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510(k) Data Aggregation

    K Number
    K212999
    Date Cleared
    2022-03-21

    (182 days)

    Product Code
    Regulation Number
    876.4300
    Reference & Predicate Devices
    Why did this record match?
    Device Name :

    Multi-Functional Electrosurgical Knife

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

    The Single Use Electrosurgical Knife has been designed to be used with flexible endoscopes to cut tissue using highfrequency current within the digestive tract.

    Device Description

    The device is an endoscopic electrosurgical knife for Endoscopic Submucosal Dissection (ESD). The Single Use Electrosurgical Knife is used with flexible endoscopes to cut tissue using high-frequency current within the digestive tract.

    It is recommended to use an ERBE VIO-200s electrosurgical unit to supply power to the device.

    AI/ML Overview

    The provided text focuses on the 510(k) summary for the "Multi-Functional Electrosurgical Knife" and details why it is considered substantially equivalent to existing predicate devices. It does not describe a study that involves acceptance criteria for device performance based on AI/human reader comparison or ground truth established by experts in a diagnostic context. Instead, the performance data section outlines bench and electrical testing to ensure the device performs similarly to predicate devices and meets safety standards for an electrosurgical knife.

    Therefore, many of the requested details, such as those related to AI effectiveness, human reader improvement, and expert-adjudicated ground truth, are not applicable to this submission as it doesn't describe such a study.

    However, I can extract information related to the performance data and the general approach to demonstrating substantial equivalence for this medical device.

    Here's a summary of the information available based on the provided text, addressing the points where information is present or clearly not applicable:

    1. Table of Acceptance Criteria and Reported Device Performance

    The document does not explicitly present a table of quantitative acceptance criteria with reported numerical performance values in the format requested (e.g., sensitivity, specificity, AUC). Instead, it lists performance tests conducted to demonstrate equivalence to predicate devices and conformance to standards. The "acceptance criteria" are implicitly that the proposed device performs "without significant difference" compared to predicate devices and meets established safety standards.

    Acceptance Criterion (Implicit)Reported Device Performance
    Cutting performance of digestive tract mucosaDemonstrated no significant difference from predicate devices.
    BiocompatibilityDemonstrated by passing cytotoxicity, intracutaneous reactivity, sensitization, acute systemic toxicity, and pyrogen testing.
    Electrical performanceDemonstrated by testing and conformance to IEC 60601 series standards (IEC 60601-1, IEC 60601-1-2, IEC 60601-2-2, IEC 60601-2-18).
    Cutting performance of tissueDemonstrated by testing; no significant difference from predicate devices.
    Thermal damage performance of tissueDemonstrated by testing; no significant difference from predicate devices.
    Endoscope compatibilityDemonstrated by testing; compatible with endoscopes with a minimum working channel of Φ2.8mm and maximum length of 2300mm.
    General durabilityDemonstrated by testing.
    Product appearanceDemonstrated by testing.
    Operational flexibilityDemonstrated by testing.
    Smoothness of movementDemonstrated by testing.
    Sterility Assurance Level (SAL)Achieved SAL 10⁻⁶ via EO sterilization.
    Shelf Life3 years.

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

    • The document does not specify exact sample sizes for each bench test conducted.
    • Data provenance is not explicitly mentioned in terms of country of origin, but the testing was conducted to support a submission to the U.S. FDA. The type of study is bench testing and conformance testing against standards, rather than a clinical trial or study on patient data.

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

    • This question is not applicable. The device is an electrosurgical knife, and its performance evaluation involves physical and electrical bench testing against established engineering and safety standards, and comparison to predicate devices, not interpretation of diagnostic images or data by human experts for ground truth establishment.

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

    • This question is not applicable. As in point 3, the evaluation of an electrosurgical knife's performance is based on measurable physical and electrical properties, not on subjective expert consensus or adjudication of diagnostic cases.

    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:

    • This question is not applicable. The device is an electrosurgical knife, not an AI-powered diagnostic tool. Therefore, no MRMC study involving human readers or AI assistance was performed.

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

    • This question is not applicable. The device is a surgical instrument, not an algorithm.

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

    • The "ground truth" for this device's performance evaluation is based on established engineering and safety standards (e.g., IEC 60601 series) and the performance characteristics of legally marketed predicate devices. For biocompatibility, it's based on ISO 10993 standards. For tissue cutting and thermal damage, it's based on measurable physical effects demonstrated during bench testing.

    8. The sample size for the training set:

    • This question is not applicable. The device is a physical electrosurgical knife; it does not involve machine learning or a "training set" of data in the conventional sense.

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

    • This question is not applicable for the same reason as point 8.
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