CN115025403B - A method and device for predicting dose based on radiotherapy - Google Patents
A method and device for predicting dose based on radiotherapy Download PDFInfo
- Publication number
- CN115025403B CN115025403B CN202210496970.XA CN202210496970A CN115025403B CN 115025403 B CN115025403 B CN 115025403B CN 202210496970 A CN202210496970 A CN 202210496970A CN 115025403 B CN115025403 B CN 115025403B
- Authority
- CN
- China
- Prior art keywords
- dose
- predicted
- value
- volume histogram
- 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.)
- Active
Links
Classifications
-
- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61N—ELECTROTHERAPY; MAGNETOTHERAPY; RADIATION THERAPY; ULTRASOUND THERAPY
- A61N5/00—Radiation therapy
- A61N5/10—X-ray therapy; Gamma-ray therapy; Particle-irradiation therapy
- A61N5/1048—Monitoring, verifying, controlling systems and methods
- A61N5/1071—Monitoring, verifying, controlling systems and methods for verifying the dose delivered by the treatment plan
-
- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61N—ELECTROTHERAPY; MAGNETOTHERAPY; RADIATION THERAPY; ULTRASOUND THERAPY
- A61N5/00—Radiation therapy
- A61N5/10—X-ray therapy; Gamma-ray therapy; Particle-irradiation therapy
- A61N5/103—Treatment planning systems
Landscapes
- Health & Medical Sciences (AREA)
- Engineering & Computer Science (AREA)
- Biomedical Technology (AREA)
- Pathology (AREA)
- Nuclear Medicine, Radiotherapy & Molecular Imaging (AREA)
- Radiology & Medical Imaging (AREA)
- Life Sciences & Earth Sciences (AREA)
- Animal Behavior & Ethology (AREA)
- General Health & Medical Sciences (AREA)
- Public Health (AREA)
- Veterinary Medicine (AREA)
- Radiation-Therapy Devices (AREA)
Abstract
The invention discloses a dose prediction method and device based on radiotherapy, comprising the steps of obtaining an original integral dose volume histogram of a structure to be predicted, obtaining reference dose distribution and actual dose distribution according to a preset measurement plane, obtaining projection weight distribution of the structure to be predicted on the preset measurement plane according to the preset measurement plane and control point parameters, obtaining a reference dose volume histogram and an actual dose volume histogram based on projection according to the projection weight distribution, the original integral dose volume histogram, the reference dose distribution and the actual dose distribution, calculating a dose difference value of the reference dose volume histogram and the actual dose volume histogram based on projection, and obtaining a predicted integral dose volume histogram according to the dose difference value, thereby completing dose prediction. The invention solves the technical problem that complex modeling and model testing processes are required to be carried out in the prior art.
Description
Technical Field
The invention relates to the technical field of medical software, in particular to a dose prediction method and device based on radiotherapy.
Background
Due to the complexity of radiation therapy, to ensure medical safety and to ensure that the plan for the therapy meets clinical requirements, to ensure compliance of the performed therapy plan with the planned design, pre-treatment dose verification is required before the therapy plan is used for the actual treatment of the patient. Dose verification is to compare the measured dose distribution with the calculated dose distribution according to the actual execution of the plan, and evaluate the actual execution effect of the plan by evaluating the difference between the measured value and the calculated value, and generally using an ionization chamber matrix, a semiconductor matrix and an electronic portal image system (Electronic Portal IMAGING DEVICE, EPID) as a pre-treatment intensity-modulated treatment plan dose measuring tool.
Common Dose distribution comparison analysis methods include a Dose difference method (Dose DIFFERENCE TEST), a Distance-To-agent method (Distance-To-agent), a Gamma analysis method and a three-dimensional Dose reconstruction comparison method, wherein the first three methods are for comparing direct measurement results, and a treatment plan needs To be transplanted To measurement equipment for calculation, so that the Dose distribution of a measurement plane is obtained. The general measuring equipment is in a uniform cube, cylinder or polygonal shape, but not in the shape of a human body or an actual therapeutic human body, because the measuring equipment is different from the actual human body, the obtained difference result is inconsistent with the actual human body dose difference result, and therefore, the greatest disadvantage of direct comparison is that clinically required data, such as integral dose volume histograms of different anatomical structures, average dose and other information, cannot be intuitively reflected, the three-dimensional dose reconstruction comparison method can obtain the result closest to treatment, but on the one hand, the measuring equipment has higher requirements to finish accurate reconstruction, such as high resolution, complete capture of accurate flux distribution is ensured, and the faster data acquisition speed is required to ensure that the acquisition process can acquire complete plan execution information in real time. On the other hand, complicated modeling and model testing processes are needed, and the quality of a modeling result can directly influence a final result.
Thus, there is a need for a dose prediction method and apparatus that avoids the modeling and model testing processes.
Disclosure of Invention
The invention provides a dose prediction method and device based on radiotherapy, which are used for solving the technical problem that complicated modeling and model testing processes are required in the prior art.
In order to solve the above technical problems, an embodiment of the present invention provides a dose prediction method based on radiation therapy, including:
Acquiring an original integral dose volume histogram of a structure to be predicted, and acquiring reference dose distribution and actual dose distribution according to a preset measurement plane;
acquiring projection weight distribution of the structure to be predicted on the preset measurement plane according to the preset measurement plane and control point parameters, wherein the control point parameters are acquired by a medical linear accelerator;
calculating and acquiring a reference dose volume histogram and an actual dose volume histogram based on projection according to the projection weight distribution, the original integral dose volume histogram, the reference dose distribution and the actual dose distribution;
And calculating a dose difference value of the projection-based reference dose volume histogram and the actual dose volume histogram, and calculating and acquiring a predicted integral dose volume histogram according to the dose difference value, thereby completing the prediction of the dose.
It can be understood that compared with the prior art, the method can acquire the original integral dose volume histogram of the structure to be predicted by the existing dose distribution comparison analysis method, acquire the reference dose distribution and the actual dose distribution according to the measurement plane, and acquire the projection weight distribution of the structure to be predicted on the preset measurement plane according to the control point parameter, thereby ensuring that the calculation of the acquired reference dose volume histogram and the actual dose volume histogram can be based on the projection weight, improving the accuracy of the dose volume histogram, accurately calculating the predicted integral dose volume histogram by the dose difference value between the reference dose volume histogram and the actual dose volume histogram, avoiding the existing complex modeling and model testing process and improving the dose prediction efficiency.
Preferably, the control point parameters comprise the total number of the control points of the medical linear accelerator, the arm support angles of all the control points and the beam-out jump number proportion of all the control points.
It can be understood that the control point parameters are determined by the arm support angle and other data of the execution control point of the medical linear accelerator, so that the projection weight distribution can be accurately calculated, and complex data required by modeling is not required.
As a preferred solution, the obtaining, according to the preset measurement plane and the control point parameter, a projection weight distribution of the structure to be predicted on the preset measurement plane specifically includes:
dividing the preset measurement plane into a plurality of measurement points, respectively obtaining the track length of the straight line corresponding to each measurement point passing through the structure to be predicted according to the straight lines determined by each measurement point and the beam outlet source of the linear accelerator, and respectively calculating and obtaining the projection weight distribution of each measurement point according to each measurement point, the track length corresponding to each measurement point, the total number of control points and the beam outlet hop count proportion of each control point.
It can be understood that by dividing a preset measurement plane, the obtained straight lines determined by each measurement point and the beam outlet source of the linear accelerator are used for obtaining the track length corresponding to each measurement point, and the structure projection weight distribution of the structure to be predicted on the measurement plane can be accurately obtained according to the execution control point parameters of the linear accelerator, so that the prediction calculation process is simplified.
Preferably, after the acquiring the original integral dose volume histogram of the structure to be predicted, the method further includes:
And respectively carrying out normalization operation on the volume value and the dose value of the original integral dose volume histogram according to the preset volume value and the preset dose value of the structure to be predicted, thereby obtaining a normalized original integral dose volume histogram.
It can be understood that the normalized operation is performed on the volume value and the dose value of the integral dose volume histogram through the preset volume value and the preset dose value of the structure to be predicted, so that the normalized original integral dose volume histogram can avoid errors in the calculation process caused by data of different magnitudes, and the calculation accuracy is improved.
Preferably, the calculating and obtaining a reference dose volume histogram and an actual dose volume histogram based on projection according to the projection weight distribution, the original integral dose volume histogram, the reference dose distribution and the actual dose distribution specifically includes:
obtaining and adding projection weights of measuring points larger than 0 in the projection weight distribution to obtain total weights of the measuring points;
Respectively carrying out normalization operation on the reference dose distribution and the actual dose distribution according to a preset dose value;
According to a dose value interval in the original integral dose volume histogram, respectively adding projection weights of a normalized reference dose distribution and a normalized actual dose distribution, which are larger than a measuring point corresponding to the dose value interval, to respectively obtain a first weight sum and a second weight sum of each dose value interval, wherein the first weight sum is a weight sum of the reference dose distribution, and the second weight sum is a weight sum of the actual dose distribution;
And respectively carrying out normalization processing on the first weight sum and the second weight sum according to the total weight of the measuring points, and respectively obtaining a reference dose volume histogram and an actual dose reference histogram based on projection according to the normalized first weight sum and second weight sum.
It can be understood that the total weight of the measuring points with the projection weight greater than zero is obtained and added through statistics of the projection weight distribution, the projection weight of the measuring points corresponding to the interval greater than the dose value is added through normalized reference dose distribution and normalized actual dose distribution, so as to obtain a first weight sum and a second weight sum, and the first weight sum and the second weight sum are respectively normalized through the total weight of the measuring points, so that a reference dose volume histogram and an actual dose reference histogram based on projection are accurately obtained.
Preferably, the calculating of the dose difference value is performed on the reference dose volume histogram and the actual dose volume histogram based on projection, and according to the dose difference value, a predicted integral dose volume histogram is calculated and obtained, specifically:
Calculating the difference of the corresponding dose values when the first weight sum is the same as the second weight sum according to the first weight sum and the second weight sum, and taking the difference as a dose difference value;
And calculating and acquiring a predicted dose value according to the dose difference value and the original integral dose volume histogram, and taking the weight sum when the first weight sum is the same as the second weight sum as a predicted volume value, thereby calculating and acquiring the predicted integral dose volume histogram.
It can be understood that, by calculating the difference between the dose values corresponding to the first weight sum and the second weight sum as the dose difference value, the dose difference value between the reference dose volume histogram and the actual dose reference histogram can be accurately calculated, the predicted dose value is calculated by the dose difference value, and the predicted integral dose volume histogram is accurately calculated and obtained by using the weight sum of the first weight sum and the second weight sum as the predicted volume value, thereby improving the calculation efficiency of the overall predicted integral dose volume histogram.
Preferably, after the calculating to obtain the predicted integral dose volume histogram, the method further comprises:
and respectively carrying out reduction operation on the predicted volume value and the predicted dose value according to the preset volume value and the preset dose value of the structure to be predicted, thereby obtaining a predicted integral dose volume histogram reduced to an absolute value.
It can be understood that the predicted volume value and the predicted dose value are respectively restored by the preset volume value and the preset dose value of the structure to be predicted, so that a predicted integral dose volume histogram restored to an absolute value is accurately obtained, the intermediate calculation complexity is simplified, the modeling process is avoided, and the calculation efficiency and accuracy are improved.
Correspondingly, the invention also provides a dose prediction device based on radiotherapy, which comprises an acquisition module, a projection weight module, a histogram module and a prediction module;
The acquisition module is used for acquiring an original integral dose volume histogram of a structure to be predicted, and acquiring reference dose distribution and actual dose distribution according to a preset measurement plane;
The projection weight module is used for acquiring the projection weight distribution of the structure to be predicted on the preset measurement plane according to the preset measurement plane and the control point parameters, wherein the control point parameters are acquired by a medical linear accelerator;
the histogram module is used for calculating and obtaining a reference dose volume histogram and an actual dose volume histogram according to the projection weight distribution, the original integral dose volume histogram, the reference dose distribution and the actual dose distribution;
the prediction module is used for calculating a dose difference value of the reference dose volume histogram and the actual dose volume histogram based on projection, and calculating and obtaining a predicted integral dose volume histogram according to the dose difference value so as to complete the prediction of the dose.
Preferably, the device also comprises a normalization module;
And the normalization module is used for respectively carrying out normalization operation on the volume value and the dose value of the original integral dose volume histogram according to the preset volume value and the preset dose value of the structure to be predicted, so as to obtain a normalized original integral dose volume histogram.
Preferably, the device also comprises a reduction module;
And the reduction module is used for respectively carrying out reduction operation on the predicted volume value and the predicted dose value according to the preset volume value and the preset dose value of the structure to be predicted, so as to obtain a predicted integral dose volume histogram reduced to an absolute value.
Drawings
FIG. 1 is a flowchart showing steps of a radiation therapy-based dose prediction method according to an embodiment of the present invention;
FIG. 2 is a schematic diagram of a beam source of a linear accelerator for traditional Chinese medicine in a dose prediction method based on radiation therapy according to an embodiment of the present invention;
FIG. 3 is a flowchart showing steps for calculating a projection-based dose volume histogram in a radiation therapy-based dose prediction method according to an embodiment of the present invention;
FIG. 4 is a flowchart showing the steps of calculating a predicted integral dose volume histogram in a radiation therapy-based dose prediction method according to an embodiment of the present invention;
Fig. 5 is a schematic structural diagram of a radiation therapy-based dose prediction device according to an embodiment of the present invention.
Detailed Description
The following description of the embodiments of the present invention will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present invention, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
Example 1
Referring to fig. 1, a dose prediction method based on radiation therapy according to an embodiment of the present invention includes the following steps S101 to S104:
S101, acquiring an original integral dose volume histogram of a structure to be predicted, and acquiring a reference dose distribution and an actual dose distribution according to a preset measurement plane.
Preferably, after the acquiring the original integral dose volume histogram of the structure to be predicted, the method further includes:
And respectively carrying out normalization operation on the volume value and the dose value of the original integral dose volume histogram according to the preset volume value and the preset dose value of the structure to be predicted, thereby obtaining a normalized original integral dose volume histogram.
In this embodiment, a normalized raw integral dose volume histogram DVH plan of the anatomy S to be predicted, including but not limited to the irradiated target volume, brain stem, spinal cord, etc., for analysis as needed in the raw treatment plan is preferably derived by a radiation treatment planning system (TREATMENT PLANNINGSYSTEM, TPS) or third-party independent dose verification software. In this embodiment, the normalized raw integrated dose volume histogram is obtained by dividing the volume value V plan of the raw integrated dose volume histogram by the volume value V plan,max of the anatomy to be predicted S and dividing the dose value D plan of the raw integrated dose volume histogram by the maximum dose value D plan,max in the raw treatment plan.
It can be understood that the normalized operation is performed on the volume value and the dose value of the integral dose volume histogram through the preset volume value and the preset dose value of the structure to be predicted, so that the normalized original integral dose volume histogram can avoid errors in the calculation process caused by data of different magnitudes, and the calculation accuracy is improved.
Further, in the present embodiment, the reference dose distribution and the actual dose distribution are obtained by transplanting the target treatment plan to a phantom of an electronic portal imaging system (EPID) by a radiation treatment planning system or a third party independent dose checking software, calculating the reference dose distribution D ref of the EPID measurement plane under ideal conditions, and executing the target treatment plan, and obtaining the actual dose distribution D eva of the medical linac executing the plan by EPID measurement.
S102, acquiring projection weight distribution of the structure to be predicted on the preset measurement plane according to the preset measurement plane and control point parameters, wherein the control point parameters are acquired through a medical linear accelerator.
The medical linear accelerator is used for accelerating electrons by utilizing a microwave electromagnetic field and has an accelerating device with a linear motion orbit, is used for the radiotherapy of tumors or other focus of a patient, can generate high-energy X-rays and electron beams, and has the characteristics of high dosage rate, short irradiation time, large irradiation field, good dosage uniformity and stability, small penumbra area and the like. The control point parameters are obtained according to a plan file (generally a standardized Dicom file) of the radiation treatment plan in the medical linac, and also can be obtained according to a log file when the medical linac executes, and the control point parameters are specific accelerator equipment parameters describing the medical linac when executing the treatment plan.
Preferably, the control point parameters comprise the total number of control points of the medical linear accelerator, the arm support (Gantry) angle of each control point and the beam-out jump number proportion of each control point.
It can be understood that the control point parameters are determined by the arm support angle and other data of the execution control point of the medical linear accelerator, so that the projection weight distribution can be accurately calculated, and complex data required by modeling is not required. Meanwhile, the control point parameters are the total number of control points for the medical linear accelerator to execute the treatment plan and the boom (Gantry) angle of each control point (the boom angle is used for determining the position of the accelerator source, and the medical linear accelerator rotates around an isocenter when executing the plan), and the beam-out hop count ratio of each control point is equal to that of each control point.
Specifically, the preset measurement plane is divided into a plurality of measurement points, the track length of the straight line corresponding to each measurement point passing through the structure to be predicted is respectively obtained according to the straight lines determined by each measurement point and the beam outlet source of the linear accelerator, and the projection weight distribution of each measurement point is respectively calculated and obtained according to each measurement point, the track length corresponding to each measurement point, the total number of control points and the beam outlet hop count proportion of each control point. The specific calculation formula is as follows:
Where (i, j) is the ith row and jth column measurement points of the measurement plane, C is the total number of planned control points, PM p is the number of hops (MU) the p-th control point exits the beam, and L is the track length through the anatomical structure S as determined by the line from the source to the measurement point (i, j), as shown in fig. 2.
It can be understood that by dividing a preset measurement plane, the obtained straight lines determined by each measurement point and the beam outlet source of the linear accelerator are used for obtaining the track length corresponding to each measurement point, and the structure projection weight distribution of the structure to be predicted on the measurement plane can be accurately obtained according to the execution control point parameters of the linear accelerator, so that the prediction calculation process is simplified.
S103, calculating and acquiring a reference dose volume histogram and an actual dose volume histogram based on projection according to the projection weight distribution, the original integral dose volume histogram, the reference dose distribution and the actual dose distribution.
As a preferred solution, referring to fig. 3, step S103 specifically includes the following steps S201 to S204:
S201, acquiring and adding projection weights of the measurement points larger than 0 in the projection weight distribution to obtain the total weight of the measurement points. The specific calculation formula is as follows:
N= Σ ijWij, where W ij >0, N is the total weight of the measurement point.
S202, respectively carrying out normalization operation on the reference dose distribution and the actual dose distribution according to a preset dose value.
In the present embodiment, it is preferable to select the maximum dose value of the reference dose distribution D ref as the dose normalization value D max. Taking the reference dose distribution as an example, the dose values D ij in the reference dose distribution D ref are normalized to D ij'＝Dij/Dmax, resulting in a normalized reference dose distribution D ref'. Similarly, for the normalization operation of the actual dose distribution D eva, the dose values in the actual dose distribution D eva are normalized to D ij'＝Dij/Dmax, thereby obtaining a normalized actual dose distribution D eva'.
S203, according to a dose value interval in the original integral dose volume histogram, respectively adding projection weights of a normalized reference dose distribution and a normalized actual dose distribution, which are larger than a measurement point corresponding to the dose value interval, to obtain a first weight sum and a second weight sum of each dose value interval, wherein the first weight sum is a weight sum of the reference dose distribution, and the second weight sum is a weight sum of the actual dose distribution.
In this embodiment, preferably, according to the dose interval D plan in the original integral dose volume histogram DVH plan being a statistical dose value interval, the first weight sum N k1 corresponding to each measurement point of the reference dose distribution D ref 'with a dose greater than D plan,k of the kth dose interval after statistical normalization, and the second weight sum N k2 corresponding to each measurement point of the actual dose distribution D eva' with a dose greater than D plan,k of the kth dose interval after statistical normalization.
S204, respectively carrying out normalization processing on the first weight sum and the second weight sum according to the total weight of the measuring points, and respectively obtaining a reference dose volume histogram and an actual dose reference histogram based on projection according to the normalized first weight sum and second weight sum.
In this embodiment, according to the total weight of the measurement points, the first weight sum and the second weight sum are normalized by N k'＝Nk/N, so as to obtain a projection-based reference dose volume histogram and an actual dose reference histogram.
It can be understood that the total weight of the measurement points with the projection weight greater than zero is obtained and added through statistics of the projection weight distribution, the projection weight of the measurement points corresponding to the interval greater than the dose value is added through normalized reference dose distribution and normalized actual dose distribution, so as to obtain a first weight sum and a second weight sum, and the first weight sum and the second weight sum are respectively normalized through the total weight of the measurement points, so that a projection-based reference dose volume histogram DVH ref and an actual dose reference histogram DVH eva are accurately obtained.
And S104, calculating a dose difference value of the reference dose volume histogram and the actual dose volume histogram based on projection, and calculating and obtaining a predicted integral dose volume histogram according to the dose difference value, thereby completing the prediction of the dose.
As a preferred solution, referring to fig. 4, step S104 specifically includes the following steps S301 to S302:
S301, calculating the difference of the corresponding dose values when the first weight sum and the second weight sum are the same according to the first weight sum and the second weight sum, and taking the difference as a dose difference value.
In the present embodiment, by comparing the projection-based reference dose volume histogram DVH ref and the actual dose volume histogram DVH eva, the difference in dose value between DVH ref and DVH eva at the same N k' is calculated as the dose difference value PD k.
S302, calculating and obtaining a predicted dose value according to the dose difference value and the original integral dose volume histogram, and taking the weight sum when the first weight sum is the same as the second weight sum as a predicted volume value, so as to calculate and obtain the predicted integral dose volume histogram.
In this embodiment, according to the dose interval D plan,k and the dose difference value PD k in the original integrated dose volume histogram, the predicted dose value D pre,k is obtained by calculating through D pre,k＝Dplan,k+PDk, and the same N k 'corresponding to the DVH ref and the same N k' corresponding to the DVH eva are used as the predicted volume value V pre,k, so as to obtain the predicted integrated dose volume histogram according to the predicted dose value D pre,k and the predicted volume value V pre,k.
It can be understood that, by calculating the difference between the dose values corresponding to the first weight sum and the second weight sum as the dose difference value, the dose difference value between the reference dose volume histogram and the actual dose reference histogram can be accurately calculated, the predicted dose value is calculated by the dose difference value, and the predicted integral dose volume histogram is accurately calculated and obtained by using the weight sum of the first weight sum and the second weight sum as the predicted volume value, thereby improving the calculation efficiency of the overall predicted integral dose volume histogram.
Preferably, after the calculating to obtain the predicted integral dose volume histogram, the method further comprises:
and respectively carrying out reduction operation on the predicted volume value and the predicted dose value according to the preset volume value and the preset dose value of the structure to be predicted, thereby obtaining a predicted integral dose volume histogram reduced to an absolute value.
In the present embodiment, the predicted volume value V pre and the predicted dose value D pre are subjected to a reduction operation by the volume value V plan,max of the anatomy to be predicted S in step S101 and the maximum dose value D plan,max in the original treatment plan. Specifically, the predicted integrated dose volume histogram reduced to an absolute value is obtained by multiplying the predicted volume value V pre by the volume value V plan,max of the anatomy S to be predicted and by multiplying the predicted dose value D pre by the maximum dose value D plan,max in the original treatment plan.
It can be understood that the predicted volume value and the predicted dose value are respectively restored by the preset volume value and the preset dose value of the structure to be predicted, so that a predicted integral dose volume histogram restored to an absolute value is accurately obtained, the intermediate calculation complexity is simplified, the modeling process is avoided, and the calculation efficiency and accuracy are improved.
As a preferred solution of this embodiment, the above steps are repeated, and calculation and acquisition of the prediction integral dose volume histogram can be performed on other anatomical structures to be analyzed, so as to obtain dose predictions of other anatomical structures.
The implementation of the embodiment has the following effects:
Compared with the prior art, the embodiment of the invention can acquire the original integral dose volume histogram of the structure to be predicted under the original treatment plan by the existing dose distribution comparison analysis method, acquire the reference dose distribution and the actual dose distribution according to the measurement plane, and acquire the projection weight distribution of the structure to be predicted on the preset measurement plane according to the control point parameter, thereby ensuring that the reference dose volume histogram and the actual dose volume histogram acquired by calculation can be based on the projection weight, improving the accuracy of the dose volume histogram, accurately calculating the predicted integral dose volume histogram by the dose difference value between the reference dose volume histogram and the actual dose volume histogram, avoiding the existing process of complex modeling and model test, and improving the efficiency of dose prediction.
Example two
Accordingly, referring to fig. 5, the invention further provides a dose prediction device based on radiotherapy, which comprises an acquisition module 401, a projection weight module 402, a histogram module 403 and a prediction module 404.
The acquiring module 401 is configured to acquire an original integral dose volume histogram of a structure to be predicted, and acquire a reference dose distribution and an actual dose distribution according to a preset measurement plane.
The embodiment of the invention further comprises a normalization module 4011, wherein the normalization module 4011 is used for performing normalization operation on the volume value and the dose value of the original integral dose volume histogram according to the preset volume value and the preset dose value of the structure to be predicted, so as to obtain a normalized original integral dose volume histogram.
The projection weight module 402 is configured to obtain a projection weight distribution of the structure to be predicted on the preset measurement plane according to the preset measurement plane and a control point parameter, where the control point parameter is obtained by a medical linac.
Preferably, the control point parameters comprise the total number of control points of the medical linear accelerator, the arm support angles of all the control points and the beam-out jump number proportion of all the control points.
The projection weight module 402 is specifically configured to divide the preset measurement plane into a plurality of measurement points, respectively obtain the track length of the straight line corresponding to each measurement point passing through the structure to be predicted according to the straight lines determined by each measurement point and the beam-emitting source of the linac, and respectively calculate and obtain the projection weight distribution of each measurement point according to each measurement point, the track length corresponding to each measurement point, the total number of control points, and the beam-emitting hop ratio of each control point.
The histogram module 403 is configured to calculate and obtain a reference dose volume histogram and an actual dose volume histogram according to the projection weight distribution, the raw integral dose volume histogram, the reference dose distribution and the actual dose distribution.
The histogram module 403 is specifically configured to obtain and add projection weights of measurement points greater than 0 in the projection weight distribution to obtain total weights of measurement points, normalize the reference dose distribution and the actual dose distribution according to preset dose values, respectively normalize the reference dose distribution and the actual dose distribution according to dose value intervals in the original integrated dose volume histogram, respectively add projection weights of measurement points greater than the dose value intervals in the normalized reference dose distribution and the normalized actual dose distribution to obtain a first weight sum and a second weight sum of each dose value interval, respectively, wherein the first weight sum is a weight sum of the reference dose distribution, the second weight sum is a weight sum of the actual dose distribution, respectively normalize the first weight sum and the second weight sum according to the total weights of the measurement points, and respectively obtain a reference dose volume histogram and an actual dose reference histogram based on projection according to the normalized first weight sum and the normalized second weight sum.
The prediction module 404 is configured to calculate a dose difference value of the reference dose volume histogram and the actual dose volume histogram based on the projection, and calculate and obtain a predicted integral dose volume histogram according to the dose difference value, so as to complete the prediction of the dose.
Preferably, the prediction module 404 is specifically configured to calculate, as a dose difference value, a difference between dose values corresponding to the first weight sum and the second weight sum when the first weight sum and the second weight sum are the same, calculate, as a predicted dose value, according to the dose difference value and the original integrated dose volume histogram, and calculate, as a predicted volume value, a weight sum when the first weight sum and the second weight sum are the same, thereby calculating, as a predicted integrated dose volume histogram.
The method also comprises a reduction module 4041, wherein the reduction module 4041 is used for respectively carrying out reduction operation on the predicted volume value and the predicted dose value according to the preset volume value and the preset dose value of the structure to be predicted, so as to obtain a predicted integral dose volume histogram reduced to an absolute value.
It will be clear to those skilled in the art that, for convenience and brevity of description, reference may be made to the corresponding process in the foregoing method embodiment for the specific working process of the above-described apparatus, which is not described herein again.
The implementation of the above embodiment has the following effects:
Compared with the prior art, the embodiment of the invention can acquire the original integral dose volume histogram of the structure to be predicted by the existing dose distribution comparison analysis method, acquire the reference dose distribution and the actual dose distribution according to the measurement plane, and acquire the projection weight distribution of the structure to be predicted on the preset measurement plane according to the control point parameter, thereby ensuring that the reference dose volume histogram and the actual dose volume histogram acquired by calculation can be based on the projection weight, improving the accuracy of the dose volume histogram, accurately calculating the predicted integral dose volume histogram by the dose difference value between the reference dose volume histogram and the actual dose volume histogram, avoiding the existing complex modeling and model test process and improving the dose prediction efficiency.
The foregoing embodiments have been provided for the purpose of illustrating the general principles of the present invention, and are not to be construed as limiting the scope of the invention. It should be noted that any modifications, equivalent substitutions, improvements, etc. made by those skilled in the art without departing from the spirit and principles of the present invention are intended to be included in the scope of the present invention.
Claims (10)
1. A radiation therapy-based dose prediction method, comprising:
Acquiring an original integral dose volume histogram of a structure to be predicted, and acquiring reference dose distribution and actual dose distribution according to a preset measurement plane;
acquiring projection weight distribution of the structure to be predicted on the preset measurement plane according to the preset measurement plane and control point parameters, wherein the control point parameters are acquired by a medical linear accelerator;
calculating and acquiring a reference dose volume histogram and an actual dose volume histogram based on projection according to the projection weight distribution, the original integral dose volume histogram, the reference dose distribution and the actual dose distribution;
And calculating a dose difference value of the projection-based reference dose volume histogram and the actual dose volume histogram, and calculating and acquiring a predicted integral dose volume histogram according to the dose difference value, thereby completing the prediction of the dose.
2. The radiation therapy-based dose prediction method of claim 1, wherein the control point parameters include a total number of control points of the medical linac, arm support angles of the respective control points, and a ratio of beam-out hops of the respective control points.
3. A dose prediction method based on radiation therapy according to claim 2, wherein the obtaining, according to the preset measurement plane and the control point parameter, a projection weight distribution of the structure to be predicted in the preset measurement plane is specifically:
dividing the preset measurement plane into a plurality of measurement points, respectively obtaining the track length of the straight line corresponding to each measurement point passing through the structure to be predicted according to the straight lines determined by each measurement point and the beam outlet source of the linear accelerator, and respectively calculating and obtaining the projection weight distribution of each measurement point according to each measurement point, the track length corresponding to each measurement point, the total number of control points and the beam outlet hop count proportion of each control point.
4. A radiation therapy-based dose prediction method as defined in claim 3, further comprising, after said obtaining an original integrated dose volume histogram of the structure to be predicted:
And respectively carrying out normalization operation on the volume value and the dose value of the original integral dose volume histogram according to the preset volume value and the preset dose value of the structure to be predicted, thereby obtaining a normalized original integral dose volume histogram.
5. A radiation therapy-based dose prediction method as defined in claim 4, wherein said computing obtains a projection-based reference dose volume histogram and an actual dose volume histogram from said projection weight distribution, said raw integral dose volume histogram, said reference dose distribution and said actual dose distribution, in particular:
obtaining and adding projection weights of measuring points larger than 0 in the projection weight distribution to obtain total weights of the measuring points;
Respectively carrying out normalization operation on the reference dose distribution and the actual dose distribution according to a preset dose value;
According to a dose value interval in the original integral dose volume histogram, respectively adding projection weights of a normalized reference dose distribution and a normalized actual dose distribution, which are larger than a measuring point corresponding to the dose value interval, to respectively obtain a first weight sum and a second weight sum of each dose value interval, wherein the first weight sum is a weight sum of the reference dose distribution, and the second weight sum is a weight sum of the actual dose distribution;
And respectively carrying out normalization processing on the first weight sum and the second weight sum according to the total weight of the measuring points, and respectively obtaining a reference dose volume histogram and an actual dose reference histogram based on projection according to the normalized first weight sum and second weight sum.
6. A radiation therapy-based dose prediction method as defined in claim 5, wherein said calculating a dose difference value for said projection-based reference and actual dose volume histograms and calculating a predicted integral dose volume histogram based on said dose difference value comprises:
Calculating the difference of the corresponding dose values when the first weight sum is the same as the second weight sum according to the first weight sum and the second weight sum, and taking the difference as a dose difference value;
And calculating and acquiring a predicted dose value according to the dose difference value and the original integral dose volume histogram, and taking the weight sum when the first weight sum is the same as the second weight sum as a predicted volume value, thereby calculating and acquiring the predicted integral dose volume histogram.
7. A radiation therapy-based dose prediction method as defined in claim 6, further comprising, after said calculating to obtain a predicted integral dose volume histogram:
and respectively carrying out reduction operation on the predicted volume value and the predicted dose value according to the preset volume value and the preset dose value of the structure to be predicted, thereby obtaining a predicted integral dose volume histogram reduced to an absolute value.
8. The dose prediction device based on the radiotherapy is characterized by comprising an acquisition module, a projection weight module, a histogram module and a prediction module;
The acquisition module is used for acquiring an original integral dose volume histogram of a structure to be predicted, and acquiring reference dose distribution and actual dose distribution according to a preset measurement plane;
The projection weight module is used for acquiring the projection weight distribution of the structure to be predicted on the preset measurement plane according to the preset measurement plane and the control point parameters, wherein the control point parameters are acquired by a medical linear accelerator;
the histogram module is used for calculating and obtaining a reference dose volume histogram and an actual dose volume histogram according to the projection weight distribution, the original integral dose volume histogram, the reference dose distribution and the actual dose distribution;
the prediction module is used for calculating a dose difference value of the reference dose volume histogram and the actual dose volume histogram based on projection, and calculating and obtaining a predicted integral dose volume histogram according to the dose difference value so as to complete the prediction of the dose.
9. The radiation therapy-based dose prediction device of claim 8, further comprising a normalization module;
And the normalization module is used for respectively carrying out normalization operation on the volume value and the dose value of the original integral dose volume histogram according to the preset volume value and the preset dose value of the structure to be predicted, so as to obtain a normalized original integral dose volume histogram.
10. The radiation therapy-based dose prediction device of claim 8, further comprising a reduction module;
and the reduction module is used for obtaining a predicted integral dose volume histogram reduced to an absolute value according to the preset volume value and the preset dose value of the structure to be predicted.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202210496970.XA CN115025403B (en) | 2022-05-07 | 2022-05-07 | A method and device for predicting dose based on radiotherapy |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202210496970.XA CN115025403B (en) | 2022-05-07 | 2022-05-07 | A method and device for predicting dose based on radiotherapy |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN115025403A CN115025403A (en) | 2022-09-09 |
| CN115025403B true CN115025403B (en) | 2025-02-25 |
Family
ID=83119313
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202210496970.XA Active CN115025403B (en) | 2022-05-07 | 2022-05-07 | A method and device for predicting dose based on radiotherapy |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN115025403B (en) |
Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN105447330A (en) * | 2015-12-30 | 2016-03-30 | 上海联影医疗科技有限公司 | Weight adjustment method and weight adjustment device of intensity-modulated radiation therapy |
| CN108568037A (en) * | 2018-03-01 | 2018-09-25 | 深圳市医诺智能科技发展有限公司 | Ejected wave knife treatment plan parameters extraction method and computer readable storage medium |
Family Cites Families (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| DE102017202930A1 (en) * | 2017-02-23 | 2017-04-13 | Carl Zeiss Smt Gmbh | Method for controlling a lighting dose of illumination of an object field of a projection exposure apparatus and projection exposure apparatus for carrying out the method |
-
2022
- 2022-05-07 CN CN202210496970.XA patent/CN115025403B/en active Active
Patent Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN105447330A (en) * | 2015-12-30 | 2016-03-30 | 上海联影医疗科技有限公司 | Weight adjustment method and weight adjustment device of intensity-modulated radiation therapy |
| CN108568037A (en) * | 2018-03-01 | 2018-09-25 | 深圳市医诺智能科技发展有限公司 | Ejected wave knife treatment plan parameters extraction method and computer readable storage medium |
Also Published As
| Publication number | Publication date |
|---|---|
| CN115025403A (en) | 2022-09-09 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| US11266858B2 (en) | Systems, devices, and methods for quality assurance of radiation therapy | |
| US10369383B2 (en) | Time-resolved pre-treatment portal dosimetry systems, devices, and methods | |
| CN104548372B (en) | The dosage determining device of radiotherapy | |
| US11020615B2 (en) | Computing radiotherapy dose distribution | |
| US11191979B2 (en) | Portal dosimetry systems, devices, and methods | |
| JP7485331B2 (en) | Methods for real-time image-guided radiation therapy - Patents.com | |
| Knopf et al. | Required transition from research to clinical application: report on the 4D treatment planning workshops 2014 and 2015 | |
| CN111001097A (en) | Radiotherapy dose evaluation system, device and storage medium | |
| US20240173571A1 (en) | Systems and methods for dose verification | |
| CN117323584A (en) | Planning and adjusting method for radiation therapy, radiation therapy system and related device | |
| US9364686B2 (en) | Planning a treatment beam aimed at one or more target regions | |
| US10881877B2 (en) | Systems and methods for evaluating motion tracking for radiation therapy | |
| CN115025403B (en) | A method and device for predicting dose based on radiotherapy | |
| US12138479B2 (en) | Independent stereotactic radiotherapy dose calculation and treatment plan verification | |
| Li et al. | Monte Carlo as a QA tool for advanced radiation therapy | |
| CN121266024A (en) | AI-based precise X-ray radiation dose measurement system | |
| CN117727423A (en) | Particle beam range real-time verification method and system | |
| CN115154926A (en) | Data processing method, device and equipment |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |