Warm start initialization for external beam radiotherapy plan optimization

Patent metadata

Field	Value
Publication number	US-11147985-B2
Application number	US-201816481998-A
Country	US
Kind code	B2
Filing date	Jan 24, 2018
Priority date	Feb 2, 2017
Publication date	Oct 19, 2021
Grant date	Oct 19, 2021

Abstract

The invention relates to a dynamic sliding-window-like initialization for, for example, iterative VMAT algorithms. Specifically, a dynamic sliding window conversion method is contemplated where typical dynamic VMAT constraints are taken into account to find an optimal set of suitable openings (i.e. binary masks) that can be used as quasi-feasible start initialization for any VMAT algorithm that can refine until a deliverable plan is reached. Here, a multileaf leaf tip trajectory least square constrained optimization is performed to find a set of optimal unidirectional trajectories for all MLC leaf pairs of all arc points. To ensure that a quasi-feasible (or better quasi-deliverable) solution is returned, for example, a maximum dose rate, a maximum gantry speed, a maximum leafs speed, and a maximum treatment time may be enforced.

First claim

The invention claimed is:

1. A computer-implemented method of generating an input for an optimization of an external beam radiotherapy plan for a multileaf collimator, the computer-implemented method comprising:
obtaining information indicative of a desired dosage and/or an intensity distribution;
solving, for each arc angular sector of a plurality of arc angular sectors a constrained optimization problem to obtain leaf tip trajectories or leaf tip positions reflecting the desired dosage and/or the intensity distribution, wherein constraints of the constrained optimization problem include static constraints and/or dynamic constraints as to the multileaf collimator;
calculating a plurality of binary masks for the plurality of the arc angular sectors, respectively, each binary mask of the plurality of binary masks indicating an exposure of bixels by the multileaf collimator; and
providing the plurality of binary masks as an input for the optimization of the external beam radiotherapy plan.

2. The computer-implemented method according to claim 1 , wherein the external beam radiotherapy plan comprises a volumetric modulated arc therapy, the computer-implemented method further comprising:
normalizing the leaf tip trajectories to a travel time.

3. The computer-implemented method according to claim 1 , wherein the constrained optimization problem comprises a least-square optimization problem.

4. The computer-implemented method according to claim 1 , wherein obtaining the information indicative of the desired dosage and/or the intensity distribution includes obtaining and de-noising a target fluence map.

5. The computer-implemented method according to claim 1 , wherein the external beam radiotherapy plan comprises a volumetric modulated arc therapy and the leaf tip trajectories comprise unidirectional moving trajectories.

6. The computer-implemented method according to claim 1 , wherein the external beam radiotherapy plan comprises a volumetric modulated arc therapy, and wherein the constraints of the constrained optimization problem include limits as to one or more slopes of the leaf tip trajectories, an avoidance of leaf tip crashing, a minimum leaf gap, a minimum leaf tip inter-digitation, jaws movement, a fluence rate, and/or a gantry speed.

7. The computer-implemented method according to claim 1 , wherein the external beam radiotherapy plan comprises a volumetric modulated arc therapy, and wherein solving, for each arc angular sector of the plurality of arc angular sectors, the constrained optimization problem comprises setting initial leaf tip trajectories to zero.

8. The computer-implemented method according to claim 1 , further comprising:
generating the plurality of binary masks for an optimization of the external beam radiotherapy plan.

9. The computer-implemented method according to claim 1 , wherein the constraints of the constrained optimization problem further include constraints as to an energy source.

10. A device for generating an input for an optimization of an external beam radiotherapy plan for a multileaf collimator, comprising:
a processor; and
a non-transitory medium for storing instructions, that when executed by the processor, cause the processor to:
obtain information indicative of a desired dosage and/or an intensity distribution;
solve a constrained optimization problem for each arc angular sector of a plurality of arc angular sectors to obtain leaf tip trajectories or leaf tip positions reflecting the desired dosage and/or the intensity distribution, wherein constraints of the constrained optimization problem include static constraints and/or dynamic constraints as to the multileaf collimator;
calculate a plurality of binary masks for the plurality of the arc angular sectors, respectively, each binary mask of the plurality of binary masks indicating an exposure of bixels by the multileaf collimator; and
provide the plurality of binary masks as an input for the optimization of the external beam radiotherapy plan.

11. The device of claim 10 , wherein the external beam radiotherapy plan comprises a volumetric modulated arc therapy, and wherein the instructions further cause the processor to:
normalize the leaf tip trajectories to a travel time.

12. The device of claim 10 , wherein the constrained optimization problem comprises a least-square optimization problem.

13. The device of claim 10 , wherein the instructions further cause the processor to:
obtain the information indicative of the desired dosage and/or the intensity distribution by obtaining and de-noising a target fluence map.

14. The device of claim 10 , wherein the external beam radiotherapy plan comprises a volumetric modulated arc therapy and the leaf tip trajectories comprise unidirectional moving trajectories.

15. The device of claim 10 , wherein the external beam radiotherapy plan comprises a volumetric modulated arc therapy, and wherein the constraints of the constrained optimization problem include limits as to one or more slopes of the leaf tip trajectories, an avoidance of leaf tip crashing, a minimum leaf gap, a minimum leaf tip inter-digitation, jaws movement, a fluence rate, and/or a gantry speed.

16. The device of claim 10 , wherein the external beam radiotherapy plan comprises a volumetric modulated arc therapy, and wherein the instructions further cause the processor to:
solve the constrained optimization problem for each arc angular sector of the plurality of arc angular sectors by setting initial leaf tip trajectories to zero.

17. The device of claim 10 , wherein the instructions further cause the processor to:
generate the plurality of binary masks for an optimization of the external beam radiotherapy plan.

18. A non-transitory computer readable medium that stores instructions that, when executed by a processor, cause the processor to:
obtain information indicative of a desired dosage and/or an intensity distribution;
solve a constrained optimization problem for each arc angular sector of a plurality of arc angular sectors to obtain leaf tip trajectories reflecting the desired dosage and/or the intensity distribution, wherein constraints of the constrained optimization problem include static constraints and/or dynamic constraints as to a multileaf collimator;
calculate a plurality of binary masks for the plurality of the arc angular sectors, respectively, each binary mask of the plurality of binary masks indicating an exposure of bixels by the multileaf collimator; and
provide the plurality of binary masks as an input for an optimization of an external beam radiotherapy plan for the multileaf collimator.

19. The non-transitory computer readable medium of claim 18 , wherein the constrained optimization problem comprises a least-square optimization problem.

20. The non-transitory computer readable medium of claim 18 , wherein the instructions further cause the processor to:
obtain the information indicative of the desired dosage and/or the intensity distribution by obtaining and de-noising a target fluence map.

Assignees

• Koninklijke Philips Nv

Inventors

• Isola Alfonso Agatino
• Neukirchen Christoph
• Vik Torbjoern
• Heese Harald Sepp
• Weese Rolf Juergen

Classifications

• A61N5/1036

  Leaf sequencing algorithms · CPC title

• A61N5/1047

  with movement of the radiation head during application of radiation, e.g. for intensity modulated arc therapy or IMAT · CPC title

• A61N5/1045

  using a multi-leaf collimator, e.g. for intensity modulated radiation therapy or IMRT · CPC title

• A61N5/10

  X-ray therapy; Gamma-ray therapy; Particle-irradiation therapy (A61N5/01 takes precedence) · CPC title

• A61N5/1042

  with spatial modulation of the radiation beam within the treatment head · CPC title