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510(k) Data Aggregation

    K Number
    K093057
    Manufacturer
    Date Cleared
    2009-12-01

    (62 days)

    Product Code
    Regulation Number
    888.3030
    Reference & Predicate Devices
    Why did this record match?
    Device Name :

    BIOMET VISION FOOTRING SYSTEM

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

    The Biomet® Vision® Foot Ring System is intended for use in the treatment of bone conditions including leg lengthening, osteotomies, arthrodesis, fracture fixation, and other bone conditions amenable to treatment by the use of the external fixation treatment modality.

    Additional indications include:

    • Correction of deformity .
    • Revision procedures where other treatments or devices have been unsuccessful .
    • Bone reconstruction procedures .
    • Fusions and replantations of the foot .
    • Charcot foot reconstruction and Lisfranc dislocations
    • Ankle distraction (arthrodiastasis)
    Device Description

    Device Desertification. and K052239.

    AI/ML Overview

    This submission is a 510(k) Premarket Notification for the Biomet® Vision® Foot Ring System. This type of submission relies on demonstrating substantial equivalence to a legally marketed predicate device rather than providing extensive clinical study data for acceptance criteria.

    Therefore, the provided document does not contain the information requested regarding acceptance criteria and a study that proves the device meets specific performance metrics.

    Instead, the document states:

    • The Biomet Trauma device is substantially equivalent to other legally marketed devices, specifically the Stryker Hoffman II Foot Ring (K041706) and the SBi RingFIX™ System (K071394).
    • The "Operational principles for the device are unchanged." (from the previously cleared device)

    The FDA's letter further confirms that they have "reviewed your Section 510(k) premarket notification... and have determined the device is substantially equivalent... to legally marketed predicate devices."

    In summary, none of the requested information (1-9) about acceptance criteria, study design, sample sizes, ground truth establishment, or human reader performance is present in this 510(k) summary because it is not typically required for a substantial equivalence determination for this type of device.

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    K Number
    K071395
    Date Cleared
    2007-07-09

    (49 days)

    Product Code
    Regulation Number
    888.3030
    Reference & Predicate Devices
    Why did this record match?
    Device Name :

    BIOMET VISION FOOTRING SYSTEM

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

    The Biomet® Vision® FootRing System is intended for use in the treatment of bone conditions including leg lengthening, osteotomies, arthrodesis, fracture fixation, and other bone conditions amenable to treatment by the use of the external fixation treatment modality.

    Device Description

    The Biomet® Vision® FootRing System is an external fixation device. The devices in this 510(k) are additional modular components to the predicate Biomet® Vision® FootRing System, which is based upon the FootRing component as the frame for a construct.

    AI/ML Overview

    The provided document is a 510(k) Summary for the Biomet® Vision® FootRing System, dated July 7, 2007. This summary outlines a request for substantial equivalence to existing legally marketed devices, primarily the EBI® DynaFix® Vision® FootPlate System (K052239).

    This document describes a medical device (an external fixation system), not an AI/ML powered device or software. Therefore, the requested information pertaining to acceptance criteria and studies for AI/ML performance (e.g., sample sizes for test/training sets, expert ground truth, MRMC studies, standalone performance) is not applicable or available in this submission.

    The submission focuses on establishing substantial equivalence through non-clinical mechanical testing and makes no mention of performance metrics related to diagnostic accuracy, sensitivity, specificity, or other metrics typically associated with AI/ML systems.

    Here's a breakdown of the available information based on the request:


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

    Acceptance Criteria (Design Specifications/Performance Requirements)Reported Device Performance
    Static Design SpecificationsMet (results were as expected)
    Fatigue Design SpecificationsMet (results were as expected)
    Performance with respect to the predicate device (EBI® DynaFix® Vision® FootPlate System, K052239)Functional within its intended use and substantially equivalent to the predicate device in performance characteristics.
    For new connection components: Static Design SpecificationsMet (results were as expected)

    Notes on Acceptance Criteria: The document states that mechanical testing was conducted "to verify the static and fatique design specifications and to determine performance with respect to the predicate" and "to verify static design specifications for new connection components." The acceptance criteria themselves (e.g., specific load limits, cycle numbers) are not detailed in this summary, but the results indicate they were met.


    The following information is not applicable to this medical device submission as it is not an AI/ML powered device or software. No information regarding these aspects is present in the provided text.

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

    • Not applicable. The submission relies on mechanical testing of the device hardware, not data-driven performance.

    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. No ground truth from experts in a clinical data context was established.

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

    • Not applicable. No adjudication method for clinical data was used.

    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 is a hardware device; no human reader studies with or without AI assistance were conducted.

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

    • Not applicable. There is no algorithm or software for standalone performance testing.

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

    • Not applicable (in the AI/ML sense). The "ground truth" for this device's performance was its adherence to engineering design specifications and mechanical performance standards, verified through physical testing.

    8. The sample size for the training set

    • Not applicable. There is no AI/ML model to train.

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

    • Not applicable. There is no AI/ML model to train.
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