A Monte Carlo Model of Stochastic Alpha Particle Microdosimetry in 3D Multicellular Aggregates

Abstract

Targeted alpha therapy (TAT) is an emerging new approach to radionuclide therapy, and promises to be especially valuable in the treatment of metastatic disease and radioresistant tumors. However, the dosimetry of TAT presents challenges not seen in photon therapy, due to uncertainties in the relative biological effectiveness (RBE) of alpha radiation. One of the most dominant sources of this uncertainty is the stochasticity originating from the discrete nature of alpha particles, resulting in nonuniform cellular uptake patterns at low specific activities. Current approaches to alpha particle internal dosimetry, based on the MIRD formalism, typically assume that activity is uniformly distributed in subcellular compartments, with resulting absorbed dose distributions being unrealistically homogeneous and isotropic. We develop a Monte Carlo generalization of the MIRD-based formalism that explicitly accounts for stochastic nonuniform localization of alpha emitters in a general 3D multicellular aggregate. In the limit of averaging over many replicates, our approach reduces to the MIRD-based one, which we verify by comparing our code’s results with those of MIRDcell, a commonly used software for TAT dosimetry based on the MIRD formalism. At low specific activity, stochasticity manifests itself as an increase in cell survival beyond that expected from MIRD-based calculations, along with corresponding shifts in the generalized equivalent uniform dose. The magnitude of this effect strongly depends on the cellular localization of alpha emission, a parameter that can be experimentally controlled by altering the chemistry of the conjugate delivery vehicle of the radionuclide.M.S