3108 - A Biomolecular Dosimeter: Incorporating Spatial (LET) and Temporal (Dose Rate) Factors in Radiation Dosimetry and Treatment Planning
Presenter(s)
M. Rezaee1, E. Traneus2, and J. W. Wong3; 1Department of Radiation Oncology and Molecular Radiation Sciences, School of Medicine, Johns Hopkins University, Baltimore, MD, 2RaySearch Laboratories AB, Stockholm, Sweden, 3Department of Radiation Oncology and Molecular Radiation Sciences, Johns Hopkins University, Baltimore, MD
Purpose/Objective(s): Biological effects of radiation depend on spatial (LET) and temporal (dose-rate) factors, which cannot be captured by absorbed dose (Gy) alone. Empirical factors such as RBE and DMF are used to compensate for this limitation; however, they lack universal applicability across different radiation modalities, making treatment plan comparison and integration difficult. To address this issue, we hypothesize a new metric, the Molecular Dosimetry Unit (MoD), which captures downstream biomolecular alterations to provide differential quantification of biological outcomes due to spatial and temporal characteristics of radiation. Here, we study the utility of MoD in radiation dosimetry by demonstrating its ability to consolidate disparate LET-dependent survival curves into a single curve for different cell lines and investigate its application in treatment planning systems.
Materials/Methods: MoD is defined as the product of Clustered Alteration Size (CAS ), the number of radiation-induced molecular alterations in a nanometric volume, and Clustered Alteration Frequency (CAF), which quantifies the frequency of CAS occurrences in a biomolecular dosimeter. CAS and CAF were modeled in an 8-µm3 nucleus-size volume containing nanometric voxels with 15 base pair of hydrated DNA. Molecular alterations were derived from Monte Carlo simulations of radicals produced by electrons, protons, helium, and carbon ions at varying LETs, mapped to experimentally measured DNA damage yields. The MoD utility was evaluated by re-analyzing published cell survival data across a broad LET range (1.0 – 880 keV/µm). The resulting MoD values were integrated into RayStation IonPG v2024B TPS to calculate MoD distributions in a water phantom under spread out Bragg peak (SOBP) conditions and compared with dose and RBE-weighted dose distributions.
Results: MoD consolidates diverse LET-dependent cell survival curves into a single unified curve for each cell line, inclusive of dose, particle type, and LET. This capability obviates the need for empirical RBE factors and enables comparison of biological outcomes across different radiation types. Comparison of depth-dose and depth-MoD distributions show that MoD follows the dose for low-LET radiation, but diverges at high-LET, highlighting increased molecular damage potential. Within the proton SOBP, dose remains uniform while MoD increases towards the distal edge. This effect is even more pronounced with higher LET particles like carbon ions. These trends resemble those predicted by RBE models (MKM and LEM), although MoD is derived directly from physical parameters rather than empirical factors.
Conclusion: MoD as a descriptor of radiation damage potential can be applied to treatment plans and dose prescriptions across vaious modalities without relying on empirical factors like RBE. Thus, MoD-based treatment plans can facilitate both initial and re-treatment strategies that combine multiple modalities.