{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,15]],"date-time":"2026-09-15T17:58:23Z","timestamp":1789495103630,"version":"build-2803163510"},"reference-count":25,"publisher":"IOP Publishing","issue":"20","license":[{"start":{"date-parts":[[2018,10,16]],"date-time":"2018-10-16T00:00:00Z","timestamp":1539648000000},"content-version":"vor","delay-in-days":15,"URL":"https:\/\/publishingsupport.iopscience.iop.org\/iop-standard\/v1"},{"start":{"date-parts":[[2018,10,16]],"date-time":"2018-10-16T00:00:00Z","timestamp":1539648000000},"content-version":"tdm","delay-in-days":15,"URL":"https:\/\/iopscience.iop.org\/info\/page\/text-and-data-mining"}],"funder":[{"DOI":"10.13039\/501100000038","name":"Natural Sciences and Engineering Research Council of Canada","doi-asserted-by":"crossref","award":["432290"],"award-info":[{"award-number":["432290"]}],"id":[{"id":"10.13039\/501100000038","id-type":"DOI","asserted-by":"crossref"}]}],"content-domain":{"domain":["iopscience.iop.org"],"crossmark-restriction":false},"short-container-title":["Phys. Med. Biol."],"published-print":{"date-parts":[[2018,10,1]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:p>The current iterative approach to inverse planning of high dose rate treatment planning can be time consuming. The purpose of this two-part study is to streamline the planning process while maintaining plan quality. In this second part, a multi-criteria optimization (MCO) planning algorithm is proposed and benchmarked against a standard planning algorithm.<\/jats:p>\n                  <jats:p>With a set of previously established regression models, a patient-specific valid solution space on the Pareto surface was predicted based on the anchor plans results. Alternative plans generated alongside the partial Pareto front were presented to the planner, and one plan was selected as the MCO plan. The dosimetric parameters results as well as the planning time were compared between the MCO plans and the physician-approved standard plans for 236 prostate cases.<\/jats:p>\n                  <jats:p>\n                    Results show that the urethra is better spared with MCO planning than with standard planning (a lower mean urethral\n                    <jats:italic>D<\/jats:italic>\n                    <jats:sub>10<\/jats:sub>\n                    value of 2.25%). The overall MCO plan quality also outperforms the standard plan quality, since MCO planning is able to increase the frequency of clinically acceptable plans meeting all of RTOG criteria simultaneously without any human intervention (from 83.05% to 97.46%). Finally, the average MCO planning time is\n                    <jats:inline-formula\/>\n                    without any interventions of treatment planners.\n                  <\/jats:p>\n                  <jats:p>The presented MCO planning algorithm constitutes a robust and automated way to improve treatment quality in brachytherapy.<\/jats:p>","DOI":"10.1088\/1361-6560\/aae24f","type":"journal-article","created":{"date-parts":[[2018,9,18]],"date-time":"2018-09-18T10:45:12Z","timestamp":1537267512000},"page":"205005","update-policy":"https:\/\/doi.org\/10.1088\/crossmark-policy","source":"Crossref","is-referenced-by-count":13,"title":["A multi-criteria optimization approach for HDR prostate brachytherapy: II. 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