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Several studies have suggested that the clinical implementation of automated contouring tools can reduce inter\u2010observer variation while increasing contouring efficiency, thereby improving the quality of radiotherapy treatment and reducing the time between simulation and treatment. In this study, a novel, commercial automated contouring tool based on machine learning, the AI\u2010Rad Companion Organs RT\u2122 (AI\u2010Rad) software (Version VA31) (Siemens Healthineers, Munich, Germany), was assessed against both manually delineated contours and another commercially available automated contouring software, Varian Smart Segmentation\u2122 (SS) (Version 16.0) (Varian, Palo Alto, CA, United States). The quality of contours generated by AI\u2010Rad in Head and Neck (H&amp;N), Thorax, Breast, Male Pelvis (Pelvis_M), and Female Pelvis (Pevis_F) anatomical areas was evaluated both quantitatively and qualitatively using several metrics. A timing analysis was subsequently performed to explore potential time savings achieved by AI\u2010Rad. Results showed that most automated contours generated by AI\u2010Rad were not only clinically acceptable and required minimal editing, but also superior in quality to contours generated by SS in multiple structures. In addition, timing analysis favored AI\u2010Rad over manual contouring, indicating the largest time saving (753s per patient) in the Thorax area. AI\u2010Rad was concluded to be a promising automated contouring solution that generated clinically acceptable contours and achieved time savings, thereby greatly benefiting the radiotherapy process.<\/jats:p>","DOI":"10.1002\/acm2.13949","type":"journal-article","created":{"date-parts":[[2023,3,5]],"date-time":"2023-03-05T06:48:21Z","timestamp":1677998901000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":16,"title":["Clinical assessment of a novel machine\u2010learning automated contouring tool for radiotherapy planning"],"prefix":"10.1002","volume":"24","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-6121-8853","authenticated-orcid":false,"given":"Yunfei","family":"Hu","sequence":"first","affiliation":[{"name":"Icon Cancer Centre Concord Rusty Priest Building Concord Repatriation Hospital  Concord NSW Australia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Huong","family":"Nguyen","sequence":"additional","affiliation":[{"name":"ICON Core Office  South Brisbane QLD Australia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Claire","family":"Smith","sequence":"additional","affiliation":[{"name":"ICON Core Office  South Brisbane QLD Australia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Tom","family":"Chen","sequence":"additional","affiliation":[{"name":"Icon Cancer Centre Springfield Cancer Care Centre Mater Private Hospital 30 Health Care Dr  Springfield Queensland Australia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Mikel","family":"Byrne","sequence":"additional","affiliation":[{"name":"Icon Cancer Centre Wahroonga Sydney Adventist Hospital  Sydney Australia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ben","family":"Archibald\u2010Heeren","sequence":"additional","affiliation":[{"name":"Icon Cancer Centre Concord Rusty Priest Building Concord Repatriation Hospital  Concord NSW Australia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"James","family":"Rijken","sequence":"additional","affiliation":[{"name":"Icon Cancer Centre Windsor Gardens  Windsor Gardens South Australia Australia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Trent","family":"Aland","sequence":"additional","affiliation":[{"name":"ICON Core Office  South Brisbane QLD Australia"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"311","published-online":{"date-parts":[[2023,3,4]]},"reference":[{"key":"e_1_2_10_2_1","unstructured":"England NHS.Modernising Radiotherapy Services in England\u2014Developing Proposals for Future Service Models. 28 October2016. 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