SYSTEM AND METHOD OF CALCULATING DOSE UNCERTAINTY

• US 20100054413A1
• Filed: 08/28/2009
• Published: 03/04/2010
• Est. Priority Date: 08/28/2008
• Status: Active Grant

• Current Assignee: Accuray Incorporated
• Original Assignee: TomoTherapy Incorporated (Accuray Incorporated)
• Inventors: Sobering, Geoff, Ruchala, Kenneth J., Schnarr, Eric
• Granted Patent: US 8,363,784 B2
• Time in Patent Office: Days
• US Class Current: 378/65
• CPC Class Codes: A61N 5/1031 using a specific method of dose optimization
• CPC Class Codes: G16H 20/40 relating to mechanical, radiation or invasive therapies, e.g. surgery, laser therapy, dialysis or acupuncture
• CPC Class Codes: G16H 40/63 for local operation

Abstract

A dose calculation tool operable to generate a variance map that represents a dose uncertainty. The variance map illustrates on a point-by-point basis where high uncertainty in the dose may exist and where low uncertainty in the dose may exist. The dose uncertainty is a result of an error in one or more data parameters related to a delivery parameter or a computational parameter.

Claims

1. A method of evaluating dosimetric uncertainties for a radiation delivery, the method comprising:

generating a treatment plan for a patient, the treatment plan including a dose to be delivered to the patient using a radiation delivery device;

identifying a data parameter for the radiation delivery device; and

generating a variance map utilizing a dose calculation module, the variance map representing an uncertainty indication in the dose to be delivered to the patient, the uncertainty indication related to the data parameter.

2. The method of claim 1 further comprising optimizing the treatment plan for the patient to reduce the variance.

3. The method of claim 2 wherein optimizing the treatment plan includes using the uncertainty indication for the data parameter as a constraint when determining a setting of the data parameter.

4. The method of claim 2 wherein optimizing the treatment plan includes reducing reliance on a particular leaf of a multi-leaf collimator that has a greater uncertainty.

5. The method of claim 2 wherein optimizing the treatment plan includes adjusting an isocenter of the treatment plan to reduce impact of uncertainties due to one of multi-leaf collimator position and jaw position.

6. The method of claim 2 wherein optimizing the treatment plan includes adjusting a fraction of leaf open time in projections to reduce uncertainties in leaf timing.

7. The method of claim 2 wherein optimizing the treatment plan includes reducing the treatment plan'"'"'s dependence on gantry angles that have higher radiation delivery device output uncertainty or shoot through regions of space that are affected by couch top position uncertainty.

8. The method of claim 2 wherein optimizing the treatment plan includes reducing the variance for a particular area in the patient.

9. The method of claim 2 further comprising evaluating deliverability of the optimized treatment plan.

10. The method of claim 2 wherein optimizing the treatment plan includes selecting a different radiation delivery device to deliver the treatment plan to the patient.

11. The method of claim 1 further comprising generating a plurality of treatment plans and selecting one of the treatment plans to deliver to the patient based on the variance map.

12. The method of claim 1 wherein the data parameter is related to a delivery parameter of the radiation delivery device.

13. The method of claim 1 wherein the data parameter includes a combination of multiple single data parameters.

14. The method of claim 1 wherein the data parameter is fluence.

15. The method of claim 1 wherein the data parameter is linac output.

16. The method of claim 1 wherein the data parameter is leaf timing.

17. The method of claim 1 wherein the data parameter is jaw position.

18. The method of claim 1 wherein the data parameter is spectral changes in attenuation/energy components of a radiation beam.

19. The method of claim 1 wherein the data parameter is couch position.

20. The method of claim 1 wherein the data parameter is gantry position.

21. The method of claim 1 wherein the data parameter is related to a modeling parameter of the radiation delivery device.

22. The method of claim 1 wherein the data parameter is one of leaf size and shape.

23. The method of claim 1 wherein the data parameter is jaw shape.

24. The method of claim 1 wherein the data parameter is related to tongue and groove information of two adjacent leaves.

25. The method of claim 1 wherein the data parameter is source-to-axis distance.

26. The method of claim 1 wherein the data parameter is related to a change in beam shape.

27. The method of claim 1 further comprising generating an alert when the variance map indicates that the uncertainty in dose exceeds a predetermined threshold.

28. The method of claim 1 wherein the radiation delivery device delivers photon-based radiation therapy.

29. The method of claim 1 wherein the radiation delivery device delivers ion-based or particle-based radiation therapy.

30. A method of detecting a delivery error in a radiation delivery device, the method comprising using a computer to carry out the steps of:

generating a treatment plan for a patient, the treatment plan including an intended fluence;

delivering radiation to the patient according to the treatment plan;

acquiring output fluence information from the radiation delivery device after delivery of the treatment plan;

comparing the output fluence information and the intended fluence to determine a fluence variance; and

applying a dose calculation algorithm to the fluence variance to generate a dose variance map.

31. The method of claim 30 wherein the fluence variance is based on feedback from the radiation delivery device over the course of a plurality of treatments.

32. The method of claim 30 further comprising modifying the treatment plan based on the fluence variance.

33. The method of claim 30 further comprising generating a new treatment plan based on the fluence variance.

34. The method of claim 30 further comprising selecting a different radiation delivery device to deliver the treatment plan based on the fluence variance.

35. The method of claim 30 further comprising modifying the treatment plan based on anticipated changes to the radiation delivery device.

36. The method of claim 30 further comprising displaying the dose variance map.

37. The method of claim 30 wherein the dose variance map represents an uncertainty indication in the dose to be delivered to the patient, the uncertainty indication related to a data parameter of the radiation delivery device.

38. The method of claim 37 wherein the data parameter includes a combination of multiple single data parameters.

39. The method of claim 37 wherein the data parameter is fluence.

40. The method of claim 37 wherein the data parameter is linac output.

41. The method of claim 37 wherein the data parameter is leaf timing.

42. The method of claim 37 wherein the data parameter is jaw position.

43. The method of claim 37 wherein the data parameter is couch position.

44. The method of claim 37 wherein the data parameter is gantry position.

45. A method of evaluating a partially delivered treatment plan, the method comprising:

generating a treatment plan for a patient, the treatment plan including a plurality of treatment fractions and intended variance information;

delivering at least one of the treatment fractions to the patient according to the treatment plan;

acquiring output fluence information from a radiation delivery device after delivery of the treatment fraction; and

evaluating future treatment fractions based on a combination of the intended variance information and the output fluence information.

46. The method of claim 45 further comprising adjusting a future treatment fraction based on the combination.

47. The method of claim 45 further comprising selecting a radiation delivery device to deliver the treatment plan to the patient based on the combination.