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510(k) Data Aggregation

    K Number
    K213815
    Device Name
    SiJoin®T3
    Manufacturer
    VGI Medical, Inc.
    Date Cleared
    2023-03-29

    (477 days)

    Product Code
    OUR
    Regulation Number
    888.3040
    Type
    Traditional
    Panel
    Orthopedic
    Reference & Predicate Devices
    K180818
    Why did this record match?
    Applicant Name (Manufacturer) :

    VGI Medical, Inc.

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

    The Siloin®T3 is intended for sacroiliac joint fusion for conditions including sacrolliac joint disruptions and degenerative sacroiliitis. Two SiJoin® T3 implants must be used in the same sacroiliac joint.

    Device Description

    The VGI Medical, LLC Siloin®T3 Implant consists of a series of titanium alloy (per ASTM F3001) implants that are designed to provide mechanical support by transfixing the sacroiliac joint while biologic fusion occurs. The device consists of the implant body and perpendicular fins to provide stability while fusion occurs. The devices are available in five sizes to accommodate varied patient's anatomy.

    AI/ML Overview

    This document describes the 510(k) premarket notification for the SiJoin®T3 implant. It does not contain information about an AI/ML medical device, and therefore does not have the details required to answer the prompt regarding acceptance criteria and a study proving a device meets these criteria in the context of AI/ML performance.

    The provided text pertains to a medical implant (SiJoin®T3) intended for sacroiliac joint fusion. The performance testing described is biomechanical in nature (Static Vertical Shear, Dynamic Vertical Shear, Axial Pushout, and a cadaver range of motion study), not related to AI/ML algorithm performance.

    Therefore, I cannot fulfill the request to describe acceptance criteria and a study proving AI/ML device performance based on the provided text. The document does not contain any of the requested information regarding:

    • A table of acceptance criteria and reported device performance for an AI/ML algorithm.
    • Sample size used for an AI/ML test set or data provenance.
    • Number of experts for AI/ML ground truth, or their qualifications.
    • Adjudication method for an AI/ML test set.
    • Multi-reader multi-case (MRMC) comparative effectiveness study for AI assistance.
    • Standalone performance for an AI algorithm.
    • Type of ground truth used for an AI/ML algorithm (e.g., pathology, outcomes data).
    • Sample size for an AI/ML training set.
    • How ground truth for an AI/ML training set was established.
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