{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,25]],"date-time":"2026-08-25T18:30:25Z","timestamp":1787682625471,"version":"build-2784847793"},"reference-count":23,"publisher":"Oxford University Press (OUP)","issue":"5","license":[{"start":{"date-parts":[[2023,8,22]],"date-time":"2023-08-22T00:00:00Z","timestamp":1692662400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2023,9,22]]},"abstract":"<jats:title>Abstract<\/jats:title>\n               <jats:p>This study aims to evaluate the dosimetric accuracy of a deep learning (DL)-based deliverable volumetric arc radiation therapy (VMAT) plan generated using DL-based automated planning assistant system (AIVOT, prototype version) for patients with prostate cancer. The VMAT data (cliDose) of 68 patients with prostate cancer treated with VMAT treatment (70\u201374 Gy\/28\u201337 fr) at our hospital were used (n\u2009=\u200955 for training and n\u2009=\u200913 for testing). First, a HD-U-net-based 3D dose prediction model implemented in AIVOT was customized using the VMAT data. Thus, a predictive VMAT plan (preDose) comprising AIVOT that predicted the 3D doses was generated. Second, deliverable VMAT plans (deliDose) were created using AIVOT, the radiation treatment planning system Eclipse (version 15.6) and its vender-supplied objective functions. Finally, we compared these two estimated DL-based VMAT treatment plans\u2014i.e. preDose and deliDose\u2014with cliDose. The average absolute dose difference of all DVH parameters for the target tissue between cliDose and deliDose across all patients was 1.32\u2009\u00b1\u20091.35% (range: 0.04\u20136.21%), while that for all the organs at risks was 2.08\u2009\u00b1\u20092.79% (range: 0.00\u201315.4%). The deliDose was superior to the cliDose in all DVH parameters for bladder and rectum. The blinded plan scoring of deliDose and cliDose was 4.54\u2009\u00b1\u20090.50 and 5.0\u2009\u00b1\u20090.0, respectively (All plans scored \u22654 points, P\u2009=\u20090.03.) This study demonstrated that DL-based deliverable plan for prostate cancer achieved the clinically acceptable level. Thus, the AIVOT software exhibited a potential for automated planning with no intervention for patients with prostate cancer.<\/jats:p>","DOI":"10.1093\/jrr\/rrad058","type":"journal-article","created":{"date-parts":[[2023,8,15]],"date-time":"2023-08-15T20:04:17Z","timestamp":1692129857000},"page":"842-849","source":"Crossref","is-referenced-by-count":14,"title":["Evaluation of deep learning-based deliverable VMAT plan generated by prototype software for automated planning for prostate cancer patients"],"prefix":"10.1093","volume":"64","author":[{"given":"Noriyuki","family":"Kadoya","sequence":"first","affiliation":[{"name":"Department of Radiation Oncology, Tohoku University Graduate School of Medicine , 1-1 Seiryo-machi, Aoba-ku, Sendai, Miyagi, 980-8574 , Japan"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yuto","family":"Kimura","sequence":"additional","affiliation":[{"name":"Radiation Oncology Center, Ofuna Chuo Hospital , Ofuna 6-2-24, Kamakura, Kanagawa 247-0056 , Japan"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ryota","family":"Tozuka","sequence":"additional","affiliation":[{"name":"Department of Radiation Oncology, Tohoku University Graduate School of Medicine , 1-1 Seiryo-machi, Aoba-ku, Sendai, Miyagi, 980-8574 , Japan"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Shohei","family":"Tanaka","sequence":"additional","affiliation":[{"name":"Department of Radiation Oncology, Tohoku University Graduate School of Medicine , 1-1 Seiryo-machi, Aoba-ku, Sendai, Miyagi, 980-8574 , Japan"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Kazuhiro","family":"Arai","sequence":"additional","affiliation":[{"name":"Department of Radiation Oncology, Tohoku University Graduate School of Medicine , 1-1 Seiryo-machi, Aoba-ku, Sendai, Miyagi, 980-8574 , Japan"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yoshiyuki","family":"Katsuta","sequence":"additional","affiliation":[{"name":"Department of Radiation Oncology, Tohoku University Graduate School of Medicine , 1-1 Seiryo-machi, Aoba-ku, Sendai, Miyagi, 980-8574 , Japan"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Hidetoshi","family":"Shimizu","sequence":"additional","affiliation":[{"name":"Department of Radiation Oncology, Aichi Cancer Center Hospital , Kanokoden 1-1, Chikusa-ku, Nagoya, Aichi, 464-8681 , Japan"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yuto","family":"Sugai","sequence":"additional","affiliation":[{"name":"Department of Radiological Technology, Keio University , Shinanomachi 35, Shinjuku-ku, Tokyo 160-8582 , Japan"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Takaya","family":"Yamamoto","sequence":"additional","affiliation":[{"name":"Department of Radiation Oncology, Tohoku University 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