Hardiansyah Deni, Riana Ade, Beer Ambros J, Glatting Gerhard
Medical Physics and Biophysics, Physics Department, Faculty of Mathematics and Natural Sciences, Universitas Indonesia, Depok, Indonesia.
Research Collaboration Centre for Theranostic Radiopharmaceuticals, BRIN, Bandung, Indonesia.
EJNMMI Phys. 2023 Feb 10;10(1):12. doi: 10.1186/s40658-023-00530-1.
This project aims to develop and evaluate a method for accurately determining time-integrated activities (TIAs) in single-time-point (STP) dosimetry for molecular radiotherapy. It performs a model selection (MS) within the framework of the nonlinear mixed-effects (NLME) model (MS-NLME).
Biokinetic data of [In]In-DOTATATE activity in kidneys at T1 = (2.9 ± 0.6) h, T2 = (4.6 ± 0.4) h, T3 = (22.8 ± 1.6) h, T4 = (46.7 ± 1.7) h, and T5 = (70.9 ± 1.0) h post injection were obtained from eight patients using planar imaging. Eleven functions were derived from various parameterisations of mono-, bi-, and tri-exponential functions. The functions' fixed and random effects parameters were fitted simultaneously (in the NLME framework) to the biokinetic data of all patients. The Akaike weights were used to select the fit function most supported by the data. The relative deviations (RD) and the root-mean-square error (RMSE) of the calculated TIAs for the STP dosimetry at T3 = (22.8 ± 1.6) h and T4 = (46.7 ± 1.7) h p.i. were determined for all functions passing the goodness-of-fit test.
The function [Formula: see text] with four adjustable parameters and [Formula: see text] was selected as the function most supported by the data with an Akaike weight of (45 ± 6) %. RD and RMSE values show that the MS-NLME method performs better than functions with three or five adjustable parameters. The RMSEs of TIA and TIA were 7.8% and 10.9% (for STP at T3), and 4.9% and 10.7% (for STP at T4), respectively.
An MS-NLME method was developed to determine the best fit function for calculating TIAs in STP dosimetry for a given radiopharmaceutical, organ, and patient population. The proof of concept was demonstrated for biokinetic In-DOTATATE data, showing that four-parameter functions perform better than three- and five-parameter functions.
本项目旨在开发并评估一种用于精确测定分子放射治疗单时间点（STP）剂量测定中时间积分活度（TIA）的方法。它在非线性混合效应（NLME）模型框架内进行模型选择（MS）（MS-NLME）。
通过平面成像从8名患者获取注射后T1 =（2.9±0.6）小时、T2 =（4.6±0.4）小时、T3 =（22.8±1.6）小时、T4 =（46.7±1.7）小时和T5 =（70.9±1.0）小时时肾脏中[铟]铟 - 奥曲肽活度的生物动力学数据。从单指数、双指数和三指数函数的各种参数化中导出了11个函数。这些函数的固定效应和随机效应参数在NLME框架内同时拟合到所有患者的生物动力学数据。使用赤池权重来选择数据最支持的拟合函数。对于通过拟合优度检验的所有函数，确定了注射后T3 =（22.8±1.6）小时和T4 =（46.7±1.7）小时时STP剂量测定中计算的TIA的相对偏差（RD）和均方根误差（RMSE）。
具有四个可调参数的函数[公式：见原文]和[公式：见原文]被选为数据最支持的函数，赤池权重为（45±6）%。RD和RMSE值表明，MS-NLME方法比具有三个或五个可调参数的函数表现更好。TIA和TIA的RMSE在T3时（对于STP）分别为7.8%和10.9%，在T4时（对于STP）分别为4.9%和10.7%。
开发了一种MS-NLME方法，以确定用于计算给定放射性药物、器官和患者群体的STP剂量测定中TIA的最佳拟合函数。针对生物动力学铟 - 奥曲肽数据证明了概念验证，表明四参数函数比三参数和五参数函数表现更好。
