Postoperative precise dosimetry evaluation method, system, device, medium and product based on iodized oil recognition correction of yttrium-90 microspheres

Abstract

This application discloses a method, system, device, medium, and product for precise postoperative dosimetry evaluation of yttrium-90 microspheres based on iodine oil recognition correction, relating to the field of smart healthcare. The method includes: obtaining patient acceptance... 90 Multimodal imaging data after SIRT treatment with Y-microspheres; preprocessing and registration of the multimodal imaging data to obtain registered imaging data; identification and 3D segmentation of iodized oil deposition areas in the liver based on the registered imaging data to obtain iodized oil identification results; and further analysis based on the iodized oil identification results. 90 The iterative reconstruction process of Y-PET or SPECT is modified to obtain a result that reflects the patient's internal environment. 90 A three-dimensional activity map of the Y distribution is obtained; using the iodized oil identification results and the three-dimensional activity map, the absorbed dose calculation is corrected to obtain a three-dimensional absorbed dose distribution map; based on the three-dimensional absorbed dose distribution map, dosimetric evaluation results are generated. This application aims to solve the problem of inaccurate dosimetric evaluation in the prior art.

Description

Technical Field

[0001] This application relates to the field of smart healthcare, and in particular to yttrium-90 based on iodine oil identification correction. 90 Y) Methods, systems, equipment, media, and products for precise postoperative dosimetry evaluation of microspheres. Background Technology

[0002] Hepatocellular carcinoma (HCC) is one of the most common malignant tumors worldwide. 90 Selective internal radiotherapy (SIRT) using gamma-ray microspheres has become an important local treatment for intermediate and advanced liver cancer, especially for patients who are not suitable for surgical resection or ablation. SIRT involves using gamma-ray microspheres to deliver radioactive isotopes... 90 Y microspheres are injected via the hepatic artery, allowing them to selectively deposit within highly vascularized tumor tissue, where they kill tumor cells at close range using beta rays.

[0003] Postoperative dosimetric evaluation after SIRT (Synthetic Injection Therapy), which involves accurately calculating the actual absorbed dose received by the tumor target area and normal liver tissue, is of crucial clinical value for predicting treatment response, assessing potential hepatotoxicity risks, guiding the development of subsequent combination therapy regimens (such as immunotherapy, targeted drug therapy, and repeat SIRT), and evaluating postoperative recovery. Precise dosimetry enables individualized treatment, maximizing therapeutic efficacy while minimizing side effects.

[0004] at present, 90 Postoperative dosimetric evaluation mainly relies on 90 Viability reconstruction is performed using positron emission tomography (e.g., via PET) or bremsstrahlung radiation (e.g., via SPECT), combined with the patient's anatomical information (usually from CT or MRI). Dosage is then calculated. However, in clinical practice, many liver cancer patients undergoing SIRT may have previously received transarterial chemoembolization (TACE), which often uses iodized oil (e.g., lipidol) as a carrier and embolic agent. Post-procedure, iodized oil can remain and accumulate in the tumor lesion and surrounding liver parenchyma for a long period.

[0005] Iodized oil has a high atomic number (Z=53) and high physical density, which manifests as a high signal (high CT value) in medical imaging (especially CT). The presence of iodized oil has... 90 Y PET or SPECT activity reconstruction and subsequent dose calculation introduce significant errors: (1) Attenuation Correction (AC) error: PET and SPECT image reconstruction requires accurate attenuation maps (μ-maps) to correct for photon attenuation in tissues. CT images are typically used to generate μ-maps. The high attenuation properties of iodized oil lead to a significant overestimation of μ values ​​in iodized oil deposition areas, thus affecting this area and adjacent areas. 90 Accurate reconstruction of Y activity usually leads to underestimation of activity. (2) Scatter Correction (SC) error: Scattered photons are another important factor affecting the quantitative accuracy of PET and SPECT. The generation and distribution of scattering are related to tissue density and atomic number. The presence of iodized oil changes the local scattering characteristics. If the existing scattering correction algorithm does not take into account the special physical properties of iodized oil, it will lead to inaccurate scattering correction, which will further affect the quantitative accuracy of activity. (3) Dosage calculation error: Accurate dose calculation (such as based on local energy deposition method, dose kernel convolution method or Monte Carlo simulation method) requires not only an accurate activity distribution map, but also an accurate tissue density (or mass) distribution map. If the high density characteristics of iodized oil are not included in the dose calculation model (for example, all soft tissues are regarded as water equivalent density), it will lead to inaccurate energy deposition calculation of the iodized oil deposition area, which will affect the accuracy of absorbed dose.

[0006] Therefore, residual iodized oil in the liver is a way to achieve... 90 A key technical bottleneck in the accurate dosimetric evaluation after G-microsphere SIRT is the use of microspheres. Existing methods often ignore or fail to effectively address interference from iodized oil, leading to reduced reliability of dosimetric results and limiting their clinical application value. Summary of the Invention

[0007] The purpose of this application is to provide a method, system, device, medium, and product for precise postoperative dosimetric evaluation of yttrium-90 microspheres based on iodized oil identification correction. This method can improve the reliability of dosimetric results and solve the problem of intrahepatic iodized oil deposition caused by preoperative treatment (such as TACE) in liver cancer patients, which interferes with the results of existing technologies. 90 The inaccurate dosimetric evaluation can be caused by the need for post-SIRT PET or SPECT activity reconstruction (attenuation correction, scattering correction) and dose calculation (mass / density) of Y-microspheres.

[0008] To achieve the above objectives, this application provides the following solution: Firstly, this application provides a precise postoperative dosimetric evaluation method for yttrium-90 microspheres based on iodized oil recognition correction, including: Obtain patient acceptance 90 Multimodal imaging data after Y-microsphere SIRT treatment; the multimodal imaging data includes 90 Y-emission photon imaging data and anatomical structure and iodized oil information imaging data; The multimodal image data is preprocessed and registered to obtain registered image data; Based on the registered image data, the iodized oil deposition area in the liver was identified and three-dimensionally segmented to obtain the iodized oil identification result. Based on the iodized oil identification results 90 The iterative reconstruction process of Y-PET or SPECT is modified to obtain a result that reflects the patient's internal environment. 90 Three-dimensional activity plot of the Y distribution; Using the iodized oil identification results and the three-dimensional activity map, the absorbed dose calculation is corrected to obtain a three-dimensional absorbed dose distribution map; Dosimetric evaluation results are generated based on the three-dimensional absorbed dose distribution map.

[0009] Secondly, this application provides a precise postoperative dosimetric evaluation system for yttrium-90 microspheres based on iodized oil recognition correction, comprising: The image data interface module is used to obtain patient data. 90 Multimodal imaging data after Y-microsphere SIRT treatment; the multimodal imaging data includes 90 Y-emission photon imaging data and anatomical structure and iodized oil information imaging data; The image processing module is used to preprocess and register the multimodal image data to obtain registered image data, and to identify and three-dimensionally segment the iodized oil deposition area in the liver based on the registered image data to obtain iodized oil identification results. The activity reconstruction module is used to perform activities based on the iodized oil identification results. 90 The iterative reconstruction process of Y-PET or SPECT is modified to obtain a result that reflects the patient's internal environment. 90 Three-dimensional activity plot of the Y distribution; The dose calculation module is used to correct the absorbed dose calculation using the iodized oil identification results and the three-dimensional activity map to obtain a three-dimensional absorbed dose distribution map. The user interface and reporting module are used to generate dosimetric evaluation results based on the three-dimensional absorbed dose distribution map and to display them visually.

[0010] Thirdly, this application provides a computer device, including: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the steps of the above-described method for precise postoperative dosimetric evaluation of yttrium-90 microspheres based on iodine oil identification correction.

[0011] Fourthly, this application provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the steps of the above-described method for precise postoperative dosimetric evaluation of yttrium-90 microspheres based on iodine oil identification correction.

[0012] Fifthly, this application provides a computer program product, including a computer program that, when executed by a processor, implements the steps of the above-described method for precise postoperative dosimetric evaluation of yttrium-90 microspheres based on iodine oil identification correction.

[0013] According to the specific embodiments provided in this application, this application has the following technical effects: This application provides a method, system, equipment, medium, and product for precise postoperative dosimetry evaluation of yttrium-90 microspheres based on iodized oil recognition correction. It utilizes iodized oil recognition results to... 90 Correcting the iterative reconstruction process of Y-PET or SPECT can significantly reduce the interference of iodized oil on the quantitative accuracy of PET / SPECT, resulting in a more accurate measurement. 90 Y-activity distribution. By utilizing iodized oil identification results and a three-dimensional activity map, the absorbed dose calculation is corrected, making the energy deposition calculation more consistent with physical reality, thus obtaining a more accurate absorbed dose distribution. Generating dosimetric evaluation results based on the three-dimensional absorbed dose distribution map improves the reliability of dosimetric results. Based on this, this application can solve the problem in the prior art where intrahepatic iodized oil deposition caused by preoperative treatment (such as TACE) in liver cancer patients interferes with... 90 The use of Y-microspheres for post-SIRT PET or SPECT activity reconstruction (attenuation correction, scattering correction) and dose calculation (mass / density) can lead to inaccurate dosimetric evaluations, thus requiring more reliable decision support for clinicians. Attached Figure Description

[0014] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0015] Figure 1A flowchart illustrating a precise postoperative dosimetric evaluation method for yttrium-90 microspheres based on iodized oil identification correction, provided in an embodiment of this application; Figure 2 Example liver CT image provided in an embodiment of this application; Figure 3 This is a schematic diagram of an iodized oil mask obtained based on AI segmentation, provided in an embodiment of this application. Figure 4 This is a schematic diagram showing the relationship between CT values ​​and density for different concentrations of iodized oil provided in an embodiment of this application; Figure 5 A schematic diagram illustrating the distribution range of iodized oil of different concentrations in CT imaging, provided in an embodiment of this application; Figure 6 This is a schematic diagram illustrating the composition of iodized oil of different concentrations provided in an embodiment of this application; Figure 7 This is a schematic diagram illustrating the relationship between different concentrations of iodized oil and density, provided in one embodiment of this application. Figure 8 A schematic diagram showing the comparison results of the effect of corrected substance density on dosage calculation provided in an embodiment of this application; Figure 9 This is a schematic diagram of the functional modules of a precise postoperative dosimetry evaluation system for yttrium-90 microspheres based on iodine oil identification correction, provided in an embodiment of this application.

[0016] Figure 10 This is a schematic diagram of the structure of a computer device provided in an embodiment of this application. Detailed Implementation

[0017] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0018] To make the above-mentioned objectives, features and advantages of this application more apparent and understandable, the application will be further described in detail below with reference to the accompanying drawings and specific embodiments.

[0019] In one exemplary embodiment, this application provides a method for precise postoperative dosimetric evaluation of yttrium-90 microspheres based on iodized oil identification correction. This method is executed by a computer device, specifically a terminal or server, or both. In this embodiment, the method is described using a server as an example. Figure 1 As shown, the method includes: Step 100: Obtain patient acceptance 90 Multimodal imaging data following Y-microsphere SIRT treatment. The multimodal imaging data includes... 90 Y-emission photon imaging data (such as...) 90 Y PET data or 90 Y Bremsstrahlung SPECT data) and anatomical structure and iodized oil information imaging data (such as CT scan data containing liver anatomy and iodized oil information, preferably dual-energy CT (DECT) or photon-counting detector CT (PCD-CT) data; if conventional CT is used, high image quality is required).

[0020] Step 101: Preprocess and register the multimodal image data to obtain registered image data. For example: The acquired multimodal image data undergoes necessary preprocessing (such as noise filtering and intensity normalization) and precise image registration, for example, registering CT images (containing anatomical structures and iodized oil information) with... 90 Y-type PET or SPECT images (containing activity information) are aligned to the same coordinate space, with a focus on ensuring accurate alignment of the liver region (even if the two are aligned within the liver region). During registration, rigid, affine, or elastic (deformable) registration algorithms can be used, with intelligent registration algorithms that incorporate liver organ segmentation or anatomical features being preferred to improve accuracy.

[0021] Step 102: Based on the registered image data, identify and three-dimensionally segment the iodized oil deposition area in the liver to obtain the iodized oil identification result. For example, based on the registered image data, an intelligent segmentation algorithm and a material decomposition method based on energy spectral CT / photon counting detector CT are used to identify and three-dimensionally segment the iodized oil deposition area in the liver to obtain the iodized oil identification result, thereby determining the three-dimensional spatial location and range information of the iodized oil deposition in the liver. The iodized oil identification result includes an iodized oil mask.

[0022] (1) The process of identifying iodized oil using the intelligent segmentation algorithm is as follows: Artificial intelligence algorithms such as deep learning (e.g., convolutional neural networks, U-Net, V-Net, and their variants) are used to process conventional CT or spectral CT images. A model trained on a large dataset of liver CT images labeled with iodized oil regions is used to automatically or semi-automatically segment iodized oil deposition areas, generating a three-dimensional mask of iodized oil (i.e., an iodized oil mask). This mask identifies voxels containing significant iodized oil components.

[0023] (2) The process of three-dimensional segmentation using the material decomposition method based on energy spectrum CT / photon counting detector CT is as follows: This process utilizes multi-energy information acquired by direct-spectral CT (DECT) or photon-counting detector CT (PC-CT). It applies material decomposition methods based on DECT / PC-CT (such as matrix material decomposition, image domain decomposition, or projection domain decomposition) to decompose mixed tissue signals into equivalent density or concentration maps of specific matrix materials. Quantitative iodine maps (such as iodine concentration maps or iodine maps) are directly generated, clearly showing the distribution and relative content of iodized oil, with high iodine value areas corresponding to iodized oil deposition areas. A three-dimensional mask of iodized oil can be generated based on a threshold set according to iodine concentration. Simultaneously, virtual non-iodine (VNI) or virtual monoenergetic (VME) images can be generated for subsequent correction. This process primarily involves applying material decomposition algorithms to process DECT or PC-CT data, generating quantitative iodine maps (such as iodine concentration maps or iodine maps), and determining the location and extent of iodized oil deposition based on these maps.

[0024] Step 103: Based on the iodized oil identification results, 90 The iterative reconstruction process of Y-PET or SPECT is modified to obtain a result that reflects the patient's internal environment. 90 A three-dimensional activity map of the Y distribution. For example, based on the results of iodized oil identification... 90 The iterative reconstruction process of Y-PET or SPECT performs attenuation correction or scattering correction to obtain a result that reflects the patient's internal environment. 90 The three-dimensional activity map of the Y distribution (i.e., the corrected one) 90 Y activity distribution map).

[0025] (1) Attenuation Correction (AC).

[0026] Step 1: Generate an initial attenuation map (μ-map) based on the attenuation-corrected CT image.

[0027] Step 2: Based on the iodized oil identification results, correct the μ value of the initial attenuation spectrum within the area marked by the iodized oil mask to obtain the corrected attenuation spectrum. This step is mainly to correct the μ value to an accurate value that reflects the high attenuation characteristics of iodized oil. This accurate value can be determined in the following ways: (a) calculated based on the iodine concentration from the energy-spectral CT and the known attenuation coefficient of iodine; (b) if conventional CT and AI segmentation are used, it can be set based on the CT value of the area or a preset iodized oil μ value; (c) using a VME image (e.g., a high keV image can reduce the influence of iodine) or VNI image generated by energy-spectral CT at a specific energy level as the base μ-map, and then combining it with iodine map information for local correction. The corrected μ-map is then used for... 90 Y-activity reconstruction.

[0028] Step 3: Apply the corrected attenuation spectrum to 90 Attenuation correction is implemented in iterative reconstruction algorithms such as YPET or SPECT (e.g., Ordered Subset Expectation Maximization (OSEM)).

[0029] Furthermore, when using energy spectrum CT or photon count CT data, the attenuation correction also includes using virtual non-iodine images generated by material decomposition or virtual monoenergetic images of specific energies as the basis for generating μ-maps.

[0030] (2) Multiple Scatter Correction (SC). This application incorporates information about iodized oil (such as location, range, density, or atomic number characteristics) into the scattering estimation model or scattering simulation process to improve the accuracy of scattering correction.

[0031] Existing scattering correction methods, such as model-based scattering estimation, simulation-based scattering estimation (e.g., Monte Carlo simulation), or two- or three-window-based methods, typically rely on attenuation maps and / or density information. However, this application incorporates a modified μ-map and / or tissue information (obtainable from energy dispersive spectroscopy (EDS) decomposition, considering the high density / high atomic number characteristics of iodized oil) into the scattering model or simulation to more accurately estimate and subtract scattered photons. The identification of high-density tissue is achieved based on step 102 above. The μ-map can accurately reflect tissue density differences, or high-density tissue can be directly identified to achieve tissue density model segmentation, providing crucial information for subsequent scattering correction. The process is as follows: (1) Generate CT images through CT scans, convert CT values ​​(Hounsfield Unit, HU) into 511keV photon attenuation coefficients required for PET imaging, and obtain a spatially registered μ-map (which must be completely matched with the PET scan field). (2) Calculation of scattered photons: Based on the μ-map, tissue regions are divided (e.g., high density in iodized oil, normal density in non-iodized oil), and corresponding scattering generation probability models are set for different regions. Iterative scattering estimation algorithms (e.g., single scattering simulation SSS, convolution back projection method) are used, with the attenuation coefficient of the μ-map as a constraint, to calculate the scattering coincidence count on each PET line of response (LOR). Combined with the preliminary estimate of the true coincidence count in the original PET data, the energy distribution and spatial dispersion effect of scattered photons are corrected.

[0032] (3) Scattering correction: Subtract the scattering coincidence count estimated by μ-map from the original PET data (total coincidence count) to obtain the corrected net coincidence count data.

[0033] Step 104: Using the iodized oil identification results and the three-dimensional activity map, correct the absorbed dose calculation to obtain a three-dimensional absorbed dose distribution map. This step mainly aims to correct the substance density or mass distribution information in the absorbed dose calculation process. The resulting three-dimensional absorbed dose distribution map can more accurately reflect the true absorption rate in vivo. 90 The Y-distribution. The implementation process of this step can be described as follows: Step 1: Generate a substance density / mass map based on the registered image data and iodized oil identification results. Wherein: Based on the registered image data, an initial voxel density or mass distribution map is generated. According to the iodized oil identification results, within the area marked by the iodized oil mask (i.e., the iodized oil deposition area), the values ​​in the initial density or mass distribution map of the voxels are corrected to accurate values ​​reflecting the actual physical density of the iodized oil-tissue mixture. This accurate value can be obtained in the following ways: a) calculated based on the material decomposition results of energy-dispersive CT (such as the relative content of basic substances like water and iodine); b) calibrated based on conventional CT values ​​using a pre-established CT value-density conversion relationship and considering the influence of iodized oil; c) obtained using effective atomic number (Zeff) maps and electron density maps generated by energy-dispersive CT. In non-iodized oil deposition areas, conventional tissue density values ​​(such as water equivalent density or converted from CT values) are used.

[0034] Dosage calculations are performed using a corrected density or mass distribution map (i.e., a substance density / mass map). When using energy-spectral CT or photon-counting CT data, the corrected precise density or mass value is calculated based on component information obtained from substance decomposition (such as water and iodine content).

[0035] Step 2: Using dose calculation methods (such as Voxel S-Value (VSV) convolution or Monte Carlo (MC) simulation), based on the three-dimensional activity map and the substance density / mass map, a more accurate three-dimensional absorbed dose distribution map (unit: Gy) is obtained, taking into account the influence of iodized oil.

[0036] Step 105: Generate dosimetric evaluation results based on the three-dimensional absorbed dose distribution map. These results include dose-volume histograms (DVH) of the tumor target area, normal liver tissue, and other related organs, as well as average dose and minimum / maximum dose. This accurate dosimetric information can be used to: more reliably predict treatment response and tumor control rate; more accurately assess the risk of liver and other organ toxicity; provide a basis for decision-making in developing subsequent individualized combination therapy plans (such as whether / when to administer immunotherapy, targeted therapy, secondary SIRT, etc.); and more objectively assess the patient's postoperative recovery.

[0037] By implementing steps 100-105 above, this application introduces precise identification of intrahepatic iodized oil (using AI or spectral CT) and feeds its information back to... 90 Key steps in gamma activity reconstruction and dose calculation (attenuation correction, scattering correction, and density distribution) can effectively overcome errors caused by iodized oil interference and significantly improve... 90 The precision of dosimetric evaluation after Y-microsphere SIRT provides a more reliable basis for individualized clinical treatment decisions.

[0038] In one exemplary embodiment of this application, taking the correction method using AI segmentation and conventional CT as an example, the above-mentioned correction method based on iodized oil identification provided in this application is described. 90 The implementation process of the precise dosimetric evaluation method for Y-microspheres after surgery is explained.

[0039] (1) Data collection: Patients undergo 90 After Y SIRT, collection 90 Y PET / CT data. CT refers to a routine diagnostic CT scan, for example, the resulting liver CT image is as follows: Figure 2 As shown in the figure, the highlighted areas correspond to iodized oil deposition; (2) Registration: The rigid + elastic algorithm was used to register PET and CT images, with a focus on optimizing the alignment of the liver region; (3) Iodized oil identification (AI segmentation): The registered CT liver region is input into a pre-trained deep learning model based on the U-Net architecture. This model has been trained on a large number of liver CT images containing iodized oil deposition after TACE (the iodized oil region is manually delineated by radiologists as the gold standard). The model outputs a three-dimensional binary mask that marks voxel regions with CT values ​​higher than a specific threshold (e.g., >200 HU) and typical morphological features of iodized oil. Among them, the obtained data is consistent with the above... Figure 2 The corresponding iodized oil mask is as follows: Figure 3 As shown. Figure 3 In the diagram, the red area represents the iodized oil, and the yellow area represents the liver.

[0040] (4) Activity Reconstruction Correction: (a) AC Correction: Generate an initial μ-map based on the original CT. Within the iodized oil mask region, uniformly set the μ value to a higher preset value (e.g., the μ value at the corresponding energy estimated based on the density of iodized oil, or a value obtained through experimental calibration). Use this corrected μ-map for PET OSEM reconstruction. (b) SC Correction: In the scattering simulation or model, use the corrected μ-map and consider its higher density within the iodized oil mask region (which can be set to a specific value, such as ~1.5 g / cm³). 3 Or higher, depending on the concentration of iodized oil. The CT value, density, and elemental composition of iodized oil with different concentration ratios are as follows: Figures 4-7 As shown, density and elemental composition have varying degrees of influence on PET imaging and dosimetry calculations.

[0041] (5) Dose calculation correction: (a) Density map correction: An initial density map is generated based on the original CT (e.g., through the CT value-density conversion curve). Within the iodized oil mask area, the voxel density is corrected to the preset iodized oil mixed tissue density value. (b) Calculation: Using the corrected activity map (from step (4)) and the corrected density map, the three-dimensional dose distribution is calculated using the VSV method. Among them, the comparison results of the influence of the corrected substance density on the dose calculation are as follows: Figure 8 As shown. Figure 8 Part (a) represents the dose distribution or DVH before correction. Figure 8 Part (b) represents the dose distribution or DVH before correction. Figure 8 Part (c) shows the uncorrected dose distribution or the effect of DVH on surrounding tissues. Figure 8 The (d) part represents the effect of the corrected dose distribution or DVH on the surrounding tissues.

[0042] (6) Output: Generate a dosimetric evaluation report containing DVH and key dose indicators.

[0043] In an exemplary embodiment of this application, the implementation process of the postoperative precise dosimetric evaluation method for yttrium-90 microspheres based on iodine oil identification correction provided above is described using a correction method based on energy spectrum CT material decomposition as an example.

[0044] (1) Data collection: Patients undergo 90 After Y SIRT, collection 90 Y PET data. Liver spectral CT (DECT) data acquired at similar time points (e.g., simultaneous PET / CT scans) or separately.

[0045] (2) Registration: Register a composite image of DECT (such as a simulated conventional 120 kVp image) with a PET image to ensure that the liver region is aligned.

[0046] (3) Iodized oil identification (substance decomposition): Using an energy dispersive CT post-processing workstation or software, perform three-substance decomposition (e.g., water, iodine, calcium / bone) on the DECT data. Generate a quantitative iodine concentration map. Set an appropriate iodine concentration threshold (e.g., greater than 2 mg / mL) to generate a three-dimensional mask of iodized oil. Simultaneously generate a virtual non-iodine (VNI) image or a VME image at a specific energy (e.g., 70 keV).

[0047] (4) Activity Reconstruction Correction: (a) AC Correction: A μ-map is generated using VNI or 70keV VME images as a base (these images have removed or reduced the influence of iodine). Then, based on the iodine concentration map and the known mass decay coefficient of iodine at PET photon energy (511keV), the additional decay contribution of the iodine oil region is calculated and superimposed on the base μ-map to form the final corrected μ-map. This is then used for PET OSEM reconstruction. (b) SC Correction: In the scattering model, the corrected μ-map is used, and tissue composition information (such as water and iodine content) obtained from material decomposition is utilized to more accurately simulate scattering characteristics.

[0048] (5) Dosage calculation correction: (a) Density map correction: Based on the decomposition results of the substances (such as the volume or mass fraction of water and iodine) and the known density of each component, the accurate density of the mixed tissue is calculated on a voxel-by-voxel basis, generating a corrected density map. (b) Calculation: Using the corrected activity map and the corrected density map, dose calculation is performed using Monte Carlo simulation software (such as GATE, MCNP). MC simulation can handle particle transport in complex geometries and non-uniform density media more accurately.

[0049] (6) Output: Generate a dosimetric evaluation report containing DVH, isodose plots and key dose indices.

[0050] Based on the above description, the iodine oil identification correction provided in this application... 90 The Y-microsphere postoperative precise dosimetric evaluation method aims to address the impact of residual iodized oil in the liver of liver cancer patients. 90 Y SIRT postoperative PET / SPECT activity reconstruction (attenuation and scattering correction) and dose calculation (material mass) errors. This method includes: obtaining patient... 90 Y PET / SPECT and CT (preferably spectral CT / photon counting CT) data; image registration; accurate identification and segmentation of intrahepatic iodized oil using intelligent segmentation algorithms or spectral CT / photon counting CT material decomposition technology; correction using the location, extent, and physical properties information of the iodized oil. 90 Attenuation and scattering corrections were performed during gamma activity reconstruction; iodized oil information was used to correct the substance density / mass distribution in dose calculation; finally, an accurate three-dimensional absorbed dose distribution was calculated. This application significantly improves the efficiency of dose calculation by effectively eliminating iodized oil interference. 90 Accurate postoperative dosimetric evaluation provides a reliable basis for predicting clinical efficacy, assessing toxicity, and making subsequent individualized treatment decisions.

[0051] Based on the same inventive concept, embodiments of this application also provide a method for implementing the above-mentioned iodine oil-based identification correction. 90 A Precise Postoperative Dosimetric Evaluation Method for Y-Microspheres Based on Iodized Oil Recognition Correction90 A precise postoperative dosimetric evaluation system for Y-microspheres. The solution provided by this system is similar to the solutions described above; therefore, one or more solutions based on iodized oil identification correction are presented below. 90 For specific limitations in the implementation examples of the Y-microsphere postoperative precision dosimetry evaluation system, please refer to the section above regarding the correction based on iodized oil identification. 90 The limitations of precise dosimetric evaluation methods after Y-microsphere surgery will not be elaborated here.

[0052] In one exemplary embodiment, such as Figure 9 As shown, a method based on iodized oil recognition correction is provided. 90 The Y-microsphere postoperative precision dosimetry evaluation system includes: an image data interface module, an image processing module, an activity reconstruction module, a dose calculation module, and a user interface and reporting module.

[0053] The image data interface module is used to obtain patient data. 90 Multimodal imaging data following SIRT treatment with Y-microspheres. This data is used for receiving or retrieving... 90 Y PET / SPECT data and CT (conventional / spectral / photon counting) data.

[0054] The image processing module is used to preprocess and register multimodal image data to obtain registered image data. This registered image data is then used to identify and 3D segment iodized oil deposition areas within the liver, yielding iodized oil identification results. In practical applications, this module can be configured with functional units that perform image preprocessing, image registration (especially intelligent liver registration), intelligent iodized oil segmentation (AI-based), and / or energy-dispersive CT material decomposition algorithms.

[0055] The activity reconstruction module is used to perform activities based on iodized oil identification results. 90 The iterative reconstruction process of Y-PET or SPECT is modified to obtain a result that reflects the patient's internal environment. 90 A three-dimensional activity map of the Y distribution. In practical applications, this module can be configured with an algorithm to perform PET / SPECT iterative reconstruction and integrates a mechanism for attenuation correction or scattering correction based on iodized oil information.

[0056] The dose calculation module uses the iodized oil identification results and the three-dimensional activity map to correct the absorbed dose calculation and obtain a three-dimensional absorbed dose distribution map. In practical applications, this module can be configured with algorithms to perform VSV or MC dose calculations and integrates a mechanism to correct the substance density / mass map based on iodized oil information.

[0057] The user interface and reporting module is used to generate dosimetric evaluation results based on three-dimensional absorbed dose distribution maps and to visualize them. In practical applications, this module is mainly used to display the processing procedures, results (activity maps, dose maps, DVH, etc.), and generate dosimetric evaluation reports.

[0058] As an optional implementation, this application provides a correction based on iodized oil recognition. 90 The Y-microsphere postoperative precision dosimetry evaluation system can be integrated into existing medical image processing platforms (such as PACS systems and TPS radiotherapy planning systems) or as a standalone software / hardware solution. After receiving image data, the system automatically or under user guidance performs steps such as registration, iodized oil identification (calling AI algorithms or energy spectrum processing algorithms), activity reconstruction correction (interacting with reconstruction software interfaces), and dose calculation correction (calling the dose calculation engine), ultimately generating a dosimetry evaluation report.

[0059] Based on the above description, compared with the prior art, this application has at least the following significant effects: 1. Improved 90 Accuracy of Y activity reconstruction: This application significantly reduces the interference of iodized oil on the quantitative accuracy of PET / SPECT by accurately identifying iodized oil and using this information to correct attenuation and scattering, thus obtaining a more accurate result. 90 Y activity distribution.

[0060] 2. Improved accuracy of dose calculation: This application incorporates the precise location and physical properties (high density) of iodized oil into the dose calculation, making the energy deposition calculation more consistent with physical reality, thereby obtaining a more accurate absorbed dose distribution.

[0061] 3. Enhanced clinical value of dosimetric evaluation: The accurate dosimetric results in this application can provide clinicians with more reliable decision support for efficacy prediction, toxicity assessment and individualized development of subsequent treatment plans, which may ultimately improve patient prognosis.

[0062] 4. Flexible and adaptable technical solutions: This application provides two iodized oil identification paths: AI-based intelligent segmentation and CT material decomposition based on energy spectrum CT / photon counting detector. The optimal solution can be selected based on available equipment and data.

[0063] 5. Promoting the development of personalized precision radiotherapy: This application aims to achieve... 90 Y SIRT is an important technical support for individualized precision dosimetry, which is in line with the trend of radiotherapy towards precision and individualization.

[0064] In one exemplary embodiment, a computer device is provided, which may be a server or a terminal, and its internal structure diagram may be as follows. Figure 10As shown. This computer device includes a processor, memory, input / output interfaces (I / O), and a communication interface. The processor, memory, and I / O interfaces are connected via a system bus, and the communication interface is also connected to the system bus via the I / O interfaces. The processor provides computing and control capabilities. The memory includes non-volatile storage media and internal memory. The non-volatile storage media stores the operating system, computer programs, and a database. The internal memory provides the environment for the operating system and computer programs in the non-volatile storage media to run. The database stores data based on iodine oil identification correction. 90 Postoperative precise dosimetric evaluation data for Y-microspheres. The computer device's input / output interface is used for information exchange between the processor and external devices. The computer device's communication interface is used for communication with external terminals via a network connection. When executed by the processor, the computer program implements a correction based on iodized oil recognition. 90 Precise dosimetric evaluation method for Y-microspheres after surgery.

[0065] Those skilled in the art will understand that Figure 10 The structure shown is merely a block diagram of a portion of the structure related to the present application and does not constitute a limitation on the computer device to which the present application is applied. Specific computer devices may include more or fewer components than those shown in the figure, or combine certain components, or have different component arrangements.

[0066] In one exemplary embodiment, a computer device is provided, including a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to implement the steps in the above-described method embodiments.

[0067] In one exemplary embodiment, a computer-readable storage medium is provided storing a computer program that, when executed by a processor, implements the steps in the above-described method embodiments.

[0068] In one exemplary embodiment, a computer program product is provided, including a computer program that, when executed by a processor, implements the steps in the above-described method embodiments.

[0069] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, data stored, data displayed, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties, and the collection, use and processing of the relevant data must comply with relevant regulations.

[0070] Those skilled in the art will understand that all or part of the processes in the above embodiments can be implemented by a computer program instructing related hardware. The computer program can be stored in a non-volatile computer-readable storage medium, and when executed, it can include the processes of the embodiments described above. Any references to memory, databases, or other media used in the embodiments provided in this application can include at least one of non-volatile and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (RRAM), magnetic random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. By way of illustration and not limitation, RAM can take many forms, such as Static Random Access Memory (SRAM) or Dynamic Random Access Memory (DRAM).

[0071] The databases involved in the embodiments provided in this application may include at least one type of relational database and non-relational database. Non-relational databases may include, but are not limited to, blockchain-based distributed databases. The processors involved in the embodiments provided in this application may be general-purpose processors, central processing units, graphics processing units, digital signal processors, programmable logic devices, quantum computing-based data processing logic devices, etc., and are not limited to these.

[0072] The technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0073] This document uses specific examples to illustrate the principles and implementation methods of this application. The descriptions of the above embodiments are only for the purpose of helping to understand the methods and core ideas of this application. Furthermore, those skilled in the art will recognize that, based on the ideas of this application, there will be changes in the specific implementation methods and application scope. Therefore, the content of this specification should not be construed as a limitation of this application.

Claims

1. A precise postoperative dosimetric evaluation method for yttrium-90 microspheres based on iodized oil recognition correction, characterized in that, include: Obtain patient acceptance 90 Multimodal imaging data after Y-microsphere SIRT treatment; the multimodal imaging data includes 90 Y-emission photon imaging data and anatomical structure and iodized oil information imaging data; The multimodal image data is preprocessed and registered to obtain registered image data; Based on the registered image data, the iodized oil deposition area in the liver was identified and three-dimensionally segmented to obtain the iodized oil identification result. Based on the iodized oil identification results 90 The iterative reconstruction process of Y-PET or SPECT is modified to obtain a result that reflects the patient's internal environment. 90 Three-dimensional activity plot of the Y distribution; Using the iodized oil identification results and the three-dimensional activity map, the absorbed dose calculation is corrected to obtain a three-dimensional absorbed dose distribution map; Dosimetric evaluation results are generated based on the three-dimensional absorbed dose distribution map.

2. The method for precise postoperative dosimetric evaluation of yttrium-90 microspheres based on iodized oil recognition correction according to claim 1, characterized in that, Based on the registered image data, the iodized oil deposition areas in the liver were identified and three-dimensionally segmented to obtain the iodized oil identification results, including: Based on the registered image data, an intelligent segmentation algorithm and a material decomposition method based on energy spectrum CT / photon counting detector CT are used to identify and three-dimensionally segment the iodized oil deposition area in the liver, and the iodized oil identification result is obtained; the iodized oil identification result includes an iodized oil mask.

3. The method for precise postoperative dosimetric evaluation of yttrium-90 microspheres based on iodized oil recognition correction according to claim 2, characterized in that, Based on the iodized oil identification results 90 The iterative reconstruction process of Y-PET or SPECT is modified to obtain a result that reflects the patient's internal environment. 90 The three-dimensional activity map of the Y distribution includes: Based on the iodized oil identification results 90 The iterative reconstruction process of Y-PET or SPECT performs attenuation correction or scattering correction to obtain a result that reflects the patient's internal environment. 90 The three-dimensional activity map of the Y distribution.

4. The method for precise postoperative dosimetric evaluation of yttrium-90 microspheres based on iodized oil recognition correction according to claim 3, characterized in that, Based on the iodized oil identification results 90 The iterative reconstruction process of Y PET or SPECT includes attenuation correction, including: An initial attenuation map is generated based on attenuation-corrected CT images; Based on the iodized oil identification result, the μ value of the initial attenuation spectrum is corrected within the area marked by the iodized oil mask to obtain the corrected attenuation spectrum; Apply the corrected attenuation map to 90 Attenuation correction is achieved during the iterative reconstruction process of Y PET or SPECT.

5. The method for precise postoperative dosimetric evaluation of yttrium-90 microspheres based on iodized oil recognition correction according to claim 1, characterized in that, Using the iodized oil identification results and the three-dimensional activity map, the absorbed dose calculation is corrected to obtain a three-dimensional absorbed dose distribution map, including: A material density / mass map is generated based on the registered image data and the iodized oil identification results. The three-dimensional absorbed dose distribution map is obtained by using a dose calculation method based on the three-dimensional activity map and the substance density / mass map.

6. The method for precise postoperative dosimetric evaluation of yttrium-90 microspheres based on iodized oil recognition correction according to claim 5, characterized in that, The dose calculation method is either the voxel S-value convolution method or the Monte Carlo simulation method.

7. A precise postoperative dosimetric evaluation system for yttrium-90 microspheres based on iodized oil recognition correction, characterized in that, include: The image data interface module is used to obtain patient data. 90 Multimodal imaging data after Y-microsphere SIRT treatment; the multimodal imaging data includes 90 Y-emission photon imaging data and anatomical structure and iodized oil information imaging data; The image processing module is used to preprocess and register the multimodal image data to obtain registered image data, and to identify and three-dimensionally segment the iodized oil deposition area in the liver based on the registered image data to obtain iodized oil identification results. The activity reconstruction module is used to perform activities based on the iodized oil identification results. 90 The iterative reconstruction process of Y-PET or SPECT is modified to obtain a result that reflects the patient's internal environment. 90 Three-dimensional activity plot of the Y distribution; The dose calculation module is used to correct the absorbed dose calculation using the iodized oil identification results and the three-dimensional activity map to obtain a three-dimensional absorbed dose distribution map. The user interface and reporting module are used to generate dosimetric evaluation results based on the three-dimensional absorbed dose distribution map and to display them visually.

8. A computer device, comprising: A memory, a processor, and a computer program stored in the memory and capable of running on the processor, characterized in that the processor executes the computer program to implement the postoperative precise dosimetric evaluation method for yttrium-90 microspheres based on iodine oil identification correction as described in any one of claims 1-6.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that, When executed by a processor, the computer program implements the precise postoperative dosimetric evaluation method for yttrium-90 microspheres based on iodine oil identification correction as described in any one of claims 1-6.

10. A computer program product, comprising a computer program, characterized in that, When executed by a processor, the computer program implements the precise postoperative dosimetric evaluation method for yttrium-90 microspheres based on iodine oil identification correction as described in any one of claims 1-6.

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