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510(k) Data Aggregation

    K Number
    K181689
    Device Name
    Nexcomp
    Date Cleared
    2018-11-15

    (142 days)

    Product Code
    Regulation Number
    872.3690
    Panel
    Dental
    Reference & Predicate Devices
    Predicate For
    N/A
    AI/MLSaMDIVD (In Vitro Diagnostic)TherapeuticDiagnosticis PCCP AuthorizedThirdpartyExpeditedreview
    Intended Use

    Nexcomp is intended to restore carious lesions or structural defects in teeth. It is indicated for Class I, III, IV, and V restorations, core-buildup to replace missing tooth structure, for splinting and for diastema closure, direct veneers, composite and porcelain repairs.

    Device Description

    Nexcomp is a light-cured, esthetic, resin-based dental restorative designed for direct placement in both anterior and posterior restorations. The material is radiopaque and indicated for all types of cavity preparations. The hybrid blend has an ultra-fine filler and 40 nm silica particles. Nexcomp will be marketed in 19 shades which corresponded with the Vita Shade Guide.

    AI/ML Overview

    The provided text describes the 510(k) premarket notification for a dental restorative material called Nexcomp. It focuses on demonstrating substantial equivalence to a predicate device rather than presenting a study proving that an AI/device meets specific acceptance criteria for diagnostic performance.

    Therefore, I cannot extract the detailed information requested regarding AI/device performance, reader studies, ground truth establishment, or sample sizes for training/test sets as these concepts are not applicable to the provided document. The document concerns a physical dental material, not an AI or diagnostic device.

    However, I can extract the acceptance criteria and performance data for the physical properties of the Nexcomp dental material and present it in a table, as well as information about the testing performed.

    Acceptance Criteria and Device Performance (for Physical Properties of Dental Material)

    The document primarily focuses on demonstrating that the new Nexcomp device has similar physical properties to its predicate device, and that these properties meet relevant ISO standards for dental materials.

    1. Table of Acceptance Criteria and Reported Device Performance

    PropertyAcceptance Criteria (ISO Standards/Predicate Similarity)Reported Device Performance (Subject Device)Reported Predicate Device Performance
    Material Properties
    Compressive strengthShould be more than 5MPa.Average 232.76 MPaAverage 288.68 MPa
    Flexural strength> 80 MPaAverage 87 MPa91.82 MPa
    Depth of cure> 1.0 mm2.88 mm4.96 mm
    Surface hardness (Vickers hardness)Based on ISO 6507-1:2005 (no specific numerical criterion stated in table, but performance is compared)Average 56 KHNAverage 39.36 KHN
    Radio-opacity> 1mmMore than 1mmMore than 1mm
    Water sorption< 40 µg/mm³2.97 µg/mm³13.78 µg/mm³
    Solubility< 7.5 µg/mm³0.0 µg/mm³0.23 µg/mm³
    Sensitivity of ambient lightPhysical homogeneityPhysical homogeneityPhysical homogeneity
    Shade and color stabilityConsistencyConsistencyConsistency
    Shelf Life3 years (equivalent to predicate)3 years3 years
    Curing/Working Properties
    Intensity for curingNot specified as a criterion to meet, but stated1000-1200 mV/cm²- (Not reported for predicate)
    Wavelength for curingNot specified as a criterion to meet, but stated420-480nm- (Not reported for predicate)
    Curing timeNot specified as a criterion to meet, but stated20sec- (Not reported for predicate)
    Working timeApplies to self-cured resin. Light-cured for this device.This device is a light curing type product.- (Not reported for predicate)
    Setting timeApplies to self-cured resin. Light-cured for this device.This device is a light curing type product.- (Not reported for predicate)
    Other Filler PropertiesNot specified as a direct criterion, but statedBarium glass : 0.78 µm, Silica :16nm- (Not reported for predicate)
    Release profileNot specified as a criterion, but statedThis device did not contain fluoride or nitrate ions.- (Not reported for predicate)

    Note: The document states that differences in depth of cure, surface hardness, and water sorption between the subject and predicate devices are acceptable because "the test results are within the range of the criteria of ISO standards such as ISO 4049 and ISO 6507 this difference does not affect the substantial equivalence."


    Regarding the other points requested (which are generally for AI/Diagnostic devices):

    2. Sample sizes used for the test set and the data provenance: Not applicable. This is not a study on diagnostic performance or an AI device. The "test set" here refers to lab samples of the material for physical property testing. No geographical data provenance is specified for these lab tests.

    3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts: Not applicable. Ground truth as in medical diagnosis is not relevant here. The "ground truth" for material properties is established by standardized laboratory testing according to ISO standards.

    4. Adjudication method (e.g. 2+1, 3+1, none) for the test set: Not applicable. This is not a human-in-the-loop diagnostic study. Lab tests follow specific protocols.

    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. This is not an AI or diagnostic device.

    6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done: Not applicable. This is not an algorithm.

    7. The type of ground truth used (expert consensus, pathology, outcomes data, etc.): The "ground truth" for the physical properties of the dental material is established through standardized laboratory testing methods following international standards (ISO 4049, ISO 6507-1, ISO 3107) and biocompatibility testing (ISO 10993 series).

    8. The sample size for the training set: Not applicable. There is no "training set" as this is not a machine learning model.

    9. How the ground truth for the training set was established: Not applicable.

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