{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,17]],"date-time":"2026-10-17T22:17:45Z","timestamp":1792275465956,"version":"4.4.0"},"reference-count":48,"publisher":"IOP Publishing","issue":"5","license":[{"start":{"date-parts":[[2021,2,26]],"date-time":"2021-02-26T00:00:00Z","timestamp":1614297600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/publishingsupport.iopscience.iop.org\/iop-standard\/v1"},{"start":{"date-parts":[[2021,2,26]],"date-time":"2021-02-26T00:00:00Z","timestamp":1614297600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/iopscience.iop.org\/info\/page\/text-and-data-mining"}],"content-domain":{"domain":["iopscience.iop.org"],"crossmark-restriction":false},"short-container-title":["Phys. Med. Biol."],"published-print":{"date-parts":[[2021,3,7]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:p>\n                    <jats:italic>Purpose<\/jats:italic>\n                    . Needle catheter positions critically affect the quality of treatment plans in prostate cancer high-dose-rate (HDR) brachytherapy. The current standard needle positioning approach is based on human intuition, which cannot guarantee a high-quality plan. This study proposed a method to simultaneously select needle catheter positions and determine dwell time for preplanning of HDR brachytherapy of prostate cancer.\n                    <jats:italic>Methods<\/jats:italic>\n                    . We formulated the needle catheter selection problem and inverse dwell time optimization problem in a unified framework. In addition to the dose objectives of the planning target volume (PTV) and organs at risk (OARs), the objective function incorporated a group-sparsity term with a needle-specific adaptive weighting scheme to generate high-quality plans with the minimal number of needle catheters. The optimization problem was solved by a fast-iterative shrinkage-thresholding algorithm. For validation purposes, we tested the proposed algorithm on 10 patient cases previously treated at our institution and compared the resulting plans with plans generated using needle catheters selected manually.\n                    <jats:italic>Results<\/jats:italic>\n                    . Compared to the plan with manually selected needle catheters, when normalizing both plans to the same PTV coverage\n                    <jats:italic>V<\/jats:italic>\n                    <jats:sub>100%<\/jats:sub>\n                    \u00a0=\u00a095%, the plans generated by the proposed algorithm reduced median\n                    <jats:italic>V<\/jats:italic>\n                    <jats:sub>125%<\/jats:sub>\n                    from 65% to 64%, but increased median\n                    <jats:italic>V<\/jats:italic>\n                    <jats:sub>150%<\/jats:sub>\n                    from 35% to 38%, and\n                    <jats:italic>V<\/jats:italic>\n                    <jats:sub>200%<\/jats:sub>\n                    from 14% to 16%. All planning objectives were met. All clinically important dosimetric parameters of OARs were reduced.\n                    <jats:italic>D<\/jats:italic>\n                    <jats:sub>1cc<\/jats:sub>\n                    of bladder and rectum were reduced from 8.57 Gy to 8.50 Gy and from 7.24 Gy to 6.80 Gy, respectively.\n                    <jats:italic>D<\/jats:italic>\n                    <jats:sub>max<\/jats:sub>\n                    of urethra was reduced from 15.85 Gy to 15.77 Gy. The median number of selected needle catheters was reduced by two. The computational time for solving the proposed optimization problem was \u223c90 s using MATLAB.\n                    <jats:italic>Conclusion<\/jats:italic>\n                    . The proposed algorithm was able to generate plans for prostate cancer HDR brachytherapy preplanning with increased median conformity index (0.73\u20130.77) and slightly lower median homogeneity index (0.64\u20130.62) with the number of selected needles reduced by two compared to the manual needle selection approach.\n                  <\/jats:p>","DOI":"10.1088\/1361-6560\/abd00e","type":"journal-article","created":{"date-parts":[[2020,12,2]],"date-time":"2020-12-02T18:02:07Z","timestamp":1606932127000},"page":"055028","update-policy":"https:\/\/doi.org\/10.1088\/crossmark-policy","source":"Crossref","is-referenced-by-count":8,"title":["Simultaneous needle catheter selection and dwell time optimization for preplanning of high-dose-rate brachytherapy of prostate cancer"],"prefix":"10.1088","volume":"66","author":[{"given":"Chao","family":"Wang","sequence":"first","affiliation":[{"name":"University of Texas Southwestern Medical Center"},{"name":"University of Texas Southwestern Medical Center"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yesenia","family":"Gonzalez","sequence":"additional","affiliation":[{"name":"University of Texas Southwestern Medical Center"},{"name":"University of Texas Southwestern Medical Center"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6490-6555","authenticated-orcid":false,"given":"Chenyang","family":"Shen","sequence":"additional","affiliation":[{"name":"University of Texas Southwestern Medical Center"},{"name":"University of Texas Southwestern Medical Center"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Brian","family":"Hrycushko","sequence":"additional","affiliation":[{"name":"University of Texas Southwestern Medical Center"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xun","family":"Jia","sequence":"additional","affiliation":[{"name":"University of Texas Southwestern Medical Center"},{"name":"University of Texas Southwestern Medical Center"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"266","published-online":{"date-parts":[[2021,2,26]]},"reference":[{"key":"pmbabd00ebib1","doi-asserted-by":"publisher","first-page":"220","DOI":"10.1109\/TCI.2015.2485078","type":"journal-article","article-title":"Iteratively reweighted \u21131 approaches to sparse composite regularization","volume":"1","author":"Ahmad","year":"2015","journal-title":"IEEE Trans. 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All rights, including for text and data mining, AI training, and similar technologies, are reserved.","name":"copyright_information","label":"Copyright Information"},{"value":"2020-07-07","name":"date_received","label":"Date Received","group":{"name":"publication_dates","label":"Publication dates"}},{"value":"2020-12-02","name":"date_accepted","label":"Date Accepted","group":{"name":"publication_dates","label":"Publication dates"}},{"value":"2021-02-26","name":"date_epub","label":"Online publication date","group":{"name":"publication_dates","label":"Publication dates"}}]}}