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510(k) Data Aggregation

    K Number
    K992895
    Device Name
    IMPREGUM F
    Manufacturer
    Date Cleared
    1999-09-08

    (12 days)

    Product Code
    Regulation Number
    872.3660
    Panel
    Dental
    Reference & Predicate Devices
    N/A
    Predicate For
    N/A
    AI/MLSaMDIVD (In Vitro Diagnostic)TherapeuticDiagnosticis PCCP AuthorizedThirdpartyExpeditedreview
    Intended Use

    Dental impression material for: Impressions for inlay, onlay, crown, and bridge restorations Functional impressions Fixation impressions Implant impressions

    Device Description

    The modified IMPREGUM® F is classified as an impression material (21 C.F.R. § 872.3660) because it is a device intended to reproduce the structure of a patient's teeth. ESPE is submitting this Special 510(k) for modifications of its polyether based impression material IMPREGUM® F. In particular one ingredient will be exchanged by a chemical compound with comparable character and another one will be added. The modified IMPREGUM® F has the same fundamental scientific technology and the same intended use, therefore, we believe these modifications are eligible for the Special 510(k) process.

    AI/ML Overview

    This document is a 510(k) summary for a modified dental impression material, IMPREGUM® F. It does not contain information about acceptance criteria or a study proving that a device meets those criteria in the way a medical AI/software device would.

    The document describes a "Special 510(k)" submission for modifications to an existing polyether-based impression material. In this context, "acceptance criteria" and "study" refer to the comparison of the modified device's chemical composition, physical, and mechanical properties to the predicate device to demonstrate substantial equivalence, rather than performance metrics for an AI or software device.

    Therefore, most of the requested information regarding AI/software performance criteria (e.g., sample size for test sets, data provenance, expert ground truth, adjudication methods, MRMC studies, standalone performance, training set details) is not applicable to this document.

    Here's an attempt to answer the relevant questions based on the provided text, while acknowledging its limitations for an AI software context:

    1. Table of Acceptance Criteria and Reported Device Performance

    This document does not provide a table with quantitative acceptance criteria for performance metrics (like sensitivity, specificity, etc.) nor reported performance in a typical clinical study outcome. Instead, the acceptance criteria for this Special 510(k) are based on demonstrating "substantial equivalence" to the predicate device by showing that the modified device has comparable characteristics, fundamental scientific technology, and the same intended use.

    Acceptance Criteria (Implied for Substantial Equivalence to Predicate)Reported Device Performance (as stated in comparison)
    Same intended useIMPREGUM® F (modified) has the same intended use.
    Same operating principleIMPREGUM® F (modified) is used by the same operating principle.
    Same basic chemical designIMPREGUM® F (modified) incorporates the same basic chemical design (with one ingredient exchanged for a comparable one, and another added).
    Same shelf lifeIMPREGUM® F (modified) has the same shelf life.
    Same manufacturing and packaging materials/processesIMPREGUM® F (modified) is manufactured and packaged using the same materials and processes.

    The study described is the comparison of the modified IMPREGUM® F with the unmodified IMPREGUM® F regarding:

    • Chemical composition
    • Physical properties
    • Mechanical properties
    • Indications for use

    The text states that these comparisons led the submitter to believe the modifications are "eligible for the Special 510(k) process" and that the modified device is "substantially equivalent to the predicate device."


    2. Sample size 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 document. The document refers to "chemical composition, the physical and mechanical properties" being compared, but no details on sample sizes or data provenance (e.g., how many batches were tested, where the testing was done) are given. This is typical for a Special 510(k) for material modifications, where the focus is on comparative testing against the predicate rather than a clinical trial.


    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 to this type of device and submission. "Ground truth" in the context of material properties is established through standardized laboratory testing methods, not expert consensus in the way clinical diagnostic AI works.


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

    This is not applicable to this type of device and submission. Adjudication methods are typically used for establishing ground truth in clinical imaging or diagnostic studies involving human interpretation.


    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 document describes a dental impression material, not an AI or diagnostic software.


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

    This is not applicable. This document describes a dental impression material, not an AI or software algorithm.


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

    For the "study" described (comparison of material properties), the "ground truth" would be the objective measurements and specifications of the predicate device, against which the modified device's properties were compared using scientific and engineering test methods.


    8. The sample size for the training set

    This is not applicable. There is no "training set" in the AI/machine learning sense for this device.


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

    This is not applicable. There is no "training set" for this device.

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