Thermal ablation temperature history reconstruction and three-dimensional damage mapping method based on CT thermal imaging end point temperature constraint
By constructing a temperature history template and a thermal damage assessment model in CT-guided microwave ablation, the temperature history of the entire ablation process is reconstructed and a three-dimensional damage map is generated. This solves the problem of quantitative characterization of thermal damage in CT-guided microwave ablation and achieves efficient quantitative assessment and visualization without real-time monitoring.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- FUZHOU UNIV
- Filing Date
- 2026-01-15
- Publication Date
- 2026-05-01
AI Technical Summary
In current CT-guided microwave ablation therapy, it is difficult to quantitatively reflect the accumulation of thermal damage in tissues during the ablation process through postoperative images, and there is a lack of quantitative characterization of the thermal accumulation effect throughout the ablation process.
Based on the temperature constraint of the endpoint of CT thermal imaging, the temperature history of the entire ablation process is reconstructed by constructing a temperature history template and introducing a thermal damage assessment model, and a three-dimensional tissue damage distribution map is generated. An engineering simplification model is used to transform the relationship between temperature history and thermal damage into a rapid mapping form.
It enables the reconstruction of the entire temperature history of ablation without real-time temperature monitoring, reduces computational complexity, provides visualized three-dimensional lesion maps, and provides quantitative imaging support for ablation adequacy assessment and clinical decision-making.
Smart Images
Figure CN121962444A_ABST
Abstract
Description
A method for thermal ablation temperature history reconstruction and 3D damage mapping based on CT thermal imaging endpoint temperature constraint Technical Field
[0001] This invention belongs to the field of medical image processing and biothermal modeling technology, specifically involving a method for reconstructing thermal ablation temperature history and creating three-dimensional damage maps based on the endpoint temperature constraint of CT thermal imaging. Background Technology
[0002] Microwave ablation is a thermotherapy widely used in the treatment of solid tumors such as the liver. Its efficacy is highly dependent on the duration of tissue exposure within a certain temperature range. In current clinical practice, doctors often rely on morphological changes in the low-density ablation zone in postoperative imaging or empirical temperature thresholds to assess the ablation effect, which makes it difficult to quantitatively reflect the cumulative thermal damage to the tissue throughout the ablation process.
[0003] The Arrhenius thermal injury model can quantitatively describe the process of tissue protein denaturation and necrosis through the integral of temperature over time, but its calculation requires complete temperature history data. In CT-guided microwave ablation clinical procedures, due to limitations in imaging dose and real-time performance, only a single endpoint temperature image at the end of ablation is usually available, which cannot be directly used for the time integral calculation of the Arrhenius model.
[0004] Therefore, how to reconstruct the temperature history of the entire ablation process under the condition that only the temperature field of the CT thermal imaging endpoint is known, and generate a reliable three-dimensional tissue damage distribution map accordingly, has become a key technical problem restricting the refined evaluation and decision support of CT-guided microwave ablation. Summary of the Invention
[0005] The purpose of this invention is to address the problem that existing CT-guided microwave ablation treatment methods mainly rely on empirical thresholds or endpoint temperature distribution for tissue thermal damage assessment, lacking quantitative characterization of the cumulative thermal effect throughout the ablation process. This invention provides a method for reconstructing the thermal ablation temperature history and creating three-dimensional damage maps based on CT thermal imaging endpoint temperature constraints. This method uses CT thermal imaging data acquired during or after the ablation procedure as input, obtaining the endpoint temperature field at the end of the ablation process through a data acquisition module. Based on this, and considering the consistency of temperature evolution patterns during clinical microwave ablation under a fixed ablation protocol, a temperature history inversion mechanism is introduced to construct a normalized temperature evolution template, parameterizing the endpoint temperature as a complete temperature history at discrete time points, thereby reconstructing the temperature changes throughout the ablation process. Simultaneously, a thermal damage assessment model is introduced to perform time integration calculations on the reconstructed temperature history, obtaining quantitative values of tissue thermal damage and corresponding necrosis fractions, thus achieving a quantitative description of the spatial cumulative effect of tissue thermal damage. To address the challenges of complex voxel-by-voxel time integral calculations and difficulties in engineering applications of thermal damage assessment models, this invention simplifies the model by transforming the relationship between temperature history and thermal damage into a rapid mapping based on endpoint temperature. This significantly reduces the complexity of three-dimensional damage calculations and improves computational efficiency and system stability. Finally, a visualization module generates a three-dimensional damage distribution map, enabling intuitive display and segmentation of tissue damage areas. This provides a calculable, reproducible, and biophysically significant quantitative imaging method for assessing ablation adequacy, determining ablation range, and assisting clinical decision-making during CT-guided microwave ablation.
[0006] To achieve the above objectives, the technical solution of the present invention is: a method for reconstructing the thermal ablation temperature history and creating three-dimensional damage maps based on the endpoint temperature constraint of CT thermal imaging, comprising:
[0007] Acquire CT thermal imaging data at the end of thermal ablation and construct a three-dimensional endpoint temperature field of the ablation area;
[0008] Based on the consistency of tissue temperature evolution under fixed ablation clinical protocols, a normalized temperature history template function is constructed.
[0009] Given the initial and final temperatures, the temperature history at discrete time points within the ablation region is reconstructed using the temperature history template function.
[0010] Based on the reconstructed temperature history, a thermal damage assessment model is introduced to perform time integration or mapping calculations to obtain the thermal damage quantification value at each spatial location.
[0011] A three-dimensional tissue damage distribution map is generated based on the thermal damage quantification value and then visualized.
[0012] Furthermore, the thermal ablation includes at least one of microwave ablation, radiofrequency ablation, laser ablation, or steam ablation.
[0013] Furthermore, the three-dimensional endpoint temperature field is obtained by converting the Hounsfield Unit values in the CT images from the CT thermal imaging data into temperature values using a linear mapping model. This three-dimensional endpoint temperature field characterizes the tissue temperature distribution at various spatial locations at the end of ablation, serving as a constraint for subsequent temperature history reconstruction and thermal damage calculation.
[0014] Furthermore, the temperature history template function is obtained by normalizing the temperature-time curves of multiple regions of interest and using robust statistical methods.
[0015] Furthermore, the temperature history reconstruction satisfies T(0) = initial temperature and T(t_end) = final temperature.
[0016] Furthermore, the thermal damage assessment model includes at least one of the Arrhenius tissue thermal damage model, the CEM43 thermal dose model, the temperature threshold model, or a machine learning model.
[0017] Furthermore, when the thermal damage assessment model is the Arrhenius tissue thermal damage model, the thermal damage quantification value at each spatial location is the thermal damage integral value, which is further converted into the theoretical necrosis fraction, and then a three-dimensional Arrhenius tissue damage distribution map is generated based on the thermal damage integral value or the theoretical necrosis fraction.
[0018] Furthermore, it also includes pre-constructing the relationship between the quantified thermal damage value and the endpoint temperature as a mapping function or lookup table to achieve fast mapping calculation based on the endpoint temperature.
[0019] Furthermore, the three-dimensional tissue damage distribution map is segmented using a preset threshold to obtain the theoretical necrosis area.
[0020] The present invention also provides a thermal ablation temperature history reconstruction and three-dimensional damage mapping system based on the endpoint temperature constraint of CT thermal imaging, including a memory, a processor, and computer program instructions stored in the memory and capable of being executed by the processor. When the processor executes the computer program instructions, it can implement the steps of the method described above.
[0021] The present invention also provides a computer-readable storage medium having stored thereon computer program instructions that can be executed by a processor, wherein when the processor executes the computer program instructions, it can implement the steps of the method described above.
[0022] Compared with the prior art, the present invention has the following beneficial effects:
[0023] 1) No real-time temperature monitoring is required; the entire temperature history of the ablation process can be reconstructed solely by the endpoint temperature of CT thermal imaging.
[0024] 2) By using temperature history template modeling, the time complexity of damage calculation in damage models such as Arrhenius is significantly reduced, making it feasible for engineering applications;
[0025] 3) For the first time, a three-dimensional tissue damage map (such as a three-dimensional Arrhenius tissue damage map) was introduced into the CT-guided microwave ablation procedure, providing a new quantitative imaging information layer for the assessment of ablation adequacy;
[0026] 4) It can output temperature field, damage quantification value and necrosis probability field, and supports three-dimensional display and segmentation, enhancing clinical interpretability and decision support capabilities. Attached Figure Description
[0027] Figure 1 is a schematic diagram of a method for reconstructing the thermal ablation temperature history and creating three-dimensional damage maps based on the endpoint temperature constraint of CT thermal imaging.
[0028] Figure 2 is a schematic diagram of a tissue damage field drawn according to an embodiment of the present invention.
[0029] Figure 3 is a schematic diagram of three-dimensional reconstruction of the tissue damage field according to an embodiment of the present invention. Detailed Implementation
[0030] The technical solution of the present invention will now be described in detail with reference to the accompanying drawings.
[0031] This invention provides a method for reconstructing the thermal ablation temperature history and creating three-dimensional damage maps based on the endpoint temperature constraint of CT thermal imaging, comprising:
[0032] Acquire CT thermal imaging data at the end of thermal ablation and construct a three-dimensional endpoint temperature field of the ablation region; (thermal ablation includes at least one of microwave ablation, radiofrequency ablation, laser ablation, or steam ablation)
[0033] Based on the consistency of tissue temperature evolution under fixed ablation clinical protocols, a normalized temperature history template function is constructed.
[0034] Given the initial and final temperatures, the temperature history at discrete time points within the ablation region is reconstructed using the temperature history template function.
[0035] Based on the reconstructed temperature history, a thermal damage assessment model is introduced for time integration or mapping calculation to obtain the quantitative value of thermal damage at each spatial location; (the thermal damage assessment model includes at least one of the following: Arrhenius tissue thermal damage model, CEM43 thermal dose model, temperature threshold model, or machine learning model).
[0036] A three-dimensional tissue damage distribution map is generated based on the thermal damage quantification value and then visualized.
[0037] The following is a detailed implementation process of the present invention.
[0038] As shown in Figure 1, a method for reconstructing the thermal ablation temperature history and creating a three-dimensional damage map based on the endpoint temperature constraint of CT thermal imaging is presented below, specifically for microwave ablation. The technical solution includes the following steps:
[0039] Step 1: Data Acquisition Steps
[0040] CT image data are acquired during or after microwave ablation, the ablation area is reconstructed and registered, and the three-dimensional endpoint temperature field at the end of ablation is obtained based on CT thermal imaging.
[0041] The endpoint temperature field is used to characterize the tissue temperature distribution at each spatial location at the end of ablation, serving as a constraint for subsequent temperature history reconstruction and thermal damage calculation.
[0042] Step 2: Temperature History Template Construction and Time Dimension Inversion
[0043] Based on the consistent temperature evolution pattern of microwave ablation under fixed clinical protocols, a normalized temperature history template function is pre-constructed to describe the typical changes in tissue temperature over time during the ablation process.
[0044] Given the initial and final temperatures, for any spatial location within the ablation region, the discrete time-point temperature history of that location during the ablation process is reconstructed based on the temperature history template function and the corresponding final temperature value, thereby obtaining a complete temperature time series.
[0045] By using the above method, the temperature information that can only be obtained at the end point can be inverted into the temperature history of the entire ablation process, thus realizing the reconstruction of time-dimensional information.
[0046] Step 3: Calculation steps for the thermal damage model (For ease of description, the Arrhenius tissue thermal damage model is used here)
[0047] Based on the reconstructed discrete-time temperature history, the Arrhenius tissue thermal damage model is introduced, treating the tissue thermal damage process as a temperature-driven first-order kinetic reaction process.
[0048] For each spatial location within the ablation zone, the temperature history is integrated over time according to the Arrhenius tissue thermal damage model to calculate the corresponding thermal damage integral value, and further to obtain the theoretical necrosis fraction, which is used to characterize the degree of irreversible thermal damage to the tissue.
[0049] This step enables the conversion of temperature information into quantitative indicators of tissue damage.
[0050] Step 4: Engineering Simplification and Rapid Mapping
[0051] To address the issues of high computational cost and insufficient real-time performance in volumetric temperature history integral calculations during engineering implementation, a mapping relationship between the endpoint temperature and the thermal damage integral is established under the condition that the temperature history template and the parameters of the Arrhenius tissue thermal damage model are fixed.
[0052] By pre-constructing a one-dimensional mapping function or lookup table, the thermal damage calculation process, which originally relied on time integration, is simplified into a fast mapping calculation based on the endpoint temperature. This significantly reduces the computational complexity of three-dimensional thermal damage mapping and improves the engineering feasibility and stability of the system.
[0053] Step 5: 3D Damage Mapping and Visualization
[0054] (1) Based on the thermal damage integral value or theoretical necrosis fraction, generate a three-dimensional Arrhenius thermal damage distribution map of the ablation area, and segment the damaged area based on a preset threshold.
[0055] (2) The obtained damage distribution results are visualized in three dimensions, and three-dimensional tissue damage images or models are output to evaluate the ablation range, ablation adequacy and spatial distribution characteristics of microwave ablation.
[0056] The following are specific embodiments of the present invention. These embodiments are for microwave ablation and use the Arrhenius tissue thermal damage model as the thermal damage assessment model to describe the method of the present invention. Other thermal ablation or thermotherapy methods, such as radiofrequency ablation, laser ablation, or steam ablation, can also be implemented using the method of the present invention. Similarly, other thermal damage assessment models, such as the clinical CEM43 thermal dose model, temperature threshold model, machine learning model, etc., can replace the Arrhenius tissue thermal damage model in the following embodiments.
[0057] Example 1: Acquisition of the temperature field at the endpoint of CT thermal imaging
[0058] After microwave ablation experiments or clinical ablation are completed, CT image data of the ablation area are acquired. The CT images are reconstructed and registered, and the CT values are converted into temperature values based on CT thermal imaging methods to generate a three-dimensional endpoint temperature field representing the end time of ablation (t=180 s).
[0059] In this embodiment, a linear mapping model is used to convert the Hounsfield Unit value HU in the CT image into a temperature value T. The mapping relationship is as follows:
[0060] T(°C) = a•HU + b,
[0061] Where a is the HU-temperature mapping slope and b is the intercept. In this embodiment, the parameters are set to: a = -0.31, b = 50.4.
[0062] To avoid interference from background regions (such as air and metal artifacts) in subsequent calculations, regions with HU values less than -500 are masked to exclude them from the temperature field construction. This yields the three-dimensional final temperature field T. 180 (x), where x represents the spatial location.
[0063] Example 2: Construction of Temperature History Template
[0064] Under clinical protocols with fixed microwave ablation power and ablation duration, the evolution of tissue temperature over time at different spatial locations exhibits a high degree of consistency, with the main difference lying in the amplitude of the final temperature. Based on this characteristic, this invention introduces a temperature history template to model the temperature evolution process.
[0065] First, multiple regions of interest (ROIs) were selected within the ablation region, and temperature-time discrete data were collected for each ROI. To eliminate initial temperature differences and measurement biases, the temperature curves for each ROI were normalized. The normalization method is defined as follows:
[0066] s i (t) = [T i (t) -T i (0)] / [T i (180) -T i (0)],
[0067] Among them, T i (t) represents the temperature of the i-th ROI at time t, where T i (0) represents the initial temperature, T i (180) represents the temperature at 180 s. This normalization process ensures that s i (0)=0, s i (180)=1.
[0068] After removing outlier ROI data, at each time point t, the median of the normalized results of all valid ROIs is taken to obtain the median form s(t) of the temperature history template. Simultaneously, the 25th and 75th quantile intervals are calculated to characterize the uncertainty range of temperature evolution.
[0069] In this embodiment, the temperature history template is represented by a piecewise linear function, and its key time nodes and corresponding normalized values are as follows:
[0070] t = 0 s, s(t) = 0;
[0071] t = 30 s, s(t) ≈ 0.110;
[0072] t = 60 s, s(t) ≈ 0.316;
[0073] t = 90 s, s(t) ≈ 0.535;
[0074] t = 120 s, s(t) ≈ 0.736;
[0075] t = 150 s, s(t) ≈ 0.894;
[0076] t = 180 s, s(t) = 1.
[0077] Piecewise linear interpolation is used between adjacent time points to form a complete temperature history template function s(t).
[0078] Example 3: Temperature History Reconstruction Based on Endpoint Temperature
[0079] Obtain the final temperature field T 180 After obtaining (x) and the temperature history template s(t), the temperature history of any spatial location x within the ablation region can be expressed as:
[0080] T(t, x) = T0 + [T 180 (x)- T0] • s(t), t ∈[0, 180 s],
[0081] Where T0 is the initial temperature. In this embodiment, the initial temperature is T0 = 15 ℃.
[0082] The above expressions ensure that the temperature history satisfies T(0,x)=T0 at t=0s and T(180,x)=T0 at t=180s. 180 (x), thus reconstructing the discrete-time temperature history of the entire ablation process when only the endpoint temperature is known.
[0083] Example 4: Calculation of Arrhenius Tissue Thermal Damage Model
[0084] Based on the reconstructed temperature history, the Arrhenius tissue thermal damage model is introduced to quantitatively calculate tissue damage. The Arrhenius damage integral is defined as:
[0085]
[0086] in, Let x represent the damage amount, t be the current time, and x be the spatial location variable. The intermediate time variable used for integration. The integral element represents the integral of the derivative with respect to time, where A is the frequency factor, ΔE is the activation energy of the reaction, R is the gas constant, and the temperature is expressed in absolute temperature.
[0087] In this embodiment, the parameter values are as follows:
[0088] A = 7.39 × 10 39 s -1 ;
[0089] ΔE = 2.577 × 10 5 J / mol;
[0090] R = 8.314 J / (mol•K).
[0091] After converting the temperature from Celsius to Kelvin, the thermal damage integral Ω(180,x) is obtained by integrating over the interval 0–180 s.
[0092] Further calculation of the theoretical necrosis fraction:
[0093] f(180,x) = 1-exp[-Ω(180,x)],
[0094] Used to characterize the probability of irreversible thermal damage to tissues.
[0095] Example 5: Engineering Simplification and Fast Mapping Implementation
[0096] Considering that time integration calculations on a voxel-by-voxel basis involve a large computational load in three-dimensional data, which is not conducive to engineering implementation, this invention simplifies the thermal damage calculation process under the condition that the temperature history template and Arrhenius model parameters are fixed.
[0097] Specifically, Ω(180) is expressed as the final temperature T. 180 Univariate function:
[0098] logΩ(180) = F(T 180 ).
[0099] By analyzing the (T) of multiple ROIs 180The data points (logΩ) are fitted using a natural cubic spline function to establish a mapping relationship. During runtime, it is only necessary to locate the corresponding interval based on the endpoint temperature value of the voxel and calculate the polynomial function to obtain logΩ(180), and then obtain Ω(180).
[0100] This method transforms the original calculation process, which relied on time-by-time integration, into a single-function calculation or table lookup operation, which greatly reduces computational complexity and improves system stability.
[0101] Example 6: 3D Damage Mapping and Visualization Output
[0102] Based on the calculated thermal damage integral field or its logarithmic form logΩ(180,x), a three-dimensional Arrhenius thermal damage distribution map is generated. In this embodiment, logΩ≥0 is used as the threshold condition, corresponding to the theoretical necrosis region with Ω≥1.
[0103] Three-dimensional visualization software is used to perform threshold segmentation of the damage field, generating three-dimensional segmentation results and closed surface models of the damage area, realizing intuitive display of three-dimensional tissue damage, which is used to evaluate the ablation range and ablation adequacy of microwave ablation.
[0104] Figure 2 is a schematic diagram of plotting a tissue damage field according to an embodiment of the present invention. Figure 3 is a schematic diagram of three-dimensional reconstruction of a tissue damage field according to an embodiment of the present invention.
[0105] The present invention also provides a microwave ablation temperature history reconstruction and three-dimensional Arrhenius lesion mapping system based on the endpoint temperature constraint of CT thermal imaging, including a memory, a processor, and computer program instructions stored in the memory and executable by the processor. When the processor executes the computer program instructions, it can implement the steps of the method described above.
[0106] The present invention also provides a computer-readable storage medium having stored thereon computer program instructions that can be executed by a processor, wherein when the processor executes the computer program instructions, it can implement the steps of the method described above.
[0107] The above are preferred embodiments of the present invention. Any changes made to the technical solution of the present invention that do not exceed the scope of the technical solution of the present invention shall fall within the protection scope of the present invention.
Claims
1. A method for reconstructing the thermal ablation temperature history and creating three-dimensional damage maps based on the endpoint temperature constraint of CT thermal imaging, characterized in that, include: Acquire CT thermal imaging data at the end of thermal ablation and construct a three-dimensional endpoint temperature field of the ablation area; Based on the consistency of tissue temperature evolution under fixed ablation clinical protocols, a normalized temperature history template function is constructed. Under the condition of known initial and final temperatures, the temperature history at discrete time points in each spatial location within the ablation area is reconstructed using the temperature history template function. Based on the reconstructed temperature history, a thermal damage assessment model is introduced to perform time integration or mapping calculations to obtain the thermal damage quantification value at each spatial location. A three-dimensional tissue damage distribution map is generated based on the thermal damage quantification value and then visualized.
2. The method for reconstructing the thermal ablation temperature history and creating three-dimensional damage maps based on the endpoint temperature constraint of CT thermal imaging according to claim 1, characterized in that, The thermal ablation includes at least one of microwave ablation, radiofrequency ablation, laser ablation, or steam ablation.
3. The method for reconstructing the thermal ablation temperature history and creating three-dimensional damage maps based on the endpoint temperature constraint of CT thermal imaging according to claim 1, characterized in that, The three-dimensional endpoint temperature field is obtained by converting the Hounsfield Unit values in the CT images of the CT thermal imaging data into temperature values through a linear mapping model.
4. The method for reconstructing the thermal ablation temperature history and creating three-dimensional damage maps based on the endpoint temperature constraint of CT thermal imaging according to claim 1, characterized in that, The temperature history template function is obtained by normalizing the temperature-time curves of multiple regions of interest and using robust statistical methods.
5. The method for reconstructing the thermal ablation temperature history and creating three-dimensional damage maps based on the endpoint temperature constraint of CT thermal imaging according to claim 1, characterized in that, The temperature history reconstruction satisfies T(0) = initial temperature and T(t_end) = final temperature.
6. The method for reconstructing the thermal ablation temperature history and creating three-dimensional damage maps based on the endpoint temperature constraint of CT thermal imaging according to claim 1, characterized in that, The thermal damage assessment model includes at least one of the following: the Arrhenius tissue thermal damage model, the CEM43 thermal dose model, the temperature threshold model, or a machine learning model.
7. The method for reconstructing the thermal ablation temperature history and creating three-dimensional damage maps based on the endpoint temperature constraint of CT thermal imaging according to claim 6, characterized in that, When the thermal damage assessment model is the Arrhenius tissue thermal damage model, the thermal damage quantification value at each spatial location is the thermal damage integral value, which is further converted into the theoretical necrosis fraction. Then, a three-dimensional Arrhenius tissue damage distribution map is generated based on the thermal damage integral value or the theoretical necrosis fraction.
8. The method for reconstructing the thermal ablation temperature history and creating three-dimensional damage maps based on the endpoint temperature constraint of CT thermal imaging according to claim 1, characterized in that, It also includes pre-constructing the relationship between the thermal damage quantification value and the endpoint temperature as a mapping function or lookup table to achieve fast mapping calculation based on the endpoint temperature.
9. The method for reconstructing the thermal ablation temperature history and creating three-dimensional damage maps based on the endpoint temperature constraint of CT thermal imaging according to claim 1, characterized in that, The three-dimensional tissue damage distribution map is segmented using a preset threshold to obtain the theoretical necrosis area.
10. A computer-readable storage medium having stored thereon computer program instructions executable by a processor, wherein when the processor executes the computer program instructions, it is able to implement the steps of the method as described in any one of claims 1-9.