Optimization methods for radiation therapy planning

Patent metadata

Field	Value
Publication number	US-9844684-B2
Application number	US-201515304306-A
Country	US
Kind code	B2
Filing date	Apr 30, 2015
Priority date	Apr 30, 2014
Publication date	Dec 19, 2017
Grant date	Dec 19, 2017

Abstract

An optimization technique for use with radiation therapy planning that combines stochastic optimization techniques such as Particle Swarm Optimization (PSO) with deterministic techniques to solve for optimal and reliable locations for delivery of radiation doses to a targeted tumor while minimizing the radiation dose experienced by the surrounding critical structures such as normal tissues and organs.

First claim

The invention claimed is:

1. An optimization method for radiation therapy planning, comprising the steps of:
(a) modeling a tumor mass and a critical mass;
(b) positioning a plurality of static particles, each with its own potential function, to a surface of each of the tumor mass and the critical mass;
(c) placing a set of kinetic particles, each with its own potential function, to the surface of each of the tumor mass and the critical mass providing a first location of each kinetic particle creating a first location map;
(d) applying a momentum to each kinetic particle;
(e) computing a static potential field for the plurality of static particles and a dynamic potential field for the set of kinetic particles;
(f) calculating a force value incident upon each kinetic particle based on step (e);
(g) updating the first location of each kinetic particle to a second location based on the force value creating a second location map;
(h) repeating steps (e) through (g) until a variation of distance between the first location map and the second location map converges to less than a given threshold value or until a number of iterations reaches a certain threshold value;
(i) recording a final location for each kinetic particle; and
(j) translating the final location for each kinetic particle to define a plan for execution by one or more radiation sources.

2. The optimization method for radiation therapy planning according to claim 1 , further comprising the step of:
determining a length of time for delivering a radiation dose such that a dose distribution is as close to a prescribed ideal dose as possible.

3. The optimization method for radiation therapy planning according to claim 2 , wherein the determining step further comprises the step of using one or more algorithms selected from the following: least squares, non-negative least squares, least distance programming, linear programming, etc.

4. The optimization method for radiation therapy planning according to claim 2 , further comprising the step of:
creating a dose-volume histogram from the dose distribution.

5. The optimization method for radiation therapy planning according to claim 1 , wherein the force value incident upon each kinetic particle is a negative gradient of both the dynamic potential field and the static potential field.

6. The optimization method for radiation therapy planning according to claim 1 , wherein step (b) comprises placing the plurality of static particles randomly.

7. The optimization method for radiation therapy planning according to claim 1 , wherein the static potential field for the plurality of static particles corresponds to a prescribed dose distribution.

8. The optimization method for radiation therapy planning according to claim 1 , wherein the dynamic potential field for the set of kinetic particles corresponds to a dose distribution of the one or more radiation sources.

9. The optimization method for radiation therapy planning according to claim 8 , wherein the one or more radiation sources is a non-invasive stereotactic machine.

10. The optimization method for radiation therapy planning according to claim 8 , wherein the one or more radiation sources is a particle therapy machine.

11. The optimization method for radiation therapy planning according to claim 8 , wherein the one or more radiation sources is a lower dose rate brachytherapy seed.

12. The optimization method for radiation therapy planning according to claim 1 , wherein the momentum is zero.

13. An optimization method for radiation therapy planning, comprising the steps of:
(a) defining a tumor structure and one or more critical structures;
(b) positioning static particles, each with its own potential function, on a surface of the tumor structure and the one or more critical structures;
(c) placing kinetic particles, each with its own potential function, within a cross-section of the tumor structure;
(d) applying an initial velocity to the kinetic particles to create a location map of the kinetic particles; and
(e) computing a static potential field for the static particles and a dynamic potential field for the kinetic particles;
(f) calculating a force value incident upon each kinetic particle based on step (e);
(g) updating the first location map of the kinetic particles to a second location based on the force value creating a second location map;
(h) repeating steps (e) through (g) until a variation of distance between the first location map and the second location map converges to less than a given threshold value, a number of iterations have reached a certain threshold value, or the kinetic particles have traversed through the entire tumor structure;
(i) recording a final location and a trajectory for each kinetic particle based on steps (a) through (h);
(j) using a regression method to smooth the trajectories of the kinetic particles;
(k) translating the final location and the trajectory for each kinetic particle to define a treatment plan for execution by a radiation source; and
(l) executing the treatment plan by the radiation source.

14. The optimization method for radiation therapy planning according to claim 13 , wherein the treatment plan includes one or more selected from the group consisting of: interstitial implant trajectories and beam locations.

15. The optimization method for radiation therapy planning according to claim 13 , wherein the second location map includes the trajectories of the kinetic particles.

16. The optimization method for radiation therapy planning according to claim 13 , wherein the initial velocity is parallel to a principal implant direction of the radiation source.

17. The optimization method for radiation therapy planning according to claim 13 , wherein step (l) further comprises the steps of:
generating a radiation dose by the radiation source; and
applying the radiation dose according to the treatment plan.

18. The optimization method for radiation therapy planning according to claim 13 , further comprising the step of:
determining a length of delivery time of a radiation dose such that a dose distribution is within a prescribed ideal dose.

19. The optimization method for radiation therapy planning according to claim 18 , wherein the determining step further comprises the step of:
using one or more algorithms selected from the following group: least squares, non-negative least squares, least distance programming, linear programming, etc.

20. The optimization method for radiation therapy planning according to claim 13 , wherein the radiation source is a brachytherapy source including an Ir-192 source.

Assignees

• Stc Unm

Inventors

• Luan Shuang
• Riofrio Almeida Daniel Andres

Classifications

• A61N2005/101

  Magazines or cartridges for seeds · CPC title

• A61N5/1001

  using radiation sources introduced into or applied onto the body; brachytherapy · CPC title

• A61N2005/1024

  Seeds · CPC title

• A61N2005/1034

  Monte Carlo type methods; particle tracking · CPC title

• A61N5/103

  Treatment planning systems · CPC title