The Dosimetry Paradox of Aguix Radiosensitizer Nanoparticles: Shifting from Macroscopic Dose Enhancement to Microdosimetric Specific Energy Distributions
Abstract
Purpose
Preclinical studies combining radiation with gadolinium-based AGuIX nanoparticles show potent radiosensitization effect. However, physics simulations to date show a lack of macroscopic dose enhancement. We address this by shifting from absorbed dose (D) to microdosimetric specific energy (z). We test the hypothesis that the therapeutic benefit is linked to alterations in the stochastic distribution of energy deposition events at the nanoscale, driven by short-range electron cascades arising from AGuIX nanoparticles.
Methods
We performed Monte Carlo simulations using the TOPAS toolkit (Geant4 code). A cell model incorporating 177Lu decays from the membrane generated a phase space source entering lysosomes. These particles were transported through a lysosomal geometry containing explicit AGuIX Gd-nanoparticles (1.5 nm radius) or water-equivalent controls. We used G4Em-Livermore for nanoparticle (AGuIX/control) interactions and G4Em-DNA for low-energy track structure in water. We scored both radial dose profiles and specific energy (z) distributions in nanometric voxels proximal to the nanoparticles to quantify stochastic energy deposition patterns.
Results
Radial dose profiles (D) showed negligible differences in Dose Enhancement Factor (DEF). However, microdosimetric analysis showed a shifted specific energy (z) probability density function in voxels proximal to the nanoparticles. While the mean specific energy remained comparable, the AGuIX group showed an increase in the frequency of high-z events (energy deposition spikes). This tail corresponds to the localized, high-density energy transfer characteristic of Auger cascades, which is conventionally averaged out in standard dosimetry.
Conclusion
The radiosensitizing efficacy of AGuIX is driven by stochastic, high-specific-energy events, rather than cumulative dose enhancement. Standard macroscopic dosimetry obscures these nanometric spikes. Consequently, specific energy (z) provides the mechanistic link between physics and biology, establishing it as the superior metric for predicting efficacy in high-Z nanoparticles radiosensitization.