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510(k) Data Aggregation

    K Number
    K142388
    Date Cleared
    2014-12-05

    (100 days)

    Product Code
    Regulation Number
    888.3560
    Reference & Predicate Devices
    Why did this record match?
    Device Name :

    Neo Total Knee System

    AI/MLSaMDIVD (In Vitro Diagnostic)TherapeuticDiagnosticis PCCP AuthorizedThirdpartyExpeditedreview
    Intended Use

    The NEO Total Knee System components are indicated for use in skeletally mature individuals, with severe knee pain and disability, undergoing surgery for total knee replacement due to:

    • . Osteoarthritis, rheumatoid arthritis, post-traumatic arthritis, moderate deformities and femoral condyle osteonecrosis.
    • . Failed osteotomies, failed partial knee replacement, or failed total knee replacement whose age, weight and activity level are compatible with an adequate long-term result.
    • Post-traumatic loss of joint configuration, particularly when there is . patellofemoral erosion, dysfunction or prior patellectomy.
    • Moderate valgus, varus, or flexion deformities. .

    The cruciate retaining (CR) femur with CR tibial insert is for use when the posterior cruciate ligament (PCL) is intact. The CR femur with UC tibial inserts is for use when the PCL is sacrificed. The posteriorly stabilized (PS) femur with PS tibial insert is for use when the PCL is sacrificed.

    The NEO Total Knee System components are indicated for use only with cement and are single use devices.

    Device Description

    The NEO Total Knee System includes:

    • Cruciate retaining (CR) Femoral Components and Posteriorly stabilized (PS) Femoral . Components in right and left configurations in sizes 1 to 10, manufactured from Cast CoCr.
    • Tibial Trays manufactured from titanium alloy in sizes 1 – 10.
    • . Tibial Inserts in cruciate retaining (CR), ultracongruent (UC), and posteriorly stabilized (PS) designs, manufactured from standard ultrahigh molecular weight polyethylene, in sizes A to E and in thicknesses 6 to 21 mm (total thickness with tibial tray is 9 to 24 mm).
    • Patellar Components in diameters of 26 to 41 mm and in thicknesses of 8, 9 or 10 mm, manufactured from standard ultrahigh molecular weight polyethylene.

    The NEO Total Knee System is designed with the potential to have an active clinical flexion of 150°.

    AI/ML Overview

    This document is a 510(k) summary for the NEO Total Knee System, a medical device. It focuses on demonstrating substantial equivalence to previously cleared devices rather than presenting a study proving the device meets specific acceptance criteria in the way an AI/software device would. Therefore, most of the requested information regarding acceptance criteria, sample sizes for test sets, ground truth establishment, expert adjudication, and MRMC studies is not applicable to this type of device submission.

    Here's an attempt to extract the relevant information where applicable, and indicate when the requested information is not provided or not relevant for this submission type:

    1. A table of acceptance criteria and the reported device performance

    This document does not present explicit "acceptance criteria" in the format of pass/fail thresholds for performance metrics. Instead, it relies on demonstrating that the device has the "same design features" and "same indications for use" as its predicate devices, and that performance testing confirmed its structural integrity and functional characteristics are comparable or acceptable within the context of a knee replacement system.

    The "Performance Testing" section lists the types of tests conducted:

    • Tibial tray fatigue strength
    • Insert locking mechanism strength
    • Tibial post strength (for PS design)
    • Femorotibial range of motion
    • Femorotibial range of constraint
    • Patellofemoral range of constraint
    • Femorotibial contact areas/contact stress
    • Patellofemoral contact area and contact stress

    No specific numerical acceptance criteria or reported performance values are provided in this summary. The implicit acceptance criterion is likely that the device performs comparably to the predicate devices and meets relevant industry standards for mechanical performance of total knee systems, which are not detailed here.

    2. Sample sized used for the test set and the data provenance (e.g. country of origin of the data, retrospective or prospective)

    This information is not provided in the summary. The tests mentioned are mechanical performance tests, not clinical studies involving patient data.

    3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts (e.g. radiologist with 10 years of experience)

    This is not applicable. The "ground truth" for mechanical testing is based on engineering principles, material properties, and established test methodologies, not expert consensus on medical images or clinical outcomes.

    4. Adjudication method (e.g. 2+1, 3+1, none) for the test set

    This is not applicable to mechanical performance testing.

    5. If a multi reader multi case (MRMC) comparative effectiveness study was done, If so, what was the effect size of how much human readers improve with AI vs without AI assistance

    This is not applicable. This is a medical device (knee implant), not an AI/software device requiring an MRMC study.

    6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done

    This is not applicable. This is a medical device (knee implant), not an AI/software device.

    7. The type of ground truth used (expert consensus, pathology, outcomes data, etc)

    For mechanical performance tests, the "ground truth" refers to the physical properties and performance limits of the materials and design, evaluated against engineering standards and established biomechanical principles. It is not an "expert consensus" or "pathology" in the typical sense of evaluating diagnostic accuracy.

    8. The sample size for the training set

    This is not applicable. This is a mechanical device, not a machine learning model that requires a training set.

    9. How the ground truth for the training set was established

    This is not applicable for the same reason as above.

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