Ablation heat metering determination method based on nuclear magnetic resonance detection signal

Abstract

The invention relates to the field of tumor ablation, in particular to an ablation heat metering determination method based on a nuclear magnetic resonance detection signal, which comprises the following steps: determining a function relationship between an effective heat conductivity coefficient and a relative contrast ratio of a tissue according to multiple groups of temperature data acquired by performing thermal ablation on a tumor model; determining the relative contrast according to the T1 signal and the T2 signal of the tumor tissue and the healthy tissue of the patient; determining a heat conduction coefficient according to the relative contrast and the function relationship; and according to the heat conduction coefficient, determining the ablation heat quantity required for performing tumor thermal ablation on the patient.

Description

Technical Field

[0001] The present invention relates to the field of tumor ablation, and particularly to a method for determining ablation heat dosage based on nuclear magnetic resonance detection signals. Background Art

[0002] Thermal ablation of tumors includes cryogenic ablation by freezing and heating ablation by radiofrequency and microwave. Thermal ablation of tumors has been proven effective in expanding the damaged area and improving the overall survival rate. Especially in the B16F10 melanoma and 4T1 murine breast cancer models, the efficacy is achieved by precisely controlling the combined cold and heat ablation process to activate the immune response. Compared with the single freezing protocol, RF heating increased the ablation area by 50%. Compared with the single RF heating protocol, the cessation of blood perfusion during the freezing process further expanded the ablation area by reducing heat dissipation. The key issues in the combination of freezing and heating lie in boundary control and matching. There is a lack of an effective means in the prior art to determine the heat dosage during thermal ablation, thereby controlling the boundary of the ablation area.

[0003] Therefore, a method for determining ablation heat dosage 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 dosage based on nuclear magnetic resonance detection signals in an attempt to solve the problems existing above.

[0005] According to a first aspect of the present invention, there is provided a method for determining ablation heat dosage based on nuclear magnetic resonance detection signals, including: determining the functional relationship between the tissue effective thermal conductivity and the relative contrast according to multiple groups of temperature data collected during the thermal ablation of a tumor model; determining the relative contrast of a patient according to the T1 signal and T2 signal of the patient's tumor tissue and healthy tissue respectively; determining the thermal conductivity according to the relative contrast and the functional relationship; determining the ablation heat dosage required for performing tumor thermal ablation on the patient according to the thermal conductivity.

[0006] Optionally, in the method according to the present invention, determining the functional relationship between the tissue effective thermal conductivity and the relative contrast according to multiple groups of temperature data collected during the thermal ablation of a tumor model includes: performing nuclear magnetic resonance detection on multiple established tumor models to determine the T1 signal and T2 signal of the healthy tissue of each group of tumor models, and the T1 signal and T2 signal of the tumor tissue; determining the relative contrast of each group of tumor models according to the T1 signal and T2 signal of each group of tumor models; performing thermal ablation on the tumor by setting an ablation probe and a temperature measurement probe in the tumor model, and collecting the tumor boundary temperature data and the ablation probe tip temperature data during the thermal ablation process; determining the thermal conductivity of each group of tumor models according to the tumor boundary temperature data and the ablation probe tip temperature data of each group; performing function fitting according to the thermal conductivity and relative contrast of multiple groups of tumor models to determine the functional relationship.

[0007] Optionally, in the method according to the present invention, the tumor model is suitable for being established by inoculating tumors into animal tissues.

[0008] Optionally, in the method according to the present invention, the T1 signal and the T2 signal are suitable for being determined by performing nuclear magnetic resonance detection on the patient.

[0009] Optionally, in the method according to the present invention, determining the relative contrast of each group of tumor models according to the T1 signal and the T2 signal of each group of tumor models includes: determining the relative contrast according to the ratio of the tumor tissue signal ratio to the healthy tissue signal ratio, where 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 group of tumor models from the tumor boundary temperature data and the ablation probe tip temperature data of each group includes: substituting the tumor boundary temperature data and the ablation probe tip temperature data into the heat transfer equation to determine the thermal conductivity coefficient of each group of tumor models.

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

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

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

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

[0015] The present invention utilizes the signal characteristics of T1 signals and T2 signals in preoperative nuclear magnetic resonance detection signals. Before and after ablation, the physical properties of water in tumor tissues will change with temperature. Through training with multiple groups of animal experimental models, the relationship between the effective thermal conductivity of tissues and the relative contrast signal is established. Then, the thermal conductivity relationship is substituted into the bioheat transfer equation to quickly calculate the heat dosage required to ablate to the target temperature. The present invention will provide a method for surgical planning of personalized and precise thermophysical minimally invasive ablation, which is beneficial to guiding clinical surgical planning and improving surgical efficiency. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] To achieve the above and related purposes, certain illustrative aspects are described herein in conjunction with the following description and drawings, which indicate various ways in which the principles disclosed herein can be practiced, and all aspects and their equivalent aspects are intended to fall within the scope of the claimed subject matter. The above and other objects, features, and advantages of the present disclosure will become more apparent by reading the following detailed description in conjunction with the drawings. Throughout the present disclosure, like reference numerals generally refer to like components or elements.

[0017] Figure 1 FIG. shows a schematic diagram of a method 100 for determining ablation heat dosage based on nuclear magnetic resonance detection signals according to an exemplary embodiment of the present invention;

[0018] Figure 2 FIG. shows a schematic diagram of determining a functional relationship according to an exemplary embodiment of the present invention;

[0019] Figure 3 FIG. shows a schematic diagram of setting an ablation probe and a temperature measurement probe for a tumor model according to an exemplary embodiment of the present invention;

[0020] Figure 4 FIG. shows a schematic diagram of performing nuclear magnetic resonance detection on tumor tissues and healthy tissues according to an exemplary embodiment of the present invention;

[0021] Figure 5 FIG. shows a schematic diagram of a temperature curve of ablating a tumor model according to an exemplary embodiment of the present invention. DETAILED DESCRIPTION

[0022] Exemplary embodiments of the present disclosure will be described in more detail below with reference to the accompanying drawings. Although the exemplary embodiments of the present disclosure are shown in the drawings, it should be understood that the present disclosure can be implemented in various forms and should not be limited by the embodiments set forth herein. On the contrary, these embodiments are provided so that the present disclosure can be more thoroughly understood and the scope of the present disclosure can be completely conveyed to those skilled in the art. The same reference numerals generally refer to the same components or elements.

[0023] Thermal ablation of tumors includes cryogenic ablation and heating ablation using radio frequency (RF) and microwave. Thermal ablation of tumors has been shown to be effective in expanding the damaged area and improving overall survival rate, especially in B16F10 melanoma and 4T1 murine breast cancer models, by precisely controlling the combined cold and heat ablation process to activate the immune response for therapeutic effect. Compared with the cryo-alone protocol, RF heating increased the ablation area by 50%. Compared with the RF heating-alone protocol, the cessation of blood perfusion during cryoablation further enlarged the ablation area by reducing heat dissipation. The key issues in combining cryoablation and heating are boundary control and matching.

[0024] However, complex thermal and physiological property changes may pose challenges to accurate prediction. For example, the thermal conductivity of human breast tumors (measured experimentally) may vary between 0.28 W / m / K and 0.58 W / m / K, while the blood perfusion rate may vary between 1.956 kg / s / m 3 and 5.968 kg / s / m 3 Between. Mechanistically, water content has a significant impact on thermal properties. In tissues with low water content (below 70%), the specific heat capacity increases exponentially with water content, while in tissues with high water content (above 70%), the specific heat capacity increases linearly with water content. The inventors of the present invention considered that incorporating individual water content into personalized modeling might help improve the accuracy of calculations.

[0025] In view of the fact that the prior art cannot quickly and accurately predict the thermal dose required for minimally invasive thermal ablation surgery and formulate a precise surgical planning scheme, the present invention proposes a method for determining ablation thermal dose based on nuclear magnetic resonance detection signals.

[0026] In nuclear magnetic resonance (MRI), T1 signal and T2 signal are two important parameters that can be used to describe the relaxation time of hydrogen protons. When performing nuclear magnetic resonance detection, when the radiofrequency pulse is emitted at the Larmor frequency, some hydrogen protons absorb the energy of the RF pulse and undergo energy level transitions. After the RF pulse stops, the hydrogen proton magnetic moment is affected by the static magnetic field, gradually releases the absorbed energy, and returns to the low-energy equilibrium state at rest originally. This process is called relaxation. During the relaxation process, two aspects of magnetic vector changes occur simultaneously and independently: one is that the longitudinal magnetization vector in the Z-axis direction recovers from small to large; the other is that the transverse magnetization vector in the XY plane decays from large to small. At the same time, the magnetic moments of hydrogen protons with instantaneously consistent phases become directionally discrete, which leads to dephasing.

[0027] During the longitudinal relaxation process, hydrogen protons release the energy they absorb and transfer it to the surrounding tissues or lattices. This phenomenon causes the magnetization vector flipped to the XY plane to gradually recover longitudinally. The recovery of the longitudinal magnetization vector is an exponential process, and a constant, namely the longitudinal relaxation time (i.e., T1 signal, T1 relaxation time, T1 time, T1), is often used to describe it. The T1 time (T1 signal) refers to the time required for the longitudinal magnetization vector to recover to 63% of its initial value. Since the T1 time (T1 signal) is related to the exchange of energy between hydrogen protons and the surrounding tissues (lattices), it is also called the spin-lattice relaxation time.

[0028] The small magnetic moments of hydrogen protons flipped to the XY plane are initially in phase and form a transverse magnetization vector. Subsequently, phase dispersion occurs, and the transverse magnetization vector also becomes smaller accordingly. The reasons for the decay and disappearance of the transverse magnetization vector are that adjacent atomic nuclei exchange energy during random motion, and this phenomenon is called spin-spin relaxation. The decay of the transverse magnetization vector is also an exponential process, and a constant, namely the transverse relaxation time (i.e., T2 signal, T2 relaxation time, T2 time, T2), is often used to describe it. The T2 time (T2 signal) refers to the time required for the transverse magnetization vector to decrease from the maximum value to 37% of it.

[0029] Considering the universality of MRI in the preoperative detection of tumor patients, the main influencing factors of the T1 and T2 signals of MRI are the water content in tissues. And under the thermophysical action, with the change of the temperature field, the activity and water content of water molecules will change accordingly. Therefore, based on this characteristic of tissues, the present invention proposes a method for determining ablation heat measurement based on nuclear magnetic resonance detection signals to achieve precise and rapid planning of thermophysical ablation surgery, formulate a reasonable surgical plan, and improve the efficiency of clinical surgery.

[0030] Further, the present invention also proposes a personalized thermal conductivity calibration method based on MRI data, which is applied to subcutaneous VX2 tumors in a rabbit model. During the freezing process, the ice ball predicted by the model is compared with the observed ice ball, demonstrating that this method helps to accurately plan the thermal dose in clinical applications.

[0031] Figure 1 FIG. shows a schematic diagram of a method 100 for determining ablation thermal dose based on nuclear magnetic resonance detection signals according to an exemplary embodiment of the present invention. As Figure 1 shown, the method 100 first performs step 110 to determine the functional relationship between the tissue effective thermal conductivity and the relative contrast based on multiple sets of temperature data collected from thermal ablation of the tumor model.

[0032] Figure 2 FIG. shows a schematic diagram of determining the functional relationship according to an exemplary embodiment of the present invention. As Figure 2 shown, first, a tumor model is established. Specifically, multiple sets of tumor models can be established; each set of tumor models can be established by inoculating tumors into animal tissues. The tumor model includes healthy tissue and tumor tissue. The tumor tissue in the tumor model includes any one of solid tumors, and the normal tissue includes any one of normal tissues such as muscle, fat, and organ tissues. According to an embodiment of the present invention, the tumor model constructed by the present invention can be specifically implemented as an animal tumor model, which is more convenient for material collection and facilitates the implementation of the method for determining ablation thermal dose of the present invention.

[0033] Subsequently, nuclear magnetic resonance detection is performed on the tumor model to determine the T1 signal and T2 signal of the healthy tissue, as well as the T1 signal and T2 signal of the tumor tissue. The T1 signal and T2 signal are suitable for being determined by performing nuclear magnetic resonance detection on the patient.

[0034] Subsequently, the relative contrast of each set of tumor models, that is, Rcon(n), representing the relative contrast of the nth set of tumor models, is determined according to the T1 signal and T2 signal of each set of tumor models. The relative contrast can be specifically implemented 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, an ablation probe and a temperature measurement probe are set in the tumor model. Among them, the ablation probe penetrates into the tumor and can be located in the middle part of the tumor, and the temperature measurement probe is located at the tumor boundary.

[0036] Figure 3 FIG. shows a schematic diagram of setting an ablation probe and a temperature measurement probe in the tumor model according to an exemplary embodiment of the present invention. As Figure 3As shown, the ablation probe can be specifically implemented as a high-temperature ablation or a cryoablation probe. When ablating tumor tissue, the ablation thermal dose preoperative planning method according to claims 1-10 is characterized in that it can be any form of thermal ablation, or cryoablation, or a combination of thermal ablation and cryoablation.

[0037] A temperature sensor is provided at the tip of the ablation probe. At the same time, a temperature measurement probe is arranged at the boundary between the tumor tissue and the healthy tissue to detect the ablation temperature of the target. The temperature detection process is mainly to read the temperature of the corresponding ablation point, so as to substitute it into the bioheat transfer equation to solve for the thermal conductivity. When the temperature measurement probe measures the temperature, it can also be arranged at multiple points to achieve more accurate measurement.

[0038] As Figure 3 shown, heat ablation of the tumor is performed according to the ablation probe in the tumor model, and tumor boundary temperature data and ablation probe tip temperature data are collected during the heat ablation process. Both the tumor boundary temperature data and the ablation probe tip temperature data include multiple temperature values during the ablation process.

[0039] Return to Figure 2 , as Figure 2 shown, subsequently, the tumor boundary temperature data and the ablation probe tip temperature data are substituted into the heat transfer equation to determine the thermal conductivity of each group of tumor models, that is, K(n), which represents the thermal conductivity of the nth group of animal models. The heat transfer equation can be specifically implemented as the Pennes bioheat transfer equation, and its expression is:

[0040]

[0041] where ρ is the mass density, c is the specific heat capacity, T is the tissue temperature, t is the time, is the vector differential operator, k is the thermal conductivity, ω b is the blood perfusion rate, ρ b represents the mass density of the blood, c b represents the specific heat capacity of the blood, T b represents the temperature of the blood, Q m is the metabolic heat generation. During the heating process, the metabolic heat generation can be ignored: Q m = 0. According to an embodiment of the present invention, the thermal conductivity can also be detected by a thermal conductivity measuring instrument.

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

[0043] According to an embodiment of the present invention, the present invention also corrects the thermal conductivity according to the thermal conductivity for each group of tumor models to determine the thermal conduction correction coefficient, that is, α(n), which represents the thermal conduction correction coefficient of the nth group of tumor models.

[0044] According to an embodiment of the present invention, the corresponding relationship between the thermal conduction correction coefficient and the thermal conductivity is as follows:

[0045] K = α * K water +(1 - α) * K dehy

[0046] where K is the thermal conductivity, α is the thermal conduction correction coefficient, K water is the thermal conductivity of water, and K dehy is the thermal conductivity of anhydrous tissue.

[0047] Finally, according to the thermal conduction correction coefficients and relative contrasts of multiple groups of tumor models, the functional relationship between the thermal conduction correction coefficient and the relative contrast is determined. According to an embodiment of the present invention, data fitting can be performed based on the thermal conduction correction coefficients and relative contrasts of multiple groups of tumor models to determine the functional relationship, and this functional relationship can be specifically implemented as an exponential relationship or a polynomial relationship.

[0048] Subsequently, step 120 is executed to determine the relative contrast of the patient according to the T1 signal and T2 signal of the patient's tumor tissue and healthy tissue respectively.

[0049] Figure 4 Fig. shows a schematic diagram of nuclear magnetic resonance detection of tumor tissue and healthy tissue according to an exemplary embodiment of the present invention. As Figure 4 shown, multi-point detection is performed on the tumor tissue and healthy tissue to determine the T1 signal and T2 signal of multiple points of the patient's tumor tissue, and the T1 signal and T2 signal of multiple points of the patient's healthy tissue.

[0050] According to an embodiment of the present invention, multi-point detection can be performed on the tumor tissue and healthy tissue respectively. For example, detection at x points is performed to obtain the x tumor tissue signal ratios of the tumor tissue and calculate the average value, as specifically shown in the following formula:

[0051]

[0052] A x is the average value of the x tumor tissue signal ratios, and i is the ith point among the x points for detecting the tumor tissue or healthy tissue;

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

[0054]

[0055] B x is the average value of the signal ratios of x healthy tissue points, and i is the i-th point among the x points for detecting tumor tissue or healthy tissue;

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

[0057]

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

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

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

[0061] Figure 5 shows a schematic diagram of the temperature curve for ablating a tumor model according to an exemplary embodiment of the present invention. As Figure 5 shown, the tumor models of a total of 7 groups of rabbits from a to g were ablated, and the temperature curves a)-g) were obtained by measuring the temperature. The thermal conductivity was determined by fitting the obtained temperature data, that is, curve h). The tumor models of the i-k three groups in the control group were ablated according to the determined thermal conductivity, and the temperature curves i)-h) were obtained. The temperature curves i)-h) are basically consistent with the temperature curves a)-g) of the a-g groups, indicating that the method for determining the ablation heat dose based on nuclear magnetic resonance detection signals of the present invention can quickly and accurately achieve personalized ablation heat dose surgical planning.

[0062] The present invention relates to a method for determining ablation heat dosage based on nuclear magnetic resonance detection signals; specifically: using MRI to collect the T1 and T2 signals of the tumor tissue to be ablated and the surrounding healthy tissue, taking the healthy tissue as the base number, and obtaining personalized tumor tissue thermal parameters according to the comparison of the T1 / T2 signals between the tumor tissue and the healthy tissue, so as to accurately calculate the heat dosage required for target ablation. The specific steps include: obtaining the T1 and T2 signals of the ablated tissue and normal tissue; calculating the relative contrast Rcon of the tumor tissue and normal tissue according to the T2 signal and T1 signal of the ablated tissue and normal tissue; establishing the functional relationship between the effective thermal conductivity K of the tissue and the relative contrast Rcon through multi-group model training; substituting the functional relationship into the bioheat transfer equation to solve the accurate heat dosage for ablating the target area to the target temperature. Using the present invention, the heat dosage of ablation can be accurately budgeted according to the preoperative MRI signals, so as to guide the clinical surgical planning, facilitate the realization of precise thermophysical treatment, and improve the clinical treatment effect.

[0063] The present invention utilizes the signal characteristics of the T1 and T2 signals in the preoperative MRI signals, and the physical properties of the tumor tissue water will change with the change of temperature before and after ablation and other characteristics. Through training with multi-group animal experimental models, the relationship between the effective thermal conductivity of the tissue and the MRI signals is established, and then the thermal conductivity relationship is brought into the bioheat transfer equation to quickly calculate the heat dosage required for ablating to the target temperature. The present invention will provide a method for the surgical planning of personalized precise thermophysical minimally invasive ablation, which is beneficial to guiding the clinical surgical planning and improving the surgical efficiency.

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

[0065] In this application, a non-transitory computer-readable storage medium can be any tangible medium that contains or stores a program, which can be used by or in conjunction with an instruction execution system, apparatus, or device. In this application, a computer-readable signal medium can include a data signal propagated in a baseband or as part of a carrier wave, which carries computer-readable program code. Such a propagated data signal can take various forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination of the above. 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 conjunction with an instruction execution system, apparatus, or device. The program code contained on a computer-readable medium can be transmitted using any appropriate medium, including but not limited to: wires, optical cables, RF (radio frequency), etc., or any suitable combination of the above.

[0066] The above computer-readable medium can be included in the above electronic device; or it can exist separately without being assembled into the electronic device.

[0067] The above description is only part of the embodiments of this application and an explanation of the applied technical principles. Those skilled in the art should understand that the scope of disclosure involved in this application is not limited to the technical solutions formed by the specific combination of the above technical features, and should also cover other technical solutions formed by any combination of the above technical features or their equivalent features without departing from the above disclosure concept. For example, a technical solution formed by mutually replacing the above features with (but not limited to) technical features having similar functions disclosed in this application.

[0068] In addition, although the operations are depicted in a specific order, this should not be construed as requiring the operations to be performed in the specific order shown or in sequential order. In certain environments, multitasking and parallel processing may be advantageous. Similarly, although 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 separate embodiments can also be implemented combinatorially in a single embodiment. Conversely, the various features described in the context of a single embodiment can also be implemented separately or in any suitable sub-combination in multiple embodiments.

[0069] Although the subject matter has been described in language specific to structural features and / or method logical acts, it should be understood that the subject matter defined in the appended claims is not necessarily limited to the specific features or acts described above. On the contrary, the specific features and acts described above are merely example forms of implementing the claims.

Claims

1. A method for determining ablation heat dosage based on nuclear magnetic resonance detection signals, the method comprising: Determining the functional relationship between the effective tissue thermal conductivity and the relative contrast according to multiple sets of temperature data collected by thermal ablation of a tumor model; Determining the relative contrast of a patient according to the T1 signal and T2 signal of the patient's tumor tissue and healthy tissue respectively; Determining the thermal conductivity according to the relative contrast and the functional relationship; Determining the ablation heat dosage required for tumor thermal ablation of the patient according to the thermal conductivity.

2. The method according to claim 1, wherein Determining the functional relationship between the effective tissue thermal conductivity and the relative contrast according to multiple sets of temperature data collected by thermal ablation of a tumor model includes: Performing nuclear magnetic resonance detection on multiple sets of established tumor models to determine the T1 signal and T2 signal of the healthy tissue of each tumor model, and the T1 signal and T2 signal of the tumor tissue; Determining the relative contrast of each tumor model according to the T1 signal and T2 signal of each tumor model; Performing thermal ablation on the tumor by setting an ablation probe and a temperature measurement probe in the tumor model, and collecting tumor boundary temperature data and ablation probe tip temperature data during the thermal ablation process; Determining the thermal conductivity of each tumor model from the tumor boundary temperature data and ablation probe tip temperature data of each group; Performing function fitting according to the thermal conductivity and relative contrast of multiple sets of tumor models to determine the functional relationship.

3. The method according to claim 2, wherein, The tumor model is suitable for being established by inoculating tumors into animal tissues.

4. The method according to claim 2 or 3, wherein, The T1 signal and T2 signal are suitable for being determined by performing nuclear magnetic resonance detection on the patient.

5. The method according to claim 2 or 3, wherein Determining the relative contrast of each tumor model according to the T1 signal and T2 signal of each tumor model includes: Determining the relative contrast according to the ratio of the tumor tissue signal ratio to the healthy tissue signal ratio, where 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.

6. The method according to claim 2, wherein Determining the thermal conductivity of each tumor model from 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 of each tumor model.

7. The method according to claim 1, wherein Determining the relative contrast of a patient according to the T1 signal and T2 signal of the patient's tumor tissue and healthy tissue respectively includes: Performing multi-point detection on the tumor tissue and healthy tissue to determine the T1 signal and T2 signal of multiple points of the patient's tumor tissue, and the T1 signal and T2 signal of multiple points of the patient's healthy tissue; Determining the average value of multiple tumor tissue signal ratios according to the T1 signal and T2 signal of multiple points of the patient's tumor tissue; Determining the average value of multiple healthy tissue signal ratios according to the T1 signal and T2 signal of multiple points of the patient's healthy tissue; Determining the relative contrast according to the average value of multiple tumor tissue signal ratios and the average value of multiple healthy tissue signal ratios.

8. The method according to claim 1, wherein Determining the ablation heat dosage required for tumor thermal ablation of the patient according to the thermal conductivity includes: Substituting the thermal conductivity or thermal conductivity correction coefficient into the bioheat transfer equation to determine the ablation heat dosage required for tumor thermal ablation.

9. A computing device, characterized in that, Including: One or more processors; A memory; And One or more devices, the one or more devices including instructions for performing the method according to any one of claims 1-8.

10. A computer-readable storage medium 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 1-8.

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