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510(k) Data Aggregation

    K Number
    K170950
    Device Name
    Well-Root ST
    Manufacturer
    Date Cleared
    2017-12-20

    (264 days)

    Product Code
    Regulation Number
    872.3820
    Panel
    Dental
    Reference & Predicate Devices
    Why did this record match?
    Device Name :

    Well-Root ST

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

    Permanent sealing of root canal

    Device Description

    Well-Root™ ST is a convenient premixed ready-to use composition which requires the presence of water to set and harden. The device is contained in a plastic syringe and the system includes a plunger, disposable tips, and a holder.

    AI/ML Overview

    The provided text describes the regulatory clearance of a root canal filling resin, Well-Root™ ST, and its substantial equivalence to predicate devices. It does not present a study with acceptance criteria and reported device performance in the context of diagnostic accuracy, clinical outcomes, or human-in-the-loop performance, as implied by the request. Instead, the "performance data" section refers to bench testing against ISO standards and biocompatibility tests. These are typically used to demonstrate the physical, chemical, and biological safety of a material, not to evaluate the diagnostic or clinical efficacy of an AI-powered medical device.

    Therefore, many of the requested items, particularly those related to diagnostic accuracy, a test set, ground truth, experts, and comparative effectiveness studies, cannot be answered from the provided text.

    Here's an attempt to answer the questions based only on the information available in the provided text, highlighting where the information is not present or not applicable to the context of AI device studies:


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

    The document lists performance standards it conformed to (ISO 6876 and ISO 10993 series), and mentions that "the test result of the subject device satisfies the requirement of the ISO 6876" and "the results of the bench and the biocompatibility tests performed demonstrates that any of these differences do not raise a new question as to safety and effectiveness." However, specific numerical acceptance criteria and reported performance values for these tests are not detailed in the provided text.

    The document mentions compliance with the following ISO standards and specific tests within them:

    Acceptance Criteria (Standard / Test)Reported Device Performance
    ISO 6876: FlowSatisfies requirements
    ISO 6876: Setting TimeSatisfies requirements
    ISO 6876: Film ThicknessSatisfies requirements
    ISO 6876: Solubility and disintegrationSatisfies requirements
    ISO 6876: Radio-opacitySatisfies requirements
    ISO 6876: Working timeSatisfies requirements
    ISO 10993-5 (Cytotoxicity)Compliant
    ISO 10993-10 (Sensitivity-LLNA, GPMT)Compliant
    ISO 10993-11 (Acute systemic Toxicity)Compliant
    ISO 10993-3 (Genotoxicity: Bacterial reverse mutation (Ames), In vitro mammalian chromosomal aberration)Compliant
    ISO 10993-6 (Implantation)Compliant
    Shelf Life: AppearanceCompliant
    Shelf Life: ISO 6876 tests (Flow, Setting Time, Film Thickness)Compliant

    Note: The text explicitly states, "the test result of the subject device satisfies the requirement of the ISO 6876 and does not raise an issue of safety and/or performance." It also mentions for shelf life "Appearance, ISO 6876 tests (Flow, Setting Time, Film Thickness)" were conducted, implying compliance.

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

    Not applicable/Not provided. This document describes physical, chemical, and biocompatibility testing of a root canal filling resin, not an AI-powered diagnostic device that would typically have a "test set" of data (e.g., images, patient records). The testing methods for ISO standards usually involve a defined number of samples for each test (e.g., N=3 or N=5 for flow, setting time, etc.), but these specific numbers are not given 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/Not provided. Ground truth, in the context of diagnostic AI, refers to the confirmed correct diagnosis or outcome. For a physical device like a root canal sealer, "ground truth" would relate to the validated methods of the ISO standards themselves, not expert judgment on cases.

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

    Not applicable/Not provided. Adjudication methods are relevant for resolving discrepancies in expert interpretations (e.g., in reading medical images) for establishing ground truth, which is not the type of study described here.

    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. This is not a study involving human readers or AI assistance. It is a submission for a physical medical device.

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

    No. This is not an algorithm or AI device.

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

    For the ISO and biocompatibility tests: The "ground truth" is established by the specified methodologies and criteria outlined within the respective ISO standards (e.g., ISO 6876 for physical properties of root canal filling materials, ISO 10993 series for biocompatibility). These standards define the acceptable range or characteristics for the device's performance.

    8. The sample size for the training set

    Not applicable/Not provided. As this is not an AI device, there is no "training set."

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

    Not applicable/Not provided. As this is not an AI device, there is no "training set" or corresponding ground truth establishment in that context.

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