Correlation model selection for internal target movement

• US 20060074304A1
• Filed: 09/29/2005
• Published: 04/06/2006
• Est. Priority Date: 10/02/2004
• Status: Active Grant

• Current Assignee: Accuray Incorporated
• Original Assignee: Accuray Incorporated
• Inventors: Sayeh, Sohail
• Granted Patent: US 8,180,432 B2
• Time in Patent Office: Days
• US Class Current: 600/427
• CPC Class Codes: A61B 5/1127 using markers
• CPC Class Codes: A61B 5/113 occurring during breathing
• CPC Class Codes: A61B 6/4458 the source unit or the detector unit being attached to robotic arms
• CPC Class Codes: A61N 2005/1061 using an x-ray imaging system having a separate imaging source
• CPC Class Codes: A61N 5/1037 taking into account the movement of the target, e.g. 4D-image based planning
• CPC Class Codes: A61N 5/1049 for verifying the position of the patient with respect to the radiation beam
• CPC Class Codes: A61N 5/1064 for adjusting radiation treatment in response to monitoring
• CPC Class Codes: A61N 5/1067 in real time, i.e. during treatment
• CPC Class Codes: A61N 5/107 in real time, i.e. during treatment

Abstract

A method and apparatus to select a correlation model from a plurality of correlation models to track target movement based on movement of an external marker.

Claims

1. A method, comprising:

generating a plurality of models, each of the plurality of models descriptive of an internal path of movement over time of a target within a patient;

selecting one of the plurality of models; and

deriving a target position of the target based on the selected model.

2. The method of claim 1, wherein the plurality of models comprises a linear model or a non-linear model.

3. The method of claim 1, wherein the plurality of models comprises a non-linear model inclusive of a non-linear approximation to approximate the internal path of movement of the target.

4. The method of claim 1, wherein the plurality of models comprises a multi-linear model inclusive of a plurality of linear approximations to approximate the internal path of movement of the target, wherein the plurality of linear approximations comprise a first linear approximation connected to a second linear approximation at a non-zero angle.

5. The method of claim 1, wherein the plurality of models comprises a linear model inclusive of a linear approximation to approximate the internal path of movement of the target.

6. The method of claim 1, further comprising generating a plurality of estimation errors corresponding to the plurality of models, each estimation error descriptive of an approximate error distance between the target position and an actual location of the target.

7. The method of claim 6, wherein the selecting of one of the plurality of models is based on the plurality of estimation errors.

8. The method of claim 6, further comprising assigning a weighting factor to each of the plurality of models, wherein the generating of the plurality of estimation errors is based on the weighting factor corresponding to each of the plurality of models.

9. The method of claim 8, wherein the selecting of one of the plurality of models comprises comparing the plurality of estimation errors with one another and selecting the one of the plurality of models having the lowest estimation error at one of a plurality of displacement points.

10. The method of claim 1, further comprising:

sending a position signal associated with the target position to a beam generator controller; and

controlling a beam generator to direct a beam at the target.

11. The method of claim 1, further comprising:

deselecting the selected model, a first estimation error associated with the selected model; and

selecting another one of the plurality of models in response to a determination that a second estimation error associated with the other one of the plurality of models is lower than the first estimation error.

12. A machine readable medium having instructions thereon, which instructions, when executed by a digital processing device, cause the digital processing device to perform the method of claim 1.

13. An apparatus, comprising:

a treatment planning system coupled to a diagnostic imaging system and a treatment delivery system; and

a digital processing device coupled to the treatment planning system, the digital processing device configured to generate a plurality of correlation models descriptive of an internal path of movement of a target and to select one of the plurality of models to derive a target position of the target.

14. The apparatus of claim 13, wherein the plurality of models comprises a linear model, a multi-poly model, or a multi-linear model.

15. The apparatus of claim 13, wherein the digital processing device is further configured to generate a plurality of estimation errors corresponding to the plurality of models and to select one of the plurality of models based on the plurality of estimation errors.

16. The apparatus of claim 15, wherein the digital processing device is further configured to compare the plurality of estimation errors with one another and to select the one of the plurality of models having the lowest estimation error at one of a plurality of displacement points.

17. The apparatus of claim 13, wherein the digital processing device is further configured to assign a weighting factor to each of the plurality of models and to generate the plurality of estimation errors based on the weighting factor corresponding to each of the plurality of models.

18. The apparatus of claim 13, wherein the digital processing device is further configured to deselect the selected model, wherein a first estimation error is associated with the selected model, and to select another one of the plurality of models in response to a determination that a second estimation error associated with the other one of the plurality of models is lower than the first estimation error.

19. An apparatus, comprising:

means for generating a plurality of models, each of the plurality of models descriptive of an path of movement over time of a target;

means for determining which one of the plurality of models most closely approximates an actual position of the target at a specified displacement point; and

means for tracking the target using the one of the plurality of models that most closely approximates the actual position of the target.

20. The apparatus of claim 19, further comprising:

means for selecting one of the plurality of models; and

means for deriving a target position of the target based on the selected model.

21. The apparatus of claim 19, further comprising means for generating a plurality of estimation errors corresponding to the plurality of models, each estimation error indicative of an estimated difference between a displacement point on one of the plurality of models and an actual position of the target.