Paper detail

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

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.

preprint2022arXivOpen access

Signal facts

What is known right now

Open access4 authors1 topic

Next steps

Decide what to do with this paper

Use like or dislike for the fast social read. The more specific scholarly feedback stays available below when needed.

Log in to curate

Reading frame

Keep the important context close to the paper

Keep the important signals around this paper in one place: votes, save state, collection context, reviews and the metadata you need before deciding what to do next.

Institutions

Add specific reaction

Move through the context

Research map

Open full explorer

Move through nearby people, institutions, topics and adjacent work without leaving the paper page.

Building this map preview

BZPEER is loading the nearby papers, people, topics and institutions for this page.

Structured reviews

0 review(s)

ContributeLeave structured feedbackUse the review template when you have a concrete strength, concern or method question.Open review form

No structured reviews yet. High-signal critique starts here.

Work discussion

0 comment(s)

DiscussAdd a high-signal commentKeep quick notes, caveats and replication pointers separate from formal reviews.Open comment form

No discussion yet. The first strong comment sets the tone.