{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,22]],"date-time":"2026-06-22T23:11:56Z","timestamp":1782169916351,"version":"3.54.5"},"reference-count":16,"publisher":"Wiley","issue":"7","license":[{"start":{"date-parts":[[2025,7,13]],"date-time":"2025-07-13T00:00:00Z","timestamp":1752364800000},"content-version":"vor","delay-in-days":12,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"},{"start":{"date-parts":[[2025,7,1]],"date-time":"2025-07-01T00:00:00Z","timestamp":1751328000000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/doi.wiley.com\/10.1002\/tdm_license_1.1"}],"content-domain":{"domain":["aapm.onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["J Applied Clin Med Phys"],"published-print":{"date-parts":[[2025,7]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:sec>\n                    <jats:title>Purpose<\/jats:title>\n                    <jats:p>Head\u2010and\u2010neck (HN) contouring presents significant challenges due to the complex anatomy of the region and the proximity of organs\u2010at\u2010risk (OARs) to the target. Manual contouring is time\u2010consuming, labor\u2010intensive, and prone to inter\u2010 and intra\u2010observer variability. Additionally, contours delineated prior to treatment may not accurately reflect the patient's anatomy over the extended treatment course. This study explores the feasibility of using auto\u2010generated OAR contours in HN planning.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>\n                      A retrospective study was conducted on 20 patients, each with a planning CT and 35 CBCT images. OARs were manually delineated and automatically generated using atlas\u2010based segmentation algorithms on planning CTs. Treatment plans were created via a novel two\u2010step optimization process, incorporating a knowledge\u2010based planning solution for both auto\u2010generated (aOAR\u2010plan) and manual OARs (mOAR\u2010plan). The accuracy of auto\u2010generated contours was quantified using the overlap index (\n                      <jats:italic>OI<\/jats:italic>\n                      ) and dose similarity coefficient (\n                      <jats:italic>DSC<\/jats:italic>\n                      ). Planning dose comparisons were performed between aOAR\u2010 and mOAR\u2010plans. Additionally, planning doses were transferred from CT to CBCTs based on clinical shifts, and contour\u2010based deformable registration was employed to calculate cumulative doses. Cumulative dose evaluations were performed for serial organs and parallel organs that can be fully imaged within the CBCT field.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>\n                      For OARs located farther from the target, even though atlas\u2010based segmentation could not accurately reproduce patient anatomy, excellent agreement in planning doses was observed between the aOAR\u2010 and mOAR\u2010plans. The average\n                      <jats:italic>OI<\/jats:italic>\n                      \/\n                      <jats:italic>DSC<\/jats:italic>\n                      between manual and auto\u2010generated contours were 85.0%\u00a0\u00b1\u00a05.4%\/87.4%\u00a0\u00b1\u00a02.6% for the larynx, 76.0%\u00a0\u00b1\u00a09.3%\/77.0%\u00a0\u00b1\u00a05.8% for the pharynx, 89.9%\u00a0\u00b1\u00a04.0%\/87.8%\u00a0\u00b1\u00a02.5% for the oral cavity, 81.5%\u00a0\u00b1\u00a010.5%\/78.2%\u00a0\u00b1\u00a05.9% and 83.2%\u00a0\u00b1\u00a010.6%\/77.8%\u00a0\u00b1\u00a07.5% for the left and right parotid, respectively. The cumulative dose differences for OARs between aOAR\u2010 and mOAR\u2010plans were within 2 Gy for 90% of patients studied.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusion<\/jats:title>\n                    <jats:p>Automated\u2010contouring tools offer improvement in contour consistency, provide acceptable doses compared with manually drawn contours in HN radiotherapy.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1002\/acm2.70150","type":"journal-article","created":{"date-parts":[[2025,7,14]],"date-time":"2025-07-14T06:25:16Z","timestamp":1752474316000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["Clinical feasibility of atlas\u2010based auto\u2010segmentation for organ\u2010at\u2010risk contouring in head\u2010and\u2010neck radiotherapy"],"prefix":"10.1002","volume":"26","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-8939-7080","authenticated-orcid":false,"given":"Han","family":"Liu","sequence":"first","affiliation":[{"name":"Department of Radiation Oncology Cone Health Cancer Center  Greensboro North Carolina USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Benjamin","family":"Sintay","sequence":"additional","affiliation":[{"name":"Department of Radiation Oncology Cone Health Cancer Center  Greensboro North Carolina USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"David","family":"Wiant","sequence":"additional","affiliation":[{"name":"Department of Radiation Oncology Cone Health Cancer Center  Greensboro North Carolina USA"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"311","published-online":{"date-parts":[[2025,7,13]]},"reference":[{"key":"e_1_2_10_2_1","doi-asserted-by":"publisher","DOI":"10.1016\/S0140-6736(21)01550-6"},{"key":"e_1_2_10_3_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.coms.2014.01.001"},{"key":"e_1_2_10_4_1","doi-asserted-by":"publisher","DOI":"10.3322\/caac.21293"},{"key":"e_1_2_10_5_1","doi-asserted-by":"publisher","DOI":"10.1016\/S1470-2045(06)70580-0"},{"key":"e_1_2_10_6_1","doi-asserted-by":"publisher","DOI":"10.1177\/11795549211036898"},{"key":"e_1_2_10_7_1","doi-asserted-by":"publisher","DOI":"10.3857\/roj.2020.00213"},{"key":"e_1_2_10_8_1","doi-asserted-by":"publisher","DOI":"10.1053\/j.seminoncol.2008.03.003"},{"key":"e_1_2_10_9_1","doi-asserted-by":"publisher","DOI":"10.1118\/1.2818738"},{"key":"e_1_2_10_10_1","doi-asserted-by":"publisher","DOI":"10.1118\/1.4947547"},{"key":"e_1_2_10_11_1","first-page":"267","volume-title":"Quality and Safety in Radiation Oncology: Implementing Tools and Best Practices for Patients, Providers, and Payers","author":"Ezzel G","year":"2017"},{"key":"e_1_2_10_12_1","volume-title":"Radiotherapy in cancer care: facing the global challenge","author":"Rosenblatt E","year":"2017"},{"key":"e_1_2_10_13_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.meddos.2019.07.002"},{"key":"e_1_2_10_14_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.ijrobp.2018.11.048"},{"key":"e_1_2_10_15_1","first-page":"1","article-title":"Interobserver variability in organ at risk delineation in head and neck cancer","volume":"16","author":"Veen J","year":"2021","journal-title":"Radiat Oncol"},{"key":"e_1_2_10_16_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.radonc.2018.03.012"},{"key":"e_1_2_10_17_1","doi-asserted-by":"publisher","DOI":"10.1002\/acm2.13939"}],"container-title":["Journal of Applied Clinical Medical 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