{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,26]],"date-time":"2026-09-26T03:53:14Z","timestamp":1790394794202,"version":"4.1.0"},"reference-count":28,"publisher":"Wiley","issue":"9","license":[{"start":{"date-parts":[[2022,7,15]],"date-time":"2022-07-15T00:00:00Z","timestamp":1657843200000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/onlinelibrary.wiley.com\/termsAndConditions#vor"}],"funder":[{"DOI":"10.13039\/100013020","name":"Compute Canada","doi-asserted-by":"publisher","id":[{"id":"10.13039\/100013020","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["aapm.onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["Medical Physics"],"published-print":{"date-parts":[[2022,9]]},"abstract":"<jats:title>Abstract<\/jats:title><jats:sec><jats:title>Background<\/jats:title><jats:p>Targeted radionuclide therapy (TRT) is a fast\u2010growing field garnering much interest, with several clinical trials currently underway, that has a steady increase in development of treatment techniques. Unfortunately, within the field and many clinical trials, the dosimetry calculation techniques used remain relatively simple, often using a mix of S\u2010value calculations and kernel\u00a0convolutions.<\/jats:p><\/jats:sec><jats:sec><jats:title>Purpose<\/jats:title><jats:p>The common TRT calculation techniques, although very quick, can often ignore important aspects of patient anatomy and radionuclide distribution, as well as the interplay there\u2010in. This paper introduces egs_mird, a new Monte Carlo (MC) 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 dose TRT calculation.<\/jats:p><\/jats:sec><jats:sec><jats:title>Methods<\/jats:title><jats:p>The novel application egs_mird is introduced along with a general outline of the structure of egs_mird simulations. The general structure of the code, and the track\u2010length (TL) estimator scoring implementation for variance reduction, is described. A new egs++ source class egs_internal_source, created to allow detailed patient\u2010wide source distribution, and a modified version of egs_radionuclide_source, changed to be able to work with egs_internal_source, are also described. The new code is compared to other MC calculations of S\u2010values kernels of <jats:sup>131<\/jats:sup>I, <jats:sup>90<\/jats:sup>Y, and <jats:sup>177<\/jats:sup>Lu in the literature, along with further self\u2010validation using a histogram variant of the electron Fano test. Several full patient prostate <jats:sup>177<\/jats:sup>Lu TRT prostate cancer treatment simulations are performed using a single set of patient DICOM CT and [<jats:sup>18<\/jats:sup>F]\u2010DCFPyL PET\u00a0data.<\/jats:p><\/jats:sec><jats:sec><jats:title>Results<\/jats:title><jats:p>Good agreement is found between S\u2010value kernels calculated using egs_mird with egs_internal_source and those found in the literature. Calculating 1000 doses (individual voxel uncertainties of \u223c0.05%) in a voxel grid Fano test for monoenergetic 500\u00a0keV electrons and <jats:sup>177<\/jats:sup>Lu electrons results in 94% and 99% of the doses being within 0.1% of the expected dose, respectively. For a hypothetical <jats:sup>177<\/jats:sup>Lu treatment, patient prostate, rectum, bone marrow, and bladder dose volume histograms (DVHs) results did not vary significantly when using the TL estimator and not modeling electron transport, modeling bone marrow explicitly (rather than using generic tissue compositions), and reducing activity to voxels containing partial or full calcifications to half or none, respectively. Dose profiles through different regions demonstrate there are some differences with model choices not seen in the DVH. Simulations using the TL estimator can be completed in under 15 min (\u223c30 min when using standard interaction scoring).<\/jats:p><\/jats:sec><jats:sec><jats:title>Conclusion<\/jats:title><jats:p>This work shows egs_mird to be a reliable MC code for computing TRT doses as realistically as the patient Computed Tomography (CT) and Positron Emission Tomography (PET) data allow. Furthermore, the code can compute doses to sub\u20101% uncertainty within 15 min, with little to no optimization. Thus, this work supports the use of egs_mird for dose calculations in\u00a0TRT.<\/jats:p><\/jats:sec>","DOI":"10.1002\/mp.15786","type":"journal-article","created":{"date-parts":[[2022,6,2]],"date-time":"2022-06-02T02:09:26Z","timestamp":1654135766000},"page":"6137-6149","update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":3,"title":["Fast beta\u2010emitter Monte Carlo simulations and full patient dose calculations of targeted radionuclide therapy: introducing egs_mird"],"prefix":"10.1002","volume":"49","author":[{"given":"Martin P.","family":"Martinov","sequence":"first","affiliation":[{"name":"Robarts Research Institute London Ontario Canada"},{"name":"Lawson Health Research Institute London Ontario Canada"},{"name":"Carleton Laboratory for Radiotherapy Physics Department of Physics Carleton University Ottawa Ontario Canada"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Chidera","family":"Opara","sequence":"additional","affiliation":[{"name":"Robarts Research Institute London Ontario Canada"},{"name":"Lawson Health Research Institute London Ontario Canada"},{"name":"Carleton Laboratory for Radiotherapy Physics Department of Physics Carleton University Ottawa Ontario Canada"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Rowan M.","family":"Thomson","sequence":"additional","affiliation":[{"name":"Robarts Research Institute London Ontario Canada"},{"name":"Lawson Health Research Institute London Ontario Canada"},{"name":"Carleton Laboratory for Radiotherapy Physics Department of Physics Carleton University Ottawa Ontario Canada"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ting\u2010Yim","family":"Lee","sequence":"additional","affiliation":[{"name":"Robarts Research Institute London Ontario Canada"},{"name":"Lawson Health Research Institute London Ontario Canada"},{"name":"Carleton Laboratory for Radiotherapy Physics Department of Physics Carleton University Ottawa Ontario Canada"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"311","published-online":{"date-parts":[[2022,7,15]]},"reference":[{"key":"e_1_2_8_2_1","doi-asserted-by":"publisher","DOI":"10.1002\/mp.14375"},{"key":"e_1_2_8_3_1","doi-asserted-by":"publisher","DOI":"10.1118\/1.598917"},{"key":"e_1_2_8_4_1","doi-asserted-by":"publisher","DOI":"10.2967\/jnumed.119.236414"},{"key":"e_1_2_8_5_1","doi-asserted-by":"publisher","DOI":"10.1016\/S0140-6736(21)00237-3"},{"key":"e_1_2_8_6_1","doi-asserted-by":"publisher","DOI":"10.2967\/jnumed.118.219352"},{"key":"e_1_2_8_7_1","doi-asserted-by":"publisher","DOI":"10.1118\/1.4871617"},{"key":"e_1_2_8_8_1","doi-asserted-by":"publisher","DOI":"10.1186\/s40658-016-0172-1"},{"key":"e_1_2_8_9_1","volume-title":"Therapeutic Nuclear Medicine","author":"Baum RP","year":"2016"},{"key":"e_1_2_8_10_1","unstructured":"KawrakowI.egspp: the EGSnrc C++ class library(Technical Report PIRS\u2013899).Ottawa Canada:National Research Council Canada;2005."},{"key":"e_1_2_8_11_1","doi-asserted-by":"publisher","DOI":"10.1088\/0031-9155\/61\/16\/5993"},{"key":"e_1_2_8_12_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.apradiso.2017.10.010"},{"key":"e_1_2_8_13_1","unstructured":"ICRU.Photon electron photon and neutron interaction data for body tissues(ICRU Report 46) ICRU;1992."},{"key":"e_1_2_8_14_1","doi-asserted-by":"crossref","unstructured":"SchneiderW BortfeldT SchlegelW.Influence of tissue composition on the results of Monte Carlo simulations for patient dose calculations. In:The Use of Computers in Radiation Therapy.Springer;2000:443\u2010445.","DOI":"10.1007\/978-3-642-59758-9_167"},{"key":"e_1_2_8_15_1","doi-asserted-by":"publisher","DOI":"10.1118\/1.1646040"},{"key":"e_1_2_8_16_1","doi-asserted-by":"crossref","unstructured":"CristyM EckermanK.Specific absorbed fractions of energy at various ages from internal photon sources: 1. Methods (Technical Report). Oak Ridge National Lab;1987.","DOI":"10.2172\/6233735"},{"key":"e_1_2_8_17_1","doi-asserted-by":"publisher","DOI":"10.1118\/1.596069"},{"key":"e_1_2_8_18_1","doi-asserted-by":"publisher","DOI":"10.1088\/0031-9155\/61\/23\/8214"},{"key":"e_1_2_8_19_1","doi-asserted-by":"publisher","DOI":"10.2307\/2683739"},{"key":"e_1_2_8_20_1","doi-asserted-by":"publisher","DOI":"10.1002\/mp.14172"},{"key":"e_1_2_8_21_1","doi-asserted-by":"publisher","DOI":"10.1088\/0031-9155\/60\/17\/6639"},{"key":"e_1_2_8_22_1","doi-asserted-by":"publisher","DOI":"10.1118\/1.3103401"},{"key":"e_1_2_8_23_1","doi-asserted-by":"publisher","DOI":"10.1088\/0031-9155\/60\/17\/6685"},{"key":"e_1_2_8_24_1","first-page":"11S","article-title":"MIRD Pamphlet No. 17: the dosimetry of nonuniform activity distributions\u2010radionuclide S values at the voxel level","volume":"40","author":"Bolch WE","year":"1999","journal-title":"J Nucl Med"},{"key":"e_1_2_8_25_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.ijrobp.2016.11.025"},{"key":"e_1_2_8_26_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.brachy.2019.06.007"},{"key":"e_1_2_8_27_1","doi-asserted-by":"publisher","DOI":"10.1118\/1.598918"},{"key":"e_1_2_8_28_1","first-page":"69","volume-title":"Recent Developments in Accurate Radiation Dosimetry, Proc. of an Int'l Workshop","author":"Seuntjens JP","year":"2002"},{"key":"e_1_2_8_29_1","unstructured":"MiksysN.Advancements in Monte Carlo Dose Calculations for Prostate and Breast Permanent Implant Brachytherapy. PhD Thesis Carleton University;2016."}],"container-title":["Medical Physics"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/onlinelibrary.wiley.com\/doi\/pdf\/10.1002\/mp.15786","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/onlinelibrary.wiley.com\/doi\/full-xml\/10.1002\/mp.15786","content-type":"application\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/aapm.onlinelibrary.wiley.com\/doi\/pdf\/10.1002\/mp.15786","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,10,19]],"date-time":"2023-10-19T16:10:29Z","timestamp":1697731829000},"score":1,"resource":{"primary":{"URL":"https:\/\/aapm.onlinelibrary.wiley.com\/doi\/10.1002\/mp.15786"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,7,15]]},"references-count":28,"journal-issue":{"issue":"9","published-print":{"date-parts":[[2022,9]]}},"alternative-id":["10.1002\/mp.15786"],"URL":"https:\/\/doi.org\/10.1002\/mp.15786","archive":["Portico"],"relation":{},"ISSN":["0094-2405","2473-4209"],"issn-type":[{"value":"0094-2405","type":"print"},{"value":"2473-4209","type":"electronic"}],"subject":[],"published":{"date-parts":[[2022,7,15]]},"assertion":[{"value":"2021-12-08","order":0,"name":"received","label":"Received","group":{"name":"publication_history","label":"Publication History"}},{"value":"2022-05-17","order":1,"name":"accepted","label":"Accepted","group":{"name":"publication_history","label":"Publication History"}},{"value":"2022-07-15","order":2,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}