SYSTEM AND METHOD FOR PRE-OPERATIVE PLANNING OF A KNEE ENDOPHRSIS

Description

[0001] The present disclosure relates to a system or device for pre-operative planning or selection of an implant type, size, and shape for a (total) knee endoprosthesis, i.e., for a total knee joint replacement (also referred to as "Total Knee Arthroplasty (TKA)"). Furthermore, the disclosure relates to a corresponding method for pre-operative planning or selection of a knee endoprosthesis. State of the art

[0002] Preoperative planning of knee endoprostheses is carried out in a conventional manner using image data that depicts the anatomy—that is, the static shape, position, and structure of the knee joint, which connects the thigh bone (femur), the shin bone (tibia), and the kneecap (patella) to form a single joint. For example, 2D or 3D planning and selection systems exist that can be used to plan and select knee endoprostheses with regard to implant type, implant size, and / or implant shape based on X-ray images, computed tomography data, or magnetic resonance imaging data.

[0003] Studies have shown that a significant proportion of patients whose knee replacement was planned using an existing 2D or 3D planning or selection system and who subsequently received a corresponding knee replacement are dissatisfied with their knee replacement. In particular, knee replacements in these patients lead to an unnatural joint sensation and restricted movement, or even cause pain. Furthermore, these patients also report premature wear and loosening of the implant.

[0004] US 2014 / 222390 A1 discloses methods and devices for pre-operative design and selection of implants or implant components for the knee joint.

[0005] WO 2017 / 196817 A1 discloses a pre-operative method for manufacturing customized implant components. This method does not involve customizing the entire implant. The femoral baseplate and the tibial baseplate are used as standard components.

[0006] WO 2021 / 008892 A1 discloses a method for designing two-part joint prostheses.

[0007] US 2014 / 222157 A1 discloses methods for obtaining kinematic information regarding a joint under weight loading and methods for designing implants based on the obtained kinematic information.

[0008] WO 2020 / 163358 A1 discloses a method and system for an arthroplasty procedure, for example, on the knee. The joint is analyzed preoperatively in a variety of flexion positions, and based on this, the performance of a knee joint is predicted using a static patient model.

[0009] US 2019 / 0380792 A1 discloses a method for virtual guidance for orthopedic surgical procedures. This includes superimposing a virtual model of a body part from a surgical plan onto the body part for attaching a prosthesis, and a display for preparing the body part and / or attaching the prosthesis to the body part. Brief description of the revelation

[0010] The object of the present disclosure is to avoid or at least mitigate the disadvantages of the prior art. In particular, the planning and selection of knee endoprostheses should be improved so that the knee endoprosthesis functions well and a natural joint sensation develops in as many patients as possible who receive a knee endoprosthesis. In particular, as many patients as possible should not experience any restricted movement or pain. Furthermore, premature wear and loosening of the implant should also be prevented.

[0011] This object is achieved by a system or a device for pre-operative planning or selection of a knee endoprosthesis according to claim 1 and a method for pre-operative planning or selection of a knee endoprosthesis according to claim 10. Advantageous embodiments and further developments are claimed in the subclaims and / or are explained below.

[0012] The disclosure initially relates to a system or a device for pre-operative planning or selection of an implant type (an implant type) and an implant size and an implant shape of a knee (total) endoprosthesis, that is to say a total knee joint replacement ("Total Knee Arthoplasty TKA"), comprising: a data provision unit which is configured to provide at least patient-specific or patient-individual kinematic data which are generated during flexion or bending of a knee orknee joint of a patient, and a control unit which is configured to process the kinematic data provided by the data providing unit and to determine the implant type and the implant size and the implant shape taking into account at least the kinematic data, that is to say on the basis of at least the kinematic data, wherein the control unit is configured to determine that patient-specific pre-operative kinematics of the knee joint can best be simulated with a so-called medial pivot implant, and to determine that, if the patient-specific pre-operative kinematics of the patient show a pronounced femoral roll-back, the kinematics of the knee joint can best be simulated with a so-called PS implant, which enforces, supports and promotes such a femoral roll-back.

[0013] In other words, according to the present disclosure, the flexion or bending movement of the knee joint and thus an actual pre-operative kinematic movement sequence in the patient's knee joint are taken into account during the pre-operative planning or selection of the knee endoprosthesis. The implant type, size, and shape are determined or selected in such a way that, post-operatively, the implanted knee endoprosthesis replicates the pre-operative kinematic movement sequence and thus the pre-operative kinematics as closely as possible. The present disclosure is therefore based on the core idea that the kinematic phenotype, i.e., the kinematic appearance of the patient, in particular the patient's movement sequence in the knee joint, is taken into account during the planning or selection of the knee endoprosthesis.

[0014] According to the disclosure, preoperative planning or selection is understood to mean planning or selection prior to a surgical procedure. Intraoperative adjustment or planning of the knee endoprosthesis is therefore not the subject of the present disclosure. The preoperative planning or selection is thus completed prior to a patient's surgery, i.e., the device according to the disclosure, or in particular its control unit, is configured to determine the implant type, size, and shape based on at least the kinematic data prior to the patient's surgery.

[0015] The kinematic data can be taken into account in such a way that they determine or influence the implant size. For example, the control unit can scale the implant accordingly depending on the kinematics in the knee joint so that the size of the implant is optimally adapted to the respective patient. Additionally or alternatively, the kinematic data can be taken into account in such a way that they determine or influence the implant shape. The implant shape is determined, for example, by the implant family / product family. Alternatively or additionally, the implant shape can also be understood to mean, for example, local, section-by-section, i.e. area-by-area adjustments or changes, such as reinforcements of the implant. It can be provided, for example, that the implant is locally reinforced taking the kinematic data into account, for example by locally ormore material is used in certain sections or by providing reinforcement structures such as ribs locally or in certain sections. Additionally or alternatively, the kinematic data can be taken into account in such a way that they determine or influence the implant type. An implant family / product family can contain different implant types / implant types. For example, the control unit can determine that the patient-specific pre-operative kinematics of the knee joint can be best replicated with a so-called medial pivot implant. If the patient's natural, pre-operative kinematics show pronounced femoral rollback, the control unit can, for example, determine that the kinematics of the knee joint can be best replicated with a so-called PS implant, which enforces, supports and promotes this type of femoral rollback.

[0016] It is advantageous if at least two influencing variables from the implant type, the implant size, and the implant shape are determined or influenced by the control unit, for example, the implant type and the implant size. A particularly preferred embodiment is characterized in that both the implant type, the implant size, and the implant shape are determined or influenced by the control unit. Particularly preferably, the implant size, the implant family, and the implant type are determined by the control unit.

[0017] The data provision unit can have an input unit and / or a detection unit. In other words, the data provision unit can have an input unit or a detection unit, or both an input unit and a detection unit. It can be provided that the kinematic data can be entered (manually) by a user via the input unit. Alternatively or additionally, it can be provided that the kinematic data is detected via the detection unit.

[0018] The input unit can be a user interface, and the kinematic data can be entered by the user via an input device of the user interface, for example, via a keyboard, a mouse, a touchscreen, speech recognition, etc. For example, the user can examine the mobility of the knee / knee joint preoperatively and enter the kinematic data obtained or obtained from this examination into the input device. The advantage here is that the mobility or flexion of the knee / knee joint is observed during the manual preoperative examination over the entire range of motion, i.e., from maximum extension to maximum flexion and back, thus obtaining kinematic data over the entire range of motion.If damage to the knee joint to be operated on no longer allows adequate determination of natural kinematics, the contralateral knee joint can also be examined, and the data obtained for the contralateral knee joint can be used. In other words, if, for example, the left knee joint is damaged, the right knee joint can be examined, or vice versa. The data provision unit can provide the kinematic data obtained via the input unit to the control unit for further processing.

[0019] The recording unit can be a camera or at least have a camera which is configured to record the kinematic data. For example, the recording unit or the camera can record or record a patient's physiological gait. According to Jacquelin Perry, a patient's physiological gait can be divided into individual (gait) phases of a double step, whereby the flexion or bending of the knee or knee joint changes continuously over the temporal sequence of the gait phases of the double step. Thus, patient-specific or patient-individual kinematic data can be recorded via the at least one camera, which is obtained during flexion or bending of a patient's knee, in particular over the temporal sequence of the gait phases of the double step.In principle, multiple cameras can also be provided to capture the kinematic data from different directions, for example, from the front, from the back, from one side, etc. According to this exemplary embodiment, the flexion or bending of the knee is thus not recorded over the entire range of motion, but only over the patient's gait, i.e., the temporal sequence of the gait phases of the double step. Even kinematic data obtained over this limited range of motion is generally sufficient, particularly for older patients, to determine a suitable implant type / size / shape by providing this kinematic data from the data provision unit to the control unit and by processing this kinematic data in the control unit.

[0020] Furthermore, at least one robot arm can be provided, which is configured or prepared to examine the mobility of the knee / knee joint. For example, two robot arms can be provided, with one of the robot arms grasping the patient's thigh, one of the robot arms grasping the patient's lower leg, and the two robot arms flexing or bending the knee, preferably over the entire range of motion, while recording the kinematic data. Thus, according to this preferred embodiment, the recording unit can be contained in the at least one robot arm. Alternatively, sensors attached to a patient, for example, inertial measurement units (IMUs), can be used to record the kinematics.When an apparatus such as a robotic arm or sensors such as inertial measuring units are used to acquire the kinematic data, standardized and comparable kinematic data can be provided in a particularly advantageous manner.

[0021] The kinematic data can contain a variety of data sets obtained from different loading or stress situations. For example, the patient's gait can be analyzed both under the load of their body weight alone and under additional loads carried by the patient. For example, there may be data sets for body weight, an additional load of 5 kg, an additional load of 10 kg, etc. The kinematic data can thus also provide information about how a considered kinematic parameter changes under load with the flexion or bending angle of the knee.

[0022] The kinematic data can contain at least one kinematic parameter, or at least one kinematic parameter can be determined from the kinematic data. Accordingly, it can be provided that the data provision unit records / provides and / or the control unit determines how the at least one kinematic parameter behaves or changes during flexion or bending of the knee. The kinematic data can also contain a plurality of kinematic parameters, or a plurality of kinematic parameters can be determined from the kinematic data. Accordingly, it can be provided that the data provision unit records / provides and / or the control unit determines how several kinematic parameters behave or change during flexion or bending of the knee.

[0023] It can be provided that the control unit determines the implant type, implant size, and implant shape directly from the at least one kinematic parameter. Alternatively, it can be provided that the control unit processes the at least one kinematic parameter in order to assign a predetermined or predefined kinematic phenotype to the patient. The implant type / implant size / implant shape can then be determined on the basis of the kinematic phenotype assigned to the patient. The implant type / implant size / implant shape can thus alternatively also be determined indirectly from the at least one kinematic parameter by first determining the patient's kinematic phenotype and then selecting / planning the knee endoprosthesis based on the kinematic phenotype.This means that the implant type / size / shape cannot be determined directly based on the kinematic parameter. However, both the direct and indirect determination of implant type / size / shape aim to achieve optimal kinematics for the patient postoperatively through preoperative analysis and planning.

[0024] The at least one kinematic parameter, which is considered as a function of the flexion or flexion angle of the knee, can be, for example, the rotation of the tibia relative to the femur, which can also be referred to as internal-external tibial rotation. For example, the extent of the tibial rotation and / or the location of the pivot point of the tibial rotation can be considered. Alternatively or additionally, the at least one kinematic parameter can be a femoral rotation, i.e. a rotation of the femur relative to the pelvis. Alternatively or additionally, the at least one kinematic parameter can be the so-called femoral rollback, in particular its extent and medio-lateral symmetry. Alternatively or additionally, the at least one kinematic parameter can be an antero-posterior femoral shift. Furthermore, it is also conceivable that the at least one kinematic parameter can be a varus or varus malposition (bow legs) or a valgus ora valgus deformity (knock-knees). For example, a change from varus to valgus (or vice versa) can be observed / evaluated via the flexion or bending angle. At least one kinematic parameter can also be abduction or adduction in the knee joint.

[0025] Preferably, at least one of the aforementioned kinematic parameters is considered when determining the implant type / implant size / implant shape. However, several of the aforementioned kinematic parameters can also be considered. It is particularly advantageous if the at least one kinematic parameter is observed, recorded, and thus stored over the entire flexion or bending movement of the knee. However, it is also conceivable that the at least one kinematic parameter is only considered during a normal stepping movement, for example, a double step.

[0026] The formation of predetermined or predefined kinematic phenotypes, on the basis of which the selection or planning of the implant can be carried out, can also be carried out based on the course of at least one of the aforementioned kinematic parameters over the extension-flexion of the knee joint.

[0027] According to a preferred exemplary embodiment, the data provision unit is configured to provide data on knee joint instability to the control unit, and the control unit is configured to also process the data on knee joint instability provided by the data provision unit and to determine the implant type, implant size, and implant shape, also taking into account the data on knee joint instability. The instability of the knee joint can, for example, be described using the so-called kinematic envelope. In the kinematic envelope, at least one (preferably all) of the aforementioned kinematic parameters are recorded or measured over the entire range of motion of the knee joint, i.e., during flexion of the knee joint from greatest possible extension to greatest possible flexion and back.The test is performed by applying a varus or valgus load through lateral force, allowing the mediolateral stability of the knee joint to be assessed across the entire range of motion. Alternatively, knee instability can be assessed using the Lachmann test. This test is particularly suitable for determining the anteroposterior stability of the knee joint.

[0028] When processing the data provided by the data provision unit, the control unit can, for example, use simulation models or carry out simulations. Furthermore, it can be provided that the control unit has neural networks and supports artificial intelligence in processing the data. Alternatively or additionally, it can be provided that the control unit processes the data provided to it, in particular the kinematic data, in order to assign a predetermined or predefined kinematic phenotype to the patient. It can be preferred if the data on the instability of the knee joint are recorded by a robot, for example a robot arm, so that standardized and comparable data are available. This data, i.e. the results of the stability examination orSoft tissue characterization can be used as input parameters for simulation models to account for a specific soft tissue situation.

[0029] The data provision unit can be configured to provide anatomical data in addition to the kinematic data, and the control unit can be configured to process the anatomical data and the kinematic data and to determine the implant type, the implant size, and the implant shape based on the anatomical data and the kinematic data. Anatomical data preferably refers to image data, for example, X-ray images and / or computed tomography data and / or magnetic resonance imaging data. Accordingly, according to a preferred embodiment, both kinematic data and / or features and anatomical data and / or features are used for the preoperative planning and / or selection of a knee endoprosthesis.

[0030] Furthermore, the data provision unit can be configured to provide patient data in addition to the kinematic data, and the control unit can be configured to process the patient data and the kinematic data and to determine the implant type, the implant size, and the implant shape based on the patient data and the kinematic data. The patient data preferably contains at least one parameter from the parameters weight, gender, height, activity level, and disease of adjacent joints. Accordingly, according to a preferred embodiment, both kinematic data or characteristics and patient data are used for the preoperative planning or selection of a knee endoprosthesis.

[0031] According to a particularly preferred embodiment, the data provision unit is configured to provide patient data and anatomical data in addition to the kinematic data, and the control unit is configured to process the patient data, the anatomical data, and the kinematic data and to determine the implant type / kind, the implant size, and the implant shape based on the patient data, the anatomical data, and the kinematic data. Accordingly, according to the particularly preferred embodiment, both kinematic data or features, anatomical data or features, and patient data are used for the preoperative planning or selection of a knee endoprosthesis, in particular with regard to implant type / size / shape.

[0032] If the data provision unit provides anatomical data to the control unit, it can be provided that the anatomical data contain at least one anatomical parameter or that at least one anatomical parameter can be determined from the anatomical data. The at least one anatomical parameter can thus be provided to the control unit by the data provision unit. Alternatively, the control unit can also be configured to determine at least one anatomical parameter from the anatomical data provided to it. The control unit can in principle also be configured to determine an anatomical phenotype of the patient on the basis of the at least one anatomical parameter. It can therefore in principle be provided that the determination in the control unit takes into account both the anatomical phenotype and the kinematic phenotype of the patient.An anatomical feature basically describes the static shape, position and structure of the knee joint, especially of the femur, tibia and patella, which connect the knee joint together to form a joint.

[0033] The device or system can in principle also contain a manufacturing unit configured to manufacture or produce the implant / knee endoprosthesis or at least individual parts / components of the implant / knee endoprosthesis based on the implant type, size, and shape determined by the control unit. In this context, it can be provided, for example, that a 3D CAD model is automatically adapted. For example, the control unit can be coupled to the manufacturing unit. The manufacturing unit can be an additive manufacturing unit, such as a 3D printer. The control unit can transmit CAD data of the knee endoprosthesis to the manufacturing unit, and the manufacturing unit in the form of the 3D printer can quickly and easily manufacture the implant.It is also conceivable that production can take place on-site in the hospital, so that there is hardly any production-related delay between the planning and selection of the implant / knee endoprosthesis and the performance of an operation by a doctor.

[0034] The present disclosure further relates to a method for pre-operative planning or selection of an implant type and an implant size and an implant shape of a knee endoprosthesis, comprising the steps of: providing at least patient-specific or patient-individual kinematic data which are used during flexion orFlexion of a patient's knee is obtained; processing the kinematic data and determining the implant type and size and the implant shape based on at least the kinematic data; and determining that patient-specific pre-operative kinematics of the knee joint can be best replicated with a so-called medial pivot implant; or determining that, if the patient-specific pre-operative kinematics of the patient show a pronounced femoral roll-back, the kinematics of the knee joint can be best replicated with a so-called PS implant, which enforces, supports and promotes such femoral roll-back.

[0035] The method preferably comprises the step of determining the implant type and the implant size and the implant shape such that a pre-operative kinematic movement sequence or pre-operative kinematics is reproduced post-operatively by an implanted knee endoprosthesis.

[0036] Preferably, the kinematic data contain at least one kinematic parameter or at least one kinematic parameter can be determined from the kinematic data, and the method comprises the step of determining how the at least one kinematic parameter behaves or changes during flexion or bending of the knee.

[0037] The method may include the step of: directly determining the implant type, implant size, and implant shape from the at least one kinematic parameter. Alternatively, the method may include the steps of: processing the at least one kinematic parameter; assigning a predetermined kinematic phenotype to the patient; and indirectly determining the implant type, implant size, and implant shape based on the kinematic phenotype assigned to the patient.

[0038] The method may comprise the following method step: recording or detecting at least one of the following kinematic parameters as a function of the flexion or flexion angle of the knee: rotation of the tibia relative to the femur; internal-external femoral rotation; internal-external tibial rotation; extent of femoral rotation; location of the pivot point of femoral rotation; femoral rollback; extent of femoral rollback; medio-lateral symmetry of femoral rollback; antero-posterior femoral shift; varus or valgus; abduction or adduction.

[0039] Furthermore, the method may include the step of providing data on instability of the knee joint; processing the provided data on the instability of the knee joint; and determining the implant type and the implant size and the implant shape, also taking into account the data on the instability of the knee joint.

[0040] Preferably, the method includes the steps of: providing anatomical data in addition to the kinematic data; processing the anatomical data and the kinematic data; and determining the implant type, implant size, and implant shape based on the anatomical data and the kinematic data. Alternatively, the method may include the steps of: providing patient data in addition to the kinematic data; processing the patient data and the kinematic data; and determining the implant type, implant size, and implant shape based on the patient data and the kinematic data.Alternatively, the method may comprise the steps of: providing anatomical data and patient data in addition to the kinematic data; processing the anatomical data, the patient data, and the kinematic data; and determining the implant type, size, and shape based on the anatomical data, the patient data, and the kinematic data.

[0041] Further preferred method steps will be apparent to the person skilled in the art from the above description of the device according to the disclosure. It should be noted that the method according to the disclosure is a pre-operative method and does not include any method step of surgical or therapeutic treatment of the human body. Short description of the characters

[0042] The disclosure is further explained below with the help of figures. They show: Fig. 1 shows a schematic view of a first embodiment of a device according to the disclosure for pre-operative planning or selection of a knee endoprosthesis; Fig. 2 shows a schematic view of a second embodiment of a device according to the disclosure for pre-operative planning or selection of a knee endoprosthesis. Fig. 3 shows four predetermined kinematic types that can be assigned to a patient; and Fig. 4 shows a schematic view of a third embodiment of a device according to the disclosure for pre-operative planning or selection of a knee endoprosthesis. Character description

[0043] The figures are merely schematic in nature and serve solely to facilitate understanding of the disclosure. Like elements are provided with the same reference numerals. The features of the individual embodiments can be interchanged.

[0044] Fig. 1shows a schematic view of a first embodiment of a device 2 according to the disclosure for pre-operative planning or selection of a knee endoprosthesis. The device 2 has at least one data provision unit 4 and a control unit 6. According to the first embodiment, a user or physician 8 examines a patient 10, in particular the mobility of the knee joint 12 of the patient 10. In doing so, the physician 8 bends the knee joint 12 from a maximum possible extension to a maximum possible flexion and back.

[0045] The physician 8 examines how kinematic parameters behave during flexion of the knee joint 12. Kinematic parameters include, for example, internal-external tibial rotation, particularly with regard to its severity and / or location of the pivot point, femoral rotation, femoral rollback, particularly its severity and medio-lateral symmetry, antero-posterior femoral shift, a varus or valgus malalignment, abduction or adduction, etc. According to the first exemplary embodiment, the physician 8 determines how at least one of the aforementioned kinematic parameters, preferably how several of the aforementioned kinematic parameters, behave or change during flexion or bending of the knee joint 12.

[0046] According to the first embodiment, the data provision unit 4 has an input unit 14 in the form of a user interface. The input unit 14 has an input device 16, which Fig. 1for example, in the form of a touchscreen. The doctor 8 can thus enter his observations during the examination of the patient 10 via the input device 16. For example, the input can be made such that the doctor 8 enters estimated or measured angles or displacements of at least one of the mentioned kinematic parameters at different flexion or bending angles of the knee joint 12 into the input device 16. Alternatively, the doctor 8 can evaluate at least one, preferably several of the mentioned kinematic parameters at different flexion or bending angles of the knee joint 12, for example as small, normal, or large.It can be provided that questions regarding the kinematic movement sequence of the knee joint 12 of the patient 10 are displayed to the physician 8 via the input device 16 designed as a touchscreen, which the physician 8 can answer using predefined answer options according to his subjective perception during the examination of the patient 10. Finally, the inputs or answers of the physician 8 are stored in the data provision unit 4, in particular in a memory 17 of the data provision unit 4, as kinematic data 18.

[0047] In the memory 17 of the data provision unit 4, preferably but not necessarily, anatomical data 20 and patient data 22 are also stored in addition to the kinematic data 18. The anatomical data 20 are, for example, X-ray images, CT data, or MRI data. The patient data 22 relate, for example, to weight, gender, height, activity level, disease of adjacent joints, etc. The physician 8 can also enter the patient data 22 via the input device 16, which is here designed as a touchscreen. With regard to the patient data 22, it can also be provided that questions about the patient 10 are displayed to the physician 8 via the input device 16, which is designed as a touchscreen. The physician 8 can answer these questions using predefined answer options or by manually entering, for example, weight and height.

[0048] Finally, the data provision unit 4 provides at least the kinematic data 18, preferably the kinematic data 18 together with the anatomical data 20 and / or the patient data 22, to the control unit 6. The control unit 6 processes the data provided to it, preferably the kinematic data 18, the anatomical data 20, and the patient data 22. The control unit 6 can use simulation models, perform simulations or calculations, or even have neural networks, so that artificial intelligence can also assist in processing the data. According to the first exemplary embodiment, the control unit 6 directly determines an implant type, an implant size, and an implant shape based on the data provided to it, in particular the kinematic data 18, the anatomical data 20, and the patient data 22.For example, the control unit 6 can determine an implant size of the knee endoprosthesis based on the data provided to it. Alternatively or additionally, the control unit 6 can determine the implant shape of the knee endoprosthesis. In particular, the control unit 6 can determine that, based on the data provided to it, adjustments or changes to the implant shape, such as reinforcements, need to be made in certain sections. Alternatively or additionally, the control unit 6 can determine, based on the data provided to it, which implant type can best replicate the pre-operative kinematics of the knee joint 12 of the patient 10, for example, with a medial pivot implant or a PS implant.

[0049] The control unit 6 can send the result(s) of its determination back to the data provision unit 4, which can display it(s) to the physician 8 via the input device 16 configured as a touchscreen. The physician 8 can then use the implant or knee endoprosthesis displayed to him / her for the subsequent surgery of the patient 10, which is optimally adapted to the patient 10, in particular to his / her anatomy (taking into account the anatomical data 20), his / her pre-operative kinematics (taking into account the kinematic data 18), and other properties or physical characteristics of the patient to be considered (taking into account the patient data 22).Alternatively, the control unit 6 can forward CAD data of the knee endoprosthesis or at least one part / component of the knee endoprosthesis to an optionally provided manufacturing unit 24, which is designed, for example, as a 3D printer, and the manufacturing unit 24 can manufacture or produce the (component / part of the) knee endoprosthesis.

[0050] Fig. 2shows a schematic view of a second embodiment of a device 2 according to the disclosure for pre-operative planning or selection of a knee endoprosthesis. The device 2 also has at least one data provision unit 4 and a control unit 6. According to the second embodiment, the data provision unit 4 has a detection unit 26. The detection unit 26 can be designed as one or more cameras that detect or record the physiological gait of a patient 10. The physiological gait of the patient 10 can be divided into the following phases of a double step, with the percentage of the double step being indicated in parentheses: initial contact (0%), load transfer (0-12%), middle stance phase (12-31%), stance phase end (31%-50%), swing phase preparation (50-62%), swing phase beginning (62-75%), middle swing phase (75-87%), and swing phase end (87-100%).The acquisition unit 26 acquires patient-specific or patient-individual kinematic data 18, in particular photos or videos, regarding the temporal sequence of the gait phases of the double step, and stores these kinematic data 18 in the memory 17. Kinematic data 18 can also be acquired for different load or stress situations (for example, a data set for the body weight of the patient 10, a data set for an additional load of 5 kg, a data set for an additional load of 10 kg, etc.). Also according to the embodiment of the . Fig. 2 In addition to the kinematic data 18, anatomical data 20 and patient data 22 are preferably, but not necessarily, stored in the memory 17 of the data provision unit 4. The physician 8 can also enter the patient data 22 here via the input device 16 of the input unit 14, which is here designed as a touchscreen.

[0051] According to the embodiment of the Fig. 2 The control unit 6 determines, on the basis of the kinematic data 18, a curve of a kinematic parameter over the temporal sequence of the gait phases of the double step. All of the already mentioned embodiments of the Fig. 1 The kinematic parameters mentioned are conceivable in this context. According to the design of the Fig. 2 The control unit 6 determines, in particular, how adduction and abduction behave, i.e., in particular, how an adduction or abduction angle α behaves over the temporal progression of the gait phases of the double step (from 0% to 100%). Once the control unit 6 has performed this processing of the kinematic data 18, it can assign a predetermined or predefined kinematic phenotype to the patient 10.

[0052] For example, in Fig. 3Four predetermined or predefined kinematic phenotypes are shown, i.e. four examples of how the adduction or abduction angle α can behave or change over the temporal course of the gait phases of the double step (from 0% to 100%). The control unit 6 now determines which of the four predetermined or predefined kinematic phenotypes the patient best fits by comparing the adduction or abduction angle α over the temporal course of the gait phases of the double step of the patient 10 with the four in Fig. 3 shown kinematic phenotypes and assigns one of the four kinematic phenotypes to the patient 10. Finally, according to the embodiment of the Fig. 2the implant type and the implant size and the implant shape are determined based on the kinematic phenotype assigned to the patient 10. For example, one of the four kinematic phenotypes may be assigned a smaller medial pivot implant, one of the four kinematic phenotypes may be assigned a larger medial pivot implant, one of the four kinematic phenotypes may be assigned a smaller PS implant, and one of the four kinematic phenotypes may be assigned a larger PS implant. According to the embodiment of the Fig. 2 the implant type / implant size / implant shape is not determined directly, but the kinematic phenotype of the patient 10 is determined indirectly from the kinematic parameter and the selection / planning of the knee endoprosthesis is carried out on the basis of the kinematic phenotype.

[0053] Also for the design of the Fig. 2applies that the result or results of the determination of the control unit 6 can be displayed to the doctor 8 or parts / components of the knee endoprosthesis can be manufactured directly via the manufacturing unit 24.

[0054] Fig. 4shows a schematic view of a third exemplary embodiment of a device 2 according to the disclosure for the pre-operative planning or selection of a knee endoprosthesis. The device 2 also has at least one data provision unit 4 and a control unit 6. According to the third exemplary embodiment, the data provision unit 4 has two robot arms, namely a first robot arm 28, which grips the thigh of a patient 10, and a second robot arm 30, which grips the lower leg of the patient 10. The first robot arm 28 and the second robot arm 30 are coordinated with one another in such a way that they can flex or bend the knee joint 12 of the patient 10, preferably over the entire range of motion. The robot arms 28, 30 can, for example, be operated together with the flexion or bending of the knee joint 12 of the patient 10.Flexion of the knee joint 12 performs a rotation of the tibia relative to the femur and detects / records which angle of rotation is possible depending on the flexion or bending of the knee joint 12. The robot arms 28, 30 can have a sensor system, for example a force sensor, which prevents excessive rotation, which could lead to tearing of ligaments in the knee joint 12, especially if resistance becomes too great. The two robot arms 28, 30 are thus to be regarded as detection units 24 or have detection units 24. Other of the aforementioned kinematic parameters can also be determined or recorded via the two robot arms 28, 30.

[0055] If according to the embodiment of the Fig. 4When flexing the knee joint 12, a varus load or a valgus load is applied by lateral force application by the two robot arms 28, 30, the medio-lateral stability of the knee joint 12 can be recorded over the entire range of motion. Thus, it is possible to determine, in addition to the kinematic data 18, specific instability data 32 of the knee joint 12. This instability data 32 of the knee joint 12 can be stored together with the kinematic data 18, the anatomical data 20, and the patient data 22 in the memory 17 of the data provision unit 4 and provided to the control unit 6 for further processing. Furthermore, the statements regarding the above embodiments apply mutatis mutantis to the embodiment of the Fig. 4 . List of reference symbols

[0056] 2Device 4Data provision unit 6Control unit 8Doctor 10Patient 12Knee joint 14Input unit 16Input device 17Memory 18Kinematic data 20Anatomical data 22Patient data 24Manufacturing unit 26Acquisition unit 28First robot arm 30Second robot arm 32Instability data

Claims

1. Device (2) for pre-operative planning or selection of an implant type and an implant size and an implant shape of a knee endoprosthesis, comprising: a data provision unit (4) which is adapted to provide at least patient-specific kinematic data (18) obtained during flexion of the knee joint (12) of a patient (10); and a control unit (6) that is adapted to process the kinematic data (18) provided by the data provision unit (4) and to determine the implant type and the implant size and the implant shape based on at least the kinematic data (18), characterized in that the control unit (6) is configured: to determine that a patient-specific pre-operative kinematics of the knee joint (12) can be best simulated with a so-called medial pivot implant; and to determine that, if the patient-specific pre-operative kinematics of the patient (10) shows a distinct femoral roll-back, the kinematics of the knee joint (12) can best be simulated with a so-called PS implant, which enforces, supports and promotes such a femoral roll-back.

2. The device (2) according to claim 1, wherein the control unit (6) is configured to pre-operatively determine the implant type and the implant size and the implant shape such that post-operatively an implanted knee endoprosthesis simulates a pre-operative kinematic motion sequence.

3. The device (2) according to claim 1 or 2, wherein the kinematic data (18) contains at least one kinematic parameter or at least one kinematic parameter can be determined from the kinematic data (18), and the data provision unit (4) pre-operatively passes on to the control unit (6), and / or the control unit (6) pre-operatively determines from the kinematic data (18) how the at least one kinematic parameter changes during flexion or bending of the knee joint (12).

4. The device (2) according to claim 3, wherein the control unit (6) is adapted to determine pre-operatively the implant type and the implant size and the implant shape directly from the at least one kinematic parameter; or the control unit (6) is adapted to process the at least one kinematic parameter pre-operatively in order to assign a predetermined kinematic phenotype to the patient (10) and to determine the implant type and the implant size and the implant shape indirectly on the basis of the kinematic phenotype assigned to the patient (10).

5. The device (2) according to any of preceding claims 1 to 4, wherein the data provision unit (4) is adapted to provide pre-operatively instability data (32) about an instability of the knee joint (12) to the control unit (6) and the control unit (6) is adapted to process pre-operatively also the instability data (32) provided by the data provision unit (4) about the instability of the knee joint, and to determine the implant type and the implant size and the implant shape also taking into account the data about the instability of the knee joint (12).

6. The device (2) according to any of preceding claims 1 to 5, wherein the data provision unit (4) is adapted to provide anatomical data (20) in addition to the kinematic data (18) and the control unit (6) is adapted to pre-operatively process the anatomical data (20) and the kinematic data (18) and to pre-operatively determine the implant type and the implant size and the implant shape based on the anatomical data (20) and the kinematic data (18).

7. The device (2) according to any of preceding claims 1 to 5, wherein the data provision unit (4) is adapted to provide patient data (22) in addition to the kinematic data (18), and the control unit (6) is adapted to pre-operatively process the patient data (22) and the kinematic data (18) and to pre-operatively determine the implant type and the implant size and the implant shape based on the patient data (22) and the kinematic data (18).

8. The device (2) according to any of preceding claims 1 to 5, wherein the data provision unit (4) is adapted to provide patient data (22) and anatomical data (20) in addition to the kinematic data (18) and the control unit (6) is adapted to pre-operatively process the patient data (22), the anatomical data (20) and the kinematic data (18) and to pre-operatively determine the implant type and the implant size and the implant shape based on the patient data (22), the anatomical data (20) and the kinematic data (18).

9. The device (2) according to claim 5, wherein the data provision unit (4) is adapted to provide patient data (22) and anatomical data (20) in addition to the kinematic data (18) and the instability data (32) and the control unit (6) is adapted to pre-operatively process the patient data (22), the anatomical data (20), the instability data (32), and the kinematic data (18), and to pre-operatively determine the implant type and the implant size and the implant shape based on the patient data (22), the anatomical data (20), the instability data (32) and the kinematic data (18).

10. A method for the pre-operative planning or selection of an implant type and an implant size and an implant shape of a knee endoprosthesis, comprising the steps of: Providing at least patient-specific kinematic data (18) obtained during flexion of the knee joint (12) of a patient (10); Processing the kinematic data (18) and determining the implant type and the implant size and the implant shape based on at least the kinematic data (18); and Determining if the patient-specific pre-operative kinematics of the patient (10) show a distinct femoral roll-back; and Determining that the patient-specific pre-operative kinematics of the knee joint (12) can be best simulated with a so-called medial pivot implant; or Determining that the patient-specific pre-operative kinematics of the knee joint (12) can be best simulated with a so-called PS implant, which forces, supports and promotes such a femoral roll-back.

11. The method according to claim 10, further comprising the step of: Pre-operatively determining the implant type, the implant size and the implant shape such that a pre-operative kinematic motion sequence is simulated post-operatively by an implanted knee endoprosthesis.

12. The method according to claim 10 or 11, wherein the kinematic data (18) contains at least one kinematic parameter or at least one kinematic parameter can be determined from the kinematic data (18), and the method comprises the step of: pre-operatively determining how the at least one kinematic parameter changes during flexion or bending of the knee joint (12).

13. The method according to claim 12, further comprising the step of: directly determining pre-operatively the implant type and the implant size and the implant shape from the at least one kinematic parameter; or comprising the steps of: pre-operatively processing the at least one kinematic parameter; pre-operatively assigning a predetermined kinematic phenotype to the patient (10); and indirectly pre-operatively determining the implant type and the implant size and the implant shape on the basis of the kinematic phenotype assigned to the patient (10).

14. The method according to any of claims 10_to 13, further comprising the step of: pre-operatively providing instability data (32) about an instability of the knee joint (12); pre-operatively processing the provided instability data (32); and pre-operatively determining the implant type and the implant size and the implant shape, also taking account of the instability data (32).