Method and apparatus to facilitate optimizing a radiation-treatment leaf-sequence plan
These teachings provide for identifying ( 101 ) a set of fluence-based control points to represent a leaf sequence and then selecting ( 102 ) a first subset of the fluence-based control points and optimizing that first subset. This first subset (now optimized) is combined ( 103 ) with a second subset of the fluence-based control points and the aggregation then optimized. The latter activities are then iteratively repeated ( 104 ) with additional subsets of the fluence-based control points to provide resultant optimized sets of fluence-based control points. This eventually results in a fully optimized complete set of fluence-based control points. This optimized set of fluence-based control points are then used ( 105 ) to specify a corresponding radiation-treatment leaf-sequence plan.
1. A method to facilitate optimizing a radiation-treatment leaf-sequence plan, comprising:
at a digital processor:
identifying a set of fluence-based control points to represent a leaf sequence;
selecting a first subset of the fluence-based control points and optimizing the first subset to provide an optimized first subset;
combining the optimized first subset with a second subset of the fluence-based control points and optimizing the combined first and second subset;
iteratively repeating the combining step with additional subsets of the fluence-based control points to provide a resultant optimized set of fluence-based control points;
using the optimized set of fluence-based control points to specify the radiation-treatment leaf-sequence plan.
2. The method of claim 1 wherein none of the subsets of the fluence-based control points overlap with one another.
3. The method of claim 1 wherein the radiation-treatment leaf-sequence plan comprises a plurality of treatment segments and wherein the leaf sequence comprises a corresponding leaf configuration for each of the segments.
4. The method of claim 1 wherein optimizing comprises using steepest descent-based optimization.
5. The method of claim 1 wherein optimizing comprising using simulated annealing-based optimization.
6. A radiation-treatment leaf-sequence plan optimizer comprising:
a memory having stored therein a set of fluence-based control points that represent a leaf sequence;
a control circuit operably coupled to the memory and being configured to:
select a first subset of the fluence-based control points and optimize the first subset to provide an optimized first subset;
combine the optimized first subset with a second subset of the fluence-based control points and optimize the combined first and second subset;
iteratively repeat the combining step with additional subsets of the fluence-based control points to provide a resultant optimized set of fluence-based control points;
use the optimized set of fluence-based control points to specify the radiation-treatment leaf-sequence plan.
7. The radiation-treatment leaf-sequence plan optimizer of claim 6 wherein none of the subsets of the fluence-based control points overlap with one another.
8. The radiation-treatment leaf-sequence plan optimizer of claim 6 wherein the radiation-treatment leaf-sequence plan comprises a plurality of treatment segments and wherein the leaf sequence comprises a corresponding leaf configuration for each of the segments.
9. The radiation-treatment leaf-sequence plan optimizer of claim 6 wherein the control circuit is configured to optimize by using steepest descent-based optimization.
10. The radiation-treatment leaf-sequence plan optimizer of claim 6 wherein the control circuit is configured to optimize by using simulated annealing-based optimization.
11. A method to facilitate optimizing a radiation-treatment leaf-sequence plan that includes a plurality of treatment segments, comprising:
at a digital processor:
identifying a set of fluence-based control points to represent a leaf sequence to accommodate each of the treatment segments;
selecting a first subset of the fluence-based control points and optimizing the first subset to provide an optimized first subset;
combining the optimized first subset with a second subset of the fluence-based control points that are different than the fluence-based control points that comprise the first subset and optimizing the combined first and second subset;
iteratively repeating the combining step with additional non-overlapping subsets of the fluence-based control points to provide a resultant optimized set of fluence-based control points;
using the optimized set of fluence-based control points to specify the radiation-treatment leaf-sequence plan.
12. The method of claim 11 wherein the radiation-treatment leaf-sequence plan comprises a radiation-treatment leaf-sequence plan for an arc therapy treatment.
13. The method of claim 11 wherein optimizing comprises using steepest descent-based optimization.
14. The method of claim 11 wherein optimizing comprising using simulated annealing-based optimization.