Abstract:
In the context of a multi-criteria optimization workspace, a control circuit provides a user opportunity to modify (202) radiation treatment plan optimization objective values, wherein the optimization objectives include at least one of a radiation treatment plan complexity optimization objective and a radiation treatment delivery time optimization objective. These teachings then provide for the control circuit receiving input from the user comprising a change (206) to at least one of these optimization objective values. By one approach the control circuit first accesses a prioritized list of clinical goals and automatically generates optimization objectives as a function of the prioritized list of clinical goals. The control circuit then generates a seed optimized radiation treatment plan as a function of the automatically generated optimization objectives and subsequently generates a collection of different radiation treatment plans by varying the automatically generated optimization objectives to thereby characterize a trade-off exploration space for the multi-criteria optimization workspace.
Abstract:
A control circuit (101) accesses (401) topograms (103) of a patient that include patient content that is beyond the portion of the patient that appears in the three-dimensional computed tomography (CT) images for that patient. The control circuit uses those topograms to derive (403) a virtual volumetric structure representing at least some of the patient content that is beyond the aforementioned portion of the patient that appears in the 3D CT images. That virtual volumetric structure can then be used (404) to predict potential collisions when assessing a radiation treatment plan for the patient that utilizes the aforementioned radiation treatment platform. By one approach the topograms include at least two substantially orthographic views of the aforementioned patient content.
Abstract:
These teachings provide for accessing optimization information (202) comprising at least one isocenter that corresponds to a body outline for a particular patient (104), field geometry information for a particular radiation treatment platform (114), and dosimetric data. The optimization information can further comprise a model of a body outline for the patient (104). A control circuit (101) optimizes a radiation treatment plan as a function of the optimization information to provide an optimized radiation treatment plan (113) where radiation dose levels delivered to the particular patient (104) from a particular field (403, 405) depends on the relative volume magnitude of field path intersections to thereby reduce radiation dose delivery to healthy patient tissue in regions having relatively more overlapping fields (403, 405).
Abstract:
A method of generating a treatment plan for treating a patient with radiotherapy, the method includes obtaining a plurality of sample plans, which are generated by use of a knowledge base comprising historical treatment plans and patient data. The method also includes performing a multi-criteria optimization based on the plurality of sample plans to construct a Pareto frontier, where the plurality of sample plans are evaluated with at least two objectives measuring qualities of the plurality of sample plans such that treatment plans on the constructed Pareto frontier are Pareto optimal with respect to the objectives. The method further includes identifying a treatment plan by use of the constructed Pareto frontier.