Establishing In Vitro Dosimetric Models and Dose-Effect Relationships for 177Lu-DOTATATE in Neuroendocrine Tumors

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Abstract

This study investigates the radiobiology of peptide receptor radionuclide therapy (PRRT) using clinically relevant cancer cell lines by developing a framework for realistic cellular dosimetry in 2- and 3-dimensional cluster-forming configurations. Methods: The radiobiologic responses of GOT1 and NCI-H69 tumor cell lines to PRRT and external beam radiotherapy (EBRT) were compared. Viability at 7 d and cell death at multiple time points were assessed. Image-based multicellular dosimetry models were developed to reflect in vitro exposure complexity and were compared with traditional approaches. Results: The PRRT absorbed dose in suspension was dominated by medium during incubation and by a cross-dose within small clusters after incubation. Our findings reveal that traditional dosimetry can underestimate absorbed doses by up to 90% in plated setups and overlooks dose heterogeneity, with initial dose rates varying by up to 2.3-fold based on cluster size and cell arrangement. The maximum relative biologic effectiveness of PRRT compared with EBRT for loss of viability at 7 d was 0.43 ± 0.07 for NCI-H69 cells and 0.22 ± 0.02 for GOT1 cells. NCI-H69 cells showed greater resistance to PRRT-induced cell death than to EBRT, whereas GOT1 cells exhibited similar cell death levels for both treatments, albeit with different dose-response dynamics. Conclusion: PRRT requires on average an absorbed dose 3 times higher than EBRT to achieve equivalent effects in vitro. Traditional dosimetry overestimates the relative biologic effectiveness by underestimating the absorbed dose.

Original languageEnglish
Pages (from-to)1291-1298
Number of pages8
JournalJournal of nuclear medicine : official publication, Society of Nuclear Medicine
Volume66
Issue number8
DOIs
Publication statusPublished - 1 Aug 2025

Bibliographical note

Publisher Copyright:
© 2025 by the Society of Nuclear Medicine and Molecular Imaging.

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 3 - Good Health and Well-being
    SDG 3 Good Health and Well-being

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