Single-time-point dosimetry using model selection and nonlinear mixed-effects modelling: a proof of concept

被引:17
作者
Hardiansyah, Deni [1 ,2 ]
Riana, Ade [1 ]
Beer, Ambros J. [3 ]
Glatting, Gerhard [3 ,4 ]
机构
[1] Univ Indonesia, Fac Math & Nat Sci, Med Phys & Biophys Phys Dept, Depok, Indonesia
[2] Res Collaborat Ctr Theranost Radiopharmaceut, BRIN, Bandung, Indonesia
[3] Ulm Univ, Dept Nucl Med, Ulm, Germany
[4] Ulm Univ, Dept Nucl Med, Med Radiat Phys, Albert-Einstein-Allee 23, D-89081 Ulm, Germany
关键词
Akaike weight; Model selection; NLME; PRRT; THERAPY; BIODISTRIBUTION; RADIOIODINE; SPECT/CT;
D O I
10.1186/s40658-023-00530-1
中图分类号
R8 [特种医学]; R445 [影像诊断学];
学科分类号
1002 ; 100207 ; 1009 ;
摘要
Purpose: 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).Methods: Biokinetic data of [In-111]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 func-tions. 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.Results: The function f(4d)(t) = A1/{ 1-alpha/lambda(1)+lambda(phys)) - (alpha/ lambda(2)+lambda(phys)) - (1-2 alpha/lambda(bc)+lambda(phys))} middot e(physt)(-lambda) middot {(1 - alpha) middot e(1)(-lambda)t - alpha middot e(2)(-lambda)t - (1 - 2 alpha) middot e(bc)(-lambda)t}with four adjustable parameters and lambda(bc) = ln(2)/ 1 min 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(NLME-PBMS) and TIA(3-parameters) were 7.8% and 10.9% (for STP at T3), and 4.9% and 10.7% (for STP at T4), respectively.Conclusion: 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-111-DOTATATE data, showing that four-parameter functions perform better than three-and five-parameter functions.
引用
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页数:12
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