Adaptive radiotherapy plan optimization method and electronic device

Abstract

Provided in the present disclosure are an adaptive radiotherapy plan optimization method and an electronic device. The method comprises: acquiring a radiotherapy plan consisting of I fractions of radiotherapy formulated for a target volume of a subject to be subjected to radiotherapy, I being an integer greater than 1; before an i-th fraction of radiotherapy starts, acquiring a morphological and positional image of said subject, and on the basis of said image, optimizing the radiotherapy plan for said subject, said image being used for indicating the morphology and / or position of the target volume of said subject, the i-th fraction of radiotherapy being the i-th fraction of radiotherapy among the I fractions of radiotherapy, and i being 1, 2, 3, ... I; and during the i-th fraction of radiotherapy, within a continuous radiation beam-on duration and / or within a radiation beam-off duration before the continuous radiation beam-on duration, acquiring a morphological and positional image of said subject, and on the basis of the morphological and positional image, optimizing the optimized radiotherapy plan for said subject.

Description

Adaptive radiotherapy planning optimization methods and electronic equipment Technical Field

[0001] This disclosure relates to the field of medical technology, and in particular to an adaptive radiotherapy planning optimization method and electronic device. Background Technology

[0002] Improving the precision of treatment has always been a key direction in the development of radiotherapy. To adapt to changes in the morphology and location of tumors during radiotherapy, improve treatment precision, thereby reducing damage to healthy tissues and enhancing the effectiveness of tumor treatment, adaptive radiotherapy is being used more and more widely in clinical practice.

[0003] Current adaptive radiotherapy techniques can only adapt to changes in tumor morphology and location between fractionated radiotherapy sessions to a certain extent, eliminating some dose errors between fractionated sessions. However, they cannot eliminate the impact of changes in tumor target morphology within the fractionated radiotherapy session. Adapting to changes in target morphology and location to continuously optimize and adjust the treatment plan is the development trend for improving radiotherapy precision.

[0004] Summary of the Invention

[0005] This disclosure provides an adaptive radiotherapy planning optimization method and electronic device, which is used to continuously optimize the treatment plan in real time by adapting to changes in the shape and position of the target area during adaptive radiotherapy, whether before or during fractionated radiotherapy, thereby improving radiotherapy accuracy.

[0006] According to one aspect of this disclosure, an adaptive radiotherapy planning optimization method is provided. The method includes: acquiring a radiotherapy plan for I fractions of radiotherapy targeting a target area of ​​a subject to be radiotherapy, where I is an integer greater than 1; before the start of the i-th fraction, acquiring a shape-position image of the subject to be radiotherapy, and optimizing the radiotherapy plan based on the shape-position image; wherein the shape-position image is used to indicate the morphology and / or position of the target area of ​​the subject to be radiotherapy, and the i-th fraction is the i-th fraction of the I fractions of radiotherapy, where i is 1, 2, 3, ..., 1; during the i-th fraction, within a sustained beam exit segment, acquiring a shape-position image of the subject to be radiotherapy, and optimizing the optimized radiotherapy plan based on the shape-position image; and / or, within a non-continuous beam exit segment before the sustained beam exit segment, acquiring a shape-position image of the subject to be radiotherapy, and optimizing the optimized radiotherapy plan based on the shape-position image.

[0007] In some embodiments, within the i-th fraction of radiotherapy, acquiring a positional image of the subject to be radiotherapy within the continuous beam emission segment of the radiation beam, and optimizing the radiotherapy plan for the subject based on the positional image, includes: acquiring a positional image of the subject to be radiotherapy at time j within the continuous beam emission segment of the i-th fraction of radiotherapy, or after time j and before time j+1; optimizing the radiotherapy plan for the subject to be radiotherapy based on the positional image of the subject to be radiotherapy, so that the subject to be radiotherapy is irradiated at time j+1 within the continuous beam emission segment of the radiation beam based on the optimized radiotherapy plan; wherein, time j is the j-th time among J times within the continuous beam emission segment of the i-th fraction of radiotherapy, where j is 1, 2, ..., J, and J is an integer greater than 1.

[0008] In some embodiments, the interval between J time points within the continuous beam emission segment of the i-th fractional radiotherapy is determined based on the respiratory cycle or respiratory rate of the subject to be radiotherapy.

[0009] In some embodiments, at time j within the continuous beam emission segment of the i-th fractional radiotherapy, or after time j and before time j+1, optimizing the radiotherapy plan for the optimized radiotherapy subject based on the geoid image includes: predicting the geoid image of the radiotherapy subject at time j+1 based on the geoid image of the radiotherapy subject acquired between time j and time j+1 within the continuous beam emission segment of the i-th fractional radiotherapy; and optimizing the radiotherapy plan for the optimized radiotherapy subject based on the geoid image of the radiotherapy subject at time j+1.

[0010] In some embodiments, during the i-th fraction of radiotherapy, the acquisition of a positional image of the target subject within the non-continuous radiation beam segment before the continuous radiation beam exits, and the optimization of the radiotherapy plan for the target subject based on the positional image, includes: acquiring a positional image of the target subject within the k-th continuous radiation beam exit segment during the i-th fraction of radiotherapy; optimizing the radiotherapy plan for the target subject based on the positional image, so as to irradiate the target subject within the k-th continuous radiation beam exit segment based on the optimized radiotherapy plan for the target subject; wherein, the k-th continuous radiation beam exit segment is the k-th continuous radiation beam exit segment among the K continuous radiation beam exit segments in the i-th fraction of radiotherapy, where k is 1, 2, ..., K, and K is an integer greater than or equal to 1.

[0011] In some embodiments, before the start of the i-th fraction of radiotherapy, and / or during the sustained beam exit segment of the i-th fraction of radiotherapy, and / or during the non-exit segment of the radiation beam before the sustained beam exit segment of the i-th fraction of radiotherapy, optimizing the radiotherapy plan for the subject to be radiotherapy based on the geopotential image includes: searching a set of control point parameters corresponding to the shape and / or position of the target area in a preset plan library based on the shape and / or position of the target area in the geopotential image of the subject to be radiotherapy, wherein the set of control point parameters is a set of control point parameters to be optimized in the radiotherapy plan of the subject to be radiotherapy; and optimizing the radiotherapy plan for the subject to be radiotherapy based on the set of control point parameters if a set of control point parameters corresponding to the shape and / or position of the target area is found in the preset plan library.

[0012] In some embodiments, the method further includes: if it is determined that a set of control point parameters corresponding to the shape and / or position of the target area cannot be found from the preset plan library, determining the shape and position changes of the target area of ​​the subject to be radiotherapy based on the shape and position image, and optimizing the optimized radiotherapy plan of the subject to be radiotherapy based on the shape and position changes of the target area; wherein, the shape and position changes of the target area include positional changes and / or shape changes of the target area caused by periodic movement and / or non-periodic movement of the subject to be radiotherapy.

[0013] In some embodiments, the continuous emission segment of the radiation beam within the i-th fractional radiotherapy is either the j-th time within the continuous emission segment of the radiation beam within the i-th fractional radiotherapy or after the j-th time and before the (j+1)-th time; wherein the j-th time is the j-th time among the J times within the continuous emission segment of the radiation beam within the i-th fractional radiotherapy, where j is 1, 2, ..., J, and J is an integer greater than 1; the non-emission segment of the radiation beam before the continuous emission segment of the radiation beam within the i-th fractional radiotherapy is the segment before the k-th continuous emission segment of the radiation beam within the i-th fractional radiotherapy; wherein the k-th continuous emission segment of the radiation beam is the k-th continuous emission segment among the K continuous emission segments of the radiation beam within the i-th fractional radiotherapy, where k is 1, 2, ..., K, and K is an integer greater than or equal to 1.

[0014] In some embodiments, at time j within the continuous beam-out segment of the k-th radiation beam in the i-th fraction of radiotherapy, or after time j and before time j+1, based on the shape and / or position of the target area in the geodesic image of the subject to be radiotherapy, a set of control point parameters corresponding to the shape and / or position of the target area is searched in a preset planning library. This includes: predicting the shape and / or position of the target area at time j+1 based on the shape and / or position of the target area in the geodesic image of the subject to be radiotherapy at time j+1, or after time j and before time j+1, within the continuous beam-out segment of the k-th radiation beam in the i-th fraction of radiotherapy; and searching the preset planning library for the set of control point parameters corresponding to the shape and / or position of the target area at time j+1.

[0015] In some embodiments, in the adaptive radiotherapy planning optimization method, both the radiotherapy plan for the subject to be radiotherapy and the optimized radiotherapy plan are stored in a preset plan library.

[0016] In some embodiments, the method further includes: determining the k-th cumulative dose deviation of the target area under-radiation within the k-th radiation beam continuous emission segment and before the k+1-th radiation beam continuous emission segment in the i-th fractional radiotherapy; wherein the k-th radiation beam continuous emission segment is the k-th radiation beam continuous emission segment during the K radiation beam continuous emission segments in the i-th fractional radiotherapy, where k is 1, 2, 3, K, and K is an integer greater than or equal to 1; compensating for the k-th cumulative dose deviation within the k+1-th radiation beam continuous emission segment, and / or compensating for the k-th cumulative dose deviation within the i+1-th fractional radiotherapy.

[0017] In some embodiments, the method further includes: determining the j-th cumulative dose deviation of the target area under-radiation at time j between time j and time j+1 within the k-th radiation beam continuous output segment in the i-th fractional radiotherapy; wherein, time j is the j-th time among J times in the radiation beam continuous output segment within the i-th fractional radiotherapy, j is 1, 2, ..., J, and J is an integer greater than 1; compensating the j-th cumulative dose deviation at time j+1 within the k-th radiation beam continuous output segment, and / or compensating the j-th cumulative dose deviation within the k+1-th radiation beam continuous output segment, and / or compensating the j-th cumulative dose deviation within the i+1-th fractional radiotherapy.

[0018] In some embodiments, the method further includes: determining the i-th cumulative dose deviation of the target area under-radiation during the i-th fraction between the i-th fraction and the i+1-th fraction; and compensating for the i-th cumulative dose deviation during the i+1-th fraction.

[0019] In some embodiments, determining the cumulative dose deviation of the under-radiation in the target area includes: obtaining the actual dose received by the target area; and determining the cumulative dose deviation of the under-radiation in the target area based on the actual dose received by the target area and a standard dose.

[0020] In some embodiments, the actual dose received by the target area is obtained based on EPD and / or radiotherapy records.

[0021] In some embodiments, the method further includes: validating the optimized adaptive radiotherapy plan based on a simulation phantom, wherein the simulation phantom includes a real dynamic simulation phantom and / or a fully digital dynamic simulation phantom.

[0022] According to another aspect of this disclosure, an electronic device is provided, comprising: at least one processor; and a memory communicatively connected to the at least one processor; wherein the memory stores instructions executable by the at least one processor, the instructions being executed by the at least one processor to enable the at least one processor to perform the adaptive radiotherapy planning optimization method provided in this disclosure.

[0023] According to another aspect of this disclosure, a non-transitory computer-readable storage medium is provided storing computer instructions, wherein the computer instructions are used to cause the electronic device to perform the adaptive radiotherapy planning optimization method provided in this disclosure.

[0024] According to another aspect of this disclosure, a computer program product is provided, including a computer program that, when executed by a processor, implements the adaptive radiotherapy planning optimization method provided in this disclosure.

[0025] The technical solution provided in this disclosure acquires a shape and position image of the subject to be treated before the start of the i-th fraction of radiotherapy and optimizes the radiotherapy plan based on the shape and position image. Next, within the continuous beam-out segment and / or the non-beam-out segment before the continuous beam-out segment of radiotherapy in the i-th fraction, a shape and position image of the subject to be treated is acquired, and the optimized radiotherapy plan is further optimized based on the shape and position image. Thus, for the entire adaptive radiotherapy process, the radiotherapy plan is first optimized based on the shape and position image acquired before the fraction, and then iteratively optimized based on the shape and position image acquired within the continuous beam-out segment and / or non-beam-out segment of radiotherapy in the fraction. Throughout the adaptive radiotherapy process, the radiotherapy plan is iteratively optimized in real time to adapt to changes in the shape and position of the target area, making the radiotherapy plan more accurate and thus improving the accuracy of adaptive radiotherapy.

[0026] It should be understood that the description in this section is not intended to identify key or essential features of the embodiments of this disclosure, nor is it intended to limit the scope of this disclosure. Other features of this disclosure will become readily apparent from the following description. Attached Figure Description

[0027] The accompanying drawings are provided to better understand this solution and do not constitute a limitation of this disclosure. Wherein:

[0028] Figure 1 is a schematic diagram of an implementation environment shown in an embodiment of this disclosure;

[0029] Figure 2 is a flowchart illustrating an adaptive radiotherapy planning optimization method according to an embodiment of this disclosure;

[0030] Figure 3 is a schematic diagram of an adaptive radiotherapy planning optimization model according to an embodiment of this disclosure;

[0031] Figure 4 is a flowchart illustrating an adaptive radiotherapy planning optimization method based on a pre-built planning library according to an embodiment of this disclosure;

[0032] Figure 5 is a flowchart illustrating an adaptive radiotherapy dose compensation method according to an embodiment of this disclosure.

[0033] Figure 6 is a schematic diagram illustrating a dose compensation method in adaptive radiotherapy according to an embodiment of this disclosure;

[0034] Figure 7 is a block diagram of an electronic device used to implement the adaptive radiotherapy planning optimization method according to embodiments of the present disclosure. Detailed Implementation

[0035] The exemplary embodiments of this disclosure are described below with reference to the accompanying drawings, including various details of the embodiments to aid understanding, and should be considered merely exemplary. Therefore, those skilled in the art will recognize that various changes and modifications can be made to the embodiments described herein without departing from the scope and spirit of this disclosure. Similarly, for clarity and brevity, descriptions of well-known functions and structures are omitted in the following description.

[0036] First, the application scenarios involved in the embodiments of this disclosure are described. The adaptive radiotherapy planning optimization method provided in the embodiments of this disclosure can be applied to the field of medical technology, specifically to the scenario of adaptive radiotherapy.

[0037] Adaptive radiotherapy (ART) is a novel radiotherapy technique developed from image-guided radiotherapy (IGRT). Its core technology lies in dynamically adjusting the radiotherapy plan based on real-time data acquired by image acquisition equipment during radiotherapy, such as changes in tumor morphology (including size, shape, and other morphological characteristics) and location, as well as the irradiation status of surrounding normal tissues. The radiotherapy plan is a file used to control the delivery of radiation by the radiotherapy equipment.

[0038] Adaptive radiotherapy typically divides the radiotherapy process into multiple sessions, i.e., multi-fraction radiotherapy. Each fraction delivers a specific radiation dose to the patient, and the radiotherapy plan is dynamically adjusted based on the patient's current condition and changes in the tumor to ensure that each radiotherapy session achieves the best therapeutic effect.

[0039] However, current adaptive radiotherapy technology can only adapt to changes in the morphology and location of the tumor between fractions (i.e., between adjacent fractions) to a certain extent, and eliminate some dose errors between fractions. However, it cannot eliminate the dose deviation caused by real-time changes in tumor morphology during fractionation, especially during radiation.

[0040] Therefore, in adaptive radiotherapy, on the one hand, how to continuously optimize and adjust the treatment plan in real time, especially within fractionated radiotherapy, is a problem worthy of attention; on the other hand, how to compensate for dose deviations within fractionated radiotherapy is another problem worthy of attention.

[0041] Based on this, embodiments of this disclosure provide an adaptive radiotherapy planning optimization method. First, multiple fractionated radiotherapy plans are obtained for the target area of ​​the subject to be radiotherapy. For any fractionated radiotherapy: before the start of the fractionated radiotherapy, a shape-position image of the subject to be radiotherapy is obtained, and the radiotherapy plan for the subject to be radiotherapy is optimized based on the shape-position image; wherein, the shape-position image is used to indicate the shape and / or position of the target area of ​​the subject to be radiotherapy; during the fractionated radiotherapy, within the continuous beam exit segment, a shape-position image of the subject to be radiotherapy is obtained, and the optimized radiotherapy plan for the subject to be radiotherapy is further optimized based on the shape-position image; and / or, within the non-exit segment before the continuous beam exit segment, a shape-position image of the subject to be radiotherapy is obtained, and the optimized radiotherapy plan for the subject to be radiotherapy is further optimized based on the shape-position image. Therefore, it can be seen that throughout the entire process of real-time adaptive radiotherapy, whether before or during the continuous beam-out and / or non-beam-out segments of the fractionated radiotherapy, the radiotherapy plan can be continuously and adaptively optimized based on the real-time morphology and / or location of the tumor. This eliminates treatment deviations caused by tumor movement and deformation during radiotherapy, further reduces the extent of radiation to the treatment target area, and reduces the radiation dose and volume of healthy tissue, providing more room for increasing the tumor radiation dose and improving treatment efficacy.

[0042] This disclosure also provides a dose compensation method for adaptive radiotherapy. The method includes: within the i-th fraction of radiotherapy, a non-radiation segment after the k-th continuous beam exit segment and before the (k+1)-th continuous beam exit segment; determining the k-th cumulative dose deviation of the target area under-radiated within the k-th continuous beam exit segment; wherein the i-th fraction of radiotherapy is the i-th fraction of I fractions of radiotherapy, i being 1, 2, 3, ..., I, where I is an integer greater than 1; the k-th continuous beam exit segment is the k-th continuous beam exit segment during the K continuous beam exit segments within the i-th fraction of radiotherapy, k being 1, 2, 3, K, where K is an integer greater than or equal to 1; compensating for the k-th cumulative dose deviation within the (k+1)-th continuous beam exit segment, and / or compensating for the k-th cumulative dose deviation within the (i+1)-th fraction of radiotherapy. This can reduce or even eliminate dose deviation problems caused by tumor movement and deformation during radiotherapy.

[0043] Figure 1 is a schematic diagram of an implementation environment according to an embodiment of this disclosure. The radiotherapy system in this diagram is applicable to both adaptive radiotherapy planning optimization methods and adaptive radiotherapy dose compensation methods. Referring to Figure 1, the implementation environment includes an image acquisition device 101, a radiotherapy planning device 102, a control computer device 103, and a radiotherapy device 104.

[0044] The image acquisition device 101 is used to acquire images of the tumor site (i.e., the target area) and surrounding normal tissue of the subject to radiotherapy (such as a patient). In some embodiments, the image acquisition device 101 can be at least one of the following: a computed tomography (CT) device, an emission computed tomography (ECT) device, a magnetic resonance imaging (MRI) device, a positron emission tomography (PET) device, and an ultrasound examination device.

[0045] The radiotherapy device 104 is a device for performing radiotherapy on a subject (such as a patient). In some embodiments, the radiotherapy device 104 may include a gantry 1041, a treatment head 1042, an image guide device 1043, and a support device 1044.

[0046] The gantry 1041 can be a rotatable gantry. The treatment head 1042 can be mounted on the gantry and is used to emit a radiation beam to irradiate the target, such as gamma rays, MV-level X-rays, proton rays, etc. For example, the treatment head 1042 can be any two of the following: a gamma knife treatment head for rotationally focused radiotherapy, an accelerator treatment head for intensity-modulated radiotherapy, or other radiotherapy heads. In this embodiment, the treatment head 1042 can correspond to different radiotherapy modes, such as rotationally focused radiotherapy and intensity-modulated radiotherapy. The image guidance device 1043 is used for positioning the subject to be radiotherapy and for real-time image guidance during radiotherapy. For example, the image guidance device 1043 includes an X-ray tube 1043A and a detector 1043B. The detector 1043B can receive the imaging beam emitted by the X-ray tube 1043A that passes through the subject to be radiotherapy and generate a shape and position image, which is used to indicate the shape and / or position of the target area of ​​the subject to be radiotherapy. The support device 1044 is used to support and move the subject to be radiotherapy and may be a treatment bed.

[0047] In some embodiments, when the subject to be radiotherapy is on the support device 1044, the rotation of the gantry 1041 can drive the treatment head 1042 to irradiate the subject in 360 degrees, thereby completing the radiotherapy.

[0048] The radiotherapy planning device 102 is used to acquire planned images of the patient to be radiotreated from the imaging device 101 and to acquire positional images of the patient to be radiotreated from the image guidance device 1043 in the radiotherapy device 104, in order to formulate, optimize, and evaluate radiotherapy plans. The radiotherapy planning device 102 may operate a radiotherapy planning system (TPS), which provides functions for formulating, optimizing, and evaluating radiotherapy plans. For example, the RT pro TPS system.

[0049] In some embodiments, the radiotherapy planning device 102 may include a TPS client 1021 and a TPS server 1022.

[0050] The TPS client 1021 can be at least one of the following devices: smartphone, smartwatch, desktop computer, laptop, virtual reality terminal, augmented reality terminal, wireless terminal, and laptop computer. For example, in some embodiments, a user can trigger the TPS server 1022 to execute an adaptive radiotherapy plan optimization process by running a radiotherapy planning system on the TPS server 1022 through the TPS client 1021, and then display the optimized radiotherapy plan. This effectively saves user time and provides a more intuitive presentation of the optimized treatment plan, allowing users to evaluate the radiotherapy plan.

[0051] The TPS server 1022 can be a standalone physical server, a server cluster consisting of multiple physical servers, a distributed file system, or at least one of the following cloud servers providing basic cloud computing services: cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communication, middleware services, domain name services, security services, content delivery networks, and big data or artificial intelligence platforms. This disclosure does not limit the specific implementation of these services. In some embodiments, the number of TPS servers 1022 can be greater or less, and this disclosure does not limit the implementation of these services. Of course, the TPS server 1022 can also include other functions to provide more comprehensive and diverse services. In some embodiments, the TPS server 1022 is used to provide background services for the TPS client 1021, such as performing an adaptive radiotherapy planning optimization process.

[0052] In one embodiment of this disclosure, the radiotherapy planning device 102 is used to acquire a radiotherapy plan for I fractions of radiotherapy targeting the target area of ​​the subject to be radiotherapy, where I is an integer greater than 1; before the start of the i-th fraction, a shape and position image of the subject to be radiotherapy is acquired, and the radiotherapy plan of the subject to be radiotherapy is optimized based on the shape and position image; wherein, the shape and position image is used to indicate the shape and / or position of the target area of ​​the subject to be radiotherapy, and the i-th fraction is the i-th fraction of the I fractions of radiotherapy, where i is 1, 2, 3, ..., I; during the i-th fraction, within the continuous beam exit segment of the radiation beam, a shape and position image of the subject to be radiotherapy is acquired, and the optimized radiotherapy plan of the subject to be radiotherapy is optimized based on the shape and position image; and / or, within the non-exit segment of the radiation beam before the continuous beam exit segment, a shape and position image of the subject to be radiotherapy is acquired, and the optimized radiotherapy plan of the subject to be radiotherapy is optimized based on the shape and position image.

[0053] In another embodiment of this disclosure, the radiotherapy planning device 102 is used to determine the k-th cumulative dose deviation of the target area under-radiation within the k-th radiation beam continuous emission segment and before the k+1-th radiation beam continuous emission segment in the i-th fractional radiotherapy; wherein, the i-th fractional radiotherapy is the i-th fractional radiotherapy in I fractional radiotherapy, i is 1, 2, 3, ..., I, and I is an integer greater than 1; the k-th radiation beam continuous emission segment is the k-th radiation beam continuous emission segment during the K radiation beam continuous emission segments in the i-th fractional radiotherapy, k is 1, 2, 3, K, and K is an integer greater than or equal to 1; the k-th cumulative dose deviation is compensated within the k+1-th radiation beam continuous emission segment, and / or, the k-th cumulative dose deviation is compensated within the i+1-th fractional radiotherapy.

[0054] The control computer device 103 is used to control the radiotherapy device 104 to execute the radiotherapy plan. In some embodiments, the control computer device 103 may include a host computer and a slave computer. The host computer is used to interact with the user, and the slave computer is used to control the movement of various moving parts in the radiotherapy device 104. The host computer may be at least one of devices such as smartphones, smartwatches, desktop computers, laptops, virtual reality terminals, augmented reality terminals, wireless terminals, and laptop computers, and / or server devices. The slave computer may be a control device such as a programmable logic controller (PLC).

[0055] The adaptive radiotherapy planning optimization method provided in this disclosure is described below based on the radiotherapy system configured in the implementation environment shown in Figure 1.

[0056] Figure 2 is a flowchart illustrating an adaptive radiotherapy planning optimization method according to an embodiment of this disclosure. In some embodiments, the adaptive radiotherapy planning optimization method is performed by an electronic device. For example, the electronic device may be the radiotherapy planning device shown in Figure 1 above. As shown in Figure 2, the method includes the following steps:

[0057] S201. Obtain a radiotherapy plan for I fractions of radiotherapy targeting the target area of ​​the patient to be radiotreated.

[0058] In this embodiment of the disclosure, the electronic device acquires a radiotherapy plan for the target area of ​​the subject to be radiotherapy. The radiotherapy plan involves multiple fractions of radiotherapy, with a total of I fractions, where I is an integer greater than 1. The subject to be radiotherapy refers to the user undergoing radiotherapy, such as a patient or a phantom used to simulate the patient.

[0059] A radiotherapy plan consisting of I fractions for the target area of ​​a patient undergoing radiotherapy can be based on the planning images of the patient and is a radiotherapy plan that divides the entire adaptive radiotherapy process into I fractions for the target area. Here, the planning images can be CT images, ECT images, MRI images, PET images, or a fusion of at least two of these images.

[0060] S202. Before the start of the i-th fraction of radiotherapy, obtain the shape and position image of the subject to be radiotherapy, and optimize the radiotherapy plan of the subject to be radiotherapy based on the shape and position image.

[0061] In this embodiment of the present disclosure, the electronic device acquires a shape-position image of the subject to be radiotreated before the start of the i-th fraction of radiotherapy, and optimizes the radiotherapy plan for the subject based on the shape-position image. The optimized radiotherapy plan should be applicable to the i-th fraction of radiotherapy. The shape-position image is used to indicate the shape and / or location of the target area of ​​the subject to be radiotreated. Since the shape-position image is acquired before the start of the i-th fraction of radiotherapy, it is closer to the current target area shape and / or location of the subject to be radiotreated than the planning image used to formulate the radiotherapy plan. Therefore, the radiotherapy plan optimized based on the shape-position image is more accurate.

[0062] It is understandable that the acquisition of the shape and position images of the subject to be radiotherapy and the optimization of the radiotherapy plan based on the shape and position images are both completed before the start of the i-th fraction of radiotherapy; the start of the i-th fraction of radiotherapy includes the positioning of the subject to be radiotherapy before the i-th fraction of radiotherapy.

[0063] In one example, acquiring the positional image of the patient before the start of the i-th fraction of radiotherapy and optimizing the radiotherapy plan based on the positional image can be done while the patient is being positioned on the support device, either invasively or non-invasively. This allows for full reuse of the positioning period and reduces the patient's waiting time in bed.

[0064] In another example, acquiring the positional image of the subject to be radiotherapy before the start of the i-th fraction of radiotherapy and optimizing the radiotherapy plan based on the positional image can also be done by acquiring the positional image of the subject to be radiotherapy before the subject is untied after the previous fraction of radiotherapy, i.e., the (i-1)-th fraction of radiotherapy, and then using this time before the start of the i-th fraction of radiotherapy to optimize the radiotherapy plan based on the positional image acquired after the (i-1)-th fraction of radiotherapy. Since the interval between two adjacent fractions of radiotherapy, such as the (i-1)th fraction and the ith fraction, is usually measured in days, for example, 1 to 2 days, and the morphology and / or position of the target area changes little after the (i-1)th fraction and before the ith fraction, on the one hand, after obtaining the shape and position images of the patient to be treated after the (i-1)th fraction, doctors have sufficient time to optimize the radiotherapy plan based on these images. On the other hand, optimizing the radiotherapy plan based on the shape and position images obtained after the (i-1)th fraction greatly shortens the patient's waiting time in bed.

[0065] Building upon this, during the positioning phase before the start of the i-th fraction of radiotherapy, a shape and position image of the patient to be radiotreated can be acquired and registered with the shape and position image acquired after the (i-1)-th fraction of radiotherapy. This determines the degree of morphological and / or positional change in the target area. If the degree of change in the morphology and / or position of the target area does not exceed a change threshold, the treatment plan optimized based on the shape and position image acquired after the (i-1)-th fraction of radiotherapy is used as the treatment plan for the i-th fraction. Otherwise, the treatment plan is re-optimized based on the shape and position image of the patient to be radiotreated acquired during the positioning phase before the start of the i-th fraction of radiotherapy. In this way, the optimized plan is more relevant to the current patient's condition, and the radiotherapy plan is more accurate.

[0066] S203. During the i-th fraction of radiotherapy, within the continuous beam-out segment, acquire the shape and position image of the subject to be radiotherapy, and optimize the radiotherapy plan of the subject based on the shape and position image; and / or, within the non-continuous beam-out segment before the continuous beam-out segment, acquire the shape and position image of the subject to be radiotherapy, and optimize the radiotherapy plan of the subject based on the shape and position image.

[0067] In this embodiment of the present disclosure, the electronic device acquires a shape and position image of the subject to be radiotreated within the continuous beam exit segment of the i-th fraction of radiotherapy and / or within the non-exit segment of the radiation beam before the continuous beam exit segment of the i-th fraction of radiotherapy, and optimizes the radiotherapy plan of the subject based on the shape and position image. In this way, adaptive optimization of the radiotherapy plan can be achieved within each fraction of radiotherapy based on the shape and position image acquired during the fraction.

[0068] It should be noted that the object of radiotherapy planning optimization within the i-th fraction can be multiple control point parameters.

[0069] The technical solution provided in this disclosure can continuously optimize the radiotherapy plan as the adaptive radiotherapy process progresses. Specifically, before the start of the i-th fraction, a shape and position image of the subject to be radiotherapy is acquired, and the radiotherapy plan is optimized based on the shape and position image. Next, within the continuous beam-out segment and / or the non-beam-out segment before the continuous beam-out segment in the i-th fraction, a shape and position image of the subject to be radiotherapy is acquired, and the optimized radiotherapy plan is further optimized based on the shape and position image. Thus, for the entire adaptive radiotherapy process, the radiotherapy plan is first optimized based on the shape and position image acquired before the fraction, and then iteratively optimized based on the shape and position image acquired within the continuous beam-out segment and / or non-beam-out segment in the fraction, in turn. Throughout the entire adaptive radiotherapy process, the radiotherapy plan is iteratively optimized in real time based on changes in the shape and position of the target area, making the radiotherapy plan more accurate and thus improving the accuracy of adaptive radiotherapy.

[0070] To more clearly explain the technical solution of this disclosure, the adaptive radiotherapy planning optimization model involved in this disclosure will be briefly introduced below.

[0071] The adaptive radiotherapy planning optimization model is a four-level iterative optimization model, as shown in Figure 3. Level 1: The radiotherapy plan for this treatment course, including the prescribed dosage, etc.; Level 2: Dividing this treatment course into 1, 2, ..., i, ..., I fractions, planning optimization can be performed between fractions; the interval between two fractions is on the order of days, for example, 1 to 2 days; Level 3: Taking the i-th fraction within the I fractions as an example, the i-th fraction is divided into 1, 2, ..., k, ..., K continuous beam exit segments and non-conducting beam exit segments before each continuous beam exit segment. Planning optimization can be performed between continuous beam exit segments (or within non-conducting beam exit segments). ) Perform plan optimization; Here, the non-exit segment of the radiation beam before the continuous beam exit segment can be a stage for adjusting the radiation field attributes, and its corresponding duration can be on the order of seconds, such as 10 seconds; Fourth level: Taking the kth continuous beam exit segment among K continuous beam exit segments as an example, the kth continuous beam exit segment is divided into 1, 2, ..., j, ..., J time moments, and the radiotherapy plan for the next time moment can be optimized at the corresponding time moment; Here, the interval between J time moments can be determined based on the respiratory cycle or respiratory rate of the subject to be radiotherapy. For example, the interval between time moments is on the order of hundreds of milliseconds, such as 100 milliseconds.

[0072] Therefore, a complete adaptive radiotherapy process is to progressively refine adaptive radiotherapy by following the progress of the radiotherapy process, taking the pre-treatment radiotherapy plan as the starting point and gold standard, and implementing it at three levels: between fractionated radiotherapy sessions, between continuous beam emission segments, and within the continuous beam emission segment.

[0073] It should be noted that within fractionated radiotherapy, the radiotherapy plan can be optimized only within the continuous beam emission segment, without optimization between continuous beam emission segments (i.e., within the non-emission segment), depending on the radiotherapy requirements. Alternatively, the plan can be optimized only between continuous beam emission segments (i.e., within the non-emission segment), without optimization within the continuous beam emission segment. Of course, it is also possible to optimize the plan both between continuous beam emission segments (i.e., within the non-emission segment) and within each continuous beam emission segment. Regardless of the choice, this disclosure iteratively optimizes the radiotherapy plan before and during fractionated radiotherapy.

[0074] The following will provide a detailed introduction to the optimization of radiotherapy plans in fractionated radiotherapy: (1) within the continuous beam-out segment of the radiation beam and (2) between the continuous beam-out segments of the radiation beam.

[0075] (1) Within the continuous beam exit segment of the radiation beam

[0076] Within the i-th fraction of radiotherapy, during the continuous beam egress segment, a shape and position image of the patient to be radiotreated is acquired, and the radiotherapy plan for the patient is optimized based on the shape and position image, including:

[0077] Referring to Figure 3, at time j within the continuous beam egress segment of the i-th fraction of radiotherapy, or after time j and before time j+1, the following steps A1 and A2 are performed:

[0078] A1. Obtain the shape and position images of the subject to be radiotherapy;

[0079] A2. Optimize the radiotherapy plan for the radiotherapy subject based on the shape and position images of the subject.

[0080] Thus, at time j+1 within the continuous beam emission segment of the radiation beam, the subject can be irradiated based on the iteratively optimized radiotherapy plan. Here, time j is the j-th time among the J times within the continuous beam emission segment of the radiation beam in the i-th fractional radiotherapy, where j is 1, 2, ..., J, and J is an integer greater than 1.

[0081] In some embodiments, at time j within the continuous beam-out segment of the i-th fraction of radiotherapy, or after time j and before time j+1, step A2 may include:

[0082] Step A21: Based on the shape and position image of the subject to be radiotherapy acquired at time j or after time j and before time j+1, predict the shape and position image of the subject to be radiotherapy at time j+1.

[0083] Step A22: Optimize the radiotherapy plan for the radiotherapy subject based on the positional image of the subject at time j+1.

[0084] Referring to Figure 3, in step S203, within the i-th fraction of radiotherapy, during the non-emergence segment before continuous beam emission, a shape and position image of the subject to be radiotherapy is acquired, and the radiotherapy plan for the subject is optimized based on the shape and position image, including:

[0085] (2) Interval between continuous beam exit segments of radiation beam

[0086] If the radiation beam before the continuous beam exit segment within the i-th fraction of radiotherapy does not exit the beam segment, steps A1 and A2 above are still performed, only the execution time is different:

[0087] A1. Obtain the shape and position images of the subject to be radiotherapy;

[0088] A2. Optimize the radiotherapy plan for the radiotherapy subject based on the shape and position images of the subject.

[0089] Thus, within the k-th radiation beam continuous output segment, the subject can be irradiated based on the optimized radiotherapy plan. Here, the k-th radiation beam continuous output segment is the k-th radiation beam continuous output segment among the K radiation beam continuous output segments within the i-th fractional radiotherapy, where k is 1, 2, ..., K, and K is an integer greater than or equal to 1.

[0090] It should be noted that when k is greater than or equal to 2, the non-emergence period of the radiation beam before the continuous beam-emergence period of the k-th radiation beam is the time period after the continuous beam-emergence period of the (k-1)-th radiation beam and before the continuous beam-emergence period of the k-th radiation beam.

[0091] To provide a detailed description of the adaptive radiotherapy planning optimization process based on the four-level iterative planning optimization model shown in Figure 3, this disclosure presents another adaptive radiotherapy planning optimization method. In some embodiments, this adaptive radiotherapy planning optimization method is executed by an electronic device. For example, the electronic device can be the radiotherapy planning device shown in Figure 1 above. Using the radiotherapy planning device as the executing entity, the method includes the following steps:

[0092] S401. Obtain the radiotherapy plan T for I fractionated radiotherapy sessions for the target area of ​​the patient to be radiotreated. Where I is an integer greater than 1.

[0093] S402. When i = 1, that is, before the start of the first fraction of radiotherapy, acquire a shape and position image of the target area of ​​the subject to be radiotherapy, indicating the shape and / or position of the target area, and optimize the radiotherapy plan T of the subject to be radiotherapy based on the shape and position image to obtain the optimized radiotherapy plan T. i =T1, execute step S403;

[0094] S403. During the K continuous beam-out segments within the i-th fraction of radiotherapy, perform the following step S4031;

[0095] S4031. When k=1, before the first continuous beam exit segment, the radiation beam exits the segment, and a shape and position image of the subject to be radiotherapy is acquired; based on the shape and position image of the subject to be radiotherapy, a radiotherapy plan T is developed. i The optimized radiotherapy plan T was obtained through optimization. ik =T i1 Based on the radiotherapy plan T during the continuous beam output segment of the k-th radiation beam. ik To administer radiation to a patient undergoing radiotherapy, follow step S4032.

[0096] S4032. At the Jth moment within the continuous beam-out segment of the kth radiation beam, perform the following step S40321;

[0097] S40321, j=1, that is, at the first moment within the continuous beam exit segment of the radiation beam, the shape and position image of the subject to be radiotherapy is acquired; based on the shape and position image of the subject to be radiotherapy, the radiotherapy device T is...ik Optimize the radiotherapy plan to obtain the optimized radiotherapy plan T ikj = T ik1 , and irradiate the radiotherapy target object based on the radiotherapy plan T at the (j + 1)-th moment within the continuous beam emission segment of the radiation beam ikj ≤;

[0098] S40322, j = j + 1; when j < J, at the j-th moment within the continuous beam emission segment of the radiation beam, obtain the morphological image of the radiotherapy target object; optimize the radiotherapy plan T based on the morphological image of the radiotherapy target object ik(j-1) to obtain the optimized radiotherapy plan T ikj , and irradiate the radiotherapy target object based on the radiotherapy plan T at the (j + 1)-th moment within the continuous beam emission segment of the radiation beam ikj , and return to execute step S40322; otherwise, execute step S4033;

[0099] S4033, k = k + 1; when k ≤ K, in the beam non-emission segment before the k-th continuous beam emission segment of the radiation beam, obtain the morphological image of the radiotherapy target object; optimize the radiotherapy plan T based on the morphological image of the radiotherapy target object i(k-1)(J-1) to obtain the optimized radiotherapy plan T ik , and irradiate the radiotherapy target object based on the radiotherapy plan T within the k-th continuous beam emission segment of the radiation beam ik , and execute step S4032; otherwise, return to execute step S404;

[0100] S404, i = i + 1; when i ≤ I, before the start of the i-th fractionated radiotherapy, obtain the morphological image indicating the morphology and / or position of the target tumor area of the radiotherapy target object, and optimize the radiotherapy plan T based on the morphological image (i-1)K to obtain the optimized radiotherapy plan T i , and return to execute step S403; otherwise, end the optimization of the adaptive radiotherapy plan.

[0101] Through the above adaptive radiotherapy plan optimization method, during the entire process of adaptive radiotherapy, the radiotherapy plan is continuously and adaptively optimized based on the real-time morphology and / or position of the tumor, improving the radiotherapy accuracy.

[0102] In the above method for optimizing the adaptive radiotherapy plan, the radiotherapy plan of the radiotherapy target object is optimized based on the morphological image, and the radiotherapy plan of the radiotherapy target object can be a radiotherapy plan optimized through one or more iterations. In the present disclosure, the methods for optimizing the radiotherapy plan of the radiotherapy target object based on the morphological image at least include the following several types:

[0103] Method 1: Directly optimize based on the morphological changes of the target tumor area of the radiotherapy target object in the morphological image.

[0104] In some embodiments, optimizing a radiotherapy plan for a subject to radiotherapy based on a geometrographic image may include:

[0105] The positional changes of the target area of ​​the patient to be radiotherapy are determined based on the positional images, and the radiotherapy plan for the patient to be radiotherapy is optimized based on the positional changes; wherein, the positional changes of the target area include the positional changes and / or shape changes of the target area caused by the periodic movement and / or non-periodic movement of the patient to be radiotherapy.

[0106] Method 2: Optimize the radiotherapy plan by searching a pre-stored radiotherapy plan or a set of control parameters within the radiotherapy plan based on a pre-set plan library; wherein, the set of control point parameters is the collection of control point parameters to be optimized in the radiotherapy plan of the object to be radiotreated.

[0107] In some embodiments, optimizing a radiotherapy plan for a subject to radiotherapy based on a geometrographic image may include:

[0108] Based on the shape and / or location of the target area in the geometry image of the patient to be radiotreated, a set of control point parameters corresponding to the shape and / or location of the target area is searched from the pre-set plan library, and the radiotherapy plan of the patient to be radiotreated is optimized based on the set of control point parameters.

[0109] Method 3 is a combination of Method 1 and Method 2.

[0110] In some embodiments, optimizing a radiotherapy plan for a subject to radiotherapy based on a geometrographic image may include:

[0111] B1. Based on the shape and / or position of the target area in the shape and position image of the subject to be radiotherapy, search the preset plan library for the set of control point parameters corresponding to the shape and / or position of the target area; wherein, the set of control point parameters is the set of control point parameters to be optimized in the radiotherapy plan of the subject to be radiotherapy.

[0112] B2. If it is determined that a set of control point parameters corresponding to the shape and / or location of the target area can be retrieved from the pre-set plan library, the radiotherapy plan for the radiotherapy subject shall be optimized based on the set of control point parameters.

[0113] B3. If it is determined that the set of control point parameters corresponding to the shape and / or position of the target area cannot be found from the pre-set plan library, determine the shape and position changes of the target area of ​​the subject to be radiotherapy based on the shape and position image, and optimize the radiotherapy plan of the subject to be radiotherapy based on the shape and position changes; wherein, the shape and position changes of the target area include the positional changes and / or shape changes of the target area caused by the periodic movement and / or non-periodic movement of the subject to be radiotherapy.

[0114] By searching the pre-built plan library, control point parameter sets can be quickly obtained based on the morphology and / or location of the target area, shortening the radiotherapy plan optimization time and thus enabling rapid optimization of radiotherapy plans for radiotherapy subjects.

[0115] In some embodiments, the radiotherapy plan for the subject to be radiotherapy may be optimized based on the geopotential image before the start of the i-th fraction, and / or during the continuous out-of-beam segment of the radiation beam in the i-th fraction, and / or during the non-out-of-beam segment of the radiation beam before the continuous out-of-beam segment of the radiation beam in the i-th fraction.

[0116] The continuous beam emission segment within the i-th fractional radiotherapy can be the j-th time within that continuous beam emission segment, or the time period after the j-th time and before the (j+1)-th time; where the j-th time is the j-th time among the J times within the continuous beam emission segment of the i-th fractional radiotherapy, and j is 1, 2, ..., J, where J is an integer greater than 1. The non-continuous beam emission segment before the continuous beam emission segment within the i-th fractional radiotherapy can be the segment before the k-th continuous beam emission segment within the i-th fractional radiotherapy; where the k-th continuous beam emission segment is the k-th continuous beam emission segment among the K continuous beam emission segments within the i-th fractional radiotherapy, and k is 1, 2, ..., K, where K is an integer greater than or equal to 1.

[0117] In some embodiments, at time j within the continuous outgoing segment of the k-th radiation beam in the i-th fraction of radiotherapy, or after time j and before time j+1, step B1 may include:

[0118] B11. Based on the shape and / or position of the target area in the shape and / or position image of the subject to be radiotherapy acquired at time j or after time j and before time j+1, predict the shape and / or position of the target area at time j+1.

[0119] B12. Search the preset plan library for the set of control point parameters that correspond to the shape and / or position of the target area at time j+1.

[0120] Figure 4 is a flowchart illustrating an adaptive radiotherapy planning optimization method based on a pre-set planning library according to an embodiment of this disclosure. In some embodiments, the adaptive radiotherapy planning optimization method based on a pre-set planning library is executed by an electronic device. For example, the electronic device can be the radiotherapy planning device shown in Figure 1 above. As shown in Figure 4, with the radiotherapy planning device as the executing entity, the method includes the following steps:

[0121] S501. Obtain a radiotherapy plan for I fractions of radiotherapy targeting the target area of ​​the patient to be radiotreated; where I is an integer greater than 1.

[0122] S502. Before the start of the i-th fraction of radiotherapy, acquire the shape and position image of the subject to be radiotherapy. Based on the shape and / or position of the target area in the shape and position image of the subject to be radiotherapy, search the preset plan library for a set of control point parameters corresponding to the shape and / or position of the target area. The set of control point parameters is the collection of control point parameters to be optimized in the radiotherapy plan of the subject to be radiotherapy. If it is determined that a set of control point parameters corresponding to the shape and / or position of the target area can be found in the preset plan library, proceed to step S503; otherwise, if it is determined that a set of control point parameters corresponding to the shape and / or position of the target area cannot be found in the preset plan library, proceed to step S504.

[0123] S503. Optimize the radiotherapy plan for the subject to be radiotherapy based on the control point parameter set, and store the optimized radiotherapy plan in the preset plan library;

[0124] S504. Determine the positional changes of the target area of ​​the subject to be radiotherapy based on the positional images, optimize the radiotherapy plan of the subject to be radiotherapy based on the positional changes of the target area, and store the optimized radiotherapy plan in the preset plan library; wherein, the positional changes of the target area include positional changes and / or shape changes of the target area caused by periodic movement and / or non-periodic movement of the subject to be radiotherapy.

[0125] S505. Before the continuous beam exit segment of the k-th radiation beam within the i-th fraction of radiotherapy, acquire the shape and position image of the subject to be radiotherapy. Based on the shape and / or position of the target area in the shape and position image of the subject to be radiotherapy, search for a set of control point parameters corresponding to the shape and / or position of the target area in the preset plan library. If it is determined that a set of control point parameters corresponding to the shape and / or position of the target area can be found in the preset plan library, proceed to step S506. Otherwise, if it is determined that a set of control point parameters corresponding to the shape and / or position of the target area cannot be found in the preset plan library, proceed to step S507.

[0126] S506. Optimize the radiotherapy plan for the target patient based on the control point parameter set, and store the optimized radiotherapy plan in the preset plan;

[0127] S507. Determine the positional changes of the target area of ​​the subject to be radiotherapy based on the positional images, optimize the radiotherapy plan of the subject to be radiotherapy based on the positional changes of the target area, and store the optimized radiotherapy plan in the preset plan; wherein, the positional changes of the target area include positional changes and / or shape changes of the target area caused by periodic movement and / or non-periodic movement of the subject to be radiotherapy.

[0128] S508. Between time j and time j+1 within the continuous output segment of the k-th radiation beam in the i-th fraction of radiotherapy, based on the shape and / or position of the target area in the shape and position image of the subject to be radiotherapy, search for a set of control point parameters corresponding to the shape and / or position of the target area in the preset plan library; if it is determined that a set of control point parameters corresponding to the shape and / or position of the target area can be found in the preset plan library, proceed to step S509; otherwise, if it is determined that a set of control point parameters corresponding to the shape and / or position of the target area cannot be found in the preset plan library, proceed to step S510.

[0129] S509. Optimize the radiotherapy plan for the target patient based on the control point parameter set, and store the optimized radiotherapy plan in the preset plan;

[0130] S5110. Determine the positional changes of the target area of ​​the subject to be radiotherapy based on the positional images, optimize the radiotherapy plan of the subject to be radiotherapy based on the positional changes of the target area, and store the optimized radiotherapy plan in the preset plan; wherein, the positional changes of the target area include the positional changes and / or shape changes of the target area caused by the periodic movement and / or non-periodic movement of the subject to be radiotherapy.

[0131] In the aforementioned adaptive radiotherapy planning optimization method based on a pre-built plan library, both the radiotherapy plan for the patient and the optimized plans at each stage are stored in the pre-built plan library. This allows for continuous optimization and improvement of the pre-built plan library, facilitating rapid searching of the corresponding control point parameter sets and enabling fast optimization of the radiotherapy plan.

[0132] Figure 5 is a schematic flowchart illustrating an adaptive radiotherapy dose compensation method according to an embodiment of this disclosure. In some embodiments, the adaptive radiotherapy dose compensation method is performed by an electronic device. For example, the electronic device may be the radiotherapy planning device shown in Figure 1 above. As shown in Figure 5, the method includes the following steps:

[0133] S601. Within the i-th fraction of radiotherapy, determine the k-th cumulative dose deviation of the target area under-radiated within the k-th radiation beam continuous emission segment after the k-th radiation beam continuous emission segment and before the k+1-th radiation beam continuous emission segment.

[0134] In this embodiment of the disclosure, as shown in FIG6, adaptive radiotherapy includes 1, 2, ..., i, ..., I fractions of radiotherapy; taking the i-th fraction of radiotherapy as an example, the i-th fraction is divided into 1, 2, ..., k, ..., K continuous beam output segments and non-beam output segments between two adjacent continuous beam output segments.

[0135] The electronic device determines the cumulative dose deviation of the target area under-radiated within the k-th radiation beam continuous emission segment of the subject during the i-th fraction of radiotherapy, after the k-th radiation beam continuous emission segment and before the k+1-th radiation beam continuous emission segment.

[0136] Among them, the subject to radiotherapy refers to the user who is to undergo radiotherapy, such as a patient or a phantom used to simulate a patient; the i-th fraction is the i-th fraction of I fractions, where i is 1, 2, 3, ..., I, and I is an integer greater than 1; the k-th continuous beam emission segment is the k-th continuous beam emission segment among K continuous beam emission segments in the i-th fraction, where k is 1, 2, 3, K, and K is an integer greater than or equal to 1.

[0137] S602. The cumulative deviation of the k-th dose is compensated within the continuous beam exit segment of the k+1-th radiation beam, and / or, the cumulative deviation of the k-th dose is compensated within the i+1-th fraction of radiotherapy.

[0138] In this embodiment of the present disclosure, as shown by arrow 1 in FIG6, the electronic device compensates for the cumulative deviation of the k-th dose during the (k+1)th radiation beam outgoing segment, and / or, as shown by arrow 2 in FIG6, the electronic device compensates for the cumulative deviation of the k-th dose during the (i+1)th fraction of radiotherapy.

[0139] In the above method, after the continuous output segment of the k-th radiation beam within the i-th fractional radiotherapy, the cumulative dose deviation of the k-th radiation under-radiation within the continuous output segment of the k-th radiation beam in the target area is first determined. Then, dose compensation is performed within the continuous output segment of the k+1-th radiation beam, but not within the i+1-th fractional radiotherapy; or, dose compensation is not performed within the continuous output segment of the k+1-th radiation beam, but is performed within the i+1-th fractional radiotherapy; or, dose compensation is performed both within the continuous output segment of the k+1-th radiation beam and within the i+1-th fractional radiotherapy. In this way, the cumulative dose deviation of the target area under-radiation caused by changes in morphology and position within the fractional radiotherapy is compensated, reducing or eliminating the dose deviation problem caused by changes in the morphology of the tumor target area.

[0140] In some embodiments, as shown in Figure 6, taking the k-th continuous beam emission segment among K continuous beam emission segments as an example, the k-th continuous beam emission segment is divided into 1, 2, ..., j, ..., J time points. Here, the interval between the J time points can be determined based on the respiratory cycle or respiratory rate of the subject to radiotherapy. Correspondingly, the above method also includes:

[0141] S603. Within the i-th fraction of radiotherapy, between time j and time j+1 within the continuous output segment of the k-th radiation beam, determine the cumulative dose deviation of the under-radiation in the target area at time j. Here, time j is the j-th time among the J times within the continuous output segment of the radiation beam in the i-th fraction of radiotherapy, where j is 1, 2, ..., J, and J is an integer greater than 1.

[0142] S604, as shown by arrow 3 in Figure 6, the cumulative dose deviation of the j-th dose is compensated at the (j+1)-th moment within the continuous beam-out segment of the k-th radiation beam, and / or, as shown by arrow 4 in Figure 6, the cumulative dose deviation of the j-th dose is compensated within the continuous beam-out segment of the k+1-th radiation beam, and / or, as shown by arrow 5 in Figure 6, the cumulative dose deviation of the j-th dose is compensated within the (i+1)-th fraction of radiotherapy.

[0143] In some embodiments, as shown in FIG3, adaptive radiotherapy includes 1, 2, ..., i, ..., I fractional radiotherapy sessions. Correspondingly, the method further includes:

[0144] S605. Between the i-th fraction of radiotherapy and the i+1-th fraction of radiotherapy, determine the i-th cumulative dose deviation of under-radiation in the target area within the i-th fraction of radiotherapy.

[0145] S606, as shown by arrow 6 in Figure 6, compensates for the cumulative deviation of the i-th dose within the (i+1)-th fraction of radiotherapy.

[0146] In some embodiments, determining the cumulative dose deviation of underradiation in the target area in steps S601, S603, and S605 described above may include:

[0147] C1. Obtain the actual dose received by the target area, which is the in vivo dose to the subject to be radiotherapy.

[0148] C2. Based on the actual dose received by the target area and the standard dose, determine the cumulative dose deviation of the under-radiation in the target area. Here, the standard dose can be obtained from the radiotherapy plan of the patient.

[0149] In some embodiments, the actual dose received by the target area can be obtained based on an Electronic Portal Imaging Device (EPID) and / or radiotherapy records. The EPID can be mounted on the gantry of the radiotherapy equipment, positioned opposite the treatment head. The radiation beam emitted from the treatment head passes through the subject and is received by the EPID, producing an EPID image. Based on the EPID image, the actual dose received by the target area can be determined. The dose emitted from the treatment head can be recorded in the radiotherapy records, thus, the actual dose received by the target area can also be determined based on the radiotherapy records.

[0150] In some embodiments, the method further includes: during the i-th fraction of radiotherapy, in the non-exit segments of the radiation beam after the k-th continuous beam exit segment and before the k+1-th continuous beam exit segment, acquiring a shape and position image of the subject to be radiotherapy, and optimizing the radiotherapy plan of the subject to be radiotherapy based on the shape and position image.

[0151] Thus, during the time window between the continuous output segment of the k-th radiation beam and the continuous output segment of the (k+1)-th radiation beam, i.e. within the non-radiation segment, such as the waiting time of the patient waiting in bed during the switch from the continuous output segment of the k-th radiation beam to the continuous output segment of the (k+1)-th radiation beam in clinical radiotherapy, on the one hand, the cumulative dose deviation of the k-th dose under-radiation in the target area within the continuous output segment of the k-th radiation beam is determined; on the other hand, the positional image of the patient is acquired, and the optimized radiotherapy plan for the patient is optimized based on the positional image of the patient. This allows for dose compensation within the continuous output segment of the (k+1)-th radiation beam, and radiation of the patient is performed based on the optimized radiotherapy plan, thereby improving the accuracy of radiotherapy.

[0152] Here, the duration corresponding to the radiation beam not exiting the beam segment can be on the order of ten seconds, for example, 10 seconds.

[0153] In some embodiments, the method further includes: acquiring a shape and position image of the subject to be radiotherapy between time j and time j+1 within the continuous output segment of the k radiation beam during the i-th fraction of radiotherapy; and optimizing the radiotherapy plan of the subject to be radiotherapy based on the shape and position image of the subject to be radiotherapy.

[0154] Thus, by utilizing the time window between time j and time j+1, on the one hand, the cumulative dose deviation of the under-radiation in the target area at time j is determined; on the other hand, the positional image of the subject to be radiotherapy is acquired, and the radiotherapy plan for the subject to be radiotherapy is optimized based on the positional image of the subject to be radiotherapy. This allows for dose compensation at time j+1, and the subject to be radiotherapy is then irradiated based on the optimized radiotherapy plan, further improving the accuracy of radiotherapy.

[0155] Here, the duration between time j and time j+1 within the continuous beam emission segment of the k-th radiation beam can be on the order of hundreds of milliseconds, such as 100 milliseconds.

[0156] The aforementioned dose compensation method for adaptive radiotherapy can also be combined with an adaptive radiotherapy planning optimization method. In this method, real-time spatial radiotherapy planning optimization is performed based on the anatomical structure of the target area in the deformed image. Simultaneously, dose deviation compensation optimization is performed physically during the iterative optimization of each stage of the radiotherapy plan. For example, at time j within the k-th continuous beam exit segment, and / or after the k-th continuous beam exit segment, and / or after the i-th fraction, the corresponding cumulative dose deviation of the under-radiated target area can be determined, and corresponding compensation for this cumulative dose deviation can be performed in subsequent steps of the adaptive radiotherapy process, such as at time j+1 within the k-th continuous beam exit segment, and / or within the k+1-th continuous beam exit segment, and / or within the i+1-th fraction. In this way, while optimizing the radiotherapy plan, the under-radiated dose of the target area can be compensated in a timely manner, making the radiotherapy more precise.

[0157] In some embodiments, after step S203, the method includes the following steps:

[0158] S204. Within the i-th fractional radiotherapy, determine the k-th cumulative dose deviation of the target area under-radiation within the k-th continuous beam emission segment, after the k-th continuous beam emission segment and before the (k+1)-th continuous beam emission segment; wherein, the k-th continuous beam emission segment is the k-th continuous beam emission segment among the K continuous beam emission segments within the i-th fractional radiotherapy, where k is 1, 2, 3, K, and K is an integer greater than or equal to 1. Compensate for the k-th cumulative dose deviation during the (k+1)-th continuous beam emission segment, and / or compensate for the k-th cumulative dose deviation within the (i+1)-th fractional radiotherapy.

[0159] In some embodiments, after step S203, the above method may further include:

[0160] S205. Within the i-th fractional radiotherapy, between time j and time (j+1) within the k-th radiation beam continuous output segment, determine the j-th cumulative dose deviation of the under-radiation in the target area at time j; wherein, time j is the j-th time among the J times of the radiation beam continuous output segment within the i-th fractional radiotherapy, j is 1, 2, ..., J, and J is an integer greater than 1; compensate for the j-th cumulative dose deviation at time (j+1) within the k-th radiation beam continuous output segment, and / or compensate for the j-th cumulative dose deviation within the k+1-th radiation beam continuous output segment, and / or compensate for the j-th cumulative dose deviation within the i+1-th fractional radiotherapy.

[0161] In some embodiments, after step S203, the above method may further include:

[0162] S206. Between the i-th fraction of radiotherapy and the (i+1)-th fraction of radiotherapy, determine the i-th cumulative dose deviation of the under-radiation of the target area within the i-th fraction of radiotherapy; and compensate for the i-th cumulative dose deviation within the (i+1)-th fraction of radiotherapy.

[0163] In some embodiments, determining the cumulative dose deviation of the under-radiation in the target area in steps S204, S205, or S206 includes: obtaining the actual dose received by the target area; and determining the cumulative dose deviation of the under-radiation in the target area based on the actual dose received by the target area and a standard dose. Here, the actual dose received by the target area is obtained based on EPD and / or radiotherapy records.

[0164] In some embodiments, the method may further include: validating the optimized adaptive radiotherapy plan based on a simulation phantom, wherein the simulation phantom includes a real dynamic simulation phantom and / or a fully digital dynamic simulation phantom. This allows for the verification of the effectiveness and safety of the adaptive radiotherapy plan.

[0165] According to embodiments of the present disclosure, the present disclosure also provides an electronic device, including at least one processor; and a memory communicatively connected to the at least one processor; wherein the memory stores instructions executable by the at least one processor, the instructions being executed by the at least one processor to enable the at least one processor to perform the adaptive radiotherapy planning optimization method or the adaptive radiotherapy dose compensation method provided in the present disclosure.

[0166] According to embodiments of the present disclosure, the present disclosure also provides a non-transitory computer-readable storage medium storing computer instructions, wherein the computer instructions are used to cause an electronic device to execute the adaptive radiotherapy planning optimization method or the adaptive radiotherapy dose compensation method provided in the present disclosure.

[0167] According to embodiments of this disclosure, this disclosure also provides a computer program product, including a computer program that, when executed by a processor, implements the adaptive radiotherapy planning optimization method or the adaptive radiotherapy dose compensation method provided in this disclosure.

[0168] In some embodiments, the electronic device may be the radiotherapy planning device shown in FIG1 above. FIG4 shows a schematic block diagram of an example electronic device 400 that can be used to implement embodiments of the present disclosure. Electronic device 400 is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. Electronic device 400 may also represent various forms of mobile devices, such as personal digital processors, cellular phones, smartphones, wearable devices, and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely examples and are not intended to limit the implementation of the present disclosure described and / or claimed herein.

[0169] As shown in Figure 4, the electronic device 400 includes a computing unit 401, which can perform various appropriate actions and processes based on a computer program stored in a read-only memory (ROM) 402 or a computer program loaded from a storage unit 408 into a random access memory (RAM) 403. The RAM 403 can also store various programs and data required for the operation of the electronic device 400. The computing unit 401, ROM 402, and RAM 403 are interconnected via a bus 404. An input / output (I / O) interface 405 is also connected to the bus 404.

[0170] Multiple components in electronic device 400 are connected to I / O interface 405, including: input unit 406, such as keyboard, mouse, etc.; output unit 407, such as various types of displays, speakers, etc.; storage unit 408, such as disk, optical disk, etc.; and communication unit 409, such as network card, modem, wireless transceiver, etc. Communication unit 409 allows electronic device 400 to exchange information / data with other devices through computer networks such as the Internet and / or various telecommunications networks.

[0171] The computing unit 401 can be various general-purpose and / or special-purpose processing components with processing and computing capabilities. Some examples of the computing unit 401 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various special-purpose artificial intelligence (AI) computing chips, various computing units running machine learning model algorithms, digital signal processors (DSPs), and any suitable processor, controller, microcontroller, etc. The computing unit 401 performs the various methods and processes described above, such as adaptive radiotherapy planning optimization methods or adaptive radiotherapy dose compensation methods. For example, in some embodiments, the adaptive radiotherapy planning optimization method or the adaptive radiotherapy dose compensation method can be implemented as a computer software program, which is tangibly contained in a machine-readable medium, such as storage unit 408. In some embodiments, part or all of the computer program can be loaded and / or installed on the electronic device 400 via ROM 402 and / or communication unit 409. When the computer program is loaded into RAM 403 and executed by computing unit 401, one or more steps of the adaptive radiotherapy planning optimization method or the adaptive radiotherapy dose compensation method described above can be performed. Alternatively, in other embodiments, computing unit 401 can be configured to perform the adaptive radiotherapy planning optimization method or the adaptive radiotherapy dose compensation method by any other suitable means (e.g., by means of firmware).

[0172] Various embodiments of the systems and techniques described above herein can be implemented in digital electronic circuit systems, integrated circuit systems, field programmable gate arrays (FPGAs), application-specific integrated circuits (ASICs), application-specific standard parts (ASSPs), systems-on-chip (SoCs), complex programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various embodiments may include implementations in one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, which may be a dedicated or general-purpose programmable processor, capable of receiving data and instructions from a storage system, at least one input device, and at least one output device, and transmitting data and instructions to the storage system, the at least one input device, and the at least one output device.

[0173] The program code used to implement the methods of this disclosure may be written in any combination of one or more programming languages. This program code may be provided to a processor or controller of a general-purpose computer, special-purpose computer, or other programmable data processing apparatus, such that when executed by the processor or controller, the program code causes the functions / operations specified in the flowcharts and / or block diagrams to be implemented. The program code may be executed entirely on a machine, partially on a machine, as a standalone software package partially on a machine and partially on a remote machine, or entirely on a remote machine or server.

[0174] In the context of this disclosure, a machine-readable medium can be a tangible medium that may contain or store a program for use by or in conjunction with an instruction execution system, apparatus, or device. A machine-readable medium can be a machine-readable signal medium or a machine-readable storage medium. A machine-readable medium can be, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, apparatus, or devices, or any suitable combination of the foregoing. More specific examples of machine-readable storage media include electrical connections based on one or more wires, portable computer disks, hard disks, random access memory, read-only memory, erasable programmable read-only memory (EPROM or flash memory), optical fibers, compact disc read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination of the foregoing.

[0175] To provide interaction with a user, the systems and techniques described herein can be implemented on a computer having: a display device for displaying information to the user, such as a cathode ray tube (CRT) or liquid crystal display (LCD) monitor; and a keyboard and pointing device (e.g., a mouse or trackball) through which the user provides input to the computer. Other types of devices can also be used to provide interaction with the user; for example, feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form (including sound input, voice input, or tactile input).

[0176] The systems and technologies described herein can be implemented in computing systems that include backend components (e.g., as a data server), or computing systems that include middleware components (e.g., an application server), or computing systems that include frontend components (e.g., a user computer with a graphical user interface or web browser through which a user can interact with implementations of the systems and technologies described herein), or any combination of such backend, middleware, or frontend components. The components of the system can be interconnected via digital data communication of any form or medium (e.g., a communication network). Examples of communication networks include local area networks (LANs), wide area networks (WANs), and the Internet.

[0177] Computer systems can include clients and servers. Clients and servers are generally located far apart and typically interact via communication networks. Client-server relationships are created by computer programs running on the respective computers and having a client-server relationship with each other. Servers can be cloud servers, servers in distributed systems, or servers incorporating blockchain technology.

[0178] It should be understood that the various forms of processes shown above can be used to rearrange, add, or delete steps. For example, the steps described in this disclosure can be executed in parallel, sequentially, or in different orders, as long as the desired result of the technical solution of this disclosure can be achieved, and this is not limited herein.

[0179] The specific embodiments described above do not constitute a limitation on the scope of protection of this disclosure. Those skilled in the art should understand that various modifications, combinations, sub-combinations, and substitutions can be made according to design requirements and other factors. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of this disclosure should be included within the scope of protection of this disclosure.

Claims

1. An adaptive radiotherapy planning optimization method, characterized in that, include: Obtain a radiotherapy plan for I fractions of radiotherapy targeting the target area of ​​the patient to be radiotreated, where I is an integer greater than 1; Before the start of the i-th fraction of radiotherapy, a shape and position image of the subject to be radiotherapy is acquired, and the radiotherapy plan for the subject to be radiotherapy is optimized based on the shape and position image; wherein, the shape and position image is used to indicate the shape and / or position of the target area of ​​the subject to be radiotherapy, and the i-th fraction of radiotherapy is the i-th fraction of the I fractions of radiotherapy, where i is 1, 2, 3, ..., I; Within the i-th fraction of radiotherapy, during the continuous beam exit segment, a shape and position image of the subject to be radiotherapy is acquired, and the radiotherapy plan for the subject to be radiotherapy is optimized based on the shape and position image; and / or, during the non-exit segment before the continuous beam exit segment, a shape and position image of the subject to be radiotherapy is acquired, and the radiotherapy plan for the subject to be radiotherapy is optimized based on the shape and position image.

2. The method according to claim 1, characterized in that, Within the i-th fraction of radiotherapy, the step of acquiring a shape and position image of the subject to be radiotherapy within the continuous beam exit segment, and optimizing the radiotherapy plan for the subject based on the shape and position image, includes: At time j within the continuous beam emission segment of the i-th fractional radiotherapy, or after time j and before time j+1, a positional image of the subject to be radiotherapy is acquired. Based on the positional image of the subject to be radiotherapy, the optimized radiotherapy plan for the subject to be radiotherapy is further optimized, so that the subject to be radiotherapy is irradiated at time j+1 within the continuous beam emission segment based on the optimized radiotherapy plan. Wherein, time j is the j-th time among J times within the continuous beam emission segment of the i-th fractional radiotherapy, where j is 1, 2, ..., J, and J is an integer greater than 1.

3. The method according to claim 2, characterized in that, The interval between J moments within the continuous beam emission segment of the i-th fractional radiotherapy is determined based on the respiratory cycle or respiratory rate of the patient to be radiotreated.

4. The method according to claim 2, characterized in that, At time j within the sustained beam egress segment of the i-th fraction of radiotherapy, or after time j and before time j+1, the optimization of the radiotherapy plan for the target patient based on the geopotential image includes: At time j, or after time j and before time j+1, within the continuous beam-out segment of the i-th fraction of radiotherapy, the shape and position image of the object to be radiotreated is predicted at time j+1 based on the shape and position image of the object to be radiotreated acquired between time j and time j+1. The radiotherapy plan for the radiotherapy subject is optimized based on the geoid image of the subject at time j+1.

5. The method according to claim 1, characterized in that, Within the i-th fraction of radiotherapy, during the non-emergence segment before sustained beam emission, a shape and position image of the patient to be radiotherapy is acquired, and the radiotherapy plan for the patient is optimized based on the shape and position image, including: In the non-emerging segment of the radiation beam before the kth continuous beam exit segment within the i-th fractional radiotherapy, a shape and position image of the target object is obtained; based on the shape and position image of the target object, the optimized radiotherapy plan for the target object is optimized, so that the target object is irradiated within the kth continuous beam exit segment based on the optimized radiotherapy plan for the target object; wherein, the kth continuous beam exit segment is the kth continuous beam exit segment among the K continuous beam exit segments within the i-th fractional radiotherapy, where k is 1, 2, ..., K, and K is an integer greater than or equal to 1.

6. The method according to claim 1, characterized in that, Before the start of the i-th fraction of radiotherapy, and / or, within the sustained beam exit segment of the i-th fraction of radiotherapy, and / or, within the non-exit segment of the radiation beam before the sustained beam exit segment of the i-th fraction of radiotherapy, the radiotherapy plan for the subject to be radiotherapy is optimized based on the positional image, including: Based on the morphology and / or location of the target area in the geometry image of the patient to be radiotherapy, a search is performed in the preset treatment plan library. A set of control point parameters corresponding to the shape and / or location of the target area, wherein the set of control point parameters is a set of control point parameters to be optimized in the radiotherapy plan of the subject to be radiotherapy; If a set of control point parameters corresponding to the shape and / or location of the target area is found from the preset plan library, the radiotherapy plan for the subject to be radiotherapy is optimized based on the set of control point parameters.

7. The method according to claim 6, characterized in that, Also includes: If it is determined that no set of control point parameters corresponding to the shape and / or position of the target area can be found from the preset plan library, the shape and position changes of the target area of ​​the subject to be radiotherapy are determined based on the shape and position image, and the optimized radiotherapy plan of the subject to be radiotherapy is optimized based on the shape and position changes of the target area; wherein, the shape and position changes of the target area include the positional changes and / or shape changes of the target area caused by the periodic movement and / or non-periodic movement of the subject to be radiotherapy.

8. The method according to claim 6, characterized in that, Within the continuous beam emission segment of the radiation beam in the i-th fractional radiotherapy, the j-th moment is defined as either the moment after the j-th moment and the moment before the (j+1)-th moment within the continuous beam emission segment of the radiation beam in the i-th fractional radiotherapy; wherein, the j-th moment is the j-th moment among the J moments within the continuous beam emission segment of the radiation beam in the i-th fractional radiotherapy, where j is 1, 2, ..., J, and J is an integer greater than 1; The non-exit segment of the radiation beam before the continuous beam exit segment in the i-th fraction of radiotherapy is the segment before the continuous beam exit segment of the k-th radiation beam in the i-th fraction of radiotherapy; wherein, the continuous beam exit segment of the k-th radiation beam is the continuous beam exit segment of the k radiation beam exit segments in the i-th fraction of radiotherapy, where k is 1, 2, ..., K, and K is an integer greater than or equal to 1.

9. The method according to claim 8, characterized in that, At time j within the continuous beam-out segment of the k-th radiation beam in the i-th fraction of radiotherapy, or after time j and before time j+1, based on the morphology and / or position of the target area in the geopotential image of the subject to be radiotherapy, a set of control point parameters corresponding to the morphology and / or position of the target area is searched in a preset planning library, including: At time j within the continuous beam-out segment of the k-th radiation beam in the i-th fraction of radiotherapy, or after time j and before time j+1, the shape and / or position of the target area in the geopotential image of the subject to be radiotherapy is predicted at time j+1. Search the preset plan library for a set of control point parameters corresponding to the shape and / or position of the target area at time j+1.

10. The method according to claim 6, characterized in that, In the adaptive radiotherapy planning optimization method, both the radiotherapy plan for the patient to be radiotreated and the optimized radiotherapy plan are stored in a preset plan library.

11. The method according to claim 1, characterized in that, Also includes: Within the i-th fraction of radiotherapy, after the k-th continuous beam emission segment and before the (k+1)-th continuous beam emission segment, the cumulative dose deviation of the target area under-radiation within the k-th continuous beam emission segment of the subject to be radiotherapy is determined; wherein, the k-th continuous beam emission segment is the k-th continuous beam emission segment among the K continuous beam emission segments within the i-th fraction of radiotherapy, where k is 1, 2, 3, K, and K is an integer greater than or equal to 1; The cumulative deviation of the k-th dose is compensated within the continuous beam exit segment of the k+1-th radiation beam, and / or the cumulative deviation of the k-th dose is compensated within the i+1-th fraction of radiotherapy.

12. The method according to claim 1, characterized in that, Also includes: Between time j and time j+1 within the k-th radiation beam continuous output segment of the i-th fractional radiotherapy, the cumulative dose deviation of the under-radiation of the target area at time j is determined; wherein, time j is the j-th time among the J times of the radiation beam continuous output segment within the i-th fractional radiotherapy, where j is 1, 2, ..., J, and J is an integer greater than 1; The cumulative dose deviation of the j-th dose is compensated at the (j+1)-th time within the continuous beam-out segment of the k-th radiation beam, and / or, the cumulative dose deviation of the j-th dose is compensated at the (j+1)-th time. The cumulative dose deviation of the j-th dose is compensated within the continuous beam exit segment of the k+1-th radiation beam, and / or the cumulative dose deviation of the j-th dose is compensated within the i+1-th fraction of radiotherapy.

13. The method according to claim 1, characterized in that, Also includes: Between the i-th fraction of radiotherapy and the (i+1)-th fraction of radiotherapy, determine the i-th cumulative dose deviation of the under-radiation of the target area within the i-th fraction of radiotherapy; The cumulative deviation of the i-th dose is compensated within the (i+1)-th fraction of radiotherapy.

14. The method according to any one of claims 11 to 13, characterized in that, The determination of the cumulative dose deviation of the under-radiation in the target area includes: Obtain the actual dose received by the target area; Based on the actual dose received by the target area and the standard dose, the cumulative dose deviation of the under-radiation in the target area is determined.

15. The method according to claim 14, characterized in that, The actual dose received by the target area is obtained based on EPD and / or radiotherapy records.

16. The method according to claim 1, characterized in that, Also includes: The optimized adaptive radiotherapy plan is validated based on the simulation phantom, which includes a real dynamic simulation phantom and / or a fully digital dynamic simulation phantom.

17. An electronic device, characterized in that, include: At least one processor; as well as A memory communicatively connected to the at least one processor; wherein, The memory stores instructions that can be executed by the at least one processor to enable the at least one processor to perform the method of any one of claims 1 to 16.

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