Fast full patient and radioisotope Monte Carlo simulations of targeted radionuclide therapy: introducing egs_mird

TL;DR

The paper introduces egs_mird, a new Monte Carlo simulation tool built in EGSnrc for fast, detailed, patient-specific radionuclide therapy dose calculations using clinical imaging data.

Contribution

It presents the design, validation, and application of egs_mird, enabling rapid and realistic TRT dose simulations directly from clinical CT and PET images.

Findings

Good agreement with literature S-value kernels

Fano test satisfied to 0.1%

Simulations completed in under 15 minutes

Abstract

BACKGROUND: Targeted Radionuclide Therapy (TRT) is a fast-growing field garnering much interest, however, dosimetry calculation techniques remain relatively simple. PURPOSE: To introduce egs_mird, a new Monte Carlo application built in EGSnrc which allows users to model full patient tissue and density (using clinical CT images) and radionuclide distribution (using clinical PET images) for fast and detailed TRT dose calculation. METHODS: The novel application egs_mird is introduced, including its structure and variation reduction approaches. A new egs++ source class egs_internal_source and a modified version of egs_radionuclide_source are described. The new code is compared to other MC calculations of S-value kernels, along with self-validation using the electron Fano test. Full patient prostate 177Lu TRT cancer treatment simulations are performed using a single set of patient DICOM CT and [18F]-DCFPyL PET data. RESULTS: Good agreement is found between S-value kernels calculated using egs_mird and those found in the literature. The Fano test is satisfied to 0.1%. Patient prostate, rectum, bone marrow, and bladder dose volume histogram results did not vary significantly when using the track-length estimator and not modelling electron transport, modelling bone marrow explicitly (rather than using generic tissue compositions), and reducing activity to voxels containing partial or full calcifications to half or none, respectively. Simulations using the track-length estimator can be completed in under 15 minutes. CONCLUSION: This work shows egs mird to be a reliable MC code for computing TRT doses as realistically as the patient CT and PET data allow, supporting the use of egs mird for dose calculations in TRT.