Multi-Criteria Optimization
RISO Radiotherapeutic Institute in the Netherlands is one of the first RayStation users. In this short video, the RISO team describes its partnership with RaySearch and how multi-criteria optimization in RayStation has helped improve workflows and more personalized patient care.
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Planners and physicians can find solutions they did not know existed. Hong et al. 2008, Müller et al. 2017
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Physicians tend to select plans with higher OAR sparing at the expense of slightly under dosing target as they can see exactly where it happens. Kamran et al. 2016, Wala et al. 2013
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The total treatment planning time is significantly reduced without compromising plan quality. Craft et al. 2012, Kamran et al. 2016
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Planners with limited experience and knowledge can produce clinically acceptable plans. Kierkels et al. 2015
Avoid iterative optimization with adjustments to functions and weights with multi-criteria optimization in RayStation. This module instead allows Pareto optimal treatment plans to be generated according to user-specified objectives and constraints.
Planners and physicians can finetune treatment plans by moving sliders in real time to find the right balance between conflicting clinical goals. The plan remains Pareto optimal with all constraints respected – no objectives can be improved without negatively impacting others. Pre-computation of all Pareto optimal plans can be fully automated, so the planner and physician can explore different solutions in a joint meeting without being interrupted by time-consuming calculations.
Deliverable sliding is supported for VMAT, DMLC, TomoTherapy and proton PBS. Plan exploration includes deliverable plans being generated with extremely narrow approximation to the navigate dose.