Method and system for generating adaptive radiotherapy plan

Abstract

The embodiment of the invention provides a method and a system for generating a self-adaptive radiotherapy plan. The method for generating the self-adaptive radiotherapy plan comprises the following steps: acquiring a first image related to one or more target objects; acquiring a first radiotherapy plan for treating one or more target objects; acquiring a second image related to one or more target objects; determining one or more regions of interest in the second image, and dividing the one or more determined regions of interest into at least two groups; generating a first intermediate plan by updating the first radiotherapy plan based on the one or more determined regions of interest; updating the first intermediate plan by performing at least two iterations; and determining an intermediate plan generated in the last iteration of the at least two iterations as a target radiotherapy plan for treating one or more target objects.

Description

Description of the case

[0001] This application is a divisional application filed for a Chinese application with a filing date of March 16, 2020, application number 202080098525.7, and invention name “System and method for generating adaptive radiation therapy plans”. Technical Field

[0002] The present description relates generally to systems and methods for radiation therapy and, more particularly, to a system and method for generating an adaptive radiation therapy plan. Background Art

[0003] Radiation therapy is widely used in cancer treatment and is also used for several other health conditions. Typically, a radiation therapy plan (also referred to as a treatment plan) is generated for a cancer patient before treatment begins. According to the radiation therapy plan, radiation can be delivered to the patient in several treatment phases, which can be distributed over a multi-day treatment period. However, during treatment, the anatomical structure of a tumor or other tissue (e.g., tissue surrounding a tumor) may change. For example, a tumor can grow, deform, or shrink. If the original treatment plan is used after a change in the target structure (e.g., shrinkage), there is a high risk of affecting healthy tissue by applying a high radiation dose to such tissue. This problem can be avoided or mitigated in adaptive radiation therapy. According to this method, an image of a target structure is acquired during the course of radiation therapy (e.g., between certain treatment phases) to identify changes in the contour of the target structure. Then, a replanning procedure is performed to adapt the treatment plan to the contour of the target structure change. When radiation is delivered to the patient in a timely manner, the repopulation of tumor cells can be effectively avoided, achieving the best efficacy of the treatment. Therefore, the replanning procedure needs to be performed quickly, otherwise, it may cause a delay in the implementation of radiation therapy, thereby affecting the results of radiation therapy. Therefore, it is desirable to provide a system and method for quickly generating an adaptive radiation therapy plan. Summary of the invention

[0004] According to a first aspect of the present specification, a system for generating an adaptive radiation therapy plan may include one or more storage devices and one or more processors configured to communicate with the one or more storage devices. The one or more storage devices may include a set of instructions. When the one or more processors execute the set of instructions, the one or more processors may be directed to perform the following operations. The one or more processors may acquire a first image related to one or more target objects, the first image being generated by a first scan; acquire a first radiation therapy plan for treating the one or more target objects, the first radiation therapy plan being associated with the first image; acquire a second image related to the one or more target objects, the second image being generated by a second scan, the second scan being performed later than the first scan; determine one or more regions of interest in the second image, and divide the one or more determined regions of interest into at least two groups; generate a first intermediate plan by updating the first radiation therapy plan based on the one or more determined regions of interest; update the first intermediate plan by performing at least two iterations; and determine the intermediate plan generated in the last iteration of the at least two iterations as a target radiation therapy plan for treating the one or more target objects.

[0005] In some embodiments, in order to update the first intermediate plan, the one or more processors may receive a second instruction for modifying or accepting the tth group of regions of interest, wherein the tth group of regions of interest includes at least one of the one or more determined regions of interest; based on the second instruction, processing the tth group of regions of interest; and generating a (t+1)th intermediate plan based on the tth intermediate plan and the processed tth group of regions of interest.

[0006] In some embodiments, in order to determine one or more regions of interest in the second image, the one or more processors may perform automatic determination of one or more regions of interest in the second image based on an estimate of the time length used to determine each of the one or more regions of interest, the automatic determination comprising: estimating the time length used to determine each of the one or more regions of interest; sorting the time lengths; and automatically determining the one or more regions of interest based on the sorting result.

[0007] In some embodiments, in order to determine one or more regions of interest in the second image, the one or more processors may automatically determine one or more first regions of interest among the one or more regions of interest in the second image; receive a first instruction, the first instruction being used to modify or accept the one or more automatically determined first regions of interest; process at least one of the one or more first regions of interest based on the first instruction; and automatically determine one or more second regions of interest among the one or more regions of interest in the second image; wherein the operation of automatically determining the one or more second regions of interest among the one or more regions of interest in the second image is performed in parallel with at least one of the operations of receiving the first instruction for modifying or accepting the one or more automatically determined first regions of interest and processing the one or more first regions of interest according to the first instruction.

[0008] In some embodiments, in order to divide the one or more determined regions of interest into at least two groups, the one or more processors may estimate the workload of manually modifying each of the one or more automatically determined regions of interest; based on the workload of manually modifying the one or more regions of interest, divide the one or more regions of interest into at least two groups; and based on the grouping results, generate instructions prompting the user to modify the one or more regions of interest.

[0009] In some embodiments, in order to generate a first intermediate plan, the one or more processors may determine a second dose distribution in the second image based on the one or more determined regions of interest, and generate the first intermediate plan by updating the first radiotherapy plan based on the second dose distribution and one or more preset conditions.

[0010] In some embodiments, the second dose distribution comprises a dose volume histogram associated with the second image, the dose volume histogram being determined based on the first dose distribution and / or the first radiation treatment.

[0011] In some embodiments, receiving a second instruction for modifying or accepting the tth group of regions of interest, processing the tth group of regions of interest based on the second instruction, and generating the (t+1)th intermediate plan based on the tth intermediate plan and the processed tth group of regions of interest are performed in parallel.

[0012] In some embodiments, the operation of generating the first intermediate plan by updating the first radiotherapy plan based on the one or more determined regions of interest is performed in parallel with at least one of the operations of receiving an instruction for modifying or accepting the first group of regions of interest and processing the first group of regions of interest based on the instruction for modifying or accepting the first group of regions of interest; or the operation of generating the (t+1)th intermediate plan based on the tth intermediate plan and the processed tth group of regions of interest is performed in parallel with at least one of the operations of receiving an instruction for modifying or accepting the (t+1)th group of regions of interest and processing the (t+1)th group of regions of interest based on the instruction for modifying or accepting the (t+1)th group of regions of interest.

[0013] According to another aspect of the present specification, a method for generating an adaptive radiotherapy plan may include: acquiring a first image related to one or more target objects, the first image being generated by a first scan; acquiring a first radiotherapy plan for treating the one or more target objects, the first radiotherapy plan being associated with the first image; acquiring a second image related to the one or more target objects, the second image being generated by a second scan, the second scan being performed later than the first scan; determining one or more regions of interest in the second image, and dividing the one or more determined regions of interest into at least two groups; generating a first intermediate plan by updating the first radiotherapy plan based on the one or more determined regions of interest; updating the first intermediate plan by performing at least two iterations; and determining the intermediate plan generated in the last iteration of the at least two iterations as the target radiotherapy plan for treating the one or more target objects.

[0014] According to another aspect of the present specification, a system for generating an adaptive radiation therapy plan may include an acquisition module and a plan determination module. The acquisition module is configured to acquire a first image related to one or more target objects, the first image being generated by a first scan; acquire a first radiation therapy plan for treating the one or more target objects, the first radiation therapy plan being associated with the first image; acquire a second image related to the one or more target objects, the second image being generated by a second scan, the second scan being performed later than the first scan. The plan determination module is configured to determine one or more regions of interest in the second image, and divide the one or more determined regions of interest into at least two groups; generate a first intermediate plan by updating the first radiation therapy plan based on the one or more determined regions of interest; update the first intermediate plan by performing at least two iterations; and determine the intermediate plan generated in the last iteration of the at least two iterations as a target radiation therapy plan for treating the one or more target objects.

[0015] According to another aspect of the present specification, a non-transitory computer-readable medium may include at least one set of instructions. The at least one set of instructions may be executed by one or more processors of a computing device. The one or more processors may acquire a first image associated with one or more target objects, the first image being generated by a first scan; acquire a first radiotherapy plan for treating the one or more target objects, the first radiotherapy plan being associated with the first image; acquire a second image associated with the one or more target objects, the second image being generated by a second scan, the second scan being performed later than the first scan; determine one or more regions of interest in the second image, and divide the one or more determined regions of interest into at least two groups; generate a first intermediate plan by updating the first radiotherapy plan based on the one or more determined regions of interest; update the first intermediate plan by performing at least two iterations; and determine the intermediate plan generated in the last iteration of the at least two iterations as a target radiotherapy plan for treating the one or more target objects. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] This specification will be further described by exemplary embodiments. These exemplary embodiments will be described in detail by the accompanying drawings. These embodiments are non-limiting exemplary embodiments, in which the same numbers in each figure represent similar structures, wherein:

[0017] Figure 1 is a schematic diagram of an exemplary radiation therapy system according to some embodiments of the present specification;

[0018] Figure 2 is a schematic diagram of hardware and / or software components of an exemplary computing device according to some embodiments of the present specification;

[0019] Figure 3 is a schematic diagram of hardware and / or software components of an exemplary mobile device according to some embodiments of the present specification;

[0020] Figure 4 is a block diagram of an exemplary processing device according to some embodiments of the present specification;

[0021] Figure 5 is a flowchart of an exemplary process for determining a target radiation therapy plan according to some embodiments of the present specification;

[0022] Figure 6 is a flowchart of an exemplary process for determining a target radiation therapy plan according to some embodiments of the present specification; and

[0023] Figure 7 is a flow chart of an exemplary process for determining a target radiation therapy plan according to some embodiments of the present specification. DETAILED DESCRIPTION

[0024] In order to more clearly illustrate the technical solutions of the embodiments of this specification, the drawings required for use in the description of the embodiments will be briefly introduced below. However, it should be understood by those skilled in the art that this specification can be implemented without these details. In other cases, in order to avoid unnecessarily obscuring various aspects of this specification, well-known methods, processes, systems, components and / or circuits have been described at a higher level. For those of ordinary skill in the art, it is obvious that various changes can be made to the disclosed embodiments, and the general principles defined in this specification can be applied to other embodiments and application scenarios without departing from the principles and scope of this specification. Therefore, this specification is not limited to the embodiments shown, but conforms to the broadest scope consistent with the patent scope of the specification.

[0025] The terms used in this specification are for the purpose of describing specific example embodiments only and are not restrictive. The singular forms "a", "an" and "the" as used in this specification may also include plural forms unless the context clearly indicates an exception. It should also be understood that the terms "including" and "comprising" as used in this specification only indicate the presence of the features, integers, steps, operations, components and / or parts, but do not exclude the presence or addition of one or more other features, integers, steps, operations, components, parts and / or combinations thereof.

[0026] It should be understood that the terms "system", "module" and / or "block" used herein are methods for distinguishing different components, elements, parts, portions or assemblies at different levels in ascending order. However, these terms may also be replaced by other expressions if the same purpose can be achieved.

[0027] Generally, the word "module" or "block" as used herein refers to logic present in hardware or firmware, or a collection of software instructions. The modules or blocks described herein may be implemented as software and / or hardware, and may be stored in any type of non-transitory computer-readable medium or other storage device. In some embodiments, software modules / units / blocks may be compiled and linked into an executable program. It should be understood that software modules may be called from other modules / units / blocks or from themselves, and / or may be called in response to detected events or interrupts. A module configured to be executed on a computing device (e.g., a processor) Figure 2 The software modules / units / blocks executed on the processor 210 shown in the figure) can be provided on a computer-readable medium, such as a compact disc, a digital video disc, a flash drive, a disk, or any other tangible medium, or as a digital download (and can be initially stored in a compressed or installable format, which needs to be installed, decompressed or decrypted before execution). The software code here can be stored in part or in whole in the storage device of the computing device performing the operation and applied in the operation of the computing device. The software instructions can be embedded in firmware, such as an electronic programmable read-only memory (EPROM). It should also be understood that the hardware modules / units / blocks can be included in connected logical components, such as gates and triggers, and / or can include programmable units, such as programmable gate arrays or processors. The modules / units / blocks or computing device functions described here can be implemented as software modules / units / blocks, but can be represented by hardware or firmware. Generally, the modules / units / blocks described here refer to logical modules / units / blocks, which can be combined with other modules / units / blocks or divided into sub-modules / sub-units / sub-blocks, although they are physical organizations or storage devices. This description can be applied to the system, engine or part thereof.

[0028] It is understood that, unless the context clearly indicates otherwise, when a module or block is referred to as being "connected to" or "coupled to" another module or block, it may be directly connected to or coupled to another module or block, or communicate with another module or block, or there may be intermediate units, engines, modules or blocks. In this specification, the term "and / or" may include any one or more of the relevant listed items or combinations thereof.

[0029] These and other features, characteristics and functions of the related structural elements and methods of operation, as well as the combination of parts and manufacturing economy of the present specification may become more apparent from the following description of the accompanying drawings, which form a part of this specification. However, it should be understood that the drawings are for illustration and description purposes only and are not intended to limit the scope of the present specification. It should be understood that the drawings are not drawn to scale.

[0030] Provided herein are systems and components for medical imaging and / or medical treatment. In some embodiments, a medical system may include an imaging system. An imaging system may include a single-modality imaging system and / or a multi-modality imaging system. A single-modality imaging system may include, for example, a magnetic resonance imaging (MRI) system, an X-ray system, a computed tomography (CT) system, a positron emission computed tomography (PET) system, an ultrasound system, etc., or any combination thereof. A multi-modality imaging system may include, for example, a computed tomography magnetic resonance imaging (CT-MRI) system, a positron emission tomography magnetic resonance imaging (PET-MRI) system, a single photon emission computed tomography magnetic resonance imaging (SPECT-MRI) system, a digital subtraction angiography magnetic resonance imaging (DSA-MRI) system, a positron emission tomography computed tomography (PET-CT), etc. In some embodiments, a medical system may include a treatment system. A treatment system may include a treatment planning system (TPS), image-guided radiation therapy (IGRT), etc. Image-guided radiation therapy (IGRT) may include a treatment device and an imaging device. Treatment equipment may include linear accelerators, cyclotrons, synchrotrons, etc., configured to perform radiation therapy on a subject. Treatment equipment may include accelerators of particles such as photons, electrons, protons, or heavy ion species. Imaging equipment may include MRI scanners, CT scanners (e.g., cone beam computed tomography (CBCT) scanners), digital radiology (DR) scanners, electronic portal imaging devices (EPIDs), etc.

[0031] For the sake of brevity, an image or a portion thereof (e.g., an ROI in an image) corresponding to an object (e.g., a tissue, an organ, a tumor, etc. of an object (e.g., a patient, etc.) may be referred to as an image, or a portion thereof (e.g., an ROI) or including an object, or the object itself. For example, an ROI corresponding to an image of a tumor may be described as the ROI including the tumor. As another example, an image of the liver or an image including the liver may be referred to as an image of the liver, or simply as the liver. For the sake of brevity, a portion of an image corresponding to an object being processed (e.g., extracted, segmented, etc.) may be described as the object being processed. For example, extracting a portion of an image corresponding to a tumor from the rest of the image may be described as the tumor being extracted.

[0032] The present invention provides a system and method for generating an adaptive radiation therapy plan during radiation therapy / treatment. When performing a replanning process in adaptive radiation therapy, the system and / or method can perform at least two operations in the replanning process in parallel, thereby improving the efficiency of generating an adaptive radiation therapy plan.

[0033] Figure 1 FIG. 1 is a schematic diagram of an exemplary radiation therapy system 100 according to some embodiments of the present specification. Figure 1 As shown, the radiation therapy system 100 may include a radiation device 110 , a network 120 , one or more terminals 130 , a processing device 140 , and a storage device 150 .

[0034] Radiation therapy is treatment that uses ionizing radiation, usually as part of cancer treatment to control or kill malignant cells. Radiation therapy can be delivered by a linear accelerator (e.g. Figure 1 The radiation therapy may be delivered by a radiation device 110 in the radiation therapy system 100. Radiation therapy may include external radiation therapy, brachytherapy, intraoperative radiation therapy, radioisotope therapy, deep inspiration breath hold (DIBH), etc. External beam radiation therapy may include conventional external beam radiation therapy (2DXRT), stereotactic radiation therapy (e.g., stereotactic radiosurgery, stereotactic body radiation therapy, etc.), virtual simulation and three-dimensional conformal radiation therapy (3DCRT), intensity modulated radiation therapy (IMRT), volumetric modulated arc therapy (VMAT), particle therapy, auger therapy (AT), etc.

[0035] The radiation device 110 can emit radiation to a subject (e.g., a patient) for treatment to control or kill malignant cells. The radiation can include alpha rays, beta rays, gamma rays, X-rays, neutrons, etc. The radiation device 110 can include a medical linear accelerator, a Cobalt-60 device, a gamma knife, an X-knife, a proton accelerator, a brachytherapy device, etc., or any combination thereof. In some embodiments, prior to treatment (or a portion of treatment), an imaging scan can be performed to identify a tumor and surrounding normal structures of the subject. Therefore, the radiation therapy system 100 can also include an imaging device ( Figure 1 (not shown), such as X-ray equipment, computed tomography (CT) equipment, positron emission tomography (PET) equipment, magnetic resonance imaging (MRI) equipment, etc., or any combination thereof.

[0036] In this specification, "subject" and "object" may be used interchangeably. For example, an object may include a patient, a man-made object, etc. As another example, an object may include a specific part, organ, and / or tissue of a patient. For example, an object may include a head, brain, neck, body, shoulder, arm, chest, heart, stomach, blood vessel, soft tissue, knee joint, foot, etc., or any combination thereof.

[0037] For convenience, the description of the method and / or system for generating an adaptive radiation therapy plan in this specification is provided in conjunction with radiation therapy / treatment. It should be noted that the description of the method and / or system for generating an adaptive radiation therapy plan for radiation therapy is provided for illustrative purposes only and is not intended to limit the scope of this specification. For those of ordinary skill in the art, various changes and modifications can be made based on the description of this specification. However, these changes and modifications do not depart from the scope of this specification.

[0038] The network 120 may include any suitable network that may facilitate information and / or data exchange of the radiation therapy system 100. In some embodiments, one or more components of the radiation therapy system 100 (e.g., the radiation device 110, the terminal 130, the processing device 140, the storage device 150, etc.) may communicate information and / or data with one or more other components of the radiation therapy system 100 via the network 120. For example, the processing device 140 may obtain information related to a radiation therapy plan or image from the radiation device 110 via the network 120. As another example, the processing device 140 may obtain a user instruction from the terminal 130 via the network 120. The network 120 may be or include a public network (e.g., the Internet), a private network (e.g., a local area network (LAN)), a wired network, a wireless network (e.g., an 802.11 network, a Wi-Fi network), a frame relay network, a virtual private network (VPN), a satellite network, a telephone network, a router, a hub, a switch, a server computer, and / or any combination thereof. Merely by way of example, the network 120 may include a cable network, a wired network, a fiber optic network, a telecommunication network, an intranet, a wireless local area network (WLAN), a metropolitan area network (MAN), a public switched telephone network (PSTN), a Bluetooth TM Network, ZigBee TM Network, near field communication (NFC), etc., or any combination thereof. In some embodiments, the network 120 may include one or more network access points. For example, the network 120 may include a wired and / or wireless network access point, such as a base station and / or an Internet exchange point, and one or more components of the radiation therapy system 100 may be connected to the network 120 to exchange data and / or information.

[0039] The terminal 130 may include a mobile device 131, a tablet computer 132, a laptop computer 133, etc., or any combination thereof. In some embodiments, the mobile device 131 may include a smart home device, a wearable device, a mobile device, a virtual reality device, an augmented reality device, etc., or any combination thereof. In some embodiments, the smart home device may include a smart lighting device, a smart appliance control device, a smart monitoring device, a smart TV, a smart camera, an intercom, etc., or any combination thereof. In some embodiments, the wearable device may include a bracelet, footwear, glasses, a helmet, a watch, clothes, a backpack, a smart accessory, etc., or any combination thereof. In some embodiments, the mobile device may include a mobile phone, a personal digital assistant (PDA), a gaming device, a navigation device, a point of sale (POS) device, a laptop computer, a tablet computer, a desktop computer, etc., or any combination thereof. In some embodiments, the virtual reality device and / or the augmented reality device may include a virtual reality helmet, virtual reality glasses, virtual reality goggles, an augmented reality helmet, augmented reality glasses, augmented reality goggles, etc., or any combination thereof. For example, the virtual reality device and / or the augmented reality device may include Google Glass. TM 、OculusRiftTM、Hololens TM 、GearVR TM Etc. In some embodiments, the terminal 130 may be a part of the processing device 140 .

[0040] The processing device 140 can process data and / or information obtained from the radiation device 110, the terminal 130 and / or the storage device 150. For example, the processing device 140 can generate and update the radiation treatment plan. In some embodiments, the processing device 140 can be a single server or a server group. The server group can be centralized or distributed. In some embodiments, the processing device 140 can be local or remote. For example, the processing device 140 can access information and / or data stored in the radiation device 110, the terminal 130 and / or the storage device 150 through the network 120. As another example, the processing device 140 can be directly connected to the radiation device 110, the terminal 130 and / or the storage device 150. In some embodiments, the processing device 140 can be implemented on a cloud platform. By way of example only, the cloud platform may include a private cloud, a public cloud, a hybrid cloud, a community cloud, a distributed cloud, an internal cloud, a multi-layer cloud, the like, or any combination thereof. In some embodiments, the processing device 140 can be implemented by a computing device 200 having one or more components, such as Figure 2 shown.

[0041] The storage device 150 may store data, instructions, and / or any other information. In some embodiments, the storage device 150 may store data obtained from the radiation device 110, the terminal 130, and / or the processing device 140. In some embodiments, the storage device 150 may store data and / or instructions that the processing device 140 may execute or use to execute the exemplary method described in this specification. In some embodiments, the storage device 150 may include a mass storage device, a removable storage device, a volatile read-write memory, a read-only memory (ROM), etc., or any combination thereof. Exemplary mass storage devices may include magnetic disks, optical disks, solid-state drives, etc. Exemplary removable storage devices may include flash drives, floppy disks, optical disks, memory cards, compressed disks, tapes, etc. Exemplary volatile read-write memory may include random access memory (RAM). Exemplary RAM may include dynamic random access memory (DRAM), double data rate synchronous dynamic random access memory (DDRSDRAM), static random access memory (SRAM), thyristor random access memory (T-RAM), and zero capacitance random access memory (Z-RAM), etc. Exemplary ROMs may include mask ROM (MROM), programmable ROM (PROM), erasable programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM), compact disk ROM (CD-ROM), and digital versatile disk ROM, etc. In some embodiments, the storage device 150 may be implemented on a cloud platform. By way of example only, the cloud platform may include a private cloud, a public cloud, a hybrid cloud, a community cloud, a distributed cloud, an internal cloud, a multi-layer cloud, etc., or any combination thereof.

[0042] In some embodiments, the storage device 150 may be connected to the network 120 to communicate with one or more other components (e.g., the processing device 140, the terminal 130, etc.) in the radiation therapy system 100. One or more components in the radiation therapy system 100 may access data or instructions stored in the storage device 150 through the network 120. In some embodiments, the storage device 150 may be directly connected to one or more other components (e.g., the processing device 140, the terminal 130, etc.) in the radiation therapy system 100. In some embodiments, the storage device 150 may be part of the processing device 140. In some embodiments, the processing device 140 may be connected to or communicate with the radiation device 110 through the network 120 or at the back end of the processing device 140.

[0043] Figure 2 is a diagram of exemplary hardware and / or software components of an exemplary computing device 200 on which the processing device 140 may be implemented according to some embodiments of the present specification. Figure 2As shown, computing device 200 may include processor 210 , memory 220 , input / output (I / O) 230 , and communication port 240 .

[0044] The processor 210 can execute computer instructions (e.g., program code) and perform the functions of the processing device 140 according to the techniques described herein. The computer instructions may include, for example, routines, programs, objects, components, data structures, processes, modules, and functions that perform specific functions described herein. For example, the processor 210 can process image data acquired from the radiation device 110, the terminal 130, the storage device 150, and / or any other component of the radiation therapy system 100. In some embodiments, the processor 210 can process images based on information related to the treatment plan. In some embodiments, the processor 210 can update the radiation therapy plan associated with the object. In some embodiments, the processor 210 may include one or more hardware processors, such as a microcontroller, a microprocessor, a reduced instruction set computer (RISC), an application-specific integrated circuit (ASIC), an application-specific instruction set processor (ASIP), a central processing unit (CPU), a graphics processing unit (GPU), a physical processing unit (PPU), a microcontroller unit, a digital signal processor (DSP), a field programmable gate array (FPGA), an advanced RISC machine (ARM), a programmable logic device (PLD), a circuit or processor that can perform one or more functions or similar functions or any combination thereof.

[0045] For illustration purposes only, only one processor is described in the computing device 200. However, it should be noted that the computing device 200 in this specification may also include multiple processors, and thus the operations and / or method steps performed by one processor as described in this specification may also be performed jointly or individually by multiple processors. For example, if in this specification, the processor of the computing device 200 performs step X and step Y simultaneously, it should be understood that step X and step Y may also be performed jointly or individually by two or more different processors in the computing device 200 (e.g., the first processor performs step X, the second processor performs step Y, or the first and second processors jointly perform steps X and Y).

[0046] The memory 220 may store data / information acquired from the radiation device 110, the terminal 130, the storage device 150, and / or any other component of the radiation therapy system 100. In some embodiments, the memory 220 may include a mass storage device, a removable storage device, a volatile read-write memory, a read-only memory (ROM), etc., or any combination thereof. For example, the mass storage may include a magnetic disk, an optical disk, a solid-state drive, etc. The removable storage may include a flash drive, a floppy disk, an optical disk, a memory card, a zipper disk, a magnetic tape, etc. The volatile read-write memory may include a random access memory (RAM). The RAM may include a dynamic RAM (DRAM), a double data rate synchronous dynamic RAM (DDR SDRAM), a static RAM (SRAM), a thyristor RAM (T-RAM), a zero-capacitance RAM (Z-RAM), etc. ROM may include mask ROM (MROM), programmable ROM (PROM), erasable programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM), compact disk ROM (CD-ROM) and digital versatile disk ROM, etc. In some embodiments, the memory 220 may store one or more programs and / or instructions to execute the exemplary methods described in this specification. For example, the memory 220 may store a program for the processing device 140 to generate and update an adaptive radiation therapy plan.

[0047] I / O 230 may input and / or output signals, data, information, etc. In some embodiments, I / O 230 may enable a user to interact with processing device 140. In some embodiments, I / O 230 may include input devices and output devices. Examples of input devices may include a keyboard, a mouse, a touch screen, a microphone, etc., or a combination thereof. Examples of output devices may include a display device, a speaker, a printer, a projector, etc., or a combination thereof. Examples of display devices may include a liquid crystal display (LCD), a display based on a light emitting diode (LED), a flat panel display, a curved screen, a television device, a cathode ray tube (CRT), a touch screen, etc., or a combination thereof.

[0048] The communication port 240 can be connected to a network (e.g., network 120) to facilitate data communication. The communication port 240 can establish a connection between the processing device 140 and the radiation device 110, the terminal 130, and / or the storage device 150. The connection can be a wired connection, a wireless connection, any other communication connection that can achieve data transmission and / or reception, and / or any combination of these connections. The wired connection can include, for example, an electrical cable, an optical cable, a telephone line, etc., or any combination thereof. The wireless connection can include, for example, a Bluetooth link, a Wi-Fi TM Link, WiMAX TMIn some embodiments, the communication port 240 may include a wireless communication port, a WLAN link, a Zigbee link, a mobile network link (e.g., 3G, 4G, 5G), etc., or any combination thereof. In some embodiments, the communication port 240 may be and / or include a standardized communication port, such as RS232, RS485, etc. In some embodiments, the communication port 240 may be a specifically designed communication port. For example, the communication port 240 may be designed according to the Digital Imaging and Communications in Medicine (DICOM) protocol.

[0049] Figure 3 1 is a schematic diagram of exemplary hardware and / or software components of an exemplary mobile device 300 on which the terminal 130 may be implemented according to some embodiments of the present specification. Figure 3 As shown, mobile device 300 may include communication platform 310, display 320, graphics processing unit (GPU) 330, central processing unit (CPU) 340, input / output 350, memory 360, and storage 390. In some embodiments, any other suitable components, including but not limited to a system bus or controller (not shown), may also be included in mobile device 300. In some embodiments, mobile operating system 370 (e.g., iOS 11) may be used to control the operation of the mobile device 300. TM 、Android TM 、WindowsPhone TM ) and one or more applications 380 may be loaded from storage 390 into memory 360 for execution by CPU 340. Applications 380 may include a browser or any other suitable mobile application for receiving and presenting information related to image processing or other information from processing device 140. User interaction with the information stream may be achieved through input / output 350 and provided to processing device 140 and / or other components of radiation therapy system 100 via network 120.

[0050] In order to implement the various modules, units and their functions described in this specification, a computer hardware platform can be used as a hardware platform for one or more components described herein. A computer with user interface elements can be used to implement a personal computer (PC) or any other type of workstation or terminal device. If the computer is properly programmed, the computer can also be used as a server.

[0051] Figure 4 4 is a schematic block diagram of an exemplary processing device according to some embodiments of the present specification. The processing device 140 may include an acquisition module 410 and a plan determination module 420 .

[0052] The acquisition module 410 may be configured to acquire a first image associated with the target object generated by the first scan.

[0053] The acquisition module 410 may also be configured to acquire a first radiation therapy plan for treating the target object. The first radiation therapy plan may be associated with the first image. In this specification, "treatment plan" and "radiation therapy plan" may be used interchangeably.

[0054] In some embodiments, before the entire treatment begins, one or more imaging scans (e.g., a first scan) can be performed to identify the target structure (e.g., a tumor) and surrounding normal structures of the target object, and one or more images (e.g., a first image) can be generated based on the one or more imaging scans.

[0055] In some embodiments, the first scan may be performed by scanning the target object with an imaging device in the radiation therapy system 100. For example, the imaging device may be combined with Figure 1 Describe the CT imaging device.

[0056] The first image may be generated based on the image data acquired from the first scan. One or more components in the radiation therapy system 100 (e.g., the processing device 140) may process the image data to provide the first image. The first image may include one or more medical images, such as an MRI image, a CT image, a PET image, an ultrasound image, an X-ray image, etc. or any combination thereof. The first image and / or corresponding image data may be stored in a storage medium (e.g., the storage device 150 and / or the memory 220). The processing device 140 (e.g., the acquisition module 410) may access the storage medium to acquire the first image.

[0057] The first image may indicate information related to the target object, such as the contour, morphology, condition, etc. of the target structure (eg, tumor) and / or surrounding tissue, or any combination thereof. In some embodiments, the first image may be two-dimensional (2D) or three-dimensional (3D).

[0058] A treatment plan may be generated based on one or more images. A treatment plan may describe how radiation therapy is to be administered to a patient, or more specifically, how radiation is to be delivered to a patient's region of interest (ROI) during a treatment course that may last for days, weeks, or months.

[0059] In some embodiments, since the patient may not be able to tolerate the total dose prescribed by the treatment plan in one treatment course, the entire treatment can be divided into at least two treatment parts. The patient can receive a portion of the total radiation dose in each of the at least two treatment parts (e.g., one or two treatment parts per day).

[0060] Treatment parameters corresponding to each treatment portion for radiation delivery and / or control of the radiation device 110 can be defined in the treatment plan, such as the planned portion duration, the planned radiation dose, the planned radiation delivery direction, the planned radiation beam shape, the planned radiation beam cross-sectional area, the planned ROI of the target object, etc., or any combination thereof.

[0061] In some embodiments, the first radiation therapy plan can be part of an original treatment plan that includes treatment parameters corresponding to the treatment fractions to be delivered. For example, the entire treatment can be divided into 4 treatment fractions, for example, fractions A to D, in sequence. The patient has already received fractions A and B. The first radiation therapy plan can be part of the original treatment plan, which can correspond to the treatment fraction (e.g., fraction C) after the treatment fractions (e.g., fractions A and B) that have already been performed.

[0062] The acquisition module 410 may also be configured to acquire a second image related to the target object generated by a second scan. The second scan may be performed later than the first scan.

[0063] During treatment, the anatomy of a target structure (e.g., a tumor) of a target subject or the anatomy of other tissues (e.g., tissue surrounding the tumor) may change. For example, a tumor may grow, deform, or shrink. If the original treatment plan is used after a change (e.g., shrinkage) in the target structure, there is a risk that the radiation dose applied to healthy tissue affects the healthy tissue. In adaptive radiation therapy, partial plan adaptation may be performed. For example, one or more images (e.g., a second image) of the target structure may be acquired during the course of radiation therapy (e.g., between certain treatment portions) to determine a changed contour of the target structure to adapt the treatment plan to the changed contour of the target structure.

[0064] The second scan may be performed before a treatment portion (not the first treatment portion of the entire treatment) is performed on the target subject. For example, the entire treatment may be divided into 4 treatment portions, for example, portions AD in sequence. The patient has already received portions A and B. The second scan may be performed before portion C is delivered to the patient.

[0065] In some embodiments, the second scan may be performed by scanning the target object with an imaging device in the radiation therapy system 100. For example, the imaging device may be combined with Figure 1 A CT imaging device is described.

[0066] The second image may be generated based on the image data acquired from the second scan. One or more components in the radiation therapy system 100 (e.g., the processing device 140) may process the image data to provide a second image. The second image may include one or more medical images, such as an MRI image, a CT image, a PET image, an ultrasound image, an X-ray image, etc. or any combination thereof. The second image and / or corresponding image data may be stored in a storage medium (e.g., the storage device 150 and / or the memory 220). The processing device 140 (e.g., the acquisition module 410) may access the storage medium to acquire the second image.

[0067] The second image may indicate information related to the target object, such as the contour, morphology, condition, etc. of the target structure (e.g., tumor) and / or surrounding tissue, or any combination thereof. In some embodiments, the second image may be two-dimensional (2D) or three-dimensional (3D).

[0068] The plan determination module 420 can be configured to determine a target radiation therapy plan based on the first radiation therapy plan, the first image, and the second image to treat the target object. The target radiation therapy plan can be the first radiation therapy plan from the original treatment plan or the second radiation therapy plan associated with the second image. In some embodiments, the target radiation therapy plan can correspond to a treatment portion to be delivered to the target object. For example, the entire treatment can be divided into 4 treatment portions, for example, portions AD in sequence. The patient has received portions A and B. In portion C, radiation can be delivered to the patient according to the target radiation therapy plan.

[0069] The second radiation therapy plan may be obtained by updating the first radiation therapy plan based on the second image to adapt the original therapy plan to the changed contours of the target structure in the second image after one or more treatment fractions.

[0070] The modules in the processing device 140 can be connected to each other or communicate with each other through a wired connection or a wireless connection. The wired connection may include a metal cable, an optical cable, a hybrid cable, etc. or any combination thereof. The wireless connection may include a local area network (LAN), a wide area network (WAN), Bluetooth, a ZigBee network, a near field communication (NFC), etc. or any combination thereof. Two or more modules can be combined into one module, and any one module can be split into two or more units. For example, the acquisition module 410 can be divided into two units. One of the two units can be configured to acquire a first image and a second image, and the other of the two units can be configured to acquire a first radiation therapy plan.

[0071] It should be noted that the above description is provided for illustrative purposes only and is not intended to limit the scope of this specification. A person skilled in the art may make various changes and modifications based on the description of this specification. However, these changes and modifications do not depart from the scope of this specification. For example, the processing device 140 may also include a storage module ( Figure 4 140). The storage module may be configured to store data generated during any processing performed by any component in the processing device 140. As another example, each component of the processing device 140 may include a storage device. Additionally or alternatively, the components of the processing device 140 may share a common storage device.

[0072] Figure 5 is a flowchart of an exemplary process for determining a target radiation therapy plan according to some embodiments of the present specification. In some embodiments, at least a portion of the processor 500 may be executed by the processing device 140 (e.g., in Figure 2 For example, process 500 may be stored in a storage device (e.g., storage device 150 and / or memory 220) in the form of instructions (e.g., an application program) and executed by processing device 140 (e.g., Figure 2 The processor 210 and / or Figure 4 The operations of the process shown below are for illustration purposes only. In some embodiments, process 500 may be performed with one or more additional operations not described and / or without one or more of the operations discussed above. In addition, as shown in FIG. Figure 5 The order in which the operations of process 500 are illustrated and described below is not intended to be limiting.

[0073] For the sake of brevity, in the description of the process, adaptive radiation therapy for treating a target object may be used as an example. It should be noted that the adaptive radiation therapy for treating a target object described below is provided for illustrative purposes and is not restrictive. For a person of ordinary skill in the art, process 500 may be applied to other similar situations, such as adaptive radiation therapy for treating more than one target object.

[0074] In some embodiments, processing device 140 may perform process 500 (eg, a re-planning process) prior to performing a treatment portion (other than the first treatment portion of the entire treatment). Processing device 140 may perform process 500 online or offline.

[0075] In 510 , the processing device 140 (eg, the acquisition module 410 ) may acquire a first image associated with the target object, the first image being generated by a first scan.

[0076] In 520, the processing device 140 (eg, the acquisition module 410) may acquire a first radiation therapy plan for treating the target object. The first radiation therapy plan may be associated with the first image. In this specification, "treatment plan" and "radiation therapy plan" may be used interchangeably.

[0077] In some embodiments, before the entire treatment begins, one or more imaging scans (e.g., a first scan) can be performed to identify the target structure (e.g., a tumor) and surrounding normal structures of the target object, and one or more images (e.g., a first image) can be generated based on the one or more imaging scans.

[0078] In some embodiments, the first scan may be performed by scanning the target object with an imaging device in the radiation therapy system 100. For example, the imaging device may be combined with Figure 1 Describe the CT imaging device.

[0079] The first image may be generated based on the image data acquired from the first scan. One or more components in the radiation therapy system 100 (e.g., the processing device 140) may process the image data to provide the first image. The first image may include one or more medical images, such as an MRI image, a CT image, a PET image, an ultrasound image, an X-ray image, etc. or any combination thereof. The first image and / or corresponding image data may be stored in a storage medium (e.g., the storage device 150 and / or the memory 220). The processing device 140 (e.g., the acquisition module 410) may access the storage medium to acquire the first image.

[0080] The first image may indicate information related to the target object, such as the contour, morphology, condition, etc. of the target structure (e.g., tumor) and / or surrounding tissue, or any combination thereof. In some embodiments, the first image may be two-dimensional (2D) or three-dimensional (3D).

[0081] A treatment plan may be generated based on one or more images. A treatment plan may describe how to perform radiation therapy on a patient, or more specifically, how to deliver radiation to a patient's region of interest (ROI) during a treatment course that may last for days, weeks, or months.

[0082] In some embodiments, since the patient may not be able to tolerate the total dose prescribed by the treatment plan in one treatment course, the entire treatment can be divided into at least two treatment parts. The patient can receive a portion of the total radiation dose in each of the at least two treatment parts (e.g., one or two treatment parts per day).

[0083] Treatment parameters corresponding to each treatment portion for radiation delivery and / or control of the radiation device 110 can be defined in the treatment plan, such as the planned portion duration, the planned radiation dose, the planned radiation delivery direction, the planned radiation beam shape, the planned radiation beam cross-sectional area, the planned ROI of the target object, etc., or any combination thereof.

[0084] In some embodiments, the first radiation therapy plan can be part of an original treatment plan that includes treatment parameters corresponding to the treatment fractions to be delivered. For example, the entire treatment can be divided into 4 treatment fractions, for example, fractions A to D, in sequence. The patient has already received fractions A and B. The first radiation therapy plan can be part of the original treatment plan, which can correspond to the treatment fraction (e.g., fraction C) after the treatment fractions (e.g., fractions A and B) that have already been performed.

[0085] In 530, the processing device 140 (eg, the acquisition module 410) may acquire a second image associated with the target object, the second image being generated by a second scan. The second scan may be performed later than the first scan.

[0086] During treatment, the anatomy of a target structure (e.g., a tumor) of a target subject or the anatomy of other tissues (e.g., tissue surrounding the tumor) may change. For example, a tumor may grow, deform, or shrink. If the original treatment plan is used after a change (e.g., shrinkage) in the target structure, there is a risk that the radiation dose applied to healthy tissue affects the healthy tissue. In adaptive radiation therapy, partial plan adaptation may be performed. For example, one or more images (e.g., a second image) of the target structure may be acquired during the course of radiation therapy (e.g., between certain treatment portions) to determine a changed contour of the target structure to adapt the treatment plan to the changed contour of the target structure.

[0087] The second scan may be performed before a treatment portion (not the first treatment portion of the entire treatment) is performed on the target subject. For example, the entire treatment may be divided into 4 treatment portions, for example, portions AD in sequence. The patient has already received portions A and B. The second scan may be performed before portion C is delivered to the patient.

[0088] In some embodiments, the second scan may be performed by scanning the target object with an imaging device in the radiation therapy system 100. For example, the imaging device may be combined with Figure 1 Describe the CT imaging device.

[0089] The second image may be generated based on the image data acquired from the second scan. One or more components in the radiation therapy system 100 (e.g., the processing device 140) may process the image data to provide a second image. The second image may include one or more medical images, such as an MRI image, a CT image, a PET image, an ultrasound image, an X-ray image, etc. or any combination thereof. The second image and / or corresponding image data may be stored in a storage medium (e.g., the storage device 150 and / or the memory 220). The processing device 140 (e.g., the acquisition module 410) may access the storage medium to acquire the second image.

[0090] The second image may indicate information related to the target object, such as the contour, morphology, condition, etc. of the target structure (e.g., tumor) and / or surrounding tissue, or any combination thereof. In some embodiments, the second image may be two-dimensional (2D) or three-dimensional (3D).

[0091] In 540, the processing device 140 (e.g., the plan determination module 420) can determine a target radiation therapy plan based on the first radiation therapy plan, the first image, and the second image to treat the target object. The target radiation therapy plan can be the first radiation therapy plan from the original treatment plan or the second radiation therapy plan associated with the second image. In some embodiments, the target radiation therapy plan can correspond to a treatment portion to be delivered to the target object. For example, the entire treatment can be divided into 4 treatment portions, for example, portions AD in sequence. The patient has received portions A and B. In portion C, radiation can be delivered to the patient according to the target radiation therapy plan.

[0092] The second radiation therapy plan may be obtained by updating the first radiation therapy plan based on the second image to adapt the original therapy plan to the changed contours of the target structure in the second image after one or more treatment fractions.

[0093] When radiation is delivered to the patient in a timely manner, the re-proliferation of tumor cells can be effectively avoided, and the best efficacy of treatment can be achieved. Therefore, the re-planning process needs to be performed quickly; otherwise, it may cause a delay in the implementation of radiotherapy, which may affect the results of radiotherapy. In some embodiments, the processing device 140 can perform at least two operations to perform the re-planning process. In order to achieve the above purpose, the processing device 140 can perform at least two independent operations in parallel. As used herein, the parallel execution of two or more operations indicates that at least a portion of the two or more operations are performed simultaneously, even if the execution of the two or more operations may start or end at the same time or at different times. As an example only, the processing device 140 can be regarded as implementing at least two independent threads performed in parallel, each thread performing one or more operations in adaptive radiotherapy. For example, in the process of determining a target radiotherapy plan, a first operation for determining one or more ROIs in a second image and a second operation for estimating a first dose distribution associated with a first radiotherapy plan can be performed. The first operation and the second operation are independent of each other. The processing device 140 can perform the first operation and the second operation in parallel. For example, the processing device 140 can start the second operation when executing the first operation, instead of starting the second operation after completing the first operation.

[0094] Further description of the determination of a target radiation therapy plan may be found elsewhere in this specification (e.g., Figure 6 , Figure 7 , and its description) are found.

[0095] In some embodiments, the processing device 140 may perform operation 540 shortly after acquiring the second image based on the second scan (e.g., within a few minutes, within a few hours, on the same day, etc.). In this case, the first image and the first radiation therapy plan may be acquired during the second scan. In some embodiments, after acquiring the second image based on the second scan, the processing device 140 may perform operation 540 at a defined time, e.g., the next day, a few days later, etc.

[0096] In some embodiments, shortly after performing the process 500 of the re-planning process (e.g., within a few minutes, within a few hours, on the same day, etc.), the processing device 140 may cause the treatment fraction to be delivered to the target subject based on the target radiation therapy plan (e.g., control the radiation device 110 to deliver the treatment fraction based on the target radiation therapy plan). In some embodiments, after performing the process 500 of the re-planning process, the processing device 140 may deliver the treatment fraction to the target subject based on the target radiation therapy plan at a defined time, e.g., the next day, a few days later, etc.

[0097] It should be noted that the above description is provided for illustrative purposes only and is not intended to limit the scope of this specification. For those of ordinary skill in the art, various changes and modifications can be made according to the description of this specification. However, these changes and modifications do not depart from the scope of this specification.

[0098] Figure 6 600 is a flowchart of an exemplary process for determining a target radiation therapy plan according to some embodiments of the present specification. In some embodiments, at least a portion of process 600 may be performed by processing device 140 (e.g., in Figure 2 For example, process 600 may be stored in a storage device (e.g., storage device 150 and / or memory 220) in the form of instructions (e.g., an application program) and executed by processing device 140 (e.g., Figure 2 The processor 210 and / or Figure 4 The operations of the process shown below are for illustration purposes only. In some embodiments, process 600 may be completed by one or more additional operations not described, and / or one or more operations not discussed. In addition, as Figure 6 The order in which the operations of process 600 are shown and described below is not intended to be limiting. In some embodiments, operation 540 of process 500 may be performed based on process 600.

[0099] In 610, the processing device 140 (e.g., the plan determination module 420) may generate a registration result by performing image registration between the first image and the second image. As used herein, image registration is to convert spatial information of different images (e.g., the first image and the second image) into the same coordinate system in order to compare or integrate data acquired from the different images.

[0100] Image registration can be performed based on any suitable image registration technique, including, for example, voxel-based registration techniques, marker-based registration techniques, segmentation-based registration techniques, etc. or a combination thereof. In some embodiments, the registration can be a rigid registration. In some embodiments, the registration can be a non-rigid deformable registration.

[0101] By way of example only, the second image can be registered with the first image based on a registration technique based on a marker. The marker used for registration can be a visible anatomical point that can be identified and located in an image (e.g., a first image, a second image). For example, the marker can be a bone. In the registration, the marker in the first image can be aligned with the corresponding marker in the second image. Image registration of the second image with the first image can be performed to remove at least a portion of the error caused by a misalignment of the target object when the second image is acquired compared to when the first image is acquired. The misalignment may be caused by, for example, a change in the weight of the target object, an error in the setting of the target object for the second scan used to acquire the second image, the like, or a combination thereof.

[0102] The registration result may include one or more images generated by image registration and / or a registration matrix representing the transformation relationship between the first image and the second image. For example, if a pixel of the ROI in the first image has a pair of coordinates (x A ,y A ), and the corresponding pixel in the second image has a pair of coordinates (x B ,y B ), then the processing device 140 can use the registration matrix to convert (x A ,y A ) to coordinate system B or (x B ,y B ) is transformed to coordinate system A.

[0103] In some embodiments, the processing device 140 can automatically perform image registration. In some embodiments, the registration result may need to be accepted by the user (e.g., a doctor, clinician, etc.) before it can be used for subsequent operations, such as determining the ROI in the second image. In some embodiments, the registration result including the fused image can be presented to the user. The fused image can be generated by fusing the registered second image and the first image using image fusion technology. Exemplary image fusion techniques may include data-level fusion, feature-level fusion, and decision-level fusion. In this article, data-level fusion may include spatial domain algorithms, transform domain algorithms, etc. Transform domain algorithms may include pyramid decomposition fusion algorithms, wavelet transform algorithms, etc. Feature-level fusion may include infrared image fusion based on heat, visible light image fusion based on brightness, etc. Decision-level fusion may be based on Bayesian algorithms, Dempster-Shafter (DS) evidence reasoning, voting algorithms, etc.

[0104] The user can view or analyze the registration result by accepting the registration result or modifying the registration result. The user's interaction with the registration result can be implemented through I / O 230 and / or I / O 350 and provided to the processing device 140 and / or other components of the radiation therapy system 100 through the network 120.

[0105] In 620, the processing device 140 (e.g., the plan determination module 420) may determine the distribution of the cumulative dose in the second image based on the registration result. The distribution of the cumulative dose in the second image may be the distribution of the cumulative dose of radiation that has been delivered to or received by the target object in the target structure (e.g., a tumor) and surrounding normal structures after one or more treatment portions are performed on the target object. In some embodiments, the distribution of the cumulative dose may be represented by the cumulative dose of each pixel / voxel in the second image. In some embodiments, the cumulative dose of each pixel / voxel in the second image may be represented as a pixel or voxel value of the pixel / voxel in the second image.

[0106] In some embodiments, the distribution of the cumulative dose in the second image can be determined based on the treatment parameters corresponding to the performed treatment portion and the registered second image. For example, the plan determination module 420 can determine the distribution of the cumulative dose in the second image by adding each dose distribution of all performed treatment portions. The dose distribution can reflect the radiation absorption rate associated with one or more positions of the target object during the treatment portion. The dose distribution can be expressed as {(A1, B1), (A2, B2), ... (Ai, Bi), ... (An, Bn)}, where Ai can represent the position of the target object and Bi can represent the radiation dose absorbed by the position Ai of the target object. For example, the plan determination module 420 can retrieve the position information of the target object Ai (e.g., represented by the coordinates of pixels / voxels) from the second image, and obtain information about the beam field applied to the position Ai based on one or more treatment parameters (e.g., radiation beam direction and / or radiation beam shape), and determine or estimate the radiation dose delivered to or absorbed by the position Ai based on the field dose of at least two treatment parameters.

[0107] In 630, the processing device 140 (e.g., the plan determination module 420) may determine one or more ROIs in the second image. The ROI may be a region of a target object in the second image that includes at least a portion of a malignant tissue (e.g., a tumor, a cancer-ridden organ, or a non-cancer target for radiation therapy). Additionally or alternatively, the ROI may include other tissues, such as normal tissue surrounding the malignant tissue.

[0108] In some embodiments, during treatment, the anatomy of the tumor or other tissue (e.g., tissue surrounding the tumor) may change. For example, the tumor may grow, deform, or shrink. One or more ROIs may be determined in the second image to determine the contours of the changes in the target structure and / or surrounding normal structures.

[0109] In some embodiments, one or more ROIs in the second image can be determined by performing automatic contouring and / or segmentation in the second image. For example, automatic contouring in the second image can be performed using a machine learning model trained to identify the contours of one or more ROIs. As another example, automatic contouring and / or segmentation in the second image can be performed using an automatic contouring algorithm and / or a segmentation algorithm. In some embodiments, determining the ROI by performing automatic contouring and / or segmentation can be performed in parallel with operation 610.

[0110] In some embodiments, one or more ROIs in the second image can be automatically determined based on the registration result and the first image. The plan determination module 420 can apply one or more corresponding ROIs in the first image to the registered second image and automatically determine one or more ROIs in the second image. One or more corresponding ROIs in the first image can be automatically determined based on, for example, a contour algorithm and / or a segmentation algorithm, or manually determined by a user of the radiation therapy system 100.

[0111] In some embodiments, one or more automatically determined ROIs in the second image may need to be reviewed or analyzed by the user before use. For example only, the plan determination module 420 may automatically determine one or more ROIs in the second image using a machine learning model or an automatic contour algorithm. The plan determination module 420 may also cause one or more automatically determined ROIs to be presented to the user to allow the user to provide instructions. In some embodiments, the user may provide instructions to indicate that one or more of the at least one automatically determined ROIs need to be modified or are acceptable. The plan determination module 420 may retain the automatically determined ROI in the second image based on a user instruction that the ROI is acceptable (or referred to as an acceptance instruction for the sake of brevity). The plan determination module 420 may update the automatically determined ROI in the second image based on a user instruction that the ROI needs to be modified (or referred to as a modification instruction for the sake of brevity). The user may provide instructions through a user interface implemented on, for example, the I / O 350 of the terminal 130, and / or the I / O 230 of the processing device 140.

[0112] In some embodiments, one or more ROIs in the second image may be manually determined by a user (e.g., a doctor, clinician, etc.) via, for example, I / O 230 of processing device 140 and / or I / O 350 of one or more terminals 130. By way of example only, a clinician may draw one or more ROIs in the second image directly on a touch screen or using a mouse. In some embodiments, manual determination of ROIs may be performed in parallel with operation 610.

[0113] In some embodiments, the processing device 140 may determine one or more ROIs in the second image one by one, or determine at least two ROIs in the second image in parallel. For example, the processing device 140 may be configured to include at least two independent threads, each thread determining the ROI one by one, and thus at least two ROIs may be determined in parallel in the second image.

[0114] In some embodiments, at least two operations of automatically determining the ROI, displaying the automatically determined ROI, and manually accepting or modifying the automatically determined ROI may be performed in parallel.

[0115] For example, after automatically determining the first ROI in the second image, the processing device 140 may determine the second ROI regardless of whether the first ROI is displayed or the processing device 140 has received an acceptance or modification instruction related to the first ROI from the user. As another example, the processing device 140 may determine whether to retain the first ROI or update the first ROI based on the user instruction while continuing to perform the determination of the second ROI in parallel.

[0116] In some embodiments, the automatic determination of one or more ROIs in the second image may be performed based on an estimate of the time length for determining each of the one or more ROIs. In some embodiments, the time length for determining the ROI may be determined by the processing device 140 or pre-set by the user based on the characteristics of the tissue in the ROI and the algorithm for determining the ROI. The plan determination module 420 may sort the time lengths, for example, in ascending order. The plan determination module 420 may automatically determine one or more ROIs based on the sorting result. In this way, there may be at least one automatically determined ROI for the user to analyze as quickly as possible. If determining the ROI may first require the processing device 140 to spend a relatively long time to determine the ROI in the second image, the user may need to wait for a relatively long time, which may reduce the efficiency of the replanning process in adaptive radiation therapy.

[0117] In some embodiments, during the period when the user decides whether to modify the automatically determined ROI, the processing device 140 can complete the determination of multiple ROIs in the second image. Therefore, after the user completes the modification of the ROI, there may be multiple automatically determined ROIs for the user to view, process or analyze. In some embodiments, the processing device 140 can sort the one or more automatically determined ROIs to be processed in descending order based on an estimate of the workload or time required to modify each of the one or more automatically determined ROIs. The (estimated) workload or time required to modify the ROI can be related to the algorithm used to automatically determine the ROI and the tissue structure included in the ROI. The higher the accuracy of the algorithm for automatically determining the ROI including the tissue, the shorter the time required to modify the ROI may be. In some embodiments, the (estimated) workload or time required to modify the ROI can be determined by the processing device 140 or preset by the user based on the characteristics of the tissue in the ROI and / or the algorithm for automatically determining the ROI. In some embodiments, the processing device 140 can cause a list to be displayed, in which the automatically determined ROIs are sorted in descending order based on the (estimated) workload or the time required to modify each ROI. In some embodiments, the user may be encouraged (but not forced) to view or modify the ROIs in ascending order, where ROIs with more (estimated) effort or length of time for the user to view or modify are ranked higher than ROIs with less (estimated) effort or length of time for the user to view or modify. In some embodiments, the processing device 140 may allow the user to view or analyze the ROIs only in descending order, where, in the descending order of the ROIs, the user needs to process those ROIs that require the user to spend more effort or time to view or modify first, and then process other ROIs.

[0118] In this way, when the user completes the review of an ROI (e.g., accepting or modifying), there will be at least one automatically determined ROI for the user to analyze; otherwise, after the user completes viewing an ROI, there may be no automatically determined ROI for the user to analyze, and if the processing device 140 determines the ROI in ascending order of the time length used to determine each ROI, the efficiency of the replanning process in adaptive radiation therapy may be reduced.

[0119] In some embodiments, one or more ROIs in the second image may be determined using different techniques. By way of example only, the plan determination module 420 may automatically determine ROI A in the second image based on a segmentation algorithm. The plan determination module 420 may automatically determine ROI B in the second image based on the result of a deformable registration between the first image and the second image (or referred to as a deformable registration result for the sake of simplicity). The plan determination module 420 may automatically determine ROI C in the second image based on the result of a rigid registration between the first image and the second image. The plan determination module 420 may determine ROI D in the second image based on instructions from a user. The technique for automatically determining the ROI may be selected from at least two techniques based on one or more factors, including, for example, the anatomy of the tissue, organ, or structure of the ROI to be determined. In some embodiments, the type of ROI to be determined may be included in the first radiation therapy plan. The technique for determining the ROI may be selected based on the type of ROI. For example, an ROI of a tissue that needs to be protected from radiation, such as the lung, rectum, pancreas, or the like, or a portion thereof, may be determined based on a segmentation algorithm. As another example, a ROI of tissue that may change after radiation, such as a target object (eg, a tumor) or a colon or a portion thereof, may be determined based on the deformable registration result. In some embodiments, determination of different ROIs in the second image may be performed in parallel.

[0120] In some embodiments, multiple techniques for determining ROIs can be applied to the same location in the second image (e.g., the same tissue), from which different ROIs corresponding to the same tissue can be determined. The user can select one determined ROI to view, and other ROIs of the tissue can be deleted. For example, for certain tissues in the second image (e.g., tumors), the plan determination module 420 can determine the ROIE based on the non-rigid deformable registration results, and determine the ROIF using the rigid registration results. The user may be allowed to select any one to view (e.g., accept or modify). As an example only, the user can accept the ROIE determined based on the non-rigid deformable registration results. Thereafter, the ROIF determined based on the rigid registration results can be deleted. In some embodiments, determining the ROI of the same tissue in the second image using different techniques can be performed in parallel.

[0121] In 640, the processing device 140 (e.g., the plan determination module 420) can estimate a first dose distribution in the second image based on the first radiation therapy plan and the second image. The first dose distribution in the second image can be a distribution of a total radiation dose delivered to or received by a target object at a target structure (e.g., a tumor) and surrounding normal structures after a treatment portion corresponding to the first radiation therapy. In some embodiments, the first dose distribution can be represented by a total radiation dose per pixel / voxel in the second image. In some embodiments, the first dose distribution can be represented as a pixel or voxel value of a pixel / voxel in the second image.

[0122] The plan determination module 420 can apply the treatment parameters of the first radiation therapy plan to the registered second image to generate a first dose distribution of the first radiation therapy plan. The determination of the first dose distribution can be similar to the determination of the cumulative dose distribution in the second image. See, for example, operation 620 and its description, which will not be repeated here.

[0123] In some embodiments, operations 620-640 are independent of each other. Processing device 140 may perform at least two of operations 620-640 in parallel.

[0124] In 650, the processing device 140 (e.g., the plan determination module 420) may estimate a second dose distribution in one or more ROIs in the second image based on the first dose distribution. The second dose distribution in the second image may be a dose of radiation delivered to or received by one or more ROIs in the second image in a treatment portion corresponding to the first radiation therapy. If the treatment portion is delivered to the target object based on the first radiation therapy plan (e.g., a portion of the original overall treatment plan), the second dose distribution may indicate an estimated radiation dose that will be delivered to each ROI in the second image.

[0125] The second dose distribution can be estimated based on the first dose distribution, one or more ROIs in the second image, and the distribution of the cumulative dose. For example, the processing device 140 can determine the third dose distribution in the second image by subtracting the distribution of the cumulative dose from the first dose distribution. The third dose distribution in the second image can be the distribution of the radiation dose delivered to the target object or received by the target object at the target structure (e.g., tumor) and the surrounding normal structure in the treatment portion corresponding to the first radiotherapy plan. In some embodiments, the third dose distribution can be represented by the radiation dose of each pixel / voxel in the second image. In some embodiments, the third dose distribution can be represented as a pixel or voxel value of a pixel / voxel in the second image. The processing device 140 can determine the second dose distribution based on the third dose distribution (e.g., the subtraction result) and one or more ROIs.

[0126] In some embodiments, the second dose distribution may include a dose volume histogram (DVH) associated with the second image. The processing device 140 may determine the DVH based on the first dose distribution and / or the first radiation treatment. The DVH may display the relationship between the radiation dose received in the treatment portion and the volume of the target object. The DVH may be helpful in evaluating different treatment portions and / or corresponding radiation treatment plans. For example, the DVH may be configured to compare the delivered radiation doses from different treatment portions.

[0127] In some embodiments, the plan determination module 420 can determine the delivered radiation dose in the treatment portion for each voxel / pixel in the second image of the target object and generate a histogram, calculating the number (or count) of voxels / pixels that received the same radiation dose according to the first radiation treatment. In some embodiments, the processing device 140 can determine a DVH corresponding to each ROI in the second image. In some embodiments, depending on how the results are analyzed, in the DVH, the volume in the vertical axis and the dose in the horizontal axis can be displayed in absolute values ​​(e.g., cubic centimeters (cc), Gy) or relative values ​​(e.g., volume %, % dose).

[0128] In some embodiments, the processing device 140 may display a first dose distribution based on one or more ROIs. In some embodiments, the processing device 140 may display a second dose distribution. In some embodiments, the display of the first dose distribution may be performed in parallel with operation 650 or the display of the second dose distribution.

[0129] In 660, the processing device 140 (e.g., the plan determination module 420) may determine whether to continue to use the first radiation therapy plan to treat the target object in the corresponding treatment portion. The processing device 140 may determine whether the first radiation therapy plan satisfies one or more preset conditions based on the second dose distribution. For example, the one or more preset conditions may include a maximum dose to be delivered to or received by surrounding normal tissues in the treatment portion, a total dose range to be delivered to or received by the target object in the treatment portion, a dose range to be delivered to or received by a target structure (e.g., a tumor) of the target object in the treatment portion, etc., or any combination thereof. In some embodiments, the user may add one or more new preset conditions and / or modify at least one of the original preset conditions for the treatment portion corresponding to the first radiation therapy plan. The processing device 140 may further determine whether to continue to use the first radiation therapy plan to treat the target object in the treatment portion based on the newly added and / or modified preset conditions. In some embodiments, the one or more preset conditions may be determined by the processing device 140 and / or the user.

[0130] In 670 , the processing device 140 (eg, the plan determination module 420 ) may treat the target object using a second radiation therapy plan in response to determining that the first radiation therapy does not satisfy one or more preset conditions.

[0131] In some embodiments, the second radiation therapy plan may be generated by the processing device 140 and / or the user based on the first radiation therapy plan, the second dose distribution, one or more ROIs in the second image, and one or more preset conditions.

[0132] At 680 , the processing device 140 (eg, the plan determination module 420 ) may treat the target object using the first radiation therapy plan in response to a determination that the first radiation therapy satisfies one or more preset conditions.

[0133] In some embodiments, the processing device 140 may perform the generation of the second radiation therapy plan and operation 660 in parallel. In this way, in response to determining that the first radiation therapy does not satisfy one or more preset conditions, the waiting time for generating the second radiation therapy plan may be shortened, thereby improving the efficiency of the adaptive radiation therapy. This means that regardless of the determination result of operation 660, the processing device 140 may determine the second treatment plan to reduce the idle time of the system 100 or the user; whether the second treatment plan is to be used may depend on the determination result of operation 660.

[0134] It should be noted that the above description is provided for the purpose of illustration only and is not intended to limit the scope of this specification. For those of ordinary skill in the art, various changes and modifications can be made according to the description of this specification. However, these changes and modifications do not depart from the scope of this specification. For example, operations 660 and 680 can be omitted.

[0135] Figure 7 700 is a flowchart of an exemplary process for determining a target radiation therapy plan according to some embodiments of the present specification. In some embodiments, at least a portion of process 700 may be performed by processing device 140 (e.g., in Figure 2 For example, process 700 may be stored in a storage device (e.g., storage device 150 and / or memory 220) in the form of instructions (e.g., an application program) and executed by processing device 140 (e.g., Figure 2 The processor 210 and / or Figure 4 The operations of the process shown below are for illustration purposes only. In some embodiments, process 700 may be completed by one or more additional operations not described, and / or one or more operations not discussed. In addition, as Figure 7The order in which the operations of process 700 are illustrated and described below is not intended to be limiting.

[0136] In 710, the processing device 140 (eg, the plan determination module 420) may determine one or more ROIs in the second image. Further description of the determination of the ROI in the second image may be found elsewhere in this specification (eg, Figure 6 Operation 630 of process 600 and its description) are found.

[0137] In 720 , the processing device 140 (eg, the plan determination module 420 ) may generate a first intermediate plan by updating the first radiation therapy plan based on the one or more determined ROIs.

[0138] In some embodiments, the processing device 140 may determine a second dose distribution in the second image based on the one or more determined ROIs, and generate a first intermediate plan by updating the first radiation therapy plan based on the second dose distribution and one or more preset conditions. More descriptions of the determination of the second dose distribution and the first intermediate plan may be found elsewhere in this specification (e.g., similar to Figure 6 Operations 650 and 670 of process 600, and their descriptions) are found.

[0139] In some embodiments, the processing device 140 may generate a DVH corresponding to the first intermediate plan based on one or more automatically determined ROIs and the second dose distribution. Further description of the DVH may be found elsewhere in this specification (e.g., similar to Figure 6 Operation 650 of process 600, and its description) is found.

[0140] In some embodiments, the processing device 140 may divide the one or more automatically determined ROIs into at least two groups (e.g., N groups of ROIs, N is a positive integer). The processing device 140 may perform at least two iterations (e.g., N iterations) to generate a second radiation therapy plan based on the first intermediate plan. For example, at least one of the at least two iterations may include operations 730-750.

[0141] In 730, the processing device 140 (eg, the plan determination module 420) may receive instructions related to viewing (eg, modifying or accepting) a tth (T=1, 2, 3, ..., N) group of ROIs. The tth group of ROIs may include at least one of the one or more determined ROIs.

[0142] In some embodiments, based on an estimate of the workload or time length for manually modifying each ROI, one or more determined ROIs can be divided into at least two groups (e.g., N groups of ROIs). For example, one or more ROIs can be divided into three groups, such as the (estimated) time length for manual modification is less than 3 minutes, between 3 minutes and 5 minutes, and more than 5 minutes. As another example, one or more ROIs can be divided into three groups, such as the (estimated) workload for manual modification is complex, medium, and simple. More descriptions of the time length for manually modifying ROIs can be found elsewhere in this specification (e.g., Figure 6 Operation 630 of process 600, and its description) is found.

[0143] In some embodiments, the processing device 140 may cause a list to be displayed in which at least two ROIs are sorted, for example, in ascending order based on the (estimated) workload or the length of time required to view each ROI. The user may be allowed or encouraged (but not mandatory) to view the ROIs according to the sorting results. In some embodiments, the processing device 140 may allow the user to view the ROIs only according to the sorting results, for example, in ascending order, in which the user needs to process those ROIs that require the user to spend less (estimated) workload or length of time to view or modify before processing other ROIs. In this way, the processing device 140 can update the first intermediate plan as quickly as possible to generate the second intermediate plan. If a set of determined ROIs is determined, it may initially take the user a long time to view, then the processing device 140 may be idle for a long time (for example, the waiting time for generating the second intermediate plan based on the first set of viewed ROIs may be relatively long), which may reduce the efficiency of the replanning process in adaptive radiation therapy.

[0144] Further description of manually modifying and / or accepting ROIs may be found elsewhere in this specification (e.g., similar to Figure 6 Operation 630 of process 600 and its description) are found and are not repeated here.

[0145] In 740 , the processing device 140 (eg, the plan determination module 420 ) may process (eg, update or maintain) the tth group of ROIs based on the instruction.

[0146] In some embodiments, the user may provide an instruction to indicate that one or more of the determined ROIs in the t-th group of ROIs need to be modified or are acceptable. The plan determination module 420 may maintain the determined ROI in the t-th group of ROIs based on the user instruction that the ROI is acceptable (or referred to as an acceptance instruction for brevity). The plan determination module 420 may update the determined ROI in the t-th group of ROIs based on the user instruction that the ROI needs to be modified (or referred to as a modification instruction for brevity).

[0147] In 750 , the processing device 140 (eg, the plan determination module 420 ) may generate a (t+1)th intermediate plan based on the tth intermediate plan and the processed tth group of ROIs.

[0148] For example, the processing device 140 may process (e.g., update or maintain) the second dose distribution in the second image determined in the previous iteration (e.g., the (t-1)th iteration) based on the processed tth group of ROIs, and generate the (t+1)th intermediate plan by processing (e.g., updating or maintaining) the tth plan based on the processed second dose distribution and one or more preset conditions. More descriptions of the determination of the first intermediate plan and the second dose distribution may be found elsewhere in this specification (e.g., similar to Figure 6 Operations 650 and 670 of process 600, and their descriptions) are found.

[0149] In some embodiments, the processing device 140 may generate a DVH corresponding to the (t+1)th intermediate plan based on the processed tth group of ROIs and the processed second dose distribution.

[0150] In some embodiments, the processing device 140 may perform operations 730 and 740 in parallel with operation 750. For example, after automatically processing the first set of ROIs in the second image, regardless of whether the processing device 140 has completed generating the second intermediate plan based on the processed first set of ROIs, once the processing device 140 receives an instruction from the user related to modifying or accepting the second set of ROIs, the processing device 140 may process (e.g., accept or update) the second set of ROIs based on the instruction.

[0151] In some embodiments, processing device 140 may perform operation 720 in parallel with processing of the first set of ROIs based on instructions from a user. For example, processing device 140 may generate a first intermediate plan based on one or more automatically determined ROIs while receiving instructions from a user to view (e.g., modify or accept) the first set of automatically determined ROIs or process (e.g., update or maintain) the first set of automatically determined ROIs based on instructions from the user.

[0152] In 760 , the processing device 140 (eg, the plan determination module 420 ) may designate the intermediate plan generated in the last iteration of the at least two iterations as a second radiation therapy plan.

[0153] In this way, during the process of viewing the determined ROIs, the processing device 140 can continue to update the first radiation therapy plan in real time based on the most recently viewed ROI. When all determined ROIs are viewed (e.g., modified or accepted), the second radiation therapy plan is generated accordingly, which may take a shorter time than performing the process of updating the first radiation therapy plan only after all ROIs are viewed (e.g., modified or accepted).

[0154] In some embodiments, process 600 and process 700 may be combined to determine a target radiation therapy plan. For example, operations 630-650 may be replaced by process 700. In some embodiments, if the user does not need processing device 140 to perform process 700, the user may close process 700, for example, via I / O 230 and / or I / O 350.

[0155] It should be noted that the above description is provided for illustrative purposes only and is not intended to limit the scope of this specification. For those with ordinary skills in the art, various changes and modifications can be made under the guidance of this specification. However, these changes and modifications do not depart from the scope of this specification.

[0156] The basic concepts have been described above. Obviously, for those of ordinary skill in the art who have read this specification, the above invention disclosure is only for example and does not constitute a limitation of this specification. Although not explicitly stated here, those of ordinary skill in the art may make various modifications, improvements and amendments to this specification. Such modifications, improvements and amendments are suggested in this specification, so such modifications, improvements and amendments still belong to the spirit and scope of the exemplary embodiments of this specification.

[0157] At the same time, this specification uses specific words to describe the embodiments of this specification. For example, "one embodiment", "an embodiment", and / or "some embodiments" refer to a certain feature, structure or characteristic related to at least one embodiment of this specification. Therefore, it should be emphasized and noted that "one embodiment" or "an embodiment" or "an alternative embodiment" mentioned twice or more in different positions in this specification does not necessarily refer to the same embodiment. In addition, certain features, structures or characteristics in one or more embodiments of this specification can be appropriately combined.

[0158] In addition, it will be understood by those skilled in the art that various aspects of this specification may be illustrated and described by a number of patentable categories or situations, including any new and useful process, machine, product, or combination of substances, or any new and useful improvement thereof. Therefore, various aspects of this specification may be implemented in full hardware, full software (including firmware, resident software, microcode, etc.), or a combination of software and hardware, which may all be generally referred to herein as "units," "modules," or "systems." In addition, various aspects of this specification may take the form of a computer program product embodied in one or more computer-readable media, having computer-readable program code embodied thereon.

[0159] A computer readable signal medium may include a propagated data signal containing computer program code, for example, in baseband or as part of a carrier wave. Such propagated signals may be in a variety of forms, including electromagnetic, optical, etc., or any suitable combination. A computer readable signal medium may be any computer readable medium other than a computer readable storage medium, which may be connected to an instruction execution system, device or apparatus to communicate, propagate or transmit a program for use. The program code on a computer readable signal medium may be propagated via any suitable medium, including radio, cable, fiber optic cable, RF, etc., or any combination of the above.

[0160] The computer program code for operating various aspects of this specification can be written in any combination of one or more programming languages, including object-oriented programming languages, such as Java, Scala, Smalltalk, Eiffel, JADE, Emerald, C++, C#, VB.NET, Python, etc. Traditional process programming languages, such as "C" programming language, VisualBasic, Fortran2103, Perl, COBOL2102, PHP, ABAP. Dynamic programming languages, such as Python, Ruby and Groovy, or other programming languages. The program code can be run completely on the user's computer, or run on the user's computer as an independent software package, or run partially on the user's computer and partially on the remote computer, or run completely on the remote computer or server. In the latter case, the remote computer can be connected to the user's computer through any type of network (including local area network (LAN) or wide area network (WAN)), or can be connected to an external computer (for example, by using the network of a network service provider) or in a cloud computing environment or as a service, for example, software as a service (SaaS).

[0161] In addition, unless explicitly stated in the claims, the order of the processing elements and sequences described in this specification, the use of alphanumeric characters, or the use of other names are not intended to limit the order of the processes and methods of this specification. Although the above disclosure discusses some invention embodiments that are currently considered useful through various examples, it should be understood that such details are only for illustrative purposes, and the attached claims are not limited to the disclosed embodiments. On the contrary, the claims are intended to cover all modifications and equivalent combinations that are consistent with the essence and scope of the embodiments of this specification. For example, although the implementation of the various components described above can be embodied in a hardware device, it can also be implemented as a pure software solution, for example, installation on an existing server or mobile device.

[0162] Similarly, it should be noted that in order to simplify the description disclosed in this specification and thus facilitate the understanding of one or more embodiments of the invention, the foregoing description of the embodiments of this specification sometimes combines multiple features into one embodiment, figure, or description thereof. However, this method of the specification should not be interpreted as reflecting the intention that the claimed object material to be scanned requires more features than those explicitly stated in each claim. In fact, the features of the embodiments are less than all the features of the single embodiment disclosed above.

Claims

1. A method for generating an adaptive radiation therapy plan, implemented on a machine having one or more processors and one or more storage devices, the method comprising: Acquire a first image associated with one or more target objects, wherein the first image is generated by a first scan; Acquire a first radiation therapy plan for treating the one or more target objects, wherein the first radiation therapy plan is associated with the first image; Acquire a second image associated with the one or more target objects, the second image being generated by a second scan performed later than the first scan; determining one or more regions of interest in the second image, and dividing the one or more determined regions of interest into at least two groups; generating a first intermediate plan by updating the first radiation therapy plan based on the one or more determined regions of interest; updating the first intermediate plan by performing at least two iterations; as well as The intermediate plan generated in the last iteration of the at least two iterations is determined as a target radiation therapy plan for treating the one or more target objects.

2. The method according to claim 1, wherein: The tth (t=1, 2, 3, ...) iteration of the at least two iterations comprises: receiving a second instruction for modifying or accepting a tth group of regions of interest, the tth group of regions of interest including at least one of the one or more determined regions of interest; Based on the second instruction, processing the tth group of regions of interest; and Based on the tth intermediate plan and the processed tth group of regions of interest, a (t+1)th intermediate plan is generated.

3. The method according to claim 1, wherein: Determining one or more regions of interest in the second image comprises: performing an automatic determination of one or more regions of interest in the second image based on an estimate of a length of time for determining each of the one or more regions of interest, the automatic determination comprising: estimating a length of time for determining each of the one or more regions of interest; Sort the length of time; The one or more regions of interest are automatically determined based on the ranking results.

4. The method according to claim 1, wherein: Determining one or more regions of interest in the second image comprises: automatically determining one or more first regions of interest among the one or more regions of interest in the second image; receiving a first instruction for modifying or accepting the one or more automatically determined first regions of interest; processing at least one of the one or more first regions of interest based on the first instruction; and automatically determining one or more second regions of interest in the one or more regions of interest in the second image; wherein The operation of automatically determining the one or more second regions of interest among the one or more regions of interest in the second image is performed in parallel with at least one of the operations of receiving the first instruction for modifying or accepting the one or more automatically determined first regions of interest and processing the one or more first regions of interest according to the first instruction.

5. The method according to claim 1, wherein: The dividing the one or more determined regions of interest into at least two groups comprises: estimating the effort of manually modifying each of the one or more automatically determined regions of interest; dividing the one or more regions of interest into at least two groups based on the workload of manually modifying the one or more regions of interest; and Based on the grouping result, an instruction is generated to prompt the user to modify the one or more regions of interest.

6. The method according to claim 1, wherein: Generating a first intermediate plan by updating the first radiotherapy plan based on the one or more determined regions of interest comprises: A second dose distribution in the second image is determined based on the one or more determined regions of interest, and the first intermediate plan is generated by updating the first radiation therapy plan based on the second dose distribution and one or more preset conditions.

7. The method according to claim 2, wherein: Receiving a second instruction for modifying or accepting the tth group of regions of interest, processing the tth group of regions of interest based on the second instruction, and generating the (t+1)th intermediate plan based on the tth intermediate plan and the processed tth group of regions of interest are executed in parallel.

8. The method according to claim 2, wherein: The operation of generating the first intermediate plan by updating the first radiation therapy plan based on the one or more determined regions of interest is performed in parallel with at least one of the operation of receiving an instruction for modifying or accepting the first set of regions of interest and the operation of processing the first set of regions of interest based on the instruction for modifying or accepting the first set of regions of interest; or The operation of generating the (t+1)th intermediate plan based on the tth intermediate plan and the processed tth group of regions of interest is performed in parallel with at least one of the operations of receiving an instruction for modifying or accepting the (t+1)th group of regions of interest and processing the (t+1)th group of regions of interest based on the instruction for modifying or accepting the (t+1)th group of regions of interest.

9. A system for generating an adaptive radiation therapy plan, comprising: Get module, configured as Acquire a first image associated with one or more target objects, wherein the first image is generated by a first scan; Acquire a first radiation therapy plan for treating the one or more target objects, wherein the first radiation therapy plan is associated with the first image; Acquire a second image associated with the one or more target objects, the second image being generated by a second scan performed later than the first scan; as well as The plan determination module is configured as determining one or more regions of interest in the second image, and dividing the one or more determined regions of interest into at least two groups; generating a first intermediate plan by updating the first radiation therapy plan based on the one or more determined regions of interest; updating the first intermediate plan by performing at least two iterations; as well as The intermediate plan generated in the last iteration of the at least two iterations is determined as a target radiation therapy plan for treating the one or more target objects.

10. A non-transitory computer readable medium comprising at least one set of instructions for generating an adaptive radiation therapy plan, wherein when executed by one or more processors of a computing device, the at least one set of instructions causes the computing device to perform a method comprising: Acquire a first image associated with one or more target objects, wherein the first image is generated by a first scan; Acquire a first radiation therapy plan for treating the one or more target objects, wherein the first radiation therapy plan is associated with the first image; Acquire a second image associated with the one or more target objects, the second image being generated by a second scan performed later than the first scan; determining one or more regions of interest in the second image, and dividing the one or more determined regions of interest into at least two groups; generating a first intermediate plan by updating the first radiation therapy plan based on the one or more determined regions of interest; updating the first intermediate plan by performing at least two iterations; as well as The intermediate plan generated in the last iteration of the at least two iterations is determined as a target radiation therapy plan for treating the one or more target objects.

Images