Abstract: In the context of a multi-criteria optimization workspace, a control circuit provides a user opportunity to modify 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 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.

Abstract: A search space used for multicriteria optimization in radiation treatment planning can be expanded using extrapolation. For instance, given an initial set of base plans, one or more virtual plans can be generated by assigning a weight to each base plan such that at least one of the weights is less than zero and/or such that the sum of the weights is not normalized to 1. The dose distribution for the virtual plan is computed as the weighted sum of the dose distributions of the base plans. Virtual plans criteria can be used together with the initial set of base plans to define an expanded search space within which interpolation can be performed to identify an optimal treatment plan.

Abstract: In the context of a multi-criteria optimization workspace, a control circuit provides a user opportunity to modify 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 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.

Abstract: A search space used for multicriteria optimization in radiation treatment planning can be expanded using extrapolation. For instance, given an initial set of base plans, one or more virtual plans can be generated by assigning a weight to each base plan such that at least one of the weights is less than zero and/or such that the sum of the weights is not normalized to 1. The dose distribution for the virtual plan is computed as the weighted sum of the dose distributions of the base plans. Virtual plans criteria can be used together with the initial set of base plans to define an expanded search space within which interpolation can be performed to identify an optimal treatment plan.

Abstract: A control circuit uses a (possibly self-generated) seed radiation treatment plan to identify a portion (possibly only a point) of a multi-criteria optimization (MCO)-based Pareto surface. The control circuit then selects a sampling plan set for MCO planning by enlarging that portion of the Pareto surface region to thereby facilitate developing an optimized radiation treatment plan. A radiation treatment platform then uses that optimized radiation treatment plan to treat a patient by administering the radiation in accordance with the plan.

Abstract: Computer-implemented methods and systems can be used to facilitate generation of VMAT treatment plans for providing radiation therapy to patients. Starting from a seed plan, a library of alternative plans, each with an associated outcome for a set of treatment objectives, can be generated via a set of parallel optimization operations performed on the seed plan. A graphical user interface is provided, via which the user can navigate within a treatment space defined by the alternative plans to identify a satisfactory outcome. Based on the satisfactory outcome and a candidate plan selected from the alternative plans, a deliverable VMAT treatment plan can be generated using another optimization operation.

Abstract: A control circuit utilizes patient information and treatment-platform information to optimize a radiation-treatment plan by permitting isocenters of various radiation-treatment fields as comprise parts of a same treatment plan to not be coincidental with one another to thereby yield an optimized treatment plan. The patient information can pertain to one or more physical aspects of the patient as desired. By one approach, the foregoing can comprise scattering the isocenters of the various radiation-treatment fields around a predetermined point (such as, for example, the center of the treatment volume and/or some or all of the beams). This approach can comprise causing an area of highest energy flux for a given field to be non-coincident for at least some of the radiation-treatment fields as are specified by the radiation-treatment plan.

Abstract: A control circuit utilizes patient information and treatment-platform information to optimize a radiation-treatment plan by permitting isocenters of various radiation-treatment fields as comprise parts of a same treatment plan to not be coincidental with one another to thereby yield an optimized treatment plan. The patient information can pertain to one or more physical aspects of the patient as desired. By one approach, the foregoing can comprise scattering the isocenters of the various radiation-treatment fields around a predetermined point (such as, for example, the center of the treatment volume and/or some or all of the beams). This approach can comprise causing an area of highest energy flux for a given field to be non-coincident for at least some of the radiation-treatment fields as are specified by the radiation-treatment plan.

Abstract: Computer-implemented methods and systems can be used to facilitate generation of VMAT treatment plans for providing radiation therapy to patients. Starting from a seed plan, a library of alternative plans, each with an associated outcome for a set of treatment objectives, can be generated via a set of parallel optimization operations performed on the seed plan. A graphical user interface is provided, via which the user can navigate within a treatment space defined by the alternative plans to identify a satisfactory outcome. Based on the satisfactory outcome and a candidate plan selected from the alternative plans, a deliverable VMAT treatment plan can be generated using another optimization operation.

Abstract: A control circuit utilizes patient information and treatment-platform information to optimize a radiation-treatment plan by permitting isocenters of various radiation-treatment fields as comprise parts of a same treatment plan to not be coincidental with one another to thereby yield an optimized treatment plan. The patient information can pertain to one or more physical aspects of the patient as desired. By one approach, the foregoing can comprise scattering the isocenters of the various radiation-treatment fields around a predetermined point (such as, for example, the center of the treatment volume and/or some or all of the beams). This approach can comprise causing an area of highest energy flux for a given field to be non-coincident for at least some of the radiation-treatment fields as are specified by the radiation-treatment plan.

Abstract: A control circuit uses a (possibly self-generated) seed radiation treatment plan to identify a portion (possibly only a point) of a multi-criteria optimization (MCO)-based Pareto surface. The control circuit then selects a sampling plan set for MCO planning by enlarging that portion of the Pareto surface region to thereby facilitate developing an optimized radiation treatment plan. A radiation treatment platform then uses that optimized radiation treatment plan to treat a patient by administering the radiation in accordance with the plan.

Abstract: A control circuit utilizes patient information and treatment-platform information to optimize a radiation-treatment plan by permitting isocenters of various radiation-treatment fields as comprise parts of a same treatment plan to not be coincidental with one another to thereby yield an optimized treatment plan. The patient information can pertain to one or more physical aspects of the patient as desired. By one approach, the foregoing can comprise scattering the isocenters of the various radiation-treatment fields around a predetermined point (such as, for example, the center of the treatment volume and/or some or all of the beams). This approach can comprise causing an area of highest energy flux for a given field to be non-coincident for at least some of the radiation-treatment fields as are specified by the radiation-treatment plan.

Abstract: A control circuit optimizes a radiation-treatment plan to provide an initially-optimized radiation-treatment plan and then modifies that initially-optimized radiation-treatment plan to reduce corresponding monitor units (MU's) to provide a radiation-treatment plan that is further optimized for monitor units. This modification can comprise, at least in part, imposing a stronger smoothing constraint with respect to fluence. Optimizing a radiation-treatment plan to provide an initially-optimized radiation-treatment plan can comprise identifying at least one particular leaf pair for a multi-leaf collimator that requires a longest amount of time to move into a position that achieves a particular desired fluence and then selectively smoothing position requirements of that particular leaf pair to reduce the amount of time associated with that particular leaf pair while not also smoothing position requirements for all leaf pairs as comprise that multi-leaf collimator.

Abstract: A control circuit optimizes a radiation-treatment plan to provide an initially-optimized radiation-treatment plan and then modifies that initially-optimized radiation-treatment plan to reduce corresponding monitor units (MU's) to provide a radiation-treatment plan that is further optimized for monitor units. This modification can comprise, at least in part, imposing a stronger smoothing constraint with respect to fluence. Optimizing a radiation-treatment plan to provide an initially-optimized radiation-treatment plan can comprise identifying at least one particular leaf pair for a multi-leaf collimator that requires a longest amount of time to move into a position that achieves a particular desired fluence and then selectively smoothing position requirements of that particular leaf pair to reduce the amount of time associated with that particular leaf pair while not also smoothing position requirements for all leaf pairs as comprise that multi-leaf collimator.