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510(k) Data Aggregation

    K Number
    K071845
    Manufacturer
    Date Cleared
    2007-09-28

    (85 days)

    Product Code
    Regulation Number
    878.4800
    Reference & Predicate Devices
    Why did this record match?
    Device Name :

    RELIEVA LUMA SINUS ILLUMINATION SYSTEM, MODEL SIS-100A

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

    The Relieva Luma™ Sinus Illumination System is intended to provide a means to access the sinus space for diagnostic and therapeutic procedures in conjunction with other nasal and sinus products. It is also intended to illuminate within and transilluminate across nasal and sinus structures.

    Device Description

    The Relieva Luma™ Sinus Illumination System is a flexible device that transmits light at the distal tip. The system also contains two accessories: a light cable and an adapter.

    AI/ML Overview

    The provided text describes the Relieva Luma™ Sinus Illumination System and its 510(k) submission. However, it does not contain the detailed information necessary to answer all sections of your request regarding acceptance criteria and a definitive study proving the device meets them.

    The document states: "The Relieva Luma™ Sinus Illumination System met all performance testing acceptance criteria." and "The Relieva Luma™ Sinus Illumination System is substantially equivalent to the predicate device as confirmed through relevant performance tests."

    This indicates that some performance testing was conducted, and the device met its criteria, but the specifics of what those criteria were, how the tests were performed, and the results (beyond a statement of "met all criteria") are not included in the provided text.

    Based on the available information, here is what can be extracted:

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

    Acceptance CriteriaReported Device Performance
    Not specified in the provided text.Met all performance testing acceptance criteria.

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

    This information is not provided in the document.

    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)

    This information is not provided in the document. This device is a manual surgical instrument, so "ground truth" would likely relate to its mechanical function, optical properties, or safety profile, rather than diagnostic accuracy established by experts.

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

    This information is not provided in the document. Adjudication methods are typically relevant for studies involving human interpretation or subjective assessments, which isn't explicitly detailed for this device's performance testing.

    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

    An MRMC study is not mentioned in the document. This type of study focuses on diagnostic systems, often involving AI, which is not the primary function described for the Relieva Luma™ Sinus Illumination System. The device is a "manual surgical instrument for general use" that provides illumination and access.

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

    A standalone performance evaluation (algorithm only) is not applicable as this is a physical medical device, not an AI algorithm.

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

    This information is not provided in the document. For a physical device like this, "ground truth" would likely relate to objective measurements of its physical and optical characteristics (e.g., light output, flexibility, durability, biocompatibility), rather than diagnostic "ground truth" derived from expert consensus or pathology.

    8. The sample size for the training set

    This information is not applicable as this is a physical medical device, not an AI algorithm requiring a training set.

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

    This information is not applicable for the same reason as in point 8.

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