A method for determining ablation heat dose based on a magnetic resonance detection signal

Abstract

The present application relates to the field of tumor ablation, in particular to a kind of ablation heat metering determination method based on nuclear magnetic resonance detection signal, comprising: according to the function relationship of the effective heat conduction coefficient of tissue and relative contrast determined by the multiple sets of temperature data collected by carrying out thermal ablation to tumor model;Relative contrast is determined according to the T1 signal and T2 signal of the tumor tissue and healthy tissue of patient respectively;Heat conduction coefficient is determined according to relative contrast and function relationship;The ablation heat metering required for carrying out tumor thermal ablation to patient is determined according to heat conduction coefficient.

Description

Technical Field

[0001] This invention relates to the field of tumor ablation, and in particular to a method for determining ablation heat measurement based on nuclear magnetic resonance detection signals. Background Technology

[0002] Thermal ablation of tumors includes cryoablation and radiofrequency / microwave ablation. Tumor thermal ablation has proven effective in expanding the lesion area and improving overall survival, particularly in B16F10 melanoma and 4T1 mouse breast cancer models, achieving therapeutic efficacy through precise control of the combined cryoablation process to activate the immune response. Compared to cryoablation alone, RF heating increased the ablation area by 50%. Compared to RF heating alone, the cessation of blood perfusion during cryoablation further expanded the ablation area by reducing heat loss. A key challenge in combining cryoablation and heating lies in boundary control and matching. Current technologies lack an effective means to determine the calorimetry during thermal ablation to control the boundaries of the ablation area.

[0003] Therefore, a method for determining ablation heat measurement based on nuclear magnetic resonance detection signals is needed. Summary of the Invention

[0004] Therefore, the present invention provides a method for determining ablation heat measurement based on nuclear magnetic resonance detection signals, in an attempt to solve the problems mentioned above.

[0005] According to a first aspect of the present invention, a method for determining ablation heat measurement based on nuclear magnetic resonance detection signals is provided, comprising: determining a functional relationship between the effective thermal conductivity of tissue and relative contrast based on multiple sets of temperature data acquired by thermal ablation of a tumor model; determining the relative contrast of the patient based on the T1 and T2 signals of the tumor tissue and healthy tissue respectively; determining the thermal conductivity based on the relative contrast and the functional relationship; and determining the ablation heat measurement required for performing tumor thermal ablation on the patient based on the thermal conductivity.

[0006] Optionally, in the method according to the present invention, determining the functional relationship between the effective thermal conductivity and relative contrast of tissue based on multiple sets of temperature data acquired through thermal ablation of tumor models includes: performing MRI on multiple established tumor models to determine the T1 and T2 signals of healthy tissue and tumor tissue in each tumor model; determining the relative contrast of each tumor model based on the T1 and T2 signals of each tumor model; performing thermal ablation on the tumor by setting ablation probe and a temperature measuring probe in the tumor model, and acquiring tumor boundary temperature data and ablation probe tip temperature data during the thermal ablation process; determining the thermal conductivity of each tumor model based on the tumor boundary temperature data and ablation probe tip temperature data of each group; and determining the functional relationship by function fitting based on the thermal conductivity and relative contrast of multiple tumor models.

[0007] Alternatively, in the method according to the invention, the tumor model is adapted to be established by inoculating animal tissue with tumors.

[0008] Alternatively, in the method according to the invention, the T1 signal and the T2 signal are adapted to be determined by performing an MRI scan on the patient.

[0009] Optionally, in the method according to the invention, determining the relative contrast of each tumor model based on the T1 and T2 signals of each tumor model includes: determining the relative contrast based on the ratio of the tumor tissue signal ratio to the healthy tissue signal ratio, wherein the tumor tissue signal ratio includes the ratio of the T2 signal to the T1 signal of the tumor tissue, and the healthy tissue signal ratio includes the ratio of the T2 signal to the T1 signal of the healthy tissue.

[0010] Optionally, in the method according to the present invention, determining the thermal conductivity coefficient of each tumor model by using the tumor boundary temperature data and ablation probe tip temperature data of each group includes: substituting the tumor boundary temperature data and ablation probe tip temperature data into the heat transfer equation to determine the thermal conductivity coefficient of each tumor model.

[0011] Optionally, in the method according to the invention, determining the relative contrast of the patient based on the respective T1 and T2 signals of the patient's tumor tissue and healthy tissue includes: performing multi-point detection on the tumor tissue and healthy tissue to determine the T1 and T2 signals of multiple points in the patient's tumor tissue and the T1 and T2 signals of multiple points in the patient's healthy tissue; determining the average of multiple tumor tissue signal ratios based on the T1 and T2 signals of multiple points in the patient's tumor tissue; determining the average of multiple healthy tissue signal ratios based on the T1 and T2 signals of multiple points in the patient's healthy tissue; and determining the relative contrast based on the average of the multiple tumor tissue signal ratios and the average of the multiple healthy tissue signal ratios.

[0012] Optionally, in the method according to the invention, determining the ablation heat metering required for performing tumor thermal ablation on the patient based on the thermal conductivity coefficient includes: substituting the thermal conductivity coefficient or thermal conductivity correction coefficient into the biological heat transfer equation to determine the ablation heat metering required for performing tumor thermal ablation.

[0013] According to a second aspect of the present invention, a computing device is provided, comprising: one or more processors; a memory; and one or more means, said one or more means including instructions for a method for determining ablation heat measurement based on nuclear magnetic resonance detection signals.

[0014] According to a third aspect of the present invention, a computer-readable storage medium is provided for storing one or more programs, the one or more programs including instructions that, when executed by a computing device, cause the computing device to perform a method for determining ablation heat measurement based on nuclear magnetic resonance detection signals.

[0015] This invention utilizes the signal characteristics of T1 and T2 signals in preoperative MRI scans. It examines the changes in the physical properties of tumor tissue moisture before and after ablation with temperature variations. Through training with multiple animal models, the relationship between the effective thermal conductivity of tissue and the relative contrast signal was established. This relationship was then incorporated into the biological heat transfer equation to rapidly calculate the calorific value required to reach the target ablation temperature. This invention provides a method for personalized, precise thermophysical minimally invasive ablation surgical planning, which will benefit clinical surgical planning and improve surgical efficiency. Attached Figure Description

[0016] To achieve the foregoing and related objectives, certain illustrative aspects are described herein in conjunction with the following description and accompanying drawings. These aspects indicate various ways in which the principles disclosed herein may be practiced, and all aspects and their equivalents are intended to fall within the scope of the claimed subject matter. The foregoing and other objectives, features, and advantages of this disclosure will become more apparent from the following detailed description, taken in conjunction with the accompanying drawings. Throughout this disclosure, the same reference numerals generally refer to the same parts or elements.

[0017] Figure 1 A schematic diagram of an ablation heat measurement determination method 100 based on nuclear magnetic resonance detection signals according to an exemplary embodiment of the present invention is shown.

[0018] Figure 2 A schematic diagram illustrating the determination of a functional relationship according to an exemplary embodiment of the present invention is shown;

[0019] Figure 3 A schematic diagram of setting up an ablation probe and a temperature probe on a tumor model according to an exemplary embodiment of the present invention is shown;

[0020] Figure 4 A schematic diagram illustrating magnetic resonance imaging of tumor tissue and healthy tissue according to an exemplary embodiment of the present invention is shown.

[0021] Figure 5 A schematic diagram of the temperature profile for ablation of a tumor model according to an exemplary embodiment of the present invention is shown. Detailed Implementation

[0022] Exemplary embodiments of the present disclosure will now be described in more detail with reference to the accompanying drawings. While exemplary embodiments of the present disclosure are shown in the drawings, it should be understood that the present disclosure may be implemented in various forms and should not be limited to the embodiments set forth herein. Rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the scope of the disclosure to those skilled in the art. The same reference numerals generally refer to the same parts or elements.

[0023] Thermal ablation of tumors includes cryoablation and radiofrequency / microwave ablation. Tumor thermal ablation has proven effective in expanding the lesion area and improving overall survival, particularly in B16F10 melanoma and 4T1 mouse breast cancer models, achieving therapeutic efficacy through precise control of the combined cryoablation process to activate the immune response. Compared to cryoablation alone, RF heating increased the ablation area by 50%. Compared to RF heating alone, the cessation of blood perfusion during cryoablation further expanded the ablation area by reducing heat loss. A key challenge in combining cryoablation and heating lies in boundary control and matching.

[0024] However, complex variations in thermal and physiological properties can pose challenges to accurate prediction. For example, the thermal conductivity of human breast tumors (based on experimental measurements) may vary between 0.28 W / m / K and 0.58 W / m / K, while the blood perfusion rate may be as low as 1.956 kg / s / m. 3 Up to 5.968 kg / s / m 3 The specific heat capacity varies between these values. Mechanistically, water content has a significant impact on thermal properties. In low-water-content tissues (below 70%), the specific heat capacity increases exponentially with water content, while in high-water-content tissues (above 70%), the specific heat capacity increases linearly with water content. Those skilled in the art have considered that incorporating individual water content into personalized modeling may help improve the accuracy of calculations.

[0025] Given that existing technologies cannot quickly and accurately predict the required thermal dose for minimally invasive thermal ablation surgery and formulate precise surgical plans, this invention proposes a method for determining ablation thermal dosage based on nuclear magnetic resonance detection signals.

[0026] In magnetic resonance imaging (MRI), T1 and T2 signals are two important parameters used to describe the relaxation time of hydrogen protons. During MRI, when a radio frequency pulse is emitted at a larmor frequency, some hydrogen protons absorb energy from the RF pulse and undergo energy level transitions. After the RF pulse stops, the hydrogen proton magnetic moments are affected by the static magnetic field, gradually releasing the absorbed energy and returning to their original low-energy-level equilibrium state. This process is called relaxation. During relaxation, two magnetic vector changes occur simultaneously and independently: first, the longitudinal magnetization vector in the Z-axis direction recovers from small to large; second, the transverse magnetization vector in the XY plane decays from large to small. Simultaneously, the hydrogen proton magnetic moments that were initially in phase become directionally discrete, leading to phase loss.

[0027] During longitudinal relaxation, hydrogen protons release the energy they have absorbed, transferring it to the surrounding structure or lattice. This phenomenon causes the magnetization vector, which has flipped to the XY plane, to gradually recover to its longitudinal position. The recovery of the longitudinal magnetization vector is an exponential process, often described by a constant, namely the longitudinal relaxation time (i.e., T1 signal, T1 relaxation time, T1 time, T1). The T1 time (T1 signal) refers to the time required for the longitudinal magnetization vector to recover to 63% of its initial value. Because the T1 time (T1 signal) is related to the exchange of energy between hydrogen protons and the surrounding structure (lattice), it is also called the spin-lattice relaxation time.

[0028] The small magnetic moments of hydrogen protons flipped onto the XY plane are initially in phase, forming a transverse magnetization vector. Subsequently, phase divergence occurs, and the transverse magnetization vector decreases accordingly. The reason for the decay and disappearance of the transverse magnetization vector is that energy exchange occurs between adjacent nuclei during random motion; this phenomenon is called spin-spin relaxation. The decay of the transverse magnetization vector is also an exponential process, often described by a constant, namely the transverse relaxation time (i.e., T2 signal, T2 relaxation time, T2 time, T2). T2 time (T2 signal) refers to the time required for the transverse magnetization vector to decrease from its maximum value to 37% of its original value.

[0029] Considering the prevalence of MRI in preoperative examination of tumor patients, the main influencing factor of MRI T1 and T2 signals is the water content in the tissue. Furthermore, under thermophysical effects, the activity of water molecules and the water content will change accordingly with the change of temperature field. Therefore, this invention proposes a method for determining ablation heat measurement based on MRI detection signals to achieve precise and rapid planning of thermophysical ablation surgery, formulate reasonable surgical plans, and improve clinical surgical efficiency.

[0030] Furthermore, this invention proposes a personalized thermal conductivity calibration method based on MRI data, applied to subcutaneous VX2 tumors in a rabbit model. During freezing, the model-predicted ice ball was compared with the observed ice ball, demonstrating that this method facilitates precise thermal dosing planning in clinical applications.

[0031] Figure 1 A schematic diagram of an ablation heat measurement determination method 100 based on nuclear magnetic resonance detection signals according to an exemplary embodiment of the present invention is shown. Figure 1 As shown, method 100 first performs step 110, which determines the functional relationship between the effective thermal conductivity of the tissue and the relative contrast based on multiple sets of temperature data collected from the thermal ablation of the tumor model.

[0032] Figure 2 A schematic diagram illustrating the determination of functional relationships according to an exemplary embodiment of the present invention is shown. Figure 2 As shown, a tumor model is first established, specifically multiple tumor models can be established; each tumor model is established by inoculating animal tissue with tumor cells. The tumor model includes healthy tissue and tumor tissue. The tumor tissue in the tumor model includes any type of solid tumor, and the normal tissue includes any type of normal tissue such as muscle, fat, and organ tissue. According to one embodiment of the present invention, the tumor model constructed by the present invention can specifically be implemented as an animal tumor model, which makes material acquisition more convenient and facilitates the implementation of the ablation heat measurement determination method of the present invention.

[0033] Subsequently, MRI scans were performed on the tumor model to determine the T1 and T2 signals of healthy tissue and the T1 and T2 signals of tumor tissue. T1 and T2 signals were suitable for determination using MRI scans of patients.

[0034] Subsequently, the relative contrast of each tumor model group is determined based on the T1 and T2 signals, i.e., Rcon(n), representing the relative contrast of the nth tumor model group. The relative contrast can be specifically realized as the ratio of the tumor tissue signal ratio to the healthy tissue signal ratio. The tumor tissue signal ratio includes the ratio of the T2 signal to the T1 signal of the tumor tissue; the healthy tissue signal ratio includes the ratio of the T2 signal to the T1 signal of the healthy tissue.

[0035] Subsequently, ablation probes and thermometric probes were placed in the tumor model. The ablation probes penetrated deep into the tumor, potentially located in the center, while the thermometric probes were positioned at the tumor boundaries.

[0036] Figure 3 A schematic diagram illustrating the placement of an ablation probe and a thermometric probe on a tumor model according to an exemplary embodiment of the present invention is shown. Figure 3As shown, the ablation probe can be either a high-temperature ablation probe or a low-temperature ablation probe. When ablating tumor tissue, it can be any form of thermal ablation, cryoablation, or a combination of thermal and cryoablation.

[0037] A temperature sensor is installed at the tip of the ablation probe, and a temperature-sensing probe is also positioned at the boundary between the tumor tissue and healthy tissue to detect the ablation temperature of the target. The temperature detection process is mainly to read the temperature at the corresponding ablation point, which is then used to solve the thermal conductivity coefficient using the biological heat transfer equation. Multiple temperature-sensing probes can be deployed for more precise measurements.

[0038] like Figure 3 As shown, the tumor was thermally ablated using an ablation probe in a tumor model, and tumor boundary temperature data and ablation probe tip temperature data were collected during the thermal ablation process. Both the tumor boundary temperature data and the ablation probe tip temperature data included multiple temperature values ​​during the ablation process.

[0039] Back Figure 2 ,like Figure 2 As shown, the tumor boundary temperature data and ablation probe tip temperature data were then substituted into the heat transfer equation to determine the thermal conductivity coefficient of each tumor model, i.e., K(n), representing the thermal conductivity coefficient of the nth animal model. The heat transfer equation can be specifically implemented as the Pennes biological heat transfer equation, whose expression is:

[0040]

[0041] Where ρ is mass density, c is specific heat capacity, T is tissue temperature, and t is time. It is a vector differential operator, where k is thermal conductivity and ω is the thermal conductivity. b It is the blood perfusion rate, ρ b c represents the mass density of blood. b T represents the specific heat capacity of blood. b Q represents the temperature of the blood. m This is for metabolic heat production. During the heating process, metabolic heat production can be neglected: Q m =0. According to one embodiment of the present invention, the thermal conductivity coefficient can also be obtained by measuring the thermal conductivity coefficient.

[0042] According to one embodiment of the present invention, the functional relationship can be determined based on the thermal conductivity coefficient and relative contrast of each group of tumor models, such as by using data fitting to determine the functional relationship.

[0043] According to one embodiment of the present invention, the present invention further corrects the thermal conductivity coefficient of each group of tumor models based on the thermal conductivity coefficient, and determines the thermal conductivity correction coefficient, i.e., α(n), which represents the thermal conductivity correction coefficient of the nth group of tumor models.

[0044] According to one embodiment of the present invention, the correspondence between the thermal conductivity correction factor and the thermal conductivity is as follows:

[0045] K = α * K water +(1-α)*K dehy

[0046] Where K is the thermal conductivity coefficient, α is the thermal conductivity correction coefficient, and K water K is the thermal conductivity coefficient of water. dehy is the thermal conductivity of anhydrous materials.

[0047] Finally, the functional relationship between the heat conduction correction coefficient and the relative contrast is determined based on the heat conduction correction coefficient and the relative contrast of multiple tumor models. According to one embodiment of the present invention, data fitting can be performed based on the heat conduction correction coefficient and the relative contrast of multiple tumor models to determine the functional relationship, which can specifically be an exponential relationship or a polynomial relationship.

[0048] Subsequently, step 120 is performed to determine the relative contrast of the patient based on the T1 and T2 signals of the patient's tumor tissue and healthy tissue, respectively.

[0049] Figure 4 A schematic diagram illustrating magnetic resonance imaging (MRI) of tumor tissue and healthy tissue according to an exemplary embodiment of the present invention is shown, such as... Figure 4 As shown, multiple points were detected in tumor tissue and healthy tissue to determine the T1 and T2 signals at multiple points in the patient's tumor tissue and the T1 and T2 signals at multiple points in the patient's healthy tissue.

[0050] According to one embodiment of the present invention, multi-point detection can be performed on tumor tissue and healthy tissue respectively, such as detecting x points, to obtain the signal ratio of x tumor tissues, and the average value is calculated, as shown in the following formula:

[0051]

[0052] A x Let be the average signal ratio of x tumor tissues, and i be the i-th point among the x points used to detect tumor tissues or healthy tissues;

[0053] The signal ratios of x healthy tissues are obtained, and the average value is calculated, as shown in the following formula:

[0054]

[0055] B x Let be the average signal ratio of x healthy tissues, and i be the i-th point among the x points used to detect tumor tissue or healthy tissue;

[0056] Subsequently, the relative contrast was calculated based on the signal ratio of tumor tissue and the signal ratio of healthy tissue, as shown in the following formula:

[0057]

[0058] Subsequently, step 130 is executed to determine the thermal conductivity coefficient based on the relative contrast and the functional relationship. Specifically, the thermal conductivity coefficient can be determined by substituting the relative contrast into the functional relationship.

[0059] According to one embodiment of the present invention, the thermal conductivity coefficient or thermal conductivity correction coefficient corresponding to the relative contrast can be determined to calculate the ablation heat metering.

[0060] Finally, step 140 is performed to determine the ablation heat dose required for tumor thermal ablation on the patient based on the thermal conductivity coefficient. When determining the ablation heat dose, the thermal conductivity coefficient or thermal conductivity correction coefficient can be substituted into the biological heat transfer equation to determine the ablation heat dose required for tumor thermal ablation. According to one embodiment of the present invention, the ablation heat dose may be related to the volume of the tumor tissue.

[0061] Figure 5 A schematic diagram of the temperature profile for ablation of a tumor model according to an exemplary embodiment of the present invention is shown. Figure 5 As shown, tumor models from seven rabbit groups (ag) were ablated, and temperature curves a)-g) were obtained. The thermal conductivity coefficient (h) was determined by fitting the obtained temperature data. Based on the determined thermal conductivity coefficient, three tumor models from the control group (ik) were ablated, yielding temperature curves i)-h). Temperature curves i)-h) are basically consistent with temperature curves a)-g) of the ag group, indicating that the ablation thermal dosing determination method based on nuclear magnetic resonance detection signals of this invention can quickly and accurately achieve personalized ablation thermal dosage surgical planning.

[0062] This invention relates to a method for determining ablation thermal dosage based on nuclear magnetic resonance (NMR) detection signals. Specifically, it utilizes MRI to acquire T1 and T2 signals of the tumor tissue to be ablated and the surrounding healthy tissue. Using healthy tissue as a baseline, personalized tumor tissue thermal parameters are obtained based on the comparison of T1 / T2 signals between the tumor tissue and healthy tissue, thereby accurately calculating the thermal dose required for target ablation. The specific steps include: acquiring the T1 and T2 signals of the ablation tissue and normal tissue; calculating the relative contrast Rcon between the tumor tissue and normal tissue based on the T2 and T1 signals of the ablation tissue and normal tissue; establishing a functional relationship between the effective thermal conductivity K of the tissue and the relative contrast Rcon through training multiple sets of models; and substituting this functional relationship into the biological heat transfer equation to solve for the precise thermal dose required to ablate the area to the target temperature. Using this invention, the thermal dose of ablation can be accurately estimated based on preoperative MRI signals, thereby guiding clinical surgical planning, facilitating precise thermophysical treatment, and improving clinical treatment outcomes.

[0063] This invention utilizes the signal characteristics of T1 and T2 signals in preoperative MRI, and the properties of tumor tissue moisture change with temperature before and after ablation. Through training with multiple animal experimental models, the relationship between the effective thermal conductivity of tissue and MRI signals was established. This relationship was then incorporated into the biological heat transfer equation to rapidly calculate the calorific value required to ablate to the target temperature. This invention will provide a method for personalized, precise thermophysical minimally invasive ablation surgical planning, which will benefit clinical surgical planning and improve surgical efficiency.

[0064] It should be noted that the storage medium (computer-readable medium) mentioned above in this application may be a computer-readable signal medium or a non-transitory computer-readable storage medium, or any combination of the two. A non-transitory computer-readable storage medium may be, for example,, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination thereof. More specific examples of a non-transitory computer-readable storage medium may include, but are not limited to: an electrical connection having one or more wires, a portable computer disk, a hard disk, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fiber, portable compact disk read-only memory (CD-ROM), optical storage device, magnetic storage device, or any suitable combination thereof.

[0065] In this application, a non-transitory computer-readable storage medium can be any tangible medium containing or storing a program that can be used by or in connection with an instruction execution system, apparatus, or device. In this application, a computer-readable signal medium can include a data signal propagated in baseband or as part of a carrier wave, carrying computer-readable program code. Such propagated data signals can take various forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination thereof. A computer-readable signal medium can also be any computer-readable medium other than a non-transitory computer-readable storage medium, which can send, propagate, or transmit a program for use by or in connection with an instruction execution system, apparatus, or device. The program code contained on the computer-readable medium can be transmitted using any suitable medium, including but not limited to: wires, optical cables, RF (radio frequency), etc., or any suitable combination thereof.

[0066] The aforementioned computer-readable medium may be included in the aforementioned electronic device; or it may exist independently and not assembled into the electronic device.

[0067] The above description is merely a partial embodiment of this application and an explanation of the technical principles employed. Those skilled in the art should understand that the scope of disclosure in this application is not limited to technical solutions formed by specific combinations of the above-described technical features, but should also cover other technical solutions formed by arbitrary combinations of the above-described technical features or their equivalents without departing from the above-described concept. For example, technical solutions formed by substituting the above features with (but not limited to) technical features with similar functions disclosed in this application.

[0068] Furthermore, while the operations are described in a specific order, this should not be construed as requiring these operations to be performed in the specific order shown or in sequential order. Multitasking and parallel processing may be advantageous in certain environments. Similarly, while several specific implementation details are included in the above discussion, these should not be construed as limiting the scope of this application. Certain features described in the context of individual embodiments may also be implemented in combination in a single embodiment. Conversely, various features described in the context of a single embodiment may also be implemented individually or in any suitable sub-combination in multiple embodiments.

[0069] Although the subject matter has been described using language specific to structural features and / or methodological logic, it should be understood that the subject matter defined in the appended claims is not necessarily limited to the specific features or actions described above. Rather, the specific features and actions described above are merely illustrative examples of implementing the claims.

Claims

1. A method for determining ablation heat measurement based on nuclear magnetic resonance detection signals, the method comprising: The functional relationship between thermal conductivity coefficient and relative contrast was determined based on multiple sets of temperature data collected from the thermal ablation of the tumor model. The relative contrast of the patient was determined based on the T1 and T2 signals of the tumor tissue and healthy tissue, respectively. The patient's thermal conductivity coefficient was determined based on the patient's relative contrast and functional relationship; The ablation heat dose required for tumor thermal ablation is determined based on the patient's thermal conductivity. The functional relationship between thermal conductivity and relative contrast was determined based on multiple sets of temperature data acquired through thermal ablation of tumor models, including: Magnetic resonance imaging was performed on the established tumor models to determine the T1 and T2 signals of healthy tissues and tumor tissues in each tumor model. The relative contrast of each tumor model was determined based on the T1 and T2 signals of each tumor model. The tumor was thermally ablated by setting up ablation probes and temperature probes in the tumor model, and the tumor boundary temperature data and ablation probe tip temperature data were collected during the thermal ablation process. The thermal conductivity coefficient of each tumor model was determined by using the tumor boundary temperature data and ablation probe tip temperature data for each group. The functional relationship was determined by fitting the function with the thermal conductivity coefficient and relative contrast of multiple tumor models. The determination of the relative contrast of each tumor model based on the T1 and T2 signals of each tumor model includes: The relative contrast is determined based on the ratio of the signal ratio of tumor tissue to the signal ratio of healthy tissue. The signal ratio of tumor tissue includes the ratio of T2 signal to T1 signal of tumor tissue, and the signal ratio of healthy tissue includes the ratio of T2 signal to T1 signal of healthy tissue.

2. The method as described in claim 1, wherein, The tumor model is suitable for establishment by inoculating animal tissues with tumors.

3. The method as described in claim 1 or 2, wherein, The T1 and T2 signals are suitable for determination by performing MRI scans on the patient.

4. The method of claim 1, wherein, The process of determining the thermal conductivity coefficient of each tumor model by using tumor boundary temperature data and ablation probe tip temperature data for each group includes: Tumor boundary temperature data and ablation probe tip temperature data were input into the heat transfer equation to determine the heat conduction coefficient of each tumor model.

5. The method of claim 1, wherein, Determining the relative contrast of a patient based on the T1 and T2 signals of their tumor and healthy tissues includes: Multiple points were detected in tumor tissue and healthy tissue to determine the T1 and T2 signals at multiple points in the patient's tumor tissue and the T1 and T2 signals at multiple points in the patient's healthy tissue. The average signal ratio of multiple tumor tissues was determined based on the T1 and T2 signals of multiple points in the patient's tumor tissue. The average value of the signal ratio of multiple healthy tissues was determined based on the T1 and T2 signals of multiple points in the patient's healthy tissues; The relative contrast was determined based on the average signal ratio of multiple tumor tissues and the average signal ratio of multiple healthy tissues.

6. The method of claim 1, wherein, The determination of the ablation heat dose required for tumor thermal ablation based on the patient's thermal conductivity includes: By incorporating the patient's thermal conductivity coefficient into the biological heat transfer equation, the required ablation heat quantification for tumor thermal ablation is determined.

7. A computing device, characterized in that, include: One or more processors; Memory; as well as One or more means, the one or more means comprising instructions for performing the method according to any one of claims 1-6.

8. A computer-readable storage medium for storing one or more programs, characterized in that, The one or more programs include instructions that, when executed by a computing device, cause the computing device to perform the method according to any one of claims 1-6.

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