{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,18]],"date-time":"2026-09-18T03:02:31Z","timestamp":1789700551494,"version":"4.0.1"},"reference-count":34,"publisher":"Wiley","issue":"9","license":[{"start":{"date-parts":[[2026,8,24]],"date-time":"2026-08-24T00:00:00Z","timestamp":1787529600000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"},{"start":{"date-parts":[[2026,8,24]],"date-time":"2026-08-24T00:00:00Z","timestamp":1787529600000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/doi.wiley.com\/10.1002\/tdm_license_1.1"}],"funder":[{"DOI":"10.13039\/501100021692","name":"LabEx PRIMES","doi-asserted-by":"publisher","award":["ANR\u201011\u2010LABX\u20100063"],"award-info":[{"award-number":["ANR\u201011\u2010LABX\u20100063"]}],"id":[{"id":"10.13039\/501100021692","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["aapm.onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["J Applied Clin Med Phys"],"published-print":{"date-parts":[[2026,9]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:sec>\n                    <jats:title>Background<\/jats:title>\n                    <jats:p>Magnetic resonance imaging (MRI) is commonly used for head\u2010and\u2010neck (H&amp;N) delineation in radiotherapy (RT) owing to the lack of contrast in computed tomography (CT) images. MRI\u2010based dosimetry is not yet fully developed for the H&amp;N area due to the inter\u2010patient variability and the difficulty of accurately quantifying cortical bone based on MRI measure.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Purpose<\/jats:title>\n                    <jats:p>Despite the difficulty of cortical bone segmentation with nearby air area, most papers in the literature show dosimetry results very close to the reference CT scan dosimetry. This study evaluated the impact of bone segmentation on dosimetry.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>A home\u2010made phantom was used to evaluate the Hounsfield unit (HU) values of different tissue at diverse scanner energies. Different dosimetry plans were considered and compared with the reference CT\u2010based RT plan used for the treatment: CT images with cortical bone voxels assigned to the density of water and three based on MR images using a density assignment (DA) method for synthetic CT (sCT) generation with various bone attribution. Images from 24 patients were compared using mean absolute error (MAE). The generated dosimetry parameters were compared on the basis of dose\u2013volume histogram values and 3%\/3\u00a0mm gamma pass rates.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>Among the sCT, the best MAE were found for the DA sCT without bone. The mean of the median dose difference for the planning tumor volume (PTV) was less than 2% for all sCT. Mean gamma pass rate for the MR\u2010based sCTs were comparable.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusions<\/jats:title>\n                    <jats:p>The DA of the bone can be of interest if correctly segmented, but in the absence of certainty, an overestimation will lead to significant errors while an underestimation gives results close to the reference. The relevance of very precise sCT can be questioned if it requires too many resources and overlooks patients with artifacts.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1002\/acm2.70722","type":"journal-article","created":{"date-parts":[[2026,8,25]],"date-time":"2026-08-25T05:12:46Z","timestamp":1787634766000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["How bone mis\u2010segmentation affects MRI\u2010based sCT dosimetry in head and neck radiotherapy: A CT\u2010referenced study"],"prefix":"10.1002","volume":"27","author":[{"given":"Laura","family":"Sayaque","sequence":"first","affiliation":[{"name":"INSA\u2010Lyon, Universit\u00e9 Lyon\u00a01 CNRS Inserm CREATIS UMR5220 U1294 Villeurbanne France"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0005-1366-5372","authenticated-orcid":false,"given":"Nils","family":"Tanneau","sequence":"additional","affiliation":[{"name":"INSA\u2010Lyon, Universit\u00e9 Lyon\u00a01 CNRS Inserm CREATIS UMR5220 U1294 Villeurbanne France"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Charl\u00e8ne","family":"Bouyer","sequence":"additional","affiliation":[{"name":"Department of medical physics Centre de lutte contre le cancer L\u00e9on B\u00e9rard  Lyon France"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3408-4156","authenticated-orcid":false,"given":"Benjamin","family":"Leporq","sequence":"additional","affiliation":[{"name":"INSA\u2010Lyon, Universit\u00e9 Lyon\u00a01 CNRS Inserm CREATIS UMR5220 U1294 Villeurbanne France"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Oliver","family":"Hamelin","sequence":"additional","affiliation":[{"name":"Department of radiology Centre de lutte contre le cancer L\u00e9on B\u00e9rard  Lyon France"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9643-5230","authenticated-orcid":false,"given":"Frank","family":"Pilleul","sequence":"additional","affiliation":[{"name":"INSA\u2010Lyon, Universit\u00e9 Lyon\u00a01 CNRS Inserm CREATIS UMR5220 U1294 Villeurbanne France"},{"name":"Department of radiology Centre de lutte contre le cancer L\u00e9on B\u00e9rard  Lyon France"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Vincent","family":"Gregoire","sequence":"additional","affiliation":[{"name":"Department of radiotherapy Centre de lutte contre le cancer L\u00e9on B\u00e9rard  Lyon France"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4516-4565","authenticated-orcid":false,"given":"Olivier","family":"Beuf","sequence":"additional","affiliation":[{"name":"INSA\u2010Lyon, Universit\u00e9 Lyon\u00a01 CNRS Inserm CREATIS UMR5220 U1294 Villeurbanne France"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"311","published-online":{"date-parts":[[2026,8,24]]},"reference":[{"key":"e_1_2_11_2_1","doi-asserted-by":"publisher","DOI":"10.4103\/0971\u20106203.44472"},{"key":"e_1_2_11_3_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.radonc.2010.01s.009"},{"key":"e_1_2_11_4_1","doi-asserted-by":"publisher","DOI":"10.1120\/jacmp.v12i4.3522"},{"key":"e_1_2_11_5_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.ejmp.2017.02.017"},{"key":"e_1_2_11_6_1","doi-asserted-by":"publisher","DOI":"10.1002\/mp.13663"},{"key":"e_1_2_11_7_1","doi-asserted-by":"publisher","DOI":"10.1120\/jacmp.v15i5.4851"},{"key":"e_1_2_11_8_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.ejmp.2025.104974"},{"key":"e_1_2_11_9_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.phro.2020.12.007"},{"key":"e_1_2_11_10_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.radonc.2023.110052"},{"key":"e_1_2_11_11_1","doi-asserted-by":"publisher","DOI":"10.1186\/s13014\u2010024\u201002429\u20102"},{"key":"e_1_2_11_12_1","doi-asserted-by":"publisher","DOI":"10.3389\/fonc.2021.746059"},{"key":"e_1_2_11_13_1","unstructured":"National Bureau of Standards handbook no.85 1964.Hathi trust. 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