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510(k) Data Aggregation

    K Number
    K213570
    Date Cleared
    2022-01-07

    (58 days)

    Product Code
    Regulation Number
    872.6660
    Panel
    Dental
    Reference & Predicate Devices
    Predicate For
    N/A
    Why did this record match?
    Reference Devices :

    K210884

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

    Dental Zirconia Ceramic are used for dental restorations using different CAD/CAM or manual milling machines. All blanks are processed thought dental laboratories or by dental professionals.

    Device Description

    The subject device, Dental Zirconia Ceramic, are derived from dental porcelain powder that has been processed into their final net shapes. These blanks are then being further fabricated (using hot press or CAD/CAM technologies) into all ceramic restorations such as veneers, inlay/ onlay, partial crowns,anterior crowns, posterior crowns. The ceramics material is composed of ZrO2, Y2O3 Al2O3 and other oxides. It also contains inorganic pigments to provide different shades on the product surface, totally 16 colors(A1,A2,A3,A3.5,A4,B1,B2,B3,B4,C1,C2,C3,C4,D2,D3,and D4), with the addition of very small amount ( < 0.5 % ) of inorganic pigments: Fe2O3 +Er2O3+C0304.

    AI/ML Overview

    This document is a 510(k) Premarket Notification from the FDA regarding a dental device. It does not describe a study that uses AI or machine learning technology to interpret medical images or other diagnostic data. Instead, it concerns a physical dental material (Zirconia Ceramic) and its comparison to a predicate device based on physical and chemical properties.

    Therefore, many of the requested categories related to AI/ML device studies (such as sample size for test set, data provenance, number of experts establish ground truth, adjudication method, MRMC study, standalone performance, training set details) are not applicable to this document.

    However, I can extract the acceptance criteria and reported device performance for the non-clinical tests that were performed.


    1. Table of Acceptance Criteria and Reported Device Performance

    ItemAcceptance CriteriaReported Device Performance
    UniformityUniformly dispersed inorganic pigment(s) to produce color.Product uniformity is qualified. Pass
    Freedom from extraneous materialsFree from extraneous materials.No extraneous materials. Pass
    RadioactivityActivity concentration of 238U not more than 1.0 Bq/g.There was no activity detected. Pass
    Flexural strengthNot less than 900 MPa.Average 943.1 MPa. Pass
    Linear thermal expansion coefficient(10.5 ± 0.5) × 10^-6 K^-1.Average 10.47 × 10^-6. Pass
    Chemical solubilityNot more than 2000 µg/cm^2. (Note: Comparison table states <100 µg/cm^2)Average 13.5. Pass
    Product composition (%)ZrO2 94%-95%; Y2O3 4.5%-5.5%; Al2O3 <0.5%; Other oxide <0.5%.ZrO2: 94.56%; Y2O3: 5.34%; Al2O3: 0.005%; Other oxide: 0.095%

    Since this is a physical medical device submission (Dental Zirconia Ceramic) and not an AI/ML diagnostic or prognostic device, the following points are not applicable:

    1. Sample size used for the test set and the data provenance: Not applicable (no "test set" in the context of AI/ML). Tests were on physical material samples.
    2. Number of experts used to establish the ground truth for the test set and the qualifications of those experts: Not applicable (no "ground truth" established by experts in an AI/ML context).
    3. Adjudication method (e.g. 2+1, 3+1, none) for the test set: Not applicable.
    4. 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: Not applicable.
    5. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done: Not applicable.
    6. The type of ground truth used (expert consensus, pathology, outcomes data, etc): Not applicable in the AI/ML sense. The "ground truth" for the physical tests are the established ISO standards and observed physical/chemical properties.
    7. The sample size for the training set: Not applicable (no "training set" in the context of AI/ML).
    8. How the ground truth for the training set was established: Not applicable.
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