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510(k) Data Aggregation

    K Number
    K190645
    Manufacturer
    Date Cleared
    2019-07-05

    (114 days)

    Product Code
    Regulation Number
    876.1500
    Reference & Predicate Devices
    Predicate For
    AI/MLSaMDIVD (In Vitro Diagnostic)TherapeuticDiagnosticis PCCP AuthorizedThirdpartyExpeditedreview
    Intended Use

    The Arthrex NanoScope system is intended to be used as an endoscopic video camera in a variety of endoscopic surgical procedures, including but not limited to: orthopedic, urologic, sinuscopic, and plastic surgical procedures. The device is also intended to be used as an accessory for microscopic surgery.

    Device Description

    The Arthrex NanoScope System provides image processing and digital documentation for endoscopic procedures. The system comprises a camera control unit (CCU) and a handpiece that provides distal LED illumination to the surgical site using a fiber optic bundle surrounding a high-resolution camera sensor.

    AI/ML Overview

    This a 510(k) summary for the Arthrex NanoScope System, which is an endoscopic video camera system. The submission seeks to prove substantial equivalence to a predicate device, the Arthrex Synergy UHD4 System (K153218). The provided document does not contain specific acceptance criteria or a detailed study report with performance metrics for the Arthrex NanoScope System.

    However, it does indicate that bench testing was performed to demonstrate equivalence to the predicate regarding environmental conditions, power requirements, image capture, and video output and resolution. This implies that the acceptance criteria would relate to these specific performance aspects, with the predicate device's performance serving as the benchmark.

    Since detailed study results and acceptance criteria are not explicitly present in the provided text, I will answer based on the information implied by the document about the type of study and the areas of comparison.

    Here's an attempt to answer the questions based on the available information and logical inference for a 510(k) submission of this nature:

    1. Table of Acceptance Criteria and Reported Device Performance

    As specific numerical acceptance criteria and reported performance metrics are not provided in the document, this table is constructed based on the types of tests mentioned as being performed for equivalence. The acceptance criterion is implied to be "Matches or performs comparably to the predicate device."

    Acceptance Criteria (Implied)Reported Device Performance (Implied)
    Environmental conditions performance is comparable to predicate.Bench testing demonstrated equivalence to predicate.
    Power requirements are comparable to predicate.Bench testing demonstrated equivalence to predicate.
    Image capture performance is comparable to predicate.Bench testing demonstrated equivalence to predicate.
    Video output and resolution performance is comparable to predicate.Bench testing demonstrated equivalence to predicate.
    No significant differences raising safety/effectiveness concerns.Differences are minor and do not raise safety/effectiveness concerns.

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

    The document mentions "bench testing." Typically, bench testing for a device like an endoscopic camera would involve a physical sample of the device rather than a "test set" of patient data.

    • Sample Size: Not explicitly stated, but for bench testing, it would generally involve one or more manufactured units of the Arthrex NanoScope System.
    • Data Provenance: Not applicable in the context of patient data. The "data" here would be the measurements and observations from the physical bench tests performed in a lab setting. It is not retrospective or prospective in the clinical sense.

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

    This question is not directly applicable. Bench testing does not typically involve human experts establishing "ground truth" in the way a clinical study would (e.g., radiologists interpreting images). The "ground truth" for bench testing would be established by validated test equipment and objective measurements against predefined specifications or the predicate's performance.

    4. Adjudication Method for the Test Set

    Not applicable. Adjudication methods like 2+1 or 3+1 are used in clinical studies for reconciling conflicting expert opinions on data. Bench testing relies on objective measurements and established test protocols.

    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 MRMC study was done. This device is an endoscopic video camera system, not an AI-assisted diagnostic tool. The submission focuses on the performance of the camera itself, primarily through bench testing comparing it to a predicate device.

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

    This question is not applicable. The Arthrex NanoScope System is a hardware device (video camera system), not a standalone algorithm. Its performance is measured directly through its physical output (image quality, resolution, etc.), not as an algorithmic output requiring a human-in-the-loop for interpretation of an algorithm's classification.

    7. The Type of Ground Truth Used

    The "ground truth" for the bench testing would be the objective measurements obtained from testing the Arthrex NanoScope System against established engineering specifications or by directly comparing its performance characteristics (e.g., resolution, light output, power consumption) to that of the predicate device (Arthrex Synergy UHD4 System K153218) using calibrated equipment. It's not expert consensus, pathology, or outcomes data.

    8. The Sample Size for the Training Set

    This question is not applicable. The Arthrex NanoScope System is a hardware device; it does not involve machine learning or AI models that require a "training set" of data.

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

    This question is not applicable, as there is no training set for this device.

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