Intensity-modulated proton therapy

• US 8,644,571 B1
• Filed: 12/05/2012
• Issued: 02/04/2014
• Est. Priority Date: 12/06/2011
• Status: Active Grant

• Current Assignee: LOMA Linda University Medical Center (Mission Healthcare Services LLC)
• Original Assignee: LOMA Linda University Medical Center (Mission Healthcare Services LLC), University of South Australia (University of Adelaide)
• Inventors: Schulte, Reinhard W., Burachik, Regina, Kaya, Yalcin
• Primary Examiner(s): Bayat, Ali
• Application Number:
  US13/705,903
• Time in Patent Office: 426 Days
• Field of Search: 382/100, 382/128, 378/65, 250/207, 250/310, 250/492.1, 250/492.2, 250/492.21, 250/396, 250/505.1, 250/494.1
• US Class Current: 382/128
• CPC Class Codes: A61N 2005/1087 Ions; Protons
• CPC Class Codes: A61N 5/1031 using a specific method of dose optimization
• CPC Class Codes: A61N 5/1039 using functional images, e.g. PET or MRI
• CPC Class Codes: A61N 5/1077 Beam delivery systems
• CPC Class Codes: A61N 5/1084 for delivering multiple intersecting beams at the same time, e.g. gamma knives

Abstract

The therapeutic treatment of a patient using intensity-modulated proton therapy is described. In one example, a method of creating a proton treatment plan is presented that divides volumes of interest into sub-volumes, applies dose constraints to the sub-volumes, finds one or more feasible configurations of a proton therapy system, and selects a proton beam configuration that improves or optimizes one or more aspects of proton therapy. In some implementations, the method of dividing volumes into sub-volumes includes creating fractional sub-volumes based at least in part on proximity to a target volume boundary. In some implementations, the method of finding an improved or optimal proton beam configuration from a set of feasible configurations includes finding a minimum of a cost function that utilizes weighting factors associated with treatment sites.

Claims

1. A method for performing intensity-modulated ion therapy, the method comprising:

obtaining a representation of a patient, the representation comprising information about structures within or on the patient;

identifying a volume of interest in the representation of the patient;

dividing the volume of interest into a plurality of sub-volumes;

for each of the plurality of sub-volumes, setting a dose constraint;

determining one or more ion treatment plans that satisfy the dose constraints for each of the plurality of sub-volumes;

from the one or more ion treatment plans, selecting an ion treatment plan that satisfies treatment criteria; and

delivering ions to the patient based on the selected ion treatment plan,

wherein dividing the volume of interest into a plurality of sub-volumes comprises;

dividing the volume of interest into a total number of voxels;

identifying one or more features of interest;

ordering the voxels according to increasing distance from a nearest feature of interest;

for each of the plurality of sub-volumes, selecting a fractional value corresponding to a ratio of a size of the sub-volume to a size of the volume of interest; and

for each of the plurality of sub-volumes, defining a sub-volume as a group of a number of consecutive voxels from the ordered voxels, wherein a ratio of the number of consecutive voxels to the total number of voxels is approximately equal to the fractional value for the sub-volume.

2. The method of claim 1, wherein the ions include protons.

3. The method of claim 1, wherein the ions include carbon ions.

4. The method of claim 1, wherein selecting an ion treatment plan that satisfies the treatment criteria comprises:

selecting an objective function;

selecting weighting factors associated with the objective function; and

determining the weighting factors that minimize the objective function.

5. The method of claim 1, wherein selecting an ion treatment plan that satisfies the treatment criteria comprises:

selecting an objective function;

selecting weighting factors associated with the objective function; and

determining the weighting factors that maximize the objective function.

6. The method of claim 1, wherein determining one or more ion treatment plans that satisfy the dose constraints for each of the plurality of sub-volumes comprises using an inverse problem solver to determine ion beam characteristics predicted to deliver radiation doses to the plurality of sub-volumes within the dose constraints.

7. An intensity-modulated ion therapy system comprising:

an ion delivery system configured to deliver a plurality of ions;

a physical processor configured to;

analyze a representation of a patient to identify a volume of interest;

divide the volume of interest into a total number of voxels;

identify one or more features of interest;

order the voxels according to increasing distance from a nearest feature of interest;

define a plurality of sub-volumes wherein a sub-volume comprises a set of a number of consecutive voxels from the ordered voxels, wherein a ratio of the number of consecutive voxels to the total number of voxels is approximately equal to a fractional value for the sub-volume;

set a dose constraint for each of the plurality of sub-volumes;

determine one or more ion treatment plans that satisfy the dose constraints for each of the plurality of sub-volumes; and

select an ion treatment plan that satisfies treatment criteria; and

a control system configured to control the ion delivery system to deliver the plurality of ions according to the selected ion treatment plan.

8. The system of claim 7, wherein the plurality of ions include protons.

9. The system of claim 7, wherein the plurality of ions include carbon ions.

10. The system of claim 7, further comprising an inverse problem solver module configured to determine ion beam characteristics predicted to deliver radiation doses to the plurality of sub-volumes within the dose constraints.

11. The system of claim 7, further comprising a forward problem solver module configured to determine predicted doses to a patient based on ion beam characteristics.

12. The system of claim 7, further comprising an improvement module configured to select the ion treatment plan that satisfies the treatment criteria, wherein the improvement module is configured to:

select an objective function;

select weighting factors associated with the objective function; and

determine the weighting factors that minimize the objective function.

13. The system of claim 7, further comprising an improvement module configured to select the ion treatment plan that satisfies the treatment criteria, wherein the improvement module is configured to:

select an objective function;

select weighting factors associated with the objective function; and

determine the weighting factors that maximize the objective function.

14. A tangible, non-transitory computer readable storage medium having computer-executable instructions stored thereon, the computer-executable instructions readable by a computing system comprising one or more computing devices, wherein the computer-executable instructions are executable on the computing system in order to cause the computing system to perform operations comprising:

obtaining a representation of a patient, the representation comprising information about structures within or on the patient;

identifying a volume of interest in the representation of the patient;

dividing the volume of interest into a plurality of sub-volumes;

for each of the plurality of sub-volumes, setting a dose constraint;

determining one or more ion treatment plans that satisfy the dose constraints for each of the plurality of sub-volumes;

from the one or more ion treatment plans, selecting an ion treatment plan that satisfies treatment criteria; and

delivering ions to the patient based on the selected ion treatment plan,

wherein dividing the volume of interest into a plurality of sub-volumes comprises;

dividing the volume of interest into a total number of voxels;

identifying one or more features of interest;

ordering the voxels according to increasing distance from a nearest feature of interest;

for each of the plurality of sub-volumes, selecting a fractional value corresponding to a ratio of a size of the sub-volume to a size of the volume of interest; and

for each of the plurality of sub-volumes, defining a sub-volume as a group of a number of consecutive voxels from the ordered voxels, wherein a ratio of the number of consecutive voxels to the total number of voxels is approximately equal to the fractional value for the sub-volume.