  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.
