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dc.contributor.authorEason, L.
dc.contributor.authorMason, J.
dc.contributor.authorCooper, R.
dc.contributor.authorRadhakrishna, Ganesh
dc.contributor.authorBownes, P.
dc.date.accessioned2020-11-16T07:49:07Z
dc.date.available2020-11-16T07:49:07Z
dc.date.issued2020en
dc.identifier.citationEason L, Mason J, Cooper R, Radhakrishna G, Bownes P. Evaluation of a collapsed-cone convolution algorithm for esophagus and surface mold (192)Ir brachytherapy treatment planning. Brachytherapy. 2020.en
dc.identifier.pmid33071170en
dc.identifier.doi10.1016/j.brachy.2020.09.006en
dc.identifier.urihttp://hdl.handle.net/10541/623374
dc.description.abstractPurpose: TG43 does not account for a lack of scatter and tissue and applicator heterogeneities. The advanced collapsed-cone engine (ACE) algorithm available for use in the Oncentra Brachy treatment planning system (Elekta AB, Stockholm, Sweden) can model these conditions more accurately and is evaluated for esophageal and surface mold brachytherapy treatments. Methods and materials: ACE was commissioned for use then compared against TG43 for five esophageal and five surface mold treatment plans. Dosimetric differences between each algorithm were assessed using superimposed comparisons and dose-volume histogram statistics. Results: Esophagus (6 Gy per fraction): Compared with TG43, ACE demonstrated up to a 0.63% and 0.05 Gy reduction in planning target volume (PTV) V100% and PTV D98, respectively. Lung D2cc and bone D2cc deviated by up to 0.09 Gy and 0.03 Gy, respectively. Lung D0.1 cc and bone D0.1 cc both deviated by up to 0.12 Gy. Surface mold (4.5 Gy per fraction): Compared with TG43, ACE demonstrated up to a 12.5% and 0.18 Gy reduction in PTV V80% and PTV D98, respectively. Bone D2cc and D0.1 cc both reduced by up to 0.2 Gy when modeled with ACE. Increasing mold size laterally increased the dosimetric differences between TG43 and ACE. Conclusions: TG43 generally overestimated dose delivered to the target volume and organs at risk for the sites investigated. Dosimetric differences observed for esophageal treatments were minimal; however, surface mold treatments would benefit from the increased dosimetric accuracy offered by ACE. Implementation should be considered for surface mold 192Ir treatment planning, but increased calculation time, additional contouring, and mass density assignment requirements should be scrutinized with regard to their potentially negative impact on current clinical practice.en
dc.language.isoenen
dc.relation.urlhttps://dx.doi.org/10.1016/j.brachy.2020.09.006en
dc.titleEvaluation of a collapsed-cone convolution algorithm for esophagus and surface mold (192)Ir brachytherapy treatment planningen
dc.typeArticleen
dc.contributor.departmentLeeds Cancer Centre, St. James's University Hospital, Leeds, United Kingdom.en
dc.identifier.journalBrachytherapyen
dc.description.noteen]


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