Method for determining adjustment value of planning target volume and storage medium

Abstract

The present disclosure relates to the medical field, in particular to a method for determining adjustment value of a planning target volume and a storage medium, wherein the method comprises: determining a reference image of a treatment target positioned on a treatment device based on a treatment plan; obtaining sample images of the treatment target positioned on the treatment device multiple times; determining a transformation matrix of the sample images relative to the reference image; calculating a mean value and a standard deviation corresponding to a degree of freedom; calculating an angle conversion value corresponding to a rotational degree of freedom according to the mean value and the standard deviation corresponding to the rotational degree of freedom, and calculating an angle equivalent displacement according to the angle conversion value; and determining an adjustment value of the planning target volume in each translational direction according to the mean value corresponding to the translational degree of freedom and the angle equivalent displacement. According to the present disclosure, considering the random fluctuations of multiple positions, the PTV can be reasonably adjusted so that the adjusted target volume can cover all tumor cells and will not cause excessive damage to the organs at risk.

Description

Technical Field

[0001] This disclosure relates to the field of medical technology, and in particular to a method for determining the adjustment value of the planned target area and a computer-readable storage medium. Background Technology

[0002] In radiotherapy, tumor cells in the target area can be killed by firing particles towards the target area. For example, in boron neutron capture therapy (BNCT), boron-containing drugs can be selectively enriched in tumor tissue, and short-range high-LET (linear energy transfer) particles can be generated by the capture reaction of neutrons with boron (e.g., 10B) to achieve selective killing of tumor cells.

[0003] Since tumor cells are generally irregular in shape, that is, the target area is irregular in shape, millimeter-level translation or small-angle rotation may result in under-irradiation of the target area edge, or cause organs at risk to enter the high-dose gradient area.

[0004] It is evident that radiotherapy can kill tumor cells in the target area, but this depends on the consistency between the target area, radiation flux, and the positioning of the treatment target (e.g., the patient). For example, for BNCT, this depends on the consistency between the target area, boron concentration, radiation field, neutron flux, and the positioning of the treatment target (e.g., the patient). Summary of the Invention

[0005] This disclosure provides a method for determining the adjustment value of the planned target area, a device for determining the adjustment value of the planned target area, a treatment device, and a computer-readable storage medium to address the deficiencies in related technologies.

[0006] According to a first aspect of the present disclosure, a method for determining the adjustment value of a planned target area is proposed, comprising: determining a reference image of the positioning of a treatment target on a treatment device based on a treatment plan, wherein the reference image includes a planned target area and an organ at risk; acquiring sample images of the treatment target positioned multiple times on the treatment device; determining a transformation matrix of the sample images relative to the reference image, wherein the transformation matrix corresponds to multiple degrees of freedom, including translational degrees of freedom and rotational degrees of freedom; calculating the mean and standard deviation corresponding to the degrees of freedom; calculating the angle transformation value corresponding to the rotational degrees of freedom based on the mean and standard deviation corresponding to the rotational degrees of freedom, calculating the angular equivalent displacement based on the angle transformation value; and determining the adjustment value of the planned target area in each translational direction based on the mean corresponding to the translational degrees of freedom and the angular equivalent displacement.

[0007] Optionally, the translational degrees of freedom include a first translational direction x (Δx), a second translational direction y (Δy), and a third translational direction z (Δz), wherein the first translational direction, the second translational direction, and the third translational direction are perpendicular to each other; and / or, the rotational degrees of freedom include a first rotational direction. degrees of freedom Second rotation direction degrees of freedom Third rotation direction degrees of freedom Wherein, the rotation axis of the first rotation direction is the first translation direction, the rotation axis of the second rotation direction is the second translation direction, and the rotation axis of the third rotation direction is the third translation direction.

[0008] Optionally, calculating the angle transformation value corresponding to the rotational degree of freedom based on the mean and standard deviation of the rotational degree of freedom includes: calculating the angle transformation value based on the following formula. : ; in, for The corresponding mean, for The corresponding standard deviation for The corresponding mean, for The corresponding standard deviation for The corresponding mean, for The corresponding standard deviation is the confidence coefficient, which is related to the number of sample images.

[0009] Optionally, calculating the equivalent angular displacement based on the angular conversion value includes: calculating the equivalent angular displacement based on the following formula. : ; in, express The corresponding tangent value, r, is the distance from the edge of the planned target area to the... The distance corresponding to the axis of rotation.

[0010] Optionally, determining the adjustment value of the planned target area in each translation direction based on the mean value corresponding to the translational degree of freedom and the equivalent angular displacement includes: determining the adjustment value of the planned target area in the translational direction based on the mean value corresponding to the translational direction in the translational degree of freedom, the equivalent angular displacement, and the conservative standard deviation corresponding to the translational direction; wherein, the conservative standard deviation corresponding to degree of freedom j Calculated based on the following formula: ; in, Let j be the standard deviation corresponding to the degree of freedom j. This is the historical prior lower bound of the standard deviation corresponding to the stated degree of freedom j.

[0011] Optionally, determining the adjustment value of the planned target area in each translation direction based on the mean value corresponding to the translational degree of freedom and the equivalent angular displacement includes: determining the adjustment value of the planned target area in the translational direction based on the mean value corresponding to the translational direction in the translational degree of freedom, the equivalent angular displacement, and the system error.

[0012] Optionally, the method further includes: based on the mean value corresponding to the degree of freedom j and standard deviation Calculate the confidence intervals of the degrees of freedom based on the t-distribution. , wherein Calculated based on the following formula: ; Where k is the confidence level and n is the number of sample images. It is the quantile of the t-distribution with n-1 degrees of freedom and the cumulative probability value CP.

[0013] Optionally, the method further includes: determining the transformation matrix corresponding to the i-th sample image among the n sample images. Where n is an integer greater than 1; determine the voxel v in the reference image in the transformation matrix. The corresponding irradiation dose under the condition The irradiation dose corresponding to voxel v is determined based on the following formula. Expected value : .

[0014] Optionally, the method further includes: calculating the probability of exceeding the radiation dose limit corresponding to voxel v based on the following formula. : ; in, The threshold is predefined, and I[x] is an indicator function that takes the value 1 when the condition in the parentheses is true and takes the value 0 when the condition in the parentheses is false.

[0015] According to a second aspect of the present disclosure, an apparatus for determining the adjustment value of a planned target area is provided, comprising: an acquisition module configured to determine a reference image of the placement of a treatment target on a treatment device based on a treatment plan, wherein the reference image includes a planned target area and an organ at risk; acquiring sample images of the treatment target placed multiple times on the treatment device; determining a transformation matrix of the sample images relative to the reference image, wherein the transformation matrix corresponds to multiple degrees of freedom, including translational degrees of freedom and rotational degrees of freedom; and a processing module configured to calculate the mean and standard deviation corresponding to the degrees of freedom; calculate an angle transformation value corresponding to the rotational degrees of freedom based on the mean and standard deviation corresponding to the rotational degrees of freedom; calculate an angular equivalent displacement based on the angle transformation value; and determine an adjustment value of the planned target area in each translational direction based on the mean corresponding to the translational degrees of freedom and the angular equivalent displacement.

[0016] According to a third aspect of the present disclosure, a treatment device is provided, including a processor; a memory for storing processor-executable instructions; wherein the processor is configured to implement the methods described in the first aspect and any of the alternative embodiments of the first aspect.

[0017] According to a fourth aspect of the present disclosure, a computer-readable storage medium is provided that stores a computer program thereon, which, when executed by a processor, implements the methods described in the first aspect and any of the alternative embodiments of the first aspect.

[0018] The technical solutions provided by the embodiments of this disclosure may include the following beneficial effects: According to embodiments of this disclosure, multiple sample images obtained through multiple positioning can be used to determine the mean and standard deviation corresponding to the degrees of freedom based on the multiple sample images. Since the random fluctuations of multiple positioning are considered in this process, it is beneficial to ensure that the adjustment value of PTV is determined based on the mean in the subsequent process. This allows for reasonable adjustment of PTV so that the adjusted target area can cover all tumor cells without causing excessive damage to organs at risk.

[0019] Furthermore, in determining the adjustment value of PTV, the embodiments of this disclosure consider not only translational degrees of freedom but also rotational degrees of freedom, and convert the mean and standard deviation corresponding to the rotational degrees of freedom into angular equivalent displacements. This enables the determination of the adjustment value of PTV based on the mean corresponding to the translational degrees of freedom and the angular equivalent displacements. This helps to ensure a more appropriate determination of the adjustment value of PTV, so that when the treatment target rotates during the positioning process, the adjusted target area can still cover all tumor cells without causing excessive damage to organs at risk.

[0020] It should be understood that the above general description and the following detailed description are exemplary and explanatory only, and are not intended to limit this disclosure. Attached Figure Description

[0021] To more clearly illustrate the technical solutions in the embodiments of this disclosure, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of this disclosure. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0022] Figure 1 This is a schematic flowchart illustrating a method for determining the adjustment value of a planned target area according to an embodiment of the present disclosure.

[0023] Figure 2 This is a schematic diagram illustrating the degrees of freedom according to embodiments of the present disclosure.

[0024] Figure 3A This is a schematic diagram illustrating the relationship between quantity and half-width of a confidence interval according to an embodiment of the present disclosure.

[0025] Figure 3B This is a schematic diagram illustrating a confidence interval according to an embodiment of the present disclosure.

[0026] Figure 4 This is an example of the relationship between an adjustment value and risk as illustrated by embodiments of this disclosure.

[0027] Figure 5 This is a schematic block diagram of a device for determining the adjustment value of a planned target area according to an embodiment of the present disclosure. Detailed Implementation

[0028] The technical solutions of the embodiments of this disclosure will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this disclosure, and not all embodiments. Based on the embodiments of this disclosure, all other embodiments obtained by those of ordinary skill in the art without creative effort are within the scope of protection of this disclosure.

[0029] The terminology used in this disclosure is for the purpose of describing particular embodiments only and is not intended to be limiting of the present disclosure. The singular forms “a” and “the” as used in this disclosure and the appended claims are also intended to include the plural forms unless the context clearly indicates otherwise. It should also be understood that the term “and / or” as used herein refers to and includes any and all possible combinations of one or more of the associated listed items.

[0030] It should be understood that although the terms first, second, third, etc., may be used to describe various information in embodiments of this disclosure, such information should not be limited to these terms. These terms are only used to distinguish information of the same type from one another. For example, first information may also be referred to as second information without departing from the scope of embodiments of this disclosure, and similarly, second information may also be referred to as first information. Depending on the context, the word "if" as used herein may be interpreted as "when," "when," or "in response to a determination."

[0031] For the sake of brevity and ease of understanding, this document uses the terms "greater than" or "less than", "higher than" or "lower than" to describe size relationships. However, it will be understood by those skilled in the art that the term "greater than" also includes the meaning of "greater than or equal to", and "less than" also includes the meaning of "less than or equal to"; the term "higher than" also includes the meaning of "higher than or equal to", and "lower than" also includes the meaning of "lower than or equal to".

[0032] In some embodiments, radiotherapy can be based on a treatment plan (e.g., a planned treatment area determined by clinical target volume in combination with positioning, imaging, registration and equipment errors, etc., the specific determination method of which is not limited in this disclosure) to determine the planning target volume (PTV), which can define the three-dimensional range of radiation dose delivery.

[0033] Because the position of the treatment target on the treatment device changes each time, there will be a problem that the actual target area in the image corresponding to the treatment target is inconsistent with the planned target area each time the treatment target is placed on the treatment device (i.e., each time it is positioned). This is precisely because the positioning of the treatment target is changed.

[0034] In other words, due to considerations such as time and economic costs, the actual target area is not redefined before each treatment according to the method of determining the planned target area. However, if the actual target area is indeed inconsistent with the planned target area, then it is necessary to consider adjusting the planned target area to ensure that the adjusted target area can include the actual target area, thereby achieving accurate killing of tumor cells.

[0035] To address the aforementioned issues, one possible implementation is to expand the boundaries of the PTV (Plan-Do-Tube) based on fixed values ​​to ensure that the expanded target area covers all tumor cells. However, this approach does not reflect the specificity of different treatment targets, making it difficult to guarantee that the expanded target area covers all tumor cells.

[0036] Another alternative approach is to perform correction based on a single image. For example, the PTV can be expanded outward based on the difference between the image corresponding to a particular positioning and the reference image (where the target area is the PTV). However, single-image correction can only provide the positional deviation of the current positioning and cannot characterize random fluctuations, systematic deviations, and rotational errors from multiple positioning sessions. Therefore, it is difficult to guarantee that the expanded target area covers all tumor cells.

[0037] Figure 1 This is a schematic flowchart illustrating a target volume adjustment method according to an embodiment of the present disclosure. The target volume adjustment method shown in this embodiment can be executed by a treatment device (e.g., by a processor in the treatment device), which can be used for radiotherapy, such as for BNCT treatment. Subsequent embodiments mainly use the BNCT scenario as an example to exemplify the technical solutions of this disclosure.

[0038] For example, embodiments of this disclosure can be applied to the treatment of tumor cells at any location within the treatment target.

[0039] Because the head and neck target area is close to the organs at risk, positioning errors can directly affect dosage safety. Therefore, the embodiments disclosed herein are particularly suitable for patients with nasopharyngeal carcinoma, oropharyngeal carcinoma, oral cancer, hypopharyngeal cancer, external auditory canal tumors or cervical lymph node metastases as treatment targets, and can record the location of organs at risk such as the brainstem, spinal cord, cochlea, glands, skin and blood vessels in the images.

[0040] like Figure 1 As shown, the planned target area adjustment method may include the following steps: In step S101, a reference image of the placement of the treatment target on the treatment device is determined based on the treatment plan.

[0041] In step S102, sample images of the treatment target being positioned multiple times on the treatment device are acquired.

[0042] In some embodiments, the type of image (e.g., quasi-image, sample image) may include at least one of the following: CT (Computed Tomography) images; MRI (Magnetic Resonance Imaging) images; Fusion images (e.g., obtained by fusing CT and MRI images).

[0043] In some embodiments, baseline images include the planning target area (PTV) and organs at risk (OARs, such as the brainstem, spinal cord, cochlea, glands, skin, nerves, and blood vessels in head and neck cancer BNCT).

[0044] In some embodiments, the image (e.g., a quasi-image, a sample image) can be a three-dimensional image containing multiple voxels, and the planned target area, organs at risk, etc., contained in the baseline image can be based on voxel composition.

[0045] In some embodiments, a coordinate system for the treatment device can be constructed, including mutually perpendicular x-axis, y-axis, and z-axis.

[0046] For example, the image (e.g., quasi-image, sample image) is located in the above coordinate system, which can be used to define a common spatial reference for the treatment bed, the head (particle flow end component), the input card (used to receive external control signals from the operating interface, and can also collect data fed back from various sensors, such as particle flow intensity, device voltage, etc.) and the dose calculation program in the treatment device.

[0047] In some embodiments, the treatment target can be fixed using a head, neck, and shoulder thermoplastic film, a headrest, shoulder traction, or a personalized pillow. In this case, the model of the fixation device, the position of the treatment target, the reference position of the treatment bed, and the head, neck, and shoulder support method can be recorded. The recorded information can be used to determine systematic errors and facilitate tracing the causes of systematic errors.

[0048] In some embodiments, the operation of arranging the treatment target to obtain sample images can be performed in treatment simulation, pre-treatment verification, or fractionated treatment verification.

[0049] In some embodiments, the number of times sample images are obtained by positioning the treatment target can be 3 to 15, or can be extended to 30 or more as needed.

[0050] For example, when the number of sample images n is greater than or equal to 3 and less than or equal to 15, a small sample mode can be used. Parameters such as the mean, standard deviation, covariance, and confidence interval (CI) can then be determined based on a t-distribution. Alternatively, a small sample mode can be avoided, in which case the mean, standard deviation, covariance, and confidence interval can be determined based on a normal distribution.

[0051] For example, when the number of sample images, n, is greater than or equal to 30, the determined parameters are relatively accurate (compared to the case of 3≤n≤15). These parameters, determined for the treatment goal, can be used as historical prior data (e.g., for adjusting PTV later for other treatment goals). Furthermore, distribution information related to the treatment goal (e.g., the patient) can be established for subsequent application and analysis. Subsequent parameters such as mean, standard deviation, covariance, and confidence intervals can be determined based on a normal distribution, or alternatively, a t-distribution.

[0052] It should be noted that when the number of sample images is greater than 15 and less than 30, subsequent parameters such as mean, standard deviation, covariance, and confidence interval can be determined based on either a normal distribution or a t-distribution, and this disclosure does not limit this.

[0053] In step S103, the transformation matrix of the sample image relative to the reference image is determined, wherein the transformation matrix corresponds to multiple degrees of freedom, including translational degrees of freedom and rotational degrees of freedom.

[0054] For example, a transformation matrix relative to a reference image can be determined for the sample image corresponding to each positioning. Specifically, the sample influence can be registered with the reference influence (e.g., rigid body registration), the purpose of which is to output the aforementioned transformation matrix; or, as needed, a region of interest (ROI) can be determined near a specified area (e.g., PTV and / or organs at risk) (e.g., within a range where the distance from the specified area is less than or equal to a distance threshold), and the sample influence can be registered with the reference influence based on the ROI (e.g., called auxiliary registration).

[0055] For example, the transformation matrix corresponds to multiple degrees of freedom, including translational and rotational degrees of freedom.

[0056] In some embodiments, the translational degrees of freedom include a first translational direction x with a degree of freedom Δx, a second translational direction y with a degree of freedom Δy, and a third translational direction z with a degree of freedom Δz, wherein the first translational direction, the second translational direction, and the third translational direction are perpendicular to each other.

[0057] In some embodiments, rotational degrees of freedom include a first rotational direction. degrees of freedom Second rotation direction degrees of freedom Third rotation direction degrees of freedom The rotation axis of the first rotation direction is the first translation direction (e.g., the x-axis), the rotation axis of the second rotation direction is the second translation direction (e.g., the y-axis), and the rotation axis of the third rotation direction is the third translation direction (e.g., the z-axis).

[0058] Figure 2 This is a schematic diagram illustrating the degrees of freedom according to embodiments of the present disclosure.

[0059] like Figure 2 As shown, the first translation direction x can correspond to the direction of the x-axis in the coordinate system, the second translation direction y can correspond to the direction of the y-axis in the coordinate system, and the third translation direction z can correspond to the direction of the z-axis in the coordinate system.

[0060] First rotation direction The axis of rotation is the x-axis, and the second direction of rotation is... The axis of rotation is the y-axis, and the third direction of rotation is... The axis of rotation is the z-axis.

[0061] For example, the first translation direction x, the second translation direction y, the third translation direction z, and the first rotation direction. Second rotation direction and the third rotation direction The meanings can be shown in Table 1 below: Table 1 For example, the degrees of freedom determined based on the i-th placement in an n-fold arrangement can be represented by a vector. Indicate, for example The expression is as follows: ; in, For the i-th placement , For the i-th placement , For the i-th placement , For the i-th placement , For the i-th placement , For the i-th placement .

[0062] In step S104, the mean and standard deviation corresponding to the degrees of freedom are calculated.

[0063] For example, mean It can be calculated based on the following formula: ; For example, the covariance can be calculated based on the following formula: ; because and They are all represented by vectors, so It is also represented by vectors, and can be obtained by... The square root of the variance of the diagonal elements is obtained corresponding standard deviation (It can also be written as) ).

[0064] In step S105, the angle transformation value corresponding to the rotational degree of freedom is calculated based on the mean and standard deviation of the rotational degree of freedom, and the angular equivalent displacement is calculated based on the angle transformation value.

[0065] In step S106, the adjustment value of the planned target area (PTV) in each translation direction is determined based on the mean value corresponding to the translational degree of freedom and the equivalent displacement of the angle.

[0066] For example, the mean can be determined for each translational degree of freedom. For instance, the mean for Δx can be denoted as... For example, the mean value corresponding to Δy is denoted as For example, the mean value corresponding to Δz is denoted as Therefore, based on Determine the adjustment value of PTV in the x-direction, based on Determine the adjustment value of PTV in the y-direction, based on Determine the adjustment value of PTV in the z-direction.

[0067] According to embodiments of this disclosure, multiple sample images obtained through multiple positioning can be used to determine the mean and standard deviation corresponding to the degrees of freedom based on the multiple sample images. Since the random fluctuations of multiple positioning are considered in this process, it is beneficial to ensure that the adjustment value of PTV is determined based on the mean in the subsequent process. This allows for reasonable adjustment of PTV so that the adjusted target area can cover all tumor cells without causing excessive damage to organs at risk.

[0068] Furthermore, in determining the adjustment value of PTV, the embodiments of this disclosure consider not only translational degrees of freedom but also rotational degrees of freedom, and convert the mean and standard deviation corresponding to the rotational degrees of freedom into angular equivalent displacements. This enables the determination of the adjustment value of PTV based on the mean corresponding to the translational degrees of freedom and the angular equivalent displacements. This helps to ensure a more appropriate determination of the adjustment value of PTV, so that when the treatment target rotates during the positioning process, the adjusted target area can still cover all tumor cells without causing excessive damage to organs at risk.

[0069] It should be noted that in the above embodiments... This refers to the mean value corresponding to all degrees of freedom. Each degree of freedom can also have its own mean value; for example, the mean value corresponding to degree j. It can be calculated based on the following formula: ; Where j can take any one of the above 6 degrees of freedom, that is, it can be any of the following 6 degrees of freedom. , , , , , Any value in the range.

[0070] It should be noted that in the above embodiments... It refers to the covariance corresponding to all degrees of freedom. This refers to the standard deviation corresponding to all degrees of freedom. Each degree of freedom can also correspond to a covariance; for example, the covariance corresponding to degree j. It can be calculated based on the following formula: ; Where j can take any one of the above 6 degrees of freedom, that is, it can be any of the following 6 degrees of freedom. , , , , , Any value in. It can be obtained by... The standard deviation of j is obtained by taking the square root of the variance of the diagonal elements. (It can also be written as) ).

[0071] In some embodiments, considering that the number of placements n is relatively small, such as 3 to 30, the number of sample images n obtained is also small. The degrees of freedom determined based on a small number of sample images are generally difficult to satisfy a normal distribution, and the standard deviation itself is unstable (fluctuates greatly). Therefore, this embodiment can determine the confidence interval (also called confidence interval) corresponding to the degree of freedom j based on the t-distribution in order to obtain a relatively accurate confidence interval.

[0072] In some embodiments, the mean value corresponding to the degree of freedom j can be used. and standard deviation Calculate the confidence intervals of the degrees of freedom based on the t-distribution. , wherein Calculated based on the following formula: ; Where n is the number of sample images. It is the quantile of the t-distribution with n-1 degrees of freedom and the cumulative probability (CP).

[0073] For example, k can be 95% or other values; for example, CP can be 0.975 or other values.

[0074] Calculated It can be displayed to users (e.g., therapists) so that they can confirm whether the confidence interval for degree of freedom j meets the requirements, and so that they can adjust the relevant parameters corresponding to degree of freedom j as needed, such as manually setting the standard deviation corresponding to degree of freedom j.

[0075] It should be noted that, in this embodiment, the sampling methods used in determining statistical data such as the mean, standard deviation, and confidence interval include, but are not limited to, Bootstrap. For example, when n is less than a threshold (e.g., 5 or other values), statistical data such as the mean, standard deviation, and confidence interval boundaries can be determined based on the historical prior lower limit (or the historical error of the treatment device); when n is greater than or equal to the threshold (e.g., 5 or other values), statistical data such as the mean, standard deviation, and confidence interval boundaries can be determined based on Bootstrap sampling.

[0076] Figure 3A This is a schematic diagram illustrating the relationship between quantity and half-width of a confidence interval according to an embodiment of the present disclosure. Figure 3B This is a schematic diagram illustrating a confidence interval according to an embodiment of the present disclosure.

[0077] like Figure 3A When n increases from 3 to 10, that is, when the number of placements (corresponding to the number of sample images) increases from 3 to 10, the half-width of the confidence interval (e.g., the gray part) decreases significantly; for example... Figure 3B As shown, the position of the vertical axis on the horizontal axis can be determined based on the mean of 10 sampling points. When n=10, the half-width of the confidence interval is already small enough.

[0078] like Figure 3A When n is greater than 15, the marginal returns gradually decrease, that is, as n increases, the half-width of the confidence interval changes very little.

[0079] That is, although the distribution of the samples approaches a normal distribution as n increases, when n is greater than 15, the degree to which the distribution of the samples approaches a normal distribution is limited. Considering the high cost of further large-scale sampling (e.g., each sampling requires the treatment target to lie on the treatment device and obtain sample images for the treatment target), it is not advisable to set n too large. For example, n can be set between 3 and 15, or between 5 and 15. Then, the t-distribution, Bootstrap, or historical prior lower bound can be introduced for estimation (e.g., it can be referred to as conservative estimation).

[0080] In some embodiments, the statistical data involved in the foregoing embodiments may be as shown in Table 2 below: Table 2 The values ​​shown in Table 2 are just examples, and the parameter values ​​in actual applications are not limited to those shown in Table 2.

[0081] For example, the mean can represent systematic error, the standard deviation can represent random error, the minimum and maximum values ​​can be used to observe the error range, and the Shapiro-Wilk p value is used to determine the degree to which a simulated sample deviates from a normal distribution.

[0082] In some embodiments, calculating the angle transformation value corresponding to the rotational degree of freedom based on the mean and standard deviation of the rotational degree of freedom includes: The angle conversion value is calculated based on the following formula. : ; in, for The corresponding mean, for The corresponding standard deviation for The corresponding mean, for The corresponding standard deviation for The corresponding mean, for The corresponding standard deviation The confidence coefficient is related to the number of sample images, for example, it may be positively or negatively correlated with the number n, and this disclosure does not limit it.

[0083] In some embodiments, calculating the angular equivalent displacement based on the angular conversion value includes: The angular equivalent displacement is calculated based on the following formula. : ; in, express The corresponding tangent value, r, is the distance from the edge of the planned target area to the... The distance corresponding to the axis of rotation.

[0084] Calculated based on the above method The rotational degrees of freedom can be converted to have the same dimensions as the translational degrees of freedom, thus working together with the translational degrees of freedom to determine the adjustment value of the PTV. Therefore, in determining the PTV adjustment value, not only the translational degrees of freedom but also the rotational degrees of freedom are considered, and the mean and standard deviation corresponding to the rotational degrees of freedom are converted into equivalent angular displacements. This allows for the determination of the PTV adjustment value based on the mean corresponding to the translational degrees of freedom and the equivalent angular displacements. This helps ensure a more appropriate determination of the PTV adjustment value, so that even when the treatment target rotates during positioning, the adjusted target area can still cover all tumor cells without causing excessive damage to organs at risk.

[0085] In some embodiments, for translational degree of freedom j, the adjustment value in the translational direction corresponding to j can be denoted as... For example, the mean value corresponding to the translational degrees of freedom is denoted as The angular equivalent displacement is , It can be calculated based on the following formula: ; Therefore, for PTV, the adjustment value can be used in the x-axis direction. Expand outwards, and the adjustment value can be used in the y-axis direction. Expand outwards, and in the z-axis direction, it can be adjusted according to the value. To expand outwards.

[0086] It should be noted that since PTV is generally an irregular three-dimensional area, it is based on the outward direction Extending this further, we can consider all aspects. , , For example, based on and The weighted summation is expanded outwards, among which, , and The corresponding weights can be determined based on the ratios of the values ​​on the x, y, and z axes of the corresponding voxels at the region boundary.

[0087] Additionally, in some embodiments, for The calculation is not limited to considering and Other parameters can also be considered, such as conservative standard deviation, systematic error, etc. The following examples illustrate this.

[0088] In some embodiments, determining the adjustment value of the planned target area in each translation direction based on the mean value corresponding to the translational degree of freedom and the equivalent angular displacement includes: determining the adjustment value of the planned target area in the translational direction based on the mean value corresponding to the translational direction in the translational degree of freedom, the equivalent angular displacement, and the conservative standard deviation corresponding to the translational direction; Wherein, the conservative standard deviation corresponds to the degree of freedom j. Calculated based on the following formula: ; in, Let j be the standard deviation corresponding to the degree of freedom j. This is the historical prior lower bound of the standard deviation corresponding to the stated degree of freedom j.

[0089] As can be seen, in this embodiment, the standard deviation was not directly used. , but in and Take the maximum value from the middle Therefore, this helps to avoid the problem of accidental clustering when the sample size is too small. Too small, thus underestimating the true uncertainty.

[0090] in this case, It can be calculated based on the following formula: ; in, The confidence coefficient is related to the number of sample images, for example, it can be positively or negatively correlated with the number n, and this disclosure does not limit it.

[0091] In this embodiment, and Based on this, further consideration can be given. The uncertainty of the sample is taken into account, which helps to ensure that the determined adjustment value of PTV is more reasonable, so that the PTV can be reasonably adjusted so that the adjusted target area can cover all tumor cells and not cause too much damage to organs at risk.

[0092] In some embodiments, determining the adjustment value of the planned target area in each translation direction based on the mean value corresponding to the translational degree of freedom and the equivalent angular displacement includes: determining the adjustment value of the planned target area in the translational direction based on the mean value corresponding to the translational direction in the translational degree of freedom, the equivalent angular displacement, and the system error.

[0093] For example, systematic error can be denoted as , It can be calculated based on the following formula: ; In this embodiment, and Based on this, further consideration can be given. The system error is taken into account (e.g., the safety margin corresponding to the inherent errors of image acquisition, registration and system), which helps to ensure that the determined adjustment value of PTV is more reasonable, so that the PTV can be reasonably adjusted so that the adjusted target area can cover all tumor cells and will not cause too much damage to organs at risk.

[0094] In some embodiments, comprehensive consideration may also be taken into account and ,So It can be calculated based on the following formula: .

[0095] For example, 0.40 mm is the systematic error in the Δz direction, 1.80 mm is the standard deviation in the Δz direction, 2.262 is the 95% confidence coefficient of the t-distribution when n=10, 5.0 mm is the fixed safety margin (i.e., the systematic error), and 0.65 mm is the equivalent linear displacement obtained by converting the rotational error. Then we can obtain: .

[0096] It should be noted that the data in this example is used to illustrate that the formula can be directly calculated and does not restrict clinical values.

[0097] In some embodiments, the transformation matrix corresponding to the i-th sample image among the n sample images is determined. , where n is an integer greater than 1; Determine the voxel v in the reference image in the transformation matrix The corresponding irradiation dose under the condition ; The irradiation dose corresponding to voxel v is determined based on the following formula. Expected value : .

[0098] In this embodiment, the transformation matrix corresponding to the i-th sample image can be denoted as... Under the perturbation geometry of this transformation matrix, the irradiation dose at voxel v can be recalculated or read. Therefore, the average radiation dose corresponding to the n sample images can be calculated, thus obtaining... .

[0099] in, Instead of an isolated value, for each voxel v, a set of irradiation doses corresponding to n sample images is first obtained, and then the expected dose value is determined based on the mean of these n irradiation doses. The result is... It is used to form a probabilistic dose distribution that takes into account placement uncertainty, and can be further used to derive robustness evaluation indicators for treatment planning such as D95, D99, Dmean, and Dmax.

[0100] In some embodiments, the probability of exceeding the radiation dose limit corresponding to voxel v is calculated based on the following formula. : ; in, The threshold is predefined, and I[x] is an indicator function that takes the value 1 when the condition in the parentheses is true and takes the value 0 when the condition in the parentheses is false.

[0101] Based on this formula, dose risk can be transformed from a single deterministic judgment into a probabilistic risk judgment, which can be used to evaluate the robustness of treatment plans (focusing on tail risk or constraint overrun risk).

[0102] Figure 4 This is an example of the relationship between an adjustment value and risk as illustrated by embodiments of this disclosure.

[0103] like Figure 4 As shown, as the PTV expansion value increases, the probability of target area coverage also increases. However, the expanded PTV is generally larger than the target area, thus covering part of the area of ​​the organ at risk, and therefore the risk of organ at risk exceeding the limit also increases.

[0104] Based on this, the probability of target area coverage and the risk of exceeding organ limits can be comprehensively considered as needed, and an appropriate adjustment value can be selected to expand the PTV.

[0105] Corresponding to the aforementioned embodiments of the method for determining the adjustment value of the planned target area, this disclosure also provides embodiments of an apparatus for determining the adjustment value of the planned target area.

[0106] Figure 5 This is a schematic block diagram illustrating a device for determining the adjustment value of a planned target area according to an embodiment of the present disclosure. The device for determining the adjustment value of a planned target area shown in this embodiment can be a treatment device, or it can be composed of modules within a treatment device.

[0107] like Figure 5 As shown, the device for determining the adjustment value of the planned target area includes: an acquisition module 501 and a processing module 502.

[0108] In some embodiments, the acquisition module is configured to determine a reference image of the positioning of the treatment target on a treatment device based on a treatment plan, wherein the reference image includes a planned target area and organs at risk; acquire sample images of the treatment target positioned multiple times on the treatment device; and the processing module is configured to determine a transformation matrix of the sample images relative to the reference image, wherein the transformation matrix corresponds to multiple degrees of freedom, including translational and rotational degrees of freedom; calculate the mean and standard deviation corresponding to the degrees of freedom; calculate the angle transformation value corresponding to the rotational degrees of freedom based on the mean and standard deviation, calculate the angular equivalent displacement based on the angle transformation value; and determine the adjustment value of the planned target area in each translational direction based on the mean and the angular equivalent displacement corresponding to the translational degrees of freedom.

[0109] In some embodiments, the translational degrees of freedom include a first translational direction x (Δx), a second translational direction y (Δy), and a third translational direction z (Δz), wherein the first translational direction, the second translational direction, and the third translational direction are perpendicular to each other; and / or, the rotational degrees of freedom include a first rotational direction. degrees of freedom Second rotation direction degrees of freedom Third rotation direction degrees of freedom Wherein, the rotation axis of the first rotation direction is the first translation direction, the rotation axis of the second rotation direction is the second translation direction, and the rotation axis of the third rotation direction is the third translation direction.

[0110] In some embodiments, the processing module is configured to calculate the angle conversion value based on the following formula. : ; in, for The corresponding mean, for The corresponding standard deviation for The corresponding mean, for The corresponding standard deviation for The corresponding mean, for The corresponding standard deviation is the confidence coefficient, which is related to the number of sample images.

[0111] In some embodiments, the processing module is configured to calculate the angular equivalent displacement based on the following formula. : ; in, express The corresponding tangent value, r, is the distance from the edge of the planned target area to the... The distance corresponding to the axis of rotation.

[0112] In some embodiments, the processing module is configured to determine the adjustment value of the planned target area in the translation direction based on the mean value of the translation direction in the translation degree of freedom, the equivalent displacement of the angle, and the conservative standard deviation of the translation direction. Wherein, the conservative standard deviation corresponds to the degree of freedom j. Calculated based on the following formula: ; in, Let j be the standard deviation corresponding to the degree of freedom j. This is the historical prior lower bound of the standard deviation corresponding to the stated degree of freedom j.

[0113] In some embodiments, the processing module is configured to determine the adjustment value of the planned target area in the translation direction based on the mean value corresponding to the translation direction in the translation degree of freedom, the equivalent displacement of the angle, and the system error.

[0114] In some embodiments, the processing module is further configured to calculate based on the mean value corresponding to the degree of freedom j. and standard deviation Calculate the confidence intervals of the degrees of freedom based on the t-distribution. , wherein Calculated based on the following formula: ; Where k is the confidence level and n is the number of sample images. It is the quantile of the t-distribution with n-1 degrees of freedom and the cumulative probability value CP.

[0115] In some embodiments, the processing module is further configured to determine the transformation matrix corresponding to the i-th sample image among the n sample images. Where n is an integer greater than 1; determine the voxel v in the reference image in the transformation matrix. The corresponding irradiation dose under the condition The irradiation dose corresponding to voxel v is determined based on the following formula. Expected value : .

[0116] In some embodiments, the processing module is further configured to calculate the probability of exceeding the radiation dose limit corresponding to voxel v based on the following formula. : ; in, The threshold is predefined, and I[x] is an indicator function that takes the value 1 when the condition in the parentheses is true and takes the value 0 when the condition in the parentheses is false.

[0117] Regarding the apparatus in the above embodiments, the specific manner in which each module performs its operation has been described in detail in the embodiments of the relevant methods, and will not be elaborated upon here.

[0118] For the device embodiments, since they basically correspond to the method embodiments, the relevant parts can be referred to in the description of the method embodiments. The device embodiments described above are merely illustrative. The modules described as separate components may or may not be physically separate, and the components shown as modules may or may not be physical modules, that is, they may be located in one place or distributed across multiple network modules. Some or all of the modules can be selected to achieve the purpose of this disclosure according to actual needs. Those skilled in the art can understand and implement this without creative effort.

[0119] Embodiments of this disclosure also provide an electronic device, comprising: a processor; and a memory for storing processor-executable instructions; wherein the processor is configured to implement the method described in any of the above embodiments.

[0120] Embodiments of this disclosure also provide a computer-readable storage medium having a computer program stored thereon that, when executed by a processor, implements the steps of the method described in any of the above embodiments.

[0121] Other embodiments of this disclosure will readily occur to those skilled in the art upon consideration of the specification and practice of the disclosure herein. This application is intended to cover any variations, uses, or adaptations of this disclosure that follow the general principles of this disclosure and include common knowledge or customary techniques in the art not disclosed herein. The specification and examples are to be considered exemplary only.

[0122] It should be understood that this disclosure is not limited to the precise structures described above and shown in the accompanying drawings, and various modifications and changes can be made without departing from its scope. The scope of this disclosure is limited only by the appended claims.

Claims

1. A method for determining the adjustment value of a planned target area, characterized in that, include: The reference image for positioning the treatment target on the treatment device is determined based on the treatment plan, wherein the reference image includes the planned target area and the organ at risk; Acquire sample images of the treatment target positioned multiple times on the treatment device; Determine the transformation matrix of the sample image relative to the reference image, wherein the transformation matrix corresponds to multiple degrees of freedom, including translational degrees of freedom and rotational degrees of freedom; the rotational degree of freedom includes a first rotation direction. degrees of freedom Second rotation direction degrees of freedom Third rotation direction degrees of freedom ; Calculate the mean and standard deviation corresponding to the degrees of freedom; Calculate the angle transformation value corresponding to the rotational degree of freedom based on the mean and standard deviation, and calculate the angular equivalent displacement based on the angle transformation value; Based on the mean value corresponding to the translational degrees of freedom and the equivalent displacement of the angle, determine the adjustment value of the planned target area in each translational direction; The step of calculating the angle transformation value corresponding to the rotational degree of freedom based on the mean and standard deviation of the rotational degree of freedom includes: calculating the angle transformation value based on the following formula. : ； in, for The corresponding mean, for The corresponding standard deviation for The corresponding mean, for The corresponding standard deviation for The corresponding mean, for The corresponding standard deviation The confidence coefficient is related to the number of sample images. The step of calculating the equivalent angular displacement based on the angle conversion value includes: calculating the equivalent angular displacement based on the following formula. : ； in, express The corresponding tangent value, r, is the distance from the edge of the planned target area to the... The distance corresponding to the axis of rotation.

2. The method according to claim 1, characterized in that, The translational degrees of freedom include a first translation direction x (Δx), a second translation direction y (Δy), and a third translation direction z (Δz), wherein the first translation direction, the second translation direction, and the third translation direction are perpendicular to each other; and / or, The rotation axis of the first rotation direction is the first translation direction, the rotation axis of the second rotation direction is the second translation direction, and the rotation axis of the third rotation direction is the third translation direction.

3. The method according to claim 1 or 2, characterized in that, The step of determining the adjustment value of the planned target area in each translation direction based on the mean value corresponding to the translational degrees of freedom and the equivalent angular displacement includes: Based on the mean value of the translation direction in the translational degree of freedom, the equivalent displacement of the angle, and the conservative standard deviation of the translation direction, the adjustment value of the planned target area in the translation direction is determined. Wherein, the conservative standard deviation corresponds to the degree of freedom j. Calculated based on the following formula: ； in, Let j be the standard deviation corresponding to the degree of freedom j. This is the historical prior lower bound of the standard deviation corresponding to the stated degree of freedom j.

4. The method according to claim 1 or 2, characterized in that, The step of determining the adjustment value of the planned target area in each translation direction based on the mean value corresponding to the translational degrees of freedom and the equivalent angular displacement includes: Based on the mean value corresponding to the translation direction in the translational degree of freedom, the equivalent displacement of the angle, and the systematic error, the adjustment value of the planned target area in the translational direction is determined.

5. The method according to claim 1 or 2, characterized in that, The method further includes: Based on the mean value corresponding to the degree of freedom j and standard deviation Calculate the confidence intervals of the degrees of freedom based on the t-distribution. , wherein Calculated based on the following formula: ； Where k is the confidence level and n is the number of sample images. It is the quantile of the t-distribution with n-1 degrees of freedom and a cumulative probability value of CP.

6. The method according to claim 1 or 2, characterized in that, The method further includes: Determine the transformation matrix corresponding to the i-th sample image among the n sample images. , where n is an integer greater than 1; Determine the voxel v in the reference image in the transformation matrix The corresponding irradiation dose under the condition ; The irradiation dose corresponding to voxel v is determined based on the following formula. Expected value : 。 7. The method according to claim 6, characterized in that, The method further includes: The probability of exceeding the radiation dose limit for voxel v is calculated based on the following formula. : ； in, The threshold is predefined, and I[x] is an indicator function that takes the value 1 when the condition in the parentheses is true and takes the value 0 when the condition in the parentheses is false.

8. A computer-readable storage medium having a computer program stored thereon, characterized in that, When executed by a processor, the program implements the steps of the method described in any one of claims 1 to 7.

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