CN118045297A - Method suitable for generating large liver cancer surgery excision type sufficient radiation treatment plan - Google Patents
Method suitable for generating large liver cancer surgery excision type sufficient radiation treatment plan Download PDFInfo
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Abstract
The invention provides a method for generating a sufficient radiation treatment plan suitable for large liver cancer surgical excision, which aims at assuming the volume of the residual liver area after surgical excision to generate the radiation treatment plan according to the concept of liver segment excision and semi-liver excision when the surgical liver excision of liver tumor is assumed, and specifically comprises the following steps: step 1, obtaining an original medical image; step 2, identifying a target area, a highest dose area and a residual liver area from the original medical image to obtain an area identification result; step 3, obtaining the volume of the residual liver area, and judging whether the volume of the residual liver area is within a preset range; ending if the volume of the residual liver area is not within the preset range; otherwise, executing the step 4; step 4, designing a radiation treatment plan based on the region identification result and the original medical image to obtain a radiation treatment plan result; the maximum value of the preset range is 700ml, and the minimum value is 300ml; the generation of the radiation treatment plan can be automatically realized through the method.
Description
Technical Field
The invention relates to the technical field of computers, in particular to a method for generating a sufficient radiation therapy plan suitable for large liver cancer surgery excision type
Background
Radiation therapy is one of the most important cancer treatments, and is the most effective local treatment for non-resectable liver cancer. The radiation therapy is performed depending on the radiation therapy plan, i.e. the planning of radiation areas and doses, the rationality of which is crucial for the treatment effect and the safety of the treatment. Currently, the design of radiation therapy plans depends on the design of forward setup parameters by a physical engineer or reverse radiation therapy planning by means of commercial software.
When a forward design mode is adopted, the design of the radiotherapy plan is easily subjectively influenced and has lower efficiency; when commercial software is adopted to design the reverse radiation treatment plan, although subjective influence can be avoided to a certain extent, in the practical application process, the dose distribution cannot meet the requirement, and the radiation treatment plan meeting the requirement cannot be designed aiming at the specific type of cancer, so that the application efficiency is low.
For large liver cancer, in order to ensure treatment safety, the international guidelines suggest that radiotherapy can be accepted only when the normal liver volume is more than 700ml, but the large liver cancer is usually less than 700ml in clinic, and referring to fig. 1, the part of patients cannot accept radical surgery, if liver radiotherapy is not performed, the local treatment means of radiotherapy with the effective rate of up to 80% is lost, so that the opportunity of obtaining excellent control and prolonging survival is lost. For this part of patients, if no new treatment plan design principle is proposed, only the average received of the normal residual liver volume is concerned, and the actual treatment requirement cannot be met either by forward design or conventional reverse planning design by means of commercial software.
Disclosure of Invention
Aiming at the limitation, the invention provides a method for generating a sufficient radiation therapy plan suitable for large liver cancer surgical excision type by means of a strategy of reserving residual livers adopted during liver cancer radical surgery, namely, according to the concept similar to liver segment excision and half liver excision during surgical liver excision, the residual liver volume of a tumor is assumed to be adopted as a target by surgical excision, and the radiation therapy plan is automatically generated through automatic identification of key areas in an original medical image, so that the large liver cancer less than 700ml can be subjected to irradiation with a dose of more than 50 Gy.
In order to achieve the above purpose, the present invention adopts the following technical scheme:
A method of generating a radiation therapy plan suitable for use in a large liver cancer type surgical resection type sufficiency, the method comprising:
Step 1, obtaining an original medical image;
Step 2, identifying a target area, a highest dose area and a residual liver area from the original medical image to obtain an area identification result;
The highest dose area is an area applying a preset highest irradiation dose;
step 3, obtaining the volume of the residual liver area, and judging whether the volume of the residual liver area is within a preset range; ending if the volume of the residual liver area is not within the preset range; otherwise, executing the step 4;
the residual liver area volume is the liver volume which is assumed to remain after the tumor is excised by adopting the operation;
Step 4, designing a radiation treatment plan based on the region identification result and the original medical image to obtain a radiation treatment plan result;
The radiation treatment plan result consists of a plurality of regional radiation dose results; the regional radiation dose results include regional coordinates and radiation doses.
Further, the following conditions are required to be met for radiation treatment planning:
the irradiation dose of the highest metering area is more than 50 Gy;
The radiation dose of the remaining liver region is not higher than 500cGy, and the volume of the remaining liver region is at least 300ml.
Further, the maximum value of the preset range is 700ml, and the minimum value is 300ml.
Compared with the prior art, the invention has the following advantages:
(1) The generation of the large liver cancer radiotherapy plan can be automatically realized according to the image recognition technology, the generated radiotherapy plan is high in quality and speed, and the working efficiency of doctors is improved;
(2) The parameter of the residual liver area volume below 500cGy is provided, and the problem that the radiation treatment plan generation cannot be performed when the residual liver volume is less than 700ml can be solved by limiting the parameter to be more than 300ml, so that the requirement of an actual medical environment is met.
The foregoing description is only an overview of the present invention, and is intended to be implemented in accordance with the teachings of the present invention, as well as the preferred embodiments thereof, together with the following detailed description of the invention, given by way of illustration only, together with the accompanying drawings.
Drawings
Fig. 1 is a schematic diagram of a large liver cancer with a residual liver area volume of less than 700ml according to an embodiment of the present invention.
Fig. 2 is a flowchart of a method for generating a radiation therapy plan suitable for large liver cancer surgery excision according to an embodiment of the present invention.
Fig. 3 is a schematic diagram of a result of a surgical excision-type radiation therapy planning in accordance with an embodiment of the present invention.
Detailed Description
Other advantages and advantages of the present invention will become apparent to those skilled in the art from the following detailed description, which, by way of illustration, is to be read in connection with certain specific embodiments, 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. For a further understanding of the present invention, the present invention will be described in further detail with reference to the following preferred embodiments.
The invention provides a method for generating a sufficient radiation therapy plan suitable for large liver cancer surgery excision, which comprises the following steps of:
Step 1, obtaining an original medical image;
the original medical image is a liver CT image or an MRI image;
The original medical image needs to contain a complete target area, wherein the target area is a complete liver area and consists of a tumor area and a residual liver area; the remaining liver region is a normal liver region;
Step 2, identifying a target area, a highest dose area and a residual liver area from the original medical image to obtain an area identification result;
The highest dose area is an area applying a preset highest irradiation dose;
step 3, obtaining the volume of the residual liver area, and judging whether the volume of the residual liver area is within a preset range; ending if the volume of the residual liver area is not within the preset range; otherwise, executing the step 4;
the residual liver area volume is the liver volume which is assumed to remain after the tumor is excised by adopting the operation;
Step 4, designing a radiation treatment plan based on the region identification result and the original medical image to obtain a radiation treatment plan result;
Referring to fig. 3, the radiation treatment plan results consist of several regional radiation dose results; the regional radiation dose results include regional coordinates and radiation doses.
Further, the following conditions are required to be met for radiation treatment planning:
the irradiation dose of the highest metering area is more than 50 Gy;
The radiation dose of the remaining liver region is not higher than 500cGy, and the volume of the remaining liver region is at least 300ml.
Further, the maximum value of the preset range is 700ml, and the minimum value is 300ml.
As an embodiment, the obtaining the region identification result in step 2 is specifically implemented by the following manner:
step 21, performing image preprocessing on an original medical image to obtain a target identification image;
step 22, identifying a target area from a target identification image by means of a target identification algorithm to obtain a first image identification result;
step 23, dividing a target area in the target identification image into a residual liver area and a tumor area by means of an image segmentation algorithm based on the first image identification result to obtain a second image identification result;
And step 24, identifying a lesion core region from a tumor region of the target identification image through a core region identification model to obtain a third image identification result, wherein the lesion core region is the highest dose region, and the dose of the region is more than 50 Gy.
Further, the target recognition algorithm is realized by adopting U-Net.
Further, the image segmentation algorithm is realized by adopting a semantic segmentation algorithm based on deep learning.
Further, the core area recognition model is a recognition model obtained based on deep learning algorithm training.
As an example, in step 3, the remaining liver area volume may be obtained by estimating and inputting.
As an embodiment, in step 3, the remaining liver region volume may also be calculated by obtaining the input target region volume and then using the region identification result; the specific calculation method comprises the following steps:
Wherein v n is the volume of the remaining liver region, N is the number of image pixels of the remaining liver region, N 0 is the number of image pixels of the target region, v 0 is the volume of the target region, and α is a preset remaining liver volume correction coefficient.
As an example, the remaining liver region volume in step 3 may also be calculated by:
vn＝v0-vc
Wherein v n is the remaining liver region volume, v 0 is the target region volume, and v c is the tumor region volume; tumor area volume was obtained by:
wherein N c is the number of image pixels of the tumor region, N 0 is the number of image pixels of the target region, v 0 is the volume of the target region, and β is a preset tumor volume correction coefficient.
As an embodiment, the radiation treatment plan performed in step 4 specifically includes:
Step 41, initializing a radiation treatment plan result, which specifically includes:
Setting the region coordinates of the first element of the radiation treatment plan result as the region boundary coordinates of the highest dose region, and setting the radiation dose of the first element of the radiation treatment plan result as the preset highest irradiation dose;
The preset highest irradiation dose is not less than 50Gy;
setting the region coordinates of the last element of the radiation treatment plan result as the region boundary coordinates of the residual liver region, and setting the radiation dose of the last element of the radiation treatment plan result as 500cGy;
and step 42, calculating the radiation areas and the radiation doses one by one from the highest dose area to the residual liver area, and storing the radiation areas and the radiation doses in a radiation treatment planning result.
Step 42 specifically includes:
Step 421, setting the current region boundary coordinate list as the region boundary coordinate of the highest dose region, and setting the current region radiation dose as the preset highest irradiation dose;
Step 422, for each boundary point in the current region boundary coordinate list, obtaining a corresponding outer layer point according to an outer layer point searching rule, and combining all the outer layer points to obtain an outer layer region coordinate;
Step 423, judging whether the coordinates of all outer layer points exceed the residual liver area; if the remaining liver area is not exceeded, go to step 424; otherwise, ending;
Step 424, subtracting the interval radiation dose from the current regional radiation dose to obtain an outer layer radiation dose;
Step 425, saving the coordinates of the outer layer region and the outer layer radiation dose to the radiation treatment planning result; meanwhile, updating the current region boundary coordinate list into an outer layer region coordinate, and updating the current region radiation dose into an outer layer radiation dose; execution continues back at step 422.
Further, the outer layer point searching rule is as follows:
(1) Obtaining an image characteristic value f 1 of the current boundary point;
(2) Searching a residual liver region boundary point closest to the current boundary point from the region boundary of the residual liver region, and obtaining an image characteristic value f 2 of the point;
(3) The image characteristic gradual change value f 0 is calculated by the following steps:
wherein M is the number of preset dose levels, namely the number of levels of the radiation dose;
(4) Selecting a point which is farthest from the current boundary point and has an image characteristic value satisfying f 1+f0 +fb from the connecting line of the current boundary point and the corresponding boundary point of the residual liver region as an outer layer point corresponding to the current boundary point; fb is a preset degree of deviation of the image characteristic value.
Further, the spaced radiation doses are calculated by:
Wherein D 0 is the spaced radiation dose; d max is the preset highest dose; d min is the preset minimum dose; m is the number of preset dose steps.
As one example, the methods of the present invention may be implemented in software and/or a combination of software and hardware, e.g., using an Application Specific Integrated Circuit (ASIC), a general purpose computer, or any other similar hardware device.
The method of the present invention may be implemented in the form of a software program that is executable by a processor to perform the steps or functions described above. Likewise, the software programs (including associated data structures) may be stored on a computer readable recording medium, such as RAM memory, magnetic or optical drive or diskette and the like.
In addition, some steps or functions of the methods described herein may be implemented in hardware, for example, as circuitry that cooperates with the processor to perform various steps or functions.
Furthermore, parts of the methods of the present application may be applied as a computer program product, such as computer program instructions, which when executed by a computer, may invoke or provide the methods and/or solutions according to the present application by way of operation of the computer. Program instructions for invoking the methods of the application may be stored in fixed or removable recording media and/or transmitted via a data stream in a broadcast or other signal bearing medium and/or stored within a working memory of a computer device operating according to the program instructions.
As an embodiment, the present invention also provides an apparatus comprising a memory for storing computer program instructions and a processor for executing the program instructions, wherein the computer program instructions, when executed by the processor, trigger the apparatus to run a method and/or a solution according to the previous embodiments.
It should be noted that, for simplicity of description, the foregoing method embodiments are all described as a series of acts, but it should be understood by those skilled in the art that the present application is not limited by the order of acts described, as some steps may be performed in other orders or concurrently in accordance with the present application. Further, those skilled in the art will also appreciate that the embodiments described in the specification are alternative embodiments, and that the acts and modules referred to are not necessarily required for the present application.
Finally, it is pointed out that in the present document relational terms such as first and second, and the like, are used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Moreover, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or terminal that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or terminal. Without further limitation, an element defined by the phrase "comprising one … …" does not exclude the presence of other like elements in a process, method, article, or terminal device that comprises the element.
In addition, the technical solutions of the embodiments may be combined with each other, but it is necessary to base that the technical solutions can be realized by those skilled in the art, and when the technical solutions are contradictory or cannot be realized, the combination of the technical solutions should be regarded as not exist and not within the scope of the invention claimed.
The present invention is not limited to the above-mentioned embodiments, but is intended to be limited to the following embodiments, and any modifications, equivalents and modifications can be made to the above-mentioned embodiments without departing from the scope of the invention.
Claims (10)
1. A method for generating a sufficient radiation therapy plan suitable for large liver cancer surgery excision is characterized in that,
The method comprises the following steps:
Step 1, obtaining an original medical image;
Step 2, identifying a target area, a highest dose area and a residual liver area from the original medical image to obtain an area identification result;
The highest dose area is an area applying a preset highest irradiation dose;
step 3, obtaining the volume of the residual liver area, and judging whether the volume of the residual liver area is within a preset range; ending if the volume of the residual liver area is not within the preset range; otherwise, executing the step 4;
the residual liver area volume is the liver volume which is assumed to remain after the tumor is excised by adopting the operation;
Step 4, designing a radiation treatment plan based on the region identification result and the original medical image to obtain a radiation treatment plan result;
The radiation treatment plan result consists of a plurality of regional radiation dose results; the regional radiation dose results include regional coordinates and radiation doses.
2. The method of claim 1, wherein the step of determining the position of the substrate comprises,
The original medical image is a liver CT image or an MRI image;
The original medical image needs to contain a complete target area, wherein the target area is a complete liver area, and the target area consists of a tumor area and a residual liver area.
3. The method of claim 1, wherein the step of determining the position of the substrate comprises,
The irradiation dose of the highest metering area is more than 50 Gy.
4. The method of claim 1, wherein the step of determining the position of the substrate comprises,
The radiation dose of the remaining liver region is not higher than 500cGy, and the volume of the remaining liver region is at least 300ml.
5. The method of claim 1, wherein the step of determining the position of the substrate comprises,
The maximum value of the preset range is 700ml, and the minimum value is 300ml.
6. The method of claim 1, wherein the step of determining the position of the substrate comprises,
The area identification result obtained in the step 2 is specifically realized by the following modes:
step 21, performing image preprocessing on an original medical image to obtain a target identification image;
step 22, identifying a target area from a target identification image by means of a target identification algorithm to obtain a first image identification result;
step 23, dividing a target area in the target identification image into a residual liver area and a tumor area by means of an image segmentation algorithm based on the first image identification result to obtain a second image identification result;
and step 24, identifying a lesion core region from the tumor region of the target identification image through the core region identification model to obtain a third image identification result, wherein the lesion core region is the highest dose region.
7. The method of claim 1, wherein the step of determining the position of the substrate comprises,
In the step 3, the residual liver region volume is obtained by calculating the input target region volume by means of a region identification result;
the specific calculation method of the residual liver area volume comprises the following steps:
Wherein v n is the volume of the remaining liver region, N is the number of image pixels of the remaining liver region, N 0 is the number of image pixels of the target region, v 0 is the volume of the target region, and α is a preset correction coefficient.
8. The method of claim 1, wherein the step of determining the position of the substrate comprises,
The radiation treatment plan performed in step 4 specifically includes:
Step 41, initializing a radiation treatment plan result, which specifically includes:
Setting the region coordinates of the first element of the radiation treatment plan result as the region boundary coordinates of the highest dose region, and setting the radiation dose of the first element of the radiation treatment plan result as the preset highest irradiation dose;
setting the region coordinates of the last element of the radiation treatment plan result as the region boundary coordinates of the residual liver region, and setting the radiation dose of the last element of the radiation treatment plan result as 500cGy;
and step 42, calculating the radiation areas and the radiation doses one by one from the highest dose area to the residual liver area, and storing the radiation areas and the radiation doses in a radiation treatment planning result.
9. The method of claim 8, wherein the step of determining the position of the first electrode is performed,
Step 42 specifically includes:
Step 421, setting the current region boundary coordinate list as the region boundary coordinate of the highest dose region, and setting the current region radiation dose as the preset highest irradiation dose;
Step 422, for each boundary point in the current region boundary coordinate list, obtaining a corresponding outer layer point according to an outer layer point searching rule, and combining all the outer layer points to obtain an outer layer region coordinate;
Step 423, judging whether the coordinates of all outer layer points exceed the residual liver area; if the remaining liver area is not exceeded, go to step 424; otherwise, ending;
Step 424, subtracting the interval radiation dose from the current regional radiation dose to obtain an outer layer radiation dose;
Step 425, saving the coordinates of the outer layer region and the outer layer radiation dose to the radiation treatment planning result; meanwhile, updating the current region boundary coordinate list into an outer layer region coordinate, and updating the current region radiation dose into an outer layer radiation dose; execution continues back at step 422.
10. The method of claim 8, wherein the step of determining the position of the first electrode is performed,
The outer layer point searching rule is as follows:
(1) Obtaining an image characteristic value f 1 of the current boundary point;
(2) Searching a residual liver region boundary point closest to the current boundary point from the region boundary of the residual liver region, and obtaining an image characteristic value f 2 of the point;
(3) The image characteristic gradual change value f 0 is calculated by the following steps:
wherein M is the number of preset dose levels, namely the number of levels of the radiation dose;
(4) Selecting a point which is farthest from the current boundary point and has an image characteristic value satisfying f 1+f0 +fb from the connecting line of the current boundary point and the corresponding boundary point of the residual liver region as an outer layer point corresponding to the current boundary point; fb is a preset degree of deviation of the image characteristic value.
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