Methods and apparatus for detecting and responding to weighted editing of radiotherapy planning points

Abstract

Various embodiments of this disclosure relate to a method and apparatus for detecting and responding to edits to point weights in a radiotherapy plan. The radiotherapy plan is optimized for a specific patient, providing corresponding synthetic radiation dose information. Such optimization may include calculating a corresponding influence matrix. Upon detection of at least one manual edit to at least one point weight corresponding to the radiotherapy plan, these teachings may responsively generate new radiation dose information based on the corresponding influence matrix, at least in near real-time.

Description

Technical Field

[0001] These teachings generally involve the planned target volume of energy used to treat patients according to an energy-based treatment plan, and more specifically, modifications in response to radiation dose information. Background Technology

[0002] The use of energy to treat medical conditions encompasses the known field of existing technology. For example, radiation therapy is a crucial component of many treatment programs used to reduce or eliminate unwanted tumors. Unfortunately, the applied energy cannot inherently distinguish between unwanted substances and adjacent tissues, organs, etc., which are necessary or even essential for the patient's continued survival. As a result, energy (such as radiation) is often applied in a carefully managed manner, at least attempting to confine the energy to a given target volume. So-called energy-based treatment programs typically function in this regard.

[0003] Energy-based treatment plans, such as radiotherapy plans, typically involve specified values ​​for various treatment platform parameters during each of multiple consecutive fields. Treatment plans for radiotherapy sessions are often generated through a process known as optimization. As used herein, "optimization" will be understood as improving candidate treatment plans without necessarily ensuring that the result of optimization is actually a single optimal solution. Such optimizations typically involve automatically adjusting one or more treatment parameters (often while simultaneously observing one or more corresponding constraints on these aspects) and mathematically calculating possible corresponding treatment outcomes to identify a given set of treatment parameters that represents a good trade-off between desired therapeutic results and the avoidance of undesirable side effects.

[0004] Unfortunately, existing optimization techniques do not necessarily address all potential needs of all patients in all potential application settings. As an example, modulated proton scans typically require optimization of so-called spot locations and spot weights to obtain optimal dose and dose rate. However, automated optimization of spot locations and weights does not always yield satisfactory results.

[0005] It is possible to manually edit point weights after optimization to improve expected results in problematic areas (or alternatively, the optimization algorithm can be continued to add or change optimization criteria to seek better results). However, existing methods in these areas require recalculating the dosage to observe and evaluate the results of such modifications. Furthermore, multiple such recalculations may be necessary to test / evaluate different adjustments to the plan. These methods can be quite time-consuming, sometimes taking several hours. This time consumption is inconvenient, at least for both the patient and the technician / physician(s), and as a result, a less-than-ideal plan may be identified. Attached Figure Description

[0006] The above-mentioned needs are at least partially met by providing the method and apparatus for detecting and responding to radiotherapy planning point weighting as described in the following detailed description, especially when studied in conjunction with the accompanying drawings, in which:

[0007] Figure 1 Block diagrams containing various embodiments configured according to these teachings;

[0008] Figure 2 Flowcharts containing various embodiments configured according to these teachings;

[0009] Figure 3 Includes illustrative screenshots of various embodiments configured according to these teachings;

[0010] Figure 4 Includes illustrative screenshots of various embodiments configured according to these teachings;

[0011] Figure 5 Includes illustrative screenshots of various embodiments configured according to these teachings;

[0012] Figure 6 Includes illustrative screenshots of various embodiments configured according to these teachings;

[0013] Figure 7 Includes illustrative screenshots of various embodiments configured according to these teachings; and

[0014] Figure 8 The diagram includes various embodiments configured according to these teachings.

[0015] The elements in the figures are illustrated for simplicity and clarity and are not necessarily drawn to scale. For example, the size and / or relative position of some elements in the figures may be exaggerated relative to other elements to aid in understanding the various embodiments of this teaching. Furthermore, common but well-known elements that are useful or necessary in commercially viable embodiments are not typically depicted to facilitate less obstructed views of these different embodiments of this teaching. Certain actions and / or steps may be described or depicted in a particular sequence of occurrence, and those skilled in the art will understand that such specificity regarding the sequence is not actually necessary. The terms and expressions used herein have the ordinary technical meaning consistent with those given by those skilled in the art, unless otherwise given a different specific meaning. Unless specifically indicated, the word “or” as used herein should be interpreted as having a separate construction rather than a connected construction. Detailed Implementation

[0016] Generally speaking, these different implementations help optimize patient treatment plans to deliver therapeutic energy, such as proton beams, to specific patients.

[0017] Through a method, these teachings optimize radiotherapy plans for specific patients and provide corresponding synthetic radiation dose information. Through a method, such optimization may include calculating a corresponding influence matrix. Upon detecting at least one manual edit to the weights of at least one point corresponding to the radiotherapy plan, these teachings can responsively generate new radiation dose information based on the corresponding influence matrix, at least in near real-time.

[0018] These teachings will apply to various methods for detecting this type of manual editing. For example, one method can detect manual editing via the user interface when the user selects an area comprising multiple points (e.g., using a cursor). Another method, and as another example, can detect manual editing when the user selects a single point.

[0019] One method involves generating new radiation dose information by multiplying the aforementioned influence matrix by the corresponding point weights. The latter may involve, for example, vector multiplication.

[0020] These teachings are both flexible and practical in practice, and will be adapted to generate new radiation dose information, for example, by calculating the total radiation dose, calculating the dose rate, or calculating both simultaneously as needed.

[0021] These teachings correspondingly support interactive dose modification in treatment planning systems. They are highly flexible in adapting to various methods of how users interact with the treatment planning system. In this configuration, these teachings provide a simple and intuitive way to address problem situations that automated optimization solutions cannot adequately solve. Perhaps equally important, the corresponding results can be provided very quickly (e.g., within 1 to 5 seconds, compared to many hours potentially required by many existing techniques).

[0022] By allowing users to see the results of their changes to point weights at least in near real-time, it is more likely to achieve a given, efficient radiotherapy plan in a real-world application setting.

[0023] These and other benefits will become clearer after a thorough review and study of the following detailed description. Refer now to the accompanying drawings, especially... Figure 1 First, an illustrative device 100 compatible with many of these teachings will be presented.

[0024] In this particular example, the enabling device 100 includes a control circuit 101. As a “circuit”, the control circuit 101 therefore includes a structure comprising at least one (and typically multiple) conductive paths (e.g., paths made of conductive metals such as copper or silver) that conduct electricity in an ordered manner, and these paths (one or more) will typically also include corresponding electronic components (which may be both passive (such as resistors and capacitors) and active (such as any of various semiconductor-based devices)) to allow the circuit to implement the control aspects of these teachings.

[0025] This type of control circuit 101 may comprise a fixed-purpose hardwired hardware platform (including, but not limited to, application-specific integrated circuits (ASICs) (which are integrated circuits designed for a specific purpose rather than for general use), field-programmable gate arrays (FPGAs), etc.), or may comprise a partially or fully programmable hardware platform (including, but not limited to, microcontrollers, microprocessors, etc.). These architectural options for this type of structure are well known and understood in the art and need not be further described herein. The control circuit 101 is configured (e.g., by using corresponding programming that will be well understood by those skilled in the art) to perform one or more steps, actions, and / or functions described herein.

[0026] Control circuitry 101 is operatively coupled to memory 102. Memory 102 may be integrated into control circuitry 101 or physically separated from control circuitry 101 ( wholly or partially) as needed. Memory 102 may also be local to control circuitry 101 (where, for example, both share a common circuit board, chassis, power supply, and / or housing), or may be partially or wholly remote to control circuitry 101 (where, for example, memory 102 is physically located in another facility, metropolitan area, or even country compared to control circuitry 101).

[0027] In addition to information such as radiation dose information, the memory 102 can also be used, for example, to non-transitory store computer instructions that, when executed by the control circuit 101, cause the control circuit 101 to operate as described herein. (As used herein, the reference to "non-transitory" will be understood to mean the non-transient state of the stored content (and thus excludes the case where the stored content constitutes only a signal or wave), rather than the volatile nature of the storage medium itself, and therefore includes both non-volatile memories (such as read-only memory (ROM)) and volatile memories (such as dynamic random access memory (DRAM)).

[0028] Alternatively, the control circuitry 101 may also be operatively coupled to the user interface 103. The user interface 103 may include any of a variety of user input mechanisms (such as, but not limited to, keyboards and keypads, cursor control devices, touch-sensitive displays, voice recognition interfaces, gesture recognition interfaces, etc.) and / or user output mechanisms (such as, but not limited to, visual displays, audio transducers, printers, etc.) to facilitate receiving information and / or instructions from and / or providing information to the user.

[0029] If necessary, the control circuitry 101 can also be operatively coupled to a network interface (not shown). With this configuration, the control circuitry 101 can communicate with other components (both within and outside the device 100) via the network interface. Network interfaces, including both wireless and non-wireless platforms, are well known in the art and require no further explanation herein.

[0030] By means of a method, computed tomography apparatus 106 and / or other imaging apparatus 107 known in the art can acquire part or all of any desired patient-related imaging information.

[0031] In this illustrative example, control circuitry 101 is configured to ultimately output an optimized energy-based treatment plan 113 (e.g., an optimized radiotherapy plan). This energy-based treatment plan 113 typically comprises specified values ​​for each of various treatment platform parameters during each of multiple consecutive exposure fields. In this case, the energy-based treatment plan 113 is generated through an optimization process. Various automated optimization processes are known in the art, and these processes are specifically configured to generate such energy-based treatment plans. Since this teaching is not overly sensitive to any particular choice of these aspects, further elaboration on these aspects is not provided here unless particularly relevant to the details of this specification.

[0032] In one method, control circuitry 101 is operatively coupled to an energy-based treatment platform 114 configured to deliver therapeutic energy 112 to a corresponding patient 104 according to an optimized energy-based treatment plan 113. These teachings are generally applicable to any of a variety of energy-based treatment platforms / devices.

[0033] In a typical application setup, the energy-based treatment platform 114 would include an energy source 115, such as an ionizing radiation source, a microwave energy source, a thermal energy source, etc. For illustrative purposes, it will be assumed here that the energy source 115 is a proton source that provides a proton beam to irradiate the diseased tissue.

[0034] In one method, the energy source 115 can be selectively moved via a gantry along an arcuate path (where the path at least partially encompasses the patient during application). The arcuate path may, as needed, comprise a complete or near-complete circle. In another method, control circuitry 101 controls the movement of the energy source 115 along the arcuate path and can accordingly control when the energy source 115 begins to move, stops moving, accelerates, decelerates, and / or the speed at which the energy source 115 travels along the arcuate path.

[0035] A typical energy-based treatment platform 114 may also include one or more support devices 110 (such as a treatment bed) for supporting the patient 104 during treatment, one or more patient fixation devices 111, a bench or other movable mechanism that allows selective movement of the energy source 115, and one or more energy shaping devices 117 (e.g., bundle shaping devices, such as jaws, multi-leaf collimators, etc.) to provide selective energy shaping and / or energy conditioning as needed.

[0036] In a typical application setting, this document assumes that during energy-based therapy, the patient support device 110 can be selectively controlled to move in any direction (i.e., any X, Y, or Z direction) via control circuitry 101. Since the foregoing components and systems are well known in the art, further description of these aspects will not be provided herein unless otherwise relating to this specification.

[0037] Now for reference Figure 2 The process 200, which can be implemented in conjunction with the above application settings (and more specifically via the above control circuit 101), will be described.

[0038] In box 201, the process 200 optimizes the radiotherapy plan 113 for a specific patient 104 and provides corresponding synthetic radiation dose information. For illustrative purposes, it will be assumed here that the radiotherapy plan 113 includes a plan to administer scanning proton therapy.

[0039] It is also assumed here that optimizing the radiotherapy plan 113 includes calculating the corresponding influence matrix. Influence matrices are known in the art. An influence matrix specifies how each point affects the dose (and thus specifies the contribution of each point). For illustrative purposes, and temporarily with reference to... Figure 8 The depicted grid 801 corresponds to a two-dimensional patient containing 4×4 voxels (two of which are indicated by reference numeral 802). The wedge-shaped element 803 is a proton beam or "point," and the dashed line 804 is the trajectory of a single proton within the patient. The star-shaped element (one of which is indicated by reference numeral 805) represents a collision between a proton and a particle in the medium, where the proton is lost and some energy is deposited (where the "dose" is equal to the energy divided by the local density).

[0040] Reference numeral 806 denotes the corresponding influence matrix. In this illustrative example, each column of the influence matrix corresponds to a point, and each row corresponds to a voxel. To form the influence matrix, control circuitry 101 simulates the trajectory of protons and adds all their individual contributions to the influence matrix based on the point to which the protons belong and the voxel of the deposition dose.

[0041] Refer again Figure 2 In block 202, control circuitry 101 detects at least one manual edit to the weight of at least one point corresponding to radiotherapy plan 113. (In the absence of a detected trigger event, process 200 can adapt to any of a variety of responses. Examples of responses may include temporary multitasking (in which control circuitry 101 performs other tasks before returning to monitor the manual edit again) and continuous looping to substantially continuously monitor the trigger event. These teachings also support this detection activity via real-time interruption capability.)

[0042] These teachings will apply to various methods of detecting manual editing. By one method, and for now, refer to... Figure 3 and 4 , Figure 3 A user interface 103 is described that presents a scanned image, including a scanned image of the patient's treatment volume 105, as well as other patient characteristics and dosage information. Figure 4 An area 401 of the treatment volume 105 selected by the user is depicted (e.g., using a cursor control and selection device such as a mouse or touchscreen display). This area 401 corresponds to and includes multiple points. In this way, the control circuitry 101 detects the selection activity as manual editing.

[0043] By another method, and for now, refer to Figure 6 and Figure 7 , Figure 6 A user interface 103 is depicted that presents a number of individual points corresponding to the treatment volume 105. Figure 7 The user interface 103 is also depicted presenting certain points (generally indicated by reference numeral 701) corresponding to the points selected by the user. In all these cases, the user can select corresponding weights for the selected points. These teachings will be adapted as needed to detect other methods of manual editing.

[0044] Upon detecting the event, in box 203, control circuit 101 responsively generates new radiation dose information based on the corresponding influence matrix, at least in near real-time. (As used herein, the expression "near real-time" should be understood as within two seconds. Longer processing times can be accommodated if necessary. For example, the generation (and display) of the aforementioned information may have to occur within, for example, five seconds, ten seconds, twenty seconds, thirty seconds, one minute, etc., as required.) In order to generate new radiation dose information, control circuit 101 calculates the dose by assigning modified weights (one or more) (which may all be the same modified weights or different weights, as required) to the points and multiplying the influence matrix by a vector of these point weights. Calculating the dose in this way is much faster than, for example, by simulating dose deposition. These teachings will also facilitate determining the contribution of each point to each voxel much faster than often found when using prior art methods.

[0045] The newly generated radiation dose information may, as needed, include, for example, the calculated total radiation dose, the calculated dose rate, or both. (Reference) Figure 5 The calculated information can be presented graphically and / or alphanumerically by any means known in the art, such as, but not limited to, via user interface 103. If desired, the speed of presentation of such information can be at least partially accelerated by using a graphics processing unit. In another approach, instead of the foregoing or in combination therewith, the dose space can be decomposed into distinct regions, and only the presentation of the affected regions needs to be updated to reflect the modified dose.

[0046] The use of this influence matrix makes it simple and intuitive to modify point weights to change the dose distribution, while also allowing for very fast calculation of the corresponding results and presentation of those results to the user.

[0047] Those skilled in the art will recognize that various modifications, alterations, and combinations can be made to the above embodiments without departing from the scope of the invention. Therefore, such modifications, alterations, and combinations will be considered to be within the scope of the invention.

Claims

1. A method for optimizing radiotherapy planning, comprising: By controlling the circuit: Optimize the radiotherapy plan for a specific patient and provide corresponding synthetic radiation dose information; Detect at least one manual edit to the weight of at least one point in the radiotherapy plan; In response to the detection of at least one manual edit, new radiation dose information is generated; Optimizing the radiotherapy plan for the specific patient includes calculating an influence matrix that specifies how each point affects the dose; and The generation of the new radiation dose information is performed at least in near real-time according to the influence matrix, and includes multiplying the influence matrix by the at least one point weight to allow the user to see the result of the user's change to the at least one point weight at least in near real-time.

2. The method of claim 1, wherein the radiotherapy plan includes a plan to implement scanning proton therapy.

3. The method of claim 1, wherein the control circuit is configured to detect the at least one manual edit by detecting at least one of the following: Selection of a single point; and Selection of regions that include multiple points.

4. The method of claim 1, wherein the control circuit is configured to detect the at least one manual edit by detecting a user selection on a user interface.

5. The method of claim 1, wherein multiplying the influence matrix by point weights includes using vector multiplication.

6. The method of claim 1, wherein generating the new radiation dose information includes calculating the total radiation dose.

7. The method of claim 1, wherein generating the new radiation dose information includes calculating the dose rate.

8. The method of claim 1, wherein generating the new radiation dose information includes calculating both the total radiation dose and the dose rate.

9. An apparatus for optimizing radiotherapy planning, comprising: The control circuit is configured as follows: Optimize the radiotherapy plan for a specific patient and provide corresponding synthetic radiation dose information; Detect at least one manual edit to the weight of at least one point in the radiotherapy plan; In response to the detection of at least one manual edit, new radiation dose information is generated. The control circuitry is configured to optimize the radiotherapy plan for the specific patient, including: calculating an influence matrix that specifies how each point affects the dose; as well as The control circuit is configured to generate the new radiation dose information based on the influence matrix at least in near real-time, and to multiply the influence matrix by the at least one point weight, so that the user can see the result of the user's change to the at least one point weight at least in near real-time.

10. The apparatus of claim 9, wherein the radiotherapy plan includes a plan to perform scanning proton therapy.

11. The apparatus of claim 9, wherein the control circuitry is configured to detect the at least one manual edit by detecting at least one of the following: Selection of a single point; and Selection of regions that include multiple points.

12. The apparatus of claim 9, further comprising: User interface, operatively coupled to the control circuitry; and The control circuitry is configured to detect the at least one manual edit by detecting a user selection on the user interface.

13. The apparatus of claim 9, wherein multiplying the influence matrix by the point weights includes using vector multiplication.

14. The apparatus of claim 9, wherein generating the new radiation dose information includes calculating the total radiation dose.

15. The apparatus of claim 9, wherein generating the new radiation dose information includes calculating the dose rate.

16. The apparatus of claim 9, wherein generating the new radiation dose information includes calculating both the total radiation dose and the dose rate.

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