Real-time radiation dose monitoring method in radiotherapy based on spiral tomography radiotherapy equipment

Abstract

The invention provides a real-time radiation dose monitoring method in radiotherapy based on spiral tomography radiotherapy equipment. The real-time radiation dose monitoring method comprises the following steps: acquiring radiation dose data of a patient and a CT image of the patient, which are acquired by a detector in real time, and performing registration; using a back-propagation algorithm to reversely calculate the initial radiation dose of each part in the body of the patient, and obtaining the final radiation dose of each part in the body of the patient through the initial radiation dose of each part in the body of the patient; generating a dose heat map in the body of the patient according to the final radiation dose of each part in the body of the patient; obtaining an optimal dose distribution scheme meeting the treatment requirement according to the dose heat map; the method has the beneficial effects that reverse reconstruction is carried out through dose data collected in real time by the spiral tomography radiotherapy equipment in the treatment process in combination with the CT image of the patient, so that a real-time dose heat map is generated, dose distribution in the body of the patient is visually displayed, a doctor is helped to adjust a treatment scheme in real time in the treatment process, and the treatment precision and safety are improved.

Description

Technical Field

[0001] The present invention relates to the technical field of radiotherapy, and particularly to a method for real-time radiation dose monitoring during radiotherapy based on a helical tomotherapy device. Background Art

[0002] In the field of radiotherapy, accurate dose distribution and real-time monitoring are crucial for ensuring treatment efficacy and patient safety. Traditional radiotherapy methods usually rely on a treatment planning system (TPS) to pre-calculate and plan the patient's dose distribution and perform treatment according to this plan. However, during the treatment, changes in the patient's body position, internal structure, and tissue density may cause a deviation between the actual dose distribution and the plan. If this deviation is not detected and adjusted in a timely manner, it may affect the irradiation accuracy of the tumor or cause unnecessary radiation to normal tissues, thereby affecting the patient's treatment efficacy and side effect risk. Currently, the dose monitoring and visualization technologies in radiotherapy mainly have the following problems:

[0003] 1. Pre-calculation and actual deviation: In traditional treatments, the dose distribution is pre-calculated based on the patient's images obtained by CT scanning. However, during the treatment, the patient's body position may change, or due to changes in the tumor position, there may be a deviation between the actual dose distribution and the plan. Although some systems can perform image guidance during the treatment, traditional image guidance methods mainly rely on CT or X-ray images and fail to provide accurate real-time dose distribution feedback.

[0004] 2. Lack of dose distribution visualization: Although modern treatment planning systems can accurately calculate the treatment dose, during actual treatment, the lack of an effective real-time dose feedback mechanism makes it difficult for doctors to timely detect the non-uniformity of the dose distribution or other potential problems. Existing dose assessment methods mainly rely on planned images and pre-determined dose calculations and lack real-time monitoring and visualization functions.

[0005] 3. Insufficient real-time dose monitoring technology: Although some high-end radiotherapy devices, such as the CyberKnife or Tomo device, have certain real-time image guidance functions, they do not fully combine real-time dose data for real-time feedback and visualization. Most of the image data collected during the treatment is used for target area positioning and irradiation range assessment, rather than directly for evaluating and optimizing the dose distribution during the treatment process.

[0006] 4. Complexity and challenges of dose reconstruction: Traditional dose reconstruction methods usually require additional radiation exposure or relatively complex physical models to deduce the actual dose distribution. These methods either increase the patient's radiation dose or cannot achieve real-time feedback and optimization.

[0007] Therefore, there are obvious deficiencies in the prior art, mainly reflected in the lack of real-time monitoring and visualization of dose distribution. Even modern radiotherapy equipment, although it can provide high-precision image data and treatment plans, still lacks the technical means to combine the dose data collected during the actual treatment process with the CT images of the patient's body for real-time dose reconstruction and visualization. Summary of the Invention

[0008] In view of the above-mentioned deficiencies of the prior art, the purpose of the present invention is to provide a method for real-time radiation dose monitoring during radiotherapy based on a helical tomotherapy device, which is used to solve the problem that the existing radiotherapy methods fail to provide accurate dose distribution feedback in real time.

[0009] To achieve the above purpose and other related purposes, the present invention provides the following technical solutions:

[0010] A method for real-time radiation dose monitoring during radiotherapy based on a helical tomotherapy device, the method includes the following steps: obtaining the radiation dose data of the patient collected in real time by the detector in the helical tomotherapy device during radiotherapy, and after obtaining the CT image of the patient, registering the radiation dose data collected by the detector and the CT image, wherein the CT image is a three-dimensional anatomical image of the patient obtained by a CT scanning device; using the backpropagation algorithm to combine the registered radiation dose data collected by the detector with each voxel in the CT image, and inversely calculating the preliminary radiation dose of each part in the patient's body according to the combination result;

[0011] Iteratively optimizing the preliminary radiation dose of each part in the patient's body, and obtaining the final radiation dose of each part in the patient's body according to the iterative optimization result; visualizing the final radiation dose of each part in the patient's body, generating a dose heat map of the patient's body according to the visualization result, wherein different regions of dose intensity are marked by colors in the dose heat map; iteratively optimizing the parameters of the preset radiotherapy plan according to the dose heat map of the patient's body, and obtaining an optimal dose distribution plan that meets the treatment requirements according to the iterative optimization result.

[0012] In an embodiment of the present invention, the registering of the radiation dose data collected by the detector and the CT image includes: using a registration algorithm to align the MVCT image with the CT image, wherein the MVCT image is composed of the radiation dose data of the patient collected in real time by the detector.

[0013] In an embodiment of the present invention, the use of the backpropagation algorithm combines the radiation dose data collected by the registered detector with each voxel in the CT image, and inversely calculates the preliminary radiation dose of each part in the patient's body according to the combination result, including: inversely calculating the preliminary radiation dose of each part in the patient's body according to the following formula: D = A -1 M; where D is the reconstructed three-dimensional dose distribution matrix, that is, the preliminary radiation dose of each part in the patient's body; A is a matrix describing the position of the detector and the ray propagation path, and this matrix contains geometric information and a radiation propagation model; M is the radiation dose data of the patient collected in real time during radiotherapy.

[0014] In an embodiment of the present invention, the iterative optimization of the preliminary radiation dose of each part in the patient's body is performed, and the final radiation dose of each part in the patient's body is obtained according to the iterative optimization result, including: determining the final radiation dose of each part in the patient's body according to the following formula: D k+1 = d k + α(M - AD K ); where D k+1 is the dose distribution of the (k + 1)-th iteration, that is, the final radiation dose of each part in the patient's body; D k is the dose distribution of the k-th iteration; α is the step size factor.

[0015] In an embodiment of the present invention, after visualizing the final radiation dose of each part in the patient's body and generating a dose heat map of the patient's body according to the visualization result, before iteratively optimizing the parameters of the preset radiotherapy plan according to the dose heat map of the patient's body and obtaining an optimal dose distribution scheme that meets the treatment requirements, it further includes: comparing the actual radiation dose distribution obtained by inverse reconstruction with the dose distribution preset in the radiotherapy plan, determining the deviation between the two according to the comparison result, and determining a dose correction factor according to the deviation between the two, where the actual radiation dose distribution obtained by inverse reconstruction is displayed in the dose heat map of the patient's body.

[0016] In an embodiment of the present invention, the determination of the dose correction factor according to the deviation between the two includes: the deviation between the two includes changes in tissue density, and a dose correction factor for each part in the patient's body is calculated using a physical model according to the changes in tissue density, where the dose correction factor is a parameter based on density changes.

[0017] In an embodiment of the present invention, iteratively optimizing the parameters of a preset radiotherapy plan according to the dose heat map in the patient's body, and obtaining an optimal dose distribution plan that meets the treatment requirements according to the iterative optimization result, including: determining an objective function between the actual radiation dose distribution and the preset dose distribution; and minimizing the objective function, and obtaining an optimal dose distribution plan that meets the treatment requirements according to the minimization process.

[0018] In an embodiment of the present invention, determining the objective function between the actual radiation dose distribution and the preset dose distribution; and minimizing the objective function, and obtaining an optimal dose distribution plan that meets the treatment requirements according to the minimization process, including: determining the objective function between the actual radiation dose distribution and the preset dose distribution according to the following formula: where F(D) is the objective function between the actual radiation dose distribution and the preset dose distribution; n is the total number of voxels in the dose distribution; D(i) is the dose value of the i-th voxel; D target (i) is the preset dose distribution in the treatment target area; D measured (i) is the actually measured radiation dose distribution; determining the optimal dose distribution plan that meets the treatment requirements according to the following formula: where D k+1 is the optimal dose distribution plan that meets the treatment requirements; γ is the learning rate; is the gradient of the objective function with respect to the dose distribution.

[0019] As described above, a real-time radiation dose monitoring method during radiotherapy based on a helical tomotherapy device of the present invention has the following beneficial effects:

[0020] 1. Real-time monitoring of dose distribution and improvement of treatment accuracy: The present invention can obtain the dose distribution data in the patient's body in real time during the treatment process. This real-time monitoring can promptly detect dose deviations caused by patient position changes or other factors. Doctors can make timely adjustments based on the real-time feedback, thereby significantly improving the treatment accuracy. Traditional treatment methods usually rely on the dose plan before treatment and cannot respond to the influence of factors such as patient position changes in real time. The present invention can ensure that the optimal dose distribution is maintained throughout the treatment process.

[0021] 2. Reduction of radiation burden and improvement of patient safety: Traditional dose monitoring and reconstruction methods usually require additional radiation exposure, increasing the patient's radiation exposure. The present invention uses a back-projection algorithm and the real-time detection data of the helical tomotherapy device to accurately calculate the actual dose distribution in the patient's body without additional radiation exposure. This technology not only reduces the patient's radiation burden but also enables a more efficient and safer treatment process, effectively protecting the patient's health.

[0022] 3. Improve the treatment effect and reduce side effects: By displaying the dose heat map in the patient's body in real time, doctors can intuitively see the dose distribution in each area, adjust the treatment plan in a timely manner, and avoid side effects caused by dose deviation. Especially when treating tumors, it can accurately control the radiation dose in the tumor area while avoiding excessive irradiation of adjacent sensitive tissues, thus effectively reducing side effects during the treatment process and improving the treatment effect and the patient's quality of life. BRIEF DESCRIPTION OF THE DRAWINGS

[0023] Figure 1 It shows a flowchart of a real-time radiation dose monitoring method during radiotherapy based on a helical tomotherapy device in the first embodiment of the present invention;

[0024] Figure 2 It shows a flowchart of a real-time radiation dose monitoring method during radiotherapy based on a helical tomotherapy device in the second embodiment of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0025] The following specific examples illustrate the embodiments of the present invention, and those skilled in the art can easily understand other advantages and effects of the present invention from the content disclosed in this specification. It should be noted that, without conflict, the following embodiments and the features in the embodiments can be combined with each other.

[0026] The first embodiment of the present invention relates to a real-time radiation dose monitoring method during radiotherapy based on a helical tomotherapy device, and the process is as Figure 1 shown as follows:

[0027] Step 101, obtain the radiation dose data of the patient collected in real time by the detector in the helical tomotherapy device during radiotherapy, and after obtaining the CT image of the patient, register the radiation dose data collected by the detector and the CT image.

[0028] Specifically, the helical tomotherapy device is hereinafter referred to as the Tomo device. The detector equipped with the Tomo device can continuously collect data on the ray beam penetrating the patient's body during treatment and provide real-time radiation dose information. Based on the data collected by the detector, the actual dose distribution in the patient's body can be inversely calculated; moreover, the detector in the Tomo device can not only collect data in real time, but also has high sensitivity and a relatively high sampling frequency to ensure that the dose data of each irradiation point can be accurately obtained during treatment; obtain the three-dimensional anatomical image of the patient through the CT scanning device as the basis for dose reconstruction. The different tissue densities (such as bones, muscles, tumors, etc.) in the CT image provide important parameters for dose calculation.

[0029] More specifically, registering the radiation dose data collected by the detector with the CT image enables the dose data to be accurately mapped to specific locations within the patient's body. This step specifically includes: aligning the MVCT image with the CT image using a registration algorithm, where the MVCT image is composed of the radiation dose data of the patient collected in real time by the detector; it should be noted that the calculation of the dose data itself is carried out in the coordinate system of the MVCT, so only the registration of the MVCT image and the CT image is required. Align the MVCT image collected by the Tomo device with the CT image to ensure that the two can be compared in the same spatial coordinate system; the registration algorithm is the mutual information method based on image intensity and the registration method based on gradient. Adjust the MVCT image through operations such as translation and scaling until it is aligned with the CT image; after the registered MVCT image and the CT image are aligned, the dose image can correspond to the anatomical structure of the CT image in the same coordinate system.

[0030] Step 102: Use the backpropagation algorithm to combine the registered radiation dose data collected by the detector with each voxel in the CT image, and inversely calculate the preliminary radiation dose of each part in the patient's body based on the combination result.

[0031] Specifically, the backpropagation algorithm is used to combine the dose data collected by the detector with each voxel (pixel point) in the CT image, and inversely calculate the preliminary radiation dose of each part in the patient's body. This process can be modeled using the weighted least squares (WLS) method or Bayesian inference method. The formula is as follows: D = A -1 M; where D is the reconstructed three-dimensional dose distribution matrix, that is, the preliminary radiation dose of each part in the patient's body; A is the matrix describing the detector position and the ray propagation path, which contains geometric information and a radiation propagation model; M is the radiation dose data of the patient collected in real time by the detector during radiotherapy; then, by minimizing the error function in the reconstruction process (such as minimizing the difference between the predicted dose and the actual measurement value), the optimal dose distribution is obtained. That is to say, after calculation using the weighted least squares (WLS) method or Bayesian inference method, multiple solutions will be obtained, and then the optimal dose distribution, that is, the preliminary radiation dose of each part in the patient's body, will be obtained through the error function.

[0032] Step 103: Iteratively optimize the preliminary radiation dose of each part in the patient's body, and obtain the final radiation dose of each part in the patient's body based on the iterative optimization result.

[0033] Specifically, based on the preliminary dose estimation, that is, on the basis of obtaining the preliminary radiation dose of each part in the patient's body, an iterative optimization method (such as the conjugate gradient method, the least squares method, or the regularization method) is used for further optimization. The specific process includes the following steps: Dk+1 = D k + α(M - AD K ); where D k+1 is the dose distribution of the (k + 1)-th iteration, that is, the final radiation dose at each part in the patient's body; D k is the dose distribution of the k-th iteration; α is the step factor; this process will continue to iterate until the dose distribution converges, that is, the error is less than the set threshold, and the threshold in this embodiment is set artificially according to the actual situation.

[0034] Step 104, visualize the final radiation dose at each part in the patient's body, and generate a dose heat map of the patient's body according to the visualization result.

[0035] Specifically, after the dose reconstruction, the final radiation dose at each part in the patient's body is obtained. By visualizing the obtained dose distribution data in the form of a heat map, it is convenient for doctors to view and analyze; in the dose heat map, the dose intensity of different regions is marked by colors, and the depth of the color represents different dose magnitudes; a common heat map color scheme is to use cold colors (such as blue) to represent low-dose regions and warm colors (such as red, yellow) to represent high-dose regions; heat map data format: the dose heat map is a three-dimensional data set, where each voxel (pixel point) contains the corresponding dose value, and this data set can be visualized in three-dimensional space through volume rendering technology to help doctors intuitively understand the dose situation of each part during the treatment process.

[0036] Step 105, iteratively optimize the parameters of the preset radiotherapy plan according to the dose heat map of the patient's body, and obtain the optimal dose distribution plan that meets the treatment requirements according to the iterative optimization result.

[0037] Specifically, first determine the objective function between the actual radiation dose distribution and the preset dose distribution; and perform minimization processing on the objective function, and then obtain the optimal dose distribution plan that meets the treatment requirements according to the minimization processing.

[0038] More specifically, based on the dose heat map generated in real time, doctors can adjust the treatment parameters in real time, such as dose, irradiation angle, irradiation duration, etc., to ensure that the dose distribution in the patient's body meets the expected treatment goal; the optimization algorithm can adopt the method of minimizing the objective function, and continuously adjust the parameters of the radiotherapy plan through iterative calculation to make the final dose distribution most meet the treatment requirements; among them, the optimization algorithm and calculation process:

[0039] Objective function definition: Assume D target (i) is the preset dose distribution of the treatment target area, and D measured (i) is the actually measured radiation dose distribution. The goal is to minimize the difference between them, and the following objective function can be defined: Among them, F(D) is the objective function; n is the total number of voxels in the dose distribution; D(i) is the dose value of the i-th voxel;

[0040] Minimize the objective function: Use the gradient descent method or other optimization algorithms to minimize the objective function to obtain the optimal dose distribution plan. The update formula is: where D k+1 is the optimal dose distribution plan that meets the treatment requirements; γ is the learning rate; is the gradient of the objective function with respect to the dose distribution.

[0041] The second embodiment of the present invention relates to a method for real-time radiation dose monitoring during radiotherapy based on a helical tomotherapy device. The second embodiment is a detailed discussion of the overall first embodiment. The main detailed discussion lies in: In the second embodiment of the present invention, an embodiment is defined, and this embodiment discusses the specific process of obtaining the dose correction factor.

[0042] Please refer to Figure 2 for this embodiment, and the following steps are described as follows:

[0043] Steps 201 to 204 are similar to steps 101 to 104 in the first embodiment and will not be repeated here.

[0044] Step 205: Compare the actual radiation dose distribution obtained by back-projection with the preset dose distribution in the radiotherapy plan, determine the deviation between the two according to the comparison result, and determine the dose correction factor according to the deviation between the two.

[0045] Specifically, during the real-time dose reconstruction process, first collect the radiation dose data during actual treatment through a detector, and perform back-projection in combination with the patient's CT image to obtain the real-time dose distribution in the patient's body. These dose data are compared with the preset dose distribution in the treatment plan, and then the difference between the two is automatically detected and fed back to the doctor, prompting the doctor about possible sources of dose errors (such as equipment position deviation, patient movement, etc.).

[0046] More specifically, for dose distribution difference detection: By comparing the actually reconstructed dose distribution with the preset dose distribution in the treatment plan, the deviation between the two can be identified. If the difference exceeds the preset tolerance range, a potential dose error is considered to exist, and then the doctor is informed through feedback about the possible sources of dose error; The density model used in the treatment plan (usually based on the planning CT images) provides the density information of tissues for calculating the predetermined dose distribution. During the actual treatment process, the patient's body position may change, or the density of tissues (such as changes in tumors or normal tissues) may change, which will all lead to differences between the actual dose distribution and the planned dose distribution;

[0047] CT image registration: During the treatment process, by comparing the CT images in actual treatment with the planning CT images, changes in the patient's body position or structural changes are detected. This process usually uses registration algorithms to align the real-time acquired CBCT (Cone Beam CT) images with the planning CT images used in the treatment plan. Through this registration, it can be calculated whether there are displacements or rotations in various regions of the patient's body; Based on the registered CT images, the impact caused by tissue density changes is calculated. If it is detected that the tissue density (such as tumors or normal tissues) has changed, or the patient's body position has a large deviation, these changes will affect the radiotherapy dose distribution; Density changes: For example, if the density of a tumor or normal tissue changes, then the radiation absorption ability of that region will also change. Tissues with higher density usually absorb more dose. Therefore, the dose for this region needs to be corrected to ensure that the preset dose distribution is not affected; Dose correction factor: For density changes and displacements, the linear weighting method is used to calculate the dose correction factor. The correction factor is a parameter based on density changes and can be calculated by comparing the back-projected dose data with the density information in the CT images to obtain the dose correction value for each voxel (pixel point). This correction factor is used to evaluate the overall radiotherapy effect of the patient.

[0048] Furthermore, in practical applications, there is also an equipment correction factor. Calculation of the equipment correction factor: It is necessary to ensure that the treatment equipment is accurate during use. To achieve this, the equipment is calibrated regularly; During the calibration process, a standard radiation source is used to check the radiation dose output by the equipment. To measure this radiation dose, a tool called a "dosimeter" is usually used to measure the actually output radiation dose under different treatment settings (such as different angles and radiation energies); Then the actually measured radiation dose is compared with the expected radiation dose. If the actual output is less than the expected output, for example, it is 10% less, then 10% more radiation dose needs to be added to compensate for this error. The calculated correction factor is 1.1 (because 1 + 10% equals 1.1), that is, 10% more dose needs to be added during the treatment;

[0049] Calculation of density correction factor: When planning treatment, CT scans are performed to obtain information about tissue density in the patient's body. These CT images provide density values ​​for each voxel (i.e., small pieces of tissue), usually expressed as "HU values" (Hounsfield units). Different tissues have different densities. For example, the density of a tumor may be different from that of surrounding normal tissue, which affects their ability to absorb radiation. During treatment, the density model used in the treatment plan is compared with the CT images obtained during actual treatment to see if the patient's tissue density has changed. For example, the tumor may have become larger, or the density of normal tissue has changed. Based on these density changes, physical models (such as linear weighted methods, Breteau models, etc.) are used to calculate the dose correction factor for each area. If the density of certain areas becomes higher, these areas will absorb more radiation doses. Therefore, the radiation dose of these areas needs to be reduced during treatment to avoid over-irradiation.

[0050] Step 206 is similar to step 105 in the first embodiment and will not be described in detail here.

[0051] In practical applications, the following are specific operations of the present invention in practical applications, which are intended to provide sufficient information for peers so that they can successfully implement the method according to the description of the present invention and apply it to clinical treatment:

[0052] 1. Equipment preparation and preliminary work:

[0053] Equipment requirements: This invention needs to rely on Tomo equipment, equipped with a CT imaging system and radiation detectors, for real-time collection of radiation dose data in the patient's body;

[0054] Software requirements: The implementation of this invention requires the corresponding computing platform and real-time dose reconstruction software, which should support image processing, data analysis and real-time dose distribution reconstruction. The software should include: a CT data processing module for inputting the patient's CT image data; a dose reconstruction module that can calculate the actual dose distribution in the patient's body through the reverse reconstruction algorithm based on the real-time dose data obtained by the Tomo device; and a visualization module that generates a dose heat map and displays it in real time on the doctor's workstation for adjustment during treatment.

[0055] 2. Real-time dose data collection:

[0056] Step 1: Tomo device setup and calibration: Before treatment, the Tomo device must be calibrated to ensure the accuracy of the radiation beam. Through a standardized calibration process, all radiation measurements can accurately reflect the output characteristics of the device.

[0057] Step 2: Patient Preparation and Image Acquisition: The patient needs to undergo a CT scan to obtain three-dimensional image data of the internal structures of the patient. According to the patient's position, the doctor can adjust the treatment couch and the patient's position to ensure that the CT image reflects the patient's actual anatomical structure.

[0058] Step 3: Real-time Data Acquisition and Recording: During the actual treatment process, the Tomo device will monitor the dose of the radiation beam in real time; this monitoring data will be collected by the detector, paired with the CT image, and transmitted to the computing platform; this data includes but is not limited to the radiation intensity generated when each radiation beam passes through the patient's body, as well as the spatial distribution information of the radiation.

[0059] 3. Inverse Reconstruction Algorithm and Dose Deduction:

[0060] Step 4: Inverse Reconstruction Calculation: Based on the radiation data collected in real time, the present invention uses an inverse reconstruction algorithm to deduce the actual dose distribution in the patient's body. The process is as follows: By analyzing the penetration path and dose distribution of each radiation beam, combined with the patient's CT data, the radiation dose of each region is inversely deduced; Using linear or non-linear optimization algorithms, combined with the CT image and real-time data, the model parameters are adjusted to minimize the error between the reconstructed dose and the actual dose.

[0061] Step 5: Real-time Dose Reconstruction: During the treatment process, each set of real-time dose data is processed by the inverse reconstruction algorithm to generate the dose distribution in the patient's body in real time. This process can be completed within a few seconds and fed back to the doctor in a timely manner.

[0062] 4. Dose Heat Map Generation and Visualization:

[0063] Step 6: Generation and Display of Dose Heat Map: The dose data after inverse reconstruction will be converted into a two-dimensional or three-dimensional dose heat map through the visualization module; The heat map uses color mapping to correspond different dose levels to different colors, so as to visually display the dose distribution in different regions of the patient's body; Among them, two-dimensional heat map: The dose distribution of each slice is displayed as a two-dimensional image, and the colors in the heat map represent the dose levels in different regions (for example, blue represents low dose, and red represents high dose); Three-dimensional heat map: For complex three-dimensional dose distributions, the dose distribution within the entire volume can be displayed through three-dimensional visualization software, enabling doctors to more intuitively observe the spatial distribution of the dose.

[0064] Step 7: Dose Calibration and Optimization: During the real-time dose reconstruction process, after obtaining the real-time dose distribution in the patient's body through inverse reconstruction, these dose data are compared with the dose distribution in the treatment plan. The differences between the two can be automatically detected and fed back to the doctor, indicating possible sources of dose errors. The doctor can view the dose distribution of the target tumor area and normal tissues through the sources of dose errors. If dose deviations or risks of over-irradiation are found, the doctor can immediately adjust treatment parameters such as radiation beam angles, radiation intensities, or treatment plans to optimize the treatment effect.

[0065] 5. Patient Position Adjustment and Optimization:

[0066] Step 8: Optimize Treatment Based on Real-Time Dose Feedback: According to the real-time dose heat map, the doctor can make precise patient position adjustments. Especially when the tumor is close to critical organs or sensitive tissues, the doctor can adjust the patient's position to avoid unnecessary radiation exposure and ensure that the treatment dose is more concentrated in the tumor area.

[0067] Step 9: Continuous Monitoring During Treatment: Throughout the treatment process, real-time dose monitoring and heat map generation will continue. The doctor can view the dose distribution at any time during the treatment and make corresponding adjustments as needed to ensure the maximization of the treatment effect.

[0068] 6. Quality Control and Post-treatment Verification:

[0069] Step 10: Quality Control and Verification: After the treatment, to ensure the safety and accuracy of the treatment, quality control is required. By comparing the patient's CT images before and after treatment with the real-time dose distribution map, the accuracy of the treatment is verified. If dose deviations are found, post-treatment analysis is carried out and the treatment plan is adjusted.

[0070] Step 11: Regular Calibration and Software Update: To ensure long-term stability and accuracy, the Tomo device and the inverse reconstruction software need to be regularly calibrated and updated. Especially for the inverse reconstruction algorithm, appropriate verification and optimization should be carried out to ensure that the algorithm can meet the needs of different patients and treatment plans.

[0071] 7. Clinical Application and Effect Evaluation:

[0072] Step 12: Clinical Application: In actual clinical treatment, this method will be able to effectively improve the precision and safety of treatment. The doctor can adjust the treatment plan in real time during the treatment process, reduce treatment errors, ensure precise irradiation of the tumor area, and at the same time protect normal tissues from excessive radiation.

[0073] Step 13: Effect evaluation: After the clinical treatment is completed, the doctor further optimizes the treatment plan by evaluating the correlation between the dose heat map and the patient's clinical response. The treatment effect and side effects of the patient will be used as the basis for subsequent adjustments, so as to provide a personalized treatment plan for each patient.

[0074] In summary, the present invention has the following beneficial effects:

[0075] 1. Realize real-time dose reconstruction and visualization: The present invention collects dose data in real time based on the detectors of the Tomo device, combines the CT images of the patient, and generates the actual dose distribution in the patient's body through a back-projection reconstruction algorithm; this method can generate a dose heat map in real time, helping doctors intuitively understand the actual dose distribution during the treatment process, so as to timely detect and adjust dose deviations and avoid the adverse effects caused by errors.

[0076] 2. Improve the accuracy and safety of radiotherapy: In traditional radiotherapy, although the treatment plan can calculate the dose distribution in advance, due to reasons such as patient body position changes, tumor movement, and treatment equipment errors, the actual dose distribution may deviate from the predetermined dose; the present invention can help doctors adjust the treatment process in real time by monitoring and reconstructing the actual dose data in real time, ensuring the treatment accuracy, thereby improving the efficacy of radiotherapy, reducing side effects, and ensuring the safety of patients.

[0077] 3. Enhance the feedback mechanism during the treatment process: In the traditional treatment process, the dose distribution and actual treatment effect often need to be evaluated after the treatment is completed, lacking real-time feedback; through the real-time dose reconstruction and visualization method of the present invention, doctors can see the dose heat map in the patient's body in real time during the treatment process and timely adjust treatment parameters such as irradiation angle and dose intensity to ensure the best treatment effect.

[0078] 4. Simplify the dose evaluation and monitoring operations: The present invention provides a method for data collection and back-projection reconstruction based on the Tomo device, which can generate a dose heat map in real time without additional radiation exposure or complex dose measurement equipment, simplifying the complex operations of traditional dose monitoring. Operators can view and adjust dose data through a simple control interface, thereby improving the efficiency and accuracy of the treatment process.

[0079] 5. Optimize the clinical treatment plan: By obtaining the dose information in the patient's body in real time, the present invention can help doctors adjust the treatment plan according to real-time data and achieve dynamic optimization during the treatment process; this real-time feedback mechanism can reduce the prediction error in the traditional method, making the treatment plan more personalized and refined, and improving the clinical application value of radiotherapy.

[0080] The objective of the present invention is to construct a method for real-time dose reconstruction and visualization by combining the real-time dose data of a Tomo device and CT images, enabling radiotherapy to be carried out on the basis of higher precision and safety, while providing more treatment feedback information for doctors. Through the treatment feedback information, doctors can timely detect possible dose deviations during the treatment process and make necessary adjustments, thereby improving the precision and safety of the treatment.

[0081] The above embodiments merely illustrate the principles and effects of the present invention and are not intended to limit the present invention. All equivalent modifications or changes made by those with ordinary knowledge in the technical field without departing from the spirit and technical ideas disclosed by the present invention shall still be covered by the claims of the present invention.

Claims

1. A real-time radiation dose monitoring method in radiotherapy based on a spiral tomography radiotherapy device, characterized in that: The method comprises the following steps: Acquire radiation dose data of the patient collected in real time by a detector in a spiral tomography radiotherapy device during radiotherapy, and after acquiring a CT image of the patient, align the radiation dose data collected by the detector with the CT image, wherein the CT image is a three-dimensional anatomical image of the patient obtained by a CT scanning device; The radiation dose data collected by the registered detector is combined with each voxel in the CT image using the back propagation algorithm, and the preliminary radiation dose of each part of the patient's body is calculated based on the combined results; Iteratively optimizing the preliminary radiation dose of each part of the patient's body, and obtaining the final radiation dose of each part of the patient's body according to the iterative optimization result; Visualizing the final radiation doses of various parts of the patient's body, and generating a dose heat map in the patient's body according to the visualization processing result, wherein the dose intensity of different areas in the dose heat map is marked by color; The parameters of the preset radiotherapy plan are iteratively optimized according to the dose heat map in the patient's body, and the optimal dose distribution scheme that meets the treatment requirements is obtained according to the iterative optimization result.

2. The method for real-time radiation dose monitoring in radiotherapy based on a helical tomography radiotherapy device according to claim 1, characterized in that: The registering the radiation dose data collected by the detector with the CT image comprises: A registration algorithm is used to align an MVCT image with the CT image, wherein the MVCT image is composed of radiation dose data of the patient acquired by the detector in real time.

3. The method for real-time radiation dose monitoring in radiotherapy based on a helical tomography radiotherapy device according to claim 1, characterized in that: The back propagation algorithm is used to combine the radiation dose data collected by the aligned detector with each voxel in the CT image, and the preliminary radiation dose of each part of the patient's body is calculated based on the combined result, including: The initial radiation dose to each part of the patient's body is calculated by reverse calculation using the following formula: D=A -1 M; Among them, D is the reconstructed three-dimensional dose distribution matrix, that is, the preliminary radiation dose of various parts of the patient's body; A is a matrix describing the detector position and the ray propagation path, which contains geometric information and a radiation propagation model; M is the patient's radiation dose data collected in real time by the detector during radiotherapy.

4. The method for real-time radiation dose monitoring in radiotherapy based on a helical tomography radiotherapy device according to claim 1, characterized in that: The iterative optimization of the preliminary radiation doses of various parts of the patient's body and obtaining the final radiation doses of various parts of the patient's body according to the iterative optimization results include: The final radiation dose to each part of the patient's body is determined according to the following formula: D k+1 =D k +α(M-AD K ); Among them, D k+1 is the dose distribution of the k+1th iteration, that is, the final radiation dose of each part of the patient's body; D k is the dose distribution at the kth iteration; α is the step size factor.

5. The method for real-time radiation dose monitoring in radiotherapy based on a helical tomography radiotherapy device according to claim 1, characterized in that: After the final radiation doses of various parts of the patient's body are visualized and a dose heat map in the patient's body is generated according to the visualization processing result, the parameters of the preset radiotherapy plan are iteratively optimized according to the dose heat map in the patient's body, and before the optimal dose distribution scheme that meets the treatment requirements is obtained according to the iterative optimization result, the method further includes: The actual radiation dose distribution obtained by reverse reconstruction is compared with the dose distribution preset in the radiotherapy plan, the deviation between the two is determined according to the comparison result, and the dose correction factor is determined according to the deviation between the two, wherein the actual radiation dose distribution obtained by reverse reconstruction is displayed in the dose heat map in the patient's body.

6. The method for real-time radiation dose monitoring in radiotherapy based on a helical tomography radiotherapy device according to claim 5, characterized in that: Determining the dose correction factor according to the deviation between the two comprises: The deviation between the two includes changes in tissue density, and a physical model is used to calculate a dose correction factor for each part of the patient's body based on the change in tissue density, wherein the dose correction factor is a parameter based on the density change.

7. The method for real-time radiation dose monitoring in radiotherapy based on a helical tomography radiotherapy device according to claim 6, characterized in that: The iterative optimization of the parameters of the preset radiotherapy plan according to the dose heat map in the patient's body, and obtaining the optimal dose distribution scheme that meets the treatment requirements according to the iterative optimization result, includes: Determine the objective function between the actual radiation dose distribution and the preset dose distribution; and minimize the objective function to obtain an optimal dose distribution scheme that meets the treatment requirements based on the minimization process.

8. The method for real-time radiation dose monitoring in radiotherapy based on a helical tomography radiotherapy device according to claim 7, characterized in that: The step of determining an objective function between the actual radiation dose distribution and the preset dose distribution; and minimizing the objective function to obtain an optimal dose distribution scheme that meets the treatment requirements according to the minimization process, includes: The objective function between the actual radiation dose distribution and the preset dose distribution is determined according to the following formula: Wherein, F(D) is the objective function between the actual radiation dose distribution and the preset dose distribution; n is the total number of voxels in the dose distribution; D(i) is the dose value of the i-th voxel; D target (i) The dose distribution preset for the treatment target area; D measured (i) is the actual measured radiation dose distribution; The optimal dose distribution plan that meets treatment needs is determined according to the following formula: Among them, D k+1 is the optimal dose distribution scheme that meets the treatment requirements; γ is the learning rate; is the gradient of the objective function with respect to dose distribution.

Images