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Single-time-point dosimetry using model selection and the Bayesian fitting method: A proof of concept.

Bisma B Patrianesha1, Steffie M B Peters2, Deni Hardiansyah3

  • 1Medical Physics and Biophysics, Physics Department, Faculty of Mathematics and Natural Sciences, Universitas Indonesia, Depok 16424, Indonesia; Directorate of Nuclear Facility Management, National Research and Innovation Agency (BRIN), Tangerang Selatan, 15314 Banten, Indonesia.

Physica Medica : PM : an International Journal Devoted to the Applications of Physics to Medicine and Biology : Official Journal of the Italian Association of Biomedical Physics (AIFB)
|December 6, 2024
PubMed
Summary

This study introduces a model selection method for simplified kidney dosimetry using Bayesian fitting (BF) and single-time-point (STP) imaging. The proposed STP-BF method with model selection demonstrates superior performance compared to the Hänscheid method for [177Lu]Lu-PSMA-617 dosimetry.

Keywords:
Bayesian fittingPopulation-based model selectionSingle-time-point dosimetry

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Area of Science:

  • Nuclear Medicine
  • Radiopharmaceutical Therapy
  • Medical Physics

Background:

  • Accurate dosimetry is crucial for optimizing radiopharmaceutical therapy, particularly for agents like [177Lu]Lu-PSMA-617 used in metastatic castration-resistant prostate cancer (mCRPC).
  • Simplified dosimetry methods, such as single-time-point (STP) imaging, are desirable for clinical efficiency but require robust model selection for accuracy.
  • Bayesian fitting (BF) offers a flexible framework for pharmacokinetic modeling and dosimetry calculations.

Purpose of the Study:

  • To evaluate the impact of different kinetic models on kidney dosimetry using Bayesian fitting (BF) and single-time-point (STP) imaging.
  • To determine the optimal model for calculating total kidney uptake (TIAC) in [177Lu]Lu-PSMA-617 therapy.
  • To compare the performance of the proposed STP-BF method with established dosimetry techniques.

Main Methods:

  • Kidney biokinetics data from [177Lu]Lu-PSMA-617 SPECT/CT scans in mHSPC patients were analyzed.
  • Eleven different kinetic models were assessed for goodness-of-fit using Akaike weights for model selection.
  • Model averaging was employed to calculate reference total kidney uptake (TIAC_REF).
  • Single-time-point Bayesian fitting (STP-BF) was performed to derive STP TIACs (TIAC_STP-BF) and compared against TIAC_REF and the Hänscheid method.

Main Results:

  • A specific two-exponential function with a shared parameter (λ2) was identified as the best-fit model, achieving an Akaike weight of 57.91%.
  • The STP-BF method using the selected model yielded root-mean-square errors (RMSE) ranging from 8.4% to 20.3% across different time points.
  • The Hänscheid method showed higher RMSEs (14.6% to 22.4%) compared to the STP-BF method for the evaluated time points.

Conclusions:

  • Model selection is critical for accurate simplified dosimetry in [177Lu]Lu-PSMA-617 kidney dosimetry.
  • The proposed STP-BF approach, guided by rigorous model selection, provides a more accurate dosimetry estimation than the conventional Hänscheid method.
  • This optimized STP-BF method enhances the reliability of kidney dosimetry in clinical practice.