{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,11,2]],"date-time":"2026-11-02T07:27:04Z","timestamp":1793604424228,"version":"4.5.0"},"reference-count":30,"publisher":"Elsevier BV","license":[{"start":{"date-parts":[[2022,10,1]],"date-time":"2022-10-01T00:00:00Z","timestamp":1664582400000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/tdm\/userlicense\/1.0\/"},{"start":{"date-parts":[[2022,10,1]],"date-time":"2022-10-01T00:00:00Z","timestamp":1664582400000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/legal\/tdmrep-license"},{"start":{"date-parts":[[2022,11,3]],"date-time":"2022-11-03T00:00:00Z","timestamp":1667433600000},"content-version":"vor","delay-in-days":33,"URL":"http:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0\/"}],"content-domain":{"domain":["phiro.science","elsevier.com","sciencedirect.com"],"crossmark-restriction":true},"short-container-title":["Physics and Imaging in Radiation Oncology"],"published-print":{"date-parts":[[2022,10]]},"DOI":"10.1016\/j.phro.2022.11.003","type":"journal-article","created":{"date-parts":[[2022,11,8]],"date-time":"2022-11-08T02:27:59Z","timestamp":1667874479000},"page":"121-128","update-policy":"https:\/\/doi.org\/10.1016\/elsevier_cm_policy","source":"Crossref","is-referenced-by-count":27,"special_numbering":"C","title":["Evaluating the Effectiveness of Deep Learning Contouring across Multiple Radiotherapy Centres"],"prefix":"10.1016","volume":"24","author":[{"given":"Zoe","family":"Walker","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Gary","family":"Bartley","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Christina","family":"Hague","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Daniel","family":"Kelly","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Clara","family":"Navarro","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jane","family":"Rogers","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Christopher","family":"South","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Simon","family":"Temple","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Philip","family":"Whitehurst","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Robert","family":"Chuter","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"78","reference":[{"key":"10.1016\/j.phro.2022.11.003_b0005","doi-asserted-by":"crossref","first-page":"321","DOI":"10.1016\/j.radonc.2014.08.028","article-title":"Prospective randomized double-blind study of atlas-based organ-at-risk auto segmentation-assisted radiation planning in head and neck cancer","volume":"112","author":"Walker","year":"2014","journal-title":"Radiother Oncol"},{"key":"10.1016\/j.phro.2022.11.003_b0010","doi-asserted-by":"crossref","first-page":"e530","DOI":"10.1259\/bjr\/66693547","article-title":"Interobserver variation in clinical target volume and organs at risk segmentation in post-parotidectomy radiotherapy: can segmentation protocols help?","volume":"85","author":"Mukesh","year":"2012","journal-title":"Br J Radiol"},{"key":"10.1016\/j.phro.2022.11.003_b0015","doi-asserted-by":"crossref","first-page":"182","DOI":"10.1016\/j.radonc.2005.09.017","article-title":"Observer variation in target volume delineation of lung cancer related to radiation oncologist-computer interaction: a \u2019Big Brother\u2019 evaluation","volume":"77","author":"Steenbakkers","year":"2005","journal-title":"Radiother Oncol"},{"key":"10.1016\/j.phro.2022.11.003_b0020","doi-asserted-by":"crossref","first-page":"77","DOI":"10.1017\/S1460396908006316","article-title":"Variations in inter-observer contouring and its impact on dosimetric and radiobiological parameters for intensity-modulated radiotherapy planning in treatment of localised prostate cancer","volume":"2","author":"Bhardwaj","year":"2008","journal-title":"J Radiother Pract"},{"key":"10.1016\/j.phro.2022.11.003_b0025","doi-asserted-by":"crossref","first-page":"32","DOI":"10.1186\/1748-717X-7-32","article-title":"3D Variation in delineation of head and neck organs at risk","volume":"7","author":"Brouwer","year":"2012","journal-title":"Radiat Oncol"},{"key":"10.1016\/j.phro.2022.11.003_b0030","doi-asserted-by":"crossref","first-page":"183","DOI":"10.1016\/j.radi.2011.01.003","article-title":"An assessment of OAR deli- neation by the radiation therapist","volume":"17","author":"Schick","year":"2011","journal-title":"Radiography"},{"key":"10.1016\/j.phro.2022.11.003_b0035","doi-asserted-by":"crossref","first-page":"160","DOI":"10.1186\/1748-717X-7-160","article-title":"Systematic evaluation of three different commercial software solutions for automatic segmentation for adaptive therapy in head-and-neck, prostate and pleural cancer","volume":"7","author":"La Macchia","year":"2012","journal-title":"Radiat Oncol"},{"key":"10.1016\/j.phro.2022.11.003_b0040","doi-asserted-by":"crossref","first-page":"807","DOI":"10.1007\/s00066-012-0117-0","article-title":"Assessment of accuracy and efficiency of atlas-based auto- segmentation for prostate radiotherapy in a variety of clinical conditions","volume":"188","author":"Simmat","year":"2012","journal-title":"Strahlenther Onkol"},{"key":"10.1016\/j.phro.2022.11.003_b0045","doi-asserted-by":"crossref","first-page":"3433","DOI":"10.1118\/1.4956021","article-title":"SU-F-J-113: multi-atlas based automatic organ segmentation for lung radiotherapy planning","volume":"43","author":"Kim","year":"2016","journal-title":"Med Phys"},{"key":"10.1016\/j.phro.2022.11.003_b0050","doi-asserted-by":"crossref","first-page":"970","DOI":"10.1118\/1.3302141","article-title":"Analysis of deformable image registration accuracy using computational modeling","volume":"37","author":"Zhong","year":"2010","journal-title":"Med Phys"},{"key":"10.1016\/j.phro.2022.11.003_b0055","doi-asserted-by":"crossref","first-page":"e30","DOI":"10.1016\/j.ejmp.2015.10.020","article-title":"The impact of the number of atlases on the performance of automatic multi-atlas contouring","volume":"31","author":"Larrue","year":"2015","journal-title":"Phys Med"},{"key":"10.1016\/j.phro.2022.11.003_b0060","doi-asserted-by":"crossref","first-page":"950","DOI":"10.1016\/j.ijrobp.2010.07.009","article-title":"Clinical validation of atlas-based auto-segmentation of multiple target volumes and normal tissue (swallowing\/mastication) structures in the head and neck","volume":"81","author":"Teguh","year":"2011","journal-title":"Int J Radiat Oncol Biol Phys"},{"key":"10.1016\/j.phro.2022.11.003_b0065","doi-asserted-by":"crossref","first-page":"126","DOI":"10.1016\/j.compbiomed.2018.05.018","article-title":"Survey on deep learning for radiotherapy","volume":"98","author":"Meyer","year":"2018","journal-title":"Comput Biol Med"},{"key":"10.1016\/j.phro.2022.11.003_b0070","doi-asserted-by":"crossref","first-page":"115","DOI":"10.1016\/j.radonc.2019.09.022","article-title":"Improving automatic delineation for head and neck organs at risk by Deep Learning Contouring","volume":"142","author":"van Dijk","year":"2020","journal-title":"Radiother Oncol"},{"key":"10.1016\/j.phro.2022.11.003_b0075","doi-asserted-by":"crossref","first-page":"959","DOI":"10.3390\/diagnostics10110959","article-title":"A Deep Learning-Based Automated CT Segmentation of Prostate Cancer Anatomy for Radiation Therapy Planning-A Retrospective Multicenter Study","volume":"10","author":"Kiljunen","year":"2020","journal-title":"Diagnostics"},{"key":"10.1016\/j.phro.2022.11.003_b0080","doi-asserted-by":"crossref","first-page":"e26151","DOI":"10.2196\/26151","article-title":"Deep learning to achieve clinically applicable segmentation of head and neck anatomy for radiotherapy","volume":"23","author":"Nikolov","year":"2021","journal-title":"J Med Internet Res"},{"key":"10.1016\/j.phro.2022.11.003_b0085","doi-asserted-by":"crossref","first-page":"312","DOI":"10.1016\/j.radonc.2017.11.012","article-title":"Clinical evaluation of atlas and deep learning based automatic contouring for lung cancer","volume":"126","author":"Lustberg","year":"2018","journal-title":"Radiother Oncol"},{"key":"10.1016\/j.phro.2022.11.003_b0090","doi-asserted-by":"crossref","first-page":"e2027426","DOI":"10.1001\/jamanetworkopen.2020.27426","article-title":"Evaluation of Deep Learning to Augment Image-Guided Radiotherapy for Head and Neck and Prostate Cancers","volume":"3","author":"Oktay","year":"2020","journal-title":"JAMA Netw open"},{"key":"10.1016\/j.phro.2022.11.003_b0095","doi-asserted-by":"crossref","first-page":"S101","DOI":"10.1016\/j.ijrobp.2020.07.2278","article-title":"Implementation of Deep Learning-Based Auto-Segmentation for Radiotherapy Planning Structures: A Multi-Center Workflow Study","volume":"108","author":"Wong","year":"2020","journal-title":"Int J Radiat Oncol Biol Phys"},{"key":"10.1016\/j.phro.2022.11.003_b0100","doi-asserted-by":"crossref","first-page":"54","DOI":"10.1016\/j.phro.2020.10.001","article-title":"Assessment of manual adjustment performed in clinical practice following deep learning contouring for head and neck organs at risk in radiotherapy","volume":"16","author":"Brouwer","year":"2020","journal-title":"Phys Imaging Radiat Oncol"},{"key":"10.1016\/j.phro.2022.11.003_b0105","doi-asserted-by":"crossref","first-page":"8","DOI":"10.1016\/j.phro.2020.06.006","article-title":"External validation of deep learning-based contouring of head and neck organs at risk","volume":"15","author":"Brunenberg","year":"2020","journal-title":"Phys Imaging Radiat Oncol"},{"key":"10.1016\/j.phro.2022.11.003_b0110","doi-asserted-by":"crossref","first-page":"83","DOI":"10.1016\/j.radonc.2015.07.041","article-title":"CT-based delineation of organs at risk in the head and neck region: DAHANCA, EORTC, GORTEC, HKNPCSG, NCIC CTG, NCRI, NRG Oncology and TROG consensus guidelines","volume":"117","author":"Brouwer","year":"2015","journal-title":"Radiother Oncol"},{"key":"10.1016\/j.phro.2022.11.003_b0115","doi-asserted-by":"crossref","first-page":"151","DOI":"10.1002\/jmrs.64","article-title":"Evaluation of atlas-based auto-segmentation software in prostate cancer patients","volume":"61","author":"Greenham","year":"2014","journal-title":"J Med Radiat Sci"},{"key":"10.1016\/j.phro.2022.11.003_b0120","doi-asserted-by":"crossref","first-page":"e80","DOI":"10.1016\/j.prro.2020.05.013","article-title":"Clinical evaluation of deep learning and atlas-based auto-contouring of bladder and rectum for prostate radiation therapy","volume":"11","author":"Zabel","year":"2020","journal-title":"Pract Radiat Oncol"},{"key":"10.1016\/j.phro.2022.11.003_b0125","doi-asserted-by":"crossref","first-page":"547","DOI":"10.1002\/mp.12045","article-title":"Segmentation of organs-at-risks in head and neck CT images using convolutional neural networks","volume":"44","author":"Ibragimov","year":"2017","journal-title":"Med Phys"},{"key":"10.1016\/j.phro.2022.11.003_b0130","unstructured":"Sim J, Wright C, Research in healthcare, concepts designs and methods. Nelson Thomas:2020."},{"key":"10.1016\/j.phro.2022.11.003_b0135","doi-asserted-by":"crossref","first-page":"20140299","DOI":"10.1259\/bjr.20140299","article-title":"The utility of atlas-based segmentation in the male pelvis is dependent on the interobserver agreement of the structures segmented","volume":"87","author":"Langmack","year":"2014","journal-title":"Br J Radiol"},{"key":"10.1016\/j.phro.2022.11.003_b0140","first-page":"1","article-title":"Evaluation of measures for assessing time-saving of automatic organ-at- risk segmentation in radiotherapy","volume":"13","author":"Vaassen","year":"2019","journal-title":"Phys Imaging Radiat Oncol"},{"key":"10.1016\/j.phro.2022.11.003_b0145","doi-asserted-by":"crossref","first-page":"55","DOI":"10.1016\/j.radonc.2020.09.008","article-title":"Overview of artificial intelligence-based applications in radiotherapy: recommendations for implementation and quality assurance","volume":"153","author":"Vandewinckele","year":"2020","journal-title":"Radiother Oncol"},{"key":"10.1016\/j.phro.2022.11.003_b0150","doi-asserted-by":"crossref","first-page":"677","DOI":"10.1016\/j.ijrobp.2019.02.040","article-title":"Deep learning-based delineation of head and neck organs at risk: geometric and dosimetric evaluation","volume":"104","author":"van Rooij","year":"2019","journal-title":"Int J Radiat Oncol Biol Phys"}],"container-title":["Physics and Imaging in Radiation Oncology"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S2405631622000938?httpAccept=text\/xml","content-type":"text\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S2405631622000938?httpAccept=text\/plain","content-type":"text\/plain","content-version":"vor","intended-application":"text-mining"}],"deposited":{"date-parts":[[2025,11,7]],"date-time":"2025-11-07T08:14:37Z","timestamp":1762503277000},"score":1,"resource":{"primary":{"URL":"https:\/\/linkinghub.elsevier.com\/retrieve\/pii\/S2405631622000938"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,10]]},"references-count":30,"alternative-id":["S2405631622000938"],"URL":"https:\/\/doi.org\/10.1016\/j.phro.2022.11.003","relation":{},"ISSN":["2405-6316"],"issn-type":[{"value":"2405-6316","type":"print"}],"subject":[],"published":{"date-parts":[[2022,10]]},"assertion":[{"value":"Elsevier","name":"publisher","label":"This article is maintained by"},{"value":"Evaluating the Effectiveness of Deep Learning Contouring across Multiple Radiotherapy Centres","name":"articletitle","label":"Article Title"},{"value":"Physics and Imaging in Radiation Oncology","name":"journaltitle","label":"Journal Title"},{"value":"https:\/\/doi.org\/10.1016\/j.phro.2022.11.003","name":"articlelink","label":"CrossRef DOI link to publisher maintained version"},{"value":"article","name":"content_type","label":"Content Type"},{"value":"\u00a9 2022 The Authors. Published by Elsevier B.V. on behalf of European Society of Radiotherapy & Oncology.","name":"copyright","label":"Copyright"}]}}