Automated software system for beam angle selection in teletherapy
A novel approach to generating radiation treatment plans through a nested partitions framework provides an optimization of radiation delivery. The nested partitions approach couples beam angle selection and dose optimization to solve treatment planning problems. An optimal beam angle selection is provided to best treat tumors, while minimizing exposure to the surrounding healthy tissues.
1. A medical treatment planning system comprising:
a central processing unit (CPU) for performing computer executable instructions; and
a memory storage device storing computer executable instructions that when executed by the CPU cause the CPU to perform a process for generating a radiation treatment plan based in-part on a nested partition framework.
2. The system according to claim 1 , wherein the nested partition framework is configured to couple beam angle selection and dose optimization data associated with a patient.
3. The system according to claim 2 , wherein the beam angle selection includes a range of beam angles from about 1 beam angle to about 360 beam angles.
4. The system according to claim 1 , wherein the radiation treatment plan is configured for maximizing delivery of a radiation dose to a target tissue and minimizing radiation delivery to a healthy tissue adjacent the target tissue.
5. The system according to claim 1 , wherein the treatment plan is configured for use with intensity modulated radiation therapy (IMRT).
6. The system according to claim 1 , wherein the treatment plan is configured for use with three dimensional conformal radiation therapy (3D CRT).
7. The system according to claim 1 , wherein the radiation treatment plan is configured for the treatment of a patient's cancer.
8. A method of preparing a patient treatment plan comprising:
obtaining medical patient imaging data;
identifying a target tissue within a patient based in part on the imaging data; and
generating a treatment plan based in-part on a nested partition framework, the imaging data being used within the nested partition framework.
9. The method according to claim 8 , further comprising: obtaining patient specific dose data, wherein the dose data is used within the nested partition framework.
10. The method according to claim 8 , wherein the generating includes coupling of beam angle selection and dose optimization.
11. The method according to claim 10 , wherein the imaging data includes tissue distribution data that is a plurality of tissue dose distributions corresponding to beam's-eye-view single beam plans for a plurality of beam angles.
12. The method according to claim 10 , wherein an integer programming optimization model utilizes weighted combinations of mean organ dose data to generate a quality index for each beam angle.
13. The method according to claim 10 , wherein the nested partition framework constructs an initial promising region based upon a warm-start and subsequently applies a nested partition global viewpoint to seek improved beam sets.
14. The method according to claim 10 , wherein a high throughput computing system is employed for at least one of the steps, the high throughput computing system performing at least two steps in parallel.
15. The method according to claim 10 , wherein each single-beam plan is normalized, an average dose to a set of voxels in planning target volumes is the same for each plan.
16. The method according to claim 10 , wherein the beam angle selection includes a plurality of beam angles in a range from about 3 beam angles to about 10 beam angles.
17. The method according to claim 8 , wherein the treatment plan is prepared for intensity modulated radiation therapy (IMRT).
18. The method according to claim 8 , wherein the treatment plan is prepared for three dimensional conformal radiation therapy (3D CRT).
19. The method according to claim 8 , wherein dose data includes dose distributions corresponding to beam's eye view single beam treatment plans.
20. The method according to claim 8 , wherein the nested partition framework uses biased sampling to improve sample quality.
21. The method according to claim 8 , wherein the nested partition framework uses biased variables to improve the partitioning process.
22. The method according to claim 8 , wherein the nested partition framework uses a scoring method to evaluate sample quality.
23. A medical treatment planning system comprising:
a processor for performing computer executable instructions; and
a memory device storing computer executable instructions that when executed by the processor cause the processor to perform a process for generating a radiation treatment plan, the process performing an algorithmic coupling of beam angle selection and dose optimization within a nested partition framework.
24. The system according to claim 23 , wherein the processor is a high throughput computing system.
25. The system according to claim 24 , wherein the high throughput computing system is connected to a radiation treatment device.
26. The system according to claim 25 , wherein the radiation treatment device is configured for intensity modulated radiation treatment (IMRT).