Abstract
PURPOSE
Recently, a GPU-based multicriteria optimization (gMCO) algorithm was integrated in
a graphical user interface (gMCO-GUI) that allowed real-time plan navigation through
a set of Pareto-optimal plans for high-dose-rate (HDR) brachytherapy. This work reports
on the inter-observer evaluation of the gMCO algorithm into the clinical workflow.
METHODS AND MATERIALS
Twenty HDR brachytherapy prostate cancer patients were retrospectively replanned with
the gMCO algorithm. The reference clinical plans were each generated by experienced
physicists using inverse planning followed by graphical optimization and approved
by a radiation oncologist (RO). Each case was replanned with the gMCO algorithm by
generating 2000 Pareto-optimal plans with four different objective functions. Two
physicists were asked to rank the objective functions according to their preferences
by choosing one preferred plan for each plans pool and ranking them using gMCO-GUI.
The optimized dwell positions and dwell times of the gMCO plans that were ranked first
were exported to Oncentra Prostate where a blinded comparison of the gMCO plans with
the clinical plans was conducted by three ROs.
RESULTS
The median planning time of the two physicists was 9 min. Both physicists preferred
the objective function with target sub-regions to cover specific target regions. Regarding
the blinded comparison, the gMCO plans were preferred 19, 17, and 12 times by the
three ROs, in which eight gMCO plans were unanimously preferred compared with the
clinical plans.
CONCLUSIONS
The plan quality and the planning time were similar between the two physicists and
within what is observed in the clinic. Moreover, the gMCO plans evaluated favorably
by ROs compared to the reference clinical plans.
Keywords
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Article Info
Publication History
Published online: May 15, 2022
Accepted:
April 6,
2022
Received in revised form:
March 15,
2022
Received:
December 30,
2021
Footnotes
Disclosures: This work was supported in part by la Fondation du CHU de Québec – Université Laval, by le centre de Recherche sur le Cancer du CHU de Québec – Université Laval, by le fond de recherche Jean-François Bergeron en cancérologie and le fond de recherche en cancérologie de l'Université Laval , by the National Sciences and Engineering Research Council of Canada (NSERC) via the NSERC-Elekta Industrial Research Chair Grant ( #484144–15 ), and via the NSERC Discovery Grants ( RGPIN-2019–05038 ).
Conflict of interest: The authors have no conflicts of interest to disclose.
Identification
Copyright
© 2022 American Brachytherapy Society. Published by Elsevier Inc. All rights reserved.
