阅读说明：本技术 放疗剂量确定系统 (Radiation therapy dose determination system ) 是由 刘艳芳 韩华杰 于 2021-08-30 设计创作，主要内容包括：本说明书实施例公开了一种放疗剂量确定系统。所述系统包括处理器,所述处理器用于执行以下方法：获取放射源相关数据、目标对象在目标放疗时刻的放疗辅助图像,以及所述目标放疗时刻对应的初始通量图；至少基于所述放疗辅助图像、所述初始通量图以及所述放射源相关数据,利用一次或多次迭代确定对应于所述目标放疗时刻的；获取所述目标对象的目标扫描图像；以及基于所述目标通量图,所述目标扫描图像以及所述放射源相关数据,确定所述目标对象在所述目标放疗时刻所接收的放疗剂量。(The embodiment of the specification discloses a radiotherapy dose determining system. The system includes a processor for performing the method of: acquiring relevant data of a radioactive source, a radiotherapy auxiliary image of a target object at a target radiotherapy time and an initial flux map corresponding to the target radiotherapy time; determining, with one or more iterations, a time corresponding to the target radiotherapy treatment based at least on the radiotherapy auxiliary images, the initial flux map, and the radiation source-related data; acquiring a target scanning image of the target object; and determining the radiotherapy dose received by the target object at the target radiotherapy time based on the target flux map, the target scanning image and the related data of the radioactive source.)

1. A radiation therapy dose determination system, wherein the system comprises a processor for performing the method of:

acquiring relevant data of a radioactive source, a radiotherapy auxiliary image of a target object at a target radiotherapy time and an initial flux map corresponding to the target radiotherapy time;

determining a target flux map corresponding to a time of the target radiotherapy with one or more iterations based at least on the radiotherapy-assisted image, the initial flux map, and the radiation source-related data;

acquiring a target scanning image of the target object; and

and determining the radiotherapy dose received by the target object at the target radiotherapy time based on the target flux map, the target scanning image and the related data of the radioactive source.

2. The system of claim 1, wherein one iteration comprises:

acquiring object information of the target object;

determining a radiotherapy predicted image in the current iteration round based on the related data of the radioactive source, a current flux map corresponding to the current iteration round and the object information;

determining whether the corrected radiotherapy auxiliary image and the radiotherapy predicted image in the current iteration turn meet a first judgment condition;

responding to the corrected radiotherapy auxiliary image and the radiotherapy predicted image in the current iteration turn to meet the first judgment condition, and determining the current flux map corresponding to the current iteration turn as the target flux map; and

and in response to the corrected radiotherapy auxiliary image and the radiotherapy predicted image in the current iteration turn not meeting the first judgment condition, updating the current flux map corresponding to the current iteration turn, and taking the current flux map corresponding to the current iteration turn after updating as the current flux map corresponding to the next iteration turn.

3. The system of claim 2, wherein the updating the current traffic map corresponding to the current iteration turn comprises:

determining a first difference between the corrected radiotherapy auxiliary image and the radiotherapy predicted image in the current iteration turn; and

and updating the current flux map corresponding to the current iteration turn based on the first difference.

4. The system of claim 2, wherein one iteration comprises:

acquiring object information of the target object;

determining a main ray prediction image and a scattering ratio value in the current iteration turn based on the related data of the radioactive source, a current flux map corresponding to the current iteration turn and the object information, wherein the current flux map corresponding to the first iteration turn is the initial flux map;

determining a de-scattering reference image in the current iteration turn based on the scattering ratio and the corrected radiotherapy auxiliary image;

determining whether the de-scattering reference image and the main ray prediction image in the current iteration turn meet a second judgment condition;

determining a current flux map corresponding to the current iteration turn as the target flux map in response to the fact that the de-scattering reference image and the main ray prediction image in the current iteration turn meet the second judgment condition; and

and in response to that the de-scattering reference image and the main ray prediction image in the current iteration turn do not meet the second judgment condition, updating the current flux map corresponding to the current iteration turn, and taking the current flux map corresponding to the current iteration turn after updating as the current flux map corresponding to the next iteration turn.

5. The system of claim 4, wherein the updating the current traffic map corresponding to the current iteration turn comprises:

determining a second difference between the de-scattered reference image and the main-ray predicted image in the current iteration round; and

and updating the current flux map corresponding to the current iteration turn based on the second difference.

6. The system of claim 4, wherein the second determination condition comprises:

the primary ray predicted image in the current iteration round converges to the de-scattered reference image in the current iteration round.

7. The system of claim 1, wherein said acquiring a target scan image of said target object comprises:

acquiring a plurality of scanning images of the target object, wherein the plurality of scanning images are sequence images respectively corresponding to a plurality of phases;

determining the target scan image from the plurality of scan images based on the radiotherapy-assisted image.

8. The system of claim 7, wherein the plurality of scan images comprise 4D-CT images acquired based on a 4D computed tomography imaging device (Four-dimensional-computed tomography) or online 4D-CT images.

9. The system of claim 7, wherein the determining the target scan image from the plurality of scan images based on the radiotherapy-assisted image comprises:

determining a plurality of predicted phase images corresponding to the plurality of phases respectively when the target object is at the target radiotherapy time from the plurality of scanning images;

determining an adapted image of the radiotherapy-assisted image from the plurality of predicted phase images; and

and determining a target phase corresponding to the adaptive image, and designating a scanning image corresponding to the target phase as the target scanning image.

10. The system of claim 9, wherein the determining a plurality of predicted phase images corresponding to the plurality of phases, respectively, comprises:

acquiring radiotherapy plan information;

determining planned beam-out information at the target radiotherapy time based on the radiotherapy plan information, wherein the planned beam-out information comprises beam-out angles and subfield parameters corresponding to each beam-out angle; and

for each of the plurality of phases, determining a predicted phase image corresponding to the phase based on the planned out beam information and the scan image corresponding to the phase.

11. The system of claim 1, wherein the processor-implemented method further comprises:

traversing radiotherapy doses received by the target object at a plurality of radiotherapy moments corresponding to a plurality of beam angles in one radiotherapy, and determining a total radiotherapy dose received by the target object in the radiotherapy.

12. The system of any one of claims 1-11, wherein the radiotherapy-assisted image comprises an EPID (Electronic Portal Imaging Device) image.

13. A radiation therapy dose determination system, wherein the system comprises:

the first acquisition module is used for acquiring relevant data of a radioactive source, a radiotherapy auxiliary image of a target object at a target radiotherapy time and an initial flux map corresponding to the target radiotherapy time;

a first determining module for determining a target flux map corresponding to the target radiotherapy time with one or more iterations based on at least the radiotherapy auxiliary image, the initial flux map and the radiation source related data;

the second acquisition module is used for acquiring a target scanning image of the target object; and

a second determining module, configured to determine, based on the target flux map, the target scan image and the data related to the radiation source, a radiation therapy dose received by the target object at the target radiation therapy time.

14. A computer-readable storage medium, wherein the storage medium stores computer instructions, and when the computer instructions in the storage medium are read by a computer, the computer performs the method performed by a processor in the radiation therapy dose determination system according to claims 1-12.

Technical Field

The specification relates to the field of medical radiation, in particular to a radiotherapy dose determining system.

Background

In the radiotherapy process, the radiation dose distribution needs to be calculated, and the radiotherapy is carried out on the patient according to the determined and calculated radiation dose. The accuracy of the calculated radiation dose distribution influences the evaluation of the effect of the radiotherapy treatment, whereby the calculation of the radiation dose distribution is particularly important. Thus, there is a need for a radiation therapy dose determination method that accurately reconstructs the true three-dimensional dose that the patient receives during treatment.

Disclosure of Invention

One embodiment of the present specification provides a radiation therapy dose determination system. The system includes a processor for performing the method of: acquiring relevant data of a radioactive source, a radiotherapy auxiliary image of a target object at a target radiotherapy time and an initial flux map corresponding to the target radiotherapy time; determining, with one or more iterations, a time corresponding to the target radiotherapy treatment based at least on the radiotherapy auxiliary images, the initial flux map, and the radiation source-related data; acquiring a target scanning image of the target object; and determining the radiotherapy dose received by the target object at the target radiotherapy time based on the target flux map, the target scanning image and the related data of the radioactive source.

One embodiment of the present specification provides a radiation therapy dose determination system. The system comprises: the first acquisition module is used for acquiring relevant data of a radioactive source, a radiotherapy auxiliary image of a target object at a target radiotherapy time and an initial flux map corresponding to the target radiotherapy time; a first determining module for determining a target flux map corresponding to the target radiotherapy time with one or more iterations based on at least the radiotherapy auxiliary image, the initial flux map and the radiation source related data; the second acquisition module is used for acquiring a target scanning image of the target object; and a second determining module, configured to determine, based on the target flux map, the target scan image and the data related to the radiation source, a radiation therapy dose received by the target object at the target radiation therapy time.

One of the embodiments of the present specification provides a computer-readable storage medium, wherein the storage medium stores computer instructions, and when the computer instructions in the storage medium are read by a computer, the computer executes the radiotherapy dose determination method executed by the processor.

Drawings

The present description will be further explained by way of exemplary embodiments, which will be described in detail by way of the accompanying drawings. These embodiments are not intended to be limiting, and in these embodiments like numerals are used to indicate like structures, wherein:

FIG. 1 is a schematic diagram of an application scenario of a radiation therapy dose determination system according to some embodiments of the present disclosure;

FIG. 2 is an exemplary diagram of hardware and/or software components of an exemplary computing device according to some embodiments of the present description;

FIG. 3 is a block diagram of a radiation therapy dose determination system according to some embodiments of the present disclosure;

FIG. 4 is an exemplary flow chart of a method of radiation therapy dosage determination according to some embodiments herein;

FIG. 5 is an exemplary flow diagram of one iteration, according to some embodiments of the present description;

FIG. 6 is another exemplary flow diagram of an iteration, according to some embodiments of the present description;

FIG. 7 is an exemplary flow diagram illustrating acquisition of a target scan image of a target object according to some embodiments of the present description.

Detailed Description

In order to more clearly illustrate the technical solutions of the embodiments of the present disclosure, the drawings used in the description of the embodiments will be briefly described below. It is obvious that the drawings in the following description are only examples or embodiments of the present description, and that for a person skilled in the art, the present description can also be applied to other similar scenarios on the basis of these drawings without inventive effort. Unless otherwise apparent from the context, or otherwise indicated, like reference numbers in the figures refer to the same structure or operation.

It should be understood that "system", "device", "unit" and/or "module" as used herein is a method for distinguishing different components, elements, parts, portions or assemblies at different levels. However, other words may be substituted by other expressions if they accomplish the same purpose.

As used in this specification and the appended claims, the terms "a," "an," "the," and/or "the" are not intended to be inclusive in the singular, but rather are intended to be inclusive in the plural, unless the context clearly dictates otherwise. In general, the terms "comprises" and "comprising" merely indicate that steps and elements are included which are explicitly identified, that the steps and elements do not form an exclusive list, and that a method or apparatus may include other steps or elements.

Flow charts are used in this description to illustrate operations performed by a system according to embodiments of the present description. It should be understood that the preceding or following operations are not necessarily performed in the exact order in which they are performed. Rather, the various steps may be processed in reverse order or simultaneously. Meanwhile, other operations may be added to the processes, or a certain step or several steps of operations may be removed from the processes.

Some embodiments of the present disclosure provide a radiotherapy dose determination system, which may iteratively calculate the emergent flux of an accelerator from a measured EPID image in combination with related parameters of a radioactive source, and finally accurately reconstruct the true three-dimensional dose received by a patient during a treatment process, thereby greatly simplifying a calculation model and improving calculation accuracy.

Figure 1 is a schematic diagram of an application scenario of a radiation therapy dose determination system according to some embodiments of the present disclosure.

In some embodiments, the radiation therapy dose determination system 100 may be applied to a medical system platform. For example, the radiation therapy dose determination system 100 may determine the true dose received by a radiation therapy subject (e.g., a patient) during radiation therapy. For example, the radiation therapy dose determination system 100 may determine a true dose received by a radiation therapy subject (e.g., a patient) using auxiliary medical images acquired during radiation therapy. As shown in fig. 1, the radiation therapy dose determination system 100 may include a radiation therapy device 110, a network 120, a processing device 130, a terminal 140, and a storage device 150. The various components of radiation therapy dosimetry system 100 may be interconnected by a network 120. For example, the processing device 130 and the radiation therapy device 110 may be connected or in communication via the network 120.

The radiation therapy device 110 can deliver a beam of radiation to a target object (e.g., a patient or phantom). In some embodiments, the radiation therapy device 110 can include a linear accelerator (also referred to as a linac) 111. Linear accelerator 111 may generate and emit a radiation beam (e.g., an X-ray beam) from treatment head 112. The radiation beam may pass through one or more specially shaped collimators (e.g., a multi-leaf grating) and be delivered to a target object. In some embodiments, the radiation beam may comprise electrons, photons, or any other type of radiation. In some embodiments, the radiation beam exhibits an energy in the megavolt range (i.e., >1MeV), and thus may be referred to as a megavolt radiation beam. The treatment head 112 may be mounted in coupling relation to the frame 113. The gantry 113 may rotate, for example, clockwise or counterclockwise about a gantry rotation axis 114. The treatment head 112 may rotate with the gantry 113. In some embodiments, the radiation therapy device 110 can include an imaging assembly 115. The imaging assembly 115 may receive a beam of radiation that traverses a target object and may acquire projection images of a patient or phantom before, during, and/or after a radiation therapy or correction procedure. The imaging component 115 may include an analog detector, a digital detector, or any combination thereof. The imaging assembly 115 may be attached to the frame 113 in any manner and/or include a telescoping housing. Accordingly, the rotating gantry 113 can cause the treatment head 112 and the imaging assembly 115 to rotate in synchronization. In some embodiments, the Imaging assembly 115 may include an Electronic Portal Imaging Device (EPID). In some embodiments, the radiation therapy device 110 may also include a couch 116. The couch 116 may support a patient during radiotherapy or imaging, and/or a phantom during calibration of the radiotherapy apparatus 110. The bed board 116 can be adjusted according to different application scenarios.

Network 120 may include any suitable network capable of facilitating the exchange of information and/or data for radiation therapy dosimetry system 100. The data and/or information may include one or more radiotherapy auxiliary images that the radiotherapy apparatus 110 sends to the processing apparatus 130. For example, the processing device 130 may obtain radiotherapy-assisted images (such as EPID images) determined by the imaging component 115 from the radiotherapy device 110 via the network 120. As another example, processing device 130 may obtain user (e.g., physician) instructions from terminal 140 via network 120. In some embodiments, network 120 may be any type of wired or wireless network. For example, network 120 may include a cable network, a wired network, a fiber optic network, a telecommunications network, an intranet, the internet, a Local Area Network (LAN), a Wide Area Network (WAN), a wireless area network (WLAN), a Metropolitan Area Network (MAN), a Public Switched Telephone Network (PSTN), a bluetooth network, a ZigBEE network, a Near Field Communication (NFC) network, an ultra-wideband (UWB) network, a mobile communication (1G, 2G, 3G, 4G, 5G) network, a narrowband internet of things (NB-IoT), an infrared communication network, and the like, or any combination thereof. In some embodiments, network 120 may include one or more network access points. For example, network 120 may include wired or wireless network access points, such as base stations and/or Internet switching points 120-1, 120-2, …, through which one or more components of radiation therapy dosage determination system 100 may connect to network 120 to exchange data and/or information.

The terminal 140 may be in communication with and/or connected to the radiation treatment device 110, the processing device 130, and/or the storage device 150. For example, the terminal 140 may obtain a dose determination result during radiation therapy from the processing device 130. As another example, the terminal 140 may obtain images (e.g., radiotherapy-assisted images) acquired by the radiation therapy device 110 and transmit the images to the processing device 130 for processing. In some embodiments, the terminal 140 may include a mobile device 140-1, a tablet computer 140-2, a laptop computer 140-3, a desktop computer 140-4, and the like, or any combination thereof. For example, the mobile device 140-1 may include a mobile phone, a Personal Digital Assistant (PDA), a gaming device, a navigation device, and the like, or any combination thereof. In some embodiments, the terminal 140 may include an input device, an output device, and the like. The input devices may include alphanumeric and other keys. The input device may be selected from keyboard input, touch screen (e.g., with tactile or haptic feedback) input, voice input, eye tracking input, brain monitoring system input, or any other similar input mechanism. Input information received via the input device may be transmitted, for example, via the bus, to the processing device 130 for further processing. Other types of input devices may include cursor control devices such as a mouse, a trackball, or cursor direction keys, among others. Output devices may include a display, speakers, printer, or the like, or any combination thereof. In some embodiments, the terminal 140 may be part of the processing device 130. In some embodiments, the terminal 140 and the processing device 130 may be integrated as a control device, e.g., a console, of the radiation therapy device 110. In some embodiments, the terminal 140 may be omitted.

Storage device 150 may store data, instructions, and/or any other information. In some embodiments, the storage device 150 may store information that the user controls the behavior of the radiation therapy device 110. In some embodiments, the storage device 150 may store data obtained from the radiation therapy device 110, the terminal 140, and/or the processing device 130. In some embodiments, storage device 150 may store data and/or instructions for use by processing device 130 in performing or using the example methods described in this application. In some embodiments, the storage device 150 may include mass storage, removable storage, volatile read-write memory, read-only memory (ROM), and the like, or any combination thereof. Exemplary mass storage devices may include magnetic disks, optical disks, solid state disks, and the like. Exemplary removable memory may include flash drives, floppy disks, optical disks, memory cards, compact disks, magnetic tape, and the like. Exemplary volatile read and write memories can 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), zero capacitance random access memory (Z-RAM), and the like. Exemplary read-only memories may include mask read-only memory (MROM), programmable read-only memory (PROM), erasable programmable read-only memory (EPROM), electrically erasable programmable read-only memory (EEPROM), compact disc read-only memory (CD-ROM), digital versatile disc read-only memory (dvd-ROM), and the like. In some embodiments, the storage device 150 may be implemented on a cloud platform.

In some embodiments, a storage device 150 may be connected to the network 120 to communicate with at least one other component (e.g., processing device 130, terminal 140) in the radiation therapy dose determination system 100. At least one component of the radiation therapy dosage determination system 100 may access data or instructions stored in the storage device 150 via the network 120. In some embodiments, the storage device 150 may be part of the processing device 130.

In some embodiments, the radiation therapy dose determination system 100 may also include one or more power sources (not shown in figure 1) connected to one or more components of the radiation therapy dose determination system 100 (e.g., the processing device 130, the radiation therapy device 110, the terminal 140, the storage device 150, etc.).

It should be noted that the foregoing description is provided for illustrative purposes only, and is not intended to limit the scope of the present application. Many variations and modifications will occur to those skilled in the art in light of the teachings herein. The features, structures, methods, and other features of the example embodiments described herein may be combined in various ways to obtain additional and/or alternative example embodiments. For example, the storage device 150 may be a data storage device comprising a cloud computing platform, such as a public cloud, a private cloud, a community and hybrid cloud, and the like. However, such changes and modifications do not depart from the scope of the present application.

FIG. 2 is an exemplary diagram of hardware and/or software components of an exemplary computing device according to some embodiments of the present description.

Computing device 200 may include a processor 210, memory 220, input/output (I/O)230, and communication ports 240.

The processor 210 may execute computer instructions (e.g., program code) and perform the functions of the processing device 130 according to the methods described herein. The computer instructions may include, for example, conventional methods, procedures, objects, components, data structures, procedures, modules, and functions that perform the specified functions described herein. For example, the processor 210 may process data of the radiation therapy device 110, the terminal 140, the storage device 150, and/or any other component in the radiation therapy dose determination system 100. In some embodiments, processor 210 may include at least one hardware processor, such as a microcontroller, microprocessor, Reduced Instruction Set Computer (RISC), Application Specific Integrated Circuit (ASIC), application specific instruction set processor (ASIP), Central Processing Unit (CPU), Graphics Processing Unit (GPU), Physical Processing Unit (PPU), microcontroller unit, Digital Signal Processor (DSP), Field Programmable Gate Array (FPGA), higher order RISC machine (ARM), Programmable Logic Device (PLD), any circuit or processor capable of performing at least one function, or the like, or any combination thereof.

For purposes of illustration only, only one processor is depicted in computing device 200. However, it should be noted that the computing device 200 in the present application may also comprise multiple processors, whereby operations and/or method steps described in the present application as being performed by one processor may also be performed by multiple processors, jointly or separately. For example, if in the present application, the processors of computing device 200 perform operations a and B, it should be understood that operations a and B may also be performed by multiple different processors in computing device 200, collectively or individually (e.g., a first processor performing operation a and a second processor performing operation B, or a first processor and a second processor performing operations a and B collectively).

Memory 220 may store data/information obtained from radiation treatment device 110, terminal 140, storage device 150, and/or any other component in radiation therapy dose determination system 100. In some embodiments, memory 220 may include mass storage, removable storage, volatile read-write memory, read-only memory (ROM), the like, or any combination thereof. For example, mass storage may include magnetic disks, optical disks, solid state drives, and the like. Removable memory may include flash drives, floppy disks, optical disks, memory cards, compact disks, magnetic tape, and the like. Volatile read and write memory can include Random Access Memory (RAM). RAM may include Dynamic RAM (DRAM), double-data-rate synchronous dynamic RAM (DDRSDRAM), Static RAM (SRAM), thyristor RAM (T-RAM), zero-capacitance (Z-RAM), and the like. Exemplary read-only memories may include mask read-only memory (MROM), programmable read-only memory (PROM), erasable programmable read-only memory (EPROM), electrically erasable programmable read-only memory (EEPROM), compact disc read-only memory (CD-ROM), digital versatile disc read-only memory (dvd-ROM), and the like. In some embodiments, memory 220 may store at least one program and/or instructions for performing the example methods described herein.

Input/output (I/O)230 may be used to input and/or output signals, data, information, and the like. In some embodiments, input/output (I/O)230 may enable a user to interact with processing device 130. In some embodiments, input/output (I/O)230 may include an input device and an output device. Exemplary input devices may include a keyboard, mouse, touch screen, microphone, etc., or any combination thereof. Exemplary output devices may include a display device, speakers, printer, projector, etc., or any combination thereof. Exemplary display devices may include Liquid Crystal Displays (LCDs), Light Emitting Diode (LED) based displays, flat panel displays, curved displays, television devices, cathode ray tubes, and the like, or any combination thereof.

The communication port 240 may be connected to a network (e.g., network 120) to facilitate data communication. The communication port 240 may establish a connection between the processing device 130 and the radiation treatment device 110, the terminal 140, and/or the storage device 150. The connection may include a wired connection, a wireless connection. The wired connection may include, for example, an electrical cable, an optical cable, a telephone line, etc., or any combination thereof. The wireless connection may include, for example, a Bluetooth link, a Wi-FiTM link, a WiMax link, a WLAN link, a ZigBEE link, a mobile network link (e.g., 3G, 4G, 5G, etc.), and the like, or any combination thereof. In some embodiments, the communication port 240 may be and/or include a standardized communication port, such as RS232, RS485, and the like. In some embodiments, the communication port 240 may be a specially designed communication port. For example, the communication port 240 may be designed in accordance with the digital imaging and communications in medicine (DICOM) protocol.

FIG. 3 is a block diagram of an exemplary processing device, shown in accordance with some embodiments of the present description.

As shown in fig. 3, the processing device 130 may include a first obtaining module 310, a first determining module 320, a second obtaining module 330, and a second determining module 340.

The first acquiring module 310 may be configured to acquire data related to a radiation source, a radiotherapy auxiliary image of a target object at a target radiotherapy time, and an initial flux map corresponding to the target radiotherapy time. The radiation source-related data may be used to specify parameters of the device and/or components associated with radiation delivery. The apparatus and/or assembly may include a radiation source, an accelerator, a collimator, and the like. Exemplary parameters may include ray energy, beam spot size, collimator physical parameters such as leaf length of a multi-leaf grating, leaf thickness, range of motion, etc. The radiotherapy-assisted images may include medical images derived by an imaging assembly of the radiotherapy apparatus based on data generated by received radiation that has passed through the target object while radiotherapy is being performed. The radiotherapy-assisted image may comprise an EPID image. In some embodiments, the initial flux map corresponding to the target radiotherapy time may be a preset image. For example, the initial flux map may be an arbitrary piece of medical image. As another example, the initial flux map may be an image obtained by processing data received by the imaging assembly after the radiation therapy device transmits radiation through the phantom.

The first determination module 320 may be configured to determine a target flux map corresponding to a time instant of the target radiotherapy using one or more iterations based on at least the radiotherapy auxiliary images, the initial flux map, and the radiation source-related data. The target flux map may be an image reflecting information on the state of the radiation source at the time of the target radiotherapy. The first determining module 320 may determine the final target flux map by simulating, for example, the physical motion process of the ray particles through an iterative simulation. The first determination module 320 may iteratively determine and update the flux map in one or more iterations. Each iteration may be a simulation and process of updating the flux map. In some embodiments, the first determining module 320 may correct the radiotherapy auxiliary images to obtain corrected radiotherapy auxiliary images, and determine a target flux map corresponding to a target radiotherapy time using one or more iterations based on the corrected radiotherapy auxiliary images, the initial flux map, and the radiation source-related data. In some embodiments, the correction may include dead pixel correction, dark current correction, gain correction, geometry correction, and the like, or any combination thereof.

In some embodiments, at each of the one or more iterations, the first determination module 320 may obtain object information for the target object and determine a predicted radiotherapy image in the current iteration based on the radiation source-related data, the current flux map corresponding to the current iteration, and the object information. The object information of the target object may include scanned image information of the target object. Exemplary scan image information may include CR image information, DR image information, CT image information, MRI image information, PET image information, and the like, or any combination thereof. In some embodiments, the subject information may be pre-acquired prior to the target radiotherapy session. In some embodiments, the first determining module 320 may determine the radiotherapy prediction image in the current iteration round by using a Monte Carlo Method (Monte Carlo Method) based on the radiation source related data, the current flux map corresponding to the current iteration round, and the object information.

In some embodiments, the first determination module 320 may determine whether the corrected radiotherapy auxiliary image and the radiotherapy predicted image in the current iteration turn satisfy the first judgment condition. The first judgment condition may include convergence of the radiotherapy predicted image in the current iteration turn to the corrected radiotherapy auxiliary image. The convergence may refer to that a difference between the radiotherapy predicted image in the current iteration round and the corrected radiotherapy auxiliary image is smaller than a preset threshold. The difference may be related to the difference between the pixel values of corresponding pixels in the two images. In response to that the corrected radiotherapy auxiliary image and the radiotherapy predicted image in the current iteration round satisfy the first judgment condition, the first determining module 320 may determine that the current flux map corresponding to the current iteration round is the target flux map. In response to that the corrected radiotherapy auxiliary image and the radiotherapy predicted image in the current iteration round do not satisfy the first judgment condition, the first determining module 320 may update the current flux map corresponding to the current iteration round, and use the current flux map corresponding to the current iteration round as the current flux map corresponding to the next iteration round. The first determination module 320 can determine a first difference between the corrected radiotherapy auxiliary image and the radiotherapy predictive image in the current iteration round. The first difference may be a first difference matrix between a first matrix representing the corrected radiotherapy auxiliary image and a second matrix representing the radiotherapy predicted image in the current iteration round. The first determination module 320 may update the current traffic map corresponding to the current iteration turn based on the first difference.

In some embodiments, at each of the one or more iterations, the first determination module 320 can obtain object information for the target object and determine a chief ray prediction image and a scatter ratio value in a current iteration turn based on the radiation source-related data, a current flux map corresponding to the current iteration turn, and the object information. The primary ray prediction image may be an image formed by primary ray particles after removing scattering particles from the beam. The scatter ratio may be a ratio between the amount of scattered particles and the amount of primary ray particles. In some embodiments, the first determination module 320 may determine the chief ray prediction image and the scatter ratio value in the current iteration round based on the radiation source-related data, the current flux map corresponding to the current iteration round, and the object information using a Monte Carlo Method (Monte Carlo Method).

In some embodiments, the first determination module 320 may determine the backscatter reference image in the current iteration round based on the scatter ratio and the corrected radiotherapy auxiliary image, and determine whether the backscatter reference image and the primary-ray prediction image in the current iteration round satisfy the second determination condition. The backscatter reference image may be an image determined by the primary particles in the actual dose captured by the detection assembly of the radiotherapy apparatus at the time of the target radiotherapy. The second determination condition may include that the primary ray prediction image in the current iteration round converges to the backscatter reference image in the current iteration round. The convergence may refer to that a difference between the main-ray predicted image in the current iteration round and the de-scattered reference image in the current iteration round is less than a preset threshold. The difference may refer to a difference between pixel values of corresponding pixels in the two images. In response to the second determination condition being satisfied by the de-scattered reference image and the primary ray prediction image in the current iteration round, the first determination module 320 may determine that the current flux map corresponding to the current iteration round is the target flux map. In response to that the de-scattered reference image and the main-ray predicted image in the current iteration turn do not satisfy the second determination condition, the first determining module 320 may update the current flux map corresponding to the current iteration turn, and use the updated current flux map corresponding to the current iteration turn as the current flux map corresponding to the next iteration turn. In some embodiments, the first determination module 320 may determine a second difference between the backscatter reference image and the primary ray prediction image in the current iteration round. The second difference may be a second difference matrix between a third matrix representing the de-scattered reference image in the current iteration round and a fourth matrix representing the primary ray predicted image in the current iteration round. The first determination module 320 may update the current traffic map corresponding to the current iteration turn based on the second difference.

The second acquisition module 330 may be used to acquire a target scan image of the target object. In some embodiments, the second acquiring module 330 may acquire a plurality of scan images of the target object before the target radiotherapy time and determine a plurality of predicted phase images of the target object corresponding to the plurality of phases respectively at the target radiotherapy time. The plurality of scan images may include a plurality of scan images reflecting different motion states of the target object in one or more autonomous motion cycles. The plurality of scan images may be pre-scan determined prior to the target radiotherapy treatment time. In some embodiments, the plurality of scan images may include a plurality of 4D-CT images acquired based on a 4D computed tomography (4D-CT) device. In some embodiments, the predicted phase image may refer to a predicted image that may reflect the state of the target object at the time of the target radiotherapy. To determine a plurality of predicted phase images corresponding to the plurality of phases, the second obtaining module 330 may obtain radiotherapy plan information and determine planned beam information at the time of the target radiotherapy based on the radiotherapy plan information. The planned beam information may include beam intensity, beam conformal shape, radiation dose, and the like. For each of the plurality of phases, the second obtaining module 330 may obtain information about the phase. The information about the phase may include state information or phase information of the target object at the phase. For example, the relevant information of the phase may include a phase of physiological motion (e.g., systolic phase, diastolic phase, etc. of cardiac motion) of the target object (e.g., patient, or organ or tissue of patient), a posture (e.g., lying down, lying on side, etc.) of the target object, a morphology, a body type, and the like. The second obtaining module 330 may determine a predicted phase image corresponding to the phase based on the planned out-beam information and the information related to the phase. For example, the second obtaining module 330 may obtain the predicted phase image by using a simulation method.

In some embodiments, the second acquisition module 330 may determine an adapted image of the radiotherapy-assisted image from the plurality of predicted phase images. The adapted image may refer to a predicted phase image closest to a radiotherapy auxiliary image corresponding to the target radiotherapy time instant. For example, the state of the target object displayed by the adapted image is closest to the state of the target object displayed by the radiotherapy-assisted image. In some embodiments, the second acquisition module 330 may determine an adapted image of the radiotherapy auxiliary image using a method of feature matching. For example, the second acquisition module 330 may compare a feature distribution (e.g., a gray distribution feature) of a plurality of predicted phase images with a gray distribution feature of the radiotherapy auxiliary image, and select a predicted phase image having a feature distribution closest to the gray distribution feature of the radiotherapy auxiliary image as the adapted image. In some embodiments, the second acquisition module 330 may determine first position information of the target tissue included in the radiotherapy-assisted image and second position information of the target tissue included in each of the plurality of predicted phase images. The target tissue may refer to a tissue of the target object that is discriminative. For example, a tumor region, or an organ. The second acquisition module 330 may determine an adapted image of the radiotherapy auxiliary image based on the first position information and the second position information. As an example, the second acquisition module 330 may compare the first position information and the second position information corresponding to each predicted phase image. When the first position information matches second position information corresponding to a certain predicted phase image, the second obtaining module 330 may determine the predicted phase image as the adapted image.

In some embodiments, the second acquisition module 330 may determine a third difference between the radiotherapy auxiliary image and each of the plurality of predicted phase images, respectively. The third difference may refer to a difference between a matrix representing the radiotherapy-assisted image and a matrix representing a predicted phase image. The second obtaining module 330 may determine a minimum value of the plurality of third differences, and designate a predicted phase image corresponding to the minimum value as the adapted image.

In some embodiments, the second obtaining module 330 may determine a target phase corresponding to the adapted image and designate a scan image corresponding to the target phase as the target scan image.

The second determination module 340 can be used for determining the radiotherapy dose received by the target object at the target radiotherapy time based on the target flux map, the target scan image and the radiotherapy source-related data. The second determination module 340 may determine the radiotherapy dose received by the target subject at the target radiotherapy time using Monte Carlo Method (Monte Carlo Method). In some embodiments, a plurality of physical processes (e.g., scattering, attenuation, etc.) of the ray particles in the target object may be simulated using the Monte Carlo method. As an example, the second determining module 340 may utilize a monte carlo method to simulate the transport process of the radiation particles, for example, after passing through the interior region of the target object reflected by the target scan image under the parameter conditions of the radiation delivery-related devices and/or components reflected by the radiation source-related data and the condition of the state of the radiation source reflected by the target flux map, to obtain the final dose distribution. Based on the dose distribution, the second determination module 340 may determine a radiation dose received by the target object at the target radiotherapy time instant.

In some embodiments, the processing device 130 may further include a third determination module (not shown in the figures). The third determination module may acquire radiotherapy doses received by the target object at a plurality of radiotherapy moments in a radiotherapy, and determine a total radiotherapy dose received by the target object in the radiotherapy based on the radiotherapy doses received at the plurality of radiotherapy moments.

With regard to the description of the above modules, reference may be made to the flow chart sections of the present application, e.g., fig. 4-7.

It should be understood that the system and its modules shown in FIG. 3 may be implemented in a variety of ways. For example, in some embodiments, the system and its modules may be implemented in hardware, software, or a combination of software and hardware. Wherein the hardware portion may be implemented using dedicated logic; the software portions may be stored in a memory for execution by a suitable instruction execution system, such as a microprocessor or specially designed hardware. Those skilled in the art will appreciate that the methods and systems described above may be implemented using computer executable instructions and/or embodied in processor control code, such code being provided, for example, on a carrier medium such as a diskette, CD-or DVD-ROM, a programmable memory such as read-only memory (firmware), or a data carrier such as an optical or electronic signal carrier. The system and its modules of the present application may be implemented not only by hardware circuits such as very large scale integrated circuits or gate arrays, semiconductors such as logic chips, transistors, or programmable hardware devices such as field programmable gate arrays, programmable logic devices, etc., but also by software executed by various types of processors, for example, or by a combination of the above hardware circuits and software (e.g., firmware).

It should be noted that the above descriptions of the candidate item display and determination system and the modules thereof are only for convenience of description, and are not intended to limit the present application within the scope of the illustrated embodiments. It will be appreciated by those skilled in the art that, given the teachings of the present system, any combination of modules or sub-system configurations may be used to connect to other modules without departing from such teachings. For example, the first obtaining module 310 and the second obtaining module 330 disclosed in fig. 3 may be different modules in a system, or may be a module that implements the functions of two or more modules. For example, each module may share one memory module, and each module may have its own memory module. Such variations are within the scope of the present application.

Figure 4 is an exemplary flow chart of a method for radiation therapy dose determination according to some embodiments of the present description. In some embodiments, the flow 400 may be performed by the processing device 130 shown in fig. 1. For example, the process 400 may be stored in the storage device 150 in the form of a program or instructions that, when executed, may implement the process 400. In some embodiments, the procedure 400 may be performed by the radiation therapy dose determination system 300. As shown in fig. 4, the process 400 may include the following steps.

Step 402, acquiring relevant data of a radioactive source, a radiotherapy auxiliary image of a target object at a target radiotherapy time, and an initial flux map corresponding to the target radiotherapy time. This step may be performed by the first acquisition module 310.

In some embodiments, the radiation source-related data may be used to account for parameters of devices and/or components related to radiation delivery. The apparatus and/or assembly may include a radiation source, an accelerator, a collimator, and the like. Exemplary parameters may include ray energy, beam spot size, collimator physical parameters such as leaf length of a multi-leaf grating, leaf thickness, range of motion, etc. In some embodiments, the radiation source related data may be acquired by calibration. By way of example, a phantom, such as a water phantom or a phantom, may be delivered with radiation therapy equipment, and the radiation source-related data determined from acquired phantom data (e.g., phantom thickness) and radiotherapy-assisted image data (e.g., EPID image data).

It is known that a target object (e.g., a cancer patient, a cancerous organ or tissue of a cancer patient, etc.) will determine a radiotherapy plan (TPS) before undergoing radiation therapy. The radiotherapy plan may account for detailed operation of the radiotherapy device (e.g., radiotherapy device 110) throughout the radiotherapy session. For example, a radiotherapy plan may specify a plurality of nodes (also referred to as control nodes), each of which may correspond to a time of day. The radiotherapy plan may show the rotation angle of the gantry 113, the position of the leaves of the multi-leaf grating and/or the tungsten door, the dose of radiation emitted by the linear accelerator 111, etc. at various times. The dose of radiation may be radiation delivered at a control node (e.g., a static intensity modulated type of radiation treatment) or radiation sustained between two control nodes (e.g., a dynamic intensity modulated type of radiation treatment). Therefore, based on the above description, the target radiotherapy time may be a time corresponding to a control node or a time between two control nodes. At this time, the radiotherapy apparatus (e.g., radiotherapy apparatus 110) starts the radiation delivery, or ends the radiation delivery.

In addition, the radiation is not completely absorbed after passing through the target object, but is attenuated and ultimately received by the imaging assembly (e.g., imaging assembly 115). The imaging component 115 may image the target object upon receiving the radiation. The medical images obtained can be used to assist in radiation therapy. For example, the pose of the target object may be confirmed or used to determine the true dose received by the target object at the time of radiation delivery. Accordingly, a medical image received by an imaging assembly (e.g., imaging assembly 115) and derived based on data generated by the received radiation after the radiation delivered by the radiation source (e.g., linear accelerator 111) at the time of radiotherapy passes through the target object may be referred to as the radiotherapy-assisted image.

In some embodiments, the radiotherapy-assisted images may comprise EPID images. For example, the Imaging assembly 115 may be an Electronic Portal Imaging Device (EPID). The detectors in the EPID may detect radiation that has passed through the target object and convert the detected radiation into electrical or digital signals (which may also be referred to as projection data). Based on the electrical or digital signals, an EPID image can be reconstructed.

The flux map can be understood as an image that reflects the state of the outgoing beam. For example, the flux map may reflect the position of the collimator (e.g., the position of the plurality of leaves in a multi-leaf grating), the beam intensity, and so on. In some embodiments, the initial flux map corresponding to the target radiotherapy time may be a preset image. For example, the initial flux map may be a preset CT image, or a CT image obtained by converting an image of another modality (e.g., a PET image, an MRI image, etc.). As another example, the initial flux map may be an image reconstructed from data received by the imaging assembly after the radiation therapy device transmits radiation beams through the phantom. Which may be pre-stored in a storage device (e.g., storage device 150). The first obtaining module 310 may communicate with the storage device 150 to obtain the initial flux map. In some embodiments, the initial flux map corresponding to the target radiotherapy time may be acquired based on a radiotherapy auxiliary image corresponding to the target radiotherapy time. For example, the first obtaining module 310 may obtain the initial flux map by normalizing the radiotherapy auxiliary image corresponding to the target radiotherapy time.

Step 404, determining a target flux map corresponding to the target radiotherapy time by one or more iterations based on at least the radiotherapy auxiliary image, the initial flux map and the radiation source related data. This step may be performed by the first determination module 320.

In some embodiments, the target flux map may be an image reflecting the relevant state information of the radiation source at the target radiotherapy time. It will be appreciated that the radiation beam, after passing through the target object, will be captured by a detection assembly of the radiation treatment apparatus (e.g., the imaging assembly 115 of the radiation treatment apparatus 110). The imaging component 115 may generate a corresponding image (e.g., the aforementioned radiotherapy-assisted image) based on the captured information. The radiotherapy auxiliary image reflects the radiation dose received by the imaging assembly 115. Based on parameters of the radiation delivery-related devices and/or components reflected by the radiation source-related data and the relevant state information of the radiation source reflected by the initial flux map, and/or other data (e.g., attenuation and/or absorption information as radiation passes through a target object), the first determination module 320 can determine the relevant state information of the radiation source at the target radiotherapy time. For example, the first determining module 320 may determine the final target flux map by simulating the physical movement process of the ray particles through an iterative simulation. The first determination module 320 may iteratively determine and update the flux map in one or more iterations. Each iteration may be a simulation and process of updating the flux map. And when the iteration is finished, the finally obtained flux map is used as the target flux map.

In some embodiments, the first determining module 320 may correct the radiotherapy auxiliary images to obtain corrected radiotherapy auxiliary images, and determine a target flux map corresponding to a target radiotherapy time using one or more iterations based on the corrected radiotherapy auxiliary images, the initial flux map, and the radiation source-related data. In some embodiments, the correction may include dead pixel correction, dark current correction, gain correction, geometry correction, and the like, or any combination thereof.

Step 406, a target scan image of the target object is acquired. This step may be performed by the second acquisition module 330.

In some embodiments, the target scan image may correspond to the target radiotherapy treatment time instant. The target scan image may be used to represent the state of the target object at the time of the target radiotherapy. In some embodiments, the target subject (e.g., patient) is itself voluntarily moving (e.g., physiological motion, such as heartbeat, respiration, etc.) during the radiation therapy session. Determining the state of the target object at the time of target radiotherapy (e.g., the state of fluctuation of the patient's chest due to breathing) has some guiding effect on radiotherapy. For example, variations in the motion of the patient's chest will affect the distribution of the dose within the patient, and the position of the target area may vary. Accordingly, the target scan image will be used in subsequent operations of procedure 400 (e.g., for determining radiation therapy dose).

In some embodiments, the state of the target object at the target radiotherapy time may be considered to substantially coincide with the state before radiotherapy, and therefore, the target scan image of the target object at the target radiotherapy time may be considered to be similar to the scan image of the target object before radiotherapy (i.e., the scan image of the target object before radiotherapy may be used as the target scan image of the target object corresponding to the target radiotherapy time). In some embodiments, the target scan image may be an image obtained by scanning the target object prior to the target radiotherapy treatment time. For example, the target object may be scanned and imaged prior to radiation therapy. And acquiring the target scan image from the acquired plurality of scan images. In some embodiments, the target scan image may be determined based on an X-ray imaging device (e.g., a Computed Radiography (CR), a Digital Radiography (DR), a Computed Tomography (CT), a mobile X-ray device such as a mobile C-arm machine, a digital subtraction angiography scanner (DSA), an Emission Computed Tomography (ECT), etc.). In some embodiments, the target scan image may be determined based on a CT imaging device.

In some embodiments, the second acquisition module 330 may acquire a plurality of scan images of the target object before radiotherapy is performed, or during the time of radiotherapy of the target. The plurality of scan images includes phase images of the target object at a plurality of phases. The second obtaining module 330 may determine predicted phase images of the target object corresponding to the plurality of phases at the target radiotherapy time, and determine an adapted image corresponding to the radiotherapy auxiliary image from the predicted phase images. The adapted image may refer to a predicted phase image closest to a radiotherapy auxiliary image corresponding to the target radiotherapy time instant. For example, the state of the target object displayed by the adapted image is closest to the state of the target object displayed by the radiotherapy-assisted image. In some embodiments, a difference between the radiotherapy auxiliary image and the adapted image corresponding to the radiotherapy auxiliary image is smaller than a preset value. The second obtaining module 330 may designate a phase image corresponding to a phase corresponding to the adapted image as the target scan image. For further description of obtaining the scan image of the target, reference may be made to fig. 7 of the present application, which is not repeated herein.

Step 408, determining the radiotherapy dose received by the target object at the target radiotherapy time based on the target flux map, the target scan image and the related data of the radioactive source. This step may be performed by the second determination module 340.

In some embodiments, the second determination module 340 may determine the radiotherapy dose received by the target subject at the target radiotherapy time using a Monte Carlo Method (Monte Carlo Method). In some embodiments, a plurality of physical processes (e.g., scattering, attenuation, etc.) of the ray particles in the target object may be simulated using the Monte Carlo method. As an example, the second determining module 340 may utilize a monte carlo method to simulate the transport process of the radiation particles, for example, after passing through the interior region of the target object reflected by the target scan image under the parameter conditions of the radiation delivery-related devices and/or components reflected by the radiation source-related data and the condition of the state of the radiation source reflected by the target flux map, to obtain the final dose distribution. Based on the dose distribution, the second determination module 340 may determine a radiation dose received by the target object at the target radiotherapy time instant.

In some embodiments, based on the same or similar process as described above, the processing device 130 (e.g., a third determining module, not shown in the figure) may acquire the radiotherapy doses received by the target object at a plurality of radiotherapy moments in a radiotherapy treatment, and determine the total radiotherapy dose received by the target object in the radiotherapy treatment based on the radiotherapy doses received at the plurality of radiotherapy moments. Each radiotherapy time may correspond to a gantry angle. The gantry angle may refer to the rotational angle of the gantry of the radiotherapy apparatus, which is indicated by the control nodes specified by the radiotherapy plan. The radiotherapy apparatus will deliver the radiation to the target object at each gantry angle, or continuously deliver the radiation within the angular range made up of two gantry angles. The processing device 130 may determine the radiotherapy doses received by the target object at each gantry angle and accumulate the radiotherapy doses to determine a total radiotherapy dose received by the target object during the radiotherapy treatment.

In some embodiments, the processing device 130 may traverse the treatment doses received by the target object at a plurality of radiation therapy moments corresponding to a plurality of beam angles in a single radiation therapy and determine the total radiation therapy dose received by the target object in the radiation therapy. It is understood that, in some embodiments, the processing device 130 may first calculate a plurality of radiotherapy doses respectively corresponding to a plurality of gantry angles in one radiotherapy, and then sum to obtain a total radiotherapy dose received by the target object in the radiotherapy. In some embodiments, the processing device 130 may sequentially calculate the radiotherapy dose corresponding to each gantry angle in one radiotherapy, and in the sequential calculation, sum the calculated radiotherapy doses corresponding to the gantry angles to finally obtain the radiotherapy total dose. For example, when two radiotherapy doses corresponding to two gantry angles are calculated, the two radiotherapy doses are summed, when a radiotherapy dose corresponding to a third gantry angle is calculated, the sum of the two radiotherapy doses acquired previously and the newly calculated radiotherapy dose are summed, and so on, until the radiotherapy doses corresponding to all gantry angles are calculated, and the total radiotherapy dose is obtained.

It should be noted that the above description related to the flow 400 is only for illustration and explanation, and does not limit the applicable scope of the present application. Various modifications and changes to flow 400 may occur to those skilled in the art in light of the teachings herein. However, such modifications and variations are intended to be within the scope of the present application.

FIG. 5 is an exemplary flow diagram of one iteration, shown in accordance with some embodiments of the present description. In some embodiments, the flow 500 may be performed by the processing device 130 shown in fig. 1. For example, flow 500 may be stored in storage device 150 in the form of a program or instructions that, when executed, may implement flow 500. In some embodiments, the procedure 500 may be performed by the radiation therapy dose determination system 300 (e.g., the first determination module 320). As shown in fig. 5, the process 500 may include the following steps.

Step 502, obtaining object information of the target object.

In some embodiments, the object information of the target object may include scanned image information of the target object. Exemplary scan image information may include CR image information, DR image information, CT image information, MRI image information, PET image information, and the like, or any combination thereof. In some embodiments, the subject information may be pre-acquired prior to the target radiotherapy session. For example, a CT scan is performed on the target object before the target radiotherapy time to acquire a CT image as object information of the target object. In some embodiments, the object information may be pre-stored in a storage device (e.g., storage device 150). The first determination module 320 may communicate with the storage device 150 to obtain the object information.

Step 504, determining a radiotherapy prediction image in the current iteration round based on the related data of the radioactive source, the current flux map corresponding to the current iteration round and the object information.

In some embodiments, the radiation therapy predictive image can be a predictive profile indicative of the plurality of particles comprising the radiation beam moving through a prediction pattern formed on a detection assembly (e.g., imaging assembly 115 of radiation treatment device 110). In some embodiments, the first determining module 320 may determine the radiotherapy prediction image in the current iteration round by using a Monte Carlo Method (Monte Carlo Method) based on the radiation source related data, the current flux map corresponding to the current iteration round, and the object information.

As an example, the first determination module 320 may simulate each particle in the radiation beam using a monte carlo method, through a transport process in an idle condition (e.g., no target object) and through a transport process of an interior region of the target object reflected by the object information under parametric conditions of devices and/or components related to radiation delivery reflected by the radiation source related data and under a state condition of the radiation source reflected by a current flux map corresponding to the current iteration. The particles in both cases can be captured by the detection assembly and reconstructed separately to obtain images. The ratio of the image intensities of the two images (e.g., in the idle condition versus passing the target object) may be referred to as a preset projection ratio. And multiplying the current flux map corresponding to the current round by the preset projection ratio to obtain the radiotherapy predicted image.

It will be appreciated that the process of determining the target flux map may be a process of multiple iterations. The corresponding flux map may be updated in each iteration. For example, the corresponding current flux map in the current round may be directly designated as the target flux map in the subsequent operations of the flow 500, or may be updated for the next iteration. Therefore, the current flux map corresponding to a certain iteration turn may be the flux map updated in the previous iteration turn. The current flux map corresponding to the first iteration turn may be the initial flux map.

Step 506, determining whether the corrected radiotherapy auxiliary image and the radiotherapy predicted image in the current iteration turn meet a first judgment condition.

In some embodiments, the first determination condition may include that the radiotherapy predicted image in the current iteration is converged to the corrected radiotherapy auxiliary image. The convergence may refer to that a difference between the radiotherapy predicted image in the current iteration round and the corrected radiotherapy auxiliary image is smaller than a preset threshold. The difference may be related to the difference between the pixel values of corresponding pixels in the two images. As an example, the difference may be represented using a matrix. For example, a value in the matrix may represent a difference between pixel values of the corresponding two pixels. The difference being smaller than the preset threshold may mean that a modulus of a matrix representing the difference or a characteristic value of the matrix is smaller than the preset threshold. The preset threshold may be predetermined or may be adjusted.

In some embodiments, when the corrected radiotherapy auxiliary image and the radiotherapy predicted image in the current iteration round satisfy the first determination condition (i.e., the radiotherapy predicted image in the current iteration round converges to the corrected radiotherapy auxiliary image), the process 500 proceeds to step 508. Otherwise, the process 500 proceeds to step 510.

And step 508, in response to that the corrected radiotherapy auxiliary image and the radiotherapy predicted image in the current iteration round satisfy the first judgment condition, determining that the current flux map corresponding to the current iteration round is the target flux map.

In some embodiments, when the corrected radiotherapy auxiliary image and the radiotherapy predicted image in the current iteration round satisfy the first determination condition, the first determining module 320 may determine that the current flux map corresponding to the current iteration round is the target flux map. This shows that the current flux map corresponding to the current iteration can better reflect the target radiotherapy time, and the relevant state information of the radioactive source can be used for the subsequent determination of radiotherapy dose.

And step 510, in response to that the corrected radiotherapy auxiliary image and the radiotherapy predicted image in the current iteration round do not satisfy the first judgment condition, updating the current flux map corresponding to the current iteration round, and taking the current flux map corresponding to the current iteration round after updating as the current flux map corresponding to the next iteration round.

In some embodiments, when the corrected radiotherapy auxiliary image and the radiotherapy predicted image in the current iteration round do not satisfy the first determination condition (i.e., the radiotherapy predicted image in the current iteration round does not converge on the corrected radiotherapy auxiliary image), the first determining module 320 may update the current flux map corresponding to the current iteration round.

In some embodiments, the first determination module 320 may determine a first difference between the corrected radiotherapy auxiliary image and the radiotherapy predictive image in the current iteration round. The first difference may be a first difference matrix between a first matrix representing the corrected radiotherapy auxiliary image and a second matrix representing the radiotherapy predicted image in the current iteration round. The first difference matrix may be a difference between the first matrix and the second matrix. For example, the second matrix is subtracted from the first matrix, or the first matrix is subtracted from the second matrix. The first difference matrix may also be a quotient between the first matrix and the second matrix. For example, it is obtained by multiplying the first matrix by the inverse of the second matrix, or by multiplying the second matrix by the inverse of the first matrix. In some embodiments, the first determination module 320 may update the current traffic map corresponding to the current iteration turn based on the first difference. As an example, the first determination module 320 may sum the current flux map corresponding to the current iteration turn with the difference matrix. For example, the first difference matrix is summed with a matrix representing a current traffic map corresponding to a current iteration round. And taking the image represented by the matrix obtained after summation as an updated flux map.

In some embodiments, the first determining module 320 may use the updated current traffic map corresponding to the current iteration turn as the current traffic map corresponding to the next iteration turn, and then enter the calculation of the next iteration turn, so that the process 500 may loop through one or more of the steps 504, 506, 508, 510. For example, in the next iteration round, step 504 may be executed again, that is, the updated traffic map is used as the current traffic map in step 504, and step 506, step 508 or step 510 corresponding to the next round is executed continuously.

It should be noted that the above description related to the flow 500 is only for illustration and explanation, and does not limit the applicable scope of the present application. Various modifications and changes to flow 500 may occur to those skilled in the art upon review of the present application. However, such modifications and variations are intended to be within the scope of the present application.

FIG. 6 is another exemplary flow diagram of an iteration in accordance with some embodiments of the present description. In some embodiments, flow 600 may be performed by processing device 130 shown in fig. 1. For example, flow 600 may be stored in storage device 150 in the form of a program or instructions that, when executed, may implement flow 600. In some embodiments, the procedure 600 may be performed by the radiation therapy dose determination system 300 (e.g., the first determination module 320). As shown in fig. 6, the process 600 may include the following steps.

Step 602, obtaining object information of the target object.

In some embodiments, step 602 is the same as or similar to step 502 in flow 500, and the detailed description about step 602 may refer to step 502, which is not repeated herein.

Step 604, determining a main ray prediction image and a scatter ratio value in the current iteration round based on the relevant data of the radiation source, the current flux map corresponding to the current iteration round and the object information. And the current flux map corresponding to the first iteration turn is the initial flux map.

In some embodiments, the primary ray prediction image may be an image formed from primary ray particles after removal of scattered particles from the beam. The scatter ratio may be a ratio between the amount of scattered particles and the amount of primary ray particles.

In some embodiments, the first determination module 320 may determine the chief ray prediction image and the scatter ratio value in the current iteration round based on the radiation source-related data, the current flux map corresponding to the current iteration round, and the object information using a Monte Carlo Method (Monte Carlo Method). As an example, the first determining module 320 may utilize a monte carlo method to simulate each particle in the radiation beam, and obtain the scatter image and the predicted chief ray image by performing a plurality of physical motion processes of an inner region of the target object reflected by the object under the parameter conditions of the device and/or component related to the radiation delivery reflected by the radiation source-related data and under the condition of the state of the radiation source reflected by the current flux map corresponding to the current iteration, and calculating the scattering specific gravity and the attenuation of the particle through the target object. The first determination module 320 may use a ratio between the scatter image and the primary ray prediction image as the scatter ratio. For example, the scattering ratio SPR_n(X，Y)＝S_n(X，Y)/P_n(X, Y). Where n is an integer greater than 0, indicating that it is currently in the second iteration, S_n(X, Y) denotes the scatter image in the current nth iteration, P_n(X, Y) denotes the current nth iterationPredict the image with the principal ray of (1).

Likewise, the process of determining the target flux map may be a multi-pass iterative process. The corresponding flux map may be updated in each iteration. For example, the corresponding current flux map in the current round may be directly designated as the target flux map in the subsequent operations of the flow 700, or may be updated for the next iteration. Therefore, the current flux map corresponding to a certain iteration turn may be the flux map updated in the previous iteration turn. The current flux map corresponding to the first iteration turn may be the initial flux map.

Step 606, determining a de-scatter reference image in the current iteration round based on the scatter ratio and the corrected radiotherapy auxiliary image.

In some embodiments, the backscatter reference image may be an image determined by primary particles in an actual dose captured by a detection assembly of the radiation treatment device (e.g., imaging assembly 115 of radiation treatment device 110) at the time of the target radiation therapy. In some embodiments, the first determination module 320 may determine the backscatter reference image using the following formula

Where n is an integer greater than 0, representing the current iteration, M (X, Y) represents the corrected radiotherapy-assisted image, SPR_n(X, Y) represents the scatter image in the current nth iteration.

Step 608, determining whether the de-scattered reference image and the main-ray predicted image in the current iteration meet a second judgment condition.

In some embodiments, the second determination condition may include that the primary ray prediction image in the current iteration round converges to the backscatter reference image in the current iteration round. The convergence may refer to that a difference between the main-ray predicted image in the current iteration round and the de-scattered reference image in the current iteration round is less than a preset threshold. The difference may refer to a difference between pixel values of corresponding pixels in the two images. As an example, the difference may be represented using a matrix. For example, a value in the matrix may represent a difference between pixel values of the corresponding two pixels. The difference being smaller than the preset threshold may mean that a modulus of a matrix representing the difference or a characteristic value of the matrix is smaller than the preset threshold. The preset threshold may be predetermined or may be adjusted.

In some embodiments, if the backscatter reference image and the primary ray prediction image in the current iteration pass satisfy the second determination condition, the process 600 proceeds to step 610. Otherwise, the process 600 proceeds to step 612.

Step 610, in response to that the de-scattering reference image and the main-ray predicted image in the current iteration round satisfy the second determination condition, determining that the current flux map corresponding to the current iteration round is the target flux map.

In some embodiments, when the de-scattered reference image and the primary ray prediction image in the current iteration pass satisfy the second determination condition, the first determining module 320 may determine that the current flux map corresponding to the current iteration pass is the target flux map. This shows that the current flux map corresponding to the current iteration can better reflect the target radiotherapy time, and the relevant state information of the radioactive source can be used for the subsequent determination of radiotherapy dose.

And step 612, in response to that the de-scattering reference image and the main-ray predicted image in the current iteration round do not meet the second judgment condition, updating the current flux map corresponding to the current iteration round, and taking the current flux map corresponding to the current iteration round after updating as the current flux map corresponding to the next iteration round.

In some embodiments, if the de-scattered reference image and the primary-ray prediction image in the current iteration round do not satisfy the second determination condition, the first determination module 320 may update the current flux map corresponding to the current iteration round.

In some embodiments, the first determination module 320 may determine a second difference between the backscatter reference image and the primary ray prediction image in the current iteration round. The second difference may be a second difference matrix between a third matrix representing the de-scattered reference image in the current iteration round and a fourth matrix representing the primary ray predicted image in the current iteration round. The second difference matrix may be a difference between the third matrix and the fourth matrix. For example, the fourth matrix is subtracted from the third matrix. The second difference matrix may also be a quotient between the third matrix and the fourth matrix. For example, the third matrix is multiplied by the inverse of the fourth matrix. In some embodiments, the first determination module 320 may update the current traffic map corresponding to the current iteration turn based on the second difference. As an example, the first determination module 320 may sum the current traffic map corresponding to the current iteration turn with the second difference matrix. For example, the second difference matrix is summed with a matrix representing a current flux map corresponding to the current iteration, and an image represented by the matrix obtained after summation is taken as an updated flux map.

It should be noted that the above description related to the flow 600 is only for illustration and explanation, and does not limit the applicable scope of the present application. Various modifications and changes to flow 600 may occur to those skilled in the art, given the benefit of this disclosure. However, such modifications and variations are intended to be within the scope of the present application.

As can be understood from the foregoing description of the flowchart, when determining the radiation dose at the target radiotherapy time, information of the target scan image corresponding to the target radiotherapy time is needed. The target scan image may reflect a state of the target object at the time of the target radiotherapy. In this case, the more accurate the state of the target object reflected by the target scan image is, the more accurate the result of the determined radiation dose is.

FIG. 7 is an exemplary flow diagram illustrating acquisition of a target scan image of a target object according to some embodiments of the present description. In some embodiments, flow 700 may be performed by processor 130 shown in fig. 1. For example, flow 700 may be stored in storage device 150 in the form of a program or instructions that, when executed, may implement flow 700. In some embodiments, the procedure 700 may be performed by the radiation therapy dose determination system 300 (e.g., the second acquisition module 330). As shown in fig. 7, the process 700 may include the following steps.

Step 702, acquiring a plurality of scan images of the target object, wherein the plurality of scan images are sequence images respectively corresponding to a plurality of phases.

In some embodiments, the plurality of scan images may include a plurality of scan images reflecting different motion states of the target object in one or more autonomous motion cycles. For example, the scan image may include a scan image of a chest of a lung cancer patient during various states of expiration, inspiration, and the like, during one or more breathing cycles. In this application, the state in which the target object is located may also be referred to as a phase. The plurality of scan images may correspond to different phases, respectively. The breathing cycle may be divided into a plurality of phases according to the breathing state, and the scan image may be a 4D image including a sequence of images distributed over time representing scan images corresponding to different phases within one breathing cycle.

In some embodiments, the plurality of scan images may be pre-scan determined prior to the target radiotherapy time instant. For example, the target object is scanned and imaged before one radiotherapy treatment which the target radiotherapy time belongs to is executed, so that the plurality of scanning images are obtained. For another example, the target object is scanned and imaged before one radiation therapy to which the target radiation therapy belongs is separated by a preset time period (for example, one week), so as to obtain the plurality of scanning images. Also for example, the target object may be periodically scan-imaged (e.g., once a week) to obtain the plurality of scan images. In some embodiments, the plurality of scan images may be scan images reconstructed from scan image data acquired one cycle most recent before a radiation therapy delivery to which the target radiation therapy belongs. For example, the plurality of scan images may be acquired prior to the beginning of the current treatment fraction. As another example, the plurality of scan images may be acquired online. The on-line acquisition can mean that after the patient is scanned to acquire an image, the patient can start treatment without leaving the bed board. It will be appreciated that the closer the time to treatment of the patient the acquired scan images are, the higher the accuracy, and thus, the more accurate the scan images may be acquired by acquiring multiple scan images on-line. Further, a plurality of scanning images can be obtained by on-line scanning for the patient, the images can be obtained when radiotherapy is about to start, in the process or just finished, the matching degree of the images and the state of the patient during radiotherapy is high, and therefore the dose reconstructed based on the images is more accurate.

In some embodiments, the plurality of scan images may include a plurality of 4D-CT images acquired based on a 4D computed tomography (4D-CT) device. Due to the fact that the time dimension is added to the 4D-CT, the states of the target object at all moments can be well reflected. The 4D-CT image reflects a more realistic state of the target object than the state of the target object reflected by the time-volume image acquired by conventional CT. Thus, the influence of the target object caused by the motion can be eliminated to a greater extent. Meanwhile, since the acquisition of the plurality of scan images can be performed before the radiotherapy is performed, the influence caused by the change of the posture (for example, the change of the body shape of the patient) and the positioning of the target object can be eliminated.

In some embodiments, a target scan image may be determined from a plurality of scan images based on a radiotherapy-assisted image. For example, step 704, step 706, and step 708 described below. In other embodiments, the target scan image may be determined from the plurality of scan images by a corresponding algorithm (e.g., a scan image processing method, etc.) based on the radiotherapy auxiliary images, which is not limited in this specification.

Step 704, determining a plurality of predicted phase images corresponding to the plurality of phases respectively when the target object is at the target radiotherapy time from the plurality of scanning images.

In some embodiments, the predicted phase image may refer to a predicted image that may reflect the state of the target object at the time of the target radiotherapy.

In some embodiments, to determine a plurality of predicted phase images corresponding to the plurality of phases, the second acquisition module 330 may acquire radiotherapy planning information. The radiotherapy planning information may be determined prior to radiation therapy delivery. For example, a radiotherapy plan of the target object is made using planning ct (planning ct), and radiotherapy plan information is determined. The radiotherapy planning information may include relevant state information of one or more treatment components of the radiotherapy device during radiotherapy. For example, the radiotherapy planning information may specify a plurality of control nodes, and each control node may correspond to a time instant. The radiotherapy planning information may include the status of various components of the planned radiotherapy device at each control node. Such as the rotation angle and speed of the gantry, the position and speed of movement of the collimator (e.g., multileaf grating) leaves and/or tungsten doors, the intensity/energy of the radiation emitted by the accelerator, the position of the couch, etc. Based on the radiotherapy planning information, the second acquisition module 330 may determine planned beam-out information for the target radiotherapy time instant. In the above description, the timing corresponding to the control node may be a radiotherapy timing. At which point the radiation therapy device can begin radiation delivery. Therefore, at the target radiotherapy time instant, the second acquisition module 330 may acquire the planned beam information from the radiotherapy plan information. The planned beam-exiting information may include beam-exiting angles and subfield parameters corresponding to each beam-exiting angle. In some embodiments, the computed beam information may also include beam current intensity, beam conformal shape, radiation dose, and the like.

In some embodiments, for each of the plurality of phases, the second acquisition module 330 may acquire information about the phase. The information about the phase may include state information or phase information of the target object at the phase. For example, the relevant information of the phase may include a phase of physiological motion (e.g., systolic phase, diastolic phase, etc. of cardiac motion) of the target object (e.g., patient, or organ or tissue of patient), a posture (e.g., lying down, lying on side, etc.) of the target object, a morphology, a body type, and the like. In some embodiments, the second acquisition module 330 may determine a predicted phase image corresponding to the phase based on the planned out beam information and the corresponding scan image of the phase. For example, the second obtaining module 330 may utilize a simulation method to simulate, based on the planned beam information, an initial state of each particle in the radiation when the imaging device delivers the radiation, and a physical motion process (e.g., scattering, attenuation, etc.) of the particle before and after passing through the target object, so as to obtain a state (e.g., energy, speed, motion direction, etc.) when each particle is finally captured by a detection assembly of the radiotherapy device and a distribution result of all particles. Based on the above data, the second acquisition module 330 may obtain the predicted phase image.

Step 706, determining an adapted image of the radiotherapy-assisted image from the plurality of predicted phase images.

In some embodiments, the adapted image may refer to a predicted phase image closest to a radiotherapy-assisted image corresponding to the target radiotherapy time instant. For example, the state of the target object displayed by the adapted image is closest to the state of the target object displayed by the radiotherapy-assisted image. In some embodiments, the second acquisition module 330 may determine an adapted image of the radiotherapy auxiliary image using a method of feature matching. For example, the second acquisition module 330 may compare a feature distribution (e.g., a gray distribution feature) of a plurality of predicted phase images with a gray distribution feature of the radiotherapy auxiliary image, and select a predicted phase image having a feature distribution closest to the gray distribution feature of the radiotherapy auxiliary image as the adapted image.

In some embodiments, the second acquisition module 330 may determine first position information of the target tissue included in the radiotherapy-assisted image and second position information of the target tissue included in each of the plurality of predicted phase images. The target tissue may refer to a tissue of the target object that is discriminative. For example, assuming that the target object is the chest of a lung cancer patient, the target tissue may be a tumor region, or a lung organ. The first position information may be used to represent the position of the target tissue in the radiotherapy-assisted image. Which may be represented using a range of coordinates. For example, the first position information may be represented by a coordinate range of a pixel point belonging to the target tissue in the radiotherapy auxiliary image in an image coordinate system. Similar to the first location information, the second location information may be used to represent the location of the target tissue in the predicted phase image. It may also be expressed using a range of coordinates. For example, the second position information may be represented using a coordinate range of a pixel point belonging to the target tissue in the predicted phase image in an image coordinate system.

In some embodiments, the second acquisition module 330 may determine an adapted image of the radiotherapy auxiliary image based on the first location information and the second location information. As an example, the second acquisition module 330 may compare the first position information and the second position information corresponding to each predicted phase image. When the first position information matches second position information corresponding to a certain predicted phase image (for example, a difference between coordinate ranges for indicating the first position information and the second position information is smaller than a preset range), the second obtaining module 330 may determine the predicted phase image as the adapted image.

In some embodiments, the second acquisition module 330 may determine a third difference between the radiotherapy auxiliary image and each of the plurality of predicted phase images, respectively. The third difference may refer to a difference between a matrix representing the radiotherapy-assisted image and a matrix representing a predicted phase image. For example, the third difference may be a matrix subtraction result of subtracting a matrix representing a predicted phase image from a matrix representing the radiotherapy auxiliary image. For another example, the third difference may be a matrix multiplication result obtained by multiplying a matrix representing the radiotherapy auxiliary image by an inverse matrix of a matrix representing the predicted phase image. The second obtaining module 330 may determine a minimum value of the plurality of third differences, and designate a predicted phase image corresponding to the minimum value as the adapted image. For example, the second obtaining module 330 may determine a modulus or an eigenvalue of a matrix subtraction result or a matrix multiplication result representing the third difference, and designate a predicted phase image corresponding to the smallest modulus or eigenvalue as the adapted image.

Step 708, determining a target phase corresponding to the adapted image, and designating a scanned image corresponding to the target phase as the target scanned image.

In some embodiments, since the adapted image is one of a plurality of predicted phase images respectively corresponding to a plurality of phases, after determining the adapted image, the second obtaining module 330 may directly determine a phase corresponding to the adapted image as the target phase. Subsequently, the second obtaining module 330 may determine the scan image corresponding to the target phase as the target scan image.

It should be noted that the above description related to the flow 700 is only for illustration and explanation, and does not limit the applicable scope of the present application. Various modifications and changes to flow 700 may occur to those skilled in the art upon review of the present application. However, such modifications and variations are intended to be within the scope of the present application.

The beneficial effects that may be brought by the embodiments of the present description include, but are not limited to: (1) the calculation complexity is reduced and the calculation precision is improved by combining the relevant data of the radioactive source with the forward iteration process; (2) the 4D-CT image is used for dose reconstruction, so that the influence of motion on the dose reconstruction is eliminated, and the influence of posture change and positioning of a target object (such as a patient) is eliminated. It is to be noted that different embodiments may produce different advantages, and in different embodiments, any one or combination of the above advantages may be produced, or any other advantages may be obtained.

Having thus described the basic concept, it will be apparent to those skilled in the art that the foregoing detailed disclosure is to be regarded as illustrative only and not as limiting the present specification. Various modifications, improvements and adaptations to the present description may occur to those skilled in the art, although not explicitly described herein. Such modifications, improvements and adaptations are proposed in the present specification and thus fall within the spirit and scope of the exemplary embodiments of the present specification.

Also, the description uses specific words to describe embodiments of the description. Reference throughout this specification to "one embodiment," "an embodiment," and/or "some embodiments" means that a particular feature, structure, or characteristic described in connection with at least one embodiment of the specification is included. Therefore, it is emphasized and should be appreciated that two or more references to "an embodiment" or "one embodiment" or "an alternative embodiment" in various places throughout this specification are not necessarily all referring to the same embodiment. Furthermore, some features, structures, or characteristics of one or more embodiments of the specification may be combined as appropriate.

Moreover, those skilled in the art will appreciate that aspects of the present description may be illustrated and described in terms of several patentable species or situations, including any new and useful combination of processes, machines, manufacture, or materials, or any new and useful improvement thereof. Accordingly, aspects of this description may be performed entirely by hardware, entirely by software (including firmware, resident software, micro-code, etc.), or by a combination of hardware and software. The above hardware or software may be referred to as "data block," module, "" engine, "" unit, "" component, "or" system. Furthermore, aspects of the present description may be represented as a computer product, including computer readable program code, embodied in one or more computer readable media.

The computer storage medium may comprise a propagated data signal with the computer program code embodied therewith, for example, on baseband or as part of a carrier wave. The propagated signal may take any of a variety of forms, including electromagnetic, optical, etc., or any suitable combination. A computer storage medium may be any computer-readable medium that can communicate, propagate, or transport a program for use by or in connection with an instruction execution system, apparatus, or device. Program code located on a computer storage medium may be propagated over any suitable medium, including radio, cable, fiber optic cable, RF, or the like, or any combination of the preceding.

Computer program code required for the operation of various portions of this specification may be written in any one or more programming languages, including an object oriented programming language such as Java, Scala, Smalltalk, Eiffel, JADE, Emerald, C + +, C #, VB.NET, Python, and the like, a conventional programming language such as C, Visual Basic, Fortran 2003, Perl, COBOL 2002, PHP, ABAP, a dynamic programming language such as Python, Ruby, and Groovy, or other programming languages. The program code may execute entirely on the user's computer, partly on the user's computer, as a stand-alone software package, partly on the user's computer and partly on a remote computer or entirely on the remote computer or server. In the latter scenario, the remote computer may be connected to the user's computer through any network format, such as a Local Area Network (LAN) or a Wide Area Network (WAN), or the connection may be made to an external computer (for example, through the Internet), or in a cloud computing environment, or as a service, such as a software as a service (SaaS).

Additionally, the order in which the elements and sequences of the process are recited in the specification, the use of alphanumeric characters, or other designations, is not intended to limit the order in which the processes and methods of the specification occur, unless otherwise specified in the claims. While various presently contemplated embodiments of the invention have been discussed in the foregoing disclosure by way of example, it is to be understood that such detail is solely for that purpose and that the appended claims are not limited to the disclosed embodiments, but, on the contrary, are intended to cover all modifications and equivalent arrangements that are within the spirit and scope of the embodiments herein. For example, although the system components described above may be implemented by hardware devices, they may also be implemented by software-only solutions, such as installing the described system on an existing server or mobile device.

Similarly, it should be noted that in the preceding description of embodiments of the present specification, various features are sometimes grouped together in a single embodiment, figure, or description thereof for the purpose of streamlining the disclosure aiding in the understanding of one or more of the embodiments. This method of disclosure, however, is not intended to imply that more features than are expressly recited in a claim. Indeed, the embodiments may be characterized as having less than all of the features of a single embodiment disclosed above.

Numerals describing the number of components, attributes, etc. are used in some embodiments, it being understood that such numerals used in the description of the embodiments are modified in some instances by the use of the modifier "about", "approximately" or "substantially". Unless otherwise indicated, "about", "approximately" or "substantially" indicates that the number allows a variation of ± 20%. Accordingly, in some embodiments, the numerical parameters used in the specification and claims are approximations that may vary depending upon the desired properties of the individual embodiments. In some embodiments, the numerical parameter should take into account the specified significant digits and employ a general digit preserving approach. Notwithstanding that the numerical ranges and parameters setting forth the broad scope of the range are approximations, in the specific examples, such numerical values are set forth as precisely as possible within the scope of the application.

For each patent, patent application publication, and other material, such as articles, books, specifications, publications, documents, etc., cited in this specification, the entire contents of each are hereby incorporated by reference into this specification. Except where the application history document does not conform to or conflict with the contents of the present specification, it is to be understood that the application history document, as used herein in the present specification or appended claims, is intended to define the broadest scope of the present specification (whether presently or later in the specification) rather than the broadest scope of the present specification. It is to be understood that the descriptions, definitions and/or uses of terms in the accompanying materials of this specification shall control if they are inconsistent or contrary to the descriptions and/or uses of terms in this specification.

Finally, it should be understood that the embodiments described herein are merely illustrative of the principles of the embodiments of the present disclosure. Other variations are also possible within the scope of the present description. Thus, by way of example, and not limitation, alternative configurations of the embodiments of the specification can be considered consistent with the teachings of the specification. Accordingly, the embodiments of the present description are not limited to only those embodiments explicitly described and depicted herein.