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510(k) Data Aggregation

    K Number
    K133716
    Device Name
    TRC-PASTE
    Manufacturer
    Date Cleared
    2014-04-09

    (125 days)

    Product Code
    Regulation Number
    872.3820
    Panel
    Dental
    Reference & Predicate Devices
    Predicate For
    N/A
    AI/MLSaMDIVD (In Vitro Diagnostic)TherapeuticDiagnosticis PCCP AuthorizedThirdpartyExpeditedreview
    Intended Use

    TRC-Paste is a biocompatible temporary root canal sealer for use in the treatment of root canals, or following pulpectomy, or for apexegenesis or apexification, and for the tip filling of prepared, treated root canals at the time of final filling with gutta- percha.

    Device Description

    TRC-Paste is an immediately available pre-mixed root canal filling material based on Calcium hydroxide and Polypropylene Glycol 2000. This pre-mixed temporary filling material maintains a constant flow, which makes it easy to inject into the canal. Depending on apicoectomy or infected root canal therapies, it can be used as a temporary root canal filling material. The device is contained in a plastic syringe and the system includes a plunger, disposable tips, a rubber, a protective cap, an indo stop and a holder for direction control of the tip.

    AI/ML Overview

    The provided text describes a 510(k) summary for the device TRC-Paste, a temporary root canal filling material. It outlines non-clinical performance data and states that the device is substantially equivalent to a predicate device. However, the document does not contain information about the acceptance criteria or a study that proves the device meets specific performance criteria in the way typically associated with AI/ML-driven medical devices.

    Instead, the performance data presented is for a traditional medical device (a paste) and focuses on compliance with established ISO and ASTM standards for material properties and biocompatibility.

    Here's an analysis of the provided information, framed to address your request, with a clear indication of what is missing based on the typical requirements for AI/ML device studies:

    1. Table of acceptance criteria and the reported device performance

    Acceptance Criteria (Based on Referenced Standards)Reported Device Performance
    ISO 6876:All test results met the preset test criteria.
    - RadiopacityMet criteria.
    - FlowabilityMet criteria.
    ISO 10993-5: CytotoxicityAll test results met the preset test criteria.
    - Biocompatibility (Cytotoxicity)Met criteria.
    ISO 10993-6: ImplantationAll test results met the preset test criteria.
    - Biocompatibility (Implantation)Met criteria.
    ISO 10993-11: Short-term systemic toxicity (Oral)All test results met the preset test criteria.
    - Biocompatibility (Systemic Toxicity)Met criteria.
    ASTM F1980-07: Shelf life testAll test results met the preset test criteria.
    - Shelf lifeMet criteria.
    Other Bench Testing:All test results met the preset test criteria.
    - AppearanceMet criteria.
    - VolumeMet criteria.
    - PackagingMet criteria.

    Study Proving Device Meets Acceptance Criteria:

    The study proving the device meets the acceptance criteria is a series of non-clinical bench tests performed by KM Corporation. The 510(k) summary states, "All the test results met the preset test criteria." This implies that for each listed standard (ISO 6876, ISO 10993-5, ISO 10993-6, ISO 10993-11, ASTM F1980-07) and other bench tests, the TRC-Paste exhibited properties within the acceptable limits defined by those standards.


    Regarding the AI/ML specific information requested, the provided document does NOT contain this information because the device is a material, not an AI/ML algorithm. Therefore, the following points are largely not applicable or missing from this specific submission:

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

    • Not Applicable / Missing: This information is not relevant for a physical material product. The "test set" here refers to samples of the TRC-Paste material, implicitly tested in a lab setting. No specific sample sizes for these bench tests are provided in this summary.

    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)

    • Not Applicable / Missing: This is not relevant. Ground truth for material properties is established by objective measurements against recognized standards, not by expert consensus in the diagnostic sense.

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

    • Not Applicable / Missing: This refers to expert adjudication for clinical or imaging data, which is not part of this device's evaluation.

    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

    • Not Applicable / Missing: This is for AI/ML diagnostic aids, not a root canal filling material.

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

    • Not Applicable / Missing: This is for AI/ML algorithms.

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

    • Type of Ground Truth (for a material): The "ground truth" for this device's performance is objective measurement against the limits and specifications defined by the referenced international standards (ISO, ASTM) for properties like radiopacity, flowability, cytotoxicity, implantation response, systemic toxicity, and shelf life.

    8. The sample size for the training set

    • Not Applicable / Missing: This is for AI/ML models.

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

    • Not Applicable / Missing: This is for AI/ML models.

    In summary, the provided document details the non-clinical performance data for a temporary root canal filling material, showing its compliance with various ISO and ASTM standards to demonstrate substantial equivalence. It does not involve AI/ML technology, so many of the requested data points (related to algorithms, readers, ground truth establishment for diagnostic tasks, etc.) are not present in this type of submission.

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