JP5105330B2 - Puncture planning support apparatus and program thereof, and insertion condition determination method - Google Patents

Description

  The present invention relates to a puncture planning support apparatus, a program for the same, and a puncture condition determination method, and more particularly, before performing puncture treatment on a living tissue such as an organ or the like, the puncture position of the needle and the puncture The present invention relates to a puncture planning support apparatus that can determine whether or not a puncture condition such as an angle is acceptable by simulation, a program thereof, and a puncture condition determination method.

  In recent medical treatment, a minimally invasive treatment with less burden on the patient is demanded. Among them, a puncture treatment method in which an affected part such as an organ is punctured and treated is attracting attention. Examples of this puncture treatment include PEIT (percutaneous ethanol injection) and RFA (radiofrequency ablation) used for the treatment of liver cancer and the like. PEIT is a therapy in which a cancer cell is necrotized by inserting a needle into the cancer cell and injecting ethanol into the cancer cell from the needle tip. RFA is a needle that penetrates the cancer cell and the needle tip. Is a therapy that causes cancer cells to become necrotic by giving high heat from radio waves to cancer cells. Here, when a target such as a cancer cell to be punctured exists inside the living tissue, the needle must be inserted from the surface of the living tissue to reach the target inside the living tissue. However, since an organ such as a liver to be punctured is composed of a soft tissue, the organ is deformed by a pressing force on the organ at the time of puncture, and the position of the target moves with the deformation. Therefore, in order to accurately reach the tip of the needle to the target, it is necessary to plan the puncture route in consideration of the deformation of the living tissue at the time of puncture, and this planning requires considerable skill, A lot depends on experience and intuition. In particular, it is said that the liver, which is one of the softest organs, is difficult to plan a puncture route even for a skilled doctor.

By the way, the present applicant has already proposed a puncture control device applied to a surgery support robot that employs a master / slave system or the like (see Patent Document 1). This puncture control device is a device that controls the operation of the manipulator that holds the needle so that the needle accurately reaches the target of the biological tissue to be punctured. Specifically, after the needle has been stabbed into the living tissue, the situation of the tip portion of the needle moving through the living tissue is judged from the image data, and the tip of the needle is bent in the living tissue. Then, the operation of the manipulator on the slave side is controlled so as to correct the puncture path in consideration of the bending.
JP 2006-271546 A

  However, the device of Patent Document 1 corrects the path of the needle after the needle is inserted into the living tissue, and before the needle is inserted into the living tissue, the insertion position and the insertion angle of the needle with respect to the living tissue. It is not determined whether the insertion conditions such as are appropriate. Therefore, even when using the surgery support robot to which the control device of Patent Document 1 is applied, the puncture route is determined by determining the optimum puncture conditions in the same manner as when directly puncturing a living tissue with a doctor's hand. Must be planned. This planning is performed on the assumption that the needle moves linearly toward the target after the needle is inserted into the living tissue. Here, during the period from when the needle is applied to the surface of the living tissue until the living tissue is cut, the living tissue is pressed. If the living tissue is a soft tissue, the living tissue is as described above. The position of the target moves greatly with the deformation. And after a biological tissue is cut | disconnected with a needle | hook, there is little change of the deformation | transformation state of a biological tissue, and the position change of a target is small in the process in which a needle | hook moves within a biological tissue.

  As described above, when planning a puncture route, the state of deformation of the living tissue until the surface of the living tissue is cut by the needle must be considered, and the displacement of the target position accompanying the deformation must be grasped. . However, according to the experiments by the present inventors, when puncturing a living tissue multiple times under the same individual and under the same conditions, the tip position of the needle at the time of cutting is not necessarily the same, and the living tissue always with the same pressing force. It has been proved that is not cut, and this situation is considered to be caused by the microscopic state of the tissue. In other words, even if the same individual is punctured under the same puncture conditions, the pressing force required to cut the biological tissue varies depending on the case, so that the living tissue immediately before the needle enters the biological tissue The deformation state is not always constant, and the position of the target at this time is not necessarily constant. Therefore, in order to accurately determine the quality of the insertion conditions such as the needle insertion position, the insertion angle, and the insertion speed, the tip position of the needle immediately before the biological tissue is cut is changed within an assumed range. However, it is necessary to judge whether or not the target can be punctured for each tip position and to evaluate them comprehensively.

  The present invention has been devised in view of the above-described problems, and its purpose is to comprehensively consider a puncture situation assumed at the time of cutting a living tissue, and to perform a predetermined insertion. An object of the present invention is to provide a puncture planning support apparatus capable of determining a condition, a program thereof, and a puncture condition determination method.

In order to achieve the above object, the present invention provides a puncture for determining a puncture condition by calculation using a model when a puncture condition of a needle for puncturing from the outside of a living tissue toward an internal target is input. A planning support device,
When calculating a plurality of tip positions of the needle just before the surface of the living tissue is cut, for each of the tip positions, stress calculation for obtaining stress of the living tissue in the vicinity of the tip position from the insertion condition And a position of the target at each tip position, and a position error that is a distance between the movement line of the needle extending from the outside of the living tissue to the target and the target is determined for each tip position. An error calculation means obtained for the case and a probability density function representing a variation in stress of the biological tissue when the biological tissue cuts, and a cutting probability due to the stress obtained by the stress calculation means for each of the respective tip positions An expected value calculation means for obtaining an expected value of the position error from the cutting probability, and based on the expected value And a determination means for determining the entry conditions, adopts a configuration that.

  In addition, it is preferable to further include a model creation unit that creates a model of the biological tissue from image data of the biological tissue acquired in advance, and the stress and position error are calculated using the model.

  Furthermore, the insertion conditions can be the needle insertion position and the insertion angle.

  Further, the insertion conditions may be the needle insertion position, the insertion angle, and the insertion speed.

  Furthermore, the determination means can determine that the insertion condition is appropriate when the expected value is equal to or less than a predetermined threshold value.

  Further, the determination means may determine that the insertion condition that provides the minimum expected value among the expected values of the plurality of input insertion conditions is optimal.

Furthermore, the present invention provides a puncture planning support apparatus that, when a needle insertion condition for puncturing from the outside of a living tissue toward an internal target is input, the insertion condition is determined by calculation using a model. A program that allows the computer to function,
When calculating a plurality of tip positions of the needle just before the surface of the living tissue is cut, for each of the tip positions, stress calculation for obtaining stress of the living tissue in the vicinity of the tip position from the insertion condition And a position of the target at each tip position, and a position error that is a distance between the movement line of the needle extending from the outside of the living tissue to the target and the target is determined for each tip position. An error calculation means obtained for the case and a probability density function representing a variation in stress of the biological tissue when the biological tissue cuts, and a cutting probability due to the stress obtained by the stress calculation means for each of the respective tip positions An expected value calculation means for obtaining an expected value of the position error from the cutting probability, and based on the expected value As the determination means for the determination of the input conditions, it adopts a configuration that causes the computer to function.

Further, the present invention provides a puncture condition determination method for determining a puncture condition by calculation using a model when a puncture condition of a needle for puncturing from the outside of a living tissue toward an internal target is input. There,
When calculating a plurality of tip positions of the needle just before the surface of the living tissue is cut, for each of the tip positions, stress calculation for obtaining stress of the living tissue in the vicinity of the tip position from the insertion condition A position of the target at each tip position, and a position error that is a separation distance between the movement line of the needle extending from the outside of the living tissue to the target and the target. An error calculation step obtained for the case, and a probability density function representing a variation in stress of the biological tissue when the biological tissue is cut, and a cutting probability due to the stress obtained in the stress calculation step for each of the respective tip positions An expected value calculation step for obtaining an expected value of the position error from the cutting probability, and the expected value Sequentially performed and a determination step of determining the insertion condition based on adopts a technique called.

  According to the present invention, the position error for a previously entered insertion condition is determined based on the cutting probability for each tip position of the needle that may be cut on the surface of the living tissue and the position error with the target at each tip position. The expected value is determined, and the insertion condition is determined probabilistically based on the expected value. Therefore, comprehensive determination of the insertion conditions can be performed in consideration of the probability of occurrence at each target position assumed when the biological tissue is cut, and the insertion conditions can be accurately determined.

  In particular, by providing the model creation means, it is possible to determine the insertion condition based on the model of the patient who is the target of the puncture treatment, and the accuracy of the determination can be further improved.

  Further, by adding the insertion speed to the insertion conditions, the viscoelastic characteristics of the living tissue can be taken into consideration, and a more accurate determination with respect to the insertion conditions becomes possible.

  Hereinafter, embodiments of the present invention will be described with reference to the drawings.

  FIG. 1 shows a functional block diagram of a puncture planning support apparatus according to an embodiment of the present invention. In this figure, the puncture planning support apparatus 10 uses a model to simulate the puncture conditions set in advance before the puncture treatment for inserting a needle into an organ as a biological tissue. This is a device for judging whether the product is good or bad. This puncture planning support apparatus 10 is composed of a predetermined computer, and a program for causing the computer to function as the following means is installed. In the present embodiment, the insertion position that is the position of the organ surface where the needle is inserted and the insertion angle that is the angle of the needle with respect to the organ surface when the needle is applied to the organ surface are used as the insertion conditions.

  The puncture planning support apparatus 10 includes a model creating unit 11 that creates a model of the organ from image data of the organ acquired in advance, and a tip position of the needle just before the organ surface is cut (hereinafter simply referred to as “cutting position”). The stress calculation means 12 for obtaining the stress of the organ in the vicinity of the insertion position of the needle at that time from the previously entered insertion conditions for each of the cutting positions, A predetermined puncture target position is obtained for each cutting position, and a position error, which is a distance between the needle movement line extending from the outside of the organ in the target direction and the target, is determined for each cutting position. The position error is calculated using a predetermined probability density function based on the error calculation means 13 to be obtained and the values obtained by the stress calculation means 12 and the error calculation means 13. The expected value calculation unit 14 for obtaining an expected value, and a determination unit 15 for the determination of the penetration conditions based on the expected value.

  The model creation means 11 includes a storage unit 18 in which basic data such as an organ modulus and Poisson's ratio are stored for each organ tissue (parenchymal cells, blood vessels, nerves, etc.), and a magnetic image resonance diagnostic apparatus (MRI). A shape position specifying unit 19 for determining the overall shape of the organ and the position of each constituent tissue based on the image data captured by the image capturing apparatus C such as a computed tomography apparatus (CT scan), an ultrasonic diagnostic imaging apparatus, and the like An element dividing unit 20 that divides the organ into a plurality of elements based on the shape of the organ obtained by the unit 19, and a relationship between the external force and the displacement is determined for each element based on the basic data stored in the storage unit 18, A rigid body equation determination unit 21 that obtains a rigid body equation representing the relationship between an external force vector acting on an organ and a displacement vector of the organ by a finite element method is provided.

  As shown in FIG. 2A, the stress calculating means 12 is created by the model creating means 11 when the needle 25 is inserted, that is, when the insertion position P and the insertion angle θ are input in advance. Using the organ model 26, the stress in the vicinity of the insertion position P of the needle 25, which is the pressing portion P of the organ, is obtained. That is, assuming that the tip position of the needle immediately before the organ cuts varies depending on the case, the cutting position, which is the needle tip position at that time, is continuously changed within a predetermined range, and each cutting position is Using the rigid body equation obtained by the rigid body equation determining unit 21 of the model creating means 11, the pressing force of the needle at the pressing portion P and the stress of the nearby organ are calculated. Details will be described later.

  The error calculation means 13 assumes that the needle moves linearly, and for each cutting position changed by the stress calculation means 12, the target T with respect to the needle movement line K extending linearly in the needle insertion direction. A position error L that is the shortest distance between the reference points is calculated. That is, the position error L is the length of a straight line perpendicular to the movement line K from the reference point of the target T. Here, when the target T is composed of a region such as a cancer cell, the reference point of the target T is set to an arbitrary point in the region, for example, the center of gravity or the center. As illustrated in FIGS. 2A and 2B, the position error L is such that the position and shape of the target T differ when the tip position (cutting position) of the needle immediately before the organ cuts is different. Become.

  The expected value calculation means 14 stores in advance a probability density function determined by experiments or the like. This probability density function represents the variation in stress when the organ cuts, that is, the cutting probability distribution of the pressing portion P with respect to the stress of the organ in the vicinity of the pressing portion P. As will be described later, the expected value calculation means 14 calculates an expected value of the position error L by a probability distribution using a probability density function.

  The determination means 15 takes into account that when the expected value of the position error L calculated by the expected value calculation means 14 is equal to or less than a predetermined threshold, the amount of displacement of the needle tip immediately before the needle enters the organ changes depending on the situation. Even so, it is determined that the input insertion conditions are appropriate, assuming that there is a high probability that the target T can be accurately punctured. On the other hand, when the expected value of the position error L exceeds the threshold value, it is determined that the input insertion condition is inappropriate because the probability that the target T can be accurately punctured is low.

  Next, processing performed by the puncture planning support apparatus of the present embodiment will be described below using the flowchart of FIG. In the following description, the organ to be processed will be described as an example of the liver, but the present invention is not limited to this.

  First, in the model creation means 11, based on the image data imaged by the imaging device C, the patient's liver to be puncture treated is modeled by the following procedure (model creation step: S101).

  Here, basic data on the elastic modulus and Poisson's ratio of a general human liver that has been scientifically elucidated is stored in the storage unit 18 for each liver constituent tissue such as hepatocytes (liver parenchymal cells), blood vessels, and nerves. It is remembered.

  After the patient's liver is imaged by the imaging device C, the shape position specifying unit 19 sets the shape of the liver and the position of each constituent tissue of the liver from the image data of the imaging device C as follows. That is, based on the image data, a three-dimensional shape of the liver or a two-dimensional shape of a predetermined cross section is derived by known image processing using a computer, and the constituent tissues (liver parenchymal cells, blood vessels, nerves) Etc.) is identified. In addition, the shape of the liver and / or the position of each constituent tissue may be set by manual input by a doctor who visually recognizes the image data, instead of the automatic processing described above. Also, the target T such as cancer cells is identified in the same manner.

  Next, the element dividing unit 20 designates the shape of the element M in the finite element method and the number of nodes (nodes N) of each element M, and uses a known method such as the Delaunay method, and the shape position specifying unit 19 The whole liver is divided into a plurality of regions from the shape of the liver obtained in step 1, and a mesh (see FIG. 2A) is generated. In FIG. 2A, in order to avoid complication of the drawing, the element M is described only in a partial region of the liver model 26, and the description of the element M in the remaining region is omitted.

以上の剛性方程式により、各ノードＮに作用する強制変位が特定できれば、そのノードＮに作用する外力ベクトルＦと、各ノードＮの変位や各要素Ｍの応力が算出可能となる。 Thereafter, the rigid body equation determination unit 21 determines the rigid body equation using the finite element method as follows. That is, first, by comparing the position of each constituent tissue of the liver obtained by the shape position specifying unit 19 with each element M determined by the element dividing unit 20, each element M is assigned to which constituent tissue of the liver. It is specified whether this is the case. Then, for each element M, a corresponding tissue is selected from the elastic modulus and Poisson's ratio of the liver stored for each constituent tissue in the storage unit 18, and nodes around each element M are obtained by a known structural calculation. A relational expression between the load applied to N and the deformation information of the element M is obtained. The deformation information here refers to the displacement of the node N constituting the element M and the stress and strain acting on the element M. Then, the stiffness equation of the entire liver model is obtained from the relational expression. Here, the stiffness equation can be expressed by the relationship of the following equation (1), assuming that the external force vector F acting on each node N, the entire stiffness matrix K, and the displacement vector U of the node N are represented.

If the forced displacement acting on each node N can be specified by the above stiffness equation, the external force vector F acting on the node N, the displacement of each node N, and the stress of each element M can be calculated.

  Further, for the created liver model 26, a node N corresponding to the needle insertion position P (pressed portion P) on the liver surface (hereinafter referred to as “insertion node N”) is specified and exists in the liver. A node N (hereinafter referred to as “target node N”) corresponding to the reference point of the target T such as a cancer cell to be identified is identified.

  Thereafter, the insertion position P and insertion angle θ arbitrarily set are input into the apparatus as insertion conditions.

  Next, the stress calculation means 12 performs the following simulation using the liver model 26 created by the model creation means 11, so that the stress in the vicinity of the pressed portion P due to the previously entered insertion conditions is as follows: (Stress calculation step: S102).

  Here, the calculation is performed on the assumption that the needle presses the insertion node N (pressing portion P) at a predetermined speed at a predetermined insertion angle θ and the insertion node N is forcibly displaced. That is, it is assumed that the external force acting in the liver model 26 acts only on the insertion node N only in a certain direction. Then, the position (displacement amount) of the insertion node N serving as the cutting position is continuously changed, and for each cutting position, one element M including the insertion node N (hereinafter referred to as “insertion element M”). The stress σ in the vicinity of the needle, which is a scalar stress of the In FIG. 2A, the area of the insertion element M is shaded for convenience of explanation.

  Specifically, from the condition that the position of the insertion node N is known and an unknown external force vector F (pressing force) acts only on the insertion node N, the liver model including the target node N is obtained by the above equation (1). A displacement vector U and an external force vector F of each node N in the node 26 are obtained. Then, when the position of each node N is obtained in this way, Mises which becomes a scalar value of the stress in the insertion element M by the structural calculation using the elastic modulus and Poisson's ratio of the corresponding constituent stored in the storage unit 18. The stress σ is determined. The stress σ obtained here may be obtained by other methods as long as it can be obtained as a scalar value. Then, the stress σ of the insertion element M is obtained for each cutting position while changing the displacement amount of the insertion node N. As the stress σ near the needle here, a plurality of elements M around the insertion node N are targeted, and the scalar stress σ obtained for each element M is averaged in one element M unit. But you can.

  Next, the error calculation means 13 calculates the position error L of the needle tip position with respect to the target T for each external force vector F changed by the stress calculation means 12 (error calculation step: S103). That is, first, when the cutting position is set to a certain value, the position of the target node N is calculated by solving the rigid body equation of the above equation (1). Then, the shortest distance between the position of the target node N at this time and the movement line K set so that the tip of the needle moves linearly along a preset insertion direction is calculated. The shortest distance is a position error L (d) determined in accordance with the displacement amount d (see FIG. 2B) of the insertion node N at this time. This position error L is obtained for each cutting position assumed by the stress calculation means 12.

  Thereafter, the expected value calculation means 14 calculates the expected value IP of the position error L using the following equations (2) and (3) (expected value calculation step: S104).

ここにおいて、α、βは、ガンマ分布のパラメータ（定数）である。 First, the scalar stress σ of the insertion element M obtained for each cutting position by the stress calculation means 12 is substituted into the probability density function of the following equation (2) using the gamma distribution, and the liver for each cutting position. The surface cutting probability f (σ) is obtained.

Here, α and β are parameters (constants) of the gamma distribution.

  In this embodiment, the gamma distribution is used as the probability density function, but other distribution functions such as a normal distribution may be used.

Then, an expected value IP of the position error L is obtained by the following equation (3). That is, here, the position error L (d) at that time obtained by the error calculating means 13 is set to the cutting probability f (σ) with respect to the stress value σ of the insertion element M when the displacement d of the needle tip is a certain value. The expected value IP can be obtained by multiplying the values and obtaining this value for each displacement amount d and summing the values.

  Finally, the determination unit 15 determines whether the puncture condition input in advance is good or not based on whether or not the expected value IP of the position error L calculated by the above equation (3) is equal to or less than a preset threshold (determination step: S105). ). That is, here, if the position error L is equal to or less than the threshold value, it is highly possible that the target T having a certain region can be punctured even if the tip position of the needle immediately before entering the liver changes. It is determined that the input puncture position P and puncture angle θ are appropriate. On the other hand, if the expected value IP exceeds the threshold value, it is determined that the input puncture position P and puncture angle θ are inappropriate, and the same calculation as described above is performed for other insertion conditions until an appropriate insertion condition is found. Is done. The threshold value here may be set in consideration of the size of the target T.

  Therefore, according to such an embodiment, even if the tip position of the needle immediately before cutting the organ surface changes depending on the situation, it is set before the puncture treatment from the viewpoint of whether or not the target T can be punctured. The quality of puncture position P and puncture angle θ can be determined. As a result, when a puncture treatment is performed directly by a doctor or when a puncture treatment is performed using a master-slave type surgical robot, the deformation state of the organ when the needle enters the organ changes and the target T Even if the position is slightly deviated, it is possible to simulate in advance a puncture route in which there is a high possibility that a needle can be inserted into the target T.

ここで、Ｃは、粘性マトリックスである。
そして、この変形例においては、上式（１）に代えて上式（４）を使うことにより、前述したように応力σと位置誤差Ｌが求められ、前述と同様に期待値ＩＰが求められて、予め入力した刺入位置Ｐ、刺入角度θ及び刺入速度の良否が判定される。 As a modification of the above embodiment, a configuration is adopted in which, in addition to the insertion position P and the insertion angle θ, the insertion speed is input in advance as the insertion condition, and the quality of the insertion condition can be determined. You can also. In this case, the model creating means 11 stores a viscoelastic coefficient as basic data for each constituent tissue of the organ in addition to the elastic modulus and Poisson's ratio of the organ, and creates a model 26 taking into account the insertion speed. The equation at this time is the following equation using a viscoelastic model.

Here, C is a viscous matrix.
In this modification, by using the above equation (4) instead of the above equation (1), the stress σ and the position error L are obtained as described above, and the expected value IP is obtained similarly to the above. Thus, it is determined whether or not the insertion position P, the insertion angle θ, and the insertion speed that have been input in advance are acceptable.

  Further, for the embodiment and the modification, a plurality of different insertion conditions are input at a time, or a plurality of insertion conditions are automatically generated in the apparatus, and the determination means 15 The insertion condition for which the expected value IP is obtained may be presented as the optimum condition.

  Further, the model creation means 11 can be omitted by storing the predetermined organ model 26 in the apparatus in advance without creating the organ model 26 using the imaging data of the imaging apparatus C.

  In addition, the configuration of each part of the apparatus in the present invention is not limited to the illustrated configuration example, and various modifications are possible as long as substantially the same operation is achieved.

The functional block diagram of the puncture planning assistance apparatus which concerns on this embodiment. (A) is a conceptual diagram of an organ (liver) for explaining elements and nodes in the finite element method, and (B) conceptually shows a state when an organ cutting condition is different from (A). FIG. The flowchart which shows the process sequence in the said puncture planning apparatus.

Explanation of symbols

DESCRIPTION OF SYMBOLS 10 Puncture planning support apparatus 11 Model preparation means 12 Stress calculation means 13 Error calculation means 14 Expected value calculation means 15 Determination means 26 Model K Movement line L Position error P Insertion position (pressed portion)
T target θ Insertion angle

Claims (8)

A puncture planning support apparatus for determining the puncture condition by calculation using a model when inputting the puncture condition of a needle when puncturing toward the internal target from the outside of the living tissue,
When calculating a plurality of tip positions of the needle just before the surface of the living tissue is cut, for each of the tip positions, stress calculation for obtaining stress of the living tissue in the vicinity of the tip position from the insertion condition And a position of the target at each tip position, and a position error that is a distance between the movement line of the needle extending from the outside of the living tissue to the target and the target is determined for each tip position. An error calculation means obtained for the case and a probability density function representing a variation in stress of the biological tissue when the biological tissue cuts, and a cutting probability due to the stress obtained by the stress calculation means for each of the respective tip positions An expected value calculation means for obtaining an expected value of the position error from the cutting probability, and based on the expected value Lancing planning support apparatus characterized by comprising a determining means for determining the entry conditions.   The puncture planning according to claim 1, further comprising model creation means for creating a model of the biological tissue from image data of the biological tissue acquired in advance, and calculating the stress and position error using the model. Support device.   The puncture planning support apparatus according to claim 1, wherein the insertion conditions are a needle insertion position and a needle insertion angle.   The puncture planning support apparatus according to claim 1, wherein the insertion conditions are a needle insertion position, a needle insertion angle, and a needle insertion speed.   The puncture planning support apparatus according to claim 1, wherein the determination unit determines that the insertion condition is appropriate when the expected value is equal to or less than a predetermined threshold value.   The determination means determines that the insertion condition from which a minimum expected value is obtained among the expected values of the plurality of input insertion conditions is optimal. The puncture planning support device according to any one of the above. A program that causes the computer of the puncture planning support apparatus to function so as to determine the puncture condition by calculation using a model when inputting the puncture condition of the needle when puncturing from the outside of the living tissue toward the internal target Because
When calculating a plurality of tip positions of the needle just before the surface of the living tissue is cut, for each of the tip positions, stress calculation for obtaining stress of the living tissue in the vicinity of the tip position from the insertion condition And a position of the target at each tip position, and a position error that is a distance between the movement line of the needle extending from the outside of the living tissue to the target and the target is determined for each tip position. An error calculation means obtained for the case and a probability density function representing a variation in stress of the biological tissue when the biological tissue cuts, and a cutting probability due to the stress obtained by the stress calculation means for each of the respective tip positions An expected value calculation means for obtaining an expected value of the position error from the cutting probability, and based on the expected value As the determination means for the determination of the input conditions, the puncture planning support apparatus for a program for causing the computer to function. When a needle insertion condition for puncturing from the outside of a living tissue toward an internal target is input, the insertion condition determination method for determining the insertion condition by calculation using a model,
When calculating a plurality of tip positions of the needle just before the surface of the living tissue is cut, for each of the tip positions, stress calculation for obtaining stress of the living tissue in the vicinity of the tip position from the insertion condition A position of the target at each tip position, and a position error that is a separation distance between the movement line of the needle extending from the outside of the living tissue to the target and the target. An error calculation step obtained for the case, and a probability density function representing a variation in stress of the biological tissue when the biological tissue is cut, and a cutting probability due to the stress obtained in the stress calculation step for each of the respective tip positions An expected value calculation step for obtaining an expected value of the position error from the cutting probability, and the expected value Insertion condition determination method characterized by performing the determination step of the determination of the insertion condition in order on the basis of.

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