Shifting the Spotlight to Low-Dose Rate Radiobiology in Radiopharmaceutical Therapies: Mathematical Modeling, Challenges, and Future Directions

Radiopharmaceutical therapy (RPT) is an established treatment modality and is of increasing interest for different cancer types. A key unmet need, both in the wider adoption of RPT and in the improvement of outcomes with existing RPTs, is in treatment planning and optimization. Research efforts have been hindered by the incomplete understanding of the radiobiology RPTs. Modeling in RPT often mirrors external beam radiotherapy (EBRT), despite key differences. The dose rate (DR) is notably distinct between the two, influencing radiation responses. In EBRT, radiation is acutely delivered in discrete transient fractions of relatively short duration, with a near-constant DR. In RPT, by contrast, exposure is gradual, protracted, and characterized by temporal nonuniformities arising from organ-specific radio-pharmacokinetics. As a result, low-DR (LDR) radiobiology adapted for RPT (LDR-RPT) has emerged as a vibrant area of research. In this review, we discuss the state-of-the-art understanding of the etiological mechanisms underlying cellular and tissue-level dose responses in LDR-RPT, with a focus on how this radiobiological knowledge is codified in mathematical and computational models. We also describe current feasibility and future prospects for utilizing such quantitative radiobiological models to perform personalized RPT planning and highlight research directions that should be prioritized to accelerate clinical adoption.

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Publication Details

Journal
IEEE Transactions on Radiation and Plasma Medical Sciences
Published
2025-02-18
DOI
https://doi.org/10.1109/trpms.2025.3540739
Citations
2
Primary Topic
Radiation Detection and Scintillator Technologies
Type
article
Field-Weighted Citation Impact
3.77
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article

Shifting the Spotlight to Low-Dose Rate Radiobiology in Radiopharmaceutical Therapies: Mathematical Modeling, Challenges, and Future Directions

Babak Saboury, Tahir Yusufaly, Arman Rahmim, C. Uribe et al.
2 citations
IEEE Transactions on Radiation and Plasma Medical Sciences
Radiation Detection and Scintillator Technologies
3.77
article

Shifting the Spotlight to Low-Dose Rate Radiobiology in Radiopharmaceutical Therapies: Mathematical Modeling, Challenges, and Future Directions

Babak Saboury, Tahir Yusufaly, Arman Rahmim, C. Uribe, Ian L. Alberts, Hamid Abdollahi
article en
2 citations

Abstract

Radiopharmaceutical therapy (RPT) is an established treatment modality and is of increasing interest for different cancer types. A key unmet need, both in the wider adoption of RPT and in the improvement of outcomes with existing RPTs, is in treatment planning and optimization. Research efforts have been hindered by the incomplete understanding of the radiobiology RPTs. Modeling in RPT often mirrors external beam radiotherapy (EBRT), despite key differences. The dose rate (DR) is notably distinct between the two, influencing radiation responses. In EBRT, radiation is acutely delivered in discrete transient fractions of relatively short duration, with a near-constant DR. In RPT, by contrast, exposure is gradual, protracted, and characterized by temporal nonuniformities arising from organ-specific radio-pharmacokinetics. As a result, low-DR (LDR) radiobiology adapted for RPT (LDR-RPT) has emerged as a vibrant area of research. In this review, we discuss the state-of-the-art understanding of the etiological mechanisms underlying cellular and tissue-level dose responses in LDR-RPT, with a focus on how this radiobiological knowledge is codified in mathematical and computational models. We also describe current feasibility and future prospects for utilizing such quantitative radiobiological models to perform personalized RPT planning and highlight research directions that should be prioritized to accelerate clinical adoption.

IEEE Transactions on Radiation and Plasma Medical SciencesVol. 9(7)
BC Cancer Agency (CA), National Institutes of Health (US), University of British Columbia (CA), Johns Hopkins University (US)
Zero hunger
Openalex Percentile: Top 9%
Radiation Detection and Scintillator Technologies
3.77
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