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510(k) Data Aggregation

    K Number
    K211891
    Date Cleared
    2022-07-22

    (396 days)

    Product Code
    Regulation Number
    888.3353
    Reference & Predicate Devices
    Why did this record match?
    Device Name :

    DM Converter - TiN coated

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

    The Medacta DM Converter is designed to be used in combination with the Mpact and Versafitcup CC Trio family cementless cups in total hip arthroplasty in primary or revision surgery.

    Total hip Arthroplasty is indicated in the following cases:

    · Severely painful and/or disabled joint as a result of arthritis, rheumatoid polyarthritis or congenital hip dysplasia

    • Avascular necrosis of the femoral head

    · Acute traumatic fracture of the femoral head or neck

    · Failure of previous hip surgery: joint reconstruction, internal fixation, arthroplasty, hip resurfacing replacement or total hip arthroplasty

    Device Description

    The DM Converter - TiN coated is a component of a total hip joint prosthesis that is used to replace the acetabulum in both primary or revision surgery. It is a highly polished metal liner made of High Nitrogen Stainless Steel according to ISO 5832-9 with a TiN coating on the external surface.

    The DM Converter - TiN coated is inserted into the acetabular shell and can be coupled with a mobile liner: Medacta Double Mobility UHMWPE (ISO 5834-2 Type 1) liners (K083116 and K131458) or HighCross (highly crosslinked UHMWPE) liners (K092265 and K131458).

    The DM Converter – TiN coated is available in 6 six sizes with a nomenclature that identifies the cup liner size (first letter) and the double mobility liner size (final three letters): D/DMB, E/DME, G/DMF, J/DMH and K/DML.

    AI/ML Overview

    The provided text is a 510(k) summary for the Medacta DM Converter - TiN coated, a component of a total hip joint prosthesis. It primarily focuses on demonstrating substantial equivalence to a predicate device through non-clinical testing.

    Here's an analysis of the acceptance criteria and study aspects based on the provided document:

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

    The document does not explicitly present a table of acceptance criteria with numerical targets. Instead, it lists the types of performance tests conducted and implies that the device satisfied the requirements of these standard tests. The "reported device performance" is not quantified in the document, but rather stated that "design validation and performance testing were conducted to written protocols" and the results support substantial equivalence.

    Implied Acceptance Criteria (based on tests performed):

    Acceptance Criteria CategoryReported Device Performance (Implied)
    Mechanical StabilityPassed ASTM F1820-13 for disassembly forces of modular acetabular devices.
    Corrosion ResistancePassed Fretting corrosion test.
    Range of MotionSatisfied Jumping distance and ROM evaluation rationale.
    Wear PerformancePassed ISO 14242-1 for wear of total hip-joint prostheses.
    Abrasion ResistancePassed ASTM 1978-18 for abrasion resistance of metallic thermal spray coatings.
    Coating AdhesionPassed ISO 20502 for adhesion of ceramic coatings by scratch testing.
    CompatibilitySatisfied Double Mobility Converter Implants Compatibility Extension Rationale.
    BiocompatibilityAssessment conducted (results not detailed, but implied acceptable).
    PyrogenicityPassed Bacterial endotoxin test (LAL) according to European Pharmacopoeia §2.6.14 (equivalent to USP ), and Pyrogen test according to USP . (Note: Not labeled as non-pyrogenic or pyrogen-free).
    Shelf-LifeEvaluation conducted (results not detailed, but implied acceptable).

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

    The document does not specify the sample sizes used for any of the performance tests.
    The data provenance (country of origin, retrospective/prospective) is not mentioned. All studies appear to be non-clinical (laboratory) studies rather than field 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 information is not applicable as the studies are entirely non-clinical performance and design validation tests for a medical device component. There is no "ground truth" in the clinical sense established by human experts for these types of tests.

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

    This information is not applicable. Adjudication methods are relevant for studies involving human interpretation or clinical outcomes, which are not present in this non-clinical submission.

    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

    No MRMC comparative effectiveness study was done. This is a submission for a mechanical implant component, not an AI-assisted diagnostic or treatment device. The document explicitly states: "No clinical studies were conducted."

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

    This question is not applicable as the device is a physical medical implant (a component of a total hip joint prosthesis), not an algorithm or AI system.

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

    For the non-clinical performance tests, the "ground truth" is typically defined by the standards themselves (e.g., ASTM, ISO specifications for material strength, wear rates, and stability). The device either meets the specified performance parameters outlined in these standards or it does not. There is no expert consensus, pathology, or outcomes data involved in establishing "ground truth" for these engineering tests.

    8. The sample size for the training set

    This is not applicable. There is no "training set" as this is a physical medical device and not a machine learning model.

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

    This is not applicable for the reasons stated above.

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