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510(k) Data Aggregation

    K Number
    K021852

    Validate with FDA (Live)

    Date Cleared
    2003-02-11

    (251 days)

    Product Code
    Regulation Number
    878.4400
    Reference & Predicate Devices
    Predicate For
    N/A
    AI/MLSaMDIVD (In Vitro Diagnostic)TherapeuticDiagnosticis PCCP AuthorizedThirdpartyExpeditedreview
    Intended Use

    This instrument has been designed to be used with Olympus recommended Electrosurgical accessories, Endoscope, Light Source and other ancillary equipment for bronchial endoscopic treatment (cutting and coagulating) including:

    • Hemostasis of superficial bleeding
    • Treatment of benign tumors like papillomatosis, granulomas, polyps, lipomas and hemangiomas in the trachea and bronchi
    • Recanalization of malignant stenoses
    • Treatment of Cicatricial stenoses of the respiratory tract
    Device Description

    This instrument has been designed to be used with Olympus recommended Electrosurgical accessories, Endoscope, Light Source and other ancillary equipment for bronchial endoscopic treatment (cutting and coagulating. Recommended endoscopes for this instrument are Olympus's series BF series, and Olympus's electrosurgical instruments such as electrosurgical snare, hot biopsy forceps. Other Olympus electrosurgical devices or instruments can be used with this subject device. Be sure to check compatibility for each device in each instrument's instruction manual. The PSD-20 unit offers Monopolar output modes; 5 Cut modes (PURE, BLEND 1/2/3/4), 1 Coagulation mode. (NORMAL COAGULATION), It offers several features to ensure the safe operation of the unit. For example, the voltage output level setting and a monitor circuit detect irreqularity or improper connections.

    AI/ML Overview

    The provided text describes the Olympus PSD-20 Electrosurgical System and its associated accessories, a device for bronchial endoscopic treatment. However, it does not contain information about acceptance criteria or a study proving the device meets specific performance criteria in the way that would typically be described for AI/ML-driven devices (e.g., sensitivity, specificity, AUC).

    This document is a 510(k) summary for a medical device that generates electrical power for electrosurgical accessories, rather than a diagnostic or AI-powered device that interprets data or makes diagnoses. Therefore, the questions about sample size for test/training sets, data provenance, number of experts, adjudication methods, MRMC studies, standalone performance, and ground truth types are not applicable to the information provided in this 510(k) submission.

    The "acceptance criteria" mentioned in the document relate to compliance with voluntary standards for electrosurgical units. The "study" proving acceptance is essentially the design and testing demonstrating compliance with these electrical and safety standards.

    Here's an attempt to answer the request based only on the provided text, acknowledging the limitations for an AI/ML context:

    1. Table of Acceptance Criteria and Reported Device Performance

    Acceptance Criteria (Voluntary Standards for Design Compliance)Reported Device Performance (Design Compliance)
    IEC 60601-1 (General requirements for safety of medical electrical equipment)Device designed to comply with this standard
    IEC 60601-2-2 (Particular requirements for the safety of high frequency surgical equipment)Device designed to comply with this standard
    IEC 60601-2-18 (Particular requirements for the safety of endoscopic equipment)Device designed to comply with this standard
    IEC 60601-1-2 (EMC – Electromagnetic compatibility)Device designed to comply with this standard
    Safe operation features (e.g., voltage output level setting, monitoring circuit for irregularity/improper connections)Device offers these features to ensure safe operation.

    2. Sample size used for the test set and the data provenance
    Not applicable. This is a submission for an electrosurgical unit, not a diagnostic or AI device with a "test set" in the conventional sense for performance evaluation. Compliance is shown through design adherence to standards and safety features.

    3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts
    Not applicable. Ground truth for performance metrics (sensitivity, specificity) is not relevant for this type of device submission.

    4. Adjudication method for the test set
    Not applicable.

    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 device is not an AI/ML-driven diagnostic or assistance tool.

    6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done
    Not applicable.

    7. The type of ground truth used (expert consensus, pathology, outcomes data, etc.)
    Not applicable for performance metrics. The "ground truth" for this device's acceptance is its compliance with established electrical, safety, and electromagnetic compatibility (EMC) standards.

    8. The sample size for the training set
    Not applicable. This device is not an AI/ML-driven device that undergoes "training."

    9. How the ground truth for the training set was established
    Not applicable.

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