Search Filters

Search Results

Found 1 results

510(k) Data Aggregation

    K Number
    K140537
    Device Name
    TENURE4G
    Date Cleared
    2014-08-20

    (169 days)

    Product Code
    Regulation Number
    872.3200
    Panel
    Dental
    Reference & Predicate Devices
    Why did this record match?
    Reference Devices :

    K910860,K872510

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

    tenure@4G is recommended for the following types of applications:

    1. All routine direct and indirect resin composite bonding

    2. Porcelain, ceramic veneers, amalgams, precious and semi-precious metals bonding

    3. Indirect gold, porcelain and ceramic inlays and onlays bonding

    4. Desensitization of root or dentin prior to impressions or temporaries

    5. Preparation desensitization of crown prior to impressions or temporaries

    Device Description

    tenure * 4G is DenMat's next generation of its popular Tenure MPB System with greater bond strength and sensitivity control. It is a 40 generation multi-purpose, self-cure adhesive system for bonding any resin restorative to all intraoral surfaces. They are polymerizable dental monomer resins that are chemically-cured with the reaction initiated when the two parts are mixed together. These polymers form strong leak and stain resistant bonds between the dental surface and restorations placed over them.

    AI/ML Overview

    This document is a 510(k) premarket notification for the "tenure®4G" resin tooth bonding agent. It evaluates the device's substantial equivalence to predicate devices (ALL-BOND 2 and Tenure MPB) based on intended use, indications for use, chemical components, safety, and technological characteristics.

    Here's an analysis of the provided information concerning acceptance criteria, device performance, and the study details:

    1. Table of Acceptance Criteria and Reported Device Performance

    The acceptance criteria for this device are implicitly tied to demonstrating substantial equivalence to the predicate devices, particularly in terms of shear bond strength. While explicit numerical acceptance criteria (e.g., "must achieve at least X psi") are not stated, the study aims to show that the tenure®4G performs "as good as or even better than the predicate devices."

    Material BondedAcceptance Criteria (Implicit)Reported tenure®4G Performance (Mean ± StDev)ALL-BOND 2 Performance (Mean ± StDev)Tenure MPB Performance (Mean ± StDev)
    PorcelainShear bond strength comparable to or better than predicate devices (ALL-BOND 2 and Tenure MPB).1907.14 ± 294.42 psi (13.149 ± 2.030 MPa)1627.21 ± 656.00 psi (11.219 ± 4.523 MPa)2041.29 ± 177.37 psi (14.074 ± 1.223 MPa)
    EnamelShear bond strength comparable to or better than predicate devices (ALL-BOND 2 and Tenure MPB).1851.84 ± 512.14 psi (12.768 ± 3.531 MPa)1147.21 ± 549.74 psi (7.910 ± 3.790 MPa)1485.50 ± 659.45 psi (10.242 ± 4.547 MPa)
    DentinShear bond strength comparable to or better than predicate devices (ALL-BOND 2 and Tenure MPB).3776.07 ± 478.64 psi (26.035 ± 3.300 MPa)2830.62 ± 217.68 psi (19.516 ± 1.501 MPa)3027.60 ± 410.47 psi (20.875 ± 2.830 MPa)

    Conclusion from Table: For Porcelain and Enamel, tenure®4G demonstrates higher mean bond strength than ALL-BOND 2, and for Enamel and Dentin, it shows higher mean bond strength than Tenure MPB. For Porcelain, its mean bond strength is slightly lower than Tenure MPB but falls within the standard deviation. Overall, the results support the claim that tenure®4G performs "as good as or even better than" the predicate devices.

    2. Sample Size Used for the Test Set and the Data Provenance

    The document mentions "Results of shear bond testing indicate that tenure®4G was as effective and performs as good as or even better than the predicate devices." However, it does not explicitly state the sample size used for the shear bond testing. The data provenance is not specified beyond being "tested in the lab using R&D test protocols." It is likely retrospective data collected for this submission. The country of origin of the data is not mentioned but can be inferred to be related to the submitter, DenMat Holdings, LLC, which is based in Lompoc, California, U.S.A.

    3. Number of Experts Used to Establish the Ground Truth for the Test Set and the Qualifications of Those Experts

    This type of study (comparative performance of a dental bonding agent) does not involve experts establishing ground truth in the same way clinical diagnostic studies do. The "ground truth" here is the objective measurement of shear bond strength, which is a physical property determined through laboratory testing methods, not expert consensus or interpretation. Therefore, this information is not applicable.

    4. Adjudication Method for the Test Set

    As the "test set" involves objective laboratory measurements of shear bond strength rather than subjective assessments requiring expert adjudication, this information is not applicable.

    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 document describes the performance of a dental bonding agent, an in-vitro material, not a diagnostic imaging device or an AI application. Therefore, an MRMC comparative effectiveness study involving human readers and AI assistance is not applicable to this submission.

    6. If a Standalone (i.e., algorithm only without human-in-the-loop performance) Was Done

    This document pertains to a dental bonding agent and not a software algorithm. Therefore, "standalone (algorithm only without human-in-the-loop performance)" is not applicable.

    7. The Type of Ground Truth Used

    The "ground truth" for this performance study is objective laboratory measurements of shear bond strength. This is determined through physical testing protocols in a lab setting, not through expert consensus, pathology, or outcomes data in a clinical sense.

    8. The Sample Size for the Training Set

    This submission is for a medical device (dental bonding agent), not a machine learning algorithm. Therefore, there is no concept of a "training set" in this context. The chemical formulation and manufacturing processes are developed through research and development, and the performance is validated through testing, not by training a model on data.

    9. How the Ground Truth for the Training Set Was Established

    As there is no "training set" for this device, this question is not applicable.

    Ask a Question

    Ask a specific question about this device

    Page 1 of 1