JP4507097B2 - Implant three-dimensional surgical planning system based on optimal balance between morphological and functional evaluation - Google Patents

Description

  The present invention relates to an implant three-dimensional surgical planning system. More particularly, the present invention relates to a technique for facilitating and precise selection of an implant to be used when performing an operation using the implant.

  The conventional surgical plan is performed by adjusting the magnification on the 2D X-ray image and assigning the template and pattern of the artificial joint part. It is very difficult to determine a surgical plan.

  Therefore, in more recent research, a three-dimensional bone shape model is constructed from the multi-slice CT that is becoming more generalized, and a three-dimensional installation position and angle are automatically drafted from objective evaluation values and shape characteristics based on the shape data. The system is being developed (Non-Patent Document 1 = Tomohito Sakai, Automatic placement of implants based on shape information in the artificial hip surgery planning system, 12th Annual Meeting of the Japan Society for Computer Aided Surgery, (2003), pp.47-48 Non-patent document 2 = Kagiyama, Y. et al, Automated preoperative 3D planning of acetate tabular cup positioning and size selection in total hip arthroplasty using CT data, Proceedings of CAOS, (2004), pp.312-313.).

  An automatic surgery planning system with a cup and a stem alone has already been developed, and it has been confirmed that 80% of applicable cases for cups can be adopted by specialists for all cases with stems. These are designed automatically for the fixed pelvis and femur individually, but as an artificial hip joint surgery plan, the installation plan should be made in a lump so that both the pelvis side and the femur side are joined. Is needed. For this reason, an automatic cup planning system for stems and stems was integrated, and a system for adjusting artificial joint parts was developed. In this technique, since a Freeman stem in which the stem and the neck are integrated is targeted, adjustment by the neck alone is not included.

  In a conventional implant surgery planning system, the spatial relationship between the patient's 3D skeletal shape reconstructed from medical images and the 3D shape of the implant is visualized by a graphics computer, and based on the visualized relationship, the surgeon selects the most appropriate for the patient. The selection of the implant and the determination of the installation position and angle were performed. In 2002, it was proposed at the Ritzori Institute in Italy to visualize the distance distribution between the implant surface and the patient's skeleton three-dimensionally as reference information for more quantitative determination of conformity. (Non-Patent Document 3 = Testi D, Simeoni M, Zannoni C, Viceconti M. Validation of twoalgorithms to evaluate the interface between bone and orthopaedic implants.Comput Methods Programs Biomed. 2004 May; 74 (2): 143-50) There is no change based on the judgment of the surgeon. More recently, in 2003, an attempt was made at Osaka University to select an optimal implant and let the computer automatically determine the installation position and angle (Non-patent Document 4 = NakamotoM, Sato Y, Sugano N, Sasama T , Nishii T, Pak PS, Akazawa K, Tada Y, YoshikawaH, and Tamura S. Automated CT-based 3D surgical planning for total hipreplacement: A pilot study, Computer Assisted Radiology and Surgery: 17th International Symposium and Exhibition (Proc. CARS2003), London, 389-394, 2003). This technique partially uses leg length consistency related to walking function, but does not use comprehensive function evaluation including joint range of motion and peri-joint soft tissue length. In addition, from 2000 to 2003, the joint movable range that directly affects the joint function has been evaluated at the University of Da Cang and Carnegie Mellon University (Non-patent Document 5 = JaramazB, Nikou C, Simon DA). , DiGioia AM III. Range Of Motion After Total HipArthroplasty: Experimental Verification Of The Analytical Simulator. LectureNotes in Computer Science, 1205 (First Joint Conference of CVRMed II and MRCASIII (Proc. CVRMed-MRCAS'97), Grenoble, France), 573 -582, 1997) are also used as reference information for comprehensive judgments made by surgeons, and no further analysis of the results by a computer has been reported.

  Patent Literature 1 describes software for creating an orthopedic surgical plan. When the software is executed by a computer processing unit, the processing unit defines a 3D (three-dimensional) template model of the patient's bone and a plurality of digitized 2D (two-dimensional) X of the patient's bone. A process for storing a line image in a computer storage device, a process for extracting a 2D reference shape of a patient's bone from each of a plurality of digitized 2DX line images, and a 3D template model using the 2D reference shape of the patient's bone Deformation is performed to minimize the error between the contour of the patient's bone and the contour of the deformed 3D template model. Further, the arithmetic processing device reads digital data associated with the deformed 3D template model of the patient's bone, and generates a surgical plan for the patient's bone based on analysis of the digital data associated with the deformed 3D model. Also do. However, these do not use comprehensive function evaluation including the range of motion of the joint and the soft tissue length around the joint, and do not describe that the comprehensive judgment made by the surgeon is further analyzed by a computer.

  Patent Document 2 discloses a system for determining an ideal theoretical position of a knee prosthesis. In order to determine the position of a tibial prosthesis, the shape of the base of the tibia and its position are determined based on the ankle joint. Means for determining the center, means for determining the high point of the tibial plateau, and the following parameters: the perpendicular to the cross section passing through the center of the prosthetic leg also passes through the center of the ankle joint, the cross section is fixed Is located at a distance from the higher point equal to the height of the prosthetic leg, the large leg of the prosthetic leg is in the center of the large end of the cross-section of the tibia in the cross section, and the small end of the prosthetic leg The ankle position, orientation, and size correspond to the tibial prosthesis and the tibial prosthesis, taking into account that the front edge of the limb is at a distance from the small end of the tibial cross section within the cross section Calculate for cross-section tibia And stage, in the prosthetic foot of the cross-section, means for large end of the prosthesis to determine the direction to be parallel to the horizontal axis of the knee, to a system comprising a. However, these do not use comprehensive function evaluation including the range of motion of the joint and the soft tissue length around the joint, and do not describe that the comprehensive judgment made by the surgeon is further analyzed by a computer.

Patent Document 3 describes the provision of a support system for application software and a method thereof for enabling image processing to be performed locally in a medical institution without transferring image data. This document is a remote image analysis system in which a plurality of processing terminals and a host computer of an image processing center are communicably connected, and the image processing desired by the processing terminal is obtained from information on the hardware and software configuration of the processing terminal. A remote image analysis system that does not require transfer of image data and a method therefor are described in which application software including control code required for execution is provided from a host computer and image processing or the like is executed locally.
Tomohito Sakai, Automatic placement of implants based on shape information in an artificial hip surgery planning system, Proceedings of the 12th Japan Computer Surgery Society, (2003), pp. 47-48 Kagiyama, Y .; et al, Automated preferential 3D planning of aceticable cup positioning and size selection in total hippotherapy using CT data, Proceedings OS. 312-313 Testi D, Simeoni M, Zannoni C, Viceconti M. Validationof two algorithms to evaluate the interface between bone and orthopaedicimplants.Comput Methods Programs Biomed. 2004 May; 74 (2): 143-50 NakamotoM, Sato Y, Sugano N, Sasama T, Nishii T, Pak PS, Akazawa K, Tada Y, YoshikawaH, and Tamura S. Automated CT-based 3D surgical planning for total hipreplacement: A pilot study, Computer Assisted Radiology and Surgery: 17th International Symposium and Exhibition (Proc. CARS2003), London, 389-394, 2003 Jaramaz B, Nikou C, SimonDA, DiGioia AM III.RangeOf Motion After Total Hip Arthroplasty: Experimental Verification Of TheAnalytical Simulator. Lecture Notes in Computer Science, 1205 (First Joint Conference of CVRMed II and MRCAS III (Proc. CVRMed-MRCAS'97) , Grenoble, France), 573-582, 1997 Special table 2003-530177 Special table 2004-512136 JP 2004-334403 A

  The present invention makes it possible to automatically perform surgical planning of implant parts based on objective criteria and the like, reducing the burden area of surgeons and the level of implant surgery by surgeons that have relied on skills so far. The problem is to keep it above a certain level.

  The present invention is a system for comprehensive evaluation of morphological evaluation and functional evaluation, where the morphological evaluation includes the relative compatibility between the three-dimensional shape of the patient skeleton and the three-dimensional shape size of the implant, The evaluation includes leg length, joint range of motion, soft tissue length around the joint, stress distribution, bone mass evaluation such as inner wall thickness, front wall thickness, rear wall thickness, bone density (bone quality) evaluation, and the like.

  Accordingly, the present invention is characterized by performing comprehensive evaluation of form evaluation and function evaluation, and balance adjustment of an evaluation item and a learning function.

Thus, the present invention provides the following.
(1) A method of selecting an implant component for obtaining a desired result in a surgical operation,
A) obtaining subject patient information;
B) obtaining information on the implant part to be implanted;
C) generating an evaluation function using the patient information and the implant part information; and D) selecting an implant part to be actually used for surgery based on the evaluation function. .
(2) The method according to item 1, wherein the evaluation function includes an internal parameter and a weight parameter between evaluation items of the evaluation function.
(3) The method according to item 2, comprising adjusting the internal parameter and the weight parameter in selecting the implant part.
(4) The method according to item 3, wherein the adjustment of the internal parameter and the weight parameter includes adjustment based on a correction result database.
(5) The method according to item 4, wherein the correction result database is an accumulated database of results obtained by a surgeon manually correcting a plan.
(6) The method according to item 1, wherein the evaluation function performs at least one evaluation selected from the group consisting of form evaluation and function evaluation.
(7) The method according to item 1, wherein the evaluation function performs an evaluation including a form evaluation and a function evaluation.
(8) The method according to item 7, wherein the morphological evaluation is determined based on a single parameter of the implant part.
(9) The method according to item 7, wherein the functional evaluation is determined based on a plurality of parameters of the implant part.
(10) The method according to item 7, wherein the functional evaluation includes one or more items selected from the group consisting of leg length, range of joint motion, periarticular soft tissue length, and periarticular soft tissue length.
(11) The morphological evaluation is one or more selected from the group consisting of the three-dimensional shape of the patient skeleton, the three-dimensional structure of the implant part, the size of the implant part, and the relative compatibility between the patient skeleton and the implant part 8. A method according to item 7, comprising a large number of items.
(12) The method according to item 1, further including a step of selecting a desired number of candidates from the evaluation values output in the evaluation function.
(13) The method according to item 1, wherein the patient information is obtained by taking a CT image or an MR image, or obtained by deforming a general three-dimensional model based on a two-dimensional X-ray image. .
(14) The method according to item 13, further comprising the step of creating a three-dimensional shape model from the CT image, MR image, or two-dimensional X-ray image.
(15) The method according to item 14, wherein, in the three-dimensional shape model, the plurality of skeletons forming the joint are created as separate three-dimensional shape models.
(16) The shape evaluation is performed by inputting a three-dimensional shape model of the implant part and a three-dimensional shape model of patient information to a computer, and matching based on a relative relationship between a single implant model and a single bone model. 8. A method according to item 7, comprising defining an evaluation function.
(17) The function evaluation according to item 7, including defining a function evaluation function reflecting each function based on a relative relationship between the information of the plurality of implant parts and the plurality of patient information. Method.
(18) The evaluation function includes evaluating morphological evaluation and functional evaluation. The morphological evaluation inputs a three-dimensional shape model of the implant part and a three-dimensional shape model of patient information to a computer, and Defining a fitness evaluation function based on a relative relationship between a single implant model and a single bone model, wherein the functional evaluation is based on a relative relationship between a plurality of the implant part information and a plurality of the patient information. And defining a function evaluation function reflecting each function, and defining an overall evaluation function for each of the conformity evaluation function and the function evaluation function by individual linear sums, products, or a combination thereof. The method according to Item 1.
(19) The method according to item 18, wherein the selection includes selecting, as an optimal solution, the size, position, and direction of the implant part to be maximized or minimized in the overall evaluation function.
(20) The method according to item 18, wherein the selection includes selecting a desired number from the top with the size, position, and direction of the implant part to be maximized or minimized as an optimal solution in the overall evaluation function. .
(21) The evaluation function includes an internal parameter and a weight parameter between evaluation items of the evaluation function. In the overall evaluation function, the internal parameter and / or linear sum, product, or a combination weight thereof in each evaluation function Item 19. The method according to Item 18, wherein the parameter is adjusted.
(22) The method according to item 1, wherein the implant part is a part of an artificial hip joint.
(23) The method according to item 22, wherein the components of the artificial hip joint include a pelvic side cup, a femoral side stem, and a stem.
(24) A system for selecting an implant component for obtaining a desired result in a surgical operation, the system comprising:
A) Means for obtaining subject patient information;
B) Means for obtaining information on the implant part to be implanted;
C) means for generating an evaluation function using the patient information and the implant part information; and D) a means for selecting an implant part to be actually used for surgery based on the evaluation function.
(25) A program for causing a computer to execute a process of selecting an implant part for obtaining a desired result in a surgical operation,
The above process
A) obtaining subject patient information;
B) obtaining information on the implant part to be implanted;
C) generating an evaluation function using the patient information and information on the implant part; and D) selecting an implant part to be actually used for surgery based on the evaluation function. .
(26) A recording medium storing a program for causing a computer to execute a process of selecting an implant part for obtaining a desired result in a surgical operation,
The above process
A) obtaining subject patient information;
B) obtaining information on the implant part to be implanted;
C) generating an evaluation function using the patient information and the implant part information; and D) selecting an implant part to be actually used for surgery based on the evaluation function. Medium.
(27) A method for generating or selecting an implant part for obtaining a desired result in a surgical procedure, comprising:
A) For the implant part x _m , an evaluation function is obtained from patient information and appropriate post-transplantation installation information.
F (x ₁ , x ₂ ,… x _m ) = Π _j {w _j f _j (x ₁ , x ₂ ,… x _m ; p _j )}
X ₁ to x _m are evaluation parameters of the i-th implant part, and f _j (x ₁ , x ₂ ,... X _m ; p _j ) is An evaluation function, p _j is an internal parameter of the j-th evaluation function, and w _j is a weight parameter for adjusting a balance between items,
B) a determining step for determining p _j and w _j for the desired result;
C) Input p _j and w _j determined for the desired result to Π _j {w _j f _j (x ₁ , x ₂ ,... X _m ; p _j )} generated in step A). And obtaining a solution of F (x ₁ , x ₂ ,... X _m ) and D) generating or selecting a part based on the solution.
(28) The method according to item 27, wherein the determination step B) is determined manually by a surgeon or automatically by a computer.

  The present invention also provides a system, a program, a recording medium, and the like that realize the above item 27.

  Preferred embodiments of the present invention will be shown below, but those skilled in the art can appropriately implement the embodiments and the like from the description of the present invention and well-known and common techniques in the field, and the effects and effects of the present invention can be easily achieved. It should be recognized to understand.

  According to the present invention, an operation using an implant is made more efficient, and further, by using a learning function, it has become possible to technically perform an operation that relied on a conventional skill with high reproducibility.

  Hereinafter, preferred embodiments of the present invention will be described. Throughout this specification, it should be understood that the singular forms also include the plural concept unless specifically stated otherwise. Accordingly, singular articles (eg, “a”, “an”, “the” in the case of English, and corresponding articles, adjectives, etc. in other languages) are plural concepts unless otherwise stated. It should be understood to include. In addition, it is to be understood that the terms used in the present specification are used in the meaning normally used in the art unless otherwise specified. Thus, unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs. In case of conflict, the present specification, including definitions, will control.

(Definition)
Listed below are definitions of terms particularly used in the present specification.

  As used herein, “bone” is a vertebrate support organ and refers to an individual component of the endoskeleton. Vertebrate bones consist mainly of bone tissue, except for crustaceans and cartilaginous fish. As used herein, bone includes cartilage. In this specification, when particularly distinguishing the hard connective tissue that forms the majority of the vertebrate skeleton, it is called a bone. In the present specification, bone is exemplified, but it is understood that the treatment can be similarly designed and performed even on a part of the body other than the bone.

  In this specification, “patient information” refers to arbitrary information related to a patient, and includes, for example, bone information, anatomical features, skeletal shape, and the like.

  In this specification, “bone information” refers to arbitrary information related to bone, and particularly means three-dimensional information. In this specification, “three-dimensional” display is usually performed using orthogonal display, but any system can be used as long as it can display three-dimensional. “Bone information” includes any information necessary for bone surgery (for example, a three-dimensional shape).

  In this specification, the target bone is usually an abnormal bone in many cases, and representative examples include bones that have passed through a fracture and bones with bone defects. Fractures include complete fractures, incomplete fractures, open fractures with skin damage, closed fractures, etc., and all the abnormal bones healed can be targeted. After a fracture, it usually heals in 6 weeks to 6 months, and in the meantime, a new bone is formed in the gap or the bone is often healed by deformation.

  In the present specification, “treatment” of bone refers to physical action on bone, such as rotation, excision, cutting, insertion (extension), fixation, etc. of a graft (implant). Although not limited to this, in particular, it often refers to insertion of an implant (part).

  In this specification, the term “surgery” is used in the same manner as is normally used, and refers to a method for treating diseases of body wounds or internal organs. Incision is performed using a surgical instrument or scalpel to treat the disease. It means to give a special treatment. Illustratively mentioned total hip arthroplasty refers to the treatment of osteoarthritis of the hip, femoral neck fracture, femoral head necrosis, and rheumatoid arthritis. It is replaced with parts to restore hip joint function.

  The hip joint consists of the tip of the femur, which has a ball shape at the tip, the mortar-shaped portion of the pelvis that serves as the socket that receives the ball head and the ball, and the acetabulum. Is replaced by. In total hip arthroplasty, it is important to select the type and size of prosthetic components suitable for each patient in advance and place them at the appropriate position and angle before surgery. If these were inadequate, the prosthetic joint components may loosen or fall off in a short period of time after surgery, and re-operation may be necessary, so they were reconstructed from X-ray images and CT images before surgery. It is necessary to make a surgical plan tailored to each patient on the three-dimensional bone shape model. The conventional surgical plan is performed by adjusting the magnification on the 2D X-ray image and assigning the template and pattern of the artificial joint part. It is very difficult to determine the surgical plan. Therefore, in this research, a three-dimensional bone shape model is constructed from multi-slice CT, which is becoming common, and a system that automatically plans a three-dimensional installation position and angle from objective evaluation values and shape characteristics based on the shape data is developed. I have done it. We have already developed an automatic surgery planning system with a cup and stem alone, and it has been confirmed that 80% of the applied cases for the cup and all cases for the stem can be adopted by specialists. . These are designed automatically for the fixed pelvis and femur individually, but as an artificial hip joint surgery plan, the installation plan should be made collectively so that both the pelvis side and the femur side are joined. Is needed.

  In order to integrate the automatic installation plan for cups and stems, it is necessary to consider the difference in leg length. The leg length difference is a difference when the left and right legs are aligned with the body axis. In general, when taking a CT, both legs are not aligned, so the body axis of the pelvis, which is the reference in the artificial hip surgery planning system, is matched. Then, adjustment is made so that the leg length difference is minimized.

  Since the pelvis is fixed as described above, the automatic pelvic cup plan is adopted as it is, and the method of joining the femoral side automatic plan to the pelvis side is explained. First, the size of the head on the femur, which is the ball, is determined automatically according to the selected size on the cup side. The installation position is -3.5mm from the cup center coordinate to the cup zenith direction. This also determines the installation coordinates of the stem that is integrated with the head and constitutes the femoral prosthesis. However, since the femur does not become parallel to the body axis of the pelvis as it is, the stem and femur While maintaining the automatic plan for determining the positional relationship, the head is rotated together with the head. Next, the leg length difference is adjusted by the neck length of the stem. The difference in leg length is calculated by rotating the femur on the non-surgical side so that the femoral bone is aligned with the pelvic axis, and then rotating in the body axis direction of the origin of the left and right femoral coordinate systems. This is done by calculating the deviation. The Freeman stem used this time has neck length variations of -4 mm, 0 mm, and 4 mm in the neck axis direction, and the one with the smallest leg length difference is automatically selected from these. As a result, the most appropriate installation plan can be automatically selected when the prosthetic joint parts are prepared, and a final automatic operation plan that integrates the automatic installation plan of the cup and stem is drawn up. Such a surgical plan can be applied in the system and method of the present invention.

  As used herein, “transplantation” refers to the transfer of an object into the body, and particularly refers to the transfer of a graft such as an implant.

  As used herein, a “graft” (implant or graft) is a homogenous or heterogeneous tissue, cell group or artifact (eg, a calcium phosphate structure) to be inserted into a specific site of the body, The one that becomes a part after insertion. Examples of the graft include, but are not limited to, a part of bone (for example, a part of natural bone (for example, autologous bone, allogenic bone, heterogeneous bone, etc.), a structure of calcium phosphate (for example, hydroxyapatite), and the like. Thus, a graft includes all that can be used to make up for a defect by inserting it into a defect in a portion, preferably a graft that does not cause immune rejection. Depending on the type of donor, autograft, allograft (allograft), xenograft (eg, coral for humans), or artificial In the present specification, an autograft (bone, tissue, cell, organ, etc.) or autograft is exemplified. Bone, tissue, cell, organ, etc., when referring to an individual, refers to a graft (bone, tissue, cell, organ, etc.) derived from that individual. In the broad sense, the term “cell, organ, etc.” can also include a graft (bone, tissue, cell, organ, etc.) from another genetically identical individual (eg, monozygotic twin). The expression “self” is used interchangeably with “derived from the subject.” Therefore, in this specification, the expression “not derived from the subject” means “not self ( That is, it has the same meaning as “non-self)”.

  In this specification, allografts (allogeneic allografts) (bones, tissues, cells, organs, etc.) are transplants (bones, tissues, Cell, organ, etc.). Because of genetic differences, allogeneic grafts (bones, tissues, cells, organs, etc.) can elicit an immune response in the transplanted individual (recipient). Examples of such grafts (bones, tissues, cells, organs, etc.) include, but are not limited to, parent-derived grafts (bones, tissues, cells, organs, etc.).

  In the present specification, a xenograft (bone, tissue, cell, organ, etc.) refers to a graft (bone, tissue, cell, organ, etc.) transplanted from a xenogeneic individual. Thus, for example, when a human is a recipient, a graft (bone, tissue, cell, organ, etc.) from a pig, a coral component, etc. are referred to as a xenograft (bone, tissue, cell, organ, etc.).

  As used herein, “artificial” grafts (bones, tissues, cells, organs, etc.) refer to grafts having portions that are not derived from natural organisms (for example, structures containing artificial calcium phosphate). When the artificial graft is an artificial bone, it preferably contains calcium phosphate. More preferably, the calcium phosphate includes hydroxyapatite.

  As used herein, a “recipient” (recipient) refers to an individual that receives a graft (bone, tissue, cell, organ, etc.) or a transplant (bone, tissue, cell, organ, etc.), and is also referred to as “host”. be called. In contrast, an individual that provides a graft (bone, tissue, cell, organ, etc.) or transplant (bone, tissue, cell, organ, etc.) is called a “donor”.

  As used herein, “subject (patient)” refers to an organism to which the treatment of the present invention is applied, and is also referred to as “patient”. The patient or subject may preferably be a human.

  The graft used in the present invention may be derived from the same strain (derived from the self (self)), derived from the same species (derived from other individuals (other families)), or derived from different species. Self-derived cells are preferred because rejection is considered, but they may be allogeneic if rejection is not a problem. Moreover, what causes rejection reaction can also be utilized by performing the treatment which eliminates rejection reaction as needed. Procedures for avoiding rejection are well known in the art. For example, the New Surgery System, Vol. 12, Organ Transplantation (From Heart Transplantation / Lung Transplantation Technical and Ethical Development to Implementation) (Revised 3rd Edition) ), Listed in Nakayama Shoten. Examples of such methods include methods such as the use of immunosuppressants and steroids. Immunosuppressants that prevent rejection are currently "cyclosporine" (Sandimune / Neoral), "Tacrolimus" (Prograf), "Azathioprine" (Imlan), "Steroid Hormone" (Predonin, Methylpredonin), "T cells There are “antibodies” (OKT3, ATG, etc.), and the method used in many facilities around the world as preventive immunosuppressive therapy is a combination of three drugs “cyclosporine, azathioprine, steroid hormone”. The immunosuppressive agent is desirably administered at the same time as the graft of the present invention, but it is not necessary. Therefore, the immunosuppressive agent can be administered before or after the method of the present invention as long as an immunosuppressive effect is achieved.

  In this specification, the information of “implant part” can be obtained based on the three-dimensional information of the object. Here, the same means as the patient information may be used.

  As used herein, “implant component to be used” refers to an implant component that is selected by the system or method of the present invention and that is appropriate for the intended operation.

  As used herein, “evaluation function” refers to a function for evaluating whether an implant part is suitable for surgery. Examples of such an evaluation function include, but are not limited to, a function that is evaluated from the viewpoint of fixing strength of an artificial joint; compatibility with an existing biological structure; ensuring sufficient joint function. The evaluation functions used in this specification are broadly classified into, but not limited to, an evaluation function of a form evaluation item and an evaluation function of a function evaluation item.

  As used herein, the evaluation function is an internal parameter (for example, a parameter of the implant part itself, which can include, for example, size, position, angle, etc.) and a weight parameter between evaluation items ( For example, a weight parameter for adjusting a balance between items can be included.

  The evaluation function of the form evaluation item can be expressed in the form of fj (xi; pj), and only a single implant part parameter xi is involved.

  The evaluation function of the function evaluation item can be expressed in the form of fj (x1, x2,... Xm; pj), and all (a plurality of) implant parts x1, x2,. In functional evaluation, each movable range in the front-rear direction, left-right direction, and leg circumference has a width of a certain angle or more; within a range where there is a difference in leg length between left and right; within a range where there is a difference in muscle length before and after surgery It can be evaluated that the change in muscle length during joint movement is within a certain range.

  In this specification, “balance adjustment” refers to adjustment of internal parameter values in constraint equations and evaluation functions that express all evaluation items involved in the evaluation of an implant surgery plan, and adjustment of weight parameter values of these evaluation items. The balance is adjusted by adjusting the weight parameter wi between the evaluation items and the internal parameter pi of the evaluation function.

  As used herein, “learning function” or “automatic balance adjustment” refers to a function or adjustment for learning about a target implant selection method (eg, a superior surgeon's selection method). The result of manually correcting the plan is accumulated, and the parameter values of wi and pi are automatically adjusted so that the result of the automatic plan approaches the correction result of the surgeon.

  In this specification, “global evaluation function” or “total evaluation function” is generally described in the form of F (x1, x2,... Xm) = Pj {wj fj (x1, x2,... Xm; pj)}. To do.

  In this specification, “parameter” refers to a parameter related to the shape of a target object (bone, implant part, etc.). Examples of parameters include size, position, and angle.

  In this specification, the “internal parameter” is a parameter of the evaluation function itself and refers to a parameter included in the function when the evaluation items listed below are expressed as an evaluation function or a constraint condition expression. Evaluation items used for internal parameters include, for example, coverage, acetabular rim diameter, CE angle, inner panel thickness, front wall thickness, rear wall thickness, stem fit, front twist angle, left and right leg length difference, movable range , Muscle length, ligament length, and stress secretion.

  In the present specification, the “weight parameter” is a weight value of each term in the statistical weighting method / frequency distribution, and in this specification, is multiplied by the entire evaluation function / constraint condition expression corresponding to each evaluation item. This value is used to adjust the balance between items. For example, (ka + lb) / (k + 1) with respect to two numbers a and b can include an average value obtained by adding weights k and l.

  In the present specification, the “method for treating bone” refers to a method to be performed on a target bone having a bone model and auxiliary members necessary for the bone (for example, for example) The shape of the implant.

  In this specification, the “parameter” in the three-dimensional direction related to the bone refers to an element that displays each dimension in the three-dimensional display to be used. For example, when space is expressed in an orthonormal system, x, y, and Each element (for example, a vector etc.) regarding the z axis is said. The space represented by the x, y and z axes can alternatively be represented by a rotation axis, a rotation angle and a distance.

  In this specification, “reinforcement” refers to improving the function of an intended part of a living body.

  In the present specification, “fixation” of bone refers to an action of substantially maintaining the state of treatment after treatment of a certain bone. Bone fixation can generally be performed only on the target bone.

  In this specification, “proximal” refers to the one closer to the heart when comparing two portions in a bone or the like.

  In this specification, “distal” refers to the one farther from the heart when comparing two portions of bone or the like.

  As used herein, “standard” refers to an entity that falls within a normal range in a certain population. Typically, a standard refers to a range that falls within ± 1 deviation from the mean when a population is statistically processed. In the present invention, as a standard, when there is a pair of bones, the bones to be treated can be used.

  In this specification, the “kit” refers to a set of members, devices, and the like to be used for a certain purpose. Such a kit includes, for example, various auxiliary members (for example, a set of implants and the like). The kit may be provided with instructions describing how to use the member.

  In the present specification, the “instruction” can be understood by a person (possibly a patient) who uses a device, a member, a kit, or the like of the present invention, or a surgical method, such as a doctor, a medical worker, or a patient. It is described as follows. This instruction manual includes words indicating the device, the implant set, the kit, the surgical method, and the like of the present invention. This instruction is prepared in accordance with the format prescribed by the national supervisory authority (for example, the Ministry of Health, Labor and Welfare in Japan and the Food and Drug Administration (FDA) in the United States, etc.) in the country where the present invention is implemented, and is approved by the supervisory authority. It is clearly stated that it has been received. The instruction sheet is a so-called package insert and is usually provided as a paper medium, but is not limited thereto. For example, an electronic medium (for example, a homepage (website) provided on the Internet, a PDF format) It can also be provided in the form of an electronic document (e-mail).

  As used herein, “auxiliary member” and “implant” or “implant component” refer to all auxiliary members required in surgery, and can be made of any material, for example, metal (for example, Stainless steel, copper, etc.), plastic, biocompatible polymer, biodegradable polymer, and the like can be used.

  As used herein, “biocompatibility” refers to the property of being able to exist without any damage in vivo due to lack of toxicity and immunological rejection ability.

  In the present specification, the “biocompatible polymer” refers to a polymer having good biocompatibility, and specifically means that it does not cause toxicity even if it remains in a living body. In this specification, a method for determining whether or not a certain polymer has such biocompatibility uses a test method such as an implantation test under the skin of a laboratory animal such as a rat, rabbit, or dog. . In this test method, as a result of the subcutaneous implantation test, it is understood that the biocompatibility is low macroscopically when a relatively acute immune reaction, allergic reaction, etc. occurs, and swelling, redness or fever occurs. Furthermore, when a biocompatible polymer is transplanted into a specific blood vessel, such as when transplanted into a blood vessel of an animal, the transplanted site is observed several days to several months later, whether or not the tissue has been engrafted, and the transplanted biocompatible The biocompatibility is determined by observing the degree of inflammation around the polymer, adhesion, and thrombus formation due to blood coagulation. In addition, a tissue section of the transplant site is prepared, and the cells are stained and observed with hematoxylin / eosin staining or other staining methods. As an indicator of poor biocompatibility, many granular cells are responsible for the immune system. It is determined whether it has invaded or whether there is formation of scar tissue separating the conventional tissue and the implanted biocompatible polymer.

  As used herein, “biodegradable” refers to the property of being degraded in vivo or by the action of microorganisms when referring to a substance. A biodegradable polymer can be decomposed into water, carbon dioxide, methane, and the like, for example, by hydrolysis. In this specification, the method for determining whether or not biodegradable is performed for several days to several years in a laboratory animal such as a rat, rabbit, or dog with respect to bioabsorbability, which is part of biodegradability. For testing and microbial degradation tests, methods such as embedding / disintegration tests for several days or years in soil of sheet-like polymers are used.

  In this specification, as the “means for obtaining information”, any means may be used as long as information on the three-dimensional object can be obtained. For example, a CCD camera, an optical camera, X-ray photography, CT, Means such as MRI (Magnetic Resonance Image) can be used, but are not limited thereto. Particularly in the present invention, patient information is often obtained by taking a CT image or an MR image, or obtained by deforming a general three-dimensional model based on a two-dimensional X-ray image. Such transformation into a three-dimensional model is described in the following documents on the creation of a three-dimensional model from a two-dimensional X-ray image: Jianhua Yao and Russell Taylor, Ninth IEEE International Conference on Computer Vision Volume 2 October, 13-16. France p. 1329 Assessing Accuracy Factors in Deformable 2D / 3D Medical Image Registration Usage a Statistical Pelvis Model. Creating a 3D model from an MR image is possible by a process similar to creating a 3D model from a CT image.

  In this specification, “means for obtaining patient information” may be any means as long as a three-dimensional shape model of an object can be obtained. For example, a CCD camera, an optical camera, an X-ray photography, a CT Software such as computer graphics can be used based on information obtained by means such as MRI (magnetic resonance image), but is not limited thereto.

  In this specification, the “three-dimensional shape model” refers to a description of a bone shape as computer information. Such a three-dimensional shape model is created using software such as computer graphics based on information obtained by using means such as a CCD camera, optical camera, X-ray imaging, CT, and MRI (magnetic resonance image). be able to. In the three-dimensional shape model, a plurality of skeletons forming a joint may be created as separate three-dimensional shape models or may be created as the same model.

(Description of Preferred Embodiment)
Hereinafter, preferred embodiments of the present invention will be described. The embodiments provided below are provided for a better understanding of the present invention, and it is understood that the scope of the present invention should not be limited to the following description. Therefore, it is obvious that those skilled in the art can make appropriate modifications within the scope of the present invention with reference to the description in the present specification.

  In one aspect, the present invention is a method for selecting an implant component for obtaining a desired result in a surgical operation, comprising A) obtaining subject patient information; B) information on an implant component to be implanted. C) generating an evaluation function using the patient information and information on the implant part; and D) selecting an implant part to be actually used for surgery based on the evaluation function. A method of including is provided.

  In another aspect, the present invention is a system for selecting an implant component for obtaining a desired result in a surgical procedure, which system A) means for obtaining subject patient information; B) to be implanted Means for obtaining information on implant parts; C) means for generating an evaluation function using the patient information and information on the implant parts; and D) an implant part to be actually used for surgery based on the evaluation function. A system is provided comprising means for selecting.

  The selection of implant parts has traditionally relied on experience and intuition, and was highly variable by the surgeon in charge. Moreover, since the surgeon depends on the skill, the skill cannot be transmitted to other doctors, and there has been a problem in the development of the technology. Since the present invention preserves the ability of surgeons having excellent skills and can transmit skills to other surgeons, the development of excellent techniques can be expected. A schematic diagram of this process is shown in FIG. Here, as patient information, information on anatomical features and skeleton shape (anatomical coordinate system) are illustrated. These and the shape model of the implant can be extracted from the implant database to select the implant parts to be actually used in the surgery in the surgical planning system or method of the present invention.

  In the above method, A) the step of obtaining target patient information can be performed by using already existing patient information or newly obtaining three-dimensional information about bone. Such acquisition of new three-dimensional information can be performed by taking a CT image or an MR image, or by deforming a general three-dimensional model based on a two-dimensional X-ray image.

  In the method of the present invention, the step of B) obtaining the information of the implant part to be implanted is also performed by utilizing the information of the existing implant part or newly obtaining three-dimensional information about the implant part. can do. Such new 3D information can be obtained by taking a CT or MR image, or by deforming a general 3D model based on a 2D X-ray image, This can be done by creating a model from the type.

  In the method of the present invention, the step of C) generating the evaluation function using the patient information and the implant part information is performed by associating and inputting the patient information and the implant part information to a predetermined evaluation function. Can be done. Here, various parameters can be set.

  In the method of the present invention, the step of D) selecting an implant part to be actually used for surgery based on the evaluation function performs predetermined processing on the evaluation function to select an implant to be used for various surgical operations. Can be implemented.

  Preferably, the evaluation function includes an internal parameter and a weight parameter between evaluation items of the evaluation function.

  In the method of the present invention, the evaluation function includes performing at least one evaluation selected from the group consisting of morphological evaluation and functional evaluation. Preferably, the evaluation function performs an evaluation including a form evaluation and a function evaluation.

  Examples of the evaluation function for each item include an evaluation function for a form evaluation item and an evaluation function for a function evaluation item. Such a form evaluation item includes, for example, the form of fj (xi; pj), and only a single implant part parameter xi is involved. The morphological evaluation can be determined, for example, based on a single parameter of the implant part. For example, the morphological evaluation item is one or more selected from the group consisting of the three-dimensional shape of the patient skeleton, the three-dimensional structure of the implant component, the size of the implant component, and the relative compatibility between the patient skeleton and the implant component. More items may be included.

  The evaluation function of the function evaluation item can be expressed, for example, in the form of fj (x1, x2,... Xm; pj), and all (a plurality of) implant parts x1, x2,. The functional evaluation can be determined, for example, based on a plurality of parameters of the implant part. Such evaluation items may include, for example, one or more items selected from the group consisting of leg length, joint range of motion, periarticular soft tissue length, and change in periarticular soft tissue length.

  In the method of the present invention, the selection of the implant part can be made by adjusting these internal and weight parameters.

  In one preferred embodiment, the adjustment of the internal parameter and the weight parameter may include adjusting based on a modification result database. Here, the correction result database refers to a database obtained by correcting a target surgery result. For example, such a correction result database may include, for example, an accumulated database of results of manual correction of a plan by a surgeon, a database automatically corrected from a surgeon's skill data record, and the like. , But not limited to them.

  The method of the present invention can further include a step of selecting a desired number of candidates from the evaluation values output in the evaluation function. The best candidate may be determined as one, but this is not always the case. Accordingly, examples of such a desired number include, but are not limited to, 2, 3, 4, 5, or an integer of 6 or more. Alternatively, the number of candidates may be one. This is because if the best candidate can be determined, only one can be selected.

  In one embodiment, patient information is obtained by taking a CT or MR image, or obtained by deforming a generic 3D model based on a 2D X-ray image. Such information may be information obtained in advance, or a three-dimensional shape model may be created from a CT image, MR image, or two-dimensional X-ray image at the time of surgery.

  In one embodiment, in the three-dimensional shape model, a plurality of skeletons that form joints may be created as separate three-dimensional shape models. Alternatively, a plurality of skeletons that form such a joint may be created as the same three-dimensional shape model.

  In one specific embodiment, the morphological evaluation inputs the 3D shape model of the implant part and the 3D shape model of the patient information to a computer, and the relative relationship between the single implant model and the single bone model. This can be done by defining a fitness evaluation function based on. The relative relationship can be correlated by, for example, evaluating the degree of fit between the stem shape of the artificial hip joint component and the medullary cavity shape of the femur. For example, as software that realizes such a relationship, for example, non-patent literature Although the software shown by 1 and nonpatent literature 2 can be mentioned, it is not limited to them.

  In one specific embodiment, the function evaluation may be performed by defining a function evaluation function reflecting each function based on a relative relationship between information on the plurality of implant parts and information on the patient. it can. The relative relationship can be related by, for example, evaluating the range of motion of the joint, and software for realizing such a selection can be selected or created by those skilled in the art based on the description in this specification. Can do.

  In another preferred specific embodiment, the evaluation function comprises evaluating a morphological evaluation and a functional evaluation, wherein the morphological evaluation is a computerized three-dimensional shape model of the implant part and a three-dimensional shape model of patient information. And defining a fitness evaluation function based on a relative relationship between a single implant model and a single bone model, wherein the functional evaluation includes a plurality of pieces of implant part information and a plurality of pieces of patient information. And defining a function evaluation function reflecting each function based on the relative relationship between the overall evaluation function and the function evaluation function by using individual linear sums, products, or a combination thereof. It can be implemented by defining. Again, relative relationships can be related by, for example, comprehensive evaluation of cup coverage, stem fit, range of motion, left and right leg length differences, etc. A trader can make or select an appropriate one based on the description of the present specification. In one embodiment, the selection includes selecting, as an optimal solution, the size, position and orientation of the implant part to maximize or minimize in the overall evaluation function. Alternatively, the selection can be achieved by selecting the desired number from the top in the overall evaluation function with the size, position and orientation of the implant part to be maximized or minimized as the optimal solution.

The overall evaluation function or the comprehensive evaluation function F (x ₁ , x ₂ ,... X _m ) has the form F (x ₁ , x ₂ ,... X _m ) = P _j {w _j f _j (x ₁ , x ₂ ,... X _m ; p _j )}.

x _i is a parameter to be obtained such as the size, position, and angle of the i-th implant part. Xm that maximizes F (x ₁ , x ₂ ,..., X _m ) can be obtained. f _j (x ₁ , x ₂ ,... x _m ; p _j ) is a j-th evaluation function for each item, and p _j is an internal parameter of the j-th evaluation function. w _j is a weight parameter for adjusting the balance between the items.

An explanation of x ₁ , x ₂ ,... x _m is described in FIG. As shown in FIG. 3, the respective parameters x ₁ , x ₂ , x ₃ ... X _m are assigned to the parts ₁ , ₂ , ₃ .

  In one embodiment, the evaluation function used in the present invention includes an internal parameter and a weight parameter between evaluation items of the evaluation function. In the overall evaluation function used in the present invention, the internal parameter in the individual evaluation function and Adjusting the weight parameter of the linear sum, product or combination thereof may be characterized.

  In the method of the present invention, the implant component is an artificial hip joint component (for example, a pelvic cup, a femoral stem and stem, etc.), an artificial knee joint component, a spinal screw, an intramedullary nail or plate in fracture treatment, a femur Examples include, but are not limited to, artificial bone heads in the treatment of cervical fractures.

The balance adjustment and adjustment of the learning functions w _i and p _i can be performed as follows, for example. Here, in the balance adjustment, the balance can be adjusted by adjusting the weight parameter w _i between the evaluation items and the internal parameter p _i of the evaluation function. In the learning function (automatic balance adjustment), after the automatic planning, the results of the manual correction of the plan by the surgeon are accumulated, and the results of the automatic planning approach the correction result of the surgeon w _i , p _i The parameter value can be automatically adjusted.

A specific example of each item is illustrated in FIG. 4: morphological evaluation f _j (x _i ; p _j ). In this evaluation example, the conformability of the stem (implant part) is evaluated. The goal is to have the stem and cortical bone well anchored and to minimize cortical bone excavation.

  Here, the evaluation is

Can be expressed as Evaluation _{function, g;} a (d n a, b, c ).

  Specific examples of each item of function evaluation include, for example, that the movable range in the front-rear direction, the left-right direction, and the leg circumference has a width of a certain angle or more; It can be performed within a certain range of the difference in muscle length before and after; it can be within a certain range of changes in muscle length during joint movement.

An example of the evaluation function related to the abduction direction movable range is shown in FIG.
[Equation 2]
f _j (x ₁ , x ₂ , ... x _m ; p _j )
The evaluation function related to the abduction direction movable range can be executed as follows, for example.
f _i (x ₁ , x ₂ ,... x _m , q _max ) = 1 if abduction direction movable range> q _max
0 Other than that For example, q _max = 40 degrees is set. In this case, there is one internal parameter. The range of motion in the abduction direction is a function of the size, position, and angle parameters x ₁ , x ₂ ,... X _m of all artificial joint parts, such as q _i (x ₁ , x ₂ ,... X _m ). Can be represented.

Next, FIG. 6 shows an example of an evaluation function related to the muscle length difference before and after the operation.
[Equation 3]
f _j (x ₁ , x ₂ , ... x _m ; p _j )
In this example, an example of an evaluation function relating to a difference in muscle length before and after the operation f _i (x ₁ , x ₂ ,... X _m , d) = 1 if L _pre −L _post (x ₁ , x ₂ ,... X _m ) | <D
0 Other than that, where _pre- operative muscle length L _pre and post-operative muscle length L _post (x ₁ , x ₂ ,... X _m ), d is the tolerance before and after surgery. .

(System construction example)
Next, the present invention can be configured around an application providing server that is a host computer, a recording medium changer that records case images, a medical image generation apparatus such as a magnetic resonance tomography apparatus or a computer tomography apparatus, Furthermore, it connects with the PC terminal which is an operation terminal of each specialist etc. by the communication line, and forms LAN.

  On the other hand, the application providing server is connected to an off-premises terminal through a public communication line such as the Internet, and can provide an application beyond the boundaries of an organization such as a hospital. The configuration of the application providing server is composed of two units, a storage server unit and a data control unit.

  The storage server unit is composed of six data groups: collected medical image data, case-specific image data, purpose-specific software, reference three-dimensional and four-dimensional image data, registered user data, and bug report management data. Note that image data and the like captured by the medical image diagnostic apparatus are transmitted to the storage server unit, and related data groups are updated and stored in real time.

  On the other hand, the data control unit is a unit for selecting and sending the required command group. Image processing / analysis target selection function, help / guidance function, new / registered user authentication function, purpose-specific software download function, It has six functions: command-based image processing / analysis function and target case database reference function.

  When there is a request to the application providing server, for example, a message screen of an image analysis and analysis support menu is output to the requested terminal.

  In this case, first, an affected area targeted for image processing is specified, and a menu that can be provided in the affected area and its guidance are displayed. A pull-down display is desirable. Then, the software configuration of the accessed terminal is obtained, and application software that needs further installation is detected when executing the menu.

  Then, by simply clicking on a desired menu item according to the guidance of the corresponding item, the control code and application delivery necessary for executing the processing are installed, and an environment in which image processing and analysis processing can be executed is prepared.

  Preferably, in the system of the present invention, when the prepared processing / analysis menu is insufficient for the operation plan design or the like, the system includes a function of referring to the target case database and complementing it. This customized data item can be searched for data items required by the accessor from among the data items recorded in the target case database so as to be searchable, and statistically processed to obtain the required data. It is configured so that processing and analysis can be executed using the collected data.

  Specific examples of system configurations that can actually be used are shown below. First, the terminals that join this system comply with a medical image communication standard called DICOM (Digital Imaging and Communication in Medicine), and the terminals and host computers of each organization have QR functions (Queries and Retrieves). The image transmission / reception function is a standard feature. In the system of this embodiment, the following command group and application are prepared, and various services can be provided.

(DICOM Print)
DICOM printing is a unified standard for a print (filming) function according to the DICOM standard.

(Data storage (still image; jpeg, bmp, xpm) (moving image; avi))
DICOM standard images can be converted to and saved in Bitmap and xpm formats for Jpeg and Windows (registered trademark), and an AVI file output function is also provided for moving images.

(VIEWER function (image comparison by modality, multi-display display, cine display, multiple patient continuous display and analysis))
For image display methods, various display methods are available to increase the efficiency of image interpretation, such as splitting the screen into multiple images, displaying images in sequence, displaying images in comparison with another sample, or another patient. Has been.

(RESLICE function, stack recon function, image paging)
There are provided a function for estimating and redisplaying another image from an image created once, a method for displaying the image by bundling and reducing the number of images, or a function for automatically switching and sequentially displaying images.

(Measurement (ROI, area, volume, profile, histogram, time density))
ROI is an abbreviation of Region of Interest (ROI). It can measure the distribution of numbers of pixels on the image of only a specific part of the image (pixel: the smallest unit composing the image), as well as area, volume, etc. The function that can measure is prepared.

(Curved MPR, arbitrary cross-section clip)
MPR is an abbreviation for Multi Planar Format (multi-section tomographic display), and CT generally displays an image of a round body, but if MPR processing is performed, it also displays coronal and sagittal sections of the body. There are functions that can be used.

(Slab MIP, VR MPR, RAY sum)
MIP is an abbreviation of Maximum Intensity Projection, which is a maximum value projection method, and is a method for displaying the maximum value in the direction of “ray” in a method called “ray tracing”, which is a method of computer graphics. It can be used to display blood vessels using. In addition, VR is a volume rendering method, and RAY-SUM is different from MIP in that it displays not the maximum value but the average value of “rays”. This process can create an image like an X-ray photograph. In this embodiment, these functions are prepared.

(Real-time volume rendering 3D)
Real-time volume rendering (VR) is a method of displaying 3D without stress using a processing code that greatly increases the calculation efficiency of VR. In this embodiment, this real-time VR function is also provided.

(Multi-volume display (FUSION) with MPR overlap function)
Processing to superimpose slice images of different medical image modalities (for example, PET and CT, PET and MRI, etc.) and a function to synthesize and display 3D images as well as 2D like slices .

(Image creation template function (2D, 3D))
The 3D image display requires a display method suitable for the purpose, such as bone and cartilage, and a template function is provided for performing default settings for displaying the target organ in advance.

(3D ROI extraction, 3D connection site extraction)
Processing for extracting only necessary parts on 3D and a function for extracting only organs of similar color and density are provided.

(Oblique, Infinite Oblique)
Oblique is generally based on the MPR method, with vertical display such that the transverse, coronal, and sagittal sections are orthogonal to each other, but an oblique function is provided for arbitrary re-slicing in an oblique direction.

(CT bone automatic extraction function)
An image processing method for extracting only the bone by utilizing the characteristic features of the bone is prepared. When other organs such as cartilage are used, the organs can be used instead of bones.

  The hardware specifications required for image processing according to the present invention are as follows. 256 MB or more of physical memory (512 MB or more is desirable). The required memory amount depends on the number of slices to be processed. A video board and display capable of displaying 24-bit color or higher with a resolution of 1,280 × 1,024 or higher (the video board and the display driver must comply with the Windows® standard). Arbitrary hard disk of about 80 GB, mouse and keyboard with wheel, Ethernet (registered trademark) interface, Windows (registered trademark) XP Professional, Windows (registered trademark) XP Home Edition, Windows (registered trademark) 2000 (all in Japanese), TCP / IP protocol software attached to the OS. However, it is not particularly limited to this.

  Examples of hardware configurations include a DELL Precision Workstation 530 (middle tower type), CPU / XEON 2 GHz (Dual), memory / 2.0 GB, HDD / 80 GB, OS / Windows (registered trademark) 2000 XP, CD- With RW can be used.

  Hereinafter, an embodiment of the present invention will be described with reference to the drawings as necessary. The embodiments provided below are provided for a better understanding of the present invention, and it is understood that the scope of the present invention should not be limited to the following description. Therefore, it is obvious that those skilled in the art can make appropriate modifications within the scope of the present invention with reference to the description in the present specification.

(Example 1: Manual balance adjustment by a surgeon)
First, a method of manual balance adjustment by a surgeon using the present invention will be described. As shown in FIG. 7, patient information, for example, skeletal shape model (anatomical coordinate system) and anatomical features (eg acetabular border) are obtained.

  Next, a shape model of the implant that can be provided is obtained. This may be obtained from a virtual database, or a database that measures the real thing may be used. From these, an implant to be used for actual surgery is selected. Here, the surgical planning model of the present invention is used. This model is described along with the actual GUI in the examples below.

  The surgeon adjusts, for example, coverage, acetabular rim diameter, CE angle, inner thickness, stem fit, front twist angle, left and right leg length difference, movable range, muscle, and ligament length as adjustment items. Here, the surgeon can adjust the adjustment items such as wi and pi and feed back to the operation planning system of the present invention.

In the present embodiment, regarding manual balance adjustment, it is preferable that the surgeon adjust each parameter of the adjustment item using a GUI (Graphic User Interface). It is also possible to use the GUI to reduce the weight of adjustment items that the surgeon considers unnecessary to consider. In this regard, it can be said that “weight and parameter adjustment” rather than balance adjustment. This is, for example, http://www004.upp.so-net.ne.jp/take-dr/biomechanics/biomechanics.htm
These appropriate values are changed according to the surgeon with reference to the normal range of motion of the hip joint shown in FIG. These values may be adjusted by the surgeon himself using the GUI and reflected in the parameters in the evaluation function.

(Example 2: Learning function (automatic balance adjustment))
Next, automatic balance adjustment is achieved using a learning function.

  FIG. 8 shows an example using a learning function. In this system, a large amount of patient information is stored as information on the skeletal shape model, and similarly, information on the shape model of the implant is accumulated. By giving predetermined parameters, the surgical plan is changed by the computer, and then the surgeon performing the operation modifies and creates a new surgical plan. This corrected surgical plan is fed back to the surgical planning system of the present invention, and parameters relating to adjustment items are stored. The stored parameters are reflected at the next automatic adjustment.

  Thus, the automatic balance adjustment (learning function) can be considered as “weight and parameter adjustment”. Here, the value of each adjustment item is calculated from the surgical plan result created or corrected manually by the surgeon, and the parameter value in the evaluation function is adjusted from the statistical value (average, variance, etc.) of these values. To do. Depending on the evaluation item, the surgeon himself does not have a clear policy on the appropriate parameter range, and visualizes the relationship between the artificial joint and the patient's skeleton with graphics, and intuitively observes this to determine the appropriateness. In such a case, it is considered that in such a case, “automatic parameter adjustment” in which the arrangement that the surgeon intuitively considers appropriate is analyzed by a computer and the range of parameter values is adjusted becomes effective. This also makes it possible to some extent reflect the surgeon's preferences.

(Example 3: Example of manual adjustment)
The manual adjustment GUI is shown in FIG. In this example, the GUI that sets the range of each angle of flexion / extension, abduction / adduction is shown as the required range of motion of the hip joint. ing. This operation method will be described below.

  The surgeon designates the minimum movable range regarding the bending direction and the extending direction by adjusting the GUI slider. Similarly, the abduction direction and the inversion direction are also specified. Thus, these pieces of information are input to the system, and internal parameters of the evaluation function corresponding to the respective movable ranges are set.

(Example 4: Application example of automatic adjustment (learning))
Next, in this embodiment, an example of internal parameter learning (automatic adjustment) of an evaluation function for stem form compatibility is provided. A specific example is shown in FIG.

  The stem is an implant that is inserted into the medullary cavity (a portion surrounded by cortical bone) of the femur. The stem size, position and orientation must be chosen so that the stem fits optimally into the shape of the medullary canal. Where the shape does not fit, there is a gap between the stem and the medullary canal, or conversely, the stem needs to cut off a portion of the cortical bone in the medullary canal for insertion and insertion. Naturally, the medullary cavity shape of each patient and the (off-the-shelf) stem shape do not completely match, so a gap or protrusion is unavoidable. The evaluation function for stem form compatibility needs to be set to have a high evaluation value when both the gap and the protrusion are within the allowable range as much as possible. However, since the balance point is preferred by the surgeon, the adjustment of the internal parameter that determines the evaluation function is determined by the stem installation plan that is manually planned by the surgeon. The idea is to prepare a large number of installation examples of surgeons, and determine the internal parameters so that the sum of the evaluation functions in the installation examples becomes maximum when the positions, angles, and sizes are set by the surgeons. Although it should be set to the maximum value, it is difficult to obtain the maximum value due to the nonlinearity of the problem, so the maximum value is obtained. In practice, if there is a reasonably good value as an internal parameter value, it is possible to obtain a parameter closer to the surgeon's preference than the initial value parameter by searching for the maximum value using the iterative method as an initial value. It becomes possible. Hereinafter, specific examples used in this embodiment will be shown.

  FIG. 10 shows an evaluation function of stem form compatibility and internal parameter learning (automatic adjustment).

  In FIG. 10, an evaluation function g (x, y, z, a, b, g; s; i, a, b, c) for stem form compatibility is used. The input data is a system installation plan example (many) by a specialist, and the output data is the optimum values of the evaluation function internal parameters a, b, and c. The other variables x, y, z, a, b, g, and s indicate the displacement from the position (x, y, z), angle (a, b, g), and size (s) of the stem installed by the surgeon. Show. Ui is the medullary cavity shape of patient i.

  The left diagram in FIG. 10 shows a stem form compatibility evaluation function and an example of internal parameters. Here, the x-axis is the distance between the stem and the bone, and the more the line goes to the left, the larger the gap, the more the line goes to the right. The y-axis is the value of the evaluation function.

  The center diagram of FIG. 10 shows a representative example in which protrusions and gaps occur. Here, an example in which a stem is fitted to skin bone and cancellous bone is shown. On the right is an installation plan example by a specialist.

  FIG. 11 shows internal parameter learning (automatic adjustment) of the evaluation function for stem form compatibility. After planning a stem installation by a computer, a correction installation plan by a surgeon is performed. By repeating this, the stem installation plan result manually corrected by the surgeon is input, and the optimum values of the internal parameters a, b, c of the stem form suitability evaluation function are estimated.

  In this way, the present invention can reflect corrections by the surgeon.

(Example 5: Specific formulation of learning (automatic adjustment))
In this embodiment, an example of specific formulation of learning (automatic adjustment) is provided. Assume that the evaluation function of stem form compatibility is g (x, y, z, a, b, g; s; Ui, a, b, c). The explanation of each variable is as follows.

x, y, z, a, b, g, s: displacement from the position, angle, and size of the stem installed by the surgeon Ui: shape of the medullary cavity of patient i a, b, c: evaluation to be automatically adjusted (learned) Function internal parameters

The total sum G of evaluation functions for all patients set by the surgeon is defined as follows.

G (x, y, z, a, b, g; s; a, b, c) = Sig (x, y, z, a, b, g; s; Ui, a, b, c)

^{_{∇G, ∇G 0, ∇ 2 G}} , is defined as follows ∇ ² G _0.

∇G: 7-dimensional gradient vector when G is regarded as a function of x, y, z, a, b, g; s G ₀ : (x, y, z, a, b, g; s) = 0 7-dimensional gradient vector value

In the mathematical expression defined above, the position, angle, and size set by the surgeon, that is, (x, y, z, a, b, g; s) = 0, and evaluation is performed so that G takes a maximum value. It is necessary to set the internal parameters a, b, c of the function. The condition for taking the maximum value is | ∇G ₀ | = 0. Therefore, it is necessary to determine the internal parameters a, b, and c of the evaluation function so that | ∇G ₀ | = 0. Here, ∇G ₀ is a function of a, b, and c. That is, ∇G ₀ (a, b, c) is applied.

(Example 6: Specific formulation of learning (automatic adjustment))
In this embodiment, an example of specific formulation of learning (automatic adjustment) is provided. Here, it is assumed that the current values of a, b, and c are a ₀ , b ₀ , and c ₀ and are corrected in consideration of the surgeon's preference.

| ∇G ₀ (a, b, c) | = 0
Is a necessary condition and is corrected to the values of a, b, and c that satisfy this condition and are closest to the current values a ₀ , b ₀ , and c ₀ . This problem can be reduced to the following constrained optimization problem.

The evaluation function F (a, b, c) = (a−a ₀ ) 2+ (b−b ₀ ) 2+ () under the condition that the constraint condition | ∇G ₀ (a, b, c) | = 0 is satisfied. _c-c 0) a to 2 in a minimum, b, and c seek.

For solving the optimization problem with constraints, for example, a method described in Applied Numerical Library Nonlinear Programming ISBN: 4254114893 Asakura Shoten (published 1999-06-10), Hiroshi Yabe and Naoichi Yamaki it can.

  As mentioned above, although this invention has been illustrated using preferable embodiment of this invention, this invention should not be limited and limited to this embodiment. It is understood that the scope of the present invention should be construed only by the claims. It is understood that those skilled in the art can implement an equivalent range from the description of specific preferred embodiments of the present invention based on the description of the present invention and common general technical knowledge. Patents, patent applications, and documents cited herein should be incorporated by reference in their entirety, as if the contents themselves were specifically described herein. Understood.

  According to the present invention, an operation using an implant is made more efficient, and further, by using a learning function, it has become possible to technically perform an operation that relied on a conventional skill with high reproducibility. Therefore, the present invention has industrial applicability in the manufacturing industry for medical products and software development.

1 shows a schematic processing scheme of a surgical planning system of the present invention. Patient information (such as skeletal shape models, anatomical features, etc.) and implant shape models can be processed by the surgical planning system of the present invention to plan the appropriate implant selection and placement for each patient. The example which implement | achieved this invention in the case of an artificial hip joint is shown. In the morphological evaluation (step 1), the fixation strength of the artificial joint and the adaptability to the existing anatomy are determined. In step 1A, the cup size and installation position are determined based on the non-secondary ratio, the acetabular rim diameter, the CE angle, the inner plate thickness, and the like. In step 1B, the stem size, position, and angle are determined based on the stem suitability, the forward twist angle, and the like. Next, functional evaluation (step 2) is performed to ensure sufficient joint function. In Step 2, the head offset and the stem neck length are determined based on the difference between the left and right leg lengths, the movable range, the muscle length, the ligament length, and the like, and the surgical plan can be completed. _{X 1,} x 2 in the parameter specification of this invention, showing a description of ... _{x m.} Specific example of each item used in the present invention: an evaluation function (middle) of the form evaluation f _j (x _i ; p _j ) is shown. The left shows the graphic model of the bone, and the right shows the evaluation model when evaluated. The specific example (external rotation direction movable range) of the function evaluation function of one Embodiment which implemented this invention is shown. The left panel shows when extended downward and the right panel shows when raised. The specific example (muscle length difference before and behind an operation) of the function evaluation function of one Embodiment which implemented this invention is shown. The left shows before surgery and the right shows after surgery. Fig. 4 shows an exemplary scheme for manual balance adjustment by a surgeon according to the present invention. Patient information (such as skeletal shape models, anatomical features, etc.) and implant shape models can be processed by the surgical planning system of the present invention to plan the appropriate implant selection and placement for each patient. Here, w _i and p _i can be adjusted by the surgeon, the surgical planning system can be improved, and the balance can be adjusted manually. In addition to the above, there are various adjustment items such as stress distribution, front wall thickness, rear wall thickness, and bone density. 2 shows an exemplary scheme of a learning function (automatic balance adjustment) according to the present invention. Patient information (such as skeletal shape models, anatomical features, etc.) and implant shape models can be processed by the surgical planning system of the present invention to plan the appropriate implant selection and placement for each patient. In this case, the correction plan by the surgeon is automatically performed by the computer and fed back. An example of a GUI implementing the present invention is shown. A specific example in which the surgeon adjusts the internal parameter of the evaluation function will be described. Here, the minimum necessary movable range of the bending direction, the extending direction, the abduction direction, and the inversion direction is designated. The example which performed the internal parameter learning (automatic adjustment) of the evaluation function of stem form compatibility according to this invention is shown. On the left, stem shape suitability evaluation functions and internal parameter examples are shown proximally and distally. The middle schematic shows the interrelationship between the bone and the implant, showing the engagement between the cortical bone, cancellous bone and the stem. Based on these data, corrections are made by specialists (right). The example which performed the internal parameter learning (automatic adjustment) of the evaluation function of stem form compatibility according to this invention is shown. A stem installation plan by a computer is set from the operation planning system of the present invention, a correction installation plan by a surgeon is made, an internal parameter in the stem form compatibility evaluation function is adjusted by the computer, and fed back to the operation planning system of the present invention. Here, the surgeon manually estimates the optimum value of the internal parameter of the stem form compatibility evaluation function using the corrected stem installation plan result as an input.

Claims (3)

A system for selecting an implant component for obtaining a desired result in a surgical procedure, the system comprising:
A) Means for obtaining target patient information, the means being a means for taking a CT image or an MR image, or a means for deforming a general three-dimensional model based on a two-dimensional X-ray image, Means in which a plurality of skeletons forming joints are created as separate three-dimensional shape models in the three-dimensional shape model;
B) Means for obtaining information on the implant part to be implanted;
C) means for generating an evaluation function using the patient information and information on the implant part; and D) means for selecting an implant part to be actually used for surgery based on the evaluation function, ,
The evaluation function performs evaluation including morphological evaluation and functional evaluation, and the morphological evaluation is determined based on parameters of a single implant among the implant parts, and the functional evaluation is performed on the implant parts. Of which is determined based on the parameters of multiple implants,
The functional evaluation includes more than one item selected from the group consisting of leg length, range of motion, peri-articular soft tissue length and peri-articular soft tissue length, and includes information on a plurality of the implant parts and a plurality of the patients. Including defining a function evaluation function reflecting each function based on the relative relationship with the information,
The morphological evaluation comprises one or more items selected from the group consisting of the three-dimensional shape of the patient skeleton, the three-dimensional structure of the implant part, the size of the implant part, and the relative compatibility between the patient skeleton and the implant part. Including the three-dimensional shape model of the implant part and the three-dimensional shape model of patient information, and the conformity evaluation is based on a relative relationship between a single implant model and a single bone model among a plurality of models. Including defining an evaluation function,
With respect to the fitness evaluation function and the function evaluation function, an overall evaluation function is defined by individual linear sums, products, or combinations thereof, and the selection is the size of the implant part that is maximized or minimized in the overall evaluation function, A system comprising selecting a position and direction as an optimal solution. A program for causing a computer to execute a process of selecting an implant part for obtaining a desired result in a surgical operation,
The process is
A) Obtaining target patient information, which is obtained by taking a CT image or MR image, or by deforming a general three-dimensional model based on a two-dimensional X-ray image Obtained, wherein in the three-dimensional shape model, a plurality of skeletons forming joints are created as separate three-dimensional shape models;
B) obtaining information on the implant part to be implanted;
C) generating an evaluation function using the patient information and the information of the implant part; and D) selecting and displaying an implant part to be actually used for surgery based on the evaluation function. And
The evaluation function is an evaluation function including an evaluation including a morphological evaluation and a functional evaluation, and the morphological evaluation is determined based on parameters of a single implant among the implant parts. , Determined based on parameters of a plurality of implants among the implant parts,
The functional evaluation includes one or more items selected from the group consisting of leg length, range of motion, periarticular soft tissue length, and periarticular soft tissue length change, Including defining a function evaluation function reflecting each function based on the relative relationship with the patient information;
The morphological evaluation comprises one or more items selected from the group consisting of the three-dimensional shape of the patient skeleton, the three-dimensional structure of the implant part, the size of the implant part, and the relative compatibility between the patient skeleton and the implant part. Including the three-dimensional shape model of the implant part and the three-dimensional shape model of patient information, and the conformity evaluation is based on a relative relationship between a single implant model and a single bone model among a plurality of models. Including defining an evaluation function,
With respect to the fitness evaluation function and the function evaluation function, an overall evaluation function is defined by individual linear sums, products, or combinations thereof, and the selection is the size of the implant part that is maximized or minimized in the overall evaluation function, A program comprising selecting a position and direction as an optimal solution. A recording medium storing a program for causing a computer to execute a process of selecting an implant part for obtaining a desired result in a surgical operation,
The process is
A) Obtaining target patient information, which is obtained by taking a CT image or MR image, or by deforming a general three-dimensional model based on a two-dimensional X-ray image Obtained, wherein in the three-dimensional shape model, a plurality of skeletons forming joints are created as separate three-dimensional shape models;
B) obtaining information on the implant part to be implanted;
C) generating an evaluation function using the patient information and the information of the implant part; and D) selecting and displaying an implant part to be actually used for surgery based on the evaluation function. And
The evaluation function is an evaluation function including an evaluation including a morphological evaluation and a functional evaluation, and the morphological evaluation is determined based on parameters of a single implant among the implant parts, and the functional evaluation is , Determined based on a plurality of implant parameters among the implant parts,
The functional evaluation includes one or more items selected from the group consisting of leg length, range of motion, periarticular soft tissue length, and periarticular soft tissue length change, Including defining a function evaluation function reflecting each function based on the relative relationship with the patient information;
The morphological evaluation comprises one or more items selected from the group consisting of the three-dimensional shape of the patient skeleton, the three-dimensional structure of the implant part, the size of the implant part, and the relative compatibility between the patient skeleton and the implant part. Including the three-dimensional shape model of the implant part and the three-dimensional shape model of patient information, and the conformity evaluation is based on a relative relationship between a single implant model and a single bone model among a plurality of models. Including defining an evaluation function,
With respect to the fitness evaluation function and the function evaluation function, an overall evaluation function is defined by individual linear sums, products or combinations thereof, and the selection is the size of the implant part to be maximized or minimized in the overall evaluation function, A recording medium comprising selecting a position and direction as an optimal solution.