data of 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 RMSE 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 RMSE 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.

摘要

简介

在肽受体放射性核素治疗 (PRRT) 中,准确估计时间积分活度系数 (TIAC) 和辐射吸收剂量 (AD) 是非常理想的。本研究旨在探讨使用基于生理的药代动力学 (PBPK) 模型、非线性混合效应 (NLME) 模型和单点成像来计算 Y-DOTATATE 在感兴趣的剂量器官和肿瘤中的 TIAC 和 AD 的简化剂量计算的准确性。

材料和方法

使用八位患者的 T1 = (2.9 ± 0.6)、T2 = (4.6 ± 0.4)、T3 = (22.8 ± 1.6)、T4 = (46.7 ± 1.7) 和 T5 = (70.9 ± 1.0) h 注射后,使用平面闪烁成像获得 IN-DOTATATE 在肿瘤、肾脏、肝脏、脾脏和全身的生物动力学数据。在注射后 5 和 15 分钟、0.5、1、2 和 4 小时以及 1、2 和 3 天测量血清活度浓度。使用发表的 PRRT PBPK 模型、NLME 和不同时间点的单点成像数据来计算肿瘤、肾脏、肝脏、脾脏、全身和血清中的 TIAC。单点成像计算的 TIAC 的相对偏差 (RD) (中位数 [最小,最大]) 与所有时间点拟合计算的 TIAC 进行比较。单点成像计算的 AD 的均方根误差 (RMSE) 与参考 AD 的 RMSE 进行比较。通过计算来自肿瘤和肾脏的 AD 的联合均方根误差 RMSE,来确定肾脏和肿瘤剂量学准确结果的时间点。使用文献中引入的指数和 (SOE) 方法重复单点剂量计算的 TIAC 和 AD。比较了我们研究中 PBPK 方法和 NLME 方法的 RD 和 RSME 与 SOE 方法。

结果

使用 PBPK 和 NLME 模型以及生物动力学测量结果基于拟合曲线的视觉检查和拟合参数的变异系数 (CV) (<50%),表明拟合良好。T4 被确定为 TIACs RD 中位数和范围相对较低的时间点,即肾脏和肿瘤的 5 [1, 21]%和 2 [-15, 21]%。T4 被发现是 AD 联合均方根误差 RMSE 最低的时间点。基于 RD 和 RMSE,我们的结果表明与 SOE 和 NLME 模型方法具有相似的性能。

总结

在这项研究中,我们引入了一种使用 PBPK 模型、NLME 模型和单点测量来简化 TIAC/AD 计算的方法。我们的结果表明,单点测量可能用于 PRRT 期间计算肾脏和肿瘤中的 TIAC/AD。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9b63/10082376/a1befbd581fa/gr5.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9b63/10082376/4aa7bd478837/gr1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9b63/10082376/10564671d756/gr2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9b63/10082376/e82c10f86959/gr3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9b63/10082376/9dbdb88b1d80/gr4.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9b63/10082376/a1befbd581fa/gr5.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9b63/10082376/4aa7bd478837/gr1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9b63/10082376/10564671d756/gr2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9b63/10082376/e82c10f86959/gr3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9b63/10082376/9dbdb88b1d80/gr4.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9b63/10082376/a1befbd581fa/gr5.jpg

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