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The NextAR™ TKA Platform is intended to be used to support the surgeon during total knee replacement procedures by providing information on bone resections, ligaments behavior, instrument and implant positioning.

The NextAR™ TKA Platform is intended to be used in combination with NextARTM stereotaxic instruments, the MyKnee® NextAR™ cutting guides, and general surgical instruments to implant the GMK Sphere Total knee system and perform ligament balancing. As an optional display, the smart glasses can be used auxiliary to the NextAR Platform to view the same 2D stereotaxic information as presented by the NextAR Platform.

The smart glasses should not be relied upon solely and should always be used in conjunction with the primary computer display.

The MyKnee® NextAR cutting guides include a camera/target holder and a PSI MyKnee® cutting guide both for tibia and femur. The MyKnee® cutting guides must be used as anatomical cutting blocks specific for a single patient anatomy, to assist in the positioning of total knee replacement components intraoperatively and in guiding the marking of bone before cutting. MyKnee® NextAR TKA cutting guides are for single use only.

The NextAR™ stereotaxic instruments are intended to be used to surgeon during specific orthopedic surgical procedures by providing information on bone resections, ligaments behavior, instrument and implant positioning. The NextAR™ stereotaxic instruments, when registered with the myKnee NextAR TKA cutting guides, provide reference to a patient's rigid anatomical structures, such as the femur and tibia, that can be identified relative to pre-operative CT based planning.

The NextAR™ TKA Platform is a CT based computer-assisted surgical navigation platform used in total knee replacement surgery and includes the following components:

• navigation software which displays information to the surgeon in real-time;
• Augmented Reality glasses;
• optical tracking system;
• PC based hardware platform;
• MyKnee NextAR Cutting Blocks; and
• reusable surgical instruments for total knee replacement procedures.

The system operates on the common principle of stereotaxic technology in which passive markers are mounted on the bones and an infrared camera is used to monitor the spatial location of the markers to avoid intraoperative registration of bony landmarks. Tracking sensors attached to the bones enable the surgeon to view the position and orientation of bones and instrumentation relative to preoperative data in real-time while performing the surgical procedure. The tracking sensors are provided sterile.

The NextAR™ TKA Platform aids the surgeon in executing the surgical plan by visualizing all the information in real time in a screen monitor. The placement of the implants is performed by cutting the bones using MyKnee® NextAR™ Cutting Blocks while reusable surgical instrumentation (provided non-sterile) guided by the tracking sensors can be used for recut. Although the position of the implants can be validated to assess the correct execution of the planning, the surgeon can change the surgical plan intraoperatively by analyzing the 3D models of the patient, the CT scan, and the 3D geometry of the implants.

The MyKnee® NextAR™ Cutting Blocks, manufactured from medical grade nylon, are single use patient-specific blocks which are designed from patient MRI or CT images. The blocks are designed to be used in standard medial or lateral parapatellar surgical approaches with each set comprised of a femoral block, a tibial block, and two bone models of the patient's femur and tibia (optional). The femoral cutting blocks are provided in right and left configurations in sizes 1 to 7 and 1+ to 6+ and the tibial cutting blocks are provided in right and left configurations in sizes 1 to 6. The blocks are provided sterile via gamma irradiation or non-sterile.

The FDA 510(k) summary for the NextAR™ TKA Platform (K193559) provides details on the device's acceptance criteria and the studies conducted to prove its performance.

1. Table of Acceptance Criteria and Reported Device Performance

The document does not explicitly present a table of acceptance criteria with corresponding performance metrics in a single, consolidated format. However, it mentions various types of testing and states that "Testing was conducted according to written protocols with acceptance criteria that were based on standards." The "Discussion" section also states, "Minor differences in the optical tracking systems and use of patient specific instrumentation are addressed by performance testing." This implies that the performance testing confirmed the device met established criteria for those specific aspects.

Based on the information provided, we can infer some of the areas where acceptance criteria would have been applied:

2. Sample Size for Test Set and Data Provenance

The document explicitly mentions a "cadaver study" as part of the performance data.

• Sample Size for the Test Set: Not explicitly stated in the provided text.
• Data Provenance: The cadaver study would involve human remains, but the exact country of origin or whether it was retrospective/prospective in the context of data collection for this specific study is not detailed. However, cadaver studies are inherently prospective for the purpose of testing the device.

3. Number of Experts and Qualifications for Ground Truth

The document does not explicitly mention the number of experts, their qualifications, or their role in establishing ground truth specifically for the reported studies (e.g., cadaver study). For a device like this, ground truth would likely be established through precise anatomical measurements or post-hoc imaging.

4. Adjudication Method for the Test Set

The document does not detail any adjudication method (e.g., 2+1, 3+1) for the test set. Adjudication methods are typically associated with human interpretation of medical images or data, which is not the primary focus for establishing the technical accuracy of a navigation system in a cadaver study.

5. Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study

No mention of an MRMC comparative effectiveness study, or the effect size of human readers improving with AI vs. without AI assistance, is made. This device is a surgical navigation platform, not an AI-assisted diagnostic tool that heavily relies on human reader interpretation of images. The smart glasses are described as an auxiliary display, not an AI-driven interpretive aid for human readers.

6. Standalone (Algorithm Only Without Human-in-the-Loop Performance) Study

The performance testing, particularly the "performance testing to evaluate mechanical and optical properties" and elements of the "cadaver study," would inherently involve evaluating the standalone performance of the algorithm and system components. The software validates the navigation software's ability to display information to the surgeon accurately. The cadaver study would assess how accurately the system guides the surgeon, implying that the system's output (measurements, guidance) is evaluated independently of a human's ultimate judgment during the assessment phase of the study, though a human surgeon performs the actions based on the guidance.

7. Type of Ground Truth Used

For the specific performance testing of this surgical navigation platform, especially in the cadaver study, the ground truth would likely be established using precise direct physical measurements (e.g., with highly accurate measurement tools or CMMs) or potentially post-operative imaging with precise measurements of the cadaver bones to verify the accuracy of resections and implant positioning as guided by the system. The "pre-operative CT based planning" is used by the device, and the device ensures "reference to a patient's rigid anatomical structures... that can be identified relative to pre-operative CT based planning." Therefore, the ground truth would be tied back to the anatomical accuracy relative to these plans.

8. Sample Size for the Training Set

The document does not provide information about a specific "training set" sample size. This type of device relies on established biomechanical principles and image processing of CT scans for its planning and navigation, rather than a deep learning model that requires a discrete training set in the conventional sense. The software is validated, but not "trained" in an iterative machine learning fashion on a large dataset of patient outcomes.

9. How the Ground Truth for the Training Set Was Established

As no specific training set for a machine learning model is mentioned, the method for establishing its ground truth is not applicable or detailed in this summary. The system's foundational data (e.g., anatomical models, instrument specifications) are established through engineering design, scientific principles, and preclinical testing.

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