A unicompartmental knee arthroplasty surgery navigation method and system and storage medium

Abstract

The application relates to the technical field of computer-aided medical treatment, and discloses a single-knee joint replacement surgery navigation method and system and a storage medium, which comprises the following steps: processing CT images and generating a three-dimensional anatomical model and a planning termination surface according to prosthesis parameters, calibrating a tool to obtain calibration parameters, establishing accurate mapping of virtual and actual spaces by using a point cloud registration formula, collecting motion data based on a kinematics principle, generating a gap curve graph by using a gap calculation formula to optimize the prosthesis parameters, monitoring the position of a handheld drill and calculating the normal distance from the tip to the planning termination surface, generating a bone grinding heat map to realize visual guidance, automatically adjusting the rotation speed and the extension state of the drill by using a safety control formula according to the normal distance, and finally collecting postoperative trajectory data to generate an evaluation report. The application solves the problems of experience dependence and lack of forced safety limitation in traditional surgeries by means of sensorless dynamic gap evaluation and a distance-based active physical intervention mechanism, and improves the accuracy and safety of surgeries.

Description

Technical Field

[0001] This invention relates to the field of computer-aided medical technology, and in particular to a navigation method, system, and storage medium for unicompartmental knee arthroplasty. Background Technology

[0002] Unicompartmental knee arthroplasty (UKA) is currently an effective treatment for unicompartmental osteoarthritis of the knee. Its core principle is to replace only the diseased articular surface while preserving the normal ligaments and the contralateral compartment. The success of the surgery highly depends on the precision of the prosthesis placement and good postoperative soft tissue balance. With the development of digital medical technology, optical navigation systems have been applied to assist surgeons in osteotomy positioning, improving surgical precision by tracking the relative position of surgical instruments and bone.

[0003] However, existing optical navigation systems still have limitations in practical clinical applications. Firstly, regarding safety control, most current mainstream navigation devices only provide passive information feedback, that is, alerting doctors by displaying the tool's position on the screen or issuing audible alarms. This mechanism lacks active physical intervention capabilities, and the safety during surgery depends entirely on the surgeon's hand-eye coordination and reaction speed. In procedures like unicompartmental arthroplasty, where the operating space is confined, even millisecond-level hand tremors or visual feedback delays are often insufficient to instantly prevent the drill from exceeding safety boundaries, leading to the risk of over-cutting or soft tissue damage.

[0004] Secondly, in terms of soft tissue balance assessment, existing technologies typically require the use of auxiliary instruments for measurement. A common practice is to insert a stretcher, tension meter, or pressure sensor after osteotomy. This not only increases the number of surgical steps, but the placement of physical measuring instruments into the joint space is itself an invasive procedure, artificially stretching or compressing the soft tissue, leading to discrepancies between the measured data and the true tension under natural joint movement. Another type of navigation technology relies entirely on the surgeon's manual testing of joint laxity. This subjective judgment lacks quantitative standards, making it difficult to ensure consistency among different surgeons and accurately predict postoperative kinematic performance during the pre-osteotomy planning stage.

[0005] Furthermore, in terms of guidance and verification, traditional navigation systems often use discrete numerical values ​​to display grinding depth, lacking intuitive graphical guidance. During high-speed grinding, surgeons struggle to accurately control subtle changes in cutting volume through rapidly shifting numbers. Simultaneously, pre-operative assessments often focus on static image alignment, lacking dynamic closed-loop verification methods based on actual motion trajectories to quantify and validate surgical outcomes. Summary of the Invention

[0006] The purpose of this invention is to provide a navigation method, system, and storage medium for unicompartmental knee arthroplasty, which solves the problems of existing unicompartmental knee arthroplasty navigation technology, such as the lack of physical active safety limiting mechanisms, reliance on invasive instruments or subjective experience for soft tissue balance assessment, and the lack of intuitive visualization depth guidance and dynamic closed-loop verification methods.

[0007] To achieve the above objectives, the present invention provides the following technical solution:

[0008] The first aspect of this invention provides a surgical navigation method for unicompartmental knee arthroplasty, comprising the following steps:

[0009] The process involves processing CT image data and prosthesis implantation parameters to generate a three-dimensional anatomical model, bone grinding region data, and planned termination surface. The marking probe and handheld drill are then calibrated to obtain tool calibration parameters. This step establishes the geometric benchmark between the virtual surgical environment and the physical tools.

[0010] A dual registration strategy was implemented using point cloud registration formulas to unify the 3D anatomical model with the patient's actual coordinate system established during surgery, generating the final mapping matrix. This process, through iterative optimization from coarse registration of anatomical landmarks to fine registration of surface point clouds, established the mapping relationship between virtual space and real anatomical structures.

[0011] Knee joint motion data is collected based on kinematic principles, and the joint space value is calculated using the gap calculation formula to generate a gap curve. The gap curve is used to optimize prosthesis implantation parameters. This step calculates the relative motion trajectory of the femur and tibia in real time during the full range of passive flexion and extension movements. Combined with a virtual prosthesis model, the distance between the lowest point of the planned femoral prosthesis surface and the tibial prosthesis surface in the normal direction of the osteotomy plane is calculated, thereby achieving dynamic quantitative assessment of soft tissue balance without implanting physical sensors.

[0012] During the bone-grinding process, the spatial position of the handheld drill is monitored in real time by combining tool calibration parameters and the final mapping matrix. The normal distance from the tip of the handheld drill to the planned termination surface is calculated, and a bone-grinding heat map is generated based on the normal distance. Then, a safety control formula is used to generate control commands based on the normal distance to automatically adjust the handheld drill. This step combines visual guidance and active control, dynamically adjusting the motor speed and telescopic mechanism status based on the real-time distance between the drill tip and the planned boundary: full-speed operation is allowed when far from the boundary; automatic deceleration is performed when approaching the boundary; and forced stop and retraction are achieved when the limit boundary is reached or exceeded, realizing physical isolation.

[0013] Postoperative trajectory data was collected after bone reshaping and compared with preoperative planning data to generate a surgical evaluation report. By comparing the actual postoperative gap with the preoperative planned gap, and verifying the lower limb alignment, a closed-loop verification of the surgical effect was achieved.

[0014] A second aspect of the present invention provides a navigation system for unicompartmental knee arthroplasty, the system running in a main control computer, comprising:

[0015] Prepare the calibration module, which is used to process CT image data and prosthesis implantation parameters to generate a three-dimensional anatomical model, bone grinding area data and planning termination surface, and to calibrate the marking probe and hand-held grinding drill to obtain tool calibration parameters.

[0016] The registration and mapping module is used to execute a dual registration strategy using point cloud registration formulas to unify the three-dimensional anatomical model with the actual patient coordinate system established during surgery in order to generate the final mapping matrix.

[0017] The gap assessment module is used to collect motion data of the knee joint based on kinematic principles and calculate the joint gap value using the gap calculation formula to generate a gap curve. The gap curve is used to optimize prosthesis implantation parameters.

[0018] The navigation control module is used to monitor the spatial position of the handheld drill in real time during the bone grinding process by combining tool calibration parameters and the final mapping matrix, calculate the normal distance from the tip of the handheld drill to the planned end surface, generate a bone grinding heat map based on the normal distance, and use the safety control formula to generate control commands based on the normal distance to automatically adjust the handheld drill.

[0019] The postoperative verification module is used to collect postoperative trajectory data after bone reshaping and compare it with preoperative planning data to generate a surgical evaluation report.

[0020] A third aspect of the present invention provides a storage medium having a computer program stored thereon, which, when executed by a processor, implements the unicompartmental knee arthroplasty navigation method described in the first aspect above.

[0021] In summary, the present invention has at least one of the following beneficial technical effects:

[0022] 1. This invention achieves distance-based active safety control, improving surgical safety. By calculating the normal distance from the drill tip to the planned termination surface in real time, the working state of the handheld drill can be automatically adjusted according to a safety control formula. When approaching a dangerous boundary, the rotation speed is automatically reduced to decrease cutting force; when reaching the limit boundary, the rotation is immediately stopped and the telescopic mechanism is driven to retract. This rapid-response physical intervention eliminates the risks caused by reaction delays and minor vibrations from manual operation, preventing accidental injury to the posterior cortical bone and soft tissues, and ensuring that the grinding depth is controlled within the planned range.

[0023] 2. This invention proposes a sensorless dynamic joint gap assessment method, optimizing soft tissue balance. Utilizing kinematic principles combined with gap calculation formulas, it allows for the inference of joint gap changes across the entire range using passive flexion and extension trajectory data before intraoperative bone reshaping. Compared to traditional physical tension meter measurements, this method eliminates the need for inserting additional instruments within the narrow joint space, avoiding invasive interference with soft tissues. Simultaneously, it provides dynamic gap curves at continuous angles, assisting surgeons in pre-adjusting prosthesis position in a virtual environment, thereby achieving a soft tissue balance scheme that better conforms to physiological kinematics.

[0024] 3. This invention improves surgical precision and efficiency by combining visual guidance with active control. At the visual level, a bone grinding heatmap visually displays the distribution of remaining bone volume, allowing surgeons to monitor the grinding progress without interpreting numerical values. At the execution level, the combination of high-precision mapping via point cloud registration and active control ensures both high efficiency and precision in the bone grinding operation. Furthermore, by comparing preoperative planning with the actual postoperative trajectory, a quantitative report including gap and force line deviations is generated, providing an objective evaluation standard for surgical quality and achieving digital management of the entire surgical process. Attached Figure Description

[0025] Figure 1 This is a flowchart of a unicompartmental knee arthroplasty surgical navigation method according to the present invention;

[0026] Figure 2 This is a flowchart of the kinematic gap balance evaluation process of the present invention;

[0027] Figure 3 This is a schematic diagram of the navigation system architecture for unicompartmental knee arthroplasty of the present invention;

[0028] Figure 4 This is a diagram of the intraoperative safety control response generated in an application embodiment of the present invention;

[0029] Figure 5 This is a postoperative gap balance assessment curve generated in an application embodiment of the present invention.

[0030] Among them, 100 is the preparation and calibration module; 200 is the registration and mapping module; 300 is the gap assessment module; 400 is the navigation control module; and 500 is the postoperative verification module. Detailed Implementation

[0031] The following is in conjunction with the appendix Figure 1 -Appendix Figure 5 The present invention will be further described in detail below.

[0032] Please refer to the appendix. Figure 1This invention provides a surgical navigation method for unicompartmental knee arthroplasty, which is implemented based on a main control carriage, an optical tracking system, a reference array assembly, a handheld drill, and a surgical instrument kit. The main control carriage is equipped with a main control computer running surgical planning and control software, a display, and input devices. The optical tracking system consists of an infrared optical tracker and a matching passive positioning reflector. The reference array assembly includes a Y-shaped femoral reference array and a T-shaped tibial reference array. The handheld drill includes a drill main unit with a built-in motor drive unit, a telescopic actuation mechanism, a drill tracking target, and a foot switch. The surgical instrument kit includes a marking probe with integrated special slots, bone screws, and calibration blocks. The method includes the following steps:

[0033] Step S1: Initialization and Joint Tool Calibration. The main control computer processes externally input image data to construct a virtual surgical environment and calibrates the spatial attributes of physical surgical tools. The generated virtual model data and tool calibration parameters serve as the basic input for subsequent steps. Specifically, the main control computer first receives externally input DICOM format CT image data of the patient's knee joint, performs image segmentation and 3D reconstruction operations on the CT image data, and generates 3D anatomical models of the femur and tibia. Subsequently, the main control computer receives the prosthesis implantation parameters confirmed by the surgeon (including prosthesis type and flexion / extension, varus / valgus, and rotation angles), performs Boolean operations and geometric calculations on the 3D anatomical model based on the prosthesis implantation parameters, and generates target bone grinding area data and planned termination surface data. The target bone grinding area data and planned termination surface data serve as the geometric reference for determining the grinding boundary in subsequent navigation.

[0034] Based on this, a dynamic spatial coordinate system is established. During the surgical procedure, an infrared optical tracker captures in real time the Y-shaped femoral reference array rigidly fixed to the distal femur and the T-shaped tibial reference array to the proximal tibia. The main control computer receives the array position data transmitted by the infrared optical tracker, and calculates and establishes the femoral coordinate system and the tibial coordinate system respectively through coordinate transformation algorithms. The femoral coordinate system and the tibial coordinate system serve as reference systems for unifying all spatial data in subsequent steps.

[0035] Simultaneously, joint calibration of the probe and handheld drill is performed. The main control computer executes the tool calibration process to obtain the geometric parameters of the tool tip. First, based on the data captured by the infrared optical tracker from the scribe probe, which rotates at multiple angles with its tip against a fixed spatial point, the tip offset is calculated. Second, the main control computer sends a test command to the handheld drill, driving the telescopic actuator to verify whether the telescopic actuator's telescopic movement is normal. Finally, based on the relative pose data of the handheld drill and the scribe probe, which are relatively stationary when inserted into the specially designed slot of the scribe probe and captured by the infrared optical tracker, the drill calibration parameters are calculated, completing the tool calibration. The drill calibration parameters are the spatial positional relationship parameters of the drill tip relative to the drill tracking target.

[0036] Step S2: Establishing Spatial Mapping Relationships through Dual Registration. Using a coarse-to-fine strategy, the 3D anatomical model generated in Step S1 is precisely unified with the femoral and tibial coordinate systems established in Step S1. First, coarse registration based on anatomical landmarks is performed. The main control computer responds to the doctor's action of using a calibrated marking probe to contact the patient's bones, acquiring anatomical landmarks of the femur and tibia. These landmarks include the distal femoral mechanical axis, medial and lateral epicondyles, tibial plateau concave point, and the ankle joint center. The main control computer then uses a singular value decomposition algorithm to calculate the initial transformation matrix between the anatomical landmarks and the corresponding point sets on the 3D anatomical model, completing the initial alignment of the two coordinate systems.

[0037] Subsequently, fine registration based on local point clouds is performed on the basis of coarse registration. The main control computer acquires dense surface point cloud data generated by the surgeon continuously sliding a dotted probe on the bone or cartilage surface of a single condyle articular surface. Using an initial transformation matrix as the initial value, the main control computer iteratively optimizes the surface point cloud data and the 3D anatomical model using the point cloud registration formula to obtain the final mapping matrix that minimizes the registration error. The point cloud registration formula is:

[0038] ;

[0039] In the formula: The objective function for registration error; The summation symbol; This represents the total number of surface point cloud data collected during the procedure. The symbol for the Euclidean norm; For the solution to be found Rotation matrix; The first point of measurement taken by the intraoperative marking probe on the patient's bone surface. The spatial coordinate vector of each sampling point; For the solution to be found Translation vector; The surface of the preoperative three-dimensional anatomical model and the transformed The coordinate vector of the corresponding point that is spatially closest.

[0040] Step S3: Kinematic-based gap balance assessment. Using optical tracking data combined with kinematic algorithms, a sensorless dynamic assessment of the knee joint's soft tissue balance is performed. The main control computer first records the initial state data of the limb in its natural extension and maximum flexion positions. Subsequently, based on data from the Y-shaped femoral reference array and T-shaped tibial reference array captured in real time by an infrared optical tracker during the doctor's application of varus / valgus stress to the knee joint and the full range (0° to 120°) of passive flexion and extension movements, the motion trajectory data between the femoral coordinate system and the tibial coordinate system is calculated.

[0041] Next, gap calculation and curve generation are performed. The main control computer calculates the buckling angle at any given moment based on the motion trajectory data. Regarding this buckling angle The system calls upon a 3D anatomical model containing the virtual prosthesis and its motion trajectory data, and calculates the current joint space value using the gap calculation formula. The main control computer compiles the joint space values ​​at different angles to generate a gap curve and displays it on the monitor. This gap curve serves as the basis for doctors to optimize prosthesis implantation parameters. The gap calculation formula is:

[0042] ;

[0043] In the formula: For the knee flexion angle is The joint space value at that time; The symbol for the Euclidean norm; To be at the buckling angle Below, the spatial coordinate vector of the lowest point on the femoral prosthesis planning surface is determined by a geometric search algorithm; To be at the buckling angle Below, the tibial prosthesis or liner is designed on the surface with The spatial coordinate vector of the contact point along the normal direction; This is the unit normal vector of the tibial osteotomy plane.

[0044] Step S4: Active Safety Navigation Bone Grinding. Visual guidance and active control are achieved by real-time monitoring of the drill's position and feedback of control commands. Specifically, the main control computer, combining the drill calibration parameters and the final mapping matrix, calculates the position of the drill tracking target captured in real-time by the infrared optical tracker, and estimates the real-time coordinates of the tip. The main control computer also calculates the normal distance between the real-time coordinates of the tip and the planned termination surface in real-time. At the same time, the main control computer drives the display according to the normal distance. Displays a heatmap of the bone reshaping area overlaid with data from the bone reshaping region; different colors correspond to different normal distances. Interval.

[0045] Based on this, the main control computer calculates the normal distance in real time. The system uses safety control formulas to generate specific motor speed and telescopic position commands, which are then sent to the handheld drill via the main control trolley to adjust the speed of the motor drive unit and the retraction state of the telescopic actuation mechanism. The safety control formulas include motor speed control models and telescopic position control models.

[0046] ;

[0047] ;

[0048] In the formula: This is a motor speed command; This is the rated full speed. This is the normal distance from the tip of the drill bit to the planned termination surface; This is the safe distance threshold; It is a deceleration function; The termination distance threshold; For retractable position commands; This represents the maximum displacement.

[0049] Step S5: Postoperative Verification and Evaluation. Performed after solid bone reshaping and prosthesis trial installation, this step verifies whether the surgical outcome meets the expected plan. The main control computer prompts the surgeon to repeat the actions in Step S3 after the prosthesis trial installation, i.e., perform passive flexion and extension movements of the knee joint within its full range (0° to 120°). Based on the Y-shaped femoral reference array and T-shaped tibial reference array data captured in real time during this process by the infrared optical tracker, the main control computer calculates the postoperative trajectory data between the femoral coordinate system and the tibial coordinate system.

[0050] Subsequently, the main control computer uses the gap calculation formula to calculate the postoperative trajectory data and generate a postoperative gap curve. The main control computer compares and analyzes the postoperative gap curve with the preoperative planning data and force line activity data, generates a surgical evaluation report containing comparisons of various indicators, and displays it on the monitor for the doctor to confirm the completion of the surgery.

[0051] In step S1, this embodiment mainly completes the construction of the virtual surgical environment and the calibration of physical tools, aiming to establish a high-precision geometric benchmark through the unification of the data space.

[0052] Step S101: Preoperative Modeling and Path Planning. To obtain high-fidelity patient anatomical data, the main control computer receives externally input patient knee CT image data via a data interface. Preferably, the CT image data must conform to the Digital Imaging and Communications in Medicine (DICOM) standard, and the slice thickness parameter should be set between 0.625 mm and 1 mm. The rationale for choosing this slice thickness range is as follows: if the slice thickness is too large (e.g., exceeding 1 mm), it will lead to a significant step effect in the reconstructed model, reducing bone surface fit; if the slice thickness is too small (e.g., less than 0.5 mm), although accuracy is improved, it will increase the scanning radiation dose and data processing time. Therefore, the above range represents a balance between reconstruction accuracy and clinical operational efficiency.

[0053] After receiving the data, the main control computer performs image segmentation and 3D reconstruction operations on the CT image data. In this embodiment, a threshold segmentation method combined with a region growing algorithm is used to separate the bone tissue from the surrounding soft tissue background.

[0054] Specifically, the segmentation threshold is typically set within the range of 300 HU to 2000 HU, which covers the typical CT value range for human bones from cancellous to cortical bone. However, it should be noted that for patients with osteoporosis, the lower threshold should be appropriately lowered based on their bone mineral density T-score (e.g., adjusted to 150 HU) to prevent the loss of bone edge information. Based on this, a smooth three-dimensional anatomical model of the femur and tibia is constructed using the moving cube algorithm. For the specific algorithmic implementation of the above image segmentation and three-dimensional reconstruction, those skilled in the art can refer to existing technologies in the fields of computer graphics and medical image processing, which will not be elaborated upon here.

[0055] After generating the 3D anatomical model, a pre-set prosthesis database is loaded. The surgeon selects a matching prosthesis model based on the patient's bone morphology and sets the prosthesis implantation parameters (including the prosthesis's flexion / extension angle, varus / valgus angle, and rotation angle relative to the bone). Based on the confirmed implantation parameters, the main control computer virtually implants the 3D prosthesis model into the 3D anatomical models of the femur and tibia. Using the difference algorithm in Boolean operations, the volume of the overlap between the prosthesis model and the bone model is calculated. The boundary of this overlap constitutes the target bone-grinding area data, which physically represents the amount of bone to be removed to fit the prosthesis. Simultaneously, the bottom surface of the prosthesis model in contact with the bone is extracted as the planned termination surface. This planned termination surface serves as the geometric boundary for the grinding operation depth, used for subsequent active safety control to prevent damage to normal bone structure due to excessive grinding.

[0056] Step S102: Establish a dynamic spatial coordinate system. During the surgical procedure, to address navigation failure caused by patient positional changes, the patient's actual position needs to be mapped to the navigation coordinate space in real time. The reference array components are rigidly fixed to the patient's bones, with the Y-shaped femoral reference array fixed to the distal femur and the T-shaped tibial reference array fixed to the proximal tibia. The asymmetric geometric design of the Y-shaped and T-shaped arrays aims to enable the optical tracking system to automatically identify and distinguish between the femur and tibia through the difference in the topological relationships of feature points, preventing identification errors caused by array occlusion or confusion.

[0057] The infrared optical tracker captures the passive positioning reflector sphere on the reference array in real time, obtaining the sphere's three-dimensional coordinates in the infrared optical tracker's coordinate system. The main control computer constructs a local coordinate system based on the relative geometric relationship of the reflector sphere using a rigid body transformation algorithm.

[0058] Specifically, three non-collinear center points of the reflection spheres in the array are selected to construct orthogonal basis vectors, establishing the origin and the X, Y, and Z axis directions, thereby establishing a femoral coordinate system that follows femoral movement and a tibial coordinate system that follows tibial movement. During this process, the collinearity of the three points needs to be detected. If the three points are found to be approximately collinear (e.g., the included angle is close to 0 or 180 degrees), a singularity risk is identified in the transformation matrix, triggering an alarm to adjust the array. In subsequent surgical procedures, regardless of the displacement or rotation of the patient's limb, all spatial position data is uniformly transformed into these two dynamic coordinate systems through a real-time updated transformation matrix.

[0059] Step S103: Joint calibration of the probe and handheld drill. To accurately display the position of the tool tip, it is necessary to determine the positional relationship between the tool's geometric center or point of action and its own tracking target.

[0060] For the dotted probe, this embodiment employs a multi-angle rotation method for calibration. During operation, the tip of the dotted probe is placed against any fixed physical point in space (such as a specially designed recess on a calibration block), and the probe handle is swung within a certain conical angle range, with the tip as the center of the sphere. This conical angle is recommended to be greater than 30 degrees. The reason for this is that if the swing amplitude is too small, the collected data points will be concentrated in a very small area of ​​the sphere, causing the equations to become ill-conditioned when fitting the sphere center using the least squares method, resulting in decreased stability of the solution. An infrared optical tracker continuously collects the pose data of the probe tracking the target during the swing process. The main control computer uses the least squares method to perform spherical fitting on the collected data. The resulting sphere center coordinates are the position vector of the probe tip in the probe-tracking target coordinate system, i.e., the tip offset.

[0061] For handheld drills, a relative position calibration method combining a marking probe and a telescoping probe is employed. The main control computer sends test commands to the handheld drill via a communication module, driving the telescopic actuator to perform a complete extension and retraction motion. By monitoring changes in motor current or feedback data from the built-in displacement sensor, the normality of the telescopic actuator's extension and retraction motion is verified. If the expected displacement feedback is not detected, the mechanism is deemed faulty and the process is prohibited from proceeding to the next step, thereby ensuring the reliability of subsequent active safety control functions.

[0062] After confirming that the function is normal, insert the drill bit of the handheld drill into the specially designed slot on the marking probe rod. The geometry of this specially designed slot is closely matched with the diameter of the drill bit, ensuring that after the drill bit is inserted, the tip of the drill bit remains relatively stationary with respect to a known geometric feature point on the marking probe (such as a marked point on the probe rod, the position of which is known relative to the probe target). While both are in this engaged state, the infrared optical tracker simultaneously captures the tracking target of both the marking probe and the handheld drill at the same timestamp.

[0063] The main control computer calculates the drill calibration parameters through coordinate chain transformation: First, using the principle of rigid body transformation, the coordinates of known geometric feature points in the scribe probe coordinate system are transformed into the global coordinate system of the infrared optical tracker, combined with the real-time pose of the scribe probe target, to obtain the absolute world coordinates of the drill tip. Then, using the inverse matrix of the real-time pose matrix of the handheld drill target, these absolute world coordinates are mapped back to the local coordinate system of the handheld drill, thereby calculating the spatial positional relationship parameters of the drill tip relative to the handheld drill target. This joint calibration method avoids the cumbersome operation and error accumulation caused by the traditional drill requiring contact with an external independent calibration block, and uses a highly accurate calibrated probe as a transfer reference, improving the positioning accuracy of the drill tip.

[0064] In step S2, this embodiment employs a coarse-to-fine dual registration strategy, aiming to precisely unify the three-dimensional anatomical model generated in step S1 (located in the CT coordinate system) with the femoral and tibial coordinate systems established in step S1 (located in the patient's actual coordinate system), thereby establishing a one-to-one mapping relationship between the virtual image space and the actual surgical space. The specific implementation is as follows:

[0065] Step S201: Coarse Registration Based on Anatomical Landmarks. This step aims to quickly establish the initial correspondence between the two coordinate systems, providing good initial values ​​for subsequent fine registration and preventing iterative calculations from getting trapped in local optima. The main control computer responds to the doctor's action of using a calibrated marking probe to contact the patient's bones, and collects specific anatomical landmark data of the patient's femur and tibia according to anatomical positioning specifications. As a preferred implementation, these landmarks are selected from geometrically distinctive locations, including the distal femoral mechanical axis, medial femoral epicondyle, lateral femoral epicondyle, tibial plateau concave point, and ankle joint center. During acquisition, it must be ensured that each point is not collinear in space to avoid singular solutions when calculating the transformation matrix.

[0066] After acquiring the aforementioned anatomical landmark data, the main control computer invokes a singular value decomposition (SVD) algorithm to calculate the rigid body transformation parameters. This algorithm, based on the least squares principle, decouples rotation and translation through centroid removal. Specifically, the main control computer calculates the geometric centroids of the intraoperatively acquired landmark set and the corresponding predefined point set on the 3D anatomical model. Then, it subtracts the centroid coordinates from the coordinates of each point in both sets, translating the point sets to coincide with the origin and eliminating the influence of the translation component. Based on this, it constructs the covariance matrix of the two centroid-removed point sets and performs singular value decomposition on this covariance matrix to parse out the rotation matrix. Finally, combining the calculated rotation matrix with the aforementioned centroid coordinates, the translation vector is derived. Through these calculation steps, an initial transformation matrix describing the pose transformation relationship between the CT coordinate system and the patient's actual coordinate system is obtained.

[0067] Step S202: Fine registration based on local point cloud. Given the limited number of anatomical landmarks and the potential for positioning errors due to soft tissue coverage, this embodiment further utilizes the morphological features of the bone surface to improve registration accuracy based on the initial positions determined by coarse registration. The main control computer collects dense surface point cloud data generated by the surgeon's continuous sliding of a dot-matrix probe across the articular surfaces (including cartilage or exposed bone surfaces) of the unicompartmental knee joint. To ensure the completeness of the constraints, the surface point cloud data acquisition area should cover anatomical regions with non-coplanar features (e.g., simultaneously including the anterior, distal, and posterior surfaces of the femoral condyle). This surface point cloud data typically contains hundreds to thousands of discrete spatial points to reflect the detailed local topographic features of the articular surface.

[0068] After obtaining the surface point cloud data, the main control computer uses the initial transformation matrix as the starting value for iterative calculations, and performs iterative optimization calculations on the surface point cloud data and the 3D anatomical model using the point cloud registration formula. This calculation process is based on the Iterative Closest Point (ICP) algorithm, which essentially searches iteratively for the optimal matching pose between the intraoperatively acquired point cloud and the preoperative CT model surface, minimizing the sum of squared Euclidean distances between them. The point cloud registration formula is:

[0069] ;

[0070] In the formula: The objective function for registration error is the mean square error characterizing the degree of alignment between the two sets of points. The summation symbol; This represents the total number of surface point cloud data collected during the procedure. The symbol for the Euclidean norm; For the solution to be found Rotation matrix; The first point of measurement taken by the intraoperative marking probe on the patient's bone surface. The spatial coordinate vector of each sampling point; For the solution to be found Translation vector; The surface of the preoperative three-dimensional anatomical model and the transformed The coordinate vector of the corresponding point that is spatially closest.

[0071] During the iterative calculation process, the main control computer monitors the objective function in real time. The rate of change or root mean square error (RMS) is used. To ensure the robustness of the algorithm, a dual termination condition is set: the iteration is considered to have converged when the RMS error is less than a preset accuracy threshold (e.g., RMS < 1 mm) or the number of iterations reaches a preset maximum iteration threshold (e.g., 50 times). If the accuracy threshold is not met even after reaching the maximum number of iterations, a registration failure message will be displayed, and data needs to be collected again.

[0072] The accuracy threshold (RMS < 1 mm) is set based on the clinical accuracy requirements for osteotomy plane and prosthesis placement in unicompartmental knee arthroplasty, ensuring that force line deviation is controlled within the allowable range. The maximum iteration threshold is set based on the real-time requirements of computational resources to prevent excessive time consumption in infinite loops. The rotation matrix at final convergence... Translation vector This is the final high-precision mapping matrix. Through this matrix, the preoperatively planned target bone-grinding area and the planned termination surface can be accurately converted into the patient's actual coordinate system during the operation, providing an accurate spatial reference for subsequent navigation.

[0073] In step S3, performed before the bone-grinding procedure, the core of this embodiment lies in using optical tracking data combined with kinematic algorithms to perform a sensorless dynamic assessment of the soft tissue balance of the knee joint. This step simulates postoperative joint activity digitally, aiming to infer the joint space distribution under soft tissue constraints based on the kinematic trajectory without the need for a physical tension meter, thereby guiding the pre-adjustment of the prosthesis position. The specific implementation method is as follows:

[0074] Step S301: Full-range motion trajectory acquisition. To obtain the true kinematic characteristics of the knee joint at different flexion angles, this embodiment collects data based on kinematic principles: First, a motion baseline is established. The main control computer records the initial state data of the limb in its natural extension position (usually defined as a flexion angle of 0°±5°) and maximum flexion position (usually greater than 120°), thereby defining the effective range of motion. During this data acquisition process, in order to simulate the true soft tissue constraint characteristics of the joint under weight-bearing or stress conditions after surgery, the doctor needs to apply continuous and stable inversion / valgus stress to the knee joint, keeping the medial collateral ligament or lateral collateral ligament in a tense state.

[0075] Subsequently, during the doctor's full-range (0° to 120°) passive flexion and extension movements of the knee joint, the infrared optical tracker acquired the spatial positions of the Y-shaped femoral reference array and the T-shaped tibial reference array in a high-frequency synchronous mode. As a preferred method, the acquisition frequency was set to 60Hz or higher. This was determined because the frequency of passive flexion and extension movements performed by hand is typically below 2Hz. According to the Nyquist sampling theorem and the requirements for smooth movement, a sampling rate of 60Hz is sufficient to capture minute movement details and prevent aliasing. Based on the acquired array data, the main control computer used a coordinate transformation algorithm to instantly calculate the relative pose matrix of the femoral coordinate system relative to the tibial coordinate system for each time frame.

[0076] Considering the tremor noise introduced by hand operation and the inherent high-frequency noise of optical measurement, B-spline interpolation or Kalman filtering algorithms are used to smooth the original relative motion trajectory data. This processing logic aims to ensure the continuity of the first and second derivatives of the trajectory, thereby ensuring that the subsequently calculated angle and gap change curves are smooth and without abrupt changes, conforming to the physiological characteristics of human joint movement.

[0077] Step S302: Gap Calculation and Curve Generation. After obtaining the smooth motion trajectory, the data processing flow enters the stage of converting geometric pose into clinical indicators. Based on the relative motion trajectory data obtained in step S301, the main control computer calculates the buckling angle at any given time using Euler angle decomposition of the rigid body rotation matrix or projection angle calculation methods. For each discrete buckling angle Perform virtual trial model calculation: call the three-dimensional anatomical model containing the virtual prosthesis generated in step S101 (at this time, the prosthesis model has been virtually implanted into the bone model according to the planning parameters), and transform the femoral prosthesis model and the tibial prosthesis model to the current relative position state respectively.

[0078] In this state, the current joint space value is calculated using the gap calculation formula. To accurately obtain the gap value, the main control computer executes the following geometric search algorithm to determine the calculation reference point: First, extract all discrete mesh vertex data of the distal condyle of the femoral prosthesis model; then, transform all mesh vertices to the current femoral coordinate system; subsequently, calculate the unit normal vector of each mesh vertex in the tibial osteotomy plane. The projection distance in the direction; finally, iterate through all projection distance values ​​and select the vertex with the smallest value (i.e., the closest to the tibial osteotomy plane) as the lowest point on the femoral prosthesis planning surface. .

[0079] The technical purpose of this calculation process is to quantify the vertical distance between the femur and tibia prostheses in the load-bearing direction, ignoring anterior-posterior or lateral shear displacement. The formula for calculating the gap is:

[0080] ;

[0081] In the formula: For the knee flexion angle is The joint space value at that time; The symbol for the Euclidean norm represents the straight-line distance between two points in space; To be at the buckling angle Below, the spatial coordinate vector of the lowest point on the femoral prosthesis planning surface is determined by a geometric search algorithm; To be at the buckling angle Below, the tibial prosthesis or liner is designed on the surface with The spatial coordinate vector of the contact point along the normal direction; The unit normal vector of the tibial osteotomy plane is introduced. The physical meaning of performing a dot product operation on this vector is to extract the component of the distance vector in the direction of the normal to the osteotomy plane, thereby obtaining the vertical gap value.

[0082] Through the above calculations, a gap data sequence covering the entire range from 0° to 120° is obtained. The main control computer compiles the joint gap values ​​at different angles and plots them into a gap-flexion curve, which is displayed on the monitor. In this graph, the horizontal axis represents the flexion angle, and the vertical axis represents the gap value (unit: mm). As a preferred selection logic, doctors make decisions by observing the morphological characteristics of the gap curve: for example, if the curve shows a "tight in extension, loose in flexion" characteristic (i.e., the gap value in the low-angle range is less than the set threshold, and the gap value in the high-angle range increases), it suggests that the distal osteotomy of the femoral prosthesis or the tibial posterior tilt angle may need to be adjusted. The gap curve serves as a quantitative basis for doctors to optimize prosthesis implantation parameters, ensuring that soft tissue balance can be pre-adjusted in a virtual environment before actual bone grinding.

[0083] See attached document Figure 2 In step S4, which is performed during the bone-grinding stage in this embodiment, the core lies in constructing a safety mechanism that combines visual guidance and active control by real-time monitoring of the drill position and feedback of control commands. This step transforms preoperative static planning into intraoperative dynamic constraints, using physical actuation mechanisms to prevent over-cutting caused by human error. The specific implementation method is as follows:

[0084] Step S401: Real-time distance calculation and visualization guidance. To provide doctors with intuitive operation guidance, the main control computer combines the drill calibration parameters obtained in step S103 with the final mapping matrix obtained in step S202 to calculate the position of the drill tracking target captured in real time by the infrared optical tracker.

[0085] Specifically, using the principle of rigid body transformation, the pose data of the grinding drill tracking target in the coordinate system of the infrared optical tracker is converted into the real-time coordinates of the grinding drill tip in the femoral or tibial coordinate system (depending on the current grinding object). Based on this, a point-to-plane distance calculation algorithm is used to calculate the normal distance between the real-time coordinates of the tip and the planned termination surface generated in step S101. The normal distance The physical meaning is the directed distance of the drill tip projected onto the plane along the direction of the normal vector of the planned termination surface. A positive value indicates that the drill bit is on the unground side (safe side), and a negative value indicates that it has crossed the termination surface (overcut side).

[0086] Before performing visualization rendering, the main control computer calls the preset safe distance threshold. (For example, set to 2mm) and termination distance threshold (For example, set to 0.5mm).

[0087] To visually represent the grinding depth, the display is driven according to the normal distance. Displays a heatmap of the bone grinding area overlaid with data from the bone grinding region.

[0088] In this embodiment, the bone-grinding heatmap employs color mapping technology to map discrete distance values ​​into a continuous color spectrum, thereby visualizing depth. As a preferred embodiment, different colors correspond to different normal distances. Interval:

[0089] when When the distance exceeds the safe distance threshold, it will be displayed in white, and the heat map will also be displayed in white, indicating that it is in the roughing zone and prompting the doctor to operate at full speed;

[0090] when When the distance is less than or equal to the safe distance threshold and greater than the termination distance threshold, the heat map is displayed in green, indicating that it is in the fine processing range, suggesting that the doctor should slow down the grinding speed.

[0091] when When the distance is less than or equal to the termination distance threshold and greater than 0, the heat map will show purple, indicating that it has entered the safe buffer and stop zone. At this time, although it has not overcut, it will trigger active braking and prompt the doctor to stop feeding.

[0092] like When the value is less than or equal to 0, the heatmap is displayed in red, indicating that overcutting has occurred.

[0093] This visual color-grading display mechanism allows doctors to intuitively judge the grinding depth without reading specific values, thereby adjusting the operating force accordingly.

[0094] Step S402: Distance-based active safety control. In addition to visual guidance, this embodiment introduces a physical-level active intervention mechanism to eliminate risks caused by delays or hand tremors. This is based on the real-time calculated normal distance. The system uses safety control formulas to generate specific motor speed and telescopic position commands. These commands are sent to the handheld drill via the main control trolley to adjust the output speed of the motor drive unit and the retraction state of the telescopic actuation mechanism. The safety control formulas include motor speed control models and telescopic position control models:

[0095] ;

[0096] ;

[0097] In the formula: This is a motor speed command; This is the rated full speed speed, which is set based on the rated power of the grinding drill motor and the optimal cutting speed for bone grinding (e.g., 60,000 rpm). This is the normal distance from the tip of the drill bit to the planned termination surface; The safety distance threshold is a safety margin (e.g., set to 2mm) calculated based on the overall response delay time (including tracking delay, calculation delay, and communication delay) and the doctor's average operating feed speed. Its physical meaning is to ensure that there is enough time and distance to complete deceleration or stop when a tendency to exceed the limit is detected. It is a deceleration function, and its value varies with... The decrease is due to the reduction of [the value], and in this embodiment, a linear decay function is preferably used: Furthermore, to avoid the denominator being zero, it is necessary to ensure that the settings are correct. Greater than The purpose of this function is to ensure a smooth transition in rotational speed and avoid discomfort in handling caused by sudden changes. The termination distance threshold represents the limit of permissible grinding, and is usually set to a value that includes a small machining allowance (such as 0.5 mm). For retractable position commands; For the maximum displacement, this displacement (e.g., 5 mm) must be greater than the maximum overcut depth generated within the maximum delay time to ensure that the drill bit can fully retract above the safe plane.

[0098] Through the above control logic, when the drill is far from the boundary, it is allowed to work at full speed to ensure efficiency; when it approaches the boundary... When the cutting force is within the specified range, the motor automatically reduces its speed to prevent overcutting caused by hand force; once the cutting force is exceeded... Upon reaching the boundary, the motor power is immediately cut off and the telescopic mechanism is triggered to retract, achieving a physical separation at the millisecond level, thereby ensuring the absolute safety of the surgical boundary.

[0099] In step S5, this embodiment is performed after the completion of solid bone grinding and the installation of the prosthesis trial model (or final prosthesis). The aim is to verify whether the surgical outcome meets the preoperative planning expectations through quantitative kinematic data, and to review the accuracy of joint function reconstruction using digital means, thereby forming a complete closed loop from planning and execution to verification. The specific implementation method is as follows:

[0100] Step S501: Postoperative motion trajectory data acquisition. After the prosthesis trial mold is installed, the articular surface morphology of the knee joint has changed from the diseased bone surface to the standard artificial articular surface, and its kinematic characteristics have changed accordingly. The main control computer prompts the doctor to repeat the actions in step S301 through the display interface, that is, to perform passive flexion and extension movements of the knee joint in the full range (0° to 120°), and apply the same varus and valgus stress as before the preoperative data acquisition to ensure the comparability of the data before and after the operation under soft tissue tension conditions.

[0101] During this process, the infrared optical tracker captures in real time the spatial position data of the Y-shaped femoral reference array and the T-shaped tibial reference array, which are rigidly fixed to the femur and tibia. Based on the femoral dynamic coordinate system and the tibial dynamic coordinate system established in step S102 (ensuring that the position of the reference array relative to the bones has not changed), the main control computer uses a rigid body transformation algorithm to calculate the postoperative relative motion trajectory data of the femoral coordinate system relative to the tibial coordinate system. In order to eliminate occasional jitter caused by surgical operation and measurement noise of the optical system, the collected discrete trajectory points are smoothed by B-spline interpolation, and the sampling frequency is kept consistent with the preoperative acquisition (e.g., 60Hz) to ensure consistency in the time domain.

[0102] Step S502: Postoperative assessment report generation. After acquiring postoperative trajectory data, the main control computer performs analysis and calculation of clinical indicators. Based on the aforementioned general gap calculation principle, the gap calculation formula is called to perform frame-by-frame calculation of the postoperative relative motion trajectory data acquired in step S501. Unlike preoperative calculation, the geometric object involved in the calculation at this time is no longer a virtual planning surface, but rather the surface data of the prosthesis trial model representing the current implantation state.

[0103] Specifically, for each calculated buckling angle The Euclidean distance between the femoral trial mold surface and the tibial trial mold (or padding) surface in the direction normal to the tibial osteotomy plane is calculated to generate the postoperative gap curve. The specific content of the gap calculation formula has been given in step S302 and will not be repeated here.

[0104] Based on this, the main control computer performs multi-dimensional comparative analysis. On the one hand, it performs soft tissue balance assessment: the generated postoperative gap curve is superimposed and compared with the expected gap curve generated during the preoperative planning stage, and the absolute deviation between the two at key functional angles (such as 0° extension, 30° initial flexion, 60° intermediate, 90° flexion, and 120° deep flexion). On the other hand, it performs force line verification: combining the coordinates of the hip joint center, knee joint center, and ankle joint center obtained by intraoperative sampling or calculation using a dotted probe, it constructs the femoral mechanical axis vector and the tibial mechanical axis vector, and calculates the angle between the two vectors to obtain the postoperative lower limb force line, while simultaneously calculating the range of motion of the joints throughout the full range of motion.

[0105] Finally, a surgical evaluation report containing comparisons of various indicators is generated and displayed on the monitor. This report visually demonstrates the differences between preoperative planned values ​​and postoperative measured values. As a preferred selection criterion, an automatic early warning mechanism based on clinical gold standards is implemented.

[0106] If the calculated gap deviation exceeds the gap deviation threshold (e.g., ±2mm), which is set based on the soft tissue laxity of the knee joint and the wear resistance characteristics of the prosthetic polyethylene pad, exceeding this range will lead to joint instability or accelerated wear.

[0107] Alternatively, if the lower limb alignment deviation exceeds the alignment deviation threshold (e.g., ±3°), this threshold is set based on the ideal alignment range (i.e., neutral ±3°) recognized in joint replacement biomechanics research;

[0108] The monitor will highlight abnormal data with a bright color (such as red or yellow). Based on this quantitative report, the doctor can make an objective decision: if the indicators are within acceptable limits, the surgery is confirmed to be completed and sutured; if the indicators are abnormal, the doctor will change the padding of different thicknesses (to adjust the gap) or fine-tune the osteotomy surface (to correct the force line) as prompted until the indicators meet the requirements.

[0109] See attached document Figure 3 The present invention also provides a unicompartmental knee arthroplasty surgical navigation system, which runs on a main control computer and is used to execute the various steps in the above method embodiments. The system includes: a preparation and calibration module 100, a registration and mapping module 200, a gap assessment module 300, a navigation control module 400, and a postoperative verification module 500.

[0110] The calibration preparation module 100 is used to initialize the system and calibrate the accuracy of hardware tools. The calibration preparation module 100 receives externally input patient knee CT image data, performs image segmentation and 3D reconstruction operations on the CT image data, and generates a 3D anatomical model. Based on this, the calibration preparation module 100 performs Boolean operations and geometric calculations on the 3D anatomical model based on the received prosthesis implantation parameters, generating bone grinding region data and planning the termination surface.

[0111] Regarding coordinate system establishment, the calibration preparation module 100 receives array position data transmitted by the infrared optical tracker, and calculates and establishes the femoral coordinate system and tibial coordinate system respectively through coordinate transformation algorithms. Regarding tool calibration, the calibration preparation module 100 calculates the tip offset based on the scribe probe data captured by the infrared optical tracker from the scribe probe; it also sends a test command to the handheld drill to verify the telescopic actuation mechanism's telescopic action; finally, it calculates the drill calibration parameters based on the relative pose data between the handheld drill and the scribe probe captured by the infrared optical tracker.

[0112] The registration and mapping module 200 is used to execute a dual registration strategy, accurately mapping the virtual three-dimensional anatomical model to the patient's actual spatial position during surgery. In response to the doctor's action of using a dotting probe to collect anatomical landmarks, the registration and mapping module 200 invokes a singular value decomposition algorithm to calculate the initial transformation matrix between the anatomical landmarks and the three-dimensional anatomical model.

[0113] The registration and mapping module 200 acquires dense surface point cloud data generated by the doctor's scribbling probe. Using an initial transformation matrix as the initial value, it iteratively optimizes the surface point cloud data and the 3D anatomical model using a point cloud registration formula to obtain the final mapping matrix. The point cloud registration formula is used to calculate the rigid body transformation parameters that minimize the error between the two point sets.

[0114] The gap assessment module 300 is used to dynamically and quantitatively analyze the soft tissue balance of the knee joint based on kinematic principles before the bone-grinding operation. The gap assessment module 300 records the initial state data and calculates the motion trajectory data between the femoral coordinate system and the tibial coordinate system based on the data captured in real time by the infrared optical tracker during passive flexion and extension movements.

[0115] The joint gap assessment module 300 calculates the flexion angle based on motion trajectory data and calls upon a three-dimensional anatomical model containing the virtual prosthesis and motion trajectory data to calculate the current joint gap value using the gap calculation formula. The joint gap assessment module 300 compiles the joint gap values ​​at different angles, generates a gap curve, and displays it on the monitor.

[0116] The navigation control module 400 provides visual guidance during the bone resurfacing process and implements a distance-based active safety control mechanism. Combining the drill calibration parameters and the final mapping matrix, the navigation control module 400 calculates the real-time target position captured by the infrared optical tracker and infers the real-time coordinates of the drill tip. The navigation control module 400 also calculates the normal distance between the real-time coordinates of the drill tip and the planned termination surface, and drives the display to show a bone resurfacing heatmap overlaid on the bone resurfacing area data based on this normal distance.

[0117] Based on the real-time calculated normal distance, the navigation control module 400 generates motor speed commands and telescopic position commands using a safety control formula. These commands are then sent to the handheld drill via the main control trolley to adjust the motor drive unit and the telescopic actuation mechanism. The safety control formula includes a motor speed control model and a telescopic position control model, which are used to logically adjust the speed and telescopic state according to changes in distance.

[0118] The postoperative verification module 500 is used to verify whether the surgical outcome meets expectations by repeatedly collecting motion data before the end of the surgery. The postoperative verification module 500 prompts the doctor to perform passive flexion and extension movements and calculates postoperative trajectory data based on data captured in real time by the infrared optical tracker.

[0119] The postoperative verification module 500 uses the gap calculation formula to calculate the postoperative trajectory data and generate a postoperative gap curve. Finally, the postoperative verification module 500 compares and analyzes the postoperative gap curve with the preoperative planning data and force line activity data, generates a surgical evaluation report, and displays it on the monitor.

[0120] The present invention also provides a storage medium storing a computer program thereon, which, when executed by a processor, implements a unicompartmental knee arthroplasty surgical navigation method provided by the present invention.

[0121] See attached document Figure 4 and Figure 5 To further illustrate the technical solution of the present invention and its practical application effects, the following detailed description is based on the surgical procedure of a typical patient with medial unicompartmental osteoarthritis of the knee.

[0122] In this application example, the patient is a 65-year-old male diagnosed with medial compartment osteoarthritis of the right knee. The surgical plan utilizes an Oxford unicompartmental prosthesis. The preset parameters are as follows: CT scan slice thickness of 0.625 mm, and segmentation threshold set to 450 HU. In the active safety control model, the motor's rated full-speed rotation speed is... Set to 60,000 rpm, safe distance threshold Set to 2.0mm, termination distance threshold. Set to 0.5mm, maximum displacement Set to 5.0mm.

[0123] 1. Preoperative planning and system initialization:

[0124] The patient's CT data was imported into the main control computer, and a three-dimensional model of the femur and tibia was reconstructed. The surgeon planned the prosthesis position in the virtual environment, setting the ideal joint space target value of 5.5 mm throughout the full range of flexion and extension. The unit normal vector of the tibial osteotomy plane was determined at this point. (For simplicity, assume that the normal vector is along the positive Y-axis in the local coordinate system.)

[0125] 2. Intraoperative registration and gap assessment:

[0126] After completing registration and registration in steps S1 and S2, the system displayed a registration error RMS of 0.65mm, meeting the accuracy requirements. Step S3 is then performed for gap assessment. The physician passively flexes and extends the knee joint. When the knee joint is flexed to... At that time, the main control computer uses kinematic data to transform the virtual prosthesis to the current pose.

[0127] At this point, the lowest point of the femoral prosthesis is extracted using a geometric search algorithm. The position vector in the coordinate system is (12.5, 25.5, 10.2). This corresponds to the tibial prosthesis contact point. The position vector in the coordinate system is (12.5, 20.0, 10.2).

[0128] Substitute into the gap calculation formula:

[0129] ;

[0130] The calculated planning gap for a 45-degree buckling is 5.5 mm. Similarly, calculations across the entire range from 0 to 120 degrees produce a planning curve that shows a straight line with a stable value of 5.5 mm (e.g., ...). Figure 5 The circular curve in the diagram indicates that the planning scheme is reasonable.

[0131] 3. Active safety navigation bone reshaping:

[0132] In step S4, the doctor uses a handheld drill to grind the distal femur. The system calculates the normal distance from the drill tip to the planned termination surface in real time. And automatically adjust the motor according to the safety control formula (such as...) Figure 4 ).

[0133] Operating Condition 1 (Full-speed grinding):

[0134] When the drill bit is in the roughing zone, the system calculates the normal distance. .

[0135] because The condition for full speed is met:

[0136] ;

[0137] ;

[0138] At this time, the heat map is displayed in white, and the drill is running at full speed.

[0139] Operating Condition 2 (Deceleration Control):

[0140] As the grinding progresses deeper, the drill enters the precision machining zone, and the calculated normal distance... .

[0141] because Call the deceleration function Perform the calculation:

[0142] ;

[0143] Immediately reduce the motor speed to 30,000 rpm. At this point, the thermal map shows green, the doctor notices the cutting sound decreases, and consciously slows down the feed rate.

[0144] Operating Condition 3 (Active Braking and Retraction):

[0145] If the doctor's hand trembles slightly during the operation, causing the drill to suddenly advance, the calculated normal distance will be affected. .

[0146] because The system triggers a protection mechanism:

[0147] ;

[0148] ;

[0149] The motor momentarily lost power and stopped rotating, while the telescopic mechanism simultaneously retracted the drill bit by 5mm. The thermal map showed this as purple. Although the drill tip was only 0.4mm from the planned surface at this point, due to the physical separation (stopping and retraction), no substantial overcut occurred. This ensures the safety of the surrounding bone and soft tissues.

[0150] 4. Postoperative verification:

[0151] After the bone reshaping is completed, postoperative trajectory data is collected again and a comparison curve is generated (e.g., Figure 5 The results showed that the postoperative measured gap (triangular marker curve) generally matched the preoperative planned expectation (circular marker curve) with high accuracy. Although a small deviation of up to 0.3 mm (measured value 5.8 mm) occurred near 80 degrees of flexion, this deviation was far less than the clinically acceptable error range of ±2 mm, verifying the precision of the surgery.

[0152] like Figure 4 This figure illustrates the process of grinding as the drill tip gradually approaches the planned termination surface (i.e., the normal distance). (The process of decreasing from 3mm to 0mm), the system's combined control logic for motor speed and telescopic mechanism displacement. Here, the horizontal axis represents the normal distance. The direction decreases from right to left; the left vertical axis represents the motor speed, and the right vertical axis represents the retraction displacement of the telescopic mechanism. The solid line in the figure indicates that the motor speed remains at full speed before the safe distance (2.0mm), and then decreases linearly until it drops to zero at the termination distance (0.5mm); the dashed line in the figure indicates that the telescopic mechanism maintains zero displacement before the termination distance, and once the termination distance is reached, the displacement jumps instantaneously to 5mm to achieve physical retraction.

[0153] like Figure 5This figure illustrates the changes and comparisons of joint space values ​​during the full range of knee flexion from 0° to 120°. The horizontal axis represents the knee flexion angle, and the vertical axis represents the joint space value (in mm). The solid line marked with a circle represents the ideal expected space (constantly 5.5 mm) set during the preoperative planning stage, while the dashed line marked with a triangle represents the postoperative measured space acquired after bone reduction. The figure clearly shows that the postoperative measured curve closely matches the planned curve, with a maximum deviation of only 0.3 mm near 80° flexion, thus quantitatively verifying that the surgical procedure achieved the expected soft tissue balance effect.

[0154] To verify the effectiveness of this invention, a comparative experiment was designed. The experimental subjects were 30 standardized artificial bone saw models, which were randomly divided into three groups of 10 models each.

[0155] 1. Experimental Groups:

[0156] Experimental group (the scheme of this invention): Using the scheme of this invention, the S3 gap assessment and S4 active safety control functions are enabled.

[0157] Control group A (traditional optical navigation): uses a conventional optical navigation system without active control functions, only providing screen visual guidance (displaying distance values ​​and colors), without motor automatic control and telescopic mechanism.

[0158] Control group B (manual operation): The osteotomy was performed by an experienced surgeon using traditional mechanical tools and experience.

[0159] 2. Evaluation indicators:

[0160] Osteotomy depth error: The average normal deviation between the actual osteotomy surface and the planned surface was measured by a high-precision 3D scanner after surgery.

[0161] Overcut rate: The statistical grinding depth exceeds the planned termination surface (i.e., The proportion of samples with diameters <0mm.

[0162] Maximum overcut depth: Record the maximum overcut depth value among the samples where overcutting occurred.

[0163] Number of soft tissue balance adjustments: Record the number of additional osteotomy corrections performed during the operation to achieve interstitial balance.

[0164] 3. Experimental Results:

[0165] The experimental data are shown in Table 1 below:

[0166] Table 1. Comparison of accuracy and safety data for different surgical methods

[0167] Evaluation indicators Experimental group (this invention) Control group A (traditional navigation) Control group B (manual operation) osteotomy depth error 0.32±0.15mm 0.85±0.42mm 1.84±0.76mm Overcutting rate 0%(0 / 10) 20%(2 / 10) 40%(4 / 10) Maximum overcut depth 0mm 1.2mm 2.5mm Number of soft tissue balance adjustments 0.2±0.4 times 1.5 ± 0.8 times 2.8±1.1 times

[0168] 4. Results Analysis:

[0169] Safety analysis: The overcut rate in the experimental group was 0%, and the maximum overcut depth was 0 mm. Thanks to the active safety control mechanism in step S4, when the distance reaches... The machine was forcibly stopped and retracted at a distance of 0.5mm, eliminating the risk of overcutting due to system delay or operational inertia. In contrast, although control group A had visual cues, two cases still resulted in slight overcutting due to insufficient doctor reaction time; control group B relied entirely on touch, resulting in a high risk of overcutting.

[0170] Accuracy analysis: The osteotomy depth error in the experimental group was lower than that in the two control groups (P<0.01). Deceleration function The application of this technology allows doctors to operate the drill more stably in the precision machining area, avoiding the phenomenon of cutting too far.

[0171] Functional analysis: The experimental group required the fewest soft tissue balance adjustments. This validates the accuracy of the kinematic gap assessment function in step S3, indicating that the surgeon optimized the parameters using virtual modeling before bone reduction, minimizing the need for repeated trial-and-error corrections during surgery.

[0172] In summary, this invention improves osteotomy accuracy and surgical efficiency while ensuring surgical safety by introducing an active safety control model and a sensorless gap assessment algorithm.

Claims

1. A navigation method for unicompartmental knee arthroplasty, characterized in that, Includes the following steps: The system processes CT image data and prosthesis implantation parameters to generate a three-dimensional anatomical model, bone grinding area data, and planned termination surface. It also calibrates the marking probe and handheld drill to obtain tool calibration parameters. A dual registration strategy is implemented using point cloud registration formulas to unify the three-dimensional anatomical model with the actual patient coordinate system established during surgery, in order to generate the final mapping matrix. Knee joint motion data are collected based on kinematic principles, and the joint gap value is calculated using the gap calculation formula to generate a gap curve. The gap curve is used to optimize prosthesis implantation parameters. During the bone grinding process, the spatial position of the handheld grinding drill is monitored in real time by combining the tool calibration parameters and the final mapping matrix. The normal distance from the tip of the handheld grinding drill to the planned termination surface is calculated. A bone grinding heat map is generated based on the normal distance. A control command is generated based on the normal distance using a safety control formula to automatically adjust the handheld grinding drill. Postoperative trajectory data was collected after the bone reshaping was completed and compared with preoperative planning data to generate a surgical evaluation report.

2. The surgical navigation method for unicompartmental knee arthroplasty according to claim 1, characterized in that, The steps of processing CT image data and prosthesis implantation parameters to generate a three-dimensional anatomical model, bone grinding region data, and planned termination surface specifically include: The main control computer receives externally input CT image data, performs image segmentation and three-dimensional reconstruction operations on the CT image data, and generates the three-dimensional anatomical model; The system receives the externally input prosthesis implantation parameters, performs Boolean operations and geometric calculations on the three-dimensional anatomical model, and generates the bone grinding region data and the planned termination surface.

3. The surgical navigation method for unicompartmental knee arthroplasty according to claim 2, characterized in that, The steps for calibrating the dotting probe and handheld drill to obtain tool calibration parameters specifically include: The main control computer receives array position data transmitted by the infrared optical tracker, and calculates and establishes the femoral coordinate system and tibial coordinate system respectively through coordinate transformation algorithm; The tip offset is calculated based on the dotted probe data captured by the infrared optical tracker from the dotted probe. A test command is sent to the handheld drill to verify the physical response function of the telescopic actuation mechanism. The drill calibration parameters are calculated based on the relative pose data of the handheld drill and the dotted probe captured by the infrared optical tracker. The tool calibration parameters include the tip offset and the grinding drill calibration parameters.

4. The surgical navigation method for unicompartmental knee arthroplasty according to claim 3, characterized in that, The steps for generating the final mapping matrix specifically include: The main control computer responds to the doctor's action of using the dotting probe to collect anatomical landmarks, calls the singular value decomposition algorithm, calculates the initial transformation matrix between the anatomical landmarks and the three-dimensional anatomical model, and completes the initial alignment. The dense surface point cloud data generated by the doctor's operation of the dotting probe is collected. Using the initial transformation matrix as the initial value, the surface point cloud data and the three-dimensional anatomical model are iteratively optimized using the point cloud registration formula to obtain the final mapping matrix.

5. The surgical navigation method for unicompartmental knee arthroplasty according to claim 3, characterized in that, The steps for generating the gap curve specifically include: The main control computer records the initial state data of the limb in the natural extension position and the maximum flexion position, and calculates the motion trajectory data between the femoral coordinate system and the tibial coordinate system based on the data captured in real time by the infrared optical tracker during the passive flexion and extension movement. The buckling angle at any given moment is calculated based on the motion trajectory data. For the flexion angle, the three-dimensional anatomical model containing the virtual prosthesis and the motion trajectory data are invoked, and the current joint space value is calculated using the gap calculation formula; The joint gap values ​​at different angles are compiled to generate the gap curve.

6. The surgical navigation method for unicompartmental knee arthroplasty according to claim 3, characterized in that, The step of generating control commands based on the normal distance using a safety control formula to automatically adjust the handheld drill specifically includes: The main control computer combines the drill calibration parameters and the final mapping matrix to calculate the position of the drill tracking target captured in real time by the infrared optical tracker, and calculates the real-time coordinates of the tip. Calculate the normal distance between the real-time coordinates of the tip and the planned termination surface in real time; The display is driven to show the bone grinding heat map over the bone grinding area data according to the normal distance, with different colors corresponding to different normal distance ranges; Based on the real-time calculated normal distance, the motor speed command and extension position command are generated using the safety control formula and sent to the handheld drill via the main control trolley to adjust the speed of the motor drive unit and the retraction state of the extension actuation mechanism.

7. The surgical navigation method for unicompartmental knee arthroplasty according to claim 6, characterized in that, The logic of the security control formula is as follows: When the normal distance is greater than the safety distance threshold, a full-speed motor rotation command and a zero-displacement telescopic position command are generated. When the normal distance is less than or equal to the safety distance threshold and greater than the termination distance threshold, a motor speed command that decreases as the normal distance decreases and a zero-displacement extension / retraction position command are generated. The motor speed command is calculated by a deceleration function. When the normal distance is less than or equal to the termination distance threshold, a motor speed command with zero rotation speed and a telescopic position command with maximum displacement are generated. The safety distance threshold is a safety margin pre-set based on the overall response delay time and the doctor's average operating feed speed. The termination distance threshold is a pre-set limit representing the allowable grinding boundary. The safety distance threshold is greater than the termination distance threshold. The deceleration function is a linear decay function.

8. The surgical navigation method for unicompartmental knee arthroplasty according to claim 5, characterized in that, The steps for generating the surgical evaluation report specifically include: The main control computer prompts the doctor to perform passive flexion and extension exercises, and calculates the postoperative trajectory data based on the data captured in real time by the infrared optical tracker. The postoperative trajectory data is calculated using the gap calculation formula to generate a postoperative gap curve, and the gap deviation between the postoperative gap curve and the expected gap curve generated in the preoperative planning stage is calculated. The postoperative lower limb force line is calculated based on the postoperative trajectory data, and the deviation between the postoperative lower limb force line and the ideal force line is calculated. The postoperative gap curve is compared and analyzed with the preoperative planning data and force line activity data to generate the surgical evaluation report; If the calculated gap deviation exceeds the gap deviation threshold, or the lower limb force line deviation exceeds the force line deviation threshold, then abnormal data will be marked on the display. The gap deviation threshold is preset based on the soft tissue laxity of the knee joint and the wear resistance characteristics of the prosthetic polyethylene pad, while the force line deviation threshold is preset based on the ideal force line range recognized in joint replacement biomechanics research.

9. A navigation system for unicompartmental knee arthroplasty, characterized in that, The navigation method for unicompartmental knee arthroplasty as described in any one of claims 1-8 includes: The calibration module 100 is prepared to process CT image data and prosthesis implantation parameters to generate a three-dimensional anatomical model, bone grinding area data and planning termination surface, and to calibrate the marking probe and hand-held grinding drill to obtain tool calibration parameters. The registration and mapping module 200 is used to perform a dual registration strategy using point cloud registration formulas to unify the three-dimensional anatomical model with the actual patient coordinate system established during surgery, so as to generate a final mapping matrix. The gap assessment module 300 is used to collect motion data of the knee joint based on kinematic principles and calculate the joint gap value using the gap calculation formula to generate a gap curve, which is used to optimize prosthesis implantation parameters. The navigation control module 400 is used to monitor the spatial position of the handheld grinding drill in real time during the bone grinding process by combining the tool calibration parameters and the final mapping matrix, calculate the normal distance from the tip of the handheld grinding drill to the planned termination surface, generate a bone grinding heat map based on the normal distance, and generate control commands based on the normal distance using a safety control formula to automatically adjust the handheld grinding drill. The postoperative verification module 500 is used to collect postoperative trajectory data after bone reshaping and compare it with preoperative planning data to generate a surgical evaluation report.

10. A storage medium having a computer program stored thereon, characterized in that, When executed by a processor, the computer program implements a unicompartmental knee arthroplasty surgical navigation method as described in any one of claims 1-8.

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