Therapy planning

1. A method of reducing radiation dose to healthy tissue near a target volume, comprising:

generating a dynamic planned target volume (PTV) for each of a plurality of motion phases of the target volume identified in a 4D motion model generated by tracking motion of a target volume during computed tomography (CT) data acquisition, wherein the motion phases are identified from one or more CT images reconstructed from acquired CT data;

tracking the target volume; and

at each motion phase of the target volume:

selecting a dynamic PTV corresponding to the motion phase to cover the target volume; and

determining multi-leaf collimator leaf positions and outputting instructions for irradiating the selected dynamic PTV at each motion phase of the target volume.

2. The method according to claim 1 , further comprising:

binning the 4D CT images of the target volume in the motion model into N motion phases, where N is an integer greater than 1.

3. The method according to claim 2 , further comprising:

computing motion estimation parameters for each tracked position of the target volume.

4. The method according to claim 3 , wherein the motion estimation parameters comprise one or more of:

target volume translations;

target volume rotations;

scale factors; and

deformable vector fields.

5. The method according to claim 3 , further comprising:

linking, to each of the N motion phases, at least one set of motion estimation parameters.

6. The method according to claim 5 , further comprising:

generating and linking a dynamic PTV that covers the target volume in each motion phase using the motion estimation parameters, in order to create a one-to-one mapping of dynamic PTVs to motion phases.

7. The method according to claim 5 , further comprising:

generating and linking a dynamic PTV for the target volume across multiple motion phases using the motion estimation parameters, in order to generate a many-to-one mapping of dynamic PTVs to motion phases, wherein at least two dynamic PTVs are generated to cover all motion phases of the target volume.

8. The method according to claim 1 , wherein the target volume is tracked using one or more of:

electromagnetic tracking;

surface tracking;

external fiducial tracking; and

internal anatomical marker tracking.

9. The method according to claim 1 , wherein the target volume is tracked using optical shape sensing.

10. A non-transitory computer-readable medium having stored thereon computer-executable instructions for performing the method according to claim 1 .

11. A therapy planning system that facilitates reducing radiation dose to healthy tissue near a target volume, comprising:

a tracking module that tracks target volume motion using one or more 4D computed tomography (CT) images reconstructed from acquired CT scan data of the target volume;

a processor configured to:

generate a 4D motion model for the target volume using tracking information generated by the tracking module;

generate a dynamic planned target volume (PTV) for each of a plurality of motion phases of the target volume identified in the motion model; and

a motion estimation tool configured to track the target volume;

wherein the processor is further configured to, at each motion phase of the target volume:

select a dynamic PTV corresponding to the motion phase to cover the target volume; and

determine multi-leaf collimator leaf positions and output instructions for irradiating the selected dynamic PTV at each motion phase of the target volume.

12. The system according to claim 11 , wherein the processor is further configured to:

bin the 4D CT images of the target volume in the motion model into N motion phases, where N is an integer greater than 1.

13. The system according to claim 12 , wherein the processor is further configured to:

compute motion estimation parameters for each tracked position of the target volume.

14. The system according to claim 13 , wherein the motion estimation parameters comprise one or more of:

target volume translations;

target volume rotations;

scale factors; and

deformable vector fields.

15. The system according to claim 13 , wherein the processor is further configured to:

link, to each of the N motion phases, at least one set of motion estimation parameters.

16. The system according to claim 15 , wherein the processor is further configured to:

generate and link a dynamic PTV that covers the target volume in each motion phase using the motion estimation parameters, in order to create a one-to-one mapping of dynamic PTVs to motion phases.

17. The system according to claim 15 , wherein the processor is further configured to:

generate and link a dynamic PTV for the target volume across multiple motion phases using the motion estimation parameters, in order to generate a many-to-one mapping of dynamic PTVs to motion phases, wherein at least two dynamic PTVs are generated to cover all motion phases of the target volume.

18. The system according to claim 11 , wherein the tracking module employs one or more of:

electromagnetic tracking;

surface tracking;

external fiducial tracking; and

internal anatomical marker tracking.

19. The system according to claim 11 , wherein the tracking module tracks the target volume using optical shape sensing.

20. A method of reducing radiation dose to healthy tissue near a target volume, comprising:

providing tracked target volume position information from a 4D motion model of the target volume to a motion estimation tool;

linking motion parameter information output from the motion estimation tool to motion phases of the target volume indicated by CT scan data;

generating a dynamic planned target volume (PTV) that covers the target volume in each motion phase;

linking the dynamic PTV for each motion phase to tracked motion parameters for each respective motion phase; and

determining multi-leaf collimator leaf positions and outputting instructions for irradiating the PTV for each motion phase.