An analytical framework for efficient and precision-controlled Monte Carlo simulation of heterogeneous targeted alpha therapy microdosimetry.

backgroundDosimetric studies of targeted alpha therapy (TAT) show that microscopic heterogeneity in geometry and source distribution strongly affects dose-effect relationships, underscoring the potential of microdosimetry. While Monte Carlo (MC) simulation is the gold standard for dose assessment, its application to TAT microdosimetry remains methodologically challenging and computationally inefficient. This necessitates a systematic and implementable methodology for microdosimetric simulation and analysis. PURPOSE: This study aimed to establish a quantitative MC simulation framework for TAT microdosimetry, in which heterogeneous conditions are analytically processed and Type A standard uncertainty of derived microdosimetric quantities can be estimated.

methods(1) Elementary-source events were defined under arbitrary microscopic conditions, and the raw moments of single-event microdosimetric quantities scored via MC simulation were identified for each event. The heterogeneous microdosimetric environments were modeled as weighted mixtures of elementary events. (2) Analytical error propagation was derived to explicitly quantify the standard error (SE) of mixture quantities. This enables, for the first time, a trace-back mechanism to identify error-dominating source components for optimized resource allocation. (3) A long-range radiation correction for

resultsA Geant4-based application implemented the framework in heterogeneous microscopic models. The validation against repeated direct sampling demonstrated consistency between the mixture framework and conventional repeated direct simulation. Subsequently, the MC SE of single-event dose-mean specific energy was adopted as the convergence criterion for simulation. Long-range radiation effects were effectively compensated, relaxing spatial-extent requirements for TAT MC geometries. The source-mixture scheme allowed reuse of elementary microdosimetric data, supporting efficient factor analysis for diverse heterogeneous conditions. Coupled with cell-line parameters and the non-Poisson-corrected microdosimetric kinetic model, the analytic results yielded dose-response characteristics consistent with prior studies of TAT.

conclusionsThe framework enables trace-back variance analysis and microdosimetry-compatible variance reduction. This enables precision-controlled MC microdosimetry in TAT, and supports flexible analysis of heterogeneity factors and reliable microdosimetric assessment.