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510(k) Data Aggregation

    K Number
    K190696
    Manufacturer
    Date Cleared
    2019-06-28

    (102 days)

    Product Code
    Regulation Number
    872.4760
    Panel
    Dental
    Reference & Predicate Devices
    Predicate For
    N/A
    AI/MLSaMDIVD (In Vitro Diagnostic)TherapeuticDiagnosticis PCCP AuthorizedThirdpartyExpeditedreview
    Intended Use

    The Stryker Surgeon iD Mandible Recon Plate is intended to be used for rigid internal fixation of primary and secondary mandibular reconstructions.

    The Stryker Surgeon iD Mandible Recon Plate is indicated for use in primary mandibular reconstruction with bone graft, temporary bridging until delayed secondary reconstruction and secondary mandibular reconstruction.

    Device Description

    The Subject Device, the Stryker Surgeon iD Mandible Recon Plate is intended to be used for rigid internal fixation of primary and secondary mandibular reconstructions.

    The Surgeon iD Mandible Recon Plate is a surgeon-specific plate which is designed based on an average mandible model. The plate is designed per surgeon's preference within the following design envelope. The Surgeon iD Mandible Recon Plate is offered in hemi and full shapes and three different sizes (Small, Medium, and Large). The plate can be designed with a profile height of 2.0 mm or 2.8 mm, with a number of screw holes between 4 and 50, and bar widths between 5.5 mm and 6.5 mm. The plate is made of commercially pure titanium.

    AI/ML Overview

    The provided text describes the Stryker Surgeon iD Mandible Recon Plate and its acceptance criteria, but it primarily focuses on establishing substantial equivalence to a predicate device rather than presenting a standalone study showing device performance against specific, quantifiable acceptance criteria in the manner typically expected for AI/software devices. The acceptance criteria in this document relate more to the validation process rather than direct performance metrics against a clinical standard.

    Here's an attempt to extract and interpret the requested information based on the provided text. It's important to note that many sections of your request are not directly applicable or explicitly stated in this type of 510(k) summary for a physical medical device. This summary focuses on materials, design, and comparison to a predicate, not AI performance.


    1. Table of Acceptance Criteria and Reported Device Performance

    Based on the provided text, the "acceptance criteria" are related to the successful completion of verification and validation (V&V) activities and the functional demonstration that the device performs as intended and is compatible with its packaging.

    Acceptance Criteria CategoryReported Device Performance
    Performance Bench Testing:
    Analysis of Functional InterfacesMet all pre-defined acceptance criteria
    Evaluation of the ModelsMet all pre-defined acceptance criteria
    Compatibility (e.g., fasteners, instruments)Met all pre-defined acceptance criteria
    Packaging (integrity, sterility maintenance)Met all pre-defined acceptance criteria
    Cleaning and Sterilization ValidationEquivalent to the Predicate Device
    Biocompatibility TestingReferenced in the Predicate Device (implying equivalence)
    SterilizationReferenced in the Predicate Device (implying equivalence)
    Substantial Equivalence (Overall Conclusion)Concluded that the information supports substantial equivalence, meaning it performs as safely and effectively as the predicate device.

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

    This information is not provided in the document. The text mentions "Verification and Validation activities" and "performance testing" but does not specify sample sizes for these tests or the provenance of any data beyond indicating that existing predicate device data was referenced for some aspects. Given this is a physical implantable device, the "test set" would likely refer to the number of plates or components tested, not a dataset in the AI sense.


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

    This information is not applicable as presented. The concept of "ground truth" established by experts, particularly for an AI/software device, is not discussed in this 510(k) summary for a bone plate. Ground truth for a physical device like this is typically established through engineering specifications, material testing standards, and ultimately, clinical outcomes (though clinical trials were not required here).


    4. Adjudication Method for the Test Set

    This information is not applicable and not provided. Adjudication methods like "2+1" or "3+1" are typically used in clinical studies involving interpretation (e.g., radiology reads) to resolve discrepancies among experts. This 510(k) summary describes bench testing and equivalence to a predicate device, not expert adjudication of a test set.


    5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study Was Done, and Effect Size

    No, a Multi-Reader Multi-Case (MRMC) comparative effectiveness study was not done. This type of study is relevant for AI or diagnostic imaging devices comparing human reader performance with and without AI assistance. This document is for a physical medical device (a bone plate), not an AI diagnostic tool. Clinical testing was explicitly stated as "not required as a basis for substantial equivalence."


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

    No, a standalone algorithm performance study was not done. This device is a physical bone plate, not an algorithm.


    7. The Type of Ground Truth Used

    For this physical device, the "ground truth" for the performance bench testing would be defined by engineering specifications, material science standards, and the expected mechanical behavior of such a plate. For aspects like biocompatibility and sterilization, the ground truth is established by regulatory standards and established test methods that were either performed or referenced from the predicate device. Clinical outcomes data was not a basis for this submission.


    8. The Sample Size for the Training Set

    This information is not applicable and not provided. The device is a physical bone plate, not an AI model that requires a training set. The design of the plate is based on an "average mandible model" and "surgeon's preference," which are design inputs, not a 'training set' in the machine learning sense.


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

    This information is not applicable and not provided. As the device is not an AI algorithm, there is no "training set" or corresponding ground truth to be established in that context.

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