{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,2]],"date-time":"2026-09-02T17:05:59Z","timestamp":1788368759407,"version":"build-2803163510"},"reference-count":40,"publisher":"IOP Publishing","issue":"6","license":[{"start":{"date-parts":[[2025,3,5]],"date-time":"2025-03-05T00:00:00Z","timestamp":1741132800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/iopscience.iop.org\/page\/copyright"},{"start":{"date-parts":[[2025,3,5]],"date-time":"2025-03-05T00:00:00Z","timestamp":1741132800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/iopscience.iop.org\/info\/page\/text-and-data-mining"}],"funder":[{"DOI":"10.13039\/501100010978","name":"Wallonie-Bruxelles International","doi-asserted-by":"crossref","award":["a financial support of Wallonia"],"award-info":[{"award-number":["a financial support of Wallonia"]}],"id":[{"id":"10.13039\/501100010978","id-type":"DOI","asserted-by":"crossref"}]}],"content-domain":{"domain":["iopscience.iop.org"],"crossmark-restriction":false},"short-container-title":["Phys. Med. Biol."],"published-print":{"date-parts":[[2025,3,16]]},"abstract":"<jats:title>Abstract<\/jats:title>\n               <jats:p>\n                  <jats:italic>Objective.<\/jats:italic> Achieving FLASH dose rate with pencil beam scanning intensity modulated proton therapy is challenging. However, utilizing a single energy layer with a ridge filter (RF) can maintain dose rate and conformality. Yet, changes in patient anatomy over the treatment course can render the RF obsolete. Unfortunately, creating a new RF is time-consuming, thus, incompatible with online adaptation. To address this, we propose to re-optimize the spot weights while keeping the same initial RF. <jats:italic>Approach.<\/jats:italic> Data from six head and neck cancer patients with a repeated computed tomography (CT<jats:sub>2<\/jats:sub>) were used. FLASH treatment plans were generated with three methods on CT<jats:sub>2<\/jats:sub>: \u2018full-adaptation\u2019 (FA), optimized from scratch with a new RF; \u2018spot-adaptation only\u2019 (SAO), re-using initial RF but adjusting plan spot weights; and \u2018no adaptation\u2019 (NoA) where the dose from initial plans on initial CT (CT<jats:sub>1<\/jats:sub>) was recomputed on CT<jats:sub>2<\/jats:sub>. The prescribed dose per fraction was 9 Gy. Different beam angles were tested for each CT<jats:sub>2<\/jats:sub> (1 beam per fraction). The FA, SAO and NoA plans were then compared on CT<jats:sub>2<\/jats:sub>. <jats:italic>Main results.<\/jats:italic> Fractions with SAO showed a median decrease of 0.05 Gy for <jats:italic>D<\/jats:italic>98% and a median increase of 0.03 Gy for <jats:italic>D<\/jats:italic>2% of CTV when compared to their homologous FA plans on nominal case. Median conformity number decreased by 0.03. Median max dose to spinal cord increased by 0.09 Gy. The largest median increase in mean dose to organs was 0.03 Gy to the mandible. The largest observed median difference in organs receiving a minimal dose rate of 40 Gy s<jats:sup>\u22121<\/jats:sup> was 0.5% for the mandible. Up to 16 of the 20 evaluated SAO fractions were thus deemed clinically acceptable, with up to 8 NoA plans already acceptable before adaptation. <jats:italic>Significance.<\/jats:italic> Proposed SAO workflow showed that for most of our evaluated plans, daily reprinting of RF was not necessary.<\/jats:p>","DOI":"10.1088\/1361-6560\/adb9b2","type":"journal-article","created":{"date-parts":[[2025,2,24]],"date-time":"2025-02-24T22:52:32Z","timestamp":1740437552000},"page":"065005","update-policy":"https:\/\/doi.org\/10.1088\/crossmark-policy","source":"Crossref","is-referenced-by-count":2,"title":["Anticipating potential bottlenecks in adaptive proton FLASH therapy: a ridge filter reuse strategy"],"prefix":"10.1088","volume":"70","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-9499-5904","authenticated-orcid":true,"given":"Benjamin","family":"Roberfroid","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9697-5440","authenticated-orcid":false,"given":"Macarena S","family":"Chocan Vera","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4034-7896","authenticated-orcid":true,"given":"Camille","family":"Draguet","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5218-759X","authenticated-orcid":false,"given":"John A","family":"Lee","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9485-3076","authenticated-orcid":false,"given":"Ana M","family":"Barrag\u00e1n-Montero","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9764-546X","authenticated-orcid":true,"given":"Edmond","family":"Sterpin","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"266","published-online":{"date-parts":[[2025,3,5]]},"reference":[{"key":"pmbadb9b2bib1","doi-asserted-by":"publisher","first-page":"242","DOI":"10.1016\/j.ejmp.2021.04.016","article-title":"Artificial intelligence and machine learning for medical imaging: a technology review","volume":"83","author":"Barragan-Montero","year":"2021","journal-title":"Phys. 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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":"2024-11-29","name":"date_received","label":"Date Received","group":{"name":"publication_dates","label":"Publication dates"}},{"value":"2025-02-24","name":"date_accepted","label":"Date Accepted","group":{"name":"publication_dates","label":"Publication dates"}},{"value":"2025-03-05","name":"date_epub","label":"Online publication date","group":{"name":"publication_dates","label":"Publication dates"}}]}}