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A constant difficulty encountered in radiation therapy treatment planning is the patient-specific trade-off between ensuring appropriate tumor coverage and avoiding excessive radiation to healthy structures. Such trade-offs are conventionally resolved by manually altering an optimization problem formulation and re-optimizing the treatment plan multiple times. Trial and error of this form is time consuming and even if a treatment plan deemed satisfactory is found, it is not clear if better treatment options exist for the current patient. With multi-criteria optimization in RayStation you can simplify your planning process while improving the quality of your plans.

Personalized care at RISO with Multi-Criteria Optimization

RISO Radiotherapeutic Institute in the Netherlands is one of the first RayStation users. In this video, they describe their partnership with RaySearch and how multi-criteria optimization in RayStation has helped them improve the workflow and personalize care for patients.

Multi-criteria optimization

MCO provides an alternative optimization workflow. Instead of the planner performing an iterative optimization with adjustments to optimization functions and weights, RayStation’s MCO quickly generates a set of relevant treatment plans that are Pareto-optimal regarding user-specified priorities, objectives and constraints. The planner or physician can fine-tune a plan by moving sliders in real time to balance between conflicting clinical goals.

These plans respect all constraints and no objectives can be improved without impairing another one. Based on these plans, the planner or physician can manipulate sliders in real time to balance between clinical trade-offs.

  • Pre-computation of all plans that are Pareto optimal to the priorities, objectives and constraints set by the planner and physician
  • The planner and the physician can together in real-time explore different solutions and the physician can directly influence the plan. They select the best clinical trade-off.
  • Automatic tool for generating a deliverable treatment plan from this selection.
  • Supports SMLC, DMLC, VMAT, TomoTherapy and Proton PBS planning.


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Short demonstration of MCO

In-depth demonstration of MCO

Directly deliverable VMAT plans

The RayStation 8B release introduces a segment-based optimization mode for VMAT, using sliding window sequencing, where Pareto plans are generated by direct machine parameter optimization. The deliverable plan is created by control point interpolation, resulting in a high level of agreement between the navigated dose and the dose of the deliverable plan. This new optimization mode is available for Elekta Agility and Elekta MLCi2.



Clinical benefits

  • Planners and physicians can find solutions they didn’t know existed.

    –Hong et al., Müller et al., 2008

  • Physicians tend to select plans with higher OAR sparing at the expense of slightly under dosing target as they can see exactly where it happen.

    –Kamran et al., Wala et al., 2016

  • The total treatment planning time is significantly reduced without compromising plan quality.

    –Craft et al., 2012

  • Planners with limited experience and knowledge can produce clinically acceptable plans.

    –Kierkels et al., 2015

"The typical trade-off in radiation treatment planning is target coverage versus critical structure sparing. Traditional treatment planning proceeds by a trial and error fashion, where the planner tries to guess at system optimization parameters that might strike the best balance amongst the multiple conflicting goals. But this process can be quite time consuming. Multi-Criteria Optimization simplifies this by presenting the planner with a set of sliders which allow them to surf across the trade-off space and quickly decide on the right balance."

David Craft

Assistant Professor at the Department of Radiation Oncology, Massachusetts General Hospital in Boston.

"Planning is one of the most important things in radiation oncology, because you want to treat the tumor right, and you don’t want to give a high dose to the normal tissue. Multi-Criteria Optimization in RayStation allows us to balance the clinical trade-offs in real time to reach a more personalized treatment plan for the patient."

Sandrine van de Pol

Radiation oncologist, Radiotherapiegroep, Deventer, The Netherlands.