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510(k) Data Aggregation

    K Number
    K121589
    Date Cleared
    2012-09-21

    (113 days)

    Product Code
    Regulation Number
    872.4760
    Panel
    Dental
    Reference & Predicate Devices
    Why did this record match?
    Device Name :

    BIOMET MICROFIXATION FACIAL PLATING SYSTEM

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

    These devices are implantable bone plates and bone screws for facial procedures including:

    1. Fractures
    2. Osteotomies
    3. Reconstructive procedures
    4. Revision procedures where other treatments or devices have failed
    Device Description

    The Biomet Microfixation Facial Plating System is comprised of a variety of titanium plates, meshes, and screws with shapes and sizes designed for internal fixation of facial fractures and reconstruction procedures. System implants are manufactured from either titanium or titanium alloy and are intended for single use only.

    The Facial Plating System plates that are the subject of this 510(k) submission include variations of straight, angle, curved, L-shape, double T-shape, Z-shape, X-shape, Y-shape, double Y-shape, H-shape, triangle, square, rectangle, matrix, mesh, orbital floor, LeFort, and chin options with various lengths and thickness. Plates are offered flat or pre-bent. Surgeons use cutting and bending instruments intraoperatively to contour flat plates to patient anatomy; prebent plates are contoured by Biomet Microfixation per surgeon specifications or patient anatomy as a convenience. The Facial Plating System screws range in diameters of 1.0mm to 2.3mm and lengths from 2:0mm to 29.0mm.

    AI/ML Overview

    The provided document describes a 510(k) premarket notification for the Biomet Microfixation Facial Plating System, which is a medical device. The submission focuses on demonstrating substantial equivalence to predicate devices through non-clinical mechanical testing, rather than clinical studies involving AI or human reader performance. Therefore, many of the requested categories related to AI performance, ground truth, experts, and human reader studies are not applicable directly to this document's content.

    Here's an analysis based on the provided text:

    1. Table of Acceptance Criteria and Reported Device Performance

    TestAcceptance Criteria (Implied)Reported Device Performance
    Plates
    Failure Force (lbf) in BendingEquivalent to or better than predicate devicesMechanical performance shown to be equivalent or better than predicate devices.
    Rate of Deflection (in/lb)Equivalent to or better than predicate devicesMechanical performance shown to be equivalent or better than predicate devices.
    Push-Through Strength (lbs)Equivalent to or better than predicate devicesMechanical performance shown to be equivalent or better than predicate devices.
    Screws
    Insertion Torque (in-oz)Equivalent to or better than predicate devicesMechanical performance shown to be equivalent or better than predicate devices.
    Fracture Torque (in-oz)Equivalent to or better than predicate devicesMechanical performance shown to be equivalent or better than predicate devices.

    Note: The document states the non-clinical test results "demonstrate that the mechanical performance of the subject Facial Plating System plates and screws are equivalent or better than the predicate devices and support the substantial equivalence to the predicate devices." Implied acceptance criteria are that the new device performs at least as well as, or better than, the predicate devices for each tested mechanical characteristic.

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

    The document does not specify the exact sample sizes (number of plates and screws) used for each mechanical test. However, it indicates these were non-clinical tests, likely conducted in a lab setting. Therefore, the "data provenance" would be laboratory testing, not human-sourced data from a specific country, nor retrospective or prospective patient data, as no clinical testing was performed for this submission.

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

    Not applicable. Ground truth, in the context of this document, refers to the objective results of mechanical tests, not expert interpretation of diagnostic data. No human experts were involved in establishing the "ground truth" for the mechanical performance of the devices beyond their role in conducting and reporting the standardized tests.

    4. Adjudication Method for the Test Set

    Not applicable. Since the "test set" consists of mechanical test results, there is no need for an adjudication method as would be used for human interpretation of medical images or diagnoses. The objective measurements from mechanical tests serve as the direct outcome.

    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. A Multi-Reader Multi-Case (MRMC) comparative effectiveness study was not done. This submission is for a physical medical device (bone plates and screws) and does not involve AI or human readers for diagnostic purposes. The document explicitly states: "Clinical testing was not performed to support this submission."

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

    No. This is not an AI algorithm. It is a physical medical device. Therefore, a standalone algorithm-only performance study is not applicable.

    7. The Type of Ground Truth Used

    The "ground truth" used was mechanical test results (e.g., failure force, rate of deflection, push-through strength, insertion torque, fracture torque). These are objective measurements obtained from standardized laboratory tests comparing the subject devices to predicate devices.

    8. The Sample Size for the Training Set

    Not applicable. There is no "training set" in the context of this device submission, as it does not involve machine learning or AI algorithms requiring training data.

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

    Not applicable. As there is no training set, there is no ground truth to be established for it.

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