Efficient Monte Carlo Framework for Microdosimetry In TAT: Microdosimetric Mird Formalism and Split-Tree Recombination Method
Abstract
Purpose
Targeted Alpha Therapy (TAT) requires precise microdosimetry due to heterogeneous source distributions and complex Relative Biological Effectiveness (RBE) modeling. However, Monte Carlo (MC) simulations for microdosimetry suffer from slow convergence and heavy computational burdens, especially for isotopes with long decay chains like 223Ra and 225Ac. Traditional variance reduction techniques often disrupt track-structure integrity, making them unsuitable for microdosimetric statistics. This study aims to develop an efficient MC framework to overcome these bottlenecks.
Methods
Four methodological advancements were implemented: (1) A generalized convergence criterion was established using high-order moments of single-event distributions to quantify MC standard error. (2) A microdosimetric MIRD formalism was developed to decouple source-target geometries, enabling the calculation of compound events from a single base-event database without re-simulation. (3) The Split-Tree Recombination Method (STRM) was developed to preserve the full track-structure integrity, ensuring that simulated microdosimetric spectra remain consistent with true physical distributions by traversing reconstructed split-event trees. (4) A long-range radiation compensation model was created to approximate distant emitters as idealized events, reducing the spatial modeling requirements for large-scale geometries.
Results
Virtual experiments validated the reliability and efficiency of the proposed framework. The microdosimetric MIRD and STRM structurally optimized computational overhead while enabling rigorous standard error estimation for endpoint microdosimetric quantities. Quantitative analysis of micro-heterogeneity using RBE models demonstrated that these methods optimize simulation workflows and provide precision control, enabling detailed assessment of microscopic factors in TAT scenarios.
Conclusion
The proposed framework enables a trace-back mechanism for precision control and targeted data supplementation. STRM extends biasing applications to microdosimetry, while long-range compensation relaxes complex geometry requirements. These tools primarily facilitate refined dosimetry investigations for TAT and lay the foundation for future personalized treatment planning and clinical dosimetry.