Computer-implemented method for radiotherapy treatment planning, computer program product for performing the method, and computer system

Abstract

A computer-based method for optimizing a radiotherapy treatment plan for a patient is proposed, in which an optimization problem including an objective function is used in a process to optimize a complete treatment including both external beam therapy and brachytherapy, the objective function being designed to optimize the total dose distribution as a combination of a first dose distribution to be delivered by a first radiation set and a second dose distribution to be delivered by a second radiation set. One of the radiation sets is external beam radiotherapy and the other is brachytherapy. The optimization is based on the total desired dose for the entire treatment, an image of the patient before the start of the treatment, and an estimated image of the patient after the first radiation set has been delivered.

Description

Field of the Invention

[0001] The present invention relates to a computer-implemented method for radiotherapy treatment planning and to a computer program product and apparatus for performing such a method. In particular, the present invention relates to treatment planning for radiotherapy which involves both external beam radiotherapy and brachytherapy for the same patient. Background Art

[0002] Most radiotherapy treatments are delivered as external radiation which is delivered to the patient from an external source and is known as external beam radiotherapy or EBRT. This is typically delivered in multiple fractions, for example 15 fractions, 30 fractions or more. Alternatively, radiation can be delivered from a source placed within the patient. This is known as brachytherapy and involves placing one or more needles or other types of instruments within the target volume in the patient to expose the target volume to radiation from within. This is typically performed in fewer fractions, for example 1 fraction or 3 fractions.

[0003] For EBRT treatment, planning is currently mainly performed as an inverse planning process in an optimization treatment planner. The aim is typically to achieve a minimum dose or a uniform dose across the entire target volume. Brachytherapy or BT planning requires physically or in a virtual environment placing the instruments for delivering radiation within the target volume and the dose is typically formulated in a pre-planning process in which the positions of the instruments and the dose obtained from the instruments are determined. In low dose rate BT, one or more sources (known as seeds) are implanted into the target volume and typically remain there for the foreseeable future. On the other hand, in high dose rate BT and pulsed dose rate BT, the radiation is delivered by a radioactive source moving through a hollow channel within the implanted instrument which consists of, for example, needles, catheters and applicators. Typically, the BT dose distribution is non-uniform but concentrated around the implanted instrument.

[0004] In the art, it is known to combine EBRT with brachytherapy in the same patient. Typically, the EBRT fractions are delivered first, followed by brachytherapy, but the reverse order is also possible. During the first treatment, the geometry of the patient will generally change. In addition, the device inserted into the patient for brachytherapy will change the shape of the target area and the surrounding tissues. For these two reasons, the two modalities will be delivered to different patient geometries. In the case where both brachytherapy and external radiation therapy are used on the same patient, two separate treatment plans are traditionally developed, one for the EBRT part of the treatment and one for the brachytherapy part of the treatment. These are typically based on the total dose and a predetermined dose allocation between the different types of treatment. For example, a total dose of 80 Gy can be set, where the EBRT treatment contributes 60 Gy and the brachytherapy contributes the remaining 20 Gy. D1 discloses a radiotherapy treatment planning method that allows the combination of two or more modalities, which can include combining brachytherapy and external beam radiation therapy. According to D1, the plan is iteratively optimized, first selecting and optimizing the most promising modality and then adding the other modality and optimizing the contribution of that other modality.

[0005] The object of the present invention is to provide an improved planning method for treatment planning that involves both EBRT and brachytherapy. Summary of the Invention

[0006] The present invention relates to a computer-based method for optimizing a radiotherapy treatment plan for a patient, comprising the steps of:

[0007] a. obtaining input data comprising a first image of the patient,

[0008] b. obtaining an optimization problem comprising an objective function designed to optimize a total dose distribution based on the input data as a combination of a first dose distribution to be provided by a first radiation set and a second dose distribution to be provided by a second radiation set, based on a dose criterion for the total dose distribution, wherein one of the radiation sets is external beam therapy and the other is brachytherapy,

[0009] c. optimizing the treatment plan as a combination of external beam therapy and brachytherapy by means of the optimization problem.

[0010] Thus, according to the present invention, the treatment parameters of two radiation sets are optimized by jointly optimizing the problem. This results in an overall treatment plan that is better than the separate plans according to the prior art. The first dose and the second dose may be delivered in any suitable order or interleaved. The input data may also include a second image of the patient, which may be an estimated image of the patient after a part of the treatment plan has been delivered. Then, the second image may be used to provide information about the patient's anatomy after the delivery of that part. Typically, that part is the part to be delivered by the first radiation set.

[0011] Preferably, the method further comprises the steps of: after the delivery of the first part of the treatment plan, determining the dose delivered to the patient, providing at least one updated image of the patient and re-optimizing the remaining treatment plan using a second optimization problem that takes into account the delivered dose and the updated image. This enables the remaining part or parts of the treatment plan to be improved based on the actual results of the delivery of the first part. The first part typically corresponds to the dose to be delivered by the first radiation set, while the remaining part typically corresponds to the dose to be delivered by the second radiation set.

[0012] In some embodiments, the first part of the treatment plan is the part to be delivered as external beam therapy. In this case, the at least one updated image preferably includes an updated image of the patient and an updated image of the patient with a brachytherapy device applied, to take into account the actual patient geometry including the brachytherapy device during delivery. The remaining treatment plan is updated based on the updated image.

[0013] In other embodiments, the first part of the treatment plan is the part to be delivered as brachytherapy. Preferably, in this case, step b is additionally performed based on the current image of the patient with a brachytherapy device applied, to take into account the actual patient geometry during delivery.

[0014] The at least one updated image may include at least one image of the patient acquired after the delivery of the first part. This will provide the most correct information about the actual patient geometry.

[0015] Alternatively or additionally, the at least one updated image may include at least one simulated image based on an estimate of the patient's geometry after the delivery of that part. This is appropriate if, for some reason, it is not feasible to acquire a new image of the patient after the delivery of that part or in the case of inserting a brachytherapy device.

[0016] In a preferred embodiment, the optimization includes deforming at least one of the doses delivered by the first radiation set and the second radiation set, respectively, to obtain a common geometry of the treatment portion and using a biological model to accumulate them, and the objective function is a set of penalties on the accumulated dose and penalties on the radiation set specific doses.

[0017] Preferably, robust planning is used to account for uncertainties in the placement of brachytherapy devices, EBRT delivery, and / or the delivered dose determined. How to implement robust planning is known in the art.

[0018] The invention also relates to a computer program product comprising a computer-readable code unit which, when run on a computer, is arranged to cause the computer to perform the method according to any one of the above embodiments. The computer program product can be stored on any suitable type of non-transitory storage medium.

[0019] The invention also relates to a computer system comprising a processor and at least one program memory, characterized in that the program memory holds the computer program as defined above.

[0020] In a preferred embodiment, the invention relates to planning a brachytherapy plan, wherein the cumulative dose already delivered to the patient by some other modality is also taken into account. This means that deviations from the planned dose to the target area can be compensated for, and over-doses to organs at risk can be compensated for by correspondingly changing the brachytherapy treatment plan. BRIEF DESCRIPTION OF THE DRAWINGS

[0021] The invention will be described in more detail hereinafter by way of example and with reference to the drawings, in which

[0022] Figure 1a 、 Figure 1b and Figure 1c are cross-sectional views of medical images of a patient.

[0023] Figure 2 is a flowchart of a general embodiment of the method.

[0024] Figure 3 is a flowchart of a more specific embodiment of the method including EBRT followed by BT.

[0025] Figure 4 is a flowchart of a second more specific embodiment of the method including BT followed by EBRT.

[0026] Figure 5 is a schematic overview of a computer system in which embodiments of the invention can be implemented. DETAILED DESCRIPTION

[0027] External beam radiation therapy (EBRT) involves delivering radiation to a patient in the form of beams delivered from outside. The radiation can be any type of radiation, including photons, electrons, protons, or other ions. Brachytherapy (BT) involves inserting a certain type of device into the target area within the patient's body and using the device to deliver radiation from one or more points within the target area. The device can 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 area and the surrounding patient will be deformed.

[0028] Due to the different natures of the two radiation sets, different treatment parameters are used in the planning of EBRT and BT. The treatment parameters for EBRT treatment include beam and beam-limiting device configurations. The treatment parameters for BT treatment include variables such as device position and dwell time. Each radiation set typically involves radiation delivered in one or more fractions. Typically but not necessarily, the number of fractions for EBRT is higher than that for BT, and BT can even be delivered in a single fraction.

[0029] As discussed above, inverse planning using optimization problems is common for EBRT planning but has not traditionally been used for brachytherapy. The dose distribution for EBRT can be expressed as

[0030] d EBRT =d EBRT (x EBRT ) (1)

[0031] And the dose distribution for brachytherapy can be expressed as

[0032] d BT =d BT (x BT ) (2)

[0033] Where x EBRT ,x BT are the treatment parameters for the corresponding treatment modalities.

[0034] The present invention relates to simultaneously optimizing the treatment parameters for EBRT treatment and BT treatment. This means that the optimization problem can be expressed as equation (3)

[0035]

[0036] Where x EBRT are the treatment parameters for the EBRT sub-part of the treatment, and x BT are the treatment parameters for the BT sub-part of the treatment. d EBRT and d BTThey are the doses for the EBRT sub - part and the BT sub - part respectively. Instead of the dose d, some other parameters related to the corresponding sub - part can be used.

[0037] Typically, the optimization includes deforming the doses to a common geometry and using a biological model to accumulate them, and the objective function is a set of penalties on the accumulated doses and on specific doses of the radiation beams.

[0038] Figure 1a 、 Figure 1b and Figure 1c are simplified examples of medical images acquired at different points during the process of the present invention, as will be discussed in more detail in conjunction with Figure 2 more detailedly. Figure 1a is a cross - section 11 of a schematic medical image through a patient's abdomen, where the target region 13 and the organs at risk 15 are indicated for a treatment plan according to an embodiment of the present invention. Figure 1b is a corresponding cross - section 11' of a medical image of the same patient after a first type of treatment, schematically showing the changes that such treatment may cause to the patient's geometry. As will be understood, the target region 13 has shrunk due to the treatment, which is generally a desired result. Figure 1c is a corresponding cross - section 11'' of a medical image of the same patient in the case where a needle is inserted into the target region to deliver brachytherapy to the patient. The needle is shown as small dots 17 within the target region. As can be seen, this also changes the geometry of the target region 13'' and the geometry of the region of the patient around the target region.

[0039] Figure 2 is a flowchart of an overall method according to an embodiment of the present invention.

[0040] In a first step S21, an image of a relevant part of the patient is obtained, such as the images discussed in conjunction with Figures 1a to 1c In step S22, a dose criterion for the total dose distribution to be delivered as a combined plan including both EBRT and brachytherapy is determined.

[0041] In step S23, an optimization problem is defined based on the image or images and the dose criterion of the desired total dose. The dose criteria are set as common in the art. They typically include a minimum dose for all voxels of the target region and usually include a maximum dose for one or more organs at risk. For example, the dose criterion can stipulate a total dose of at least 60 Gy in each target region voxel and at most 30% of the organs at risk are subjected to a total dose exceeding 40 Gy. The dose criterion can 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.

[0042] In step S25, a part of the treatment plan is delivered to the patient, and in step S26, the cumulative dose delivered to the patient from this part of the treatment plan is estimated. The cumulative dose can be determined in any suitable manner. The methods for doing so are well known in the art and typically based on at least one medical image, such as a plurality of fraction images acquired during the delivery of the first part of the treatment plan.

[0043] In step S27, a new image of the same part of the patient is obtained to view the new patient geometry after the partial delivery in step S25. If applicable, other modifications can be made, such as inserting a brachytherapy device, and an image reflecting the resulting geometry can be acquired. The new image can be an image of the patient acquired at this stage or a synthetic image based on an estimate of the new patient geometry.

[0044] In step S28, the remaining part of the treatment plan is re-optimized using an inverse planning method based on an optimization function that will be discussed in more detail below. The plan takes into account the cumulative dose of the partial delivery that has been performed previously. Then, the optimization problem should include an objective function according to the following formula:

[0045]

[0046] where is the dose delivered from the first radiation set determined in step S26, and d RS2 is the dose to be delivered by the second radiation set, and one of RS1 and RS2 is EBRT and the other is BT.

[0047] where g is another objective function, which can be equal to or different from f, and the dose delivered from the first radiation set over all fractions (measured or estimated) is used as a fixed background dose for the plan of the second radiation set.

[0048] In step S28, the re-optimized remaining part of the plan is delivered to the patient.

[0049] Figure 3 is a flowchart of an embodiment of the method of the present invention, where the total treatment plan includes first performing EBRT treatment and then performing BT treatment. The input data S31 of the plan includes the current medical image of the patient, the dose criteria of the desired dose distribution, and a prediction model of the patient geometry after EBRT treatment. The prediction model can be an adjusted or synthetic medical image. The input data can also include a prediction model of the patient geometry after EBRT treatment in the case of including an EB device. The medical image can be a CT image or any other suitable image modality, such as an MR or ultrasound image.

[0050] In method step S32, an optimization problem is obtained based on a dose criterion and input data. The optimization problem includes an objective function for the total dose of both the treatment-based EBRT sub-part and the BT sub-part according to equation (3) and optionally the dose to be delivered for each radiation set. This typically includes deforming at least one of the doses d EBRT and d BT to a common geometry and using an appropriate biological model to accumulate them. This can include setting a combination of penalties on the accumulated dose and on specific doses. Models for establishing the common geometry are known and typically include deformable registration of images. Models for determining the accumulated dose are also known to the person skilled in the art. For example, the biological concept EQD2 can be applied to give an estimate of the total effective dose.

[0051] In subsequent method step S33, optimization is performed based on the common geometry and the accumulated dose. The optimization problem includes the objective function according to equation (3) above. As will be appreciated, the objective function can also be extended to depend on treatment parameters, and the optimization problem can also include constraints depending on the dose or treatment parameters. The output S34 from the optimization step S33 is a total treatment plan including a sub-part (i.e., an EBRT sub-part and a BT sub-part) for each radiation set. Each sub-part includes the portion of the dose to be delivered by the corresponding radiation set and the number of fractions for delivering it.

[0052] Then, in step S35, the EBRT sub-part of the treatment plan is delivered to the patient, and in step S36, the actual delivered dose from this delivery is determined or estimated. Preferably, the situation after EBRT delivery is evaluated and used to improve the BT sub-part of the treatment plan, as outlined in the following steps.

[0053] In step S37, updated images of the patient after EBRT treatment are obtained. These include new images of the patient to account for geometric changes that occur during EBRT treatment. It also includes images of the patient with the BT device inserted, as depending on the type of device, the BT device will cause a certain amount of deformation of the target area and the surrounding patient geometry.

[0054] In subsequent step S38, the BT sub-part of the treatment is re-optimized taking into account the delivered dose from step S35 and the new images obtained in step S37. The optimization problem in this case includes the objective function expressed as equation (2) below:

[0055]

[0056] where is the delivered dose determined in step S35.

[0057] The output from step S38 is the new optimized BT treatment plan S39, which is preferably delivered to the patient.

[0058] As discussed for Figure 2 Steps S36 to S39 can be performed without first performing the previous steps, that is, the BT plan can perform the previous EBRT treatment even without the initial combined plan of both.

[0059] Figure 4 is a flow chart of a method in which the first radiation set to be delivered is BT. The input data S41 of the plan includes the patient's current medical images, the medical images of the patient with the BT device inserted, and the dose criteria of the desired dose distribution. Preferably, the input data also includes a prediction model of the patient's geometry after BT treatment. The medical images can be CT images or any other suitable image modality, such as MR or ultrasound images.

[0060] In method step S42, an optimization problem is defined in a manner similar to step S32. When the BT dose fraction is delivered first, the images of the patient with the BT device inserted are already available as input. These images can be deformably registered to provide a geometric correspondence between the treatment geometries. As in step S32, the doses d EBRT and d BT are deformed to a common geometry and accumulated using an appropriate biological model. This can include setting a combination of penalties on the accumulated dose and penalties on specific doses. The model for establishing the common geometry is known and typically includes deformable registration of images. The model for determining the accumulated dose is also known to those skilled in the art.

[0061] In the subsequent method step S43, optimization is performed based on the common geometry and the accumulated dose. The optimization problem includes the objective function according to equation (3) above. As will be understood, the optimization problem can also be extended to depend on treatment parameters and also includes other objective functions and / or constraints. The output S44 from the optimization step S43 is the total treatment plan including one sub - part (i.e., one BT sub - part and one EBRT sub - part) for each radiation set.

[0062] Then, in step S45, the BT sub - part of the treatment plan is delivered to the patient, and in step S46, the actual delivered dose from this delivery is determined or estimated. Preferably, the situation after BT delivery is evaluated and used to improve the EBRT sub - part of the treatment plan, as outlined in the following steps.

[0063] In step S47, updated images of the patient after BT treatment are obtained to account for the geometric changes that occur during BT treatment.

[0064] In a subsequent step S48, the EBRT sub - part of the treatment is re - optimized considering the delivered dose from step S45 and the new images obtained in step S47. The optimization problem in this case includes an objective function expressed as equation (2) below:

[0065]

[0066] where is the delivered dose determined in step S45.

[0067] The output from step S48 is a new optimized EBRT treatment plan S49, which is preferably delivered to the patient.

[0068] As discussed for Figure 2 and Figure 3 steps S46 to S49 can be performed without first performing the preceding steps, that is, the EBRT plan can perform a previously delivered BT treatment even without the initial combined plan of both.

[0069] It will also be possible to create a plan where the BT and EBRT fractions are not given as two consecutive sub - parts, but the BT fractions are distributed between the EBRT fractions. In this type of treatment, one or more sub - parts of the treatment that have not yet been delivered can be re - optimized considering the delivered dose. Both the delivered and non - delivered sub - parts of the treatment will typically be a combination of BT and EBRT. The optimization in this case includes an objective function expressed as equation (7):

[0070]

[0071] In all of the above methods, the simultaneous optimization should be performed carefully to ensure that the individual doses of each radiation set remain separately satisfactory. One possible adverse effect of co - optimization would be that the EBRT dose has cold spots in the target area, which are later filled by the BT dose. This can be mitigated by incorporating robustness in the model for uncertainties such as instrument positioning and deformation effects of the instrument. A treatment - specific objective function is also a possibility (similar to the current beam - set - specific objective function).

[0072] As with any radiotherapy treatment plan, there will be sources of uncertainty, including patient placement, the positioning of the BT device, and the estimated delivered dose. To compensate for this, robust planning can be used. In particular, deformations between images will result in an approximate cumulative dose, the quality of which depends on the accuracy of the deformable registration. To avoid over-optimizing for a cumulative dose that is different from the dose that will actually be delivered, methods for robust planning on the representation of uncertainty can be employed. Various degrees of improvement can be used, such as:

[0073] · A margin can be applied as an ITV on the prediction image, or as a smearing of just the region to be treated.

[0074] · A robust plan for scenarios generated using rigid shifts of the patient geometry can be applied independently to each of the radiation beams.

[0075] · A robust plan using scenarios generated by multiple deformable registrations can be applied. In the case of delivering an EBRT partial dose before a BT partial dose, this will involve using multiple predictions. In the case of delivering a BT partial dose before an EBRT partial dose, this will involve either using perturbations of the registration between the acquired images. Deformations can also arise from anatomical changes during EBRT, such as tumor shrinkage.

[0076] The method according to an embodiment of the present invention can also be combined with multi-criteria optimization. In this case, the navigation can be carried out in several aspects, where several trade-off objectives are targeted at either the total dose or any one of the individual treatment doses.

[0077] Figure 5 is a schematic representation of a computer system in which the method of the present invention can be implemented. The computer 31 includes a processor 33 connected to a first data memory 34, a second data memory 35, and a program memory 36. Preferably, there is also one or more user input devices 38, 39 in the form of a keyboard, mouse, joystick, voice recognition device, or any other available user input device. The user input device can also be arranged to receive data from an external storage unit.

[0078] The first data memory 34 includes the necessary data for performing the method, such as the necessary images. The second data memory 35 stores data related to one or more current patients for whom a treatment plan is to be developed. The program memory 36 stores a computer program arranged to cause the computer to execute the method steps discussed, for example, in any one of Figure 2 , Figure 3 and Figure 4 .

[0079] As will be appreciated, the data memories 34, 35 and the program memory 36 are shown and discussed schematically. There may be a number of data storage units, each storing one or more different types of data, or one data memory stores all data in a suitably structured manner, and the same applies to the program memory. One or more of these components may be found in a cloud environment as long as the components are able to communicate with each other.

Claims

1. A computer-based method for optimizing a radiotherapy treatment plan for a patient, comprising the steps of: a. obtaining (S21; S31; S41) input data comprising a first image of the patient and a second image of the patient, wherein the second image is an estimated resultant image of the patient after a portion of the treatment plan has been delivered, b. obtaining (S23; S32; S42) an optimization problem comprising an objective function designed to optimize a total dose distribution based on the input data as a combination of a first dose distribution to be provided by a first radiation set and a second dose distribution to be provided by a second radiation set based on a dose criterion for the total dose distribution, wherein one of the radiation sets is external beam therapy and the other is brachytherapy, c. optimizing (S24; S33; S43) the treatment plan as a combination of external beam therapy and brachytherapy by means of the optimization problem, wherein the optimization comprises deforming the first dose distribution and the second dose distribution to a common geometry and using a biological model to accumulate the doses, and the objective function is a set of penalties on the accumulated dose and on radiation set-specific doses.

2. The method according to claim 1, further comprising the steps of: d. after delivery of a first portion of the treatment plan, determining (S26; S36; S46) the dose delivered to the patient, providing (S27; S37; S47) at least one updated image of the patient and re-optimizing (S28; S38; S48) the remaining treatment plan using a second optimization problem taking into account the delivered dose and the updated image.

3. The method according to claim 2, wherein The at least one updated image comprises at least one image of the patient acquired after delivery of the portion.

4. The method according to claim 2, wherein, The at least one updated image comprises at least one simulated image based on an estimate of the geometry of the patient after delivery of the portion.

5. The method according to claim 1, wherein A robust plan is used to account for uncertainties in brachytherapy delivery, EBRT delivery, and / or the determined delivered dose.

6. A computer program product comprising a computer-readable code unit which, when run on a computer, is arranged to cause the computer to perform the method according to any one of claims 1 to 5.

7. A computer system (31), comprising a processor (33) and at least one program memory (36), characterized in that, The program memory stores the computer program product according to claim 6.

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