COMPUTER IMPLEMENTED METHOD FOR RADIATION THERAPY PLANNING, COMPUTER PROGRAM PRODUCT AND COMPUTER SYSTEM FOR PERFORMING THE METHOD - Patent application

Abstract

A computer-based method for optimizing a radiation treatment plan for a patient is proposed, which optimizes the treatment plan provided by one radiation set by taking into account previously delivered doses delivered by different radiation sets, one of which is external beam radiation therapy and the other of which is brachytherapy.

Description

[Technical field]

[0001] The present invention relates to a computer-implemented method for radiation therapy planning, a computer program product and an apparatus for performing such a method. In particular, the present invention relates to treatment planning for radiation therapy that provides both external beam radiation therapy and brachytherapy for the same patient. [Background technology]

[0002] Most radiation treatments are given as external radiation delivered to the patient from an external source, known as external beam radiation therapy (or EBRT). This is usually delivered in many fractions, for example 15, 30 or more. Alternatively, radiation may be delivered from a source placed inside the patient's body. This is known as brachytherapy and involves placing one or more needles or other types of devices into a target inside the patient's body to expose it to radiation from within. This is usually done in a smaller number of fractions, for example 1 or 3.

[0003] For EBRT treatment, the planning is currently mainly done as an inverse treatment planning process in an optimization treatment planning machine. The objective is usually to achieve a minimum dose or a uniform dose throughout the target. Brachytherapy (or BT) planning requires the placement of a device to deliver radiation in the target, either on the body or in a virtual environment, and the dose is usually developed in a forward planning process, where the location of the device and the resulting dose are determined. In low dose rate BT, one or more radiation sources, known as seeds, are implanted in the target and usually left there for a period of time. On the other hand, in high dose rate BT and pulsed dose rate BT, radiation is delivered by a radiation source that moves through a hollow channel of an implanted device, consisting of, for example, a needle, catheter, and applicator. Usually, the BT dose distribution is not uniform, but instead is concentrated around the implanted device.

[0004] It is known in the art to combine EBRT and brachytherapy in the same patient. Typically, the EBRT fraction is delivered first, followed by the brachytherapy, although the reverse order is possible. Usually, the patient geometry changes during the first treatment. Also, the device inserted in the patient for the brachytherapy changes the shape of the target and the surrounding tissue. For both of these reasons, the two modalities are delivered to different patient geometries. When both brachytherapy and external beam radiation therapy are used on the same patient, traditionally, two separate treatment plans are developed, one for the EBRT portion of the treatment and one for the brachytherapy portion of the treatment. These are typically based on the total dose and a predefined division of the dose between the different types of treatment. For example, a total dose of 80 Gy may be set, where the EBRT treatment is for delivering 60 Gy and the brachytherapy is for delivering the remaining 20 Gy.

[0005] It is an object of the present invention to provide improved planning methods for radiation therapy, including both EBRT and brachytherapy. Summary of the Invention

[0006] The present invention relates to a) determining a dose previously delivered to a patient using a first set of rays based on at least a first medical image of the patient; b) obtaining a first optimization problem including an optimization function designed to optimize a dose distribution resulting from a second radiation set depending on a dose criterion set for a total dose and a previously delivered dose, the total dose being the dose resulting from the second radiation set and the previously delivered dose; c) optimizing a treatment plan for delivering radiation therapy with a second radiation set using the first optimization problem, where the optimization function is an objective function or constraint, and one of the first and second radiation sets is brachytherapy and the other is external beam radiation therapy; The present invention relates to a computer-based method for optimizing a radiation treatment plan for a patient, comprising:

[0007] This improves planning of the treatment to be delivered by the second radiation set by taking into account the treatment already delivered by the first radiation set. The previously delivered dose may be estimated or calculated using any suitable method.

[0008] In a preferred embodiment, the first optimization problem includes an optimization function designed to optimize the dose distribution resulting from the second radiation set to match the difference between the desired total dose distribution represented by the dose criterion and the previously delivered dose, providing an actual total dose resulting from the combined dose delivered by both radiation sets that is a good match for the desired total dose distribution.

[0009] The dose criteria is preferably based on at least earlier medical images taken prior to the delivery of the first set of radiation.

[0010] According to a preferred embodiment, the method further comprises, before step a), the following step: d) obtaining an initial optimization problem including an optimization function designed to optimize a total dose distribution as a combination of a first dose distribution provided by the first set of rays and a second dose distribution provided by the second set of rays; e) optimizing the treatment plan as a combination of the first and second radiation sets using the initial optimization problem; Further includes:

[0011] This further refines the planning by already considering both radiation sets when planning the dose to be delivered by the first radiation set.

[0012] The at least one first medical image may include at least one image of the patient taken after delivery of the first portion, which provides the most accurate information about the actual patient geometry.

[0013] Alternatively or additionally, the at least one first medical image may include at least one simulated image based on an assumption of the patient geometry after delivery of the portion, which may be preferred if for some reason it is not feasible to take a new image of the patient after delivery of the portion or with the brachytherapy device inserted.

[0014] In a preferred embodiment, the method includes transforming at least one of the doses delivered by the first and second radiation sets respectively to obtain a common geometry for the treatment portion and accumulating them using a biological model, where the optimization function is a set of accumulated doses from the second radiation set and penalties for radiation set specific doses. Typically, the dose of the second radiation set is transformed relative to the first medical image.

[0015] Preferably, robust planning is used to account for uncertainties in brachytherapy device placement, EBRT delivery and / or the determined delivered dose. Methods for performing robust planning are known in the art.

[0016] The invention also relates to a computer program product comprising computer readable code means adapted to cause a computer to carry out a method according to any of the above embodiments when run on the computer. The computer program product may be stored on any suitable type of non-transitory storage medium.

[0017] The invention also relates to a computer system comprising a processor and at least one program memory, characterized in that the program memory holds a computer program as defined above.

[0018] In a preferred embodiment, the invention involves planning the brachytherapy plan taking into account also the accumulated dose already delivered to the patient by several other modalities, which means that deviations from the planned dose to the target can be compensated for and also too high doses to organs at risk can be compensated for by altering the brachytherapy treatment plan accordingly.

[0019] The invention will be explained in more detail below, by way of example and with reference to the accompanying drawings, in which: [Brief description of the drawings]

[0020] [Figure 1a] 1 is a cross-section of a medical image of a patient. [Figure 1b] 1 is a cross-section of a medical image of a patient. [Figure 1c] 1 is a cross-section of a medical image of a patient. [Diagram 2] 1 is a flow chart of a general embodiment of the method. [Diagram 3] 1 is a flow chart of a more specific embodiment of the method including BT after EBRT. [Figure 4] 1 is a flow chart of a second, more specific embodiment of the method including EBRT after BT. [Diagram 5] 1 is a schematic overview of a computer system on which embodiments of the present invention may be implemented; DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0021] In external beam radiation therapy (i.e., EBRT), radiation is given to a patient in the form of an externally delivered beam. The radiation may be any type of radiation, such as photons, electrons, protons, or other ions. In brachytherapy (i.e., BT), some type of device is inserted into a target inside the patient's body and used to deliver radiation from one or more points within the target. The device may include many small needles and / or catheters, one or more larger applicators, one or more seeds, or any combination of different types of devices. Depending on the number and size of the devices, the geometry of the target and the surrounding patient is modified.

[0022] Due to the different nature of the two radiation sets, EBRT and BT plans use different treatment parameters. Treatment parameters for EBRT treatments include beam and beam limiting device configurations. Treatment parameters for BT treatments include variables such as device position and dwell time. Each radiation set typically requires radiation to be delivered in one or more fractions, a larger number for EBRT than for BT, which can typically, but not necessarily, even be delivered in one single fraction.

[0023] As discussed above, inverse treatment planning using optimization problems is common for EBRT planning, but has not traditionally been used for brachytherapy.

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[0024] The present invention relates to the simultaneous optimization of treatment parameters for EBRT and BT treatments, which solves the optimization problem in equation (3):

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[0025] Typically, optimization involves transforming the doses into a common geometric shape and accumulating them using a biological model, where the objective function is a set of penalties for the accumulated dose and radiation set specific doses.

[0026] 1a, 1b and 1c are simplified examples of medical images taken at different times during a procedure of the invention, as will be discussed in more detail below in connection with 2. FIG. 1a is a cross-section 11 of a conceptual medical image of a patient's abdomen looking at a target 13 and an organ at risk 15, used for treatment planning according to an embodiment of the invention. FIG. 1b is a corresponding cross-section 11' of a medical image of the same patient after a first type of treatment, showing diagrammatically the changes that may occur in the geometry of the patient due to said treatment. Of course, the target 13 has shrunk due to said treatment, which is usually the desired result. FIG. 1c is a corresponding cross-section 11'' of a medical image of the same patient with needles inserted into the target to give the patient brachytherapy. The needles are shown as small dots 17 within the target. As shown in the figure, this also changes the geometry of the target 13'' and the area of ​​the patient surrounding the target.

[0027] FIG. 2 is a flow chart of an overall method according to one embodiment of the present invention.

[0028] In a first step S21, images of the relevant portion of the patient are obtained as discussed in connection with Figures 1a-1c. In step S22, dose criteria are determined for the total dose distribution to be delivered as a combined plan including both EBRT and brachytherapy.

[0029] In step S23, an optimization problem is defined based on one or more images and dose criteria for the desired total dose. The dose criteria are set as is common in the art. They typically include a minimum dose for all voxels of the target and often a maximum dose for one or more organs at risk. For example, the dose criteria may specify a total dose of at least 60 Gy in each target voxel and a maximum of 30% of the organs at risk to be subjected to a total dose of more than 40 Gy. The dose criteria may also include a partial or complete dose distribution. In S24, the optimization problem is used to optimize the treatment plan. The optimization problem includes an objective function such as function (3) above.

[0030] In step S25, a portion of the treatment plan is delivered to the patient, and in step S26, the accumulated dose delivered to the patient from that portion of the treatment plan is estimated. The accumulated dose may be determined in any suitable manner. Methods for doing this are well known in the art and are typically based on at least one medical image, for example a number of fraction images taken throughout the delivery of the first portion of the treatment plan.

[0031] In step S27, a new image of the same portion of the patient is obtained to confirm the new geometry of the patient after the partial delivery in step S25. If applicable, other modifications, such as the insertion of a brachytherapy device, may be made and an image may be taken that reflects the resulting geometry. The new image may be an image of the patient taken at this stage or a synthetic image based on an estimate of the new geometry of the patient.

[0032] In step S28, the remainder of the treatment plan is re-optimized using an inverse treatment planning method and based on an optimization function, discussed in more detail below, which takes into account the cumulative dose of the previous partial deliveries. The optimization problem must then include an objective function related to:

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[0033] where g is another objective function, which may or may not be equal to f, and the dose delivered from the first radiation set over all fractions (measured or estimated) is used as a fixed background dose for planning for the second radiation set.

[0034] In step S28, the reoptimized remainder of the plan is delivered to the patient.

[0035] 3 is a flow chart of an embodiment of the method of the present invention, where the overall treatment plan includes first an EBRT treatment, then a BT treatment. Input data S31 to this plan includes a current medical image of the patient, dose criteria for the desired dose distribution, and a predicted model of the patient's geometry after the EBRT treatment. The predicted model may be a trained or synthetic medical image. The input data may also include a predicted model of the patient's geometry after the EBRT treatment with the EB device included. The medical image may be a CT image or any other suitable modality image, such as an MR or ultrasound image.

[0036] In method step S32, an optimization problem is obtained based on the dose criteria and the input data. The optimization problem includes an objective function according to equation (3) based on the total dose of both the EBRT and BT fractions of the treatment and, optionally, the dose delivered for each radiation set. This typically involves the dose d EBRT and d BT to a common geometry and accumulating them using a suitable biological model. This may include setting a combination of accumulated dose and penalty for a particular dose. Models for establishing the common geometry are known, typically involving non-rigid registration of the images. Models for determining the accumulated dose are also known to those skilled in the art. For example, the biological concept of EQD2 may be applied to provide an estimate of the total effective dose.

[0037] A subsequent method step S33 optimizes based on a common geometry and accumulated dose. The optimization problem includes an objective function according to equation (3) above. Of course, the objective function can be extended to depend on the treatment parameters, and the optimization problem may also include constraints depending on the dose or treatment parameters. The output S34 from the optimization step S33 is a global treatment plan with one fraction for each radiation set, i.e. one EBRT fraction and one BT fraction. Each fraction includes the part of the dose delivered by the corresponding radiation set and the number of fractions to deliver it.

[0038] Then, in step S35, the EBRT subportion of the treatment plan is delivered to the patient, and in step S36, the actual delivered dose is determined or estimated from this delivery. Preferably, the situation after EBRT delivery is evaluated and used to refine the BT subportion of the treatment plan as outlined in the following steps.

[0039] In step S37, updated images of the patient after EBRT treatment are obtained. These include new images of the patient to compensate for the geometric changes that occurred during EBRT treatment. The images also include images of the patient with the BT device inserted, since the BT device causes some deformation of the target and surrounding patient geometry depending on the type of device.

[0040] In a subsequent step S38, the BT fraction of the treatment is reoptimized, taking into account the delivered dose from step S35 and the new image obtained in step S37. The optimization problem is then solved by the following equation (2):

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[0041] The output from step S38 is a new optimized BT treatment plan S39, which is preferably delivered to the patient.

[0042] As discussed with respect to FIG. 2, steps S36-S39 may be performed without first performing the preceding steps, i.e., the BT plan may take into account prior EBRT treatments even if the two initial combined plans do not exist.

[0043] 4 is a flow chart of a method in which the first radiation set delivered is BT. The input data S41 to this plan includes a current medical image of the patient, and a medical image of the patient with the BT device inserted, and a dose criterion for a desired dose distribution. Preferably, this input data also includes a predicted model of the patient's geometry after BT treatment. The medical images may be CT images or any other suitable modality images, such as MR or ultrasound images.

[0044] In method step S42, the optimization problem is defined in a similar manner to step S32. Images of the patient with the BT device inserted when the first BT dose portion is delivered are already available as input. These images can be non-rigidly registered to provide a geometric correspondence between the treatment geometries. As in step S32, the dose d EBRT and d BT to a common geometry and accumulate using a suitable biological model. This may include setting a combination of accumulated dose and a penalty for a particular dose. Models for establishing the common geometry are known, typically involving non-rigid registration of the images. Models for determining accumulated dose are also known to those skilled in the art.

[0045] In a subsequent method step S43, optimization is performed based on a common geometry and accumulated dose. The optimization problem includes an objective function according to equation (3) above. Of course, the optimization problem can be extended to depend on the treatment parameters and include other objective functions and / or constraints. The output S44 from the optimization step S43 is a global treatment plan with one fraction for each radiation set, i.e. one BT fraction and one EBRT fraction.

[0046] Then, in step S45, the BT subportion of the treatment plan is delivered to the patient, and in step S46, the actual delivered dose is determined or estimated from this delivery. Preferably, the post-BT delivery situation is evaluated and used to refine the EBRT subportion of the treatment plan, as outlined in the steps below.

[0047] In step S47, an updated image of the patient after BT treatment is obtained to compensate for the geometric changes that occurred during the BT treatment.

[0048] Thereafter, in step S48, the EBRT fraction of the treatment is re-optimized taking into account the delivered dose from step S45 and the new images obtained in step S47. The optimization problem in this case is the following equation (2):

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[0049] The output from step S48 is a new optimized EBRT treatment plan S49, which is preferably delivered to the patient.

[0050] As discussed with respect to Figures 2 and 3, steps S46-S49 may be performed without first performing the preceding steps, i.e., the EBRT plan may take into account a previously delivered BT treatment even in the absence of these two initial combined plans.

[0051] It is also possible to create a plan in which the BT and EBRT fractions are not given as two consecutive fractions, but instead the BT fraction is distributed between the EBRT fractions. In this type of treatment, one or more fractions of the treatment that have not yet been delivered can be reoptimized taking into account the delivered dose. Both the delivered and non-delivered fractions of the treatment are typically a combination of BT and EBRT. The optimization is then calculated using the following equation (7):

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[0052] In all of the above methods, the joint optimization must be done with some care to ensure that the individual doses of each radiation set are still satisfactory on their own. One possible adverse effect of joint optimization is that the EBRT dose has cold spots in the target that are subsequently filled by the BT dose. This can be mitigated, for example, by building robustness to uncertainties in the device positioning and deformation effects of the device into the model. Treatment-specific objective functions are also possible (similar to the current beam set specific objective functions).

[0053] As with any radiation therapy plan, there are sources of uncertainty such as patient placement, BT machine positioning and estimated delivered dose. Robust planning may be used to compensate for this. In particular, deformations between images result in an approximate accumulated dose, the quality of which depends on the accuracy of the non-rigid registration. To avoid over-optimization for an accumulated dose that differs from the actual delivered dose, methods for robust planning that go beyond the indication of uncertainty can be used. Various degrees of refinement can be used, e.g. Margins as ITV across the predicted image or just a smearing of the area to be treated can be applied. · Robust planning may be applied using scenarios generated as rigid body shifts of the patient geometry independently for each radiation set. ·Robust planning using scenarios generated by multiple non-rigid registrations can be applied. If an EBRT partial dose is delivered before a BT partial dose, this requires the use of multiple predictions. If a BT partial dose is delivered before an EBRT partial dose, this requires the use of perturbations of the registration between the acquired images. These deformations can also result from anatomical deformations during EBRT, e.g. tumor shrinkage.

[0054] Methods according to embodiments of the present invention may also be combined with multi-criteria optimization, where navigation can be performed in several planes with several trade-off objectives targeting either the total dose or the individual treatment doses.

[0055] Figure 5 is a schematic diagram of a computer system capable of carrying out the method of the invention. The computer 31 comprises a processor 33 and a program memory 36 connected to first and second data memories 34, 35. There are also one or more user input means 38, 39, preferably in the form of a keyboard, mouse, joystick, voice recognition means or any other available user input means. The user input means may also be arranged to receive data from an external memory unit.

[0056] A first data memory 34 contains data necessary to perform the method, such as required images. A second data memory 35 holds data relating to one or more current patients for which a treatment plan is to be developed. A program memory 36 holds a computer program configured to cause a computer to perform the method steps, for example as discussed in connection with any of Figures 2, 3 and 4.

[0057] It will be appreciated that the data memories 34, 35 as well as the program memory 36 are shown and discussed diagrammatically. There may be several data memory units each holding one or more different types of data, or there may be one data memory holding all the data in a suitably structured manner, which holds the program memory. One or more of the components may be present in the cloud environment, as long as they are able to communicate with each other.

Claims

1. 1. A computer-implemented method for optimizing a radiation treatment plan for delivering radiation to a patient using a second set of rays, the method comprising: a) determining a first dose distribution provided by a first set of radiation previously delivered to a patient based on at least one first medical image of the patient; b) obtaining a first optimization problem including an optimization function designed to optimize a second dose distribution delivered by a second set of rays based on a set of dose criteria for a desired total dose distribution and the first dose distribution, the total dose being the sum of the doses delivered by the second set of rays and the first set of rays; c) optimizing a treatment plan for delivering radiation by the second radiation set using the optimization problem, wherein the optimization function is an objective function or constraint, and one of the first radiation set and the second radiation set is delivered by brachytherapy and the other is delivered by external beam radiation therapy; A method comprising:

2. 2. The method of claim 1, wherein the optimization function is designed to optimize the second dose distribution such that the second dose distribution matches a difference between the total dose distribution and the first dose distribution.

3. The method of claim 1 or 2, wherein the dose reference set is established based on at least an earlier medical image taken before the delivery of the first set of radiation.

4. Prior to step a), the following: d) obtaining an initial optimization problem including an objective function designed to optimize the total dose distribution as a combination of the first dose distribution and the second dose distribution; e) optimizing a treatment plan as a combination of the first and second radiation sets using the initial optimization problem; The method of any one of claims 1 to 3, further comprising:

5. The method of any one of claims 1 to 4, wherein the first optimization problem is obtained further based on a second medical image.

6. 6. The method of claim 5, wherein the second set of radiation is delivered by brachytherapy and the second medical image is an image including a brachytherapy device being applied to the patient.

7. The method of any one of claims 1 to 6, wherein the at least one first medical image comprises at least one image of the patient taken after delivery of the first set of radiation.

8. 8. The method of claim 1, wherein the at least one first medical image comprises at least one simulated image based on an estimate of a patient geometry after delivery of the first set of radiation.

9. 9. The method of claim 1, further comprising: deforming the second dose distribution based on a geometry of the first medical image; and accumulating dose using a biological model, wherein the objective function is a set of accumulated doses of the second ray set and penalties for ray set specific doses.

10. 10. The method of any one of claims 1 to 9, wherein robustness is built into the optimization problem to account for uncertainties in the brachytherapy delivery, the external beam radiation therapy delivery and / or the determined first dose distribution.

11. A computer program comprising computer readable code means adapted to, when executed on a computer, cause said computer to carry out a method according to any one of claims 1 to 10.

12. A computer system comprising a processor and at least one program memory, said program memory holding a computer program according to claim 11.

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