SYSTEM AND METHODS FOR ACCELERATING SIMULATION OF RADIATION TREATMENT

• US 20110202324A1
• Filed: 10/19/2009
• Published: 08/18/2011
• Est. Priority Date: 10/20/2008
• Status: Active Grant

• Current Assignee: Fred J. Currell, Marcus Mendenhall
• Original Assignee: Queen's University Belfast (Queen's University), Vanderbilt University
• Inventors: Currell, Fred, Mendenhall, Marcus
• Granted Patent: US 9,044,601 B2
• Time in Patent Office: Days
• US Class Current: 703/2
• CPC Class Codes: A61B 6/03 Computed tomography [CT] echo-tomography A61B8/14
• CPC Class Codes: A61N 2005/1034 Monte Carlo type methods; particle tracking
• CPC Class Codes: A61N 5/1031 using a specific method of dose optimization
• CPC Class Codes: G06F 30/20 Design optimisation, verification or simulation optimisation, verification or simulation of circuit designs G06F30/30

Abstract

A method for estimating a radiation dose and distribution for a target volume is provided. The method includes receiving a simulated dose array (606) describing a plurality of simulated dose values for a plurality of voxels in the target volume, generating an energy deposition coefficient function for the plurality of voxels (608), and obtaining a raw fluence array based at least on the simulated dose array and the energy deposition coefficient function (612). The method also includes generating an adjusted fluence array (613) based on the raw fluence array and at least one adjustment criteria, and generating an adjusted dose array (622) for the target volume based on the adjusted fluence array and the energy deposition coefficient function.

Claims

1-29. -29. (canceled)

30. A method for estimating a radiation dose and distribution for a target volume, the method comprising:

receiving a simulated dose array and a composition array, the dose array describing a plurality of simulated dose values for a plurality of voxels in the target volume, the composition array describing one or more compositions associated with each of the plurality of voxels in the target volume;

generating an energy deposition coefficient function for the plurality of voxels;

obtaining a raw fluence array based at least on the simulated dose array and the energy deposition coefficient function;

generating an adjusted fluence array based on the raw fluence array and at least one adjustment function;

generating an adjusted dose array for the target volume based on the adjusted fluence array and the energy deposition coefficient function.

31. The method of claim 30, wherein the generating the energy deposition coefficient function further comprises:

computing energy deposition coefficient values for each of the compositions in the target volume.

32. The method of claim 31, wherein the computing further comprises deriving the energy coefficient values such that differences in fluence values are minimized for the plurality of voxels along a border between a first of the compositions and a second of the compositions.

33. The method of claim 30, wherein the method further comprises

rescaling one of the simulated dose array and the composition array according to a plurality of scaling factors for each of the plurality of voxels, and

reversing the rescaling of the one of the simulated dose array and the composition array after the generating of the adjusted dose array.

34. The method of claim 30, wherein the adjustment function comprises a smoothing function that is a weighted convolution with a kernel having an anisotropy, wherein the anisotropy is based on the direction of the flux of particles used for generating the simulated dose array.

35. The method of claim 34, wherein the raw fluence array has a plurality of dimensions, and wherein the adjustment function specifies a kernel width for each of the plurality of dimensions, and wherein the applying the kernel function comprises:

extending the raw fluence array in each of the dimensions by at least 1½

times the kernel width for each of the plurality of dimensions to construct a padded fluence array;

constructing a padded kernel array based on the kernel function and the dimension of the padded fluence array; and

multiplying the padded fluence array by the padded kernel array to produce values for adjusted kernel array.

36. The method of claim 35, wherein the multiplying comprises a fast Fourier transform multiplication of the padded fluence array and the padded kernel array.

37. A radiation treatment system, comprising:

a storage element for receiving a simulated dose array and a composition array, the simulated dose array describing a plurality of simulated dose values for a plurality of voxels in a target volume comprising one or more different compositions, the composition array describing one or more compositions associated with the plurality of voxels in the target volume; and

a processing element configured for;

generating an energy deposition coefficient function for the plurality voxels;

obtaining a raw fluence array based at least on the simulated dose array and the energy deposition coefficient function,

generating an adjusted fluence array based on the raw fluence array and at least one adjustment function, and

generating an adjusted dose array for the target volume based on the adjusted fluence array and the energy deposition coefficient function.

38. The system of claim 37, wherein the processing element is further configured during the generating the energy deposition coefficient function for:

computing energy deposition coefficient values for each of the compositions in the target volume.

39. The system of claim 38, wherein the computing further comprises deriving the energy coefficient values such that differences in fluence values are minimized for the plurality of voxels along a border between a first of the compositions and a second of the compositions.

40. The system of claim 37, wherein the processing element is further configured during the obtaining the raw fluence array for:

rescaling one of the simulated dose array and the composition array according to a plurality of scaling factors for each of the plurality of voxels, and

reversing the rescaling of the one of the simulated dose array and the composition array after the generating of the adjusted dose array.

41. The system of claim 37, wherein wherein the adjusts function comprises a smoothing function that is a weighted convolution with a kernel having an anisotropy, wherein the anisotropy is based on the direction of the flux of particles used for generating the simulated dose array.

42. The system of claim 41, wherein the raw fluence array of dimensions, and wherein the adjustment function specifies a kernel width for each of the plurality of dimensions, and wherein the applying the kernel function comprises:

extending the raw fluence array in each of the dimensions by at least 1½

times the kernel for each of the plurality of dimensions to construct a padded fluence array;

constructing a padded kernel array based on the kernel function the dimension of the padded fluence array; and

multiplying the padded fluence array by the padded kernel array to produce values for adjusted kernel array.

43. The system of claim 42, wherein the multiplying comprises a fast Fourier transform multiplication of the padded fluence array and the padded kernel array.

44. A computer-readable medium, having stored thereon a computer program for estimating a radiation dose and distribution for a target volume, the computer program comprising a plurality of code sections, the code sections executable by a computer for causing the computer to perform the steps of:

receiving a simulated dose array and a composition array, the dose array describing a plurality of simulated dose values for a plurality of voxels in the target volume, the composition array describing one or more compositions associated with each of the plurality of voxels in the target volume;

generating energy deposition coefficient function for the plurality of voxels;

obtaining a raw fluence array based at least on the simulated dose array and the energy deposition coefficient function;

generating an adjusted fluence array based on the raw fluence array and at least one adjustment function;

generating an adjusted dose array for the target volume based on the adjusted fluence array and the energy deposition coefficient function.

45. The computer-readable medium of claim 44, wherein the code sections for generating the energy deposition coefficient function further comprise code sections for:

computing energy deposition coefficient values for each of the compositions in the target volume.

46. The computer-readable medium of claim 45, wherein the code sections for the computing further comprise code sections for deriving the energy coefficient values such that differences in fluence values are minimized for the plurality of voxels along a border between a first of the compositions and a second of the compositions.

47. The computer-readable medium of claim 44, further comprising code sections for:

rescaling one of the simulated dose array and the composition array according to a plurality of scaling factors for each of the plurality of voxels, and

reversing the rescaling of the one of the simulated dose array and the composition array after the generating of the adjusted dose array.

48. The computer-readable medium of claim 44, wherein the adjustment function comprises a smoothing function that is a weighted convolution with a kernel having an anisotropy, wherein the anisotropy is based on the direction of the flux of particles used for generating the simulated dose array.

49. The computer-readable medium of claim 48, wherein the raw fluence array has a plurality of dimensions, and wherein the adjustment function specifies a kernel width for each of the plurality of dimensions, and wherein the code sections for the applying the kernel function comprise code sections for:

extending the raw fluence array in each of the dimensions by at least 1½

times the kernel width for each of the plurality of dimensions to construct a padded fluence array;

constructing a padded kernel array based on the kernel function and the dimension of the padded fluence array; and

multiplying the padded fluence array by the padded kernel array to produce values for adjusted kernel array.

50. The computer-readable medium of claim 49, wherein the multiplying comprises a fast Fourier transform multiplication of the padded fluence array and the padded kernel array.