Fast generation of multi-leaf collimator (MLC) openings using hierarchical multi-resolution matching

Patent metadata

Field	Value
Publication number	US-12138481-B2
Application number	US-202017601121-A
Country	US
Kind code	B2
Filing date	Mar 27, 2020
Priority date	Apr 4, 2019
Publication date	Nov 12, 2024
Grant date	Nov 12, 2024

Abstract

A device for optimizing a radiation therapy plan ( 30 ) for delivering therapeutic radiation to a patient using a therapeutic radiation source ( 16 ) while modulated by a multi-leaf collimator (MLC) ( 14 ) includes at least one electronic processor ( 25 ) connected to a radiation therapy device ( 12 ). A non-transitory computer readable medium ( 26 ) stores instructions readable and executable by the at least one electronic processor to perform a radiation therapy plan optimization method ( 102 ) including: optimizing MLC settings of the MLC respective to an objective function wherein the MLC settings define MLC leaf tip positions for a plurality of rows of MLC leaf pairs at a plurality of control points (CPs). The optimizing is performed in two or more iterations with a resolution of the MLC settings increasing in successive iterations.

First claim

What is claimed is:

1. A device for optimizing a radiation therapy plan for delivering therapeutic radiation to a patient using a therapeutic radiation source while modulated by a multi-leaf collimator (MLC), the device comprising:
at least one electronic processor connected to a radiation therapy device; and
a non-transitory computer readable medium storing instructions readable and executable by the at least one electronic processor to perform a radiation therapy plan optimization method, the method comprising:
optimizing MLC settings of the MLC respective to an objective function wherein the MLC settings define MLC leaf tip positions for a plurality of rows of MLC leaf pairs at a plurality of control points (CPs),
wherein: the optimizing is performed in two or more iterations with a resolution of the MLC settings increasing in successive iterations; and the optimizing comprises reducing a travel range of the leaf tip positions and increasing a resolution of the leaf tip positions within the reduced travel range in the successive iterations.

2. The device of claim 1 , wherein the optimizing comprises:
in a first iteration, optimizing the MLC leaf tip positions over a coarse grid; and
in succeeding iterations, optimizing the MLC leaf tip positions over a finer grid than the last iteration until a mechanical resolution of the MLC leaf tips is reached.

3. The device of claim 1 , wherein the optimizing further comprises reducing a range constraint on the leaf tip positions in successive iterations.

4. The device of claim 1 , wherein the optimizing comprises increasing a number of rows of MLC leaf pairs in successive iterations.

5. The device of claim 4 , where the optimizing further comprises:
in a first iteration, reducing the number of rows of MLC leaf pairs compared with a physical number of rows of MLC leaf pairs in the MLC by grouping adjacent leaf rows such that the MLC settings are optimized over a coarse grid in a direction transverse to the rows; and
in succeeding iterations, grouping the leaf rows using a finer grid until the physical number of rows of the MLC leaf pairs in the MLC is reached.

6. The device of claim 4 , where the optimizing further comprises:
in a first iteration, reducing the number of rows of MLC leaf pairs compared with a physical number of rows of MLC leaf pairs in the MLC by selecting a sub-set of the leaf rows and interpolating unselected rows between the selected rows of the sub-set such that the MLC settings are optimized over a coarse grid in a direction transverse to the rows; and
in succeeding iterations, increasing the number of rows in the selected sub-set until the physical number of rows of the MLC leaf pairs in the MLC is selected.

7. The device of claim 1 , wherein the optimizing comprises controlling a number of angular positions of the CPs along a trajectory comprising an arc.

8. The device of claim 1 , wherein the radiation therapy plan optimization method further comprises:
optimizing a fluence map by optimizing beamlets at the CPs along a trajectory comprising an arc respective to clinical objectives of the radiation therapy plan; and
wherein the objective function is defined by the optimized fluence map.

9. The device of claim 1 , wherein the objective function comprises clinical objectives of the radiation therapy plan, the clinical objectives comprising a minimum number of leaf pairs in an opening, a minimum opening area, a smoothness of an opening, and or other characteristics of the shape of an opening.

10. The device of claim 1 , further comprising a radiation therapy device configured to deliver therapeutic radiation to the patient using the therapeutic radiation source of the radiation therapy device traversing a trajectory comprising arc while modulated by the MLC in accordance with a radiation therapy plan optimized by the radiation therapy plan optimization method;
wherein the traversing of the trajectory comprises moving the therapeutic radiation source along the arc.

11. A non-transitory computer readable medium storing instructions executable by at least one electronic processor to perform a radiation therapy plan optimization method, the method comprising:
optimizing multi-leaf collimator (MLC) settings of an MLC of a radiation therapy device respective to an objective function wherein the MLC settings define MLC leaf tip positions for a plurality of rows of MLC leaf pairs at a plurality of control points (CPs) along an arc,
wherein the optimizing is performed in two or more iterations with a resolution of the MLC settings increasing in successive iterations; and the optimizing comprises reducing a travel range of the leaf tip positions and increasing a resolution of the leaf tip positions within the reduced travel range in the successive iterations.

12. The non-transitory computer readable medium of claim 11 , wherein the optimizing comprises:
in a first iteration, optimizing the MLC leaf tip positions over a coarse grid; and
in succeeding iterations, optimizing the MLC leaf tip positions over a finer grid than the last iteration until a mechanical resolution of the MLC leaf tips is reached.

13. The non-transitory computer readable medium of claim 11 , wherein the optimizing further comprises reducing a range constraint on the leaf tip positions in successive iterations.

14. The non-transitory computer readable medium of claim 11 , wherein the optimizing further comprises increasing a number of rows of MLC leaf pairs in successive iterations.

15. The non-transitory computer readable medium of claim 14 , where the optimizing further comprises:
in a first iteration, reducing the number of rows of MLC leaf pairs compared with a physical number of rows of MLC leaf pairs in the MLC by grouping adjacent leaf rows such that the MLC settings are optimized over a coarse grid in a direction transverse to the rows; and
in succeeding iterations, grouping the leaf rows using a finer grid until the physical number of rows of the MLC leaf pairs in the MLC is reached.

16. The non-transitory computer readable medium of claim 11 , wherein the optimizing comprises optimizing angular positions of the CPs along the arc.

17. The non-transitory computer readable medium of claim 11 , wherein the radiation therapy plan optimization method further comprises:
optimizing a fluence map by optimizing beamlets at the CPs along the arc respective to clinical objectives of the radiation therapy plan;
wherein the objective function is defined by the optimized fluence map.

18. The non-transitory computer readable medium of claim 11 , wherein the objective function comprises clinical objectives of the radiation therapy plan.

19. A radiation therapy plan optimization method, comprising:
optimizing multi-leaf collimator (MLC) settings of an MLC of a radiation therapy device respective to an objective function wherein the MLC settings define MLC leaf tip positions for a plurality of rows of MLC leaf pairs at a plurality of control points (CPs) along the arc; and
delivering therapeutic radiation to the patient using a therapeutic radiation source of the radiation therapy device traversing the arc while modulated by the MLC in accordance with a radiation therapy plan;
wherein: the optimizing is performed in two or more iterations with a resolution of the MLC settings increasing in successive iterations; and the optimizing comprises reducing a travel range of the leaf tip positions and increasing a resolution of the leaf tip positions within the reduced travel range in the successive itera

Assignees

• Elekta Inc

Inventors

• Neukirchen Christoph
• Isola Alfonso Agatino
• Heese Harald Sepp
• Vik Torbjoern
• Weese Rolf Jürgen
• Bal Matthieu Frédéric

Classifications

• A61N5/1047

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

• G16H30/20

  for handling medical images, e.g. DICOM, HL7 or PACS · CPC title

• G16H20/40

  relating to mechanical, radiation or invasive therapies, e.g. surgery, laser therapy, dialysis or acupuncture · CPC title

• A61N5/1036 Primary

  Leaf sequencing algorithms · CPC title