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510(k) Data Aggregation

    K Number
    K231884
    Device Name
    TRIOCLEAR System
    Date Cleared
    2023-09-01

    (66 days)

    Product Code
    Regulation Number
    872.5470
    Panel
    Dental
    Reference & Predicate Devices
    Predicate For
    N/A
    AI/MLSaMDIVD (In Vitro Diagnostic)TherapeuticDiagnosticis PCCP AuthorizedThirdpartyExpeditedreview
    Intended Use

    The TRIOCLEAR System is a series of clear, lightweight, plastic appliances indicated for the treatment of tooth malocclusions in patients with permanent dentition (i.e. all second molars). Utilizing a series of increment, it sequentially positions teeth by way of continuous gentle force.

    Device Description

    The TRIOCLEAR System is a removable, non-sterile device intended for single patient use. TRIOCLEAR is a series of clear plastic aligners that offer a solution for patients who want an aesthetic orthodontic treatment by utilizing sets of removable aligners to correct tooth malocclusions without the use of conventional wire and bracket orthodontic technology.

    AI/ML Overview

    The provided text describes the TRIOCLEAR System, an orthodontic device. However, it does not include the information requested regarding acceptance criteria and a study proving the device meets those criteria in the context of an AI/ML-driven device.

    The document is a 510(k) summary for the TRIOCLEAR System, which is a series of clear plastic aligners. The submission aims to establish substantial equivalence to a predicate device, primarily due to changes in raw material and thickness types. The performance testing section focuses on material properties of the thermoforming sheet, not the performance of an AI/ML component.

    Therefore, I cannot provide the requested information from the given text. The text does not discuss:

    • Acceptance criteria for an AI/ML device's performance.
    • A study proving an AI/ML device meets acceptance criteria.
    • Sample size for test sets or data provenance for AI/ML validation.
    • Details about experts for ground truth establishment.
    • Adjudication methods.
    • MRMC studies or effect sizes for AI assistance.
    • Standalone AI algorithm performance.
    • Type of ground truth (expert consensus, pathology, outcomes) in the context of AI.
    • Training set sample size or ground truth establishment for a training set for an AI/ML model.
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    K Number
    K193622
    Device Name
    TRIOCLEAR System
    Date Cleared
    2021-07-06

    (558 days)

    Product Code
    Regulation Number
    872.5470
    Panel
    Dental
    Reference & Predicate Devices
    Predicate For
    AI/MLSaMDIVD (In Vitro Diagnostic)TherapeuticDiagnosticis PCCP AuthorizedThirdpartyExpeditedreview
    Intended Use

    The TRIOCLEAR System is a series of clear, lightweight, plastic appliances indicated for the treatment of tooth malocclusions in patients with permanent dentition (i.e. all second molars). Utilizing a series of incremental tooth movement, it sequentially positions teeth by way of continuous gentle force.

    Device Description

    The TRIOCLEAR System is a removable, non-sterile device intended for single patient use. TRIOCLEAR is a series of clear plastic aligners that offer a solution for patients who want an aesthetic orthodontic treatment by utilizing sets of removable aligners to correct tooth malocclusions without the use of conventional wire and bracket orthodontic technology.

    AI/ML Overview

    The information provided describes the TRIOCLEAR System, an orthodontic clear aligner device, and its substantiation for 510(k) clearance. The document focuses on demonstrating substantial equivalence to predicate devices rather than providing a detailed study proving the device meets specific acceptance criteria in a clinical performance context typically seen for diagnostic AI.

    However, based on the provided text, we can glean information relevant to your request, particularly regarding physical properties testing and validation.

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

    Acceptance CriteriaReported Device Performance
    Physical Properties Testing
    Tensile strength (according to ISO 527-2)Met acceptance criteria
    Modulus (according to ISO 527-2)Met acceptance criteria
    Elongation (according to ISO 527-2)Met acceptance criteria
    Hardness (according to ASTM D785)Met acceptance criteria
    Humidity absorption (immersion in distilled water for 24 hours at 23°C)Met acceptance criteria
    Validation of Digital and 3D Printed Models & Thermoformed Aligners
    Differences calculated using CAD overlay methodAll aligners fabricated met pre-defined acceptance criteria
    RMS calculationsAll aligners fabricated met pre-defined acceptance criteria
    Form and fit of thermoformed alignersReceived an A grade
    Biocompatibility Testing
    CytotoxicityNon-cytotoxic
    SensitizationNon-sensitizing
    IrritationNon-irritant
    Acute Systemic ToxicityNo acute systemic toxicity
    PyrogenicityNon-pyrogenic
    Subacute ToxicityNo subacute repeated exposure systemic toxicity
    ImplantationNon-irritant when compared to implanted negative control article

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

    The document does not explicitly state the sample sizes for the physical properties testing or the validation of digital/3D printed models and aligners. It also does not specify the provenance (country of origin, retrospective/prospective) of any data used beyond stating that "Physical properties testing was conducted on the device" and "Validation was performed on the digital and 3D printed models, as well as the thermoformed aligners." Since this is a submission from Hong Kong, it is likely the testing was conducted there, but this is not explicitly stated for the data provenance.

    3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts

    This information is not provided. The study focuses on physical and material properties and validation of the manufacturing process, rather than a clinical performance study with expert ground truth. The "pre-defined acceptance criteria" for aligner validation and "A grade for form and fit" would imply an internal standard or expert assessment, but details are absent.

    4. Adjudication method for the test set

    This information is not applicable or provided. The testing described is primarily objective physical and material properties, and validation of manufacturing accuracy. There is no mention of an adjudication method typical for human-interpreted diagnostic tasks.

    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 such study was conducted or described in this document. The TRIOCLEAR System is an orthodontic appliance, not an AI diagnostic tool that assists human readers.

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

    This is not applicable. The device is a physical clear aligner system. There is a "digital design" phase where "Perfection designs a series of plastic trays intended to gradually realign the patient's teeth in accordance with the physician's prescription," and "The prescribing physician reviews and approves the model scheme before the molds are produced." While this involves digital tools, it's a design and manufacturing process, not an AI algorithm performing a standalone diagnostic task.

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

    For the physical properties and material testing, the "ground truth" is defined by established international standards (ISO 527-2, ASTM D785) and internal "pre-defined acceptance criteria." For the validation of the digital and 3D printed models and aligners, the ground truth for comparison appears to be the intended design (physician's prescription transformed into a digital model), against which the actual fabricated products (digital models, 3D printed models, thermoformed aligners) are measured using CAD overlay and RMS calculations.

    8. The sample size for the training set

    Not applicable. This is not an AI/machine learning device that involves a training set.

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

    Not applicable, as there is no training set for an AI algorithm.

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