A method for optimizing parameters of spatially fractionated radiotherapy stereotactic center ablation therapy

Abstract

The application discloses a kind of space segmentation radiotherapy stereotactic center ablation treatment parameter optimization method, belong to the field of radiotherapy technique.The method is as follows specifically: first, construct parameter automatic optimization calculation unit, second, DICOM data acquisition, third, delineate structure selection, obtain delineation area;Fourth, self-defined intermediate hot zone generation parameter, fifth, parameter automatic optimization calculation unit imports the intermediate hot zone generation parameter obtained in last step into radiotherapy planning system;Sixth, radiotherapy plan is designed according to the method of only irradiating intermediate hot zone volume, and the dose of surrounding normal tissue is controlled according to the design proportion, and output radiotherapy plan;And the treatment plan is transmitted to treatment equipment for treatment.The space segmentation radiotherapy stereotactic center ablation treatment parameter optimization method of the application can improve the accuracy of hot zone design, standardize the clinical use of SCART technology, and improve the efficiency and quality of stereotactic center ablation irradiation delineation.

Description

Technical Field

[0001] This invention specifically relates to a method for optimizing the parameters of stereotactic central ablation therapy in spatial segmentation radiotherapy, belonging to the field of radiotherapy technology. Background Technology

[0002] Spatial fractionated radiotherapy (SFRT) introduces the concept of irradiating only a portion of the tumor with a high dose in fewer fractions, controlling the tumor while ensuring dose tolerance in surrounding normal tissues. This has provided more creative and complementary applications in the field. SFRT's GRID and Lattice therapies have demonstrated advantages in large tumor environments. GRID and Lattice aim to generate multiple hot zones or heat islands within large tumors. These hot zones not only directly kill cancer cells but also trigger biological effects such as SFRT. Because GRID and Lattice limit the dose to surrounding tissues, side effects are also minimal. However, their design is complex, particularly in the planning and treatment of GRID. Lattice and similar methods require a large workforce; more importantly, generating multiple hot zones and adapting to large tumors may limit the size of each hot zone, and the total volume of the hot zones (strips or islands) is smaller compared to the volume of the large tumor. Among them, the core principle of SCART is similar to that of GRID and Lattice. The purpose of SCART is to stereotactically irradiate a portion of the target volume (hot spot) located at the center of a large tumor with an ablation dose (15 Gy or higher), and the dose rapidly decreases from the edge of the hot spot to a low dose (3 Gy or lower) at the edge of the tumor volume; the goal is to irradiate the largest possible volume with an ablation dose while keeping the dose at the tumor edge low. SCART has the following advantages: (1) It only requires designing one hot spot in the middle, which is easier to achieve using modern radiotherapy technology and has a shorter treatment time; (2) The hot zone volume is larger, approximately 30 times and 500 times larger than Grid and Lattice, respectively, resulting in a significant increase in efficacy; however, the therapeutic effect of SCART is highly correlated with the volume of the hot zone, and a larger hot zone volume also brings higher treatment risks and side effects; how to design the volume of the central hot zone and how to control the dose drop outside the hot zone to protect normal tissues are the key factors for achieving SCART. Summary of the Invention

[0003] To address the aforementioned issues, this invention proposes an optimization method for stereotactic central ablation treatment parameters in spatial segmentation radiotherapy. By utilizing an automatic parameter optimization calculation unit, the method not only improves the accuracy of thermal zone design but also standardizes the clinical application of SCART technology, thereby enhancing the efficiency and quality of stereotactic central ablation irradiation delineation.

[0004] The method for optimizing the parameters of spatial segmentation radiotherapy stereotactic central ablation therapy according to the present invention is as follows:

[0005] The first step is to construct an automatic parameter optimization calculation unit, which is connected to the image storage system and radiotherapy system of the hospital or clinic respectively;

[0006] The second step is DICOM data acquisition. First, data is captured. The automatic parameter optimization calculation unit automatically extracts the patient's DICOM file through the image storage system. The automatic parameter optimization calculation unit supports batch import of image data. Next, the automatic optimization calculation unit automatically parses the DICOM file, parsing the image data and image-related metadata in the DICOM file. After confirming that all data has been accurately read, the DICOM data acquisition is completed.

[0007] The third step is to delineate the selected structure. The automatic parameter optimization calculation unit automatically delineates the DICOM data, selects the structure or region to be delineated, distinguishes the tumor region, tissue organs or other related regions, and obtains the delineated region.

[0008] The fourth step involves customizing the intermediate hot zone generation parameters. The parameter automatic optimization calculation unit selects the intermediate hot zone based on the outlined area obtained in the third step, with the tumor area as the default. The dose gradient, size, and shape parameters of the high-dose area are set to adapt to the treatment needs of different types of tumors. The intermediate hot zone generation parameters are generated according to the prescription requirements and the proportions calculated by the mathematical model.

[0009] Fifth, the automatic parameter optimization calculation unit imports the intermediate hot zone generation parameters obtained in the previous step into the radiotherapy planning system;

[0010] The sixth step involves the radiotherapy planning system designing a treatment plan that irradiates only the central thermal zone volume, controlling the dose to the surrounding normal tissues according to the design ratio, outputting the radiotherapy plan, and transmitting the treatment plan to the treatment equipment for treatment.

[0011] Furthermore, the radiotherapy plan is designed with a core irradiation dose that is 3 to 8 times the boundary irradiation dose.

[0012] Furthermore, the image data includes pixel data, resolution, inter-slice spacing, and scanning parameters; the metadata includes patient information and examination date.

[0013] Furthermore, the process of generating intermediate heat zone generation parameters based on prescription requirements and proportions calculated by the mathematical model is as follows:

[0014] 1. The automatic parameter optimization calculation unit obtains known definitions and initial conditions:

[0015] 1.1 Input data: GTVslices∈Rn×3, containing the coordinates of points (x1,y1,z1);

[0016] 1.2 Output data: SCARTslices∈Rn×3, new coordinates (x2,y2,z1);

[0017] 1.3 Parameters: ogapFeet: offset parameter; oshrinkpercentage: shrinkage ratio; main loop: traverses the range k∈ [1+gapFeet,j+gapFeet];

[0018] 2. Next, perform initial point transformation and calculate the centroid:

[0019] 2.1 Extract the point set of the intermediate hot zone - slice: GTVslices={(x1,y1,z1)};

[0020] 2.2 Calculate the centroid of the polygon: (Xorigin,Yorigin)=centroid(polyshape(x1,y1));

[0021] 2.3 Translate the point coordinates to the centroid: xshift = x1 - Xorigin, yshift = y1 - Yorigin;

[0022] 3. Transform to polar coordinates and optimize the centroid:

[0023] 3.1 Transform to polar coordinates: (θ,ρ)=cart2pol(xshift,yshift);

[0024] 3.2 Adjust the centroid 360 times: First, find the directions with the minimum and maximum current radius:

[0025] ρmin=min(ρ),θmin=θ(index(ρmin));

[0026] θmax=θmin+π,ρmax=ρ(index(min(θ-θmax)));

[0027] Secondly, adjust the centroid according to the ρ difference: Δρ = 0.01(ρmax - (ρmax + ρmin) / 2);

[0028] New centroid position: (Xorigin,Yorigin)←(Xorigin,Yorigin)+pol2cart(θmax,Δρ); then, update xshift, yshift, θ,ρ;

[0029] 4. Shear radius: The radius ρ of all points is restricted as follows: ρ(t) = {0, if ρ(t) ≤ 20 mm, ρ(t), otherwise};

[0030] 5. Scaling radius: Scaling ρ ← ρ shrinkpercentage;

[0031] 6. Convert back to Cartesian coordinates: Convert the polar coordinates obtained in the previous step to Cartesian coordinates: (x2, y2) = pol2cart(θ,ρ);

[0032] 7. Translate back to the original centroid position: x2←x2+Xorigin, y2←y2+Yorigin;

[0033] 8. Construct the output slice: SCARTslices={(x2,y2,z1)};

[0034] 9. Store the result: SCARTk-gapFeet,1=SCARTslices.

[0035] Compared with existing technologies, the optimization method for stereotactic central ablation treatment parameters in spatial segmentation radiotherapy of the present invention utilizes an automatic parameter optimization calculation unit to perform parameter optimization calculations. This not only improves the accuracy of hot zone design but also standardizes the clinical use of SCART technology. Based on prescription requirements and proportions calculated by mathematical models, intermediate hot zone generation parameters are generated. The proportions of the intermediate hot zone (STV) volume and diameter relative to the entire treatment target volume are simulated, enabling irradiation only of the intermediate hot zone, eliminating irradiation of the entire tumor volume. This results in a faster dose drop and lower doses to surrounding normal tissues. It improves the efficiency and quality of stereotactic central ablation irradiation delineation, enhances treatment efficacy, and significantly reduces the side effects of radiotherapy. Attached Figure Description

[0036] Figure 1 This is a schematic diagram illustrating the workflow of the method for optimizing the parameters of spatial segmentation radiotherapy stereotactic central ablation therapy according to the present invention.

[0037] Figure 2 This diagram illustrates the optimized ASCART ablation treatment state of the present invention and the existing ASCART ablation treatment state.

[0038] Figure 3 The dosimetric distribution and thermal volume maps generated on a case using the Grid of the present invention are shown.

[0039] Figure 4 The dosimetric distribution and thermal volume maps generated by the Lattice of the present invention on a medical case are shown.

[0040] Figure 5 This is a dosimetric distribution of the SCART of the present invention on a case and a thermal volume map of the respective generated area. Detailed Implementation

[0041] Example 1:

[0042] like Figures 1 to 5 The method for optimizing the parameters of spatial segmentation radiotherapy stereotactic central ablation therapy is shown below:

[0043] The first step is to construct an automatic parameter optimization calculation unit, which is connected to the hospital or clinic's image storage system (such as a PACS server) and radiotherapy system respectively.

[0044] The second step is DICOM data acquisition. First, data is captured. The automatic parameter optimization calculation unit automatically extracts the patient's DICOM file through the image storage system. The automatic parameter optimization calculation unit supports batch import of image data. Next, the automatic optimization calculation unit automatically parses the DICOM file, parsing the image data and image-related metadata in the DICOM file. After confirming that all data has been accurately read, the DICOM data acquisition is completed.

[0045] The third step is to delineate the selected structure. The automatic parameter optimization calculation unit automatically delineates the DICOM data, selects the structure or region to be delineated, distinguishes the tumor region, tissue organs or other related regions, and obtains the delineated region.

[0046] The fourth step involves customizing the intermediate hot zone generation parameters. The parameter automatic optimization calculation unit selects the intermediate hot zone based on the outlined area obtained in the third step, with the tumor area as the default. The dose gradient, size, and shape parameters of the high-dose area are set to adapt to the treatment needs of different types of tumors. The intermediate hot zone generation parameters are generated according to the prescription requirements and the proportions calculated by the mathematical model.

[0047] Fifth, the automatic parameter optimization calculation unit imports the intermediate hot zone generation parameters obtained in the previous step into the radiotherapy planning system;

[0048] The sixth step involves the radiotherapy planning system designing a treatment plan that irradiates only the central thermal zone volume, controlling the dose to the surrounding normal tissues according to the design ratio, outputting the radiotherapy plan, and transmitting the treatment plan to the treatment equipment for treatment.

[0049] like Figure 2 As shown, Figure 2 In this context, P1 represents the ASCII design scheme output by this invention; P2 represents an existing ASCII design scheme. Figure 2 P1 in the study is a narrow beam that directly irradiates only the STV (hot zone) (the core of the GTV); the dose distribution is extremely uneven, with a core / boundary dose ratio of 3 to 8 times, and the dose decays rapidly outside the STV. Figure 2In P2, a wide beam directly irradiates the entire GTV; the dose distribution is relatively uniform, with a core / boundary dose ratio of 1.1 to 2 times; the dose outside the gross tumor volume (GTV) range is moderately reduced.

[0050] The method for optimizing stereotactic central ablation therapy parameters for spatial fractionation radiotherapy of this invention is a novel approach to spatial fractionation radiotherapy, based on previous GRID and Lattice methods. It is technically simple to implement, can be performed using current radiotherapy equipment, requires no additional accessories, and is easy to promote; it is applicable to the treatment of most large-volume tumors >5cm; the clinical efficacy of spatial fractionation irradiation is significantly correlated with the hot zone volume, with SCART having a larger hot zone volume compared to Grid and Lattice, by 30 times and 500 times respectively. Figures 3 to 5 As shown, Figures 3 to 5 To address the different dosimetric distributions and the resulting thermal volumes on the same case, i.e. Figures 3 to 5 The different dosimetric distributions generated by Grid, Lattice, and SCART in the same case are shown in Table 1.

[0051]

[0052] Dmax (cGy): The highest dose produced within the hot zone;

[0053] MU: This is a unit of measurement for treatment equipment. This item represents the amount of equipment required for treatment.

[0054] V100% (cc): Volume of the prescribed dose.

[0055] Because a larger hot zone volume will shrink the tumor volume more quickly, increase the probability of related tumor immune responses, and produce better treatment effects; this invention uses a standard model to simulate the ratio of the volume and diameter of the central hot zone (STV) to the entire treatment target volume, so as to promote the technology of SCART; only the central hot zone is irradiated, and the entire tumor volume is no longer irradiated, so that the dose drops faster and the dose to the surrounding normal tissue is lower.

[0056] The radiotherapy plan is designed with a core dose that is 3 to 8 times the boundary dose.

[0057] The image data includes pixel data, resolution, inter-slice spacing, and scanning parameters; the metadata includes patient information and examination date.

[0058] The process of calculating the intermediate hot zone generation parameters based on prescription requirements and mathematical models is as follows:

[0059] 1. The automatic parameter optimization calculation unit obtains known definitions and initial conditions:

[0060] 1.1 Input data: GTVslices∈Rn×3, containing the coordinates of points (x1,y1,z1);

[0061] 1.2 Output data: SCARTslices∈Rn×3, new coordinates (x2,y2,z1);

[0062] The prescription requirements are shown in Table 2 below:

[0063]

[0064] 1.3 Parameters: ogapFeet: Offset parameter; oshrinkpercentage: Shrinkage ratio;

[0065] Main loop: Iterates through the range k∈ [1+gapFeet,j+gapFeet];

[0066] 2. Next, perform initial point transformation and calculate the centroid:

[0067] 2.1 Extract the point set of the intermediate hot zone - slice: GTVslices={(x1,y1,z1)};

[0068] 2.2 Calculate the centroid of the polygon: (Xorigin,Yorigin)=centroid(polyshape(x1,y1));

[0069] 2.3 Translate the point coordinates to the centroid: xshift = x1 - Xorigin, yshift = y1 - Yorigin;

[0070] 3. Transform to polar coordinates and optimize the centroid:

[0071] 3.1 Transform to polar coordinates: (θ,ρ)=cart2pol(xshift,yshift);

[0072] 3.2 Adjust the centroid 360 times: First, find the directions with the minimum and maximum current radius:

[0073] ρmin=min(ρ),θmin=θ(index(ρmin));

[0074] θmax=θmin+π,ρmax=ρ(index(min(θ-θmax)));

[0075] Secondly, adjust the centroid based on the ρ difference: Δρ = 0.01 · (ρmax - (ρmax + ρmin) / 2); New centroid position: (Xorigin,Yorigin) ← (Xorigin,Yorigin) + pol2cart(θmax,Δρ); Next, update xshift, yshift, θ, ρ;

[0076] 4. Shear radius: The radius ρ of all points is restricted as follows: ρ(t) = {0, if ρ(t) ≤ 20 mm, ρ(t), otherwise};

[0077] 5. Scaling radius: Scaling ρ ← ρ shrinkpercentage;

[0078] 6. Convert back to Cartesian coordinates: Convert the polar coordinates obtained in the previous step to Cartesian coordinates: (x2, y2) = pol2cart(θ,ρ);

[0079] 7. Translate back to the original centroid position: x2←x2+Xorigin, y2←y2+Yorigin;

[0080] 8. Construct the output slice: SCARTslices={(x2,y2,z1)};

[0081] 9. Store the result: SCARTk-gapFeet,1=SCARTslices.

[0082] The method for optimizing stereotactic central ablation therapy parameters for spatial segmentation radiotherapy of the present invention involves the following steps: First, a medical DICOM image is acquired and imported into the radiotherapy system. The physician determines the irradiation area based on the patient's clinical data and multimodal imaging. An automatic parameter optimization calculation unit receives the delineated structure and automatically identifies it. A stereotactic volume (STV) is generated based on the prescribed dose. The automatically generated STV is imported into the radiotherapy system. The dose of the STV is calculated using the radiotherapy system's optimization algorithm and evaluated using clinical parameters. Once clinical needs are met, the STV is transferred to the treatment device for treatment. This method simplifies the clinical implementation of the previous two spatial segmentation irradiation methods, improves the volume of the hot zone dose (the therapeutic effect is related to the size of the hot zone volume), establishes standard data for the hot zone volume, and forms a standard design system.

[0083] The above embodiments are merely preferred embodiments of the present invention. Therefore, all equivalent changes or modifications made to the structure, features and principles described in the claims of the present invention are included within the scope of the present invention.

Claims

1. A method for optimizing parameters in spatially segmented stereotactic central ablation radiotherapy, characterized in that, The method is as follows: The first step is to construct an automatic parameter optimization calculation unit, which is connected to the image storage system and radiotherapy system of the hospital or clinic respectively; The second step is DICOM data acquisition. First, data is captured. The automatic parameter optimization calculation unit automatically extracts the patient's DICOM file through the image storage system. The automatic parameter optimization calculation unit supports batch import of image data. Next, the automatic optimization calculation unit automatically parses the DICOM file, parsing the image data and image-related metadata in the DICOM file. After confirming that all data has been accurately read, the DICOM data acquisition is completed. The third step is to delineate the selected structure. The automatic parameter optimization calculation unit automatically delineates the DICOM data. Select the structure or region to be delineated, including one of the tumor region, tissue organ or other related regions, and obtain the delineated region. The fourth step involves customizing the intermediate hot zone generation parameters. The parameter automatic optimization calculation unit selects the intermediate hot zone based on the outlined area obtained in the third step, with the tumor area as the default. The dose gradient, size, and shape parameters of the high-dose area are set to adapt to the treatment needs of different types of tumors. The intermediate hot zone generation parameters are generated according to the prescription requirements and the proportions calculated by the mathematical model. Fifth, the automatic parameter optimization calculation unit imports the intermediate hot zone generation parameters obtained in the previous step into the radiotherapy planning system; The sixth step involves the radiotherapy planning system designing a plan based on the method of irradiating only the central thermal zone volume, controlling the dose to the surrounding normal tissues according to the design ratio, and outputting the radiotherapy plan. The treatment plan is then transmitted to the treatment equipment for treatment.

2. The method for optimizing the parameters of spatial segmentation radiotherapy stereotactic central ablation therapy according to claim 1, characterized in that: The radiotherapy plan is designed with a core dose that is 3 to 8 times the boundary dose.

3. The method for optimizing the parameters of spatial segmentation radiotherapy stereotactic central ablation therapy according to claim 1, characterized in that: The image data includes pixel data, resolution, inter-slice spacing, and scanning parameters; the metadata includes patient information and examination date.

4. The method for optimizing the parameters of spatial segmentation radiotherapy stereotactic central ablation therapy according to claim 1, characterized in that: The process of generating intermediate heat zone parameters based on prescription requirements and mathematical model calculations is as follows: First, the automatic parameter optimization calculation unit obtains known definitions and initial conditions; specifically as follows: 1.1 Input data ∈ Rn×3, including the coordinates of points (x1, y1, z1); 1.2 Output data ∈ Rn×3, new coordinate point (x2,y2,z1); 1.3 Parameters: Offset parameter and scaling ratio; The main loop iterates over the range: k∈ [1+gapFeet,j+gapFeet], where gapFeet is the offset parameter; Second, the initial point transformation and centroid calculation are performed: extract the point set of the middle hot zone-slice, calculate the centroid of the polygon, and translate the point coordinates to the centroid. Third, transform to polar coordinates and optimize the centroid: Fourth, shear radius: a constraint is imposed on the radius ρ of all points; Fifth, scaling radius; Sixth, convert back to Cartesian coordinates: convert the polar coordinates obtained in the previous step to Cartesian coordinates; Seventh, translate back to the original position of the center of mass; Eighth, construct the output slice; Ninth, store the results.

5. The method for optimizing the parameters of spatial segmentation radiotherapy stereotactic central ablation therapy according to claim 4, characterized in that: The process of converting to polar coordinates and optimizing the centroid is as follows: First, convert to polar coordinates (θ, ρ), and adjust the centroid 360 times. The centroid adjustment is as follows: First, find the current minimum and maximum radius directions; second, adjust the centroid according to the ρ difference; then, update and optimize the centroid.

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