Intelligent joint replacement revision operation system and method based on CBCT and optical navigation

Abstract

The invention discloses an intelligent joint replacement revision operation system and method based on CBCT and optical navigation, and the system comprises an imaging device which is used for collecting the positive and lateral two-dimensional images of a femur region and an ankle joint region of an affected limb and the three-dimensional image of a knee joint region, and reconstructing the three-dimensional models of the femur and the tibia; the optical tracking equipment is used for acquiring poses of the first tracing equipment and the second tracing equipment in real time; the key point acquisition module is used for acquiring three-dimensional positions of a femoral head central point and an ankle joint central point in the positive and lateral two-dimensional image and acquiring femoral inner and outer upper condyle points and a tibia marrow cavity point in the three-dimensional model; the affected limb section extraction module is used for obtaining the far-end section, the anterior section and the posterior section of the femur in the knee joint area and the plateau section of the tibia in the knee joint area; and the planning execution module is used for determining the target pose of the new implant according to the corresponding section, and performing planning execution according to the target pose. According to the invention, the accuracy and safety of the joint replacement revision operation can be improved.

Description

Technical Field

[0001] This invention relates to the field of joint revision surgery, and more particularly to an intelligent joint replacement revision surgery system and method based on CBCT and optical navigation. Background Technology

[0002] Joint revision surgery is a complex surgical procedure aimed at replacing a failed or loosened prosthesis. Traditional revision surgery relies on preoperative CT imaging and intraoperative X-ray fluoroscopy, which has the following problems: 1. Inaccurate intraoperative localization: Relying on intraoperative two-dimensional fluoroscopic images, it is difficult to accurately locate the anatomical structures of the femur and tibia in three-dimensional space; 2. High radiation exposure: Preoperative scanning of the patient's entire lower limbs is required, and repeated fluoroscopy during the operation increases the radiation risk for both patients and medical staff; 3. Implants interfere with imaging results: The presence of metal implants during preoperative CT scans can significantly interfere with the imaging results, making it difficult to capture image details of the joint area. 4. Low surgical efficiency: It relies heavily on the surgeon's experience, and the identification of anatomical structures and prosthesis planning take a long time; 5. High risk of revision failure: Poor implant positioning may lead to loosening or dislocation again.

[0003] In recent years, CBCT (cone-beam computed tomography) and optical navigation technology have been gradually applied to orthopedic surgery, but a complete integrated revision surgery process, from two-dimensional imaging to three-dimensional reconstruction, and then to intelligent planning and navigation, is still lacking. Therefore, there is an urgent need for a revision joint replacement surgery system that can achieve real-time intraoperative three-dimensional modeling, intelligent planning, and precise navigation. Summary of the Invention

[0004] Purpose of the invention: To address the above-mentioned shortcomings, this invention proposes an intelligent joint replacement revision surgery system and method based on CBCT and optical navigation. This system avoids the need to collect a large number of data points during surgery using methods such as probes, which would otherwise take a lot of time. It can improve the accuracy and safety of joint replacement revision surgery and assist doctors in accurately completing the revision surgery.

[0005] Technical solution: This invention provides an intelligent joint replacement revision surgery system based on CBCT and optical navigation, comprising: Imaging equipment is used to acquire two-dimensional anteroposterior and lateral images of the femoral and ankle joint regions of the patient's affected limb, as well as three-dimensional images of the knee joint region, based on which three-dimensional models of the femur and tibia are reconstructed. An optical tracking device for real-time acquisition of the pose of a first tracking device mounted on an imaging device and a second tracking device mounted on the patient's affected limb; The key point acquisition module is used to acquire the three-dimensional positions of the femoral head center point and the ankle joint center point in the two-dimensional images of the front and sides acquired by the imaging equipment, as well as the medial and lateral epicondyles of the femur and the medullary canal of the tibia in the three-dimensional models of the femur and tibia. The affected limb cross-section extraction module is used to obtain the distal and anterior and posterior cross-sections of the femur in the knee joint region based on the femoral head center point and the medial and lateral epicondyles of the femur, and to obtain the plateau cross-section of the tibia in the knee joint region based on the ankle joint center point and the tibial medullary cavity point. The planning and execution module is used to determine the target pose of the new implant based on the corresponding cross-section extracted by the affected limb cross-section extraction module, and to perform planning and execution accordingly.

[0006] Specifically, the affected limb section extraction module obtains the anatomical axis direction of the femur based on the center point of the femoral head and the medial and lateral epicondyles of the femur. It then cross-multiplies this axis with the direction of the line connecting the medial and lateral epicondyles of the femur to obtain the first direction. From the surface point cloud of the three-dimensional model of the femur, it removes all points whose normal direction and the direction perpendicular to the anatomical axis of the femur are within a set angle. After clustering, it retains the point cloud that is closer to the knee joint and extracts the points whose normal direction is perpendicular to the anatomical axis direction of the femur and the first direction, respectively. Through clustering, it obtains the corresponding distal face point set and anterior and posterior face point sets, respectively. Finally, it obtains the distal section and anterior and posterior sections of the patient's femur in the knee joint region through fitting.

[0007] Specifically, the affected limb cross-section extraction module obtains the tibial anatomical axis direction based on the ankle joint center point and the tibial medullary cavity point. It removes all points from the three-dimensional surface point cloud of the tibia whose normal direction and the direction perpendicular to the tibial anatomical axis are within a set angle. After clustering, it retains the point cloud that is closer to the knee joint and extracts all points whose normal direction is parallel to the tibial anatomical axis. Through clustering, it obtains the corresponding platform point set and fits it to obtain the platform cross-section of the tibia located in the knee joint region.

[0008] More specifically, points whose angle between the normal and the direction perpendicular to the anatomical axis of the femur / tibia is within a set angle are removed from the surface point cloud of the 3D model of the femur / tibia, as follows: Based on the surface point cloud of the three-dimensional model of the femur / tibia, obtain the adjacent points of each point. Traverse each point in the surface point cloud of the three-dimensional model of the femur / tibia and filter out the points whose angle between the normal and the direction perpendicular to the anatomical axis of the femur / tibia is less than a first set value to obtain the first point set. The first point set is expanded based on the principle of similar local normals, and then the first point set is updated. Remove all points from the updated first point set, that is, remove all points from the surface point cloud of the femur / tibia whose normal direction is within a set angle to the direction perpendicular to the anatomical axis of the femur / tibia.

[0009] Furthermore, the expansion of the first point set based on the principle of similar local normals is specifically as follows: Iterate through all points in the first point set, and select points from its adjacent points that do not belong to the first point set and whose angle between their normal and the normal of the current point is less than the second set value. Expand these points into the first point set and update the first point set until there are no points in the first point set that meet the above conditions.

[0010] More specifically, after clustering the femur / tibia, points whose distance to the corresponding cross-section obtained by fitting is less than a set distance are searched in the point cloud that is closer to the knee joint. These points are then added to the point set of the corresponding cross-section, and the plane is fitted again to update the distal cross-section plane and the anterior and posterior cross-section plane of the femur in the knee joint region or the plateau cross-section plane of the tibia in the knee joint region.

[0011] Specifically, the planning and execution module determines the target pose of the new implant based on the corresponding cross-section of the knee joint region extracted by the affected limb cross-section extraction module, as follows: The planning and execution module obtains the target posterior section of the femur in the knee joint region based on the corresponding cross-section of the extracted knee joint region, and performs osteotomy or bone cement supplementation on the posterior section of the femur in the knee joint region accordingly. At the same time, based on the previously obtained set of points of the anterior section of the femur in the knee joint region, it calculates and obtains the point that is closest to the target posterior section of the femur in the knee joint region, and uses the corresponding distance as the distance between the anterior and posterior planes of the new implant, thereby matching the implant and determining the target pose of the new implant.

[0012] More specifically, the planning execution module obtains the intersection line between the distal section and the posterior section of the patient's femur in the knee joint region based on the corresponding section extracted from the knee joint region. The key point acquisition module obtains the femoral-knee joint center point in the three-dimensional model of the femur and projects it onto the intersection line. Using the distal section of the patient's femur in the knee joint region as the reference plane, the posterior section and the distal section are orthogonalized based on the obtained projection point to obtain the target posterior section. Based on this, osteotomy or bone cement is added at the posterior section.

[0013] Specifically, the key point acquisition module acquires the three-dimensional positions of the femoral head center point and the ankle joint center point in the anteroposterior and lateral two-dimensional images acquired by the imaging device, as follows: The key point acquisition module extracts the femoral head center point and ankle joint center point from the frontal and lateral two-dimensional images of the femoral and ankle joint regions of the patient's affected limb. Combined with the poses of the first and second tracer devices obtained by the optical tracking device and the imaging model of the imaging device, its three-dimensional position is calculated.

[0014] Specifically, the imaging device acquires two-dimensional images of the femoral region and ankle joint region of the patient's affected limb through fluoroscopic acquisition by setting angles in the anteroposterior and lateral views.

[0015] More specifically, the side-position setting angle is the angle between the ray emission direction of the imaging device and the ray emission direction in the orthogonal position, and is set to 30-60°.

[0016] Specifically, the imaging device segments the three-dimensional image of the knee joint region it acquires using a pre-trained segmentation model.

[0017] More specifically, the imaging device uses the MarchingCube algorithm to segment the acquired three-dimensional image of the knee joint region and convert the result into triangular patches to generate three-dimensional models of the femur and tibia.

[0018] The present invention also provides a method for using the aforementioned intelligent joint replacement revision surgery system, comprising: S1. Acquire two-dimensional images of the femoral and ankle regions of the patient's affected limb, as well as three-dimensional images of the knee region, using imaging equipment, and reconstruct three-dimensional models of the femur and tibia accordingly; simultaneously, acquire the pose of the first tracking device mounted on the imaging equipment and the second tracking device mounted on the patient's affected limb in real time using optical tracking equipment. S2. Obtain the three-dimensional positions of the femoral head center point and the ankle joint center point in the frontal and lateral two-dimensional images of the femoral region and ankle joint region of the patient's affected limb through the key point acquisition module, as well as the medial and lateral epicondyles of the femur and the medullary canal of the tibia in the three-dimensional model of the femur and tibia. S3. Using the affected limb section extraction module, obtain the distal section and anterior and posterior sections of the patient's femur in the knee joint region based on the center point of the femoral head and the medial and lateral epicondyles of the femur, and obtain the plateau section of the tibia in the knee joint region based on the center point of the ankle joint and the medullary canal of the tibia. S4. The planning and execution module determines the target pose of the new implant based on the corresponding cross-section extracted by the affected limb cross-section extraction module, and performs planning and execution accordingly.

[0019] Beneficial effects: This invention enables personalized and precise surgical planning, and provides full-process navigation from image acquisition and coordinate mapping to surgical execution. It avoids the need to collect a large number of points during surgery using methods such as probes, thus saving a lot of time. It improves the accuracy and safety of joint replacement revision surgery, assists doctors in accurately completing revision surgery, and has clinical practicality and promotional value. Attached Figure Description

[0020] To more clearly illustrate the technical solutions of this invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the drawings described below are merely embodiments of this invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0021] Figure 1 This is an example diagram illustrating an application scenario of the intelligent joint replacement and revision surgery system of the present invention.

[0022] Figure 2 This is a schematic diagram illustrating the principle of extracting the three-dimensional position of the femoral head center according to the present invention.

[0023] Figure 3 This is an example diagram of femoral cross-section extraction according to the present invention.

[0024] Figure 4 This is a flowchart of the method for using the joint revision surgery system of the present invention. Detailed Implementation

[0025] To make the objectives, technical solutions and advantages of the present invention clearer, the present application will be further described in detail below with reference to specific embodiments and accompanying drawings.

[0026] It should be noted that, unless otherwise defined, the technical or scientific terms used in the embodiments of the present invention should have the ordinary meaning as understood by one of ordinary skill in the art to which this invention pertains.

[0027] The intelligent joint replacement revision surgery system of the present invention includes: Imaging equipment is used to acquire two-dimensional anteroposterior and lateral images of the femoral and ankle joint regions of the patient's affected limb, as well as three-dimensional images of the knee joint region, based on which three-dimensional models of the femur and tibia are reconstructed. An optical tracking device for real-time acquisition of the pose of a first tracking device mounted on an imaging device and a second tracking device mounted on the patient's affected limb; The key point acquisition module is used to acquire the three-dimensional positions of the femoral head center point and the ankle joint center point in the two-dimensional images of the front and sides acquired by the imaging equipment, as well as the medial and lateral epicondyles of the femur and the medullary canal of the tibia in the three-dimensional models of the femur and tibia.

[0028] Specifically, the key point acquisition module extracts the femoral head center point and ankle joint center point from the anteroposterior and lateral two-dimensional images of the femoral and ankle joint regions of the patient's affected limb, and calculates their three-dimensional position by combining the poses of the first and second tracer devices obtained by the optical tracking device and the imaging model of the imaging device. The affected limb cross-section extraction module is used to obtain the distal and anterior and posterior cross-sections of the femur in the knee joint region based on the femoral head center point and the medial and lateral epicondyles of the femur, and to obtain the plateau cross-section of the tibia in the knee joint region based on the ankle joint center point and the tibial medullary cavity point. Among them, the extraction of the distal section and the anterior and posterior sections of the patient's femur in the knee joint region, as follows: Figure 3 As shown, the details are as follows: Based on the femoral head center point and the medial and lateral epicondyles of the femur, the anatomical axis direction and the first direction of the femur are obtained respectively. All points whose normal direction and the angle between them and the direction perpendicular to the femoral anatomical axis direction are within a set angle are removed from the surface point cloud of the 3D model of the femur. After clustering, the point cloud closer to the knee joint is retained, and the points whose normal direction is perpendicular to the femoral anatomical axis direction and the first direction are extracted respectively. The corresponding distal face point set and anterior and posterior face point sets are obtained by clustering respectively. The distal section and anterior and posterior sections of the patient's femur in the knee joint region can be obtained by fitting. The plateau section of the tibia located in the knee joint region is extracted as follows: The tibial anatomical axis direction is obtained based on the ankle joint center point and the tibial medullary cavity point. All points whose normal direction and the angle between them and the direction perpendicular to the tibial anatomical axis are within a set angle are removed from the 3D surface point cloud of the tibia. After clustering, the point cloud closer to the knee joint is retained, and all points whose normal direction is parallel to the tibial anatomical axis are extracted. The corresponding plateau point set is obtained through clustering, and the plateau cross-section of the tibia in the knee joint region is obtained by fitting.

[0029] The planning and execution module is used to determine the target pose of the new implant based on the corresponding cross-section extracted by the affected limb cross-section extraction module, and to perform planning and execution accordingly.

[0030] The key point acquisition module calculates the three-dimensional positions of the femoral head center point and the ankle joint center point, as follows: When acquiring anteroposterior and lateral two-dimensional images of the femoral and ankle regions of the patient's affected limb using optical tracking devices, the poses of the first and second tracking devices are determined. The spatial transformation relationship between the three-dimensional images and the first tracking device is obtained through calibration. The center points of the femoral head and ankle joint in the extracted anteroposterior and lateral two-dimensional images of the patient's affected limb are transformed to the reference of the second tracking device. Combined with the imaging model of the imaging device, the three-dimensional positions of the center points of the femoral head and ankle joint can be obtained. Figure 2 As shown, C1 represents the anteroposterior fluoroscopy of the target area, and C2 represents the lateral fluoroscopy of the target area. Lines connecting the cone-beam emission point to the center point of the femoral head or the center point of the ankle joint in the extracted 2D images are obtained from the obtained anteroposterior and lateral 2D images, respectively. Figure 2In the 2D frontal view, the corresponding center point is denoted as P, and the corresponding center point is denoted as P' on the 2D lateral view. The intersection of the two is the corresponding 3D location point. Figure 2 The middle part is represented by Q.

[0031] In this invention, the imaging equipment acquires anteroposterior and lateral two-dimensional images of the femoral and ankle regions of the patient's affected limb through fluoroscopic acquisition at set angles in the anteroposterior and lateral views. This invention, through dual-angle two-dimensional scanning and the imaging model of the imaging equipment, enables rapid intraoperative three-dimensional localization, reducing reliance on preoperative CT scans.

[0032] In this embodiment, the side view setting angle is the angle between the ray emission direction of the imaging device and the ray emission direction in the front view, and can be set to 30-60°. In this embodiment, it is preferred to set it to 45°.

[0033] In this invention, the imaging device acquires a three-dimensional image of the knee joint region, which is a three-dimensional image of the patient's knee joint region after the removal of the old implant.

[0034] In this invention, the imaging device segments the acquired three-dimensional images of the knee joint region, thereby reconstructing three-dimensional models of the femur and tibia. Specifically, the imaging device can use a pre-trained segmentation model to segment the acquired three-dimensional images of the knee joint region, which can improve reconstruction accuracy and efficiency. Specifically, the pre-trained segmentation model can be trained using a U-Net convolutional neural network.

[0035] In this invention, the imaging device can use the MarchingCube algorithm to segment the three-dimensional image of the knee joint region it has acquired and convert the result into triangular patches to generate three-dimensional models of the femur and tibia.

[0036] In this invention, the second tracing device includes a femoral tracing device and a tibial tracing device, which are rigidly mounted on the femur and tibia respectively to trace the position of the femur and tibia.

[0037] In this invention, the application scenarios of the intelligent joint replacement revision surgery system of this invention are as follows: Figure 1 As shown, OTS represents an optical tracking device, KT represents a C-arm tracer used by the imaging device to acquire three-dimensional images of the knee joint region, Femur represents a femoral tracer, and Tibia represents a tibial tracer. A1 represents the anteroposterior fluoroscopy of the femoral region, A2 represents the lateral fluoroscopy of the femoral region, HT represents the C-arm tracer when the imaging equipment acquires the anteroposterior two-dimensional image of the femoral region, and HT' represents the C-arm tracer when the imaging equipment acquires the lateral two-dimensional image of the femoral region. B1 represents the anteroposterior fluoroscopy of the ankle joint area, B2 represents the lateral fluoroscopy of the ankle joint area, AT represents the C-arm tracer when the imaging equipment acquires the anteroposterior two-dimensional image of the ankle joint area, and AT' represents the C-arm tracer when the imaging equipment acquires the lateral two-dimensional image of the ankle joint area.

[0038] In this invention, the femoral anatomical axis is determined by the midpoint of the line connecting the center point of the femoral head and the medial and lateral epicondyles of the femur, while the tibial anatomical axis is determined by the line connecting the medullary canal of the tibia and the center point of the ankle joint. The first direction is obtained by the cross product of the direction vector of the line connecting the medial and lateral epicondyles of the femur and the direction vector of the femoral anatomical axis.

[0039] In this invention, after removing all points whose normal direction and the direction perpendicular to the anatomical axis of the femur / tibia are within a set angle from the surface point cloud of the three-dimensional model of the femur / tibia, the remaining points can be clustered, and the adjacent remaining points can be clustered into one class, retaining the point cloud that is closer to the knee joint. Thus, the distal section and anterior and posterior sections of the femur in the knee joint region and the plateau section of the tibia in the knee joint region can be extracted respectively.

[0040] In this invention, all points whose normal direction is within a set angle to the direction perpendicular to the anatomical axis of the femur / tibia are removed from the surface point cloud of the three-dimensional model of the femur / tibia, specifically as follows: Based on the surface point cloud of the 3D model of the femur / tibia, obtain the adjacent points of each point. Traverse each point in the surface point cloud of the 3D model of the femur / tibia and filter out the points whose normal is nearly perpendicular to the anatomical axis of the femur / tibia to obtain the first point set S0. The first point set S0 is expanded based on the principle of similar local normals, and the first point set S0 is updated. Remove all points from the updated first point set S0, that is, remove all points from the surface point cloud of the 3D model of the femur / tibia whose normal and the direction perpendicular to the anatomical axis of the femur / tibia are within a set angle.

[0041] In this invention, a point whose normal direction is nearly perpendicular to the anatomical axis of the femur / tibia can be defined as having an angle between its normal direction and the anatomical axis of the femur / tibia that is less than a first preset value. In this embodiment, the first preset value can be 5°.

[0042] In this invention, the first point set S0 is expanded based on the principle of similar local normals, specifically as follows: Iterate through all points in the first point set S0, and filter out points from its adjacent points that do not belong to the first point set S0 and whose angle between their normal and the normal of the current point is less than a second preset value. Expand these points into the first point set S0 and update the first point set S0, until there are no points in the first point set S0 that meet the above conditions. In this embodiment, the second preset value can be 5°.

[0043] In this invention, after clustering the extracted points, plane fitting is performed on the point sets of each cross-section obtained from the clustering, thereby obtaining the distal cross-sectional plane and anterior and posterior cross-sectional planes of the patient's femur in the knee joint region, or the plateau cross-sectional plane of the tibia in the knee joint region. To improve the confidence of the fitted cross-sectional planes, the point cloud that is closer to the knee joint after clustering can be expanded. Specifically, points whose distance to the corresponding plane obtained from the fitted plane is less than a set distance can be searched in the point cloud that is closer to the knee joint after clustering of the femur / tibia, and these points are added to the point set of the corresponding cross-section. Plane fitting is then performed again to update and obtain a more accurate distal cross-sectional plane Pb and anterior cross-sectional plane Pf, posterior cross-sectional plane Pr of the patient's femur in the knee joint region, or the plateau cross-sectional plane Tt of the tibia in the knee joint region.

[0044] In this embodiment, the set distance can be 1.5mm.

[0045] In this invention, the planning and execution module obtains the target posterior section based on the corresponding section of the extracted knee joint region, and performs osteotomy or adds bone cement to the posterior section accordingly. At the same time, based on the aforementioned set of anterior section points, it calculates and obtains the point closest to the target posterior section, and uses its corresponding distance as the distance between the anterior and posterior planes of the new implant, thereby matching the implant and determining the target pose of the new implant.

[0046] In this invention, the planning and execution module extracts the corresponding cross-section of the knee joint region, obtains the intersection line between the distal cross-section and the posterior cross-section of the patient's femur in the knee joint region, obtains the femoral-knee joint center point in the three-dimensional model of the femur through the key point acquisition module, projects the femoral-knee joint center onto the intersection line, takes the distal cross-section of the patient's femur in the knee joint region as the reference plane, orthogonally processes the posterior cross-section and the distal cross-section based on the obtained projection point to obtain the target posterior cross-section, and performs osteotomy or bone cement supplementation at the posterior cross-section to make it correspond to the target posterior cross-section, that is, the posterior cross-section forms the target posterior end face through osteotomy or bone cement supplementation.

[0047] In this invention, the center point of the femoral-knee joint acquired by the key point acquisition module can be the center point of the intercondylar fossa of the femur, the center point of the intercondylar eminence of the femur, the midpoint of the medial and lateral femoral condyles, the midpoint of the soft tissue at the level of the knee joint space, or the midpoint of the tibial plateau. In this embodiment, the center point of the femoral-knee joint acquired by the key point acquisition module is the center point of the intercondylar fossa of the femur.

[0048] In this invention, the planning and execution module can project the aforementioned set of front section points onto the fitted front section, thereby calculating and obtaining the point closest to the target rear section. After matching the implant, the rear plane of the implant is aligned with the target rear section, and the bottom plane of the implant is aligned with the distal section, thereby determining the placement position of the new implant, i.e., determining the target pose of the new implant.

[0049] The method for extracting residual cross-sections from a three-dimensional digital model of the femur / tibia provided by this invention can avoid the need to collect a large number of points during surgery using methods such as probes, thus avoiding a significant time expenditure.

[0050] The present invention also provides a method for using the aforementioned intelligent joint replacement revision surgery system based on CBCT and optical navigation, comprising: S1. Acquire two-dimensional images of the femoral and ankle regions of the patient's affected limb, as well as three-dimensional images of the knee region, using imaging equipment, and reconstruct three-dimensional models of the femur and tibia accordingly; simultaneously, acquire the pose of the first tracking device mounted on the imaging equipment and the second tracking device mounted on the patient's affected limb in real time using optical tracking equipment. S2. Obtain the three-dimensional positions of the femoral head center point and the ankle joint center point in the frontal and lateral two-dimensional images of the femoral region and ankle joint region of the patient's affected limb through the key point acquisition module, as well as the medial and lateral epicondyles of the femur and the medullary canal of the tibia in the three-dimensional model of the femur and tibia. S3. Using the affected limb section extraction module, obtain the distal section and anterior and posterior sections of the patient's femur in the knee joint region based on the center point of the femoral head and the medial and lateral epicondyles of the femur, and obtain the plateau section of the tibia in the knee joint region based on the center point of the ankle joint and the medullary canal of the tibia. S4. The planning and execution module determines the target pose of the new implant based on the corresponding cross-section extracted by the affected limb cross-section extraction module, and performs planning and execution accordingly.

[0051] In this invention, the imaging equipment can be cone-beam CT, i.e., CBCT, such as... Figure 4 As shown, the method of using the intelligent joint replacement revision surgery system of the present invention may include: (1) Install an optical tracer on the CBCT, i.e., the first tracer device, and at the same time, obtain the relationship between the CBCT imaging model and the optical tracer and the relationship between the 3D image acquired by the CBCT and the optical tracer through calibration. (2) Two-dimensional images of the femoral region and ankle joint region of the patient's affected limb were scanned by CBCT in the anteroposterior and lateral views during the operation; (3) When the optical tracking device acquires the two-dimensional images of the femoral region and ankle joint region of the patient's affected limb in the CBCT, the optical tracer and the femoral tracer, i.e. the second tracer, are positioned according to the calibration in step (1). The center point of the femoral head in the two-dimensional images of the femoral region of the patient's affected limb and the center point of the ankle joint in the two-dimensional images of the ankle joint region of the patient's affected limb are transformed to the reference of the femoral and tibial tracers respectively. Combined with the imaging model of CBCT, the three-dimensional position of the center point of the femoral head and the center point of the ankle joint can be obtained. (4) Remove the patient’s old implants, and use CBCT to perform 3D scanning of the knee joint area of ​​the patient’s affected limb during the operation to obtain its three-dimensional image, and then segment it using a pre-trained segmentation model. (5) Based on the segmentation results of step (4), a three-dimensional model of the femur and tibia in the knee joint region of the patient's affected limb is reconstructed, and the medial and lateral epicondyles of the femur and the medullary canal of the tibia are extracted. (6) Based on the femoral head center point and the medial and lateral epicondyles of the femur, obtain the distal section and anterior and posterior sections of the femur in the knee joint region, and based on the ankle joint center point and the tibial medullary cavity point, obtain the plateau section of the tibia in the knee joint region; (7) Determine the target pose of the new implant based on the corresponding cross-section extracted by the limb cross-section extraction module, and then plan and execute accordingly.

[0052] This invention combines anteroposterior and lateral two-dimensional images of the femoral and ankle regions of the patient's affected limb with three-dimensional images of the knee region to obtain the three-dimensional positions of anatomical points. It then uses reconstructed three-dimensional models of the femur and tibia to obtain key anatomical points, thereby extracting the corresponding residual cross-sections of the femur and tibia. Based on this, the target pose of the new implant is determined, and the surgical plan is executed accordingly. This achieves personalized and precise surgical planning, enabling end-to-end navigation from image acquisition and coordinate mapping to surgical execution. It avoids the need for extensive time-consuming data collection using methods such as probes during surgery, improving the accuracy and safety of joint replacement revision surgery. It assists surgeons in accurately completing revision surgeries and has clinical practicality and promotional value.

[0053] Those skilled in the art should understand that the discussion of any of the above embodiments is merely exemplary and is not intended to imply that the scope of the invention (including the claims) is limited to these examples; within the framework of the invention, the technical features of the above embodiments or different embodiments can also be combined, the steps can be implemented in any order, and there are many other variations of different aspects of the embodiments of the invention as described above, which are not provided in the details for the sake of brevity.

[0054] The embodiments of this invention are intended to cover all such substitutions, modifications, and variations falling within the broad scope of the appended claims. Therefore, any omissions, modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the embodiments of this invention should be included within the protection scope of this invention.

Claims

1. An intelligent joint replacement revision surgery system based on CBCT and optical navigation, characterized in that, include: Imaging equipment is used to acquire two-dimensional anteroposterior and lateral images of the femoral and ankle joint regions of the patient's affected limb, as well as three-dimensional images of the knee joint region, based on which three-dimensional models of the femur and tibia are reconstructed. An optical tracking device for real-time acquisition of the pose of a first tracking device mounted on an imaging device and a second tracking device mounted on the patient's affected limb; The key point acquisition module is used to acquire the three-dimensional positions of the femoral head center point and the ankle joint center point in the two-dimensional images of the front and sides acquired by the imaging equipment, as well as the medial and lateral epicondyles of the femur and the medullary canal of the tibia in the three-dimensional models of the femur and tibia. The affected limb cross-section extraction module is used to obtain the distal and anterior and posterior cross-sections of the femur in the knee joint region based on the femoral head center point and the medial and lateral epicondyles of the femur, and to obtain the plateau cross-section of the tibia in the knee joint region based on the ankle joint center point and the tibial medullary cavity point. The planning and execution module is used to determine the target pose of the new implant based on the corresponding cross-section extracted by the affected limb cross-section extraction module, and to perform planning and execution accordingly.

2. The intelligent joint replacement revision surgery system of claim 1, wherein, The limb section extraction module obtains the anatomical axis direction of the femur based on the center point of the femoral head and the medial and lateral epicondyles of the femur. It then cross-multiplies this axis with the direction of the line connecting the medial and lateral epicondyles of the femur to obtain the first direction. From the surface point cloud of the 3D model of the femur, it removes all points whose normal direction and the direction perpendicular to the anatomical axis of the femur are within a set angle. After clustering, it retains the point cloud that is closer to the knee joint and extracts the points whose normal direction is perpendicular to the anatomical axis direction of the femur and the first direction, respectively. Through clustering, it obtains the corresponding distal point set and anterior and posterior point sets, respectively. Finally, it obtains the distal section and anterior and posterior sections of the patient's femur in the knee joint region by fitting.

3. The intelligent joint replacement revision surgery system of claim 1, wherein, The limb cross-section extraction module obtains the tibial anatomical axis direction based on the ankle joint center point and the tibial medullary cavity point. It removes all points from the 3D surface point cloud of the tibia whose normal direction and the direction perpendicular to the tibial anatomical axis are within a set angle. After clustering, it retains the point cloud that is closer to the knee joint and extracts all points whose normal direction is parallel to the tibial anatomical axis. Through clustering, it obtains the corresponding plateau point set and fits it to obtain the plateau cross-section of the tibia in the knee joint region.

4. The intelligent joint replacement revision surgery system of claim 2 or 3, wherein, Remove all points from the surface point cloud of the 3D model of the femur / tibia that have an angle between their normal and the direction perpendicular to the anatomical axis of the femur / tibia within a set angle, as follows: Based on the surface point cloud of the three-dimensional model of the femur / tibia, obtain the adjacent points of each point. Traverse each point in the surface point cloud of the three-dimensional model of the femur / tibia and filter out the points whose angle between the normal and the direction perpendicular to the anatomical axis of the femur / tibia is less than a first set value to obtain the first point set. The first point set is expanded based on the principle of similar local normals, and then the first point set is updated. Remove all points from the updated first point set, that is, remove all points from the surface point cloud of the femur / tibia whose normal direction is within a set angle to the direction perpendicular to the anatomical axis of the femur / tibia.

5. The intelligent joint replacement revision surgery system of claim 4, wherein, The expansion of the first point set based on the principle of similar local normals is as follows: Iterate through all points in the first point set, and select points from its adjacent points that do not belong to the first point set and whose angle between their normal and the normal of the current point is less than the second set value. Expand these points into the first point set and update the first point set until there are no points in the first point set that meet the above conditions.

6. The intelligent joint replacement revision surgery system of claim 2 or 3, wherein, After clustering the femur / tibia, points closer to the knee joint are searched in the point cloud that are less than a set distance from the corresponding fitted cross-section. These points are then added to the point set of the corresponding cross-section. Plane fitting is performed again to update the distal cross-section plane and anterior cross-section plane of the femur in the knee joint region, posterior cross-section plane, or plateau cross-section plane of the tibia in the knee joint region.

7. The intelligent joint replacement revision surgery system of claim 1, wherein, The planning and execution module determines the target pose of the new implant based on the corresponding cross-section of the knee joint region extracted by the affected limb cross-section extraction module, as follows: The planning and execution module obtains the target posterior section of the femur in the knee joint region based on the corresponding cross-section of the extracted knee joint region, and performs osteotomy or bone cement supplementation on the posterior section of the femur in the knee joint region accordingly. At the same time, based on the previously obtained set of points of the anterior section of the femur in the knee joint region, it calculates and obtains the point that is closest to the target posterior section of the femur in the knee joint region, and uses the corresponding distance as the distance between the anterior and posterior planes of the new implant, thereby matching the implant and determining the target pose of the new implant.

8. The intelligent joint replacement revision surgery system of claim 7, wherein, The planning execution module obtains the intersection line between the distal section and the posterior section of the patient's femur in the knee joint region based on the corresponding cross-section of the extracted knee joint region. The key point acquisition module obtains the center point of the femoral-knee joint in the three-dimensional model of the femur and projects it onto the intersection line. Using the distal section of the patient's femur in the knee joint region as the reference plane, the posterior section and the distal section are orthogonalized based on the obtained projection point to obtain the target posterior section. Based on this, osteotomy or bone cement is added at the posterior section.

9. The intelligent joint replacement revision surgery system of claim 1, wherein, The key point acquisition module acquires the three-dimensional positions of the femoral head center point and the ankle joint center point in the anterolateral 2D images acquired by the imaging device, as follows: The key point acquisition module extracts the femoral head center point and ankle joint center point from the frontal and lateral two-dimensional images of the femoral and ankle joint regions of the patient's affected limb. Combined with the poses of the first and second tracer devices obtained by the optical tracking device and the imaging model of the imaging device, its three-dimensional position is calculated.

10. The intelligent joint replacement revision surgery system of claim 1, wherein, The imaging device acquires two-dimensional images of the femoral and ankle regions of the patient's affected limb from both anteroposterior and lateral perspectives by using fluoroscopic imaging at set angles in the anteroposterior and lateral views.

11. The intelligent joint replacement revision surgery system according to claim 10, characterized in that, The lateral angle setting is the angle between the ray emission direction of the imaging device and the ray emission direction in the orthogonal position, and is set to 30-60°.

12. The intelligent joint replacement revision surgery system according to claim 1, characterized in that, The imaging device uses a pre-trained segmentation model to segment the three-dimensional image of the knee joint region it acquires.

13. The intelligent joint replacement revision surgery system according to claim 12, characterized in that, The imaging device uses the MarchingCube algorithm to segment the acquired three-dimensional images of the knee joint region and convert the results into triangular patches to generate three-dimensional models of the femur and tibia.

14. A method for using the intelligent joint replacement revision surgery system according to any one of claims 1-3 and 7-13, characterized in that, include: S1. Acquire two-dimensional images of the femoral and ankle regions of the patient's affected limb, as well as three-dimensional images of the knee region, using imaging equipment, and reconstruct three-dimensional models of the femur and tibia accordingly; simultaneously, acquire the pose of the first tracking device mounted on the imaging equipment and the second tracking device mounted on the patient's affected limb in real time using optical tracking equipment. S2. Obtain the three-dimensional positions of the femoral head center point and the ankle joint center point in the frontal and lateral two-dimensional images of the femoral region and ankle joint region of the patient's affected limb through the key point acquisition module, as well as the medial and lateral epicondyles of the femur and the medullary canal of the tibia in the three-dimensional model of the femur and tibia. S3. Using the affected limb section extraction module, obtain the distal section and anterior and posterior sections of the patient's femur in the knee joint region based on the center point of the femoral head and the medial and lateral epicondyles of the femur, and obtain the plateau section of the tibia in the knee joint region based on the center point of the ankle joint and the medullary canal of the tibia. S4. The planning and execution module determines the target pose of the new implant based on the corresponding cross-section extracted by the affected limb cross-section extraction module, and performs planning and execution accordingly.

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