A nanodose-weighted dose optimization method for ion irradiation scheme design

Abstract

This invention discloses a method for designing an ion irradiation scheme based on nanodose-weighted dose optimization. By optimizing the ion irradiation scheme using nanodose-weighted dose, the invention fully utilizes the radiation quality of the ion beam, enabling more precise ion irradiation scheme and plan design, thereby improving the accuracy of applying and predicting ion beam radiation effects.

Description

Technical Field

[0001] The present invention relates to a method for designing ion irradiation plans based on nanodose-weighted dose (NQWD) optimization. This method can achieve nanodose-weighted dose optimization for the irradiation target area, thereby reducing the biological uncertainty associated with relative biological effectiveness (RBE)-weighted dose optimization. The present invention can be used in the design of ion beam irradiation plans and programs, as well as in radiation protection. Background Art

[0002] Ion radiotherapy has developed into a mature technology, but there are still some radiobiological issues that need further research and resolution. The ion beam irradiation plan aims to provide a uniform biologically effective dose to the irradiated tumor target area and maximize the protection of organs at risk around the target area. Compared with photon irradiation, the uncertainty of the biological effective dose must be incorporated into the ion beam irradiation plan, especially when the organs at risk are near the target area. At present, the trend in the design of ion irradiation plans is to implement personalized treatment considering specific patient, tissue, and tumor-related factors, which requires the development of more rigorous strategies.

[0003] Currently, ion beam irradiation protocol design often uses RBE-weighted dose (RWD), where the RBE is calculated using biophysical models. However, RBE values ​​are influenced by many factors and have significant uncertainty, increasing the risk of ion irradiation. For example, different institutions use different RBE models when implementing RWD. Japan primarily uses the mixed beam model or the microdose kinetic model (MKM), while Europe primarily uses the local effects model (LEM). Fossati et al. compared the RBE models (LEM and MKM) in use (P. Fossati, et al. Physics in Medicine and Biology. 2012, 57:7543). Their results showed that the physical doses produced by the same RWD using different RBE models varied by up to 15%. Currently, it is unclear which RBE model is more accurate. Future efforts are needed to confirm the reproducibility of results from a single institution and to conduct multicenter trials. Secondly, in clinical settings, multiple clinical endpoints are of interest. These clinical endpoints have varying dependencies on radiation quality and fractionation, resulting in different RBE values. Furthermore, existing RBE models do not consider the effects of irradiation fractionation. It is well known that the tumor microenvironment exhibits an adaptive response during radiation exposure, and the same dose of photons or ions produces different irradiation effects in the first and third fractions. However, most RBE experiments conducted in vivo or in vitro are based on a single fraction. Furthermore, experimental conditions, cellular oxygen levels, cell cycle phase, and cell type all influence RBE values. Future plans exist to expand ion therapy to include helium (He) ions, oxygen (O) ions, and mixed ion beam therapy, further increasing the complexity of ion irradiation protocol design.

[0004] To reduce the biological uncertainty caused by RBE values, different forms of robust optimization have been developed. However, the problem of quantitatively describing the factors affecting RBE is still in the exploratory stage, making the interpretation of the results of biological robust optimization more difficult. On the other hand, some scholars have proposed an ion irradiation scheme optimization method based on the physical quantities of dose and linear energy transfer (LET), and have proven that it can effectively reduce the biological uncertainty caused by RBE changes during ion irradiation. However, LET has limitations in its use. Experiments have shown that different ion beams with the same LET have different RBE values, that is, they cannot be used to set absolute dose limits. Therefore, the practicality of ion beam irradiation schemes based on LET is poor. These limitations have increased the interest in nanodose quantities as the basis for ion irradiation scheme design. Summary of the Invention

[0005] In order to achieve precise ion irradiation scheme design and reduce the biological uncertainty introduced by the use of RBE values, the present invention proposes a method for irradiation scheme design based on nanodose physical quantities. This method can not only fully utilize the essential characteristics of ion beam radiation quality and reduce the biological uncertainty in RWD-based optimization of ion irradiation schemes, but also, with the development of experimental nanodose, can measure nanodose physical quantities to achieve rapid verification of ion irradiation schemes, improve the precision and accuracy of ion beam irradiation, and ensure the safe and effective implementation of ion beam irradiation. In addition, the present invention can also be applied to aspects such as radiation protection, such as the re-evaluation of radiation protection doses based on nanodose physical quantities.

[0006] The method for designing an irradiation scheme based on nanodose physical quantities provided by the present invention comprises the following steps:

[0007] 1) Acquisition of dose and nanodose quantities

[0008] The dose distribution D of the ion beam is obtained by experimental measurement or calculated by Monte Carlo (MC) simulation and analytical methods;

[0009] The probability density distribution P(v|Q) of the ionization cluster size v of the photon and ion beam is obtained by nanodose meter measurement or calculated by track structure MC simulation. The normalized probability density distribution is calculated by formula 1:

[0010]

[0011] Where Q is the radiation quality of the photon or ion beam, and v is the size of the ionized cluster;

[0012] According to the probability density distribution of ionized cluster size, the cumulative probability F2 of the probability density distribution of ionized cluster size v≥2 is calculated by formula (2):

[0013]

[0014] According to the probability density distribution of ionized cluster size, the cumulative probability F3 of the probability density distribution of ionized cluster size v≥3 is calculated by formula (3):

[0015]

[0016] According to the probability density distribution of ionized cluster size, the cumulative probability F of the probability density distribution of ionized cluster size v≥n is calculated by formula (4): n :

[0017]

[0018] The obtained ion beam dose distribution D and nanodose quantities F2, F3 and F nMake a table as the basic data for ion irradiation program design.

[0019] Wherein, the ionization cluster size v is the number of ionizations occurring within a nanovolume element;

[0020] 2) Design of ion beam irradiation scheme

[0021] Select the appropriate nanodose dose F according to the radiation sensitivity of the irradiated target area n According to the prescription dose of photons and the dose limit of organs at risk, the prescription dose of the target area and the dose limit of organs at risk of the ion beam irradiation scheme are determined according to formula (5):

[0022]

[0023] In the above formula, NQWD is the nanodose-weighted dose, D is the physical absorbed dose (i.e., the dose distribution of the ion beam in step 1), and F n_Ion and F n_X are the cumulative probabilities of ion beam and X-ray ionization cluster size v ≥ n, respectively;

[0024] By calculating the obtained nanodose quantity and basic dose distribution data, the existing RWD optimization algorithm is used to optimize the NQWD and obtain a uniform NQWD irradiation plan in the target area.

[0025] In step 1) of the above method, when applying the track structure MC simulation, the MC simulation modeling geometry introduces the simplified DNA chromatin model proposed by Bueno et al. (M. Bueno, et al. Physics in Medicine and Biology. 2015, 60: 8583-8599), such as Figure 1 As shown in the figure, 1800 small cylinders (bottom diameter 2.3nm, height 3.4nm) are uniformly and randomly distributed without overlapping in a large cylinder (bottom diameter 30.4nm, height 161nm). The small cylinder is the nanovolume element mentioned above, corresponding to the size of 10 base pairs of the DNA double helix structure, and the large cylinder corresponds to a chromatin fiber.

[0026] The photons are X-rays, and the ion beams are proton beams and heavy ion beams.

[0027] The energy of the X-ray is in the range of kV-MV, and the energy of the ion beam is in the range of 10MeV / n-500MeV / n.

[0028] Cumulative probability is currently considered to be the most relevant nanodose quantity for radiobiological effects. Figure 2 The dependence of DNA double-strand break yield on the nanodose doses of different ion beams (F2, F3 and F4) is shown.

[0029] The probability density distribution of ionized cluster size is simulated and calculated at different penetration depths.

[0030] In step 2) of the above method, for radiation applications, it is necessary to convert single-event nanodose quantities into multi-event nanodose quantities. The dose used in ion radiotherapy is low enough, so there is only a single ion interacting with it in the nanovolume element. That is, the multi-event nanodose quantities can be obtained by linearly superposing the single-event nanodose quantities. Since the multi-event nanodose quantities increase linearly with the beam flux, the current algorithm used for RWD optimization can be directly applied to NQWD-based optimization.

[0031] The target area prescription dose and the dose limit of organs at risk of the ion irradiation scheme based on NQWD optimization can be determined based on the experience of photons. Therefore, the simplified DNA chromatin model constructed by the ion beam MC simulation mentioned above is used to simulate and calculate the probability density distribution of the ionization cluster size of photons, and then calculate the nanodose quantities F2, F3, F n wait.

[0032] Select the appropriate nanodose dose F according to the radiation sensitivity of the irradiated target area n For the target area that is sensitive to radiation, a nanodose with a smaller n is selected, and for the target area that is resistant to radiation, a nanodose with a larger n is selected.

[0033] The method of the present invention further comprises the step of implementing the ion beam irradiation plan obtained by the method of the present invention on a passive beam delivery device.

[0034] In the present invention, the passive beam delivery device can be similar devices known in the art, including but not limited to ridge filters (e.g., the device described in Kanai T, Furusawa Y, Fukutsu K, Itsukaichi H, Eguchi Kasai K, Ohara H (1997) Irradiation of Mixed Beam and Design of Spread-Out Bragg Peak for Heavy-Ion Radiotherap. Radiation Research. 147:78), rotational energy reduction devices (e.g., the device described in Chinese Patent Application No. CN 200710018043.2), etc. After passing through the passive beam delivery device, the ion beam will be modulated into a series of ion beams with different ranges, which will be superimposed on each other to form a broadened Bragg peak, thereby achieving irradiation of the radiation target area.

[0035] In another preferred embodiment, the method of the present invention further comprises the step of implementing the ion beam irradiation plan obtained by the method of the present invention on an active beam delivery device.

[0036] In the present invention, the active beam delivery device can adopt similar devices known in the art, including, but not limited to, a spot scanning beam delivery device (for example, the device described in Kanai T, Kawachi K, Kumamoto Y, et al. Spotscanning system for proton radiotherapy. Medical Physics, 1980, 7(4): 365-369), a raster scanning beam delivery device (for example, the device described in Furukawa T, Inaniwa T, Sato S, et al. Design study of a raster scanning system for moving target irradiation in heavy-ion radiotherapy. Medical Physics, 2007, 34(3): 1085), etc.

[0037] The present invention also provides a passive beam delivery device, which includes: an industrial computer, an ion beam accelerator, an ion beam extraction device, a ridge filter or a rotational energy degeneration device, wherein the industrial computer includes a central processing unit, and the central processing unit is capable of executing steps 1) to 2) of the method of the present invention to obtain an ion beam irradiation plan and generate a control signal containing the ion beam irradiation plan, and send the control signal to the ion beam accelerator, the ion beam extraction device, the ridge filter or the rotational energy degeneration device so as to irradiate the target area according to the ion beam irradiation plan.

[0038] It can be understood that the passive beam delivery device of the present invention can be configured with reference to the existing technology (for example, Kanai T, Furusawa Y, Fukutsu K, Itsukaichi H, Eguchi-Kasai K, Ohara H (1997) Irradiation of Mixed Beam and Design of Spread-Out Bragg Peak for Heavy-Ion Radiotherap. Radiation Research. 147: 78 and Chinese patent application number CN 200710018043.2).

[0039] The present invention also provides an active beam delivery device, which includes: an industrial computer, an ion beam extraction device, an ion beam accelerator with variable extraction energy, a Bragg peak micro-broadening device, an ion beam dose monitoring device and a scanning magnet, wherein the industrial computer includes a central processing unit, and the central processing unit is capable of executing steps 1) to 2) of the method of the present invention to obtain an ion beam irradiation plan and generate a control signal containing the ion beam irradiation plan, and sending the control signal to the ion beam extraction device, the ion beam accelerator with variable extraction energy, the Bragg peak micro-broadening device, the ion beam dose monitoring device and the scanning magnet so as to irradiate the target area according to the ion beam irradiation plan.

[0040] It can be understood that the active beam delivery device of the present invention can be configured with reference to the existing technology (for example, Kanai T, Kawachi K, Kumamoto Y, et al. Spot scanning system for proton radiotherapy [J]. Medical Physics, 1980, 7 (4): 365-369 or Furukawa T, Inaniwa T, Sato S, et al. Design study of a raster scanning system for moving target irradiation in heavy-ion radiotherapy. Medical Physics. 2007, 34 (3): 1085. etc.).

[0041] It is understood that in the present invention, the industrial computer can be any industrial control computer (system) in the art that has computing, analysis, data processing, and control functions (installed with corresponding computing and analysis software commonly used in the art and equipped with a controller). Both the method and the verification method of the present invention can be stored in the form of a software program in the industrial computer and executed by a central processing unit.

[0042] With the development of experimental nanodose and track structure Monte Carlo (MC) simulation, the correlation between nanodose quantities and cell survival data has been verified, which makes it possible to design ion irradiation schemes using nanodose quantities and track structure MC simulations. The present invention uses nanodose weighted dose to optimize the ion irradiation scheme, which essentially makes full use of the radiation quality of the ion beam, realizes a more accurate ion irradiation scheme design, and thus improves the accuracy of applying and predicting the radiation effects of the ion beam. Compared with the solution disclosed in the patent (CN110412639B) of quantifying the radiation effect by nanodose quantities and then designing the irradiation scheme based on the radiation effect, the solution of the present invention is to directly design the irradiation scheme through the physical quantity of nanodose quantities, reducing the uncertainty of the biological effects involved.

[0043] The advantages and effects of the present invention are as follows: (1) it can reduce the biological uncertainty introduced by using RBE weighted dose optimization, and provide a powerful means for designing accurate ion irradiation schemes; (2) it can make full use of the radiation quality of the ion beam in essence, and can realize the design of more accurate ion irradiation schemes, thereby improving the reliability of ion irradiation effects; (3) nanodose physical quantities are used to design ion irradiation schemes, and nanodose quantities can be obtained by nanodose meter measurement or track structure MC simulation calculation, thereby realizing rapid and accurate verification of ion irradiation schemes; (4) through measurable physical quantities, the widely used photon irradiation experience is applied to the design of ion irradiation schemes, so that the ion irradiation schemes of different institutions can be directly compared; (5) the application scope of the method of the present invention is not limited to the field of ion irradiation, but can also be applied to other fields such as radiation protection. BRIEF DESCRIPTION OF THE DRAWINGS

[0044] Figure 1 To simplify the DNA chromatin filament model, one of the small cylinders is a nanovolume element.

[0045] Figure 2 is the dependence of DNA double-strand break yield on nanodose dose (F2, F3 and F4).

[0046] Figure 3 This is a flow chart of the ion irradiation scheme design method based on NQWD optimization of the present invention.

[0047] Figure 4 This is the integrated depth dose distribution of a 150.71 MeV / n carbon ion pencil beam in an embodiment of the present invention and the selected penetration depth for calculating nanodose quantities.

[0048] Figure 5 Figure 3 is the dependence of the nanodose dose (F2, F3, and F4) of a 150.71 MeV / n carbon ion pencil beam at different penetration depths on the penetration depth in an embodiment of the present invention.

[0049] Figure 6 Figure 5 is the dependence of the ratio of the nanodose dose (F2, F3 and F4) of the 150.71 MeV / n carbon ion pencil beam at different penetration depths to the 6 MV X-ray nanodose dose (F2, F3 and F4) on the penetration depth in an embodiment of the present invention. DETAILED DESCRIPTION

[0050] The present invention will be further described in detail below in conjunction with specific embodiments. The examples provided are only for illustrating the present invention and are not intended to limit the scope of the present invention. The examples provided below can serve as a guide for further improvements by those skilled in the art and are not intended to limit the present invention in any way.

[0051] Unless otherwise specified, the experimental methods in the following examples are conventional methods and were performed according to the techniques or conditions described in the literature in the field or according to the product instructions. The materials and reagents used in the following examples, unless otherwise specified, were all commercially available.

[0052] Example 1

[0053] Combined with the case of designing ion irradiation plan based on the open source radiotherapy planning system matRad, the ion irradiation plan design method based on NQWD optimization is further described. Figure 3 As shown,

[0054] It is divided into the following six steps:

[0055] (1) MC simulation calculates the dose-related data of the matRad input database. In order to cover most tumor target scenarios encountered in clinical applications, the database simulates a carbon ion pencil beam with a total of 121 energies, ranging from 115.23 MeV / n to 398.84 MeV / n, covering a depth of 27.1 mm to 260.5 mm in water, with an energy layer spacing of 2 mm and a Bragg peak width of 6 mm.

[0056] (2) MC simulation calculation of nanodose related data in matRad input database. First, a simplified DNA chromatin filament model for track structure MC simulation was established, and the basic data of ionization cluster size probability density distribution at different penetration depths of 6MV X-rays and ion beams were simulated respectively. Each energy carbon ion beam adopts a variable spacing method, that is, the plateau area is sparse and the peak area is dense. About 60 penetration depths are selected for ionization cluster size probability density distribution simulation calculation. The penetration depth position information is as follows: Figure 4 As shown;

[0057] (3) According to the probability density distribution of ionized cluster size and the nanodose calculation formulas (2)-(4), the nanodose quantities F2, F3, and F are calculated respectively. n The calculated nanodose quantities at different penetration depths are as follows: Figure 5 As shown in Figure 2, the nanodose quantity at any penetration depth can be obtained by using the PHCIP difference;

[0058] (4) Select the appropriate nanodose dose according to the radiation sensitivity of the tumor in the irradiated target area. For tumors with high radiation sensitivity, select the nanodose dose F2; the stronger the tumor's radiation resistance, the larger the nanodose dose n. Figure 6 The figure shows the dependence of the ratio of the nanodose dose of the 150.71MeV / n carbon ion pencil beam to the nanodose dose of the 6MV X-ray at different penetration depths on the penetration depth.

[0059] (5) Based on the prescription dose of photons and the dose limit of organs at risk, determine the prescription dose of the target area and the dose limit of organs at risk of the ion beam irradiation plan according to formula (5);

[0060] (6) Based on the basic data such as nanodose and dose obtained by calculation, the existing RWD optimization algorithm is used to optimize the NQWD to obtain a uniform NQWD irradiation plan within the target area.

[0061] The present invention has been described in detail above. For those skilled in the art, without departing from the purpose and scope of the present invention, and without the need to carry out unnecessary experimental conditions, the present invention can be implemented in a wide range under equivalent parameters, concentrations and conditions. Although the present invention provides specific embodiments, it should be understood that further improvements can be made to the present invention. In short, according to the principles of the present invention, this application is intended to include any changes, uses or improvements to the present invention, including changes that depart from the disclosed scope in this application and are made using conventional techniques known in the art.

Claims

1. A method for designing an irradiation plan based on nanodose physical quantities, comprising the following steps: 1) Acquisition of dose and nanodose quantities The dose distribution of the ion beam is obtained by experimental measurement or calculated by Monte Carlo (MC) simulation and analytical methods; The probability density distribution P(v|Q) of the ionization cluster size v of the photon and ion beam is obtained by nanodose meter measurement or calculated by track structure MC simulation. The normalized probability density distribution is calculated by formula 1: in, Q is the radiation quality of the photon or ion beam, v is the ionization cluster size; According to the probability density distribution of ionized cluster size, the cumulative probability F2 of the probability density distribution of ionized cluster size v≥2 is calculated by formula (2): According to the probability density distribution of ionized cluster size, the cumulative probability F3 of the probability density distribution of ionized cluster size v≥3 is calculated by formula (3): According to the probability density distribution of ionized cluster size, the cumulative probability F of the probability density distribution of ionized cluster size v≥n is calculated by formula (4): n : The obtained ion beam dose distribution and nanodose quantities F2, F3 and F n Make a table as the basic data for ion irradiation program design. Wherein, the ionization cluster size v is the number of ionizations occurring within a nanovolume element; 2) Design of ion beam irradiation scheme Select the appropriate nanodose dose F according to the radiation sensitivity of the irradiated target area n According to the prescription dose of photons and the dose limit of organs at risk, the prescription dose of the target area and the dose limit of organs at risk of the ion beam irradiation scheme are determined according to formula (5): In the above formula, NQWD is the nanodose weighted dose, D is the physical absorption dose, F n_Ion and F n_X are the cumulative probabilities of ion beam and X-ray ionization cluster size v ≥ n, respectively; By calculating the obtained nanodose quantity and basic dose distribution data, the existing relative biological effect weighted dose (RWD) optimization algorithm is used to optimize the NQWD and obtain a uniform NQWD irradiation plan within the target area.

2. The method according to claim 1, wherein: The photons are X-rays, and the ion beams are proton beams and heavy ion beams.

3. The method according to claim 2, wherein: The energy of the X-ray is in the range of kV-MV, and the energy of the ion beam is in the range of 10MeV / n-500MeV / n.

4. The method according to any one of claims 1 to 3, characterized in that: The application scenario of the method is ion beam tumor radiotherapy and related irradiation plan design.

5. The method according to any one of claims 1 to 4, characterized in that: In step 2), the appropriate nanodose dose F is selected according to the radiation sensitivity of the irradiated target area. n For the target area that is sensitive to radiation, a nanodose with a smaller n is selected, and for the target area that is resistant to radiation, a nanodose with a larger n is selected.

6. A passive beam delivery device, comprising: An industrial computer, an ion beam accelerator, an ion beam extraction device, a ridge filter or a rotational energy degrading device, wherein the industrial computer includes a central processing unit, and the central processing unit is capable of executing steps 1) to 2) of any one of claims 1 to 5 to obtain an ion beam irradiation plan and generate a control signal containing the ion beam irradiation plan, and sending the control signal to the ion beam accelerator, the ion beam extraction device, the ridge filter or the rotational energy degrading device so as to irradiate the target area according to the ion beam irradiation plan.

7. An active beam delivery device, comprising: An industrial computer, an ion beam extraction device, an ion beam accelerator with variable extraction energy, a Bragg peak micro-broadening device, an ion beam dose monitoring device, and a scanning magnet, wherein the industrial computer includes a central processing unit, and the central processing unit is capable of executing steps 1) to 2) of any one of claims 1 to 5 to obtain an ion beam irradiation plan and generate a control signal containing the ion beam irradiation plan, and sending the control signal to the ion beam extraction device, the ion beam accelerator with variable extraction energy, the Bragg peak micro-broadening device, the ion beam dose monitoring device, and the scanning magnet to irradiate the target area according to the ion beam irradiation plan.

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