ArticleEJNMMI physics2021
A population-based method to determine the time-integrated activity in molecular radiotherapy.
Article in EJNMMI physics, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.
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Who cites it
14 citing papers in PubMed.
- Recent advances and current landscape of software tools for image analysis and dosimetry in nuclear medicine.EJNMMI physics · 2026Review
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- Understanding time-activity curve and time-integrated activity variations in radiopharmaceutical therapy challenge: Experience and results.Medical physics · 2025Article
- Non-linear mixed-effects modelling and population-based model selection forEJNMMI physics · 2025Article
- Accuracy and precision analyses of single-time-point dosimetry utilising physiologically-based pharmacokinetic modelling and non-linear mixed-effects modelling.EJNMMI physics · 2025Article
- Population pharmacokinetic modeling in radiopharmaceutical therapy: a review.Frontiers in nuclear medicine · 2025Review
- Heterogeneity of absorbed dose distribution in kidney tissues and dose-response modelling of nephrotoxicity in radiopharmaceutical therapy with beta-particle emitters: A review.Zeitschrift fur medizinische Physik · 2024Review
- Impact of the Reference Multiple-Time-Point Dosimetry Protocol on the Validity of Single-Time-Point Dosimetry for [Journal of nuclear medicine : official publication, Society of Nuclear Medicine · 2024Article
- Population-based model selection for an accurate estimation of time-integrated activity using non-linear mixed-effects modelling.Zeitschrift fur medizinische Physik · 2024Article
- Uncertainty Analysis of Time-Integrated Activity Coefficient in Single-Time-Point Dosimetry Using Bayesian Fitting Method.Nuclear medicine and molecular imaging · 2024Article
- Metabolic kinetic modeling of [European journal of nuclear medicine and molecular imaging · 2023Article
- Single-time-point dosimetry using model selection and nonlinear mixed-effects modelling: a proof of concept.EJNMMI physics · 2023Article
- Investigation of image-based lesion and kidney dosimetry protocols forEJNMMI physics · 2023Article
- Single-time-point estimation of absorbed doses in PRRT using a non-linear mixed-effects model.Zeitschrift fur medizinische Physik · 2023Article
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8 authors.
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Abstract
backgroundThe calculation of time-integrated activities (TIAs) for tumours and organs is required for dosimetry in molecular radiotherapy. The accuracy of the calculated TIAs is highly dependent on the chosen fit function. Selection of an adequate function is therefore of high importance. However, model (i.e. function) selection works more accurately when more biokinetic data are available than are usually obtained in a single patient. In this retrospective analysis, we therefore developed a method for population-based model selection that can be used for the determination of individual time-integrated activities (TIAs). The method is demonstrated at an example of [
methodsRenal biokinetics of [
resultsThe function [Formula: see text] with shared parameter [Formula: see text] was selected as the function most supported by the data with an Akaike weight of 97%. Parameters [Formula: see text] and [Formula: see text] were fitted individually for every patient while parameter [Formula: see text] was fitted as a shared parameter in the population yielding a value of 0.9632 ± 0.0037.
conclusionsThe presented population-based model selection allows for a higher number of parameters of investigated fit functions which leads to better fits. It also reduces the uncertainty of the obtained Akaike weights and the selected best fit function based on them. The use of the population-determined shared parameter for future patients allows the fitting of more appropriate functions also for patients for whom only a low number of individual data are available.
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