{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,20]],"date-time":"2026-09-20T12:41:23Z","timestamp":1789908083088,"version":"4.0.1"},"reference-count":40,"publisher":"Wiley","issue":"8","license":[{"start":{"date-parts":[[2018,7,3]],"date-time":"2018-07-03T00:00:00Z","timestamp":1530576000000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/onlinelibrary.wiley.com\/termsAndConditions#vor"}],"funder":[{"DOI":"10.13039\/100007210","name":"Varian Medical Systems","doi-asserted-by":"publisher","id":[{"id":"10.13039\/100007210","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":[[2018,8]]},"abstract":"<jats:sec><jats:title>Purpose<\/jats:title><jats:p>To present a new adaptive radiotherapy (<jats:styled-content style=\"fixed-case\">ART<\/jats:styled-content>) method based on relative gamma analysis and patient classification for the identification of anatomical changes that induce a sufficient dosimetric impact to affect the treatment delivery and require complete replanning.<\/jats:p><\/jats:sec><jats:sec><jats:title>Methods<\/jats:title><jats:p>This retrospective study includes 55 patients treated for a head and neck cancer with <jats:styled-content style=\"fixed-case\">IMRT<\/jats:styled-content>,<jats:styled-content style=\"fixed-case\"> VMAT<\/jats:styled-content>, or 3D conformal <jats:styled-content style=\"fixed-case\">RT<\/jats:styled-content>. Electronic Portal Imaging Device images for all treatment fields were acquired daily at every fraction. <jats:styled-content style=\"fixed-case\">CBCT<\/jats:styled-content>s were collected at least once a week. Gamma analysis was performed using the first fraction of the treatment as a reference once validated that it was delivered without error. Gamma analysis parameters (&lt;<jats:italic>\u03b3<\/jats:italic>&gt;, standard deviation and the Top 1% <jats:italic>\u03b3<\/jats:italic>) were used to define categories using statistic from a k\u2010means clustering analysis. From these categories an action threshold was defined and correlated with dosimetric changes. For 23 of 55 patients, the V100% for <jats:styled-content style=\"fixed-case\">PTV<\/jats:styled-content> was computed for both, the planning <jats:styled-content style=\"fixed-case\">CT<\/jats:styled-content> and original contours deformed onto <jats:styled-content style=\"fixed-case\">CBCT<\/jats:styled-content> acquired at the last fraction. These values were then compared with 2D image relative <jats:italic>\u03b3<\/jats:italic>\u2010analysis of <jats:styled-content style=\"fixed-case\">EPID<\/jats:styled-content> images. Sensitivity and specificity of the method for the detection of dosimetric changes were computed.<\/jats:p><\/jats:sec><jats:sec><jats:title>Results<\/jats:title><jats:p>Three categories indicating an increasing level of change with the planned treatment were identified. A threshold was established for which patients were at risk of deviation at &lt;<jats:italic>\u03b3<\/jats:italic>&gt;\u00a0=\u00a00.42. From 23 recomputing plans, it has been confirmed that patients with a strong dosimetric impact were above this threshold, with a specificity of 0.80 and a sensitivity of 0.84.<\/jats:p><\/jats:sec><jats:sec><jats:title>Conclusions<\/jats:title><jats:p>The specificity and the sensitivity value confirmed the performance of the method to detect anatomical changes. The <jats:italic>\u03b3<\/jats:italic>\u2010analysis threshold correlated well with morphological changes that have a relevant dosimetric impact. Analysis of daily <jats:styled-content style=\"fixed-case\">EPID<\/jats:styled-content> images provides a method to identify patients at risk of deviation from their planned treatment and can support an early replanning decision.<\/jats:p><\/jats:sec>","DOI":"10.1002\/mp.13045","type":"journal-article","created":{"date-parts":[[2018,6,13]],"date-time":"2018-06-13T07:43:57Z","timestamp":1528875837000},"page":"3534-3545","update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":18,"title":["Establishing action threshold for change in patient anatomy using <scp>EPID<\/scp> gamma analysis and <scp>PTV<\/scp> coverage for head and neck radiotherapy treatment"],"prefix":"10.1002","volume":"45","author":[{"given":"Oph\u00e9lie","family":"Piron","sequence":"first","affiliation":[{"name":"Department de Radio\u2010oncologie CHU de Quebec 11 C\u00f4te du Palais Quebec QC Canada"},{"name":"Universit\u00e9 Laval 2325 Rue de l'Universit\u00e9 Ville 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