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510(k) Data Aggregation

    K Number
    K041980
    Date Cleared
    2004-08-06

    (14 days)

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

    Indicated for coagulation of soft tissue
    These devices are intended for use by qualified medical personnel trained in the use of electrosurgery.

    Device Description

    MSI S-500L RF Generator

    AI/ML Overview

    This 510(k) submission (K041980) for the MSI S-500L RF Generator provides limited information regarding specific acceptance criteria and study details. The document focuses on demonstrating substantial equivalence to a predicate device through general performance testing rather than providing detailed quantitative acceptance criteria and a standalone clinical study report.

    Based on the provided text, here's what can be extracted and what is not available:

    1. Table of Acceptance Criteria and Reported Device Performance

    The submission states, "Performance testing was done to validate its intended use." However, it does not provide a specific table of acceptance criteria or quantitative performance metrics for the MSI S-500L RF Generator. The evaluation primarily relies on comparison to a predicate device.

    2. Sample size used for the test set and the data provenance

    The document does not specify a "test set" in the context of an AI/algorithm-based device for which this information would typically be relevant. This is an electrosurgical generator, and "performance testing" usually refers to bench testing, electrical safety, electromagnetic compatibility, and functional verification, not clinical data sets in the AI sense.

    3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts

    Not applicable, as this is not an AI/algorithm-based device and no clinical "ground truth" establishment by experts is described in the provided text.

    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 is not an AI-assisted device for human readers.

    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. The "ground truth" for an electrosurgical generator's performance would likely be based on established engineering standards, electrical performance specifications, and safety benchmarks, not clinical ground truth in the context of imaging or diagnostics.

    8. The sample size for the training set

    Not applicable. This is not an AI/machine learning device that would require a training set.

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

    Not applicable.


    Summary of available information:

    • Acceptance Criteria & Performance: Not explicitly detailed in quantitative terms. The submission states that "Performance testing was done to validate its intended use" and that "The comparison and performance testing results in this 510(k) notification shows MSI S-500L RF Generator is substantially equivalent to predicate device and is safe and effective in its intended use." This implies that the device's performance met the general expectations for such a device, in line with its predicate.
    • Study Type: No large-scale clinical study with a "test set" in the typical sense of AI/diagnostic device evaluation is described. The focus is on demonstrating substantial equivalence to a predicate device (MSI S-500 RF Generator K033888) through engineering and functional performance testing.
    • Device Type: Electrosurgical Generator, not an AI/ML-based device. Therefore, many of the requested criteria (test set, ground truth, experts, MRMC studies, training set) typically apply to AI algorithms or diagnostic devices and are not relevant or addressed in this document.
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