CN110652661A - Convolution superposition dosage calculation system - Google Patents
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- A61N—ELECTROTHERAPY; MAGNETOTHERAPY; RADIATION THERAPY; ULTRASOUND THERAPY
- A61N5/00—Radiation therapy
- A61N5/10—X-ray therapy; Gamma-ray therapy; Particle-irradiation therapy
- A61N5/103—Treatment planning systems
- A61N5/1031—Treatment planning systems using a specific method of dose optimization
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- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61N—ELECTROTHERAPY; MAGNETOTHERAPY; RADIATION THERAPY; ULTRASOUND THERAPY
- A61N5/00—Radiation therapy
- A61N5/10—X-ray therapy; Gamma-ray therapy; Particle-irradiation therapy
- A61N5/1048—Monitoring, verifying, controlling systems and methods
- A61N5/1071—Monitoring, verifying, controlling systems and methods for verifying the dose delivered by the treatment plan
Abstract
The invention relates to a convolution superposition dose calculation system which comprises an information input module, a point kernel energy distribution simulation module, a point kernel model parameter extraction module, a point kernel lookup table generation module, a TERM value calculation module, a dose calculation module and an information output module, wherein the point kernel model parameter extraction module is used for constructing a new sampling model at a dose deposition point, and storing an included angle between a line segment from the dose deposition point to a collision point and an incident ray at the collision point by utilizing the axial symmetry characteristic and the rotation invariant characteristic of the new model to generate a lookup table. On one hand, the invention constructs a new sampling model at the dose deposit point, thereby improving the dose calculation precision; on the other hand, the rotation information of the point core is stored to generate a lookup table by utilizing the axial symmetry and the rotation invariance of the new model, so that the dose calculation speed is improved.
Description
Technical Field
The invention relates to the technical field of radiation therapy systems, in particular to a convolution superposition dose calculation system.
Background
Radiation therapy is one of the major current treatments for malignant tumors. Dose calculation is the core of a radiotherapy plan, and the speed and the precision of dose calculation have important influence on the efficiency and the quality of the radiotherapy plan. Research shows that the accuracy of the irradiation dose is improved by l%, and the cure rate can be improved by 2%. Generally, the allowable range of the irradiation dose error is ± 5% recommended in ICRU (international compliance units & measures) 24 report. In inverse planning of intensity modulated radiation therapy, the optimization process requires multiple dose calculations (about 10 to 1000), and therefore the calculation speed is also very demanding. A dose calculation model with clinical practicability can complete single-field and low-precision dose calculation within 1 minute; the calculation of multi-field, high-precision or optimized dose is completed within 1 hour.
Models for calculating dose distribution can be divided into 3 major classes: empirical models, semi-analytical models and analytical models. In order to meet the quality requirements of clinical radiotherapy planning, inverse planning dose calculations are generally performed using semi-analytical models, such as convolution superposition dose calculation methods based on kernel (pencil beam kernel, point kernel) models. Although the analytical model has the highest accuracy of dose calculation, the required calculation amount is very large, and the analytical model cannot be used for inverse planning dose calculation and is generally only used for calculating the dose distribution of the final treatment plan. The dose calculation method based on the semi-analytic model is relatively small in calculation amount compared with the analytic model, but the total calculation amount is also considerable when the dose distribution is calculated for multiple times in the inverse planning. Some hardware-accelerated methods are used to accelerate convolution superposition dose calculation methods based on kernel models, such as FPGA and GPU.
The semi-analytic model capable of meeting the accurate requirement of clinical radiotherapy is a point-core dose calculation method. The method of the point-and-core dose calculation has a large computational complexity. In the clinic, the radiation source is considered to be a point source, and the radiation is emitted to irradiate the tumor by taking the point source as a center. In the case where divergent rays are obliquely incident on the phantom surface, the kernel of the point at each collision point in the dose calculation process is rotated to be parallel to the rays passing through the collision point. Each point kernel is rotated under a rectangular coordinate system, the calculation complexity of the point kernel dose calculation method is increased, and the calculation time is increased by 2-3 times. The convolution superposition dose calculation method is a semi-analytic algorithm, and the calculation precision and the calculation speed of the convolution superposition dose calculation method are further improved.
In view of the above, there is a need for improvement in the art, and a need therefore exists for an improved method and apparatus.
Disclosure of Invention
The invention aims to provide a convolution superposition dosage calculation system to improve dosage calculation accuracy and dosage calculation speed.
In order to achieve the purpose of the invention, the following technical scheme is adopted.
A convolution superposition dose calculation system, comprising:
the information input module is used for inputting data information required by dose calculation, wherein the required data information comprises three-dimensional density information of a die body, organ delineation information, treatment head information and radiation field information;
the point nuclear energy distribution simulation module is used for simulating point nuclear energy distribution by utilizing a Monte Carlo algorithm according to the input treatment head information;
the point kernel model parameter extraction module is used for extracting the energy distribution of point kernels in each solid angle direction and performing parameter fitting to obtain point kernel model parameters;
the point kernel lookup table generation module is used for constructing a new sampling model at the dose deposition point, storing the included angle between the line segment from the dose deposition point to the collision point and the incident ray at the collision point by utilizing the axisymmetric characteristic and the rotation invariant characteristic of the new model, and generating a lookup table;
the TERM (Total Energy recovered per unit Mass) value calculating module is used for calculating two-dimensional fluence distribution on the surface of the mold body according to the treatment head information under a rectangular coordinate system, and calculating the intersection length of an incident beam and each voxel by using a ray tracing algorithm so as to calculate the TERM value of each voxel;
the dose calculation module is used for calculating the absolute position of a dose deposition point and reading a lookup table according to the position information; taking the incident direction of the dose deposition point ray as the initial direction of polar angle direction sampling, and calculating the position of a collision point in the axial direction of each solid angle; reading an included angle value between a line segment from the dose deposition point to the collision point at the collision point and an incident ray at the collision point from a lookup table according to the position information of the collision point; dose calculations were performed.
And the information output module outputs three-dimensional dose distribution under the rectangular coordinate system and counts the dose-volume curve of each organ.
Further, the point kernel lookup table generation module constructs a new sampling model at the dose deposit point, and takes the ray incidence direction at the dose deposit point as the initial direction of polar angle direction sampling.
Furthermore, the new model is on two solid angle axes with the same polar angle and different azimuth angles at the same dose deposition point, and the line segments from the dose deposition points to the collision points at the two collision points with the same relative position and the included angle value of the incident ray at the collision points are the same.
Furthermore, the new model rotates by taking the radiation source as a center and the distance from the radiation source to the dose deposition point as a radius, and at the new dose deposition point, the included angle value between the line segment from the dose deposition point to the collision point and the incident ray at the collision point is the same as the included angle value at the collision point with the same relative position as the original dose deposition point.
Further, the lookup table stores a set of included angle values at the collision points under different polar angles for the same source-to-dose deposition point distance.
Further, the convolution superposition dose calculation system is accelerated by adopting FPGA and/or GPU hardware.
The invention has the following beneficial effects: on one hand, the invention constructs a sampling model at the dose deposit point, and further improves the dose calculation precision; on the other hand, by utilizing the structural characteristics of the new model, the rotation information of the point core is stored to generate a lookup table so as to improve the dose calculation speed; due to the special structure of the algorithm, the algorithm is very suitable for hardware acceleration of the FPGA and the GPU.
Drawings
FIG. 1 is a block diagram of a convolution superposition dosage calculation system of the present invention.
FIG. 2 is a schematic diagram of ray parallel incidence for a convolution superposition dosimetry system of the present invention.
FIG. 3 is a schematic diagram of the ray tilt incidence of a convolution stack dose calculation system of the present invention.
FIG. 4 is a schematic diagram of a new model of a convolution superposition dose calculation system of the present invention.
FIG. 5 is a schematic diagram of the axial symmetry of a new model of a convolution superposition dose calculation system of the present invention.
FIG. 6 is a schematic diagram of the rotational invariance of a new model of a convolution superposition dose calculation system of the present invention.
Detailed Description
The invention is described in detail below with reference to the accompanying drawings and specific embodiments.
As shown in fig. 1, the present invention provides a convolution superposition dose calculation system, which includes an information input module 10, a point kernel energy distribution simulation module 20, a point kernel model parameter extraction module 30, a point kernel lookup table generation module 40, a TERM value calculation module 50, a dose calculation module 60, and an information output module 70.
The information input module 10 is used for inputting data information required by dose calculation, wherein the required data information comprises three-dimensional density information, organ delineation information, treatment head information and radiation field information of a patient. Wherein the three-dimensional density information of the patient can be CT images, MR images or patient density information acquired by other means. The organ delineation information can be obtained by delineating on the three-dimensional density information by a physicist, and can also be obtained by automatically delineating through automatic delineation software. The treatment head information comprises complete treatment head shape structure and parameter information, irradiation direction, position of isocenter and the like. In this embodiment, a spiral CT device is used to acquire CT data, which may be used to represent density information of a patient. The CT data is input into organ delineation software, and the physical engineer delineates the shape of each patient, so as to obtain the organ information of the patient.
The energy distribution simulation module 20 is configured to simulate energy distribution of the core-point model by using a monte carlo algorithm according to the input therapy head information. Simulating the energy distribution of the point kernels in a spherical coordinate system, wherein the sampling interval in the polar angle direction is 3.75 degrees, and the sampling number is 48; the sampling interval of the azimuth angle is 360 degrees, and the sampling number is 1; radial sampling with unequal intervals is used, the sampling number is 24, and the maximum range is 60 cm.
The point kernel model parameter extraction module 30 is configured to extract energy distribution of point kernels in each solid angle direction, and perform parameter fitting to obtain point kernel model parameters. In this embodiment, the energy spread function of the point kernel model is represented as:
wherein A isθ、aθ、BθAnd bθIs a parameter value related to the polar angle direction. And extracting energy distribution of each solid angle direction along the radial direction, and calculating the parameter value of the point kernel model (formula 1) by a fitting method.
The point core lookup table generating module 40 is configured to generate a lookup table. According to the theory of interaction, the dose calculation can be expressed as a convolution of the TERM value and the kernel model:
where T(s) is the TERM value from the original ray at point s. Strictly speaking, the spatial invariance of the kernel can be satisfied only under the condition that the single-energy ray is parallelly incident into the infinite uniform phantom, and the formula (2) can be established. Here we only discuss the effect of ray oblique incidence on the computational accuracy of equation (2). Although the equal-interval sampling mode is adopted for the azimuth angle phi and the polar angle theta, the solid angles at different sampling positions
Are different in magnitude, wherein phinAnd thetamRespectively, an azimuth value at the nth sampling position and a polar value at the mth sampling position. FIG. 2 is a schematic diagram of ray parallel incidence, wherein point r is the dose deposition point and point s is where the primary ray collidesA point, namely a TERM point. Taking the incident direction of the ray as the sampling starting point of the polar angle, and setting the polar angle position of the s point as theta and the azimuth angle as phi relative to the r point; with respect to the point s, the point r is located at a polar angular position β ═ pi- θ and at an azimuth angle Φ + pi. Because theta is complementary to beta, the solid angle omega where the s point is positionedθ,φSolid angle omega with point rβ,φ+π＝Ωπ-θ,φ+πAre equal.
Fig. 3 is a schematic diagram of oblique incidence of rays. Taking the direction of the z axis as a sampling starting point of a polar angle, and relative to a point r, the polar angle position of a point s is theta and the azimuth angle is phi; and taking the incident direction of the ray as the sampling starting point of the polar angle, wherein the polar angle position of the r point is beta ≠ pi-theta and the azimuth angle phi + pi relative to the s point. Since theta and beta are not complementary, the solid angle omega where the point s is positionedθ,φSolid angle omega with point rβ,φ+π≠Ωπ-θ,φ+πAnd are not equal. Therefore, in the case of oblique incidence of the ray, the dose calculation convolution formula of formula (2) does not hold, and not only the point kernel model h(s) at the point s needs to be rotated in the direction of the incident ray at the point s, but also the influence of the coincidence of the sampling intervals of the solid angle before and after rotation at the same position on the dose calculation accuracy needs to be considered. The polar angle sampling starting point at the r point is kept consistent with the r point, and similar to parallel incidence of rays, the dose calculation error caused by sampling inconsistency caused by rotation of a point kernel model at the s point can be reduced. However, the incident directions of the rays at the collision points s are not consistent, and the initial direction of polar angle sampling at the r point is determined according to the incident direction of the ray at one collision point s, which inevitably causes the dosage calculation errors at other collision points. In order to reduce the total error of the dose introduced by the sampling start direction of the polar angle, the invention takes the incident ray direction at the dose deposition point r as the sampling start point of the polar angle, as shown in fig. 4. Because the distance between the ray source and the surface of the model is larger, the incident ray at the collision point which is closer to the r point is approximately parallel to the incident ray at the r point, so that the interaction theorem is approximately satisfied, and the contribution of the collision points to the dose at the r point is far greater than that of other collision points; incident rays at collision points farther from the r point are not parallel to the incident rays at the r point and thus do not satisfy the theorem of interaction, but these collision pointsThe contribution to the dose at point r is small.
The dose calculation by using the new model requires the calculation of the initial point of polar angle sampling at the dose deposition point, which inevitably increases the algorithm complexity of dose calculation. However, the new model has axial symmetry and rotational invariance, and by utilizing the two characteristics, the algorithm complexity of convolution/superposition dose calculation can be further reduced. Figure 5 shows the axial symmetry of the new model. As shown in fig. 5, the collision point s is relative to the dose deposition point r1And s2Having the same polar angle theta and collision point s1And s2The distances to the dose deposition point r are the same. At these two collision points, the dose deposit point to collision point line segments are at equal angles α to the incident ray passing through the collision point. Therefore, the included angle α at the collision point can be calculated once at the same polar angle at the point r. The angle values are used to determine the values of the parameters in equation (1). FIG. 6 shows the rotation invariance of the new model. As shown in fig. 6, point r1And point r2Is two dose deposition points, points s, of equal length from the source1And point s2Is a relative point r1And point r2Two collision points at the same polar angle, azimuth angle and distance. At these two collision points, the angle α is also equal. Therefore, the included angle alpha at the collision point can be calculated once from the dose deposition point with the same length of the ray source.
In the convolution superposition dose calculation method, the calculation amount required for calculating the angle value at the collision point is very large. In the invention, the included angle value at the collision point is stored in the lookup table by utilizing the axial symmetry and the rotation invariance of the new model, so that the calculation amount required for calculating the included angle value in the dose calculation is greatly reduced. In this embodiment, the polar angle sampling number is 48, the radial sampling number is 60, the sampling interval in the depth direction of the phantom is 0.01cm, and the sampling number is 10000, so that the size of the total lookup table is 109.86 MB. The point check lookup table generation module only needs to generate a lookup table once for the same treatment head.
The TERM value calculation module 50 is configured to calculate a two-dimensional fluence distribution on the surface of the phantom according to the treatment head information in a rectangular coordinate system, and calculate the intersection length of the incident beam and each voxel by using a ray tracing algorithm, thereby calculating the TERM value of each voxel.
The dose calculation module 60 is configured to calculate an absolute position of a dose deposition point, and read a lookup table according to the position information; taking the incident direction of the dose deposition point ray as the initial direction of polar angle direction sampling, and calculating the position of a collision point in the axial direction of each solid angle; reading an included angle value between a line segment from the dose deposition point to the collision point at the collision point and an incident ray at the collision point from a lookup table according to the position information of the collision point; dose calculations were performed. The dose deposited at point r by the energy released at collision point s can be written as:
wherein omegamnIs the solid angle, η, relative to point r, at which point s is locatedrmnAnd ρrmnIs the relative density and density values at point r, T(s), σ(s) and ds are the TERM value, density value and radial infinitesimal length at point s, and the distance between point r and point s is rlThe distance is divided into l segments, each segment having a length Δ riRelative density of each segment is ηimn. Knowing the location of the s point, the T(s) and σ(s) values can be calculated; knowing the position of the r point, η can be calculatedrmnAnd ρrmnA value of (d); knowing the positions of the s point and the r point, the included angle between the line segment from the r point to the s point and the incident ray at the s point can be calculated, so that the parameter A is determinedm、am、BmAnd bmA value of (d); and knowing the length and relative density of each sampling interval from point r to point s, the ∑ η ∑ can be calculatedimnΔriThe value of (c). In the implementation, the dose is calculated by taking a dose deposition point as a center, the polar angle sampling interval is 3.75 degrees, and the sampling number is 48; the sampling interval of the azimuth angle is 45 degrees, and the sampling number is 8; the radial direction uses non-equal interval sampling, the sampling number is 60, and the maximum radius is 60 cm. Thus, the value of the radial sampling interval Δ riFixed, the relative density, and TERM values in each sampling interval are approximately equal to the relative density, and TERM values at the center point of the sampling interval. In view of the above, it is desirable to provide,knowing the location of points s and r, and the center location of each sampling interval between these two points, the dose deposition at point r of the energy released at the collision point s can be calculated using equation (3).
The information output module 70 is configured to output three-dimensional dose distribution in a rectangular coordinate system, and count dose-volume curves of each organ.
To verify the validity of the algorithm of the present invention, a new algorithm was tested in a water phantom. The size of the used water model is 128 multiplied by 128, and the sampling intervals of the x direction, the y direction and the z direction are all 0.25 cm; irradiating the water phantom by using a 6MeV ray source, wherein the distance from the ray source to the surface layer of the phantom is 100 cm; the two-dimensional fluence map of the die body surface layer is a uniform fluence map, the size of the uniform fluence map is 40 multiplied by 40, and the sampling intervals in the x direction and the y direction are both 0.5 cm. The new method is compared with the ray parallel incidence method and the ray oblique incidence method. From the experimental results, the new method avoids the dose 'humping' phenomenon at the edge of the section dose ray, and is closer to the result of the dose calculation method of directly rotating the point kernel. The calculation time required by the ray parallel incidence method is 108.8 s; the calculation time required by the ray oblique incidence method is 305.4 s; the calculation time required for the new process was 200.5 s. Compared with the ray oblique incidence method, the calculation time required by the novel method is shortened by 34%.
According to the convolution superposition dose calculation system, on one hand, a new sampling model at a dose deposit point is constructed, and the dose calculation precision is improved; on the other hand, the rotation information of the point core is stored to generate a lookup table by utilizing the axial symmetry and the rotation invariance of the new model, so that the dose calculation speed is improved.
The foregoing shows and describes the general principles and features of the present invention, together with the advantages thereof. It will be understood by those skilled in the art that the present invention is not limited to the embodiments described above, which are described in the specification and illustrated only to illustrate the principle of the present invention, but that various changes and modifications may be made therein without departing from the spirit and scope of the present invention, which fall within the scope of the invention as claimed. The scope of the invention is defined by the appended claims and equivalents thereof.
Claims (6)
1. A convolution superposition dose calculation system, comprising:
the information input module is used for inputting data information required by dose calculation, wherein the required data information comprises three-dimensional density information of a die body, organ delineation information, treatment head information and radiation field information;
the point nuclear energy distribution simulation module is used for simulating point nuclear energy distribution by utilizing a Monte Carlo algorithm according to the input treatment head information;
the point kernel model parameter extraction module is used for extracting the energy distribution of point kernels in each solid angle direction and performing parameter fitting to obtain point kernel model parameters;
the point kernel lookup table generation module is used for constructing a new sampling model at the dose deposition point, storing the included angle between the line segment from the dose deposition point to the collision point and the incident ray at the collision point by utilizing the axisymmetric characteristic and the rotation invariant characteristic of the new model, and generating a lookup table;
the TERM value calculation module is used for calculating the two-dimensional fluence distribution on the surface of the mold body according to the treatment head information under a rectangular coordinate system, and calculating the intersection length of an incident beam and each voxel by using a ray tracing algorithm so as to calculate the TERM value of each voxel;
the dose calculation module is used for calculating the absolute position of a dose deposition point and reading a lookup table according to the position information; taking the incident direction of the dose deposition point ray as the initial direction of polar angle direction sampling, and calculating the position of a collision point in the axial direction of each solid angle; reading an included angle value between a line segment from the dose deposition point to the collision point at the collision point and an incident ray at the collision point from a lookup table according to the position information of the collision point; dose calculations were performed.
And the information output module outputs three-dimensional dose distribution under the rectangular coordinate system and counts the dose-volume curve of each organ.
2. The system of claim 1, wherein the point kernel lookup table generation module constructs a new sampling model at the dose deposit point, and uses the incident direction of the ray at the dose deposit point as the starting direction of the polar angle direction sampling.
3. A convolution superposition dose calculation system according to claim 2, wherein the new model is on two solid angle axes with the same polar angle and different azimuth angles at the same dose deposition point, and the line segment from the dose deposition point to the collision point at the two collision points with the same relative position has the same included angle value as the incident ray at the collision point.
4. A convolution superposition dose calculation system according to claim 2, wherein the new model is rotated around the source as the center and the distance from the source to the dose deposition point as the radius, and at the new dose deposition point, the line segment from the dose deposition point to the collision point has the same included angle value with the incident ray at the collision point as the included angle value at the collision point with the same relative position as the original dose deposition point.
5. A convolution superposition dose calculation system according to claim 1, wherein the look-up table stores a copy of the pinch angle values at the collision points at different polar angles for the same source-to-dose deposition point distance.
6. The system of claim 1, wherein the system employs FPGA and/or GPU hardware acceleration.
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| CN111494815A (en) * | 2020-05-14 | 2020-08-07 | 安徽慧软科技有限公司 | Three-dimensional dose calculation method, device and medium based on mixed variable-scale model |
| CN111494815B (en) * | 2020-05-14 | 2022-04-29 | 安徽慧软科技有限公司 | Three-dimensional dose calculation method, device and medium based on mixed variable-scale model |
| CN113117253A (en) * | 2021-04-20 | 2021-07-16 | 中北大学 | Dose calculation system based on anisotropic kernel |
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