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510(k) Data Aggregation

    K Number
    K190170
    Date Cleared
    2019-05-13

    (101 days)

    Product Code
    Regulation Number
    888.3060
    Reference & Predicate Devices
    Why did this record match?
    Device Name :

    MVP Cervical Plate System

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

    The MVP Cervical Plate System is intended for anterior cervical fixation (C2-C7) in skeletally mature patients as an adjunct to fusion for the following indications:

    • Degenerative disc disease (defined as neck pain of discogenic origin with degeneration of the disc confirmed by history and radiographic studies)

    • · Spondylolisthesis
    • · Trauma (including fracture or dislocation)
    • · Spinal Stenosis
    • Deformities or curvatures (kyphosis, lordosis, or scoliosis)
    • Tumors
    • · Pseudoarthrosis
    • Failed Previous Fusion
    Device Description

    The MVP Cervical Plate System is a multiple component system that comprises several sizes of plates and screws and associated manual surgical instruments. The MVP Cervical Plate System implants are supplied non-sterile, are single use, and are fabricated from medical grade titanium alloy (Ti6Al4V ELI, ASTM F 136). The Instruments in the MVP Cervical Plate System are supplied non-sterile, are reusable, and are fabricated from titanium alloy Ti-6Al-4V or stainless steel.

    AI/ML Overview

    The provided text describes a medical device, the MVP Cervical Plate System, and its clearance process with the FDA. It does not contain information about acceptance criteria and a study proving the device meets those criteria in the context of AI/ML performance, human reader improvement with AI assistance, or standalone algorithm performance.

    Instead, the document details a traditional 510(k) submission for a physical medical device (cervical plate system) and focuses on demonstrating substantial equivalence to predicate devices through mechanical performance testing.

    Therefore, many of the requested sections (e.g., sample size for test set, number of experts for ground truth, adjudication method, MRMC study, standalone performance, training set details) are not applicable to this document as they are specific to studies evaluating AI/ML-driven devices.

    Here's the relevant information that can be extracted:

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

    Acceptance Criteria (Defined by predicate device performance)Reported Device Performance
    Static compression performance (per ASTM F1717-15)Met
    Dynamic compression performance (per ASTM F1717-15)Met
    Torsional testing performance (per ASTM F1717-15)Met
    Reprocessing instruction validationMet

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

    • Sample Size: Not explicitly stated as a "test set" in the context of clinical data. The performance testing refers to mechanical testing of the device components.
    • Data Provenance: Not applicable in the context of clinical data. The performance details refer to mechanical tests of the physical device.

    3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts (e.g. radiologist with 10 years of experience)

    • Not Applicable. This document describes mechanical testing of a physical device, not an AI/ML algorithm requiring expert-established ground truth for image interpretation or diagnosis.

    4. Adjudication method (e.g. 2+1, 3+1, none) for the test set

    • Not Applicable. This document describes mechanical testing of a physical device.

    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 document describes mechanical testing of a physical device. There is no mention of AI assistance or human readers.

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

    • Not Applicable. This document describes a physical medical device (cervical plate system), not an algorithm.

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

    • The "ground truth" for this device's performance was established by comparison to the mechanical performance of predicate devices as measured by standardized engineering tests (ASTM F1717-15).

    8. The sample size for the training set

    • Not Applicable. This document describes mechanical testing of a physical device, not an AI/ML algorithm.

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

    • Not Applicable. This document describes mechanical testing of a physical device, not an AI/ML algorithm.
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