JP2008054975A - A method for simulating the heat conduction in the treatment area and estimating the treatment area in cancer freeze-thaw necrosis therapy - Google Patents

Abstract

<P>PROBLEM TO BE SOLVED: To provide a method and equipment to estimate a treatment region in a cancer freeze and fusion necrosis therapy. <P>SOLUTION: The method of estimating a treatment region by simulating thermal conduction through a planned operation region of the organ to have operation consists of: (1) a thermal conduction simulator, where the thermal conductance, blood flow and metabolic heat inflow of the organ subject to operation under a freeze and fusion necrosis therapy have been adjusted, is used to simulate thermal conduction from a freeze probe of this therapy equipment to the operated organ, temperature distribution around the freeze probe in the operated organ is measured to estimate a region to be frozen, (2) X-ray CT image data for the organ given a freeze and fusion necrosis treatment by this treatment apparatus is compared with the freeze region estimated in the step (1), and (3) the treatment region subject to freeze and fusion necrosis therapy is estimated by the comparison in the step (2). <P>COPYRIGHT: (C)2008,JPO&INPIT

Description

  The present invention relates to a method and an apparatus for estimating a treatment area in freeze-thaw necrosis therapy.

  Freeze-thaw necrosis therapy is a minimally invasive treatment method in which a freezing probe using the Joule-Thompson effect is percutaneously punctured into a tumor, and the tumor is repeatedly frozen and thawed to obtain local necrosis. This method has the advantage that there is no therapeutic pain, treatment can be performed only with local anesthesia, and there are no serious complications or side effects.

  The clinical application of this therapy is being promoted for lung cancer, which has increased in recent years (see Non-Patent Documents 1 and 2). The surgical procedure is performed under X-ray CT fluoroscopy, which can instantly grasp the positional relationship between the tumor and pulmonary arteriovenous veins. In a standard clinical operation, 5 to 10 minutes of freezing and thawing cycles until the temperature inside the freezing probe reaches 20 ° C. are repeated 2 to 3 times. In this method, a change area due to bleeding appearing in an X-ray CT image after freeze-thawing has been determined as a treatment area. The rate of recurrence in this treatment one year after surgery is as high as about 20% of all cases. One reason for this high recurrence rate is thought to be due to the above-mentioned treatment area determination by X-ray CT. In order to perform treatment while estimating an accurate treatment area, it is necessary to know the lung temperature distribution during the operation. For the estimation of the treatment area of the freezing and thawing necrosis therapy for a solid organ tumor other than the lung, an image diagnostic method using MRI or ultrasonic diagnosis capable of imaging the frozen area of the tissue is used (see Non-Patent Documents 3 and 4). . Since these image diagnostic methods cannot image the frozen region of the lung, they cannot be used to estimate the therapeutic region of lung cancer freeze-thaw necrosis therapy. The puncture type temperature sensor requires a puncture route different from that for the freezing probe, and cannot be used clinically because it is highly invasive. Under such circumstances, development of a method for obtaining intraoperative lung temperature has been desired.

Nakatsuka, M. et al., Cryogenic Medicine. 30 (1): 9-15, 2004. Kawamura M. et al., Lung Cancer. 49 (S2): S353, 2005. Junta Harada et al., Journal of Nippon Medical School. 69 (5): 476-479, 2002. Wakabayashi Tsuyoshi et al., Japanese Journal of Interventional Radiology. 19 (2): 113-116, 2004.

  An object of the present invention is to provide a method and an apparatus for estimating a treatment area in freeze-thaw necrosis therapy for cancer.

  The present inventors have sought to develop a method for estimating intraoperative treatment area by X-ray CT by obtaining three correspondences between intraoperative lung temperature distribution, X-ray CT image change area, and postoperative treatment effect. Study was carried out. The present inventors first tried to construct a finite element heat conduction simulator that estimates the intraoperative lung temperature distribution from the operating conditions of the freezing device. Control experimental systems were prepared ex vivo and in vivo to measure lung cooling temperature history. At this time, the parameters of the heat conduction simulator were adjusted by comparing the temperature change curve calculated with a simple two-dimensional finite element model and the cooling temperature history obtained as a result of the experiment. Specifically, after adjusting the specific heat and thermal conductivity of the lung through experiments using ex vivo lungs in a static state where there is no blood flow or breathing, blood flows and breathing are performed through experiments using in vivo lungs. Adjusted the heat inflow due to As a result, a heat conduction simulator that can estimate the temperature distribution of healthy lungs at the time of the first freezing without bleeding has been constructed.

  Furthermore, the present inventors estimated the temperature distribution of the lung to be operated using the constructed heat conduction simulator and compared it with the post-operative X-ray CT image. As a result, it has been found that the lung treatment area can be estimated from the estimated lung temperature distribution, and the present invention has been completed.

That is, the present invention is as follows.
[1] A method for estimating the treatment area by simulating the heat conduction from the freezing probe of the freezing and thawing necrosis therapy device in the target organ for the freezing and thawing necrosis therapy of cancer by finite element analysis, A method of estimating a treatment region by constructing a heat conduction simulator based on a finite element method using a thermal conductivity of an organ to be treated and estimating a treatment region, and simulating heat conduction using the heat conduction simulator.

[2] Adjust the parameters for thermal conductivity in the heat conduction analysis by the finite element method, and further adjust the parameters for heat inflow due to blood flow and metabolic heat, and build a heat conduction simulator by the finite element method. A method for estimating a treatment area.
[3] A method for estimating a therapeutic area according to [1] or [2], wherein the cancer is selected from the group consisting of lung cancer, liver cancer, kidney cancer and prostate cancer.

[4] A method for estimating a treatment area according to any one of [1] to [3], in which the thermal conductivity of an organ to be treated is determined for each individual to be treated, and a heat conduction simulator is constructed.
[5] A method of simulating the heat conduction in the treatment area of the organ to be treated in freeze-thaw necrosis therapy for cancer and estimating the treatment area, and at least the following steps (1) to (3) are performed once Method:
(1) Heat from the freezing probe of the freeze-thaw necrosis therapy apparatus in the target organ using a heat conduction simulator that adjusts the heat conductivity of the target organ for freeze-thaw necrosis therapy, blood flow, and metabolic heat. Simulating conduction, obtaining a temperature distribution around the freezing probe in the organ to be treated, and estimating a frozen region;
(2) A step of comparing X-ray CT image data of an organ subjected to freeze-thaw necrosis treatment with a freeze-thaw necrosis therapy device and a frozen region estimated in step (1); and (3) Freezing by comparison of (2) Estimating a treatment site by melting necrosis therapy.

[6] The method for estimating a treatment area according to [5], wherein steps (1) to (3) are repeated a plurality of times.
[7] The method for estimating a treatment area according to [6], wherein steps (1) to (3) are repeated two or three times.
[8] A method for estimating a therapeutic region according to any one of [5] to [7], wherein the cancer is selected from the group consisting of lung cancer, liver cancer, kidney cancer and prostate cancer.

[9] A device for estimating a treatment area in freeze-thaw necrosis therapy for cancer,
(A) In order to simulate the heat conduction from the freezing probe of the freezing and thawing necrosis therapy device in the target organ by adjusting the heat conductivity, blood flow and heat inflow due to metabolic heat of the target organ for the freezing and thawing necrosis therapy Storage means for storing the heat conduction simulator of
(B) a computing means for estimating the temperature distribution of the organ to be treated around the freezing probe by the heat conduction simulator of (a), and
(c) An apparatus including means for displaying the temperature distribution analyzed by the computing means of (b).

[10] In freeze-thaw necrosis therapy for cancer, an apparatus for estimating a treatment area,
(a) To simulate the heat conduction from the freezing probe of the freeze-thaw necrosis therapy device in the target organ, adjusting the heat conductivity, blood flow and heat inflow due to metabolic heat of the target organ for freeze-thaw necrosis therapy Storage means for storing the heat conduction simulator of
(b) a computing means for estimating the temperature distribution of the organ to be treated around the freezing probe by the heat conduction simulator of (a),
(c) means for receiving X-ray CT image data obtained by the X-ray CT apparatus, and
(d) An apparatus including means for comparing the temperature distribution analyzed by the computing means in (b) with the X-ray CT image data received in (c) and displaying the result.

[11] The means for comparing the temperature distribution analyzed by the computing means with the received X-ray CT image data and displaying the result is the means for displaying the temperature distribution superimposed on the X-ray CT image. apparatus.
[12] A device for estimating a therapeutic region according to any one of [9] to [11], wherein the cancer is selected from the group consisting of lung cancer, liver cancer, kidney cancer, and prostate cancer.
[13] A device for estimating a treatment region according to any one of [9] to [12], further comprising an X-ray CT device and / or a cancer freeze-thaw necrosis therapy device.

[14] A program for simulating heat conduction at a treatment site in cancer freeze-thaw necrosis therapy and estimating a treatment area,
Computer
(I) To simulate the heat conduction from the freezing probe of the freezing and thawing necrosis therapy device in the target organ by adjusting the heat conductivity, blood flow and heat inflow due to metabolic heat of the target organ for the freezing and thawing necrosis therapy Storage means for storing the heat conduction simulator of
(Ii) a computing means for estimating the temperature distribution of the organ to be treated around the freezing probe by the heat conduction simulator of (i), and
(iii) A program for functioning as a means for displaying the temperature distribution in the treated organ analyzed by the computing means of (ii).

[15] Further, (iv) means for receiving X-ray CT image data, (v) temperature distribution in the surgical organ analyzed by means of (iii), and X-ray CT image received by means of (iv) The program for estimating the treatment area | region of [15] for functioning as a means to compare data, and a means to display the result compared by the means of (vi) (v).
[16] The program for estimating a therapeutic area according to [15], wherein the cancer is selected from the group consisting of lung cancer, liver cancer, kidney cancer, and prostate cancer.

  In the present invention, a finite element heat conduction simulator for estimating the lung temperature distribution was constructed in order to estimate the intraoperative treatment area in the lung cancer freeze-thaw necrosis therapy. The inventors adjusted the heat conduction parameters by comparing the lung cooling temperature history measured in the control experiment with the calculated temperature change curve. Specific heat and thermal conductivity were adjusted by ex vivo experiments. The thermal conductivity of the lung depends on the lung density, and the relationship was clarified. In vivo experiments, heat inflow and metabolic fever due to blood flow in the tissue were added to the heat conduction simulator. As a result, the temperature distribution at the time of freezing of the lungs (from the start of freezing to 10 minutes) could be estimated with a precision of ± 3 ° C by using a two-dimensional heat conduction simulator. By using the built-in heat conduction simulator, it is possible to estimate the intraoperative treatment area in freeze-thaw necrosis therapy for lung cancer. In addition, this method makes it possible to estimate a treatment area even in cancers other than lung cancer.

  In the method of simulating the heat conduction in the treatment area of the organ to be treated and performing the estimation of the treatment area when performing cancer freeze-thaw necrosis therapy according to the present invention, the target cancer is not limited, and any cancer is targeted. Become. However, lung cancer, liver cancer, kidney cancer, and prostate cancer are preferred because effective treatment methods are not well established and cancer freeze-thaw necrosis therapy is more effective than other treatment methods. Among these cancers, lung cancer is particularly preferable because it is difficult to determine a frozen region by diagnostic imaging using X-ray CT in current cancer freeze-thaw necrosis therapy.

  In freeze-thaw necrosis therapy, a freezing probe of a freeze-thaw necrosis therapy apparatus (cryosurgery apparatus) to be used is inserted into a cancer site, the probe part is cooled to freeze the cancer region around the probe. In the cancer freeze-thaw necrosis therapy of the present invention, the heat conduction in the treatment region is simulated, and in the method for estimating the treatment region, the heat conduction from the freezing probe is simulated, and the temperature distribution of the cancer region around the freezing probe Is estimated. From the obtained temperature distribution data, a frozen region of the cancer part, that is, a treatment region can be estimated.

  The type of freeze-thaw necrosis therapy apparatus employed in the method for simulating the heat conduction in the treatment area and estimating the treatment area of the present invention is not limited, and the apparatus using argon gas or helium gas or the apparatus using liquid nitrogen is not limited. Either can be adopted. A commercially available device may be used as the freeze-thaw necrosis therapy device.

  In the method of simulating the heat conduction in the treatment area and estimating the treatment area according to the present invention, a two-dimensional or three-dimensional finite element analysis is performed on the temperature distribution in the organ having cancer to create and calculate a finite element model. . The heat conduction calculation by the finite element method divides the object for which heat conduction is to be calculated into fine elements and assumes that heat is transferred only between adjacent elements, and heat at the nodes (nodes) of the divided elements. This is a method of calculating heat conduction using a transport equation. In this case, a heat conduction simulator for the organ can be constructed by deriving parameters specific to the organ to be treated using a commercially available heat conduction calculation program. An example of such a program is Quick Therm BIO (registered trademark) (Computational Mechanics Laboratory), which is a two-dimensional finite element heat conduction analysis software created based on heat conduction to the myocardium. By inputting physical property parameters of a certain organ, a heat conduction simulator for the organ can be constructed. At this time, the parameters that contribute to the heat transfer from the freezing probe of the freeze-thaw necrosis therapy device are specified as parameters, the parameters in the target organ to be treated by freeze-thaw necrosis therapy are adjusted, and the freezing probe is analyzed by finite element analysis Simulates heat transfer from to the target organ. The parameters include the heat conductivity inherent to the target organ and the heat inflow to the treatment area due to blood flow and metabolic heat in the target organ. The parameter adjustment is performed by predicting a temperature change in a certain region using a finite element model and comparing the temperature history actually obtained by using the organ or the organ model. The shape of the finite element model is not limited, but may be, for example, a rectangle or a hexagon on the horizontal cross section of the organ passing through the central axis of the freezing probe of the freeze thaw necrosis therapy apparatus. In actual cancer treatment, it is necessary to grasp the treatment area in three dimensions. However, in the freeze-thaw necrosis therapy apparatus, heat conduction from the freezing probe occurs radially around the freezing probe, so a two-dimensional finite element. A three-dimensional finite element model can be obtained by rotating the model obtained by the analysis.

  The thermal conductivity of the target organ can be obtained, for example, by sampling the organ and experimentally obtaining the value. The organ may be a human organ or a non-human animal organ such as a pig. However, since the organ density differs depending on the individual organ to be treated, it is necessary to obtain the thermal conductivity from the density. In this case, the density is obtained from the volume and weight of the organ to be treated collected in advance, and a part of the organ is crushed and the specific heat of the organ is obtained by experiment to calculate the thermal conductivity. Next, the relationship between the density and the thermal conductivity is obtained, and the thermal conductivity can be calculated from the density by creating an equation or the like. The density of the specific organ to be treated can be obtained from the CT value of the X-ray CT image, and the thermal conductivity of the specific individual can be obtained from the relationship between the already obtained density and the thermal conductivity. In particular, since the density difference between individuals is large in the lung, it is desirable to obtain the thermal conductivity for each individual by obtaining the density. In organs other than the lung, such as the liver and kidney, there is no difference in density between individuals as much as in the lungs, and there is no great difference in thermal conductivity between individuals. In this case, the density for each individual may be obtained, or the thermal conductivity or literature values determined in advance using an organ collected without adjusting the thermal conductivity for each individual may be used.

  In the cancer freeze-thaw necrosis therapy of the present invention, the temperature distribution centered on the freezing probe of the freeze-thaw necrosis therapy device can be estimated by a simulator that simulates heat conduction in the treatment area. By superimposing the estimated temperature distribution on the X-ray CT image, a region frozen by freeze-thaw necrosis therapy can be estimated, and the frozen region can be estimated as a treatment region. If the cancer area is determined in advance using an X-ray CT device, it is possible to know the area treated by freeze-thaw necrosis therapy in the cancer area, and whether the estimated treatment area covers the cancer area. Can be judged. When the estimated treatment area covers the cancer area, the treatment can be terminated by assuming that the cancer treatment has been completed.

FIG. 11 shows a concept of a method for estimating a treatment area in freeze-thaw necrosis therapy.
The method for simulating the heat conduction in the treatment area and estimating the treatment area in the freeze-thaw necrosis therapy of the present invention comprises the following steps.
(1) Heat from the freezing probe of the freeze-thaw necrosis therapy apparatus in the target organ using a heat conduction simulator that adjusts the heat conductivity of the target organ for freeze-thaw necrosis therapy, blood flow, and metabolic heat. Simulating conduction, obtaining a temperature distribution around the freezing probe in the organ to be treated, and estimating a frozen region;
(2) A step of comparing X-ray CT image data of an organ that has been subjected to freeze-thaw necrosis treatment with a freeze-thaw necrosis therapy device and a frozen region estimated in step (1), and (3) freezing by comparison of (2) Estimating a treatment site by melting necrosis therapy.

  In freeze-thaw necrosis therapy, freezing is usually performed for 5 to 10 minutes. In step (1), a temperature change with time during freezing for 5 to 10 minutes can be estimated, and a temperature history in freeze-thaw necrosis therapy can also be estimated.

  In the step (1), for example, an area of −20 ° C. or lower can be estimated as a frozen area. In the step (1), if the heat conductivity of the organ to be treated, blood flow and heat inflow due to metabolic heat are adjusted in advance, each time the method of the present invention is carried out, the heat conductivity, blood flow, and metabolism are performed. There is no need to adjust parameters such as heat. However, when the organ to be treated is the lung, the density of the lung varies depending on the individual, and therefore the thermal conductivity of the lung varies depending on the individual. Therefore, it is necessary to adjust the thermal conductivity every time step (1) is performed. That is, when the organ to be treated is a lung, the step (1) more specifically adjusts the heat conductivity, blood flow and heat inflow due to metabolic heat of the lung to be treated by freeze-thaw necrosis therapy, It can be expressed as a step of simulating the heat conduction from the freezing probe of the freeze-thaw necrosis therapy apparatus in the organ, obtaining the temperature distribution around the freezing probe in the operation target lung, and estimating the freezing area. In this case, as described above, the density is known from the CT value obtained by the X-ray CT analysis, and the thermal conductivity for each individual can be obtained by calculation from the density.

  At this time, when constructing a heat conduction simulator, it is first determined whether there is a density difference between individuals of the organ to be treated, and if it is judged that there is a density difference between individuals, the heat of the organ to be treated for each individual is determined. What is necessary is just to estimate conductivity and adjust the heat conduction calculation formula. On the other hand, when it is judged that there is no difference in density between individuals, it is not necessary to consider the thermal conductivity for each individual, and a predetermined thermal conductivity for the organ may be adopted.

  The X-ray CT image data in the step (2) is obtained as an image or as CT value data at each pixel. For comparison between the X-ray CT image data and the estimated frozen region, for example, an X-ray CT image and an image showing the frozen region around the freezing probe may be superimposed. The display is displayed with the temperature distribution superimposed on the X-ray CT image. Further, the CT value of each pixel in the X-ray CT image data may be compared with the estimated temperature at each node obtained by finite element analysis using a heat conduction simulator corresponding to each pixel. The result of the comparison is displayed. For example, the X-ray CT image is displayed in a state where the temperature is superimposed, and the temperature distribution is expressed by, for example, an isotherm centered on the freezing probe. These displays are displayed on a display unit such as a monitor.

  In the step (3), for example, a treatment region can be estimated from an image displayed with an overlaid temperature distribution on an X-ray CT image, and a region estimated to be frozen in a cancer region is treated. It can be estimated that this is a region that has been processed.

  FIG. 12 is a flowchart schematically showing a method for estimating a treatment area in freeze-thaw necrosis therapy using the heat conduction simulator of the present invention.

  The present invention includes a method for constructing the above heat conduction simulator and a method for simulating heat conduction by the constructed heat conduction simulator. The method of constructing the heat conduction simulator is a method of constructing a simulator that simulates the heat conduction from the freezing probe of the freeze thaw necrosis therapy device in the target organ of the freeze thaw necrosis therapy of cancer by finite element analysis. Using the thermal conductivity of the target organ for freeze-thaw necrosis therapy, adjust the parameters related to the thermal conductivity in the heat conduction analysis formula by the finite element method, and further adjust the parameters related to the heat inflow due to blood flow and metabolic heat. This is a method for constructing a heat conduction simulator including setting a heat conduction analysis calculation formula by a finite element method. Furthermore, the method of simulating heat conduction with the built-in heat conduction simulator simulates heat conduction from the freezing probe of the freeze thaw necrosis therapy device in the target organ of the freeze thaw necrosis therapy by finite element analysis. This method determines the thermal conductivity of the target organ for freeze-thaw necrosis therapy, adjusts the parameters related to thermal conductivity in the thermal conduction analysis formula by the finite element method, and further controls the heat inflow due to blood flow and metabolic heat. This is a method of adjusting, constructing a heat conduction simulator by a finite element method, and simulating heat conduction by the heat conduction calculation formula.

  Freeze-thaw necrosis therapy is usually repeated multiple times. Preferably, it is repeated within 5 times, more preferably 2 or 3 times. Bleeding occurs in the thawed area after the first freezing by freeze thaw necrosis therapy. When the second freezing is performed, the thermal conductivity changes due to the influence of bleeding, and the frozen region cannot be accurately estimated by the first heat conduction simulator. For this reason, when performing the second and subsequent freezing in the freeze-thaw necrosis therapy, it is necessary to adjust the change in thermal conductivity due to bleeding and simulate the thermal conduction. For this purpose, an X-ray CT image of an area subjected to the first freezing is obtained, and a bleeding area is determined. Since the bleeding region looks like a ground glass on the X-ray CT image, it can be determined as a non-bleeding region. In the X-ray CT apparatus, a CT value can be obtained for each pixel on the X-ray CT image, and the bleeding region can be determined based on the CT value. The air content at the position of the organ corresponding to each pixel can be obtained from the CT value, and the thermal conductivity at that position can be obtained from the obtained air content. The thermal conductivity is corrected using the obtained thermal conductivity, and a heat conduction simulator reflecting the influence of bleeding can be constructed. The present invention is not only a method of simulating heat conduction for estimating a treatment area due to first freezing in which bleeding does not occur, but also a method of simulating heat conduction for estimating a treatment area due to freezing after the first time. In addition, a method of simulating heat conduction reflecting changes in heat conductivity due to bleeding is also included. In this case, if it is determined that the estimated treatment area covers the cancer area, the treatment should be terminated, and the estimated treatment area does not cover the cancer area and the treatment is not sufficient. If it is determined, freeze necrosis therapy may be repeated.

  For example, when freeze-thaw necrosis therapy is repeated twice, the method of simulating the heat conduction of the treatment site in the freeze-thaw necrosis therapy of the present invention and estimating the treatment area is performed by the following steps.

(1) A probe for freezing a freeze-thaw necrosis therapy apparatus in a target organ using a heat conduction simulator that adjusts the heat conductivity of the target organ for the first freeze-thaw necrosis therapy, blood flow, and heat inflow due to metabolic heat Simulating the heat conduction from the body, obtaining the temperature distribution around the freezing probe in the organ to be treated, and estimating the frozen region,
(2) a step of comparing X-ray CT image data of an organ subjected to freeze-thaw necrosis treatment with the first freeze-thaw necrosis therapy device and the frozen region estimated in step (1);
(3) Estimating a treatment site by freeze-thaw necrosis therapy by comparing (2),
(4) Freeze-thaw necrosis in the target organ using a heat conduction simulator that adjusts the heat conductivity, blood flow, metabolic fever, and heat inflow due to bleeding associated with freeze-thaw in the second freeze-thaw necrosis therapy. Simulating heat conduction from the freezing probe of the therapy device, obtaining a temperature distribution centered on the freezing probe in the organ to be treated, and estimating a freezing region,
(5) a step of comparing the X-ray CT image data of the organ that has been subjected to freeze-thaw necrosis treatment with the second freeze-thaw necrosis therapy device with the frozen region estimated in step (1), and (6) in (5) A step of estimating a treatment site by freeze-thaw necrosis therapy by comparison.

  When the freeze-thaw necrosis therapy is further repeated, the above steps (4) to (6) may be repeated.

  The present invention further includes a device for estimating a frozen region, that is, a treatment region in freeze-thaw necrosis therapy using the heat conduction simulator of the present invention.

The device
(a) To simulate the heat conduction from the freezing probe of the freeze-thaw necrosis therapy device in the target organ, adjusting the heat conductivity, blood flow and heat inflow due to metabolic heat of the target organ for freeze-thaw necrosis therapy Storage means for storing the heat conduction simulator of
(b) a computing means for estimating the temperature distribution of the organ to be treated around the freezing probe by the heat conduction simulator of (a), and
(c) means for displaying the temperature distribution analyzed by the computing means of (b).

The apparatus of the present invention may further include means for receiving an X-ray CT image obtained by the X-ray CT apparatus, comparing with the temperature distribution analyzed by the computing means of (b), and displaying the result. . The device in this case is
(a) To simulate the heat conduction from the freezing probe of the freeze-thaw necrosis therapy device in the target organ, adjusting the heat conductivity, blood flow and heat inflow due to metabolic heat of the target organ for freeze-thaw necrosis therapy Storage means for storing the heat conduction simulator of
(b) a computing means for estimating the temperature distribution of the organ to be treated around the freezing probe by the heat conduction simulator of (a),
(c) means for receiving X-ray CT image data obtained by the X-ray CT apparatus, and
(d) includes a means for comparing the temperature distribution analyzed by the computing means in (b) with the X-ray CT image data received in (c) and displaying the result.

The treatment area by the treatment can be estimated by displaying the comparison result in (d).
The above-described device of the present invention may be further combined with a freeze-thaw necrosis therapy device, and may further be combined with an X-ray CT device. In this case, the image processing apparatus includes means for obtaining an image of a target organ treated using the freeze-thaw necrosis therapy apparatus as image data by an X-ray CT apparatus and transferring the image data to the apparatus.

  That is, the present invention also includes an apparatus in which a freeze-thaw necrosis therapy apparatus and / or an X-ray CT apparatus are combined with the apparatus including the means (a) to (d).

  FIGS. 13 and 14 are schematic views of an apparatus for estimating a treatment area in freeze-thaw necrosis therapy using a heat conduction simulator. FIG. 14 includes the therapy of the X-ray CT apparatus and the freeze-thaw necrosis therapy apparatus, but this is an example, and only one of them may be included.

The present invention further includes a program for simulating the heat conduction of the treatment site in the above-described freeze-thaw necrosis therapy and estimating the treatment area. In the freeze thaw necrosis therapy, the program uses a computer to estimate the frozen area, that is, the therapeutic area,
(I) To simulate the heat conduction from the freezing probe of the freezing and thawing necrosis therapy device in the target organ by adjusting the heat conductivity, blood flow and heat inflow due to metabolic heat of the target organ for the freezing and thawing necrosis therapy Storage means for storing the heat conduction simulator of
(Ii) a computing means for estimating the temperature distribution of the organ to be treated around the freezing probe by the heat conduction simulator of (i), and
(iii) A program for functioning as a means for displaying the temperature distribution in the treated organ analyzed by the computing means of (ii).

  The program of the present invention further comprises (iv) means for receiving X-ray CT image data, (v) temperature distribution in the treated organ analyzed by means of (iii) and X-rays received by means of (iv) It also includes a program for functioning as means for comparing CT image data and means for displaying the results of comparison by means of (vi) and (v).

The present invention will be specifically described by the following examples, but the present invention is not limited to these examples.
Example 1 Construction of a heat conduction simulator in the lung Adjustment method of heat conduction parameter (1) Adjustment of specific heat and heat conductivity by ex vivo experiment Lung density is known to vary in the range of 0.1 to 0.8 × 10 ^-3 g / mm ³ depending on the state of the lung. (Kalef EJ et al., Acta Radiologica. 40 (3): 333-337, 1990). It is thought that the thermal conductivity of the lung changes in correlation with the lung density. On the other hand, the specific heat of the lung is not expected to change significantly depending on the lung density. Therefore, adjustment was performed in the order of specific heat and thermal conductivity. Put the pulverized and centrifugally degassed pig lungs into a container (100 mm x 100 mm x 50 mm) (height 40 mm), T-type thermocouple (HYP-1, Ishikawa Sangyo, Tokyo). A cooling source with liquid nitrogen (−196 ° C.) as a refrigerant and an aluminum foil (thickness 12 μm) at the bottom (20 mm × 60 mm) was created. The cooling source was placed on the upper surface of the lung tissue fluid, taking care not to introduce bubbles, and cooling was started, and the temperature history for 10 minutes was measured. Two-dimensional finite element heat conduction analysis software Quick Therm BIO (registered trademark) (Computational Mechanics Research Center, Tokyo) was used for heat conduction calculation. In order to verify the effective accuracy of this heat conduction analysis, the temperature distribution can be estimated with an accuracy of ± 2 ° C by conducting a comparative study between the cooling temperature history of the cold insulation material whose thermophysical properties are known in advance and the calculated temperature change curve. confirmed. The finite element model was set to a rectangle (100 mm x 40 mm). Thermal conductivity and latent heat of solidification include water values (0.6 mW / (mm · ° C) (when frozen), 2.0 mW / (mm · ° C) (when frozen) (333 J / g) (Rewcastle JC et al, 43 (12): 3519-3534, 1998) The latent heat of coagulation was measured at tissue freezing point (-2 ° C) (Duck FA: Physical Properties of Tissue-A Comprehensive Reference Book. Academic Press, London, 1990, pp. 9-41.) Equivalent specific heat was converted into the heat conduction simulator within the range of 10 ° C below.The boundary condition of the finite element model is air (room temperature 23 ° C). The actual temperature change was set as the lung boundary temperature, and the specific heat was calculated so that the difference between the cooling temperature history at each position and the calculated temperature change curve at each time was 2 ° C. or less.

In order to investigate the dependence of thermal conductivity on lung density, the ex vivo swine lung density was varied in the range of 0.1 to 0.8 x 10 ^-3 g / mm ³ depending on the amount of infused air, and the cooling temperature history for 10 minutes was similarly determined. Measured and used to adjust the thermal conductivity. For temperature measurement, a thermocouple of 0.9 mmφ with the tip of the temperature measuring point improved so that the alveolar diameter was larger than 0.3 mm was used. FIG. 1 shows an experimental system. The shape of the finite element model was a rectangle (110 mm x 80 mm) with a simplified lung cross section. A value obtained from the volume and weight of each lung was used as the density, and a value adjusted by an experiment using the pulverized lung was used as the specific heat. The coagulation latent heat was calculated by obtaining a value obtained by multiplying the value of water by the specific gravity of the lung in order to take into account differences due to lung density, and setting it in the heat conduction simulator in the same manner as adjusting the specific heat.

は以下のように生体熱伝導方程式の熱輸送項より求める（Pennes HH, Journal of Applied Physiology. 1(2): 93-122, 1948）。

(2) Adjustment of heat inflow by in vivo experiments
The heat inflow term due to blood flow and respiration in the tissue in the heat conduction simulator was adjusted by an in vivo lung temperature measurement experiment. In order to select the elementary processes to be considered when estimating the temperature distribution of the lung in vivo, the heat flow of each process was estimated from the literature and the order was compared. Heat transport by blood flow in tissue

Is obtained from the heat transport term of the biological heat conduction equation as follows (Pennes HH, Journal of Applied Physiology. 1 (2): 93-122, 1948).

は、熱換気量

を肺胞壁全面で伝達すると仮定して下記の(2)式を立て、これを用いて求める。

熱換気量

はYokoyamaらの知見より(3)式で表される（Yokoyama S et al., Japanese Journal of Biometeorology. 20(1): 1-7, 1983）。

On the other hand, heat transfer by breathing

Is the thermal ventilation

Assuming that is transmitted across the entire alveolar wall, the following equation (2) is established and obtained using this.

Thermal ventilation

Is expressed by equation (3) based on the findings of Yokoyama et al. (Yokoyama S et al., Japanese Journal of Biometeorology. 20 (1): 1-7, 1983).

がある。これは、以下のように表される（Chato JC: Thermal Properties of Tissue. In: Skalak R, Chien S ed, Handbook of Bioengineering. McGraw Hill, New York, 1987, pp. 9.1-9.13.）。

である。以上より(1)および(4)式で示される組織内血流による熱輸送および代謝熱を熱伝導シミュレータで調整することにした。具体的には、組織内血流による熱輸送は(1)式内の組織血流量を調整し、代謝熱は(4)式より求めた熱量とした。熱伝導シミュレータには、血流による熱流入を熱伝達率

代謝熱を発熱項として設定し、計算する。 Lung tissue ^{(20 ℃, 0.3 × 10 -3} g / mm 3) of the unit volume (1 mm ³⁾ When considering heat inflow into, (1) to (3) the contribution by the blood flow from the equation 1.5 mW, respiratory Is estimated to be 1.1 × 10 ^-3 mW (assuming room temperature 26 ° C., relative humidity 60%, alveoli (0.3 mmφ) in the face-centered close-packed tissue). Therefore, the contribution of respiration in heat inflow can be ignored because it is 3 orders of magnitude smaller than the contribution of blood flow in the tissue. Metabolic fever, which is tissue fever as a thermal factor other than heat inflow

There is. This is expressed as follows (Chato JC: Thermal Properties of Tissue. In: Skalak R, Chien Sed, Handbook of Bioengineering. McGraw Hill, New York, 1987, pp. 9.1-9.13.).

It is. Based on the above, it was decided to adjust the heat transport and metabolic heat due to blood flow in the tissue expressed by equations (1) and (4) using a heat conduction simulator. Specifically, the heat transport by blood flow in the tissue was adjusted to the blood flow volume in the equation (1), and the heat of metabolism was the calorific value obtained from the equation (4). In the heat conduction simulator, the heat transfer rate of heat inflow due to blood flow

Set metabolic heat as the fever term and calculate.

A cooling temperature measurement experiment as a control of heat conduction calculation was performed in the lung in vivo. A clinical freezing probe (CRYO-Care Cryosurgical Unit, Endocare, USA) was used for cooling. A domestic pig (male, 12 weeks old) was placed under respiratory control with total anesthesia and ventilator (ventilator KV-1 + 1, Kimura Medical Equipment, Tokyo) (5 L / min, O ₂ : 60%), right chest The chest was opened to expose the lungs. The procedure for inserting the freezing probe into the lung was the same as in clinical practice. An 8Gauge stainless steel outer tube (Dimon puncture needle, Silks, Saitama) (outer diameter 4 mm, inner diameter 3.5 mm) was inserted 25 mm from the pleural surface of the lower lobe. In order to ensure heat conduction between the outer cylinder and the freezing probe, a freezing probe (outer diameter 3.4 mm) was inserted after injecting physiological saline into the outer cylinder. FIG. 2 shows the positional relationship between the outer cylinder and the freezing probe. The temperature measuring points were placed at 6 concentric circles 10mm and 15mm apart from the outer cylinder. A T-type φ0.5mm sheathed thermocouple (SH304-T-05-G-200-1500M, grounded type, Ishikawa Sangyo, Tokyo) was used for temperature measurement. FIG. 3 shows the positional relationship between the freezing probe and the thermocouple. The temperature change of the lung for 10 minutes from the start of freezing was measured. FIG. 4 shows the installation state of the freezing probe and thermocouple during temperature measurement. The finite element model was two-dimensional, and the horizontal cross section of the lung passing through the central axis (φ3.4mm) of the freezing probe was set as a simplified hexagon. FIG. 5 shows the created finite element model. When the lung cross section after temperature measurement was observed, bleeding was observed in a range of about 40 mm square from the pleural surface. Because this range is considered to have a large amount of temperature change, the distance between elements of the finite element model was made shorter (1.2mm x 0.9mm) than the surroundings to increase the calculation resolution. As the lung density, a value obtained from the volume and weight of the upper lobe (expired state) not used in the experiment was used. Specific heat and thermal conductivity are as described in 1. above. The value adjusted in (1) was used.

2. Results (1) Adjustment of specific heat and thermal conductivity The adjusted specific heat of the lung was 3.7 J / (g · ° C) in the normal temperature range and 1.8 J / (g · ° C) in the freezing range. The water content of lung tissue is about 80% (Kunio Kanno, Kazuo Shimao: Biochemical Data. Medical School, Tokyo, 1968, pp. 448-449), and the specific heat of water and ice is 4.2 J / (g · ° C, respectively) ) (Chato JC: Thermal Properties of Tissue. In: Skalak R, Chien S ed, Handbook of Bioengineering. McGraw Hill, New York, 1987, pp. 9.1-9.13.), 2.0 J / (g · ° C) (Rewcastle JC et al., Physics in Medicine and Biology. 43 (12): 3519-3534, 1998). The protein (collagen) content of the lung tissue is about 15% (Kunio Kanno, Kazuo Shimao: Biochemical Data. Medical School, Tokyo, 1968, pp. 448-449.), And the specific heat of protein at room temperature is 1.09J / (g. ° C.) (Chato JC: Thermal Properties of Tissue. In: Skalak R, Chien Sed, Handbook of Bioengineering. McGraw Hill, New York, 1987, pp. 9.1-9.13.). In the normal temperature range, the specific heat of the lung is derived from the composition of the lung and the specific heat of its constituents (Chato JC: Thermal Properties of Tissue. In: Skalak R, Chien S ed, Handbook of Bioengineering. McGraw Hill, New York, 1987, pp. 9.1-9.13.) and calculated to be 3.8 J / (g · ° C). Therefore, the adjusted specific heat of the lung in the normal temperature range is considered to be a reasonable value because it is close to the estimated value. There is no report on the specific heat of protein in the low temperature range (0 ° C or lower). The specific heat of the lung in the frozen region was 1.76 J / (g · ° C) when calculated in the same manner using the specific heat in the normal temperature region. Therefore, the specific heat of the lung in the adjusted frozen region is also considered to be a reasonable value.

FIG. 6 shows the relationship between lung density and adjusted thermal conductivity. It has been reported that the thermal conductivity of a porous material resembling the structure of the lung is expressed as a power function of porosity (Thermophysical Society of Japan, Thermophysical Handbook. Yokendo, Tokyo, 1990, pp. 176-178.). Here, the porosity means the ratio of the pore volume to the entire volume of the porous material, and is represented by the following formula.

  Based on this report, the porosity was replaced with the lung density, and a power function of the lung density was fitted to the adjusted heat conductivity of the lung by the least square method. The correlation coefficient between the heat conductivity of the lung and the fitted power function in the adjusted normal temperature region and the frozen region was 0.99. There has been no report on the density dependence of the thermal conductivity of the lung. Since the lung density can be derived from the CT value of the X-ray CT image (Kalef EJ et al., Acta Radiologica. 40 (3): 333-337, 1990), using the relationship in FIG. The rate can be calculated.

(2) Adjustment of heat inflow Generally, tissue blood flow decreases with decreasing tissue temperature (Akio Nakayama: Thermophysiology. Science and Engineering, Tokyo, 1983, pp. 129-135.) -2 ℃). When the flow is laminar and the pipe diameter is constant, the flow rate of the Newtonian fluid flowing in the pipe is known to be inversely proportional to the fluid viscosity change (Poiseuille's law) (Mikio Hino: Fluid Dynamics. Asakura). Bookstore, Tokyo, 2005, pp. 215-218.).

Here, Poiseuille's law is that the flow rate of fluid flowing in a circular pipe is proportional to the fourth power of the circular pipe radius and the pressure gradient at both ends of the pipe in the laminar flow region (Reynolds number 2300 or less), and inversely proportional to the fluid viscosity. This is the law (Mikio Hino: Fluid Dynamics. Asakura Shoten, Tokyo, 2005, pp. 215-218). The equation for the flow in the tube is expressed as follows:

It has been reported that the blood flow in the tissue is in a laminar flow state with negligible influence of the pulsation associated with cardiac output (Oka Koten: Biorheology. Sohwabo, Tokyo, 1982, p. 35.). Therefore, the present inventors assumed that the blood flow in the tissue of the lung is the above ideal state. Literature values were used for changes in blood viscosity (Shorrock JET et al., Cryobiology. 5 (5): 324-327, 1969). FIG. 7 shows the relationship between blood viscosity and the set blood flow rate. It was also assumed that the decrease in blood flow occurred when the lung tissue temperature fell below 15 ° C. When the temperature change curve calculated by changing the blood flow based on this assumption is adjusted to the actual measurement, the blood flow set value at body temperature (36 ° C) is the maximum value calculated from the cardiac output (72 mm ³ / (g s)) 1.5 times. Therefore, the actual measurement value cannot be explained only by the blood flow rate. Therefore, the maximum blood flow was set to 72 mm ³ / (g · s), and the value calculated from equation (4) was added to the heat conduction calculation as the exothermic term due to metabolism. FIG. 8 shows a cooling temperature history and a temperature change curve calculated based on the above assumption. The maximum temperature difference between the calculated value and the average measured value at each time was 3 ° C. The heat conduction simulator in freeze-thaw necrosis therapy of other parenchymal organs has not been verified by comparison with the actual temperature distribution in vivo (Zhang J et al., S Journal of Biomechanical Engineering. 127 (2): 279 -294, 2005; Zhang A et al., Cryobiology. 47 (2): 143-154, 2003). As described above, the heat conduction simulator was adjusted so that the temperature distribution at the first freezing of a healthy lung in which no bleeding had occurred by in vivo experiments could be estimated. Although the constructed heat conduction simulator is two-dimensional as shown in FIG. 5, since the control experiment is performed in three dimensions, it corresponds to the simulation calculation of the three-dimensional temperature distribution in two dimensions. . The thermophysical value of the tissue after freezing and thawing is different from that before freezing due to the effect of bleeding, but if the bleeding part is set to a finite element model, the constructed heat conduction simulator can estimate the lung temperature distribution at the second and subsequent freezing. Conceivable. When a tumor is present, specific heat, thermal conductivity, and blood vessel distribution are considered to be different from normal. These need to be considered separately.

Example 2 Estimation of treatment area in intraoperative X-ray CT image In clinical cases, the temperature distribution estimated by the heat conduction simulator constructed in Example 1 was compared with the intraoperative X-ray CT image.

  The subjects were two cases of metastatic lung tumor, and the treatment location was in the upper lobe of the right lung. The cryotherapy apparatus was the same as that used in Example 1, and the freezing time was 5 minutes or 7 minutes. Lung density and thermal conductivity were set for each case. Specific heat, blood flow and metabolic fever were the same. FIG. 9 shows an example of an X-ray CT image and a finite element model.

  FIG. 10 is a diagram in which the actual X-ray CT image and the temperature distribution estimated by the heat conduction simulator are overlaid and compared. 10A and 10B are diagrams for different cases. In the figure, the temperature distribution obtained by the thermal conductivity simulator centering on the freezing probe is shown by lines in the regions of −2 ° C., −20 ° C. and −40 ° C. Arrows indicate areas that bleed due to freeze-thaw. The region at -40 ° C is a region that is directly damaged by freezing, and the region at -20 ° C is a region that is necrotized by bleeding (AAGage et al., Cryobiology, Vol. 37, No. 3, pp. 171-186, 1998).

  The frozen region of the lung estimated by the thermal conductivity simulator was about 5 to 10 mm smaller than the actual bleeding region. In addition, the treatment area at the first freezing was estimated to be in a range of about 7 mm from the freezing probe.

It is a figure which shows the ex vivo temperature measurement experiment system for the heat conductivity adjustment of the lung in a heat conduction simulator. It is a figure which shows the positional relationship of the probe for freezing and an outer cylinder. It is a figure which shows the positional relationship of the probe for freezing and the thermocouple at the time of the cooling temperature log | history measurement of pig lung in vivo. It is a figure which shows the installation condition of the probe for freezing and a thermocouple during an in vivo cooling side temperature experiment. It is a figure which shows the finite element model for calculating the temperature at the time of cooling of the lung in vivo. It is a figure which shows the relationship between the heat conductivity of the lung and lung density which were adjusted in the heat conduction simulator. It is a figure which shows the relationship between the blood viscosity and the set blood flow rate. It is a figure which shows the comparison of the cooling temperature history of a lung, and the calculated temperature change curve. It is a figure which shows the example of an X-ray CT image and a finite element model. It is the figure which superposed and compared the temperature distribution estimated by the actual X-ray CT image and the heat conduction simulator. It is a figure which shows the concept of the method of the treatment area estimation in freeze thaw necrosis therapy. It is a figure which shows the flowchart which represents roughly the method for estimating the treatment area | region in freeze thaw necrosis therapy using the heat conduction simulator of this invention. It is a schematic diagram of the apparatus for estimating the treatment area | region in freeze thaw necrosis therapy using a heat conduction simulator. It is an apparatus for estimating the treatment area | region in freeze thaw necrosis therapy using a heat conduction simulator, and is a schematic diagram of the apparatus containing an X-ray CT apparatus and a freeze thaw necrosis therapy apparatus.

Claims (16)

  A method of simulating the heat conduction from the freezing probe of the freeze-thaw necrosis therapy device in the target organ of the freeze-thaw necrosis therapy for cancer by finite element analysis, and estimating the treatment area, the treatment of freeze-thaw necrosis therapy A method of constructing a heat conduction simulator by a finite element method using the heat conductivity of a target organ, simulating heat conduction by the heat conduction simulator, and estimating a treatment region.   The treatment region according to claim 1, wherein a parameter relating to heat conductivity in a heat conduction analysis by a finite element method is adjusted, a parameter relating to heat inflow due to blood flow and metabolic heat is further adjusted, and a heat conduction simulator by the finite element method is constructed. How to estimate.   The method for estimating a treatment region according to claim 1 or 2, wherein the cancer is selected from the group consisting of lung cancer, liver cancer, kidney cancer and prostate cancer.   The method of estimating the treatment area | region of any one of Claims 1-3 which determines the heat conductivity of a treatment object organ for every individual | organization | operated, and builds a heat conduction simulator. A method of simulating the heat conduction of a treatment area of an organ to be treated in freeze thaw necrosis therapy for cancer and estimating a treatment area, wherein at least the following steps (1) to (3) are performed once:
(1) Heat from the freezing probe of the freeze-thaw necrosis therapy apparatus in the target organ using a heat conduction simulator that adjusts the heat conductivity of the target organ for freeze-thaw necrosis therapy, blood flow, and metabolic heat. Simulating conduction, obtaining a temperature distribution around the freezing probe in the organ to be treated, and estimating a frozen region;
(2) A step of comparing X-ray CT image data of an organ subjected to freeze-thaw necrosis treatment with a freeze-thaw necrosis therapy device and a frozen region estimated in step (1); and (3) Freezing by comparison of (2) Estimating a treatment site by melting necrosis therapy.   The method of estimating a treatment area according to claim 5, wherein steps (1) to (3) are repeated a plurality of times.   The method of estimating a treatment region according to claim 6, wherein steps (1) to (3) are repeated two or three times.   The method for estimating a therapeutic region according to any one of claims 5 to 7, wherein the cancer is selected from the group consisting of lung cancer, liver cancer, kidney cancer and prostate cancer. An apparatus for estimating a treatment area in freeze-thaw necrosis therapy for cancer,
(A) In order to simulate the heat conduction from the freezing probe of the freezing and thawing necrosis therapy device in the target organ by adjusting the heat conductivity, blood flow and heat inflow due to metabolic heat of the target organ for the freezing and thawing necrosis therapy Storage means for storing the heat conduction simulator of
(B) a computing means for estimating the temperature distribution of the organ to be treated around the freezing probe by the heat conduction simulator of (a), and
(c) An apparatus including means for displaying the temperature distribution analyzed by the computing means of (b). An apparatus for estimating a treatment area in freeze-thaw necrosis therapy for cancer,
(a) To simulate the heat conduction from the freezing probe of the freeze-thaw necrosis therapy device in the target organ, adjusting the heat conductivity, blood flow and heat inflow due to metabolic heat of the target organ for freeze-thaw necrosis therapy Storage means for storing the heat conduction simulator of
(b) a computing means for estimating the temperature distribution of the organ to be treated around the freezing probe by the heat conduction simulator of (a),
(c) means for receiving X-ray CT image data obtained by the X-ray CT apparatus, and
(d) An apparatus including means for comparing the temperature distribution analyzed by the computing means in (b) with the X-ray CT image data received in (c) and displaying the result.   11. The apparatus according to claim 10, wherein the means for comparing the temperature distribution analyzed by the computing means and the received X-ray CT image data and displaying the result overlaps the temperature distribution on the X-ray CT image.   The apparatus for estimating a treatment region according to any one of claims 9 to 11, wherein the cancer is selected from the group consisting of lung cancer, liver cancer, kidney cancer and prostate cancer.   Furthermore, the apparatus for estimating the treatment area | region of any one of Claims 9-12 containing an X-ray CT apparatus and / or the freeze thaw necrosis therapy apparatus of cancer. A program for simulating the heat conduction at the treatment site in cancer freeze-thaw necrosis therapy and estimating the treatment area,
Computer
(I) To simulate the heat conduction from the freezing probe of the freezing and thawing necrosis therapy device in the target organ by adjusting the heat conductivity, blood flow and heat inflow due to metabolic heat of the target organ for the freezing and thawing necrosis therapy Storage means for storing the heat conduction simulator of
(Ii) a computing means for estimating the temperature distribution of the organ to be treated around the freezing probe by the heat conduction simulator of (i), and
(iii) A program for functioning as a means for displaying the temperature distribution in the treated organ analyzed by the computing means of (ii).   Furthermore, the computer (iv) means for receiving X-ray CT image data, (v) comparing the temperature distribution in the treated organ analyzed by means of (iii) and the X-ray CT image data received by means of (iv) The program for estimating the treatment area | region of Claim 14 for functioning as a means to display and the means to display the result compared by the means of (vi) (v).   The program for estimating a treatment region according to claim 15, wherein the cancer is selected from the group consisting of lung cancer, liver cancer, kidney cancer and prostate cancer.

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