Method and computer program product for use in a radiation therapy delivery system and computer system - Patents.com

Abstract

The functionality of a radiation therapy delivery system may be tested by comparing actual delivery data with simulated delivery data based on a system model, where the actual delivery data may be obtained from a dry run of the system.

Description

[Technical field]

[0001]

[0001] The present invention relates to radiation therapy delivery systems for scanned proton beams, and in particular to quality assurance of treatments delivered from such systems. [Background technology]

[0002]

[0002] The goal of radiation therapy, or radiotherapy, is to deliver a sufficient dose of radiation to a target, typically a tumor, to eliminate the tumor or at least reduce its size. Radiation therapy delivery systems for delivering scanned ion beams to a patient are known in the art. The ions are typically protons, although other types of ions may also be used.

[0003]

[0003] Radiation therapy always involves delivering a dose outside the target, i.e. to healthy tissues or organs at risk, so there is always a risk that the radiation will damage healthy organs or tissues. One newer treatment that seems to cause less unwanted damage is FLASH therapy, which involves treatment at a much higher dose rate than conventional treatments, for example 70 Gy / s. In the literature on FLASH, various dose rate lower limits have been proposed, such as at least 40 Gy / s or 50 Gy / s. For example, if one wishes to deliver a dose of 20 Gy at a dose rate of 70 Gy / s, the entire dose would be delivered in 0.29 seconds. In contrast, conventional radiation therapy is delivered at a much lower dose rate, with typical dose rates for conventional radiation therapy being several Gy per minute.

[0004]

[0004] It has been shown that FLASH therapy causes less damage to healthy tissues at a given dose than conventional therapy, while leaving the effect on the target, i.e., tumor tissue response, unchanged. Therefore, FLASH therapy may have a significant advantage over conventional radiation therapy, since it can act on tumors while reducing damage to healthy tissues.

[0005]

[0005] The FLASH effect is highly dependent on the time structure of the radiation delivery to ensure that the dose rate is high enough to activate the FLASH effect.

[0006]

[0006] Therefore, knowledge of the time structure of the beam delivery is crucial to ensure that the treatment plan has the intended effect on the patient. The rate of energy deposition within a voxel depends on several factors, including: Scanning characteristics of the delivery system Beam current Beam quality Treatment planning

[0007]

[0007] When delivering FLASH therapy with a scanned proton beam, dose is the cumulative resultant energy deposition. Energy deposition over time is significant and depends on the rate of energy deposition within a voxel, which is a function of the scanning characteristics of the delivery system, the beam current, the treatment plan, and the beam quality.

[0008]

[0008] Typically, predictions of system characteristics may be provided by system vendors in the form of nominal data or models of the system. This is not always the case, and even if it is, it may be desirable to verify the data to ensure that the treatment delivered to the patient will have the intended characteristics. As explained above, this is particularly important in the case of FLASH therapy, where time structure is essential to achieve the desired effect. Summary of the Invention

[0009]

[0009] Accordingly, it is an object of the present disclosure to ensure that radiation therapy is delivered as intended by the delivery device.

[0010]

[0010] The present invention provides a computer-based method for use with a radiation therapy delivery system configured to deliver ion radiation therapy according to a plan, comprising: obtaining a time-resolved simulation of quantities representative of a beam delivery sequence of the planned delivery according to a model of the system; obtaining time-resolved measurements of quantities representative of a beam delivery sequence of the delivery of the plan associated with execution of the plan; comparing data relating to the time-resolved measurements with time-resolved simulations; performing an action depending on the result of the comparison, the action including at least one of: deciding whether to adapt the model or the plan, or diagnosing the functionality of the delivery system; The present invention relates to a method comprising the steps of:

[0011]

[0011] This allows the evaluation or validation of system properties by comparing a simulation of a plan based on a model of the system with the actual execution of the plan. As explained above, system properties are particularly important for treatment plans such as FLASH treatment plans, which are highly dependent on the time structure of delivery. This means that if the model is incorrect, the effective dose can change significantly. The plan may be a treatment plan designed for delivery to a patient, or a test plan, which is usually simpler than a treatment plan and is used to test aspects of the delivery system. Adapting the model may involve modifying the model itself or adjusting one or more parameters of the model.

[0012] The comparing step typically involves comparing the time-resolved measurement with a time-resolved simulation.

[0013] According to an embodiment, the method further comprises: obtaining simulated dose information based on a time-resolved simulation; Obtaining measured dose information based on time-resolved measurements Including, The comparing step includes comparing the simulated dose information with measured dose information, the dose information including information regarding at least one of a physical dose, an RBE weighted dose, and a FLASH dose resulting from the plan.

[0014]

[0014] Relative biological effectiveness (RBE)-weighted dose refers to the effective dose to the patient, which is affected by dose rate, type of radiation, and other factors known to those skilled in the art, and may differ from the physical dose. A FLASH dose is a special case of an RBE-weighted dose, where very high dose rates result in an even larger change between the physical dose and the RBE-weighted dose.

[0015]

[0015] In some preferred embodiments, the time-resolved measurements are obtained from a dry run of the plan, which allows for tuning of the model parameters prior to execution of the actual treatment plan on the patient.

[0016] In other embodiments, time-resolved measurements are obtained during delivery of the plan to the patient, in which case data obtained from the measurements may be used to adjust the remaining fraction of the plan based on the error between the dose according to the plan and the actually delivered dose.

[0017]

[0017] As is common in the art, a treatment plan may be designed to be delivered to a patient in multiple fractions, and time-resolved simulations may be obtained for one or more of these fractions. In these cases, simulations may be obtained at various stages of the treatment, usually just prior to the delivery of one of the fractions, taking into account that changes in environmental factors such as temperature and atmospheric pressure may affect the simulation.

[0018]

[0018] The time-resolved measurements may be obtained during the delivery of one or more of the same fractions as the time-resolved simulation, and the step of taking an action includes adapting the delivery of the subsequent fractions. This is particularly useful when the measurements are obtained as a dry run of the system delivering the subsequent fractions. In this case, the dry run may be used to obtain information about the current functionality of the system and what the outcome of the delivery of the subsequent fractions will be, and this information may be used to adapt the subsequent fractions to the current functionality of the system.

[0019]

[0019] Preferably, the time resolved measurements are obtained during the delivery of one or more of the same fractions as the time resolved simulation.

[0020]

[0020] The method may include a step of obtaining delivered FLASH dose information from time-resolved measurements and a step of obtaining simulated FLASH dose information from time-resolved simulations, where the comparing step includes comparing the delivered FLASH dose information with the simulated FLASH dose information, and the taking action step includes modifying the plan for a subsequent fraction.

[0021] The comparing step may include comparing cumulative dose information from one fraction or multiple fractions. If time-resolved measurements are obtained from a dry run prior to delivery of a particular fraction, the results of the comparison may be used to adapt that particular fraction to account for differences.

[0022]

[0022] The step of taking an action may include adjusting the model based on the results of the comparison.

[0023]

[0023] The step of taking an action may include evaluating functionality of the delivery system based on the results of the comparison.

[0024]

[0024] The measurements may be carried out in any suitable manner and using any suitable detector, for example a detector such as a radiation detector array or a lateral integrating detector.

[0025]

[0025] The model of the system may include parameter values ​​based on nominal data provided for the delivery system. Such parameter values ​​are typically provided by the system vendor. Alternatively, the model may include data obtained by experimental characterization of the system. This means that the parameter values ​​are determined based on testing of the delivery system. In either case, this method allows for validation and / or adjustment of the model's parameters. In either case, this method may also be used to adjust the model itself.

[0026]

[0026] The present disclosure also relates to a computer program product comprising computer readable code means which, when executed on a computer, causes the computer to perform the method according to any one of the embodiments discussed herein. The computer program product may comprise a non-transitory storage medium on which the code means is stored.

[0027]

[0027] The present disclosure also relates to a computer system comprising a processor, a program memory and optionally a data memory, the program memory comprising such a computer program product. [Brief description of the drawings]

[0028]

[0028] The invention is explained in more detail below, by way of example, with reference to the accompanying drawings, in which:

[0029] [Figure 1a] The dose rate and dose deposition of a voxel over a period of 500 ms are shown. [Figure 1b] The dose rate and dose deposition of a voxel over a period of 500 ms are shown. [Diagram 2] 1 is a general flow chart of a method according to an embodiment of the present invention. [Diagram 3] 4 is a flowchart of a method according to a second embodiment. [Figure 4] 11 is a flowchart of a method according to a third embodiment. [Diagram 5] 11 is a flowchart of a method according to a third embodiment. [Figure 6] 1 illustrates a computer system capable of implementing the disclosed methods. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0030]

[0029] Typical dose rate and dose accumulation time traces of a voxel in a PBS beam are shown in Fig. 1a and Fig. 1b. As shown in Fig. 1a, a voxel receives multiple dose contributions in a 500 ms period, and the dose rate varies because a spot aimed at a location close to a voxel will affect the voxel differently depending on how close it is. As can be seen, the dose rates of the four highest peaks vary from about 100 Gy / s to about 300 Gy / s, but each peak is only a few milliseconds long. The peaks are only a few milliseconds apart, meaning that they work together to produce an improved FLASH effect. Fig. 1b is a corresponding diagram showing the accumulated dose of the same voxel. Modeling the FLASH tissue compensation effect may require such a time trace as input data. It is therefore essential to be able to predict and measure such data.

[0031]

[0030] In accordance with the present disclosure, it is desirable to obtain time trace data related to dose rate or dose deposition, or both, to be used as input data in modeling the effect of a treatment plan, particularly a FLASH treatment plan. Such time trace data may be obtained in a variety of ways. For example, in a proton beam scanning delivery system, as will be appreciated by those skilled in the art, the plan includes multiple energy levels and multiple spots within each energy level.

[0032]

[0031] Figure 2 is a flow chart of a general embodiment of the method according to the invention. The input data to the method include an ion-based radiation treatment plan S21 obtained by any suitable method and a model S22 of a treatment delivery system used to execute (deliver) the plan. The model may be provided by the system vendor or obtained in another way. In step S23, a simulated signal related to the execution of the treatment plan is obtained based on the plan S21 and the model S22. In step S24, a measurement signal related to the execution of the treatment plan using the delivery system is obtained by measuring a beam delivery sequence. The beam delivery sequence may include the execution of the plan on a patient or may be a dry run without a patient. Both the simulated signal and the measurement signal are time-resolved signals reflecting quantities representative of the beam delivery sequence of the execution of the treatment plan S21 based on the model and the measurement, respectively. Instead of the treatment plan S21, the plan may be a test plan designed to test the functionality of the system but not suitable for execution on a patient.

[0033]

[0032] In step S25, the simulated signal is compared with the measured signal. Step S26 is a decision step to determine what action to take depending on the result of the comparison. As a result, some action may need to be taken (S27). As will be discussed in more detail below, actions may include adjusting model parameters or improving the model itself, adapting the plan, or determining that the delivery system needs to be adjusted. As a result of the comparison, no action may need to be taken (S28).

[0034]

[0033] In each embodiment herein, the models S22, S32, S42, S52 of the therapy delivery system may be system models that include nominal parameters provided by the delivery system vendor or may be based on experimental characterization of the system. The models include parameter values ​​that may also be provided by the delivery system vendor or based on experimental characterization of the system. Thus, the simulated signals in S23, S33, S43, S53 represent simulations of the therapy delivery system that may deviate from the actual behavior of the therapy delivery system.

[0035]

[0034] The measurements may be performed using any suitable form of detector, typically a type of ion chamber detector. Such detectors are available as detector arrays and as transverse integrating detectors configured to measure the total signal of the entire beam. The measured quantities may include the beam current and / or one or more other parameters that vary over time, e.g. · the current to the magnets controlling the beam (this will be particularly useful for comparing measured data with modelled or nominal data); Gantry angle for ARC treatment One or more of these may be used in the delivery data.

[0036]

[0035] In each embodiment herein, the time-resolved measurements S24, S34, S44, S54 may be performed as a dry run of the plan using the treatment delivery system. The dry run may be performed without a patient, with or without a phantom. Another way to obtain such data is during the execution of the plan on the patient. In this case, a measuring device needs to be provided near the patient to measure the actual radiation delivered, e.g., the beam current as a function of time. The measurements need to have a sufficiently high time resolution to allow the desired radiobiological modeling, preferably at least 1 ms. More preferably, it will be a fraction of a ms, e.g., 1 / 10 of a ms. In both cases, the time-resolved measurements represent the actual beam delivery sequence from the treatment delivery system.

[0037]

[0036] In both above cases, the measurement can be performed by methods known per se, for example by picking up the signal from one of the existing ion chamber monitors, or by inserting a dedicated independent detector into the beam or the phantom being delivered. The measurement can be performed over a suitable period of time that corresponds to the time of radiation delivery. The detector can generally include an array of detectors, each configured to detect the time at which the dose is received and the magnitude of the dose received. Alternatively, a single ion chamber detector can be used, such as a wide parallel planar ion chamber that measures the current of the entire beam. Both radiation detector arrays and single ion chamber detectors are available to those skilled in the art. Matching the plan data (spot data and energy layer data) with the time trace allows accurate plan execution timing characterization. The data will have essentially the same structure as shown in Figure 1a and Figure 1b.

[0038]

[0037] As is common in the art, a treatment plan may be divided into multiple treatment fractions that are administered to a patient at regular time intervals, for example, one fraction per day. The simulation of steps S23, S33, S43, S53 and the measurement of steps S24, S34, S44, S54 may be performed for the complete plan including one or more fractions. Alternatively, the simulation and measurement steps may be performed for one or more fractions.

[0039]

[0038] As discussed below, the comparison may be performed by comparing the simulated time-resolved signal with the time-resolved measurement signal, and the signal may be processed in an appropriate manner before the comparison. For example, as discussed in more detail in connection with FIG. 4, the dose delivered according to the simulated time-resolved signal and the measured time-resolved signal may be calculated and the doses compared. The dose may be calculated as a physical dose. In many cases, it will be more appropriate to calculate the dose as an RBE dose, taking into account the effective dose in each specific case. As explained above, the RBE dose may differ from the physical dose depending on factors such as the type of radiation, the dose rate, the total dose, and other factors. If the treatment includes a FLASH treatment, the dose may be calculated as a FLASH dose to reflect the FLASH effect resulting from the beam delivery sequence. This is a special case of RBE, since the very high dose rate used in FLASH treatment results in a large error between the physical dose and the RBE dose. As mentioned above, the FLASH effect is highly dependent on the time structure of treatment delivery, and therefore differences between the model and the actual system characteristics can lead to large errors between the planned dose and the actual dose delivered to the patient.

[0040]

[0039] Figure 3 shows a specific embodiment of the method according to the invention, which can be used to evaluate the function of a treatment delivery system. This is suitably performed at regular time intervals, for example once a week, to ensure that the system is functioning properly. As in Figure 2, the input data includes a treatment plan S31 and a system model S32. In this case, the treatment plan may be a simple plan that is not intended to be executed, for example just a uniform beam. As in Figure 2, a simulated time-resolved signal is obtained based on the treatment plan S31 and the system model S32. During the execution of the plan, a measured time-resolved signal is obtained (S34). Step S34 will usually be performed during a dry run. In step S35, the simulated time-resolved signal is compared with the measured time-resolved signal. Step S36 is a decision step. If the comparison in step S35 indicates a system anomaly, an action is taken in step S37, for example, to warn the operator that the system needs adjustment. If the comparison shows that the measured time-resolved signal and the simulated time-resolved signal match, no action needs to be taken (step S38).

[0041]

[0040] Figure 4 shows another embodiment of the method according to the invention. As before, the input data includes a treatment plan S41 and a system model S42. As in Figures 2 and 3, in step S43, a simulated time-resolved signal is obtained based on the treatment plan S41 and the system model S42, and in step S44, a measured time-resolved signal is obtained. In this embodiment, the simulated signal is processed in step S43' to obtain simulated dose information related to the dose resulting from the plan according to the system model S42. Similarly, the measured signal is processed in step S44' to obtain measured dose information related to the dose resulting from the plan according to the measured data. In step S45, the simulated dose information is compared with the measured dose information. Step S45 may also optionally include comparing the simulated signal with the measured signal, as in step S25. If the comparison indicates that the measured dose information deviates from the simulated dose information by more than a certain threshold, a decision step S46 determines that an action needs to be taken in step S47. Alternatively, if the measured and simulated dose information match, then no action may be taken in step S48. In this embodiment, the actions taken in step S47 include: - errors in the system model may cause a signal to be generated to warn the operator that the actual delivered dose resulting from the execution of the treatment plan will deviate from the planned dose; A comparison may be performed between the simulated and measured signals obtained in steps S43 and S44 to help identify sources of error; It may contain one or more of the following:

[0042]

[0041] In each of the embodiments discussed in relation to Figures 2, 3 and 4, the treatment plan may be designed to be performed all at once or in one or more fractions. In the latter case, the simulations in steps 23, 33, 43 and the measurements in steps 23, 33, 43 may relate to all fractions or just one fraction, or to multiple fractions.

[0043]

[0042] Figure 5 shows a third embodiment that allows dose tracking and plan adaptation when a treatment plan is designed to be performed in multiple fractions. In such a case, it is appropriate to evaluate the dose and adjusted dose delivered to the patient during one fraction and accumulated for all performed fractions, and to use this data to adapt the plan for the remaining fractions.

[0044]

[0043] As before, the input data includes the treatment plan S51 and the model S52 of the treatment delivery system. In step S53, simulated signals are obtained, which are time-resolved measurement signals of quantities representative of the beam delivery sequence of the execution of one or more fractions of the plan. In step S54, measurement signals are obtained, which are time-resolved measurement signals of quantities representative of the beam delivery sequence of the execution of one or more fractions of the plan. Optionally, steps S53' and S54' may be included to calculate simulated dose information and measured dose information, respectively, based on the simulated and measured signals, similar to steps S43' and S44'. In step S55, the simulated and measured signals and / or the simulated and measured doses are compared. Step S56 is a decision step to determine the need for further action.

[0045]

[0044] In a first implementation of the third embodiment, the measured signal is obtained in step S54 during a dry run of a target fraction not yet performed on the patient, preferably a fraction to be performed immediately after the measurement, for example on the same day. In this case, the result of the comparison in step S55 is an indication of how the system will perform the delivery and what the actual dose resulting from the target fraction will be. In the dry run, more than one fraction may be considered. In this implementation, the result of the comparison can be used to modify the target fraction, and possibly other remaining fractions, to match the current characteristics of the system. It can also be used to determine that a completely new plan needs to be obtained if the simulated and measured signals are too different.

[0046]

[0045] In the second implementation of the third embodiment, the measurement signal obtained in step S54 may have been obtained during the execution of one or more previous fractions or as a dry run of one or more previous fractions. Thus, in step S54', actual accumulated dose information from one or more previous fractions is obtained based on the dry run of the system or the execution of the actual fractions on the patient. A simulated accumulated dose is calculated in step S53' based on the simulated signal. The information on the actual accumulated dose may be used to recalculate the remaining fractions, taking into account the difference between the actual accumulated dose and the simulated accumulated dose.

[0047]

[0046] Figure 6 is a schematic overview of a computer system capable of implementing the method according to the present disclosure. A computer 61 comprises a processor 63, a data memory 64 and a program memory 65. Preferably, there are also one or more user input / output means 67, 68 in the form of a keyboard, a mouse, a joystick, voice recognition means and / or other available user input means, as well as a display, a speaker etc. for output. The user input means may also be arranged to receive data from an external memory unit.

[0048]

[0047] The data memory 64 holds data that may be used in the method, such as nominal system data provided by the vendor, one or more treatment plans, and / or simulation results. As will be appreciated, the data memory 64 is shown only diagrammatically. There may be several data memory units, each holding one or more different types of data.

[0049]

[0048] The program memory 65 holds a computer program configured to control the processor to execute procedures according to any of the embodiments discussed above. As with the data memory 64, the program memory may also be implemented as one or several units, as required.

Claims

1. 1. A computer-based method for use with a radiation therapy delivery system configured to deliver ion radiation therapy according to a plan, the method comprising: - obtaining a time-resolved simulation of quantities representative of a beam delivery sequence of the delivery of said plan according to a model of said system; - obtaining time resolved measurements of quantities representative of a beam delivery sequence of the treatment plan associated with the delivery of the plan; - comparing data associated with said time-resolved measurements with said time-resolved simulations; - taking actions depending on the results of the comparison, the actions including at least one of: deciding whether to adapt the model or the plan, or diagnosing the functionality of the delivery system; The method includes:

2. The method of claim 1 , wherein the comparing step comprises comparing the time-resolved measurement to the time-resolved simulation.

3. - obtaining simulated dose information based on said time-resolved simulation; - obtaining measured dose information based on said time-resolved measurements; Further comprising: the comparing step includes comparing the simulated dose information with the measured dose information, the dose information including information regarding at least one of a physical dose, an RBE weighted dose, and a FLASH dose obtained from the plan. The method according to claim 1 or 2.

4. The method of claim 1 , wherein the time-resolved measurements are obtained based on a dry run of the plan.

5. 4. The method of claim 1, wherein the plan is a treatment plan and the time-resolved measurements are obtained based on delivery of the treatment plan to a patient.

6. The method of claim 5 , wherein the treatment plan is designed to be delivered to the patient in two or more fractions, and the time-resolved simulations are obtained for one or more of these fractions.

7. 7. The method of claim 6, wherein the time-resolved measurements are obtained during delivery of the same or more fractions as the time-resolved simulation, and the taking of an action comprises adapting delivery of one or more subsequent fractions.

8. 8. The method of claim 7, comprising the steps of obtaining delivered FLASH dose information from the time-resolved measurements and obtaining simulated FLASH dose information from the time-resolved simulations, and wherein the comparing step comprises comparing the delivered FLASH dose information to the simulated FLASH dose information.

9. The method of claim 6 , wherein the comparing step comprises comparing cumulative dose information from multiple fractions.

10. The method of claim 1 , wherein the step of taking an action comprises adjusting the model of the system based on the results of the comparison.

11. The method of claim 3 , wherein the step of taking an action includes evaluating the functionality of the delivery system based on a result of the comparison.

12. The method of claim 1 , wherein the model of the system includes parameters based on nominal data provided to the delivery system, or the model of the system includes parameters obtained by experimental characterization of the system.

13. A computer program product comprising computer readable code means which, when executed on a computer, causes said computer to carry out the method of any one of claims 1 to 12.

14. 15. A computer system comprising a processor, a program memory and optionally a data memory, said program memory comprising the computer program product of claim 14.

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