{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,7,8]],"date-time":"2025-07-08T09:10:07Z","timestamp":1751965807828,"version":"3.41.2"},"reference-count":19,"publisher":"IOP Publishing","issue":"14","license":[{"start":{"date-parts":[[2025,7,8]],"date-time":"2025-07-08T00:00:00Z","timestamp":1751932800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/iopscience.iop.org\/page\/copyright"},{"start":{"date-parts":[[2025,7,8]],"date-time":"2025-07-08T00:00:00Z","timestamp":1751932800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/iopscience.iop.org\/info\/page\/text-and-data-mining"}],"content-domain":{"domain":["iopscience.iop.org"],"crossmark-restriction":false},"short-container-title":["Phys. Med. Biol."],"published-print":{"date-parts":[[2025,7,20]]},"abstract":"<jats:title>Abstract<\/jats:title>\n               <jats:p>Monte Carlo simulations offer the highest accuracy for calculating dose distributions in radiation therapy (RT). Precise modeling of the Elekta Synergy linear accelerator (LINAC) with Agility multi-leaf collimator (MLC) is essential for accurate dose verification. The 6 MV flattened (FF) and FF-free (FFF) Elekta Synergy LINAC with Agility MLC was modeled using TOPASMC, providing an additional verification tool for patient dose distributions. An initial model was developed based on vendor specifications. The 160-leaf MLC was constructed from a computer-aided design mesh of a single leaf. Proprietary code was created to manage the placement and movement of the field-defining diaphragms. Using measurements of depth doses, dose profiles, and output factors in a water phantom for energies of 6 MV and 6 MV FFF across field sizes from 1 \u00d7 1 cm<jats:sup>2<\/jats:sup> to 36 \u00d7 36 cm<jats:sup>2<\/jats:sup>, we adjusted the incident electron beam energy distribution, flattening filter geometry, jaw and MLC leaf geometry, and leaf-bank rotation. A DICOM interface between the treatment planning system and TOPAS was developed, and patient plans of increasing complexity were calculated using the model. The local gamma index pass rate (1%\/1 mm for 1D, 2%\/2\u202fmm for 3D) was used to evaluate the agreement between reference and simulation. Over 99% of depth dose points and 92% of dose profile points passed the gamma criterion for all field sizes. The model accurately replicated the leaf-tip and tongue-and-groove effects. Calculated RT plans showed a gamma agreement between 87% and 99%, depending on the delivery technique. The developed model accurately replicates measured dose distributions and can be used to externally validate treatment plans, serving as an additional tool for secondary dose calculations.<\/jats:p>","DOI":"10.1088\/1361-6560\/ade92c","type":"journal-article","created":{"date-parts":[[2025,6,27]],"date-time":"2025-06-27T22:53:02Z","timestamp":1751064782000},"page":"14NT01","update-policy":"https:\/\/doi.org\/10.1088\/crossmark-policy","source":"Crossref","is-referenced-by-count":0,"title":["Monte Carlo modeling of the Elekta Synergy linear accelerator platform with Agility MLC using TOPASMC for secondary dose calculation"],"prefix":"10.1088","volume":"70","author":[{"ORCID":"https:\/\/orcid.org\/0009-0004-3790-3278","authenticated-orcid":true,"given":"Sebastian","family":"Sch\u00e4fer","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Michael","family":"Schaks","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Martin","family":"Janich","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Dirk","family":"Vordermark","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"266","published-online":{"date-parts":[[2025,7,8]]},"reference":[{"key":"pmbade92cbib1","doi-asserted-by":"publisher","DOI":"10.1016\/j.radphyschem.2023.111433","article-title":"A Monte Carlo model of an agility head for a 6 MV Elekta photon beam","volume":"216","author":"Al-Saleh","year":"2024","journal-title":"Radiat. 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All rights, including for text and data mining, AI training, and similar technologies, are reserved.","name":"copyright_information","label":"Copyright Information"},{"value":"2025-03-04","name":"date_received","label":"Date Received","group":{"name":"publication_dates","label":"Publication dates"}},{"value":"2025-06-27","name":"date_accepted","label":"Date Accepted","group":{"name":"publication_dates","label":"Publication dates"}},{"value":"2025-07-08","name":"date_epub","label":"Online publication date","group":{"name":"publication_dates","label":"Publication dates"}}]}}