{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,11,15]],"date-time":"2025-11-15T10:31:48Z","timestamp":1763202708878,"version":"3.40.5"},"reference-count":29,"publisher":"Wiley","issue":"S2","license":[{"start":{"date-parts":[[2022,11,24]],"date-time":"2022-11-24T00:00:00Z","timestamp":1669248000000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0\/"}],"content-domain":{"domain":["onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["J of Medical Radiation Sci"],"published-print":{"date-parts":[[2023,4]]},"abstract":"<jats:title>Abstract<\/jats:title><jats:sec><jats:title>Introduction<\/jats:title><jats:p>Stereotactic body radiotherapy (SBRT) is an ablative method for lung malignancies. Here, the definition of the gross target volume (GTV) is subject to interobserver variation. In this study, we aimed to evaluate the interobserver variability during SBRT and its dosimetric impact, as well as to introduce a semi\u2010automated delineation tool for both planning computer tomography (P\u2010CT) and cone beam CT (CBCT) to help to standardise GTV delineation and adaptive volume\u2010change registration.<\/jats:p><\/jats:sec><jats:sec><jats:title>Methods<\/jats:title><jats:p>The interobserver variation of GTV manual contours from five physicians was analysed in 15 patients after lung SBRT on free breathing (FB) P\u2010CT (<jats:italic>n<\/jats:italic>\u00a0=\u00a015) and CBCT (<jats:italic>n<\/jats:italic>\u00a0=\u00a090) before and after each fraction. The dosimetric impact from interobserver variations of GTV based on the original treatment plan was analysed. Next, the accuracy of an in\u2010house easy\u2010to\u2010use semi\u2010automated\u2010segmentation algorithm for pulmonary lesions was compared with gold standard contours in FB P\u2010CT and CBCT, as well as 4D P\u2010CT of additional 10 patients.<\/jats:p><\/jats:sec><jats:sec><jats:title>Results<\/jats:title><jats:p>The interobserver variability in manual contours resulted in violations of dose coverage of the planning target volume (PTV), which, in turn, resulted in compromised tumour control probability in contours from four physicians. The validation of the semi\u2010automated delineation algorithm using thorax phantom led to a highly reliable accuracy in defining GTVs. Comparing the unsupervised auto\u2010contours with the gold standard delineation revealed high equal high concordance for FB P\u2010CT, 4D P\u2010CT and CBCT, with a DSC of 0.83, 0.76 and 0.8, respectively. The supervised use of the semi\u2010automated delineation tool improved its accuracy, with DSCs of 0.86, 0.86 and 0.8 for FB P\u2010CT, 4D P\u2010CT and CBCT, respectively. The use of the algorithm was associated with a significantly shorter working time. The semi\u2010automated delineation tool can accurately register volume changes in CBCTs.<\/jats:p><\/jats:sec><jats:sec><jats:title>Conclusion<\/jats:title><jats:p>The segmentation algorithm provides a reliable, standardised and time\u2010saving alternative for manual delineation in lung SBRT in P\u2010CT and CBCT.<\/jats:p><\/jats:sec>","DOI":"10.1002\/jmrs.637","type":"journal-article","created":{"date-parts":[[2022,11,25]],"date-time":"2022-11-25T03:23:55Z","timestamp":1669346635000},"page":"37-47","update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["Clinical validation of a semi\u2010automated segmentation algorithm for target volume definition on planning <scp>CT<\/scp> and <scp>CBCT<\/scp> in stereotactic body radiotherapy (<scp>SBRT<\/scp>) for peripheral lung lesions"],"prefix":"10.1002","volume":"70","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-0650-3576","authenticated-orcid":false,"given":"Ahmed Allam","family":"Mohamed","sequence":"first","affiliation":[{"name":"Department of Radiation Oncology RWTH Aachen University  Aachen Germany"},{"name":"Center for Integrated Oncology Aachen, Bonn, Cologne and Duesseldorf (CIO ABCD)  Aachen Germany"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Kathrin","family":"Risse","sequence":"additional","affiliation":[{"name":"Department of Radiation Oncology RWTH Aachen University  Aachen Germany"},{"name":"Center for Integrated Oncology Aachen, Bonn, Cologne and Duesseldorf (CIO ABCD)  Aachen Germany"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Laura","family":"Schmitz","sequence":"additional","affiliation":[{"name":"Department of Radiation Oncology RWTH Aachen University  Aachen Germany"},{"name":"Center for Integrated Oncology Aachen, Bonn, Cologne and Duesseldorf (CIO ABCD)  Aachen 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