Systems and methods for automatic treatment planning and optimization
Systems and methods for the automatic generation and optimization of radiation therapy treatment plans, and systems and methods for the automatic generation and optimization of an adapted plan in an adaptive radiation therapy workflow.
1. An automatic treatment planning system, comprising:
a user interface; and
a processing device configured to:
receive, via the user interface, clinical data of a first data source and clinical data of a second data source, the second data source being of a different type than the first data source; and
execute a sequence of programmed instructions embodied on a computer-readable storage medium to generate one or more treatment plan candidates based on the received clinical data;
the processing device comprising a treatment planning module configured to:
derive a first set of objectives for the clinical data of the first data source;
derive a second set of objectives for the clinical data of the second data source;
combine the first set of objectives and the second set of objectives using a weighting factor; and
automatically generate one or more treatment plan candidates based on the weighted combination of the first set of objectives and the second set of objectives;
the processing device being further configured to send the treatment plan candidates to a controller of a treatment device to operate the treatment device according to a selected treatment plan candidate.
2. The system of claim 1 , wherein the first data source includes a prioritized set of clinical goals, and the second data source includes knowledge-based information.
3. The system of claim 2 , wherein the treatment planning module comprises:
a function generator configured to generate a cost function (C Total ) for the combined set of objectives; and
an optimizer configured to generate the one or more treatment plan candidates based on the generated cost function.
4. The system of claim 3 , wherein the treatment planning module is further configured to:
generate a first cost function (C G ) representing the first set of objectives; and
generate a second cost function (C K ) representing the second set of objectives;
wherein the cost function (C Total ) is a weighted combination of the first cost function and the second cost function (C Total =C G +mC K ).
5. The system of claim 4 , wherein the first cost function (C G ) is obtained via a goal-based approach, and the second cost function (C K ) is obtained via a knowledge-based approach.
6. The system of claim 5 , wherein the optimizer is further configured to determine treatment parameters for the treatment plan candidates, wherein the treatment parameters are executable by a processing unit of a treatment device to operate the treatment device according to the selected treatment plan candidate.
7. The system of claim 6 , wherein a first treatment plan candidate includes a weighting factor (m) of 10% for the second cost function, and a second treatment plan candidate includes a weighting factor (m) of 90% for the second cost function.
8. The system of claim 1 , further comprising a selector configured to allow for the selection by a user of a treatment plan candidate from the generated treatment plan candidates.
9. A method for automatically generating a plurality of treatment plan candidates, comprising:
executing a sequence of programmed instructions embodied on a computer-readable storage medium of a processing device to:
receive, via a user interface of the processing device, a first set of clinical data from a first data source, and a second set of clinical data from a second data source, the second data source being of different type than the first data source;
generate a first cost function for the first set of clinical data;
generate a second cost function for the second set of clinical data;
generate a cost function for the combined first and second set of clinical data, wherein the cost function is a weighted sum of the first cost function and the second cost function; and
generate a plurality of treatment plan candidates by optimizing the cost function, wherein the optimization is influenced by a weighting value of the second cost function,
the treatment plan candidates being configured to be supplied by the processing device to a controller of a treatment device to operate the treatment device according to a selected treatment plan candidate.
10. The method of claim 9 , wherein the first source of clinical data includes a prioritized set of clinical goals, and a second source of clinical data includes knowledge-based information.
11. The method of claim 10 , wherein the first cost function is obtained using a clinical goal-based approach, and the second cost function is obtained using a knowledge-based approach.
12. The method of claim 11 , wherein a first treatment plan candidate is obtained for a weighting value of 10% for the second cost function, and a second treatment plan is obtained for weighting value of 90% for the second cost function.
13. The method of claim 9 , further comprising:
selecting a treatment plan candidate from the plurality of treatment plan candidates; and
determining treatment parameters for the selected treatment plan candidate, the treatment parameters being executable by a processing unit of a treatment device to operate the treatment device according to the selected treatment plan candidate.