Target Region Partitioning in Radiation Therapy for minimising Irradiation of Non-target Tissue

• US 20180028837A1
• Filed: 10/15/2015
• Published: 02/01/2018
• Est. Priority Date: 10/15/2015
• Status: Active Grant

• Current Assignee: Brainlab AG
• Original Assignee: Brainlab AG
• Inventors: SCHAETTI, Andreas, SCHELL, Stefan, GRUMMT, Robert
• Granted Patent: US 10,639,500 B2
• Time in Patent Office: Days
• CPC Class Codes: A61N 2005/1087 Ions; Protons
• CPC Class Codes: A61N 5/103 Treatment planning systems
• CPC Class Codes: A61N 5/1047 with movement of the radiation head during application of radiation, e.g. for intensity modulated arc therapy or IMAT

Abstract

Disclosed is a method for determining an irradiation trajectory for the movement of a treatment device for irradiating an anatomical structure with ionising treatment radiation, the method comprising steps of

acquiring medical image data describing a medical image of the anatomical structure;
determining, based on the medical image data, image concavity data;
acquiring predetermined concavity data;
determining, based on the image concavity data and the predetermined concavity data, partition data;
determining, based on the medical image data, partition boundary data; and
determining, based on the partition boundary data, irradiation trajectory data.

Claims

1-15. -15. (canceled)

16. A method for determining an irradiation trajectory for the movement of a treatment device for irradiating an anatomical structure with ionising treatment radiation, the method comprising executing, on at least one processor of at least one computer, steps of:

a) acquiring, at the at least one processor, medical image data describing a medical image of the anatomical structure, wherein the anatomical structure comprises both a target region which defines a target of the irradiation and non-target tissue, wherein irradiation of the non-target tissue is to be avoided;

b) determining, by the at least one processor and based on the medical image data, image concavity data describing a value of a measure of concavity of at least part of the target region described by the medical image;

c) acquiring, at the at least one processor, predetermined concavity data describing a predetermined value of the measure of concavity for the at least part of the target region;

d) determining, by the at least one processor and based on the image concavity data and the predetermined concavity data, partition data describing whether the at least part of the target region is to be partitioned into target region partitions;

e) determining that the partitioning data describes that the target region is to be partitioned, and determining, by the at least one processor, in response to the determination that the target region is to be partitioned, and based on the medical image data, partition boundary data describing the position of a partition boundary between the target region partitions, wherein the position of the partition boundary is defined in a reference system in which positions in the medical image are defined; and

f) determining, by the at least one processor and based on the partition boundary data, irradiation trajectory data describing at least one trajectory of the treatment device usable for irradiating a target region partition with the ionising treatment radiation, wherein at least one trajectory is determined individually for each target region partition.

17. The method according to claim 16, wherein the image concavity data is determined by determining, by the at least one processor, the value of a concavity measure defined as a ratio of the volume of a convex hull of the target region and the volume of the target region.

18. The method according to claim 17, wherein the concavity is the topological concavity such that the convex hull is defined by all image units that lie on a straight line between any two image units of the at least part of the target region.

19. The method according to claim 16, wherein the at least part of the target region is itself a target region partition determined by executing steps a) to e).

20. The method according to claim 16, wherein the partition data is determined by comparing, by the at least one processor, the value of the measure of the concavity described by the image concavity data to the value of the measure of the concavity described by the predetermined concavity data.

21. The method according to claim 20, wherein comparing the value of the measure of the concavity described by the image concavity data to the value of the measure of the concavity described by the predetermined concavity data comprises determining, by the at least one processor, whether the value of the measure of the concavity described by the image concavity data is greater than the predetermined value of the measure of the concavity described by the predetermined concavity data.

22. The method according to claim 21, wherein the partition boundary data is determined in response to a determination that the value of the measure of the concavity described by the image concavity data is greater than the value of the measure of the concavity described by the predetermined concavity data.

23. The method according to claim 16, comprising:

acquiring, at the at least one processor, maximum target region partition data defining a predetermined maximum number of target region partitions into which the target region may be partitioned;

determining, by the at least one processor and based on the partition boundary data, target region partition number data describing the number of target region partitions into which the target region has already been partitioned;

determining, by the at least one processor and based on the maximum target region partition data and the target region partition number data, target region number comparison data indicating whether the number of target region partitions into which the target region has already been partitioned is greater than or equal to the maximum number of target region partitions into which the target region may be partitioned;

wherein the partition data is determined, by the at least one processor, to describe that the at least part of the target region is not to be partitioned into target region partitions, in response to a determination that the target region number comparison data indicates that the number of target region partitions into which the target region has already been partitioned is greater than or equal to the maximum number of target region partitions into which the target region may be partitioned.

24. The method according to claim 16, wherein determining the partition boundary data comprises:

determining, by the at least one processor and based on the medical image data and the partition boundary data, concavity sum data describing the sum of concavities of all target region partitions;

determining, by the at least one processor and based on the concavity sum data and the image concavity data, whether the sum of concavities of all target region partitions is less than the concavity of the at least part of the target region; and

accepting the assumed position of the boundary for further processing and stopping further partitioning of the at least part of the target region in response to a determination that the sum of concavities of all target region partitions is less than the concavity of the at least part of the target region.

25. The method according claim 16, wherein the partition boundary data is determined by applying, by the at least one processor, a skeletonizing algorithm to the representation of the target region in the medical image, and defining the boundary between the target region partitions such that an intersection area between a plane, representing the boundary and passing through an image unit on the skeleton, and the target region near this image unit on the skeleton is minimized or such that the plane representing the boundary is determined as passing through an image unit on the skeleton and being positioned in a direction perpendicular to the direction in which the part of the skeleton extends.

26. The method according to claim 16, wherein the partition boundary data is determined by determining, by the at least one processor and for each image unit in the medical image representing the target region, possibilities for positioning a boundary between target region partitions such that the sum of all individual concavities of the target region partitions is less than the concavity of the target region as a whole.

27. The method according to claim 16, comprising:

determining, by the at least one processor and based on the irradiation trajectory data, treatment plan data describing a treatment plan for conducting a medical procedure including irradiation of the anatomical structure with ionising radiation.

28. The method according to claim 27, wherein the medical procedure is radiotherapy or radiosurgery.

29. A non-transitory computer-readable storage medium having stored thereon computer-executable instructions that, when executed, configure at least one processor to:

a) acquire medical image data describing a medical image of the anatomical structure, wherein the anatomical structure comprises both a target region which defines a target of the irradiation and non-target tissue, wherein irradiation of the non-target tissue is to be avoided;

b) determine, based on the medical image data, image concavity data describing a value of a measure of concavity of at least part of the target region described by the medical image;

c) acquire predetermined concavity data describing a predetermined value of the measure of concavity for the at least part of the target region;

d) determine, based on the image concavity data and the predetermined concavity data, partition data describing whether the at least part of the target region is to be partitioned into target region partitions;

e) determine that the partitioning data describes that the target region is to be partitioned, and further determine, in response to the determination that the target region is to be partitioned, and based on the medical image data, partition boundary data describing the position of a partition boundary between the target region partitions, wherein the position of the partition boundary is defined in a reference system in which positions in the medical image are defined; and

f) determine, based on the partition boundary data, irradiation trajectory data describing at least one trajectory of the treatment device usable for irradiating a target region partition with the ionising treatment radiation, wherein at least one trajectory is determined individually for each target region partition.

30. A system for controlling an irradiation therapy device for use in a medical procedure involving irradiation of an anatomical structure with ionising radiation, the system comprising:

at least one processor configured to;

a) acquire medical image data describing a medical image of the anatomical structure, wherein the anatomical structure comprises both a target region which defines a target of the irradiation and non-target tissue, wherein irradiation of the non-target tissue is to be avoided;

b) determine, based on the medical image data, image concavity data describing a value of a measure of concavity of at least part of the target region described by the medical image;

c) acquire predetermined concavity data describing a predetermined value of the measure of concavity for the at least part of the target region;

d) determine, based on the image concavity data and the predetermined concavity data, partition data describing whether the at least part of the target region is to be partitioned into target region partitions;

e) determine that the partitioning data describes that the target region is to be partitioned, and further determine, in response to the determination that the target region is to be partitioned, and based on the medical image data, partition boundary data describing the position of a partition boundary between the target region partitions, wherein the position of the partition boundary is defined in a reference system in which positions in the medical image are defined; and

f) determine, based on the partition boundary data, irradiation trajectory data describing at least one trajectory of the treatment device usable for irradiating a target region partition with the ionising treatment radiation, wherein at least one trajectory is determined individually for each target region partition;

at least one electronic data storage device storing the medical image data and the predetermined concavity data, wherein the at least one processor is operably coupled to the at least one electronic data storage device for acquiring, from the at least one electronic data storage device, the medical image data and the predetermined concavity data; and

the irradiation therapy device which is configured to emit a beam of ionising treatment radiation, wherein the at least one processor is operatively coupled to the irradiation therapy device so as to effect emission of the treatment radiation by the irradiation therapy device based on the irradiation trajectory data.

31. The system according to claim 30, wherein the at least one processor determines the image concavity data by determining the value of a concavity measure defined as a ratio of the volume of a convex hull of the target region and the volume of the target region.

32. The system according to claim 31, wherein the concavity is the topological concavity such that the convex hull is defined by all image units that lie on a straight line between any two image units of the at least part of the target region.

33. The system according to claim 30, wherein the at least one processor determines the partition data by comparing the value of the measure of the concavity described by the image concavity data to the value of the measure of the concavity described by the predetermined concavity data.

34. The system according to claim 33, wherein the at least one processor compares the value of the measure of the concavity described by the image concavity data to the value of the measure of the concavity described by the predetermined concavity data by determining whether the value of the measure of the concavity described by the image concavity data is greater than the predetermined value of the measure of the concavity described by the predetermined concavity data.

35. The system according to claim 34, wherein the at least one processor determines the partition boundary data in response to a determination that the value of the measure of the concavity described by the image concavity data is greater than the value of the measure of the concavity described by the predetermined concavity data.