A full central dose verification method based on EBT3 film without washing

Abstract

The application discloses a kind of based on wash-free film EBT3 whole central dose verification method, belong to radiation measurement technical field, specifically include: after irradiation, radiochromatogram film is continuously collected, and the driving voltage sequence of synchronous acquisition gray data and scanning device;According to the mean value of the driving voltage value and corresponding gray data of each collection time, the response function model between driving voltage and gray response is established;Predetermine target voltage, and determine the correction coefficient corresponding to each driving voltage value based on target voltage and the response function model, according to the correction coefficient, the preset dose-gray curve is corrected, the current film gray data and corresponding driving voltage are acquired, the gray value is corrected point by point using correction coefficient, and is converted into dose value based on corrected dose-gray curve, finally generates dose distribution chart.The application significantly improves the accuracy of dose measurement by real-time monitoring and dynamic correction of scanning voltage fluctuation.

Description

Technical Field

[0001] This invention relates to the field of radiation measurement technology, and specifically to a method for verifying central nervous system dose based on EBT3 non-washable film. Background Technology

[0002] A Chinese patent with publication number CN118131294A discloses a method for measuring gamma radiation dose based on machine vision. In this method, a regression analysis is performed on the relationship between the radiation intensity received by the camera and the radiation noise caused by gamma rays in the camera image through numerical statistics to obtain the radiation intensity and thus infer the radiation dose. This reflects the technical idea of ​​using image features to infer the dose.

[0003] Meanwhile, washable radiochromatographic films (such as EBT3) are gradually becoming an important tool for dose verification due to their high spatial resolution, direct digitization, and rapid analysis advantages. They acquire two-dimensional dose distribution through direct scanning after irradiation, accurately reflecting the effects of multi-leaf grating (MLC) dynamic intensity modulation, X-ray scattering, and tissue inhomogeneity. When using radiochromatographic films for dose measurement, net optical density (netOD) calibration is required to eliminate systematic biases introduced by scanner hardware characteristics and scanning environment factors. However, this method relies on the assumption that the light source intensity is completely consistent during scanning the background and exposing the film; therefore, it cannot effectively compensate for errors when the light source intensity changes dynamically.

[0004] Furthermore, methods such as reference film calibration and spatial non-uniformity interpolation correction also have their limitations. For example, reference film calibration requires the preparation of high-precision reference films, which is complex and costly; spatial non-uniformity interpolation correction has high requirements for the distribution and number of calibration points, limiting its application in complex scenarios. Therefore, there is an urgent need for a technical solution that can effectively compensate for dynamic changes in the brightness of scanning instruments and improve the accuracy of digital dosimetry verification of radiochromatographic films. Summary of the Invention

[0005] The purpose of this invention is to provide a method for verifying the entire central nervous system dose based on washable film EBT3, and to solve the following technical problems:

[0006] There is an urgent need for a technical solution that can effectively compensate for dynamic changes in the brightness of scanning instruments and improve the accuracy of digital dosimetry verification of radiochromatographic films.

[0007] The objective of this invention can be achieved through the following technical solutions:

[0008] A method for validating central nervous system dose based on washable film EBT3 includes the following steps:

[0009] S1, continuously acquire the grayscale data sequence and the corresponding scanning device drive voltage sequence of each acquisition of the same radiochromatographic film after irradiation;

[0010] S2, Based on the driving voltage value at each acquisition time and the mean value of the corresponding grayscale data, establish a response function model between the driving voltage and the grayscale response;

[0011] S3, Predetermine the target voltage, and determine the correction coefficients corresponding to each driving voltage value based on the target voltage and the response function model;

[0012] S4, The preset dose-grayscale curve is corrected according to the correction coefficient to obtain the corrected dose-grayscale curve;

[0013] S5, acquire the grayscale data of the current radiochromatographic film and the driving voltage at the time of acquisition, and determine the grayscale correction coefficient corresponding to the driving voltage. For any data point in the grayscale image, multiply the grayscale data of the data point by the grayscale correction coefficient to obtain the corrected grayscale data.

[0014] S6. Substitute the corrected grayscale data into the corrected dose-grayscale curve to obtain the dose value at the data point. Collect the dose values ​​at all data points to generate the final dose distribution map.

[0015] As a further aspect of the present invention: in step S4, the specific process for obtaining the preset dose-grayscale curve is as follows:

[0016] S11, add annotations and dosage information to multiple target radiochromatographic films;

[0017] S12, Irradiate multiple target radiochromatographic films based on the dose information of each target radiochromatographic film;

[0018] S13, scan the irradiated target radiochromatographic film and simultaneously acquire the driving voltage of the scanning device to obtain the grayscale data corresponding to the driving voltage;

[0019] S14, calculate the mean value of grayscale data, pair the corresponding dose information with the calculated mean value of grayscale data to generate a set of discrete data points, and establish a dose-grayscale curve based on the set of discrete data points.

[0020] As a further aspect of the present invention: in step S3, the specific process for determining the target voltage is as follows:

[0021] Multiple film sets with different predetermined dose levels are acquired. The film sets are scanned at several different voltages and the corresponding optical density values ​​of each film are measured. Based on each predetermined dose level and its corresponding optical density value, a curve of optical density value changing with voltage is generated. The rate of change of optical density value in different voltage ranges is calculated, the voltage range where the rate of change of optical density value tends to be the minimum is identified, and the mean value of this voltage range is selected as the target voltage.

[0022] As a further aspect of the present invention: in step S3, the process of obtaining the correction coefficient is as follows:

[0023] Based on the response function model, the theoretical value of the first gray-scale mean corresponding to the target voltage is determined. For each driving voltage value, the theoretical value of the second gray-scale mean is obtained through the response function model. The ratio of the first gray-scale mean theoretical value to the second gray-scale mean theoretical value is calculated to obtain the gray-scale correction coefficient corresponding to each voltage value.

[0024] As a further aspect of the present invention: the specific process of correcting the preset dose-grayscale curve in step S4 is as follows:

[0025] For each dose-grayscale data point in the preset dose-grayscale curve, its grayscale value is multiplied by the grayscale correction coefficient corresponding to the voltage value at the acquisition time of the data point to obtain the corrected grayscale data; the dose value is paired with its corrected grayscale data point to generate the corrected dose-grayscale curve.

[0026] As a further aspect of the present invention: if there are multiple voltage ranges with the same rate of change of optical density values ​​and all of them being the minimum, then the average voltage of each range is taken as the test voltage, and multiple radiochromatographic films after irradiation are scanned under each test voltage. The standard deviation of the optical density value corresponding to each test voltage is calculated, and the test voltage with the smallest standard deviation is selected as the target voltage.

[0027] As a further aspect of the present invention: S6 further includes obtaining a verification plan dose distribution map, and performing image registration based on the final dose map and the verification plan dose distribution map to obtain a dose pass value. If the dose pass value is greater than or equal to the preset pass value threshold, the dose is determined to be qualified.

[0028] As a further aspect of the present invention: the specific calculation process for the dose pass value is as follows:

[0029] Feature points are extracted from the dose map and the planned dose distribution map. The feature points include field boundary points, dose extreme points, and anatomical structure markers. Spatial transformation parameters are calculated based on the correspondence of the feature points. The spatial transformation parameters include translation, rotation angle, scaling ratio, and shearing factor. The dose map is then subjected to coordinate transformation based on the spatial transformation parameters so that the dose map and the planned dose distribution map are in the same coordinate system.

[0030] For all pixels in the dose map, the dose value corresponding to each pixel is identified. For pixel i, the planned dose value at the same position in the planned dose distribution map is obtained, and the difference between the planned dose value and the dose value of pixel i is calculated to obtain the dose difference value D. The spatial distance d from pixel i to the isodose line in the planned dose distribution map that is closest to its dose value is calculated. Based on the spatial distance d and the dose difference value D, the error value of pixel i is calculated, thereby obtaining the error value corresponding to all pixels. Pixels with error values ​​less than a preset error threshold are marked as qualified pixels. The ratio of qualified pixels to total pixels in the dose map is counted, and the ratio is used as the dose pass value.

[0031] The beneficial effects of this invention are:

[0032] 1) This invention obtains film sets with different predetermined dose levels, scans them under several different voltages and generates curves showing the change in optical density with voltage, calculates the rate of change of optical density values ​​within different voltage ranges, identifies the voltage range where the rate of change of optical density values ​​tends to be the smallest and selects its average value as the target voltage, thereby determining the voltage range where the light source intensity is relatively stable, and allowing scanning to be performed under the target voltage. This reduces the impact of light source intensity fluctuations on subsequent dose measurements from the source, breaks the dependence of traditional methods on the complete consistency of light source intensity during background scanning and film exposure, and improves the stability of dose measurement.

[0033] 2) Based on the determined target voltage and the generated grayscale mean response function model as a function of voltage, a grayscale correction coefficient corresponding to the voltage value at each point is determined, and the pixel grayscale values ​​of the current grayscale image are corrected. This operation can track the dynamic changes of the light source intensity in real time during the scanning process, and accurately compensate for the pixel grayscale value deviation caused by fluctuations in light source intensity through the correction coefficient. This allows the corrected grayscale values ​​to more realistically reflect the actual irradiation of the radiochromatographic film, solving the problem that the error cannot be effectively compensated when the light source intensity changes dynamically in traditional methods, and providing a guarantee for the accurate conversion of subsequent dose maps.

[0034] 3) This invention eliminates the influence of light source intensity fluctuations by determining the target voltage and correcting the actual acquired dose value. Unlike the reference film calibration method, it eliminates the need for preparing high-precision reference films, avoiding the problems of complex operation and high cost. It also overcomes the limitations of spatial non-uniformity interpolation correction, which requires a high distribution and number of calibration points. This method simplifies the whole-central dose verification process, improves the efficiency and reliability of dose verification, and makes it better suited to the stringent dose verification accuracy requirements of complex techniques such as intensity-modulated radiotherapy. Attached Figure Description

[0035] The invention will now be further described with reference to the accompanying drawings.

[0036] Figure 1 This is a schematic diagram of a whole-central dose verification method based on washable film EBT3 according to the present invention. Detailed Implementation

[0037] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0038] Please see Figure 1 As shown, this invention is a method for verifying the entire central nervous system dose based on washable film EBT3, comprising the following steps:

[0039] S1, continuously acquire the grayscale data sequence and the corresponding scanning device drive voltage sequence of each acquisition of the same radiochromatographic film after irradiation;

[0040] S2, Based on the driving voltage value at each acquisition time and the mean value of the corresponding grayscale data, establish a response function model between the driving voltage and the grayscale response;

[0041] S3, Predetermine the target voltage, and determine the correction coefficients corresponding to each driving voltage value based on the target voltage and the response function model;

[0042] S4, The preset dose-grayscale curve is corrected according to the correction coefficient to obtain the corrected dose-grayscale curve;

[0043] S5, acquire the grayscale data of the current radiochromatographic film and the driving voltage at the time of acquisition, and determine the grayscale correction coefficient corresponding to the driving voltage. For any data point in the grayscale image, multiply the grayscale data of the data point by the grayscale correction coefficient to obtain the corrected grayscale data.

[0044] S6. Substitute the corrected grayscale data into the corrected dose-grayscale curve to obtain the dose value at the data point. Collect the dose values ​​at all data points to generate the final dose distribution map.

[0045] 1) This invention obtains film sets with different predetermined dose levels, scans them under several different voltages and generates curves showing the change in optical density with voltage, calculates the rate of change of optical density values ​​within different voltage ranges, identifies the voltage range where the rate of change of optical density values ​​tends to be the smallest and selects its average value as the target voltage, thereby determining the voltage range where the light source intensity is relatively stable, and allowing scanning to be performed under the target voltage. This reduces the impact of light source intensity fluctuations on subsequent dose measurements from the source, breaks the dependence of traditional methods on the complete consistency of light source intensity during background scanning and film exposure, and improves the stability of dose measurement.

[0046] 2) Based on the determined target voltage and the generated grayscale mean response function model as a function of voltage, a grayscale correction coefficient corresponding to the voltage value at each point is determined, and the pixel grayscale values ​​of the current grayscale image are corrected. This operation can track the dynamic changes of the light source intensity in real time during the scanning process, and accurately compensate for the pixel grayscale value deviation caused by fluctuations in light source intensity through the correction coefficient. This allows the corrected grayscale values ​​to more realistically reflect the actual irradiation of the radiochromatographic film, solving the problem that the error cannot be effectively compensated when the light source intensity changes dynamically in traditional methods, and providing a guarantee for the accurate conversion of subsequent dose maps.

[0047] 3) This invention eliminates the influence of light source intensity fluctuations by determining the target voltage and correcting the actual acquired dose value. Unlike the reference film calibration method, it eliminates the need for preparing high-precision reference films, avoiding the problems of complex operation and high cost. It also overcomes the limitations of spatial non-uniformity interpolation correction, which requires a high distribution and number of calibration points. This method simplifies the whole-central dose verification process, improves the efficiency and reliability of dose verification, and makes it better suited to the stringent dose verification accuracy requirements of complex techniques such as intensity-modulated radiotherapy.

[0048] In a preferred embodiment, the specific process for obtaining the preset dose-grayscale curve in step S4 is as follows:

[0049] S11, add annotations and dosage information to multiple target radiochromatographic films;

[0050] S12, Irradiate multiple target radiochromatographic films based on the dose information of each target radiochromatographic film;

[0051] S13, scan the irradiated target radiochromatographic film and simultaneously acquire the driving voltage of the scanning device to obtain the grayscale data corresponding to the driving voltage;

[0052] S14, calculate the mean value of grayscale data, pair the corresponding dose information with the calculated mean value of grayscale data to generate a set of discrete data points, and establish a dose-grayscale curve based on the set of discrete data points.

[0053] First, multiple target radiochromatographic films are uniquely identified and labeled with dose information. For example, a number is clearly written on the edge of each film using a marker, and its preset absorbed dose value is recorded. This step ensures that each film has a distinguishable identity and a clear dose assignment, laying the foundation for establishing an accurate dose-grayscale correspondence. Next, based on the dose information labeled on each film, it is precisely irradiated using a radiation source (such as a medical linear accelerator). The radiation beam parameters are controlled so that the actual absorbed dose value of each film is consistent with the preset value, thereby ensuring that the film response truly reflects the expected dose level. After irradiation, under determined scanning conditions, each processed radiochromatographic film is scanned using a film digitizer, and the scan is monitored and recorded simultaneously. The device uses a light source to drive the voltage and acquires the overall grayscale response data of the film under that voltage. This step uses a scanning device to convert the physical response of the film into a quantifiable digital signal, while recording the working state during scanning to eliminate errors introduced by external factors. For the grayscale data obtained from scanning each film, invalid and edge areas are removed, and the overall grayscale average value is calculated. The calculated grayscale average value is paired with the preset dose value corresponding to the film to form raw data points. After collecting the paired data of all films, a fitting method is used to establish the correspondence curve between dose and grayscale value. Characterizing the overall response level through the grayscale average value can reduce the interference of local non-uniformity, while data fitting can reveal the inherent law between dose and grayscale, providing a conversion basis for subsequent actual measurements.

[0054] Unique identifiers and dose labeling effectively distinguish different films and clarify their target doses, avoiding confusion and misoperation, and providing a foundation for subsequent data correlation. Precise irradiation based on the labeled dose ensures that the dose received by each film is accurately known, establishing a reliable correspondence between film response and dose. Simultaneous recording of the driving voltage during scanning helps monitor and compensate for the instability of the scanning system itself, improving data consistency and repeatability. Calculating the overall grayscale mean and performing data fitting effectively reduces the impact of random errors and local variations on the results, thereby establishing a stable and accurate dose-grayscale conversion curve. This method ultimately provides a crucial quantitative conversion basis for the entire validation scheme, making it possible to infer the dose distribution from grayscale data, significantly improving the accuracy and reliability of dose validation, and providing a solid guarantee for comprehensively evaluating the execution quality of radiotherapy plans.

[0055] In another preferred embodiment, the specific process for determining the target voltage in step S3 is as follows:

[0056] Multiple film sets with different predetermined dose levels are acquired. The film sets are scanned at several different voltages and the corresponding optical density values ​​of each film are measured. Based on each predetermined dose level and its corresponding optical density value, a curve of optical density value changing with voltage is generated. By calculating the rate of change of optical density value in different voltage ranges, the voltage range in which the rate of change of optical density value tends to be the minimum is identified, and the mean value in this voltage range is selected as the target voltage.

[0057] In practice, five radiochromatographic films with different predetermined dose levels are first acquired to form a film group, for example, labeled A, B, C, D, and E, corresponding to predetermined dose levels of 5 Gy, 10 Gy, 15 Gy, 20 Gy, and 25 Gy, respectively. Next, the film group is scanned at several different voltages, such as 15 W, 20 W, 25 W, and 30 W. The film group is placed in the scanner for each scan to ensure a consistent scanning environment. Then, using professional optical density measurement software or equipment, the optical density value of each film at each voltage is measured. For example, the optical density of film A at 15 W is recorded as OD1, and at 20 W as OD2, etc. Afterwards, based on each predetermined dose level and its corresponding optical density value at different voltages, a curve of optical density value versus voltage is generated using plotting software. For example, voltage is plotted on the x-axis and optical density value on the y-axis, and curves are plotted for films A through E. Then, through mathematical calculation methods, the rate of change of optical density values ​​in different voltage ranges is calculated. For example, the voltage range is divided into ranges such as 15-20W, 20-25W, and 25-30W. The slope of the optical density value changing with voltage in each range is calculated as the rate of change. Then, the voltage range where the rate of change of optical density value tends to be the smallest is identified. Assuming that the calculation shows that the rate of change of optical density of each curve is the smallest in the 20-25W range, the mean value in this voltage range is finally selected as the target voltage.

[0058] Different voltages affect the stability of the scanner's light source, leading to fluctuations in the measurement of film optical density. By acquiring optical density values ​​of film at different dose levels under multiple voltages and plotting curves, the trend of optical density changes with voltage can be visually observed. Calculating the rate of change across different voltage ranges and finding the range with the smallest rate of change indicates that the light source intensity is relatively stable within that range, and the optical density value is less affected by voltage fluctuations. Selecting the average value of this range as the target voltage allows subsequent scanning operations to be performed under conditions of high light source stability, thereby reducing optical density measurement errors caused by light source intensity fluctuations. This lays a reliable foundation for subsequent dose-grayscale curve construction based on the target voltage and grayscale image correction, ensuring that the final radiochromatographic film dose map accurately reflects the actual irradiation dose, achieving precise verification of the entire central nervous system dose, and guaranteeing the accuracy and reliability of radiotherapy plan execution.

[0059] In another preferred embodiment, the process of obtaining the correction coefficient in step S3 is as follows:

[0060] Based on the response function model, the theoretical value of the first gray-scale mean corresponding to the target voltage is determined. For each measured voltage point, the theoretical value of the second gray-scale mean is obtained through the response function model. The ratio of the first gray-scale mean theoretical value to the second gray-scale mean theoretical value is calculated to obtain the gray-scale correction coefficient corresponding to each voltage value.

[0061] This is because the voltage of the light source may fluctuate during the scanning process, affecting the grayscale values ​​of the acquired grayscale image. By determining the correction coefficient based on a response function model, the average grayscale value under the actual acquisition voltage can be converted into the theoretical average grayscale value under the target voltage, thereby compensating for the impact of light source voltage fluctuations on the grayscale values. This eliminates the error caused by light source intensity fluctuations, allowing the corrected grayscale image to more accurately reflect the actual irradiation dose received by the radiochromatographic film. Consequently, the conversion of the grayscale image into a dose map is more precise, ensuring the reliability of dose verification results and providing strong support for the correct execution of radiotherapy plans.

[0062] In another preferred embodiment, the specific process of correcting the preset dose-grayscale curve in step S4 is as follows:

[0063] For each dose-grayscale data point in the preset dose-grayscale curve, its grayscale value is multiplied by the grayscale correction coefficient corresponding to the voltage value at the acquisition time of the data point to obtain the corrected grayscale data; the dose value is paired with its corrected grayscale data point to generate the corrected dose-grayscale curve.

[0064] First, the original dose-grayscale curve, pre-calibrated through experiments, is obtained. This curve consists of a series of discrete dose values ​​and their corresponding grayscale data points. For each data point in the curve, based on the scanning time corresponding to the acquisition of its grayscale value, the driving voltage value of the light source of the scanning device at that time is looked up. Then, according to the established voltage-grayscale response relationship model, the grayscale correction coefficient corresponding to that voltage value is obtained. For example, if the driving voltage at the acquisition time of a certain data point is 5.0V, the correction coefficient at that voltage is found to be 1.05. The original grayscale value is then multiplied by this coefficient to obtain the corrected grayscale value. The above operation is performed sequentially on all data points on the original curve, i.e., the grayscale values ​​are recalibrated one by one. Finally, each dose value is re-paired with the corrected new grayscale value to form a new set of data points, and a corrected dose-grayscale curve after system error compensation is generated accordingly.

[0065] The reason for performing point-by-point voltage-driven grayscale correction on the preset curve is that during the establishment of the original dose-grayscale relationship, the driving voltage of the scanner light source may fluctuate, causing the recorded grayscale values ​​to be interfered with by non-dose factors, and thus failing to fully and accurately reflect the physical correspondence between dose and film response. By tracing the acquisition voltage of each grayscale data point and correcting it using a correction coefficient that reflects the voltage-grayscale dependence, errors caused by the instability of the scanning system itself can be effectively eliminated, making the corrected curve more accurately reflect the essential law between dose and grayscale. This approach improves the reliability and accuracy of the dose-grayscale conversion relationship, reduces system errors at the data source, and provides a more reliable mathematical model basis for converting the grayscale data of the film under test into a dose distribution. This ensures the repeatability and accuracy of the whole central dose verification results, and ultimately supports the effectiveness and safety verification of radiotherapy plans at the execution level.

[0066] In another preferred embodiment, if multiple voltage ranges have the same rate of change of optical density values ​​and all are minimum values, then the average voltage of each range is used as the test voltage. Multiple radiochromatographic films after irradiation are scanned at each test voltage, the standard deviation of optical density values ​​corresponding to each test voltage is calculated, and the test voltage with the smallest standard deviation is selected as the target voltage.

[0067] If multiple voltage ranges have the same rate of change in optical density values, and all of them are at their minimum, the midpoint voltage value of these voltage ranges is first calculated as the candidate test voltage. For example, when the rate of change in the 15-20V and 25-30V ranges is the same and the lowest, two test voltages, 17.5V and 27.5V, are calculated respectively. Then, under each test voltage, multiple radiochromatographic films irradiated with the same known dose are repeatedly scanned to obtain multiple sets of optical density readings. Next, the multiple optical density values ​​measured on all films under each test voltage are statistically analyzed, and their standard deviation is calculated. The magnitude of the standard deviation reflects the degree of dispersion of the multiple measurement results under that voltage. Finally, the test voltage with the smallest standard deviation is selected as the final target voltage. For example, if the standard deviation value is smaller at 17.5V, it is determined as the target voltage.

[0068] The reason for introducing repeated scanning and calculating the standard deviation for secondary screening when the rate of change is the same and cannot be distinguished is that the rate of change of optical density value can only measure the sensitivity of voltage fluctuations to the reading, but cannot directly reflect the repeatability and stability of the measurement itself at that voltage. By performing actual repeated scanning at candidate voltages and calculating the standard deviation of optical density values, we can objectively evaluate which voltage condition the scanning system output is most stable and least affected by random errors. Selecting the voltage with the smallest standard deviation as the target voltage means that all subsequent scanning and measurement will be performed under the condition that the system is most stable and has the lowest noise. This minimizes the random fluctuations introduced by the measuring instrument itself from the source, providing a crucial stability guarantee for the subsequent accurate establishment of dose-grayscale curves and accurate dose conversion of the film to be tested. Ultimately, this ensures the high reliability and consistency of the whole central dose verification results, meeting the strict requirements of radiotherapy for precise dose control.

[0069] In another preferred embodiment, step S6 further includes obtaining a validation plan dose distribution map, and performing image registration based on the final dose map and the validation plan dose distribution map to obtain a dose pass value. If the dose pass value is greater than or equal to the preset pass value threshold, the dose is determined to be qualified.

[0070] First, feature points with clear physical or geometric significance are extracted from the two images, such as the boundary inflection points of the radiation field, the center points of high or low dose values, etc. These stable and identifiable features establish a spatial correspondence between the two images. Next, based on this correspondence, a set of transformation parameters is calculated using a spatial transformation algorithm. These parameters typically include translation distance, rotation angle, and scaling ratio. Using these parameters, the coordinates of each pixel in the final dose map are mathematically transformed to ensure complete spatial alignment with the planned dose distribution map. This eliminates positional, angular, and scale differences between images caused by physical factors such as patient positioning and scanner placement. This provides a unified spatial benchmark for subsequent accurate dose comparisons. After registration, for each pixel in the dose map, its planned dose value is read at the corresponding position in the planned dose distribution map, and the dose difference between the two is calculated. At the same time, the spatial distance between the dose value of the pixel and the nearest isodose line in the planned map is calculated. The dose deviation and spatial distance deviation are combined to form a comprehensive error index. The comprehensive error of all pixels in the entire map is statistically analyzed, and pixels with errors lower than the preset tolerance threshold are judged as qualified points. The final dose pass value is the proportion of qualified pixels to the total number of pixels. If this proportion is greater than or equal to the preset pass threshold, the dose verification is judged to be qualified.

[0071] This is because, in actual clinical settings, there are inevitably slight spatial shifts, rotations, or scaling between the actual dose distribution map measured by radiochromatographic film and the planned dose distribution map calculated by the treatment planning system. These geometric mismatches, if not corrected, can directly lead to serious misjudgments during dose comparison. Image registration by extracting stable features can accurately eliminate these geometric deviations, ensuring that every pixel is in the same anatomical position for dose comparison. This is the primary prerequisite for accurate dose verification. Furthermore, using a comprehensive error index that combines dose deviation and spatial distance for pass rate calculation is because a single dose difference is sometimes insufficient to fully reflect the clinical acceptability of the dose distribution. For example, in high-dose gradient regions, even a small spatial shift can lead to a huge dose difference. A comprehensive criterion can more scientifically and clinically assess the accuracy of dose execution.

[0072] In another preferred embodiment, the specific calculation process for the dose value is as follows:

[0073] Feature points are extracted from the dose map and the planned dose distribution map. The feature points include field boundary points, dose extreme points, and anatomical structure markers. Spatial transformation parameters are calculated based on the correspondence of the feature points. The spatial transformation parameters include translation, rotation angle, scaling ratio, and shearing factor. The dose map is then subjected to coordinate transformation based on the spatial transformation parameters so that the dose map and the planned dose distribution map are in the same coordinate system.

[0074] For all pixels in the dose map, the dose value corresponding to each pixel is identified. For pixel i, the planned dose value at the same position in the planned dose distribution map is obtained, and the difference between the planned dose value and the dose value of pixel i is calculated to obtain the dose difference value D. The spatial distance d from pixel i to the isodose line in the planned dose distribution map that is closest to its dose value is calculated. Based on the spatial distance d and the dose difference value D, the error value of pixel i is calculated, thereby obtaining the error value corresponding to all pixels. Pixels with error values ​​less than a preset error threshold are marked as qualified pixels. The ratio of qualified pixels to total pixels in the dose map is counted, and the ratio is used as the dose pass value.

[0075] The specific calculation process for the dose pass value is as follows:

[0076] ;

[0077] Where Hi is the error value corresponding to the i-th pixel, Delta D is the preset dose tolerance, Delta d is the preset spatial distance tolerance, Di is the dose difference D corresponding to the i-th pixel, and di is the spatial difference d corresponding to the i-th pixel.

[0078] In practice, the dose map and planned dose distribution map are first processed using image processing software (such as MATLAB). Edge detection algorithms (such as the Canny operator) are used to identify the contours of the radiation irradiation area in the dose map, thereby extracting the radiation field boundary points, such as finding the edge inflection points of the skull base radiation field in the dose map. The highest and lowest dose points are determined by traversing the image pixel values, extracting extreme dose points, such as the lowest dose point in the spinal cord region and the highest dose point in the tumor target area. Based on a preset anatomical structure template, anatomical structure markers such as cervical vertebrae and ventricles are marked in the image as anatomical structure markers. Next, a transformation model is selected based on the degree of deformation of the two images. If the images only have linear transformations such as translation, rotation, and scaling, an affine transformation model is used; if there is nonlinear deformation, an elastic transformation model is selected. Taking the affine transformation model as an example, the correspondence between feature point pairs is calculated using the least squares method to solve for the spatial transformation parameters, such as a translation of (5 pixels, -3 pixels), a rotation angle of 5 degrees, a scaling ratio of 1.02, and a shearing factor of 0.01. Finally, the calculated spatial transformation parameters are applied to the dose map to transform the coordinates of each pixel in the dose map. For example, if the original coordinates of a pixel are (x, y), after translation, rotation, scaling and shearing, the new coordinates (x', y') are obtained, so that the dose map and the planned dose distribution map are in the same coordinate system, thus completing image registration. For example, the position of the spinal cord in the dose map is precisely aligned with the position of the spinal cord in the planned map.

[0079] Because the dose map and the planned dose distribution map may have spatial discrepancies due to factors such as scanning angle and patient positioning, extracting representative feature points such as field boundary points, dose extreme points, and anatomical landmarks can accurately capture the spatial correspondence between the two images. Using affine or elastic transformation models to calculate spatial transformation parameters and perform coordinate transformation can eliminate spatial differences such as translation, rotation, scaling, and shearing between the images, placing them in the same coordinate system. This ensures that the actual dose distribution and the planned dose distribution can be accurately compared on the same spatial scale during subsequent dose pass value calculations, avoiding misjudgments due to spatial misalignment. It achieves high-precision spatial alignment between the dose map and the planned dose distribution map, laying the foundation for accurate dose pass value calculation and dose qualification determination. Ultimately, this ensures the accuracy of central nervous system dose verification, making the comparison between the dose distribution in the radiotherapy plan and the actual execution more reliable, and providing strong support for precise radiotherapy of tumors.

[0080] In practice, the center pixel of the dose map is first located, for example, by calculating the middle position of the image's rows and columns. A Cartesian coordinate system is established with this point as the origin, with the horizontal and vertical axes corresponding to the horizontal and vertical directions of the image, respectively. Then, for each pixel in the grayscale image, its corresponding coordinates (x, y) are generated according to the established coordinate system. For example, if a pixel is located 10 positions to the right and 5 positions above the origin, its coordinates are (10, 5). Simultaneously, the dose value corresponding to this pixel is identified from the previously generated radiochromatographic film dose map, for example, a dose value of 20 Gy. Next, the dose tolerance DeltaD and spatial distance tolerance Deltaad are set according to the requirements of clinical radiotherapy, for example, by setting appropriate reasonable tolerance ranges based on conventional standards. For each pixel i (xi, yi), the nearest isodose line is found in the planned dose distribution map, and the spatial distance d from the pixel to this isodose line is calculated, for example, by using the geometric distance formula, the distance is calculated to be 1.5 units. Then, based on this distance d and the set tolerance, the error value of each pixel is calculated. For example, the distance d is compared with the spatial distance tolerance (Deltad), while also considering the difference between the dose value and the planned dose. If the error value is less than a preset threshold, the pixel is marked as a qualified pixel. For example, if the distance d of a pixel is less than the spatial distance tolerance and the dose difference is also within the dose tolerance, it is marked as qualified. Finally, the number of all qualified pixels in the dose map is counted, and the ratio of the qualified pixels to the total number of pixels is calculated. This ratio is marked as the deviation value. For example, if there are 900 qualified pixels and the total number of pixels is 1000, the ratio is 0.9.

[0081] Establishing a Cartesian coordinate system with the center pixel of the dose map as the origin provides a unified spatial reference for both the dose map and the planned dose distribution map, facilitating subsequent comparative analysis of the spatial position and dose value of each pixel. Generating the coordinates of all pixels and identifying their corresponding dose values ​​enables a refined quantitative assessment of the dose distribution. Setting dose tolerance and spatial distance tolerance clarifies the criteria for determining whether the dose is acceptable, ensuring a systematic assessment. Calculating the distance from each pixel to the nearest isodose line and using this distance to calculate the error value allows for a comprehensive evaluation of the dose accuracy of each pixel from both spatial position and dose deviation dimensions. Marking pixels with error values ​​less than a preset threshold as acceptable and statistically analyzing their proportion provides a quantitative and intuitive reflection of the degree of conformity between the actual and planned dose distributions. This approach allows for an objective and comprehensive assessment of the accuracy of actual dose execution during whole-center dose verification, providing a quantitative basis for determining whether the radiotherapy plan is accurately implemented. The ultimate goal is to obtain reliable dose pass values ​​through a series of rigorous calculations and statistical steps, thereby determining whether the dose is acceptable. It can ensure the accuracy and reliability of the results of central nervous system dose verification, providing an important guarantee for the precise irradiation of the tumor target area and the effective protection of normal tissues during radiotherapy, and helping to achieve the goal of precision radiotherapy.

[0082] The foregoing has provided a detailed description of one embodiment of the present invention, but this description is merely a preferred embodiment and should not be construed as limiting the scope of the invention. All equivalent variations and modifications made within the scope of the claims of this invention should still fall within the patent coverage of this invention.

Claims

1. A full-patient dose verification method based on EBT3 film without washing, characterized in that, The method comprises the following steps: S1, continuously collecting the same irradiated radiochromatogram film to obtain a gray data sequence and a corresponding scanning device driving voltage sequence of each collection; S2, establishing a response function model between the driving voltage and the gray response according to the driving voltage value and the corresponding gray data mean value at each collection time; S3, determining a target voltage in advance, and determining a correction coefficient corresponding to each driving voltage value based on the target voltage and the response function model; S4, correcting a preset dose-gray curve graph according to the correction coefficient to obtain a corrected dose-gray curve graph; S5, obtaining the gray data of the current radiochromatogram film and the driving voltage at the time of collection, and determining the gray correction coefficient corresponding to the driving voltage, for any data point in the gray graph, multiplying the gray data of the data point by the gray correction coefficient to obtain corrected gray data; S6, substituting the corrected gray data into the corrected dose-gray curve to obtain the dose value at the data point, and collecting the dose values at all data points to generate a final dose distribution graph; The specific determination process of the target voltage is: A plurality of film groups with different predetermined dose levels are obtained, the film groups are scanned at different voltages to measure the optical density values corresponding to each film, a curve of the optical density value changing with the voltage is generated according to each predetermined dose level and the corresponding optical density value, the change rate of the optical density value in different voltage intervals is calculated, the voltage interval in which the change rate of the optical density value tends to be the smallest is identified, and the mean value of the voltage interval is selected as the target voltage; The acquisition process of the correction coefficient is: A first gray mean theoretical value corresponding to the target voltage is determined based on the response function model, a second gray mean theoretical value is obtained for each driving voltage value through the response function model, and the first gray mean theoretical value and the second gray mean theoretical value are subjected to ratio operation, thereby obtaining the gray correction coefficient corresponding to each voltage value.

2. A full-midline dose verification method based on the EBT3 film without washing according to claim 1, characterized in that, In the S4, the specific acquisition process of the preset dose-gray curve graph is: S11, labeling information and dose information of a plurality of target radiochromatogram films; S12, irradiating a plurality of target radiochromatogram films based on the dose information of each target radiochromatogram film; S13, scanning the irradiated target radiochromatogram film to obtain the driving voltage of the scanning device and the corresponding gray data at the driving voltage; S14, calculating the mean value of the gray data, pairing the corresponding dose information with the calculated mean value of the gray data to generate a discrete data point set, and establishing a dose-gray curve graph based on the discrete data point set.

3. A full-midline dose verification method based on the EBT3 film without washing according to claim 1, characterized in that, In the S4, the specific process of correcting the preset dose-gray curve graph is: For each dose-gray data point of the preset dose-gray curve graph, the gray value of the data point is multiplied by the gray correction coefficient corresponding to the voltage value at the collection time of the data point to obtain the corrected gray data; The dose value is paired with the corrected gray data point to generate a corrected dose-gray curve.

4. The full-midline dose verification method based on the EBT3 film without washing according to claim 1, wherein, If there are multiple voltage intervals corresponding to the same optical density value change rate and all are minimum values, then the average voltage of each interval is taken as the test voltage, and the multiple radiocolorimetric films after irradiation are scanned under each test voltage, the standard deviation of the optical density value corresponding to each test voltage is calculated, and the test voltage with the smallest standard deviation is selected as the target voltage.

5. The method of claim 1, wherein the method is based on a filmless EBT3 full-portal dose verification method. In the S6, a verification plan dose distribution map is acquired, and image registration is performed based on the final dose distribution map and the verification plan dose distribution map to obtain a dose passing value. If the dose passing value is greater than or equal to a preset passing value threshold, it is determined that the dose is qualified.

6. A full-midline dose verification method based on the EBT3 film without washing according to claim 5, characterized in that, The specific calculation process of the dose passing value is as follows: Feature points in the final dose distribution map and the verification plan dose distribution map are extracted, the feature points including field boundary points, dose extreme points and anatomical structure identification points; spatial transformation parameters including translation, rotation angle, scaling ratio and shear factor are calculated according to the corresponding relationship of the feature points; coordinate transformation is performed on the final dose distribution map based on the spatial transformation parameters, so that the final dose distribution map and the verification plan dose distribution map are in the same coordinate system; For all pixel points in the final dose distribution map, the dose value corresponding to each pixel point is identified, for pixel point i, the planned dose value at the same position in the verification plan dose distribution map is acquired, the difference between the planned dose value and the dose value of pixel point i is calculated to obtain a dose difference value D; the spatial distance d of pixel point i to the isodose line closest to its dose value in the verification plan dose distribution map is calculated, the error value of pixel point i is calculated based on the spatial distance d and the dose difference value D, thereby obtaining the error value corresponding to all pixel points in the final dose distribution map, the pixel points with error values less than a preset error threshold are marked as qualified pixel points, the ratio of qualified pixel points to total pixel points in the final dose distribution map is counted, and the ratio is taken as the dose passing value.

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