CN118267640A - Method and system for verifying MRI-guided adaptive radiotherapy dosage - Google Patents
Method and system for verifying MRI-guided adaptive radiotherapy dosage Download PDFInfo
- Publication number
- CN118267640A CN118267640A CN202410305930.1A CN202410305930A CN118267640A CN 118267640 A CN118267640 A CN 118267640A CN 202410305930 A CN202410305930 A CN 202410305930A CN 118267640 A CN118267640 A CN 118267640A
- Authority
- CN
- China
- Prior art keywords
- dose
- mri
- image
- pseudo
- dose distribution
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
- 238000001959 radiotherapy Methods 0.000 title claims abstract description 61
- 230000003044 adaptive effect Effects 0.000 title claims abstract description 37
- 238000000034 method Methods 0.000 title claims abstract description 36
- 206010028980 Neoplasm Diseases 0.000 claims abstract description 28
- 238000012795 verification Methods 0.000 claims abstract description 27
- 238000004088 simulation Methods 0.000 claims abstract description 26
- 238000005259 measurement Methods 0.000 claims abstract description 13
- 238000007639 printing Methods 0.000 claims abstract description 6
- 238000004364 calculation method Methods 0.000 claims description 19
- 238000004590 computer program Methods 0.000 claims description 12
- 239000011800 void material Substances 0.000 claims description 9
- 230000008569 process Effects 0.000 claims description 5
- 238000000342 Monte Carlo simulation Methods 0.000 claims description 4
- 238000006243 chemical reaction Methods 0.000 abstract 1
- 238000002595 magnetic resonance imaging Methods 0.000 description 42
- 230000005855 radiation Effects 0.000 description 5
- 238000011161 development Methods 0.000 description 3
- 238000005516 engineering process Methods 0.000 description 3
- 230000006870 function Effects 0.000 description 3
- 210000000920 organ at risk Anatomy 0.000 description 3
- 230000001225 therapeutic effect Effects 0.000 description 3
- 210000004881 tumor cell Anatomy 0.000 description 3
- 230000008859 change Effects 0.000 description 2
- 230000000694 effects Effects 0.000 description 2
- 238000005457 optimization Methods 0.000 description 2
- 210000000056 organ Anatomy 0.000 description 2
- 230000001360 synchronised effect Effects 0.000 description 2
- 238000010146 3D printing Methods 0.000 description 1
- 210000003484 anatomy Anatomy 0.000 description 1
- 230000009286 beneficial effect Effects 0.000 description 1
- 230000037237 body shape Effects 0.000 description 1
- 210000000133 brain stem Anatomy 0.000 description 1
- 238000004422 calculation algorithm Methods 0.000 description 1
- 230000001419 dependent effect Effects 0.000 description 1
- 238000010586 diagram Methods 0.000 description 1
- 230000001815 facial effect Effects 0.000 description 1
- 239000011521 glass Substances 0.000 description 1
- 238000009499 grossing Methods 0.000 description 1
- 210000002216 heart Anatomy 0.000 description 1
- 238000003384 imaging method Methods 0.000 description 1
- 238000002721 intensity-modulated radiation therapy Methods 0.000 description 1
- 210000003734 kidney Anatomy 0.000 description 1
- 230000003902 lesion Effects 0.000 description 1
- 239000007788 liquid Substances 0.000 description 1
- 210000004185 liver Anatomy 0.000 description 1
- 210000004072 lung Anatomy 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 230000036285 pathological change Effects 0.000 description 1
- 231100000915 pathological change Toxicity 0.000 description 1
- 230000000191 radiation effect Effects 0.000 description 1
- 230000003439 radiotherapeutic effect Effects 0.000 description 1
- 230000004044 response Effects 0.000 description 1
- 239000007787 solid Substances 0.000 description 1
- 210000000278 spinal cord Anatomy 0.000 description 1
- 230000003068 static effect Effects 0.000 description 1
- 230000009466 transformation Effects 0.000 description 1
- 238000000844 transformation Methods 0.000 description 1
Landscapes
- Radiation-Therapy Devices (AREA)
Abstract
The application belongs to the technical field of radiotherapy dose verification, and discloses a method and a system for verifying MRI-guided self-adaptive radiotherapy dose. By collecting MRI images of the patient currently treated, tumor target areas and normal tissues are delineated on the MRI images; converting the MRI image into a pseudo CT image, and calculating a desired dose distribution; constructing a three-dimensional model corresponding to the MRI image through modeling software, and printing the three-dimensional model into a simulation model body; determining at least one dose verification point for placing a first dose measurement device and an orthogonal gap for placing a second dose measurement device in a tumor target area of the simulation phantom; performing on-line adaptive planning on the simulation die body through a magnetic resonance accelerator, and collecting actual dose distribution received by the first dose measuring device and the second dose measuring device; and comparing the actual dose distribution with the expected dose distribution obtained based on the pseudo CT image, and verifying the accuracy of the calculated dose based on the pseudo CT according to the comparison result. The accuracy of the pseudo CT based MRI image conversion can be verified.
Description
Technical Field
The application relates to the technical field of radiotherapy dose verification, in particular to a method and a system for verifying MRI-guided self-adaptive radiotherapy dose.
Background
Radiation therapy is one of the main means of tumor treatment, and mainly uses X-rays to kill tumor cells, so that the tumor dose is increased, and the irradiated dose of organs at risk and normal tissues is reduced. With the development of electronic computer technology and radiotherapy equipment, radiotherapy has entered the era of accurate radiotherapy, for example, intensity modulated radiotherapy (INTENSITY MODULATED RADIOTHERAPY, IMRT) technology is now commonly used in clinic, and can simultaneously protect normal tissues while maximizing tumor dose, so that the irradiation dose distribution is more dependent on the geometry of a target region and organs at risk of a patient. However, during the treatment, the actual dose to be irradiated at the target area deviates from the plan due to the change of the body shape of the patient, the change of the tumor, the relative movement of organs in the body and the like, thereby affecting the treatment effect. To solve the above problems, adaptive radiotherapy by image guidance has been developed.
In recent years, on-line adaptive radiotherapy guided by magnetic resonance images (Magnetic Resonance Imaging, MRI) gradually enters clinical application, and becomes one of the most advanced image-guided radiotherapy technologies at present. MRI guided on-line adaptive radiotherapy (MRIgART) is based on MRI images in the current treatment process, changes of tumors and surrounding tissues are monitored in real time, a radiotherapy plan is adjusted and optimized in real time, and deformation errors in treatment are corrected, so that the method is a revolutionary progress and development of radiotherapy technology development. However, since the MRI image has no electron density information, the MRI image needs to be converted into a pseudo CT for dose calculation, and the accuracy of the pseudo CT directly affects the treatment result. The conventional dose verification is to simulate the beam out of the patient before the treatment by various universal models, and verify whether the beam out of the machine has errors, namely whether the equipment can accurately output the expected dose according to preset parameters and conditions, but cannot verify whether the converted pseudo CT is accurate.
Disclosure of Invention
To this end, embodiments of the present application provide a method and system for verifying MRI-guided adaptive radiotherapy doses that can verify the accuracy of pseudo-CTs based on MRI image transformations.
In a first aspect, the application provides a method of validating an MRI-guided adaptive radiotherapy dose.
The application is realized by the following technical scheme:
Acquiring an MRI image of the patient treated at the time, and carrying out tumor target area and normal tissue sketching on the MRI image to obtain sketching results;
Converting the MRI image into a pseudo CT image, calculating a desired dose distribution based on the pseudo CT image;
constructing a three-dimensional model corresponding to the MRI image by modeling software according to the sketching result, and printing the three-dimensional model into a simulation die body;
determining a dose verification point and an orthogonal void in a tumor target region of the phantom; wherein a first dose measurement device is placed at the dose verification point and a second dose measurement device is placed within the orthogonal void;
Performing on-line adaptive planning on the simulation die body through a magnetic resonance accelerator, and collecting actual dose distribution received by the first dose measuring device and the second dose measuring device;
and comparing the actual dose distribution with the expected dose distribution obtained based on the pseudo CT image, and verifying the accuracy of calculating the dose based on the pseudo CT according to a comparison result.
In a preferred embodiment of the application, it is further provided that the MRI image is converted into a pseudo CT image on the basis of electron density assignment.
In a preferred example of the present application, it may be further arranged that the step of calculating the desired dose distribution based on the pseudo CT image comprises:
setting dose distribution parameters of radiotherapy according to a treatment target, wherein the dose distribution parameters comprise total dose, fractionated dose, dose rate and irradiation angle of the radiotherapy;
A desired dose distribution is calculated using a dose calculation model based on the pseudo CT image and the dose distribution parameters.
In a preferred embodiment of the present application, it may be further provided that the dose calculation model uses a monte carlo simulation method.
In a preferred embodiment of the present application, it may be further provided that the first dose measuring device is a point dose measuring device and the second dose measuring device is a face dose measuring device.
In a second aspect, the present application provides a system for validating an MRI-guided adaptive radiotherapy dose.
The application is realized by the following technical scheme:
a system for validating an MRI-guided adaptive radiotherapy dose,
The system comprises:
The data acquisition module is configured to acquire an MRI image of the current treatment of the patient, and the tumor target area and the normal tissue are delineated on the MRI image to obtain a delineating result;
a desired dose calculation module configured to convert the MRI image into a pseudo CT image, calculate a desired dose distribution based on the pseudo CT image;
The simulation die body module is configured to construct a three-dimensional model corresponding to the MRI image through modeling software by using the sketching result, and print the three-dimensional model into a simulation die body;
Dose measurement equipment, which is placed in the dose verification point and the orthogonal gap of the simulation die body and is used for collecting and implementing the actual dose distribution received in the online adaptive planning process;
And the verification module is configured to compare the actual dose distribution with the expected dose distribution obtained based on the pseudo CT image, and verify the accuracy of calculating the dose based on the pseudo CT according to the comparison result.
In a preferred embodiment of the application, it is further provided that the expected dose calculation module is also used for converting the MRI image into a pseudo CT image based on an electron density assignment method.
In a preferred embodiment of the present application, the expected dose calculation module is further configured to set dose distribution parameters of radiotherapy according to a therapeutic target, where the dose distribution parameters include a total dose of radiotherapy, a fractionated dose, a dose rate, and an irradiation angle;
the pseudo CT image and the dose distribution parameters are input into a dose calculation model to obtain a desired dose distribution.
In a third aspect, the application provides an apparatus for validating an MRI-guided adaptive radiotherapy dose.
The application is realized by the following technical scheme:
An apparatus for validating an MRI-guided adaptive radiotherapy dose, comprising a memory, a processor and a computer program stored on the memory, the processor executing the computer program to perform the steps of the method of the first aspect.
In a fourth aspect, the present application provides a computer-readable storage medium.
The application is realized by the following technical scheme:
The computer readable storage medium stores a computer program which, when executed by a processor, implements the steps of the method of the first aspect.
In summary, compared with the prior art, the technical scheme provided by the embodiment of the application has the following beneficial effects:
Acquiring an MRI image of the patient treated at the time, and carrying out tumor target area and normal tissue sketching on the MRI image to obtain sketching results; converting the MRI image into a pseudo CT image, calculating a desired dose distribution based on the pseudo CT image; constructing a three-dimensional model corresponding to the MRI image by using the sketching result through modeling software, and printing the three-dimensional model into a simulation die body; determining a dose verification point and an orthogonal gap in a tumor target area of the simulation phantom; wherein a first dose measurement device is placed at the dose verification point and a second dose measurement device is placed within the orthogonal void; performing on-line adaptive planning on the simulation die body through a magnetic resonance accelerator, and collecting actual dose distribution received by the first dose measuring device and the second dose measuring device; and comparing the actual dose distribution with the expected dose distribution obtained based on the pseudo CT image, and verifying the accuracy of the calculated dose based on the pseudo CT according to the comparison result. The accurate implementation of MRI guided adaptive radiotherapy can be ensured to the greatest extent by verifying the dose accuracy of the MRI image converted into pseudo CT.
Drawings
FIG. 1 is a flow chart of a method for verifying MRI-guided adaptive radiotherapy doses according to an exemplary embodiment of the present application;
fig. 2 is a schematic diagram of a system for verifying MRI-guided adaptive radiotherapy doses according to an exemplary embodiment of the present application.
Detailed Description
The present embodiment is only for explanation of the present application and is not to be construed as limiting the present application, and modifications to the present embodiment, which may not creatively contribute to the present application as required by those skilled in the art after reading the present specification, are all protected by patent laws within the scope of claims of the present application.
For the purpose of making the objects, technical solutions and advantages of the embodiments of the present application more apparent, the technical solutions of the embodiments of the present application will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present application, and it is apparent that the described embodiments are some embodiments of the present application, but not all embodiments of the present application. All other embodiments, which can be made by those skilled in the art based on the embodiments of the application without making any inventive effort, are intended to be within the scope of the application.
In addition, the term "and/or" in the present application is merely an association relationship describing the association object, and indicates that three relationships may exist, for example, a and/or B may indicate: a exists alone, A and B exist together, and B exists alone. In the present application, unless otherwise specified, the term "/" generally indicates that the associated object is an "or" relationship.
The terms "first," "second," and the like in this disclosure are used for distinguishing between similar elements or items having substantially the same function and function, and it should be understood that there is no logical or chronological dependency between the terms "first," "second," and "n," and that there is no limitation on the amount and order of execution.
Embodiments of the application are described in further detail below with reference to the drawings.
In one embodiment of the present application, a method of validating an MRI-guided adaptive radiotherapy dose is provided, as shown in fig. 1, with the main steps described as follows:
and S10, collecting MRI image data of the patient in the current treatment, and carrying out tumor target area and normal tissue sketching on the MRI image to obtain sketching results.
Specifically, when the patient receives treatment, the patient is placed on the magnetic resonance accelerator in a stable posture, and the MRI scanning parameters such as the scanning area, the scanning resolution, the scanning time, etc. are set according to the treatment plan and the specific condition of the patient, so that it is ensured that MRI image data containing sufficient image information and high quality is obtained. The MRI image data includes T1 weighted images, T2 weighted images, and the like. The MRI image data may provide anatomical information of the tumor location, morphology, and tumor surrounding tissue of the patient. In some embodiments, to further improve the quality of the MRI image data, the image may also be pre-processed to eliminate noise, enhance contrast, etc.
Further, the radiologist or radiotherapeutic professional transmits the pseudo MRI image to a radiotherapy planning system (TPS), delineates a tumor target region (GTV, gross Tumor Volume) according to the tumor position presented in the image, and also needs to delineate normal tissues or organs around the tumor target region, such as spinal cord, brainstem, glasses, lung, heart, liver, kidney, etc., the purpose of the delineated normal tissues being to limit the irradiation dose during subsequent radiotherapy, protecting the normal tissues from unnecessary radiation damage. In addition to this, it is necessary to delineate the intended target area. And obtaining a final sketching result according to the region division. The sketching results help to accurately determine the treatment area, protect normal tissue, formulate personalized treatment plans, and evaluate the treatment effect.
And S20, converting the MRI image data into a pseudo CT image, and calculating the expected dose distribution based on the pseudo CT image.
In some embodiments, the MRI image is converted to a pseudo CT image based on electron density assignment. Specifically, the electron density assignment can be performed according to different tissue structure types in the MRI image and according to a CT average electron density value or a report recommendation of ICRU (international radiation unit and measurement committee) number 46, so as to generate a pseudo CT image.
Wherein, obtaining the desired dose distribution based on the pseudo CT image specifically comprises: setting dose distribution parameters of radiotherapy according to a treatment target, wherein the dose distribution parameters comprise total dose, fractionated dose, dose rate and irradiation angle of the radiotherapy; based on the pseudo-CT image and the dose distribution parameters, a desired dose distribution is calculated using a dose calculation model. The dose calculation model adopts a Monte Carlo simulation method. The monte carlo simulation method may be implemented on Talemu simulation software.
It should be noted that, to achieve a better therapeutic goal, dose distribution parameters of radiotherapy, including but not limited to total dose of radiotherapy, divided dose, dose rate, and irradiation angle, need to be set according to the therapeutic goal. The total radiotherapy dosage refers to the total radiotherapy dosage which needs to be received by a patient in the whole radiotherapy process, and needs to be determined according to factors such as the illness state, the pathological change part, the radiosensitivity and the like of the patient, and the total radiotherapy dosage needs to be enough to kill or inhibit tumor cells and avoid excessive damage to normal tissues. The divided dose means that the total dose is divided into a plurality of shots, and the dose of each shot becomes a divided dose. The purpose of the fractionated irradiation is to reduce the damage to normal tissue from a single high dose irradiation while leaving tumor cells with a greater chance of being lethally damaged. The dose rate refers to the dose received per unit time, expressed in terms of either Gy/h or rad/h. The larger the general dose rate, the more pronounced the radiation effect, and the appropriate dose rate needs to be selected according to the specific situation. The irradiation angle refers to the angle between the rays and the body of a patient during radiation treatment, the irradiation angle is selected by considering factors such as the position and shape of a tumor, the structure of surrounding tissues and the like, and a proper angle is selected to ensure that the imaging can accurately irradiate the lesion part and reduce the damage to the surrounding normal tissues. The radiation treatment planning system calculates the position, size and shape of each irradiation field or source and the dose weight of each irradiation field or source according to the dose distribution parameters through an optimization algorithm. These parameters are calculated and optimized to obtain a desired dose distribution that is capable of maximally covering the tumor target area while minimally affecting surrounding normal tissue. The dose distribution response radiation is a dose distribution generated at different locations or at different depths in the patient.
And S30, constructing a three-dimensional model corresponding to the MRI image data by using the sketching result through modeling software, and printing the three-dimensional model into a simulation die body.
In particular, the modeling software may employ 3D MAX, maya, ZBrush, etc., all of which support the introduction of DICOM format. The method can be used for importing the DICOM of MRI into modeling software, combining the sketching results of a tumor target area and normal tissues, generating corresponding three-dimensional models by different structures, carrying out optimization such as surface smoothing, noise removal, size adjustment and the like, storing the three-dimensional models into a proper format, exporting the three-dimensional models, and printing the three-dimensional models into a simulation model body by using a 3D printing technology. The personalized three-dimensional die body is generated according to the MRI image data of the patient, so that the anatomical structure and tissue characteristics of the patient can be accurately reflected, and the irradiation dose can be conveniently and accurately estimated later.
S40, determining at least one dose verification point and an orthogonal gap in a tumor target area of the simulation die body; wherein a first dose measuring device is placed at the dose verification point and a second dose measuring device is placed within the orthogonal void.
Wherein the first dose measuring device is a point dose measuring device and the second dose measuring device is a face dose measuring device. In particular, the spot-dose measuring device is an ionization chamber, which may be one of an air ionization chamber, a liquid ionization chamber and a solid ionization chamber. The facial dose measuring device is a measuring film.
At least one dose verification point is selected from the tumor target area and used for verifying the accuracy of the dose of the important position point. And selecting a plurality of dose verification points in the target region tissue and the important organs at risk, and comprehensively considering the verification results of the plurality of dose verification points can ensure more accurate verification and improve the verification precision. And selecting a dose verification point at the center of the target tissue, and setting an orthogonal gap at the dose verification point by adjusting the angle and the position of the irradiation field. The orthogonal void refers to a blank area provided on two orthogonal planes (cross section or longitudinal section) for verifying accuracy of the surface dose.
S50, performing on-line adaptive planning on the simulation die body through the magnetic resonance accelerator, and acquiring actual dose distribution received by the first dose measuring device and the second dose measuring device.
Specifically, a magnetic resonance accelerator is started, a simulation die body is placed on a treatment bed of the magnetic resonance accelerator, on-line adaptive planning is carried out, the received actual dose is collected by using a first dose measuring device and a second dose device which are placed in the simulation die body, and the first actual dose collected by the first dose device and the second actual dose collected by the second dose device are comprehensively considered to determine final actual dose distribution.
S60, comparing the actual dose distribution with the expected dose distribution obtained based on the pseudo CT image, and verifying the accuracy of the calculated dose based on the pseudo CT according to the comparison result.
The actual dose distribution received by the dose measuring device during the actual treatment is spatially matched and aligned with the desired dose distribution obtained from the pseudo-CT image by geometric information to compare the dose deviations of the actual dose distribution and the desired dose distribution. In order to more intuitively judge the difference between the two, the dose deviation map may be displayed, where the dose deviation map includes a point-to-point difference between an actual dose distribution and an expected dose distribution, and an average value, a maximum value, a minimum value, a standard deviation, and the like between the dose differences may be further calculated. If the dose variation is within an acceptable preset variation range, then it is considered accurate; dose variation is considered inaccurate if it is outside an acceptable preset variation range.
In another embodiment of the present application, a system for validating an MRI-guided adaptive radiotherapy dose is provided, as shown in fig. 2, comprising: the data acquisition module 01, the expected dose calculation module 02, the simulation phantom module 03, the dose measurement device 04 and the verification module 05.
The data acquisition module 01 is configured to acquire an MRI image of the patient currently treated, and perform tumor target area and normal tissue sketching on the MRI image to obtain sketching results; a desired dose calculation module 02 configured to convert the MRI image into a pseudo CT image, based on which a desired dose distribution is calculated; the simulation die body module 03 is configured to construct a three-dimensional model corresponding to the MRI image by modeling software according to the sketching result, and print the three-dimensional model into a simulation die body; a dose measurement device 04 placed in at least one dose verification point and in the orthogonal void of the simulation phantom for acquiring the actual dose distribution received during implementation of the on-line adaptive planning process; the verification module 05 is configured to compare the actual dose distribution with the expected dose distribution obtained based on the pseudo-CT image, and verify the accuracy of calculating the dose based on the pseudo-CT according to the comparison result.
The expected dose calculation module 02 is also used to convert MRI images into pseudo CT images based on electron density assignments. Further, the method is also used for setting the dose distribution parameters of the radiotherapy according to the treatment target, wherein the dose distribution parameters comprise the total dose, the fractionated dose, the dose rate and the irradiation angle of the radiotherapy; the pseudo-CT image and the dose distribution parameters are input into a dose calculation model to obtain a desired dose distribution.
In one embodiment, a device for validating an MRI-guided adaptive radiotherapy dose is provided, which may be a server.
The device includes a processor, a memory, a network interface, and a database connected by a system bus. Wherein the processor of the device is configured to provide computing and control capabilities. The memory of the device includes a non-volatile storage medium, an internal memory. The non-volatile storage medium has an operating system, computer programs, and a database. The internal memory provides an environment for the operation of the operating system and computer programs in the non-volatile storage media. The network interface of the computer device is used for communicating with an external terminal through a network connection. The computer program is executed by a processor to implement a method of validating an MRI-guided adaptive radiotherapy dose as described above.
In one embodiment, a computer readable storage medium is provided that includes a memory, a processor, and a computer program stored on the memory and executable on the processor, the processor executing the computer program to implement any one of the methods of verifying MRI-guided adaptive radiotherapy doses described above.
Those skilled in the art will appreciate that implementing all or part of the above described methods may be accomplished by way of a computer program stored on a non-transitory computer readable storage medium, which when executed, may comprise the steps of the embodiments of the methods described above. Any reference to memory, storage, database, or other medium used in embodiments provided herein may include non-volatile and/or volatile memory. The nonvolatile memory can include Read Only Memory (ROM), programmable ROM (PROM), electrically Programmable ROM (EPROM), electrically Erasable Programmable ROM (EEPROM), or flash memory. Volatile memory can include Random Access Memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in a variety of forms such as Static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double Data Rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous link (SYNCHLINK), DRAM (SLDRAM), memory bus (Rambus) direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM), among others.
It will be apparent to those skilled in the art that, for convenience and brevity of description, only the above-described division of the functional units and modules is illustrated, and in practical application, the above-described functional distribution may be performed by different functional units and modules according to needs, i.e. the internal structure of the apparatus of the present application is divided into different functional units or modules to perform all or part of the above-described functions.
Claims (10)
1. A method of validating an MRI-guided adaptive radiotherapy dose, the method comprising:
Acquiring an MRI image of the patient treated at the time, and carrying out tumor target area and normal tissue sketching on the MRI image to obtain sketching results;
Converting the MRI image into a pseudo CT image, calculating a desired dose distribution based on the pseudo CT image;
constructing a three-dimensional model corresponding to the MRI image by modeling software according to the sketching result, and printing the three-dimensional model into a simulation die body;
Determining at least one dose verification point and one orthogonal void in a tumor target region of the phantom; wherein a first dose measurement device is placed at the dose verification point and a second dose measurement device is placed within the orthogonal void;
Performing on-line adaptive planning on the simulation die body through a magnetic resonance accelerator, and collecting actual dose distribution received by the first dose measuring device and the second dose measuring device;
and comparing the actual dose distribution with the expected dose distribution obtained based on the pseudo CT image, and verifying the accuracy of calculating the dose based on the pseudo CT according to a comparison result.
2. The method of validating MRI guided adaptive radiotherapy dosage of claim 1, wherein MRI images are converted to pseudo CT images based on electron density assignment.
3. The method of validating MRI guided adaptive radiotherapy dosage of claim 2, wherein said step of calculating a desired dosage distribution based on said pseudo CT image comprises:
setting dose distribution parameters of radiotherapy according to a treatment target, wherein the dose distribution parameters comprise total dose, fractionated dose, dose rate and irradiation angle of the radiotherapy;
A desired dose distribution is calculated using a dose calculation model based on the pseudo CT image and the dose distribution parameters.
4. A method of validating MRI guided adaptive radiotherapy doses as claimed in claim 3, wherein the dose calculation model employs a monte carlo simulation method.
5. A method of validating MRI guided adaptive radiotherapy doses according to claim 1, characterized in that the first dose measuring device is a point dose measuring device and the second dose measuring device is a face dose measuring device.
6. A system for validating an MRI-guided adaptive radiotherapy dose, the system comprising:
The data acquisition module is configured to acquire an MRI image of the current treatment of the patient, and the tumor target area and the normal tissue are delineated on the MRI image to obtain a delineating result;
a desired dose calculation module configured to convert the MRI image into a pseudo CT image, calculate a desired dose distribution based on the pseudo CT image;
The simulation die body module is configured to construct a three-dimensional model corresponding to the MRI image through modeling software by using the sketching result, and print the three-dimensional model into a simulation die body;
A dose measurement device placed in at least one dose verification point and an orthogonal void of the simulation phantom for acquiring actual dose distribution received during implementation of an on-line adaptive planning process;
And the verification module is configured to compare the actual dose distribution with the expected dose distribution obtained based on the pseudo CT image, and verify the accuracy of calculating the dose based on the pseudo CT according to the comparison result.
7. The system for validating MRI guided adaptive radiotherapy dosage of claim 6, wherein,
The expected dose calculation module is further configured to convert the MRI image to a pseudo CT image based on the electron density assignment method.
8. The system for validating MRI guided adaptive radiation therapy dose of claim 6, wherein said desired dose calculation module is further configured to set radiation therapy dose distribution parameters including total radiation therapy dose, fraction dose, dose rate, and angle of irradiation based on a treatment objective;
the pseudo CT image and the dose distribution parameters are input into a dose calculation model to obtain a desired dose distribution.
9. An apparatus for validating an MRI-guided adaptive radiotherapy dosage, comprising a memory, a processor and a computer program stored on the memory, the processor executing the computer program to perform the steps of the method of any one of claims 1 to 5.
10. A computer-readable storage medium, characterized in that it stores a computer program which, when executed by a processor, implements the steps of the method according to any one of claims 1 to 5.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202410305930.1A CN118267640A (en) | 2024-03-18 | 2024-03-18 | Method and system for verifying MRI-guided adaptive radiotherapy dosage |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202410305930.1A CN118267640A (en) | 2024-03-18 | 2024-03-18 | Method and system for verifying MRI-guided adaptive radiotherapy dosage |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN118267640A true CN118267640A (en) | 2024-07-02 |
Family
ID=91644669
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202410305930.1A Pending CN118267640A (en) | 2024-03-18 | 2024-03-18 | Method and system for verifying MRI-guided adaptive radiotherapy dosage |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN118267640A (en) |
-
2024
- 2024-03-18 CN CN202410305930.1A patent/CN118267640A/en active Pending
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| US11266858B2 (en) | Systems, devices, and methods for quality assurance of radiation therapy | |
| JP6783398B2 (en) | Systems and methods for modeling dose calculations in radiation therapy planning | |
| Ahunbay et al. | An on‐line replanning scheme for interfractional variations a | |
| JP6624695B2 (en) | 3D localization of moving targets for adaptive radiation therapy | |
| US9511241B2 (en) | Irradiation planning for particle therapy | |
| JP6498934B2 (en) | Beam segment level dose calculation and temporal motion tracking for adaptive treatment planning | |
| RU2682455C2 (en) | System and method for patient-specific radiotherapy treatment verification and quality assurance | |
| CN101069771B (en) | For setting up the equipment irradiating planning | |
| US10076673B2 (en) | Interactive dose gradient based optimization technique to control IMRT delivery complexity | |
| KR20100016039A (en) | Improved treatment plan evaluation in radiotherapy by stochastic analysis of delineation uncertainty | |
| EP1708788A2 (en) | Systems and methods for global optimization of treatment planning for external beam radiation therapy | |
| KR20110039514A (en) | Device and method for 3d dose tracking in radiation therapy | |
| CN114681813A (en) | Automatic planning system, automatic planning method and computer program product for radiation therapy | |
| CN109513121A (en) | Dose-guided adaptive radiotherapy plan re-optimization system and method | |
| Yang et al. | Variable planning margin approach to account for locoregional variations in setup uncertainties a | |
| US20230302298A1 (en) | Method and system for robust radiotherapy treatment planning for dose mapping uncertainties | |
| CN118267640A (en) | Method and system for verifying MRI-guided adaptive radiotherapy dosage | |
| EP3338860A1 (en) | Registration of particle beam radiography data | |
| Bridge | Principles and Practice of Treatment Planning | |
| CN117653927A (en) | Dose verification method, device and equipment for radiotherapy process | |
| CN117379707A (en) | Method and system for setting parameters of magnetic resonance image guided ion beam radiotherapy | |
| WO2023009332A1 (en) | Dose coverage margin metric for evaluating radiotherapy treatment plans | |
| Wong et al. | 15 Cone beam CT: Transforming radiation treatment guidance, planning, and monitoring | |
| Frantzen-Steneker | S12 3rd ESTRO Forum 2015 | |
| Thongphiew | ON-LINE RE-OPTIMIZATION OF PROSTATE IMRT PLAN FOR ADAPTIVE RADIATION THERAPY–A FEASIBILITY STUDY AND IMPLEMENTATION |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication |