Models and phantoms for internal dose assessment.

Area of Science:

• Medical Physics
• Radiation Biology
• Computational Modeling

Background:

• Internal dosimetry relies on biokinetic and dosimetric models with computational phantoms to estimate radiation doses from incorporated radionuclides.
• Traditional organ-level dosimetry is insufficient for short-range radiation emitters (alpha particles, Auger electrons).
• Micro- and nano-dosimetry are emerging fields addressing cellular and molecular radiation transport and deposition.

Purpose of the Study:

• To discuss the challenges, limitations, and future perspectives of models and phantoms in internal dosimetry.
• To highlight the increasing complexity and realism of computational models.
• To emphasize the role of uncertainty studies in validating new dose estimates.

Main Methods:

• Review of biokinetic and dosimetric modeling approaches.
• Discussion of computational phantom development and their increasing anatomical and physiological realism.
• Analysis of uncertainty quantification in internal dose assessment.

Main Results:

• Organ-level dosimetry is inadequate for short-range emitters, necessitating micro- and nano-dosimetry.
• Increased model complexity requires more detailed input data, which may not always be available.
• Uncertainty studies are vital for assessing the significance of advanced dosimetry models and comparing new estimates with older values.

Conclusions:

• Advanced modeling, including micro- and nano-dosimetry, is essential for accurate dose assessment of incorporated radionuclides, particularly for targeted therapies.
• The complexity of modern models necessitates robust uncertainty quantification to ensure reliable dose estimates.
• Future research should focus on improving model realism and data availability while validating through uncertainty analysis.