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510(k) Data Aggregation

    K Number
    K971275
    Device Name
    MILL-ROSE DISPOSABLE POLYPECTOMY SNARE
    Manufacturer
    MILL-ROSE LABORATORY
    Date Cleared
    1997-05-23

    (46 days)

    Product Code
    FDI
    Regulation Number
    876.4300
    Type
    Traditional
    Panel
    Gastroenterology/Urology
    Reference & Predicate Devices
    K912254,K792343,K951600
    Why did this record match?
    Device Name :

    MILL-ROSE DISPOSABLE POLYPECTOMY SNARE

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

    The intended use of the subject device is to electrosurgically remove GI tract polyps through the channel of an endoscope

    Device Description

    The device consists of a handle, cable, snare loop and cable. The loop is attached to the handle assembly by means of the cable. The sheath is also connected to the handle assembly and collapses the loop upon its retraction into the sheath.

    AI/ML Overview

    The provided text describes a 510(k) premarket notification for a medical device called the "Mill-Rose Disposable Polypectomy Snare." This is a regulatory submission to demonstrate that a new device is substantially equivalent to a legally marketed predicate device.

    Based on the provided documents, there is no information about acceptance criteria or a study that proves the device meets specific acceptance criteria in the manner you've outlined for AI/software devices.

    Here's why and what can be extracted based on your questions:

    • Type of Device: The Mill-Rose Disposable Polypectomy Snare is a physical medical instrument used for electrosurgical removal of GI tract polyps. It is not an AI/software device, imaging device, or diagnostic tool that would typically have performance metrics like sensitivity, specificity, or reader improvement studies.
    • Regulatory Pathway: The 510(k) pathway focuses on demonstrating "substantial equivalence" to a predicate device already on the market. This typically involves comparing material, design, technological characteristics, and intended use to the predicate device, not necessarily conducting performance studies in the way an AI/diagnostic device would. The goal is to show it performs as safely and effectively as the predicate, not necessarily to quantify its performance against a set of statistical cutoffs like an AI model.

    Therefore, the requested information categories (e.g., sample size for test sets, ground truth establishment, MRMC studies, standalone performance) are not applicable or not provided in this type of regulatory submission for this type of device.

    Here's what can be answered from the provided text, largely by stating "Not Applicable" or "Not Provided" due to the nature of the device and submission:

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

    Acceptance CriteriaReported Device Performance
    Not Applicable (This is a 510(k) for a physical medical device, not an AI/diagnostic tool with performance metrics like sensitivity/specificity). The acceptance criteria for this type of device focus on substantial equivalence to a predicate in terms of materials, design, technological characteristics, and intended use, rather than quantitative performance metrics against a medical condition.Not Applicable. Performance is established through substantial equivalence to a predicate device (K912254, K792343, K951600), implying similar safety and effectiveness. No specific quantitative performance metrics are reported in the provided text.

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

    • Sample Size for Test Set: Not Applicable / Not Provided. This type of performance testing with a "test set" and ground truth is not described for this physical device in a 510(k) submission.
    • Data Provenance: Not Applicable / Not Provided.

    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)

    • Number of Experts: Not Applicable / Not Provided.
    • Qualifications of Experts: Not Applicable / Not Provided.

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

    • Adjudication Method: Not Applicable / Not Provided.

    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

    • MRMC Study: No, Not Applicable. This is a physical device, not an AI system.
    • Effect Size of Human Readers with AI: Not Applicable.

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

    • Standalone Performance: No, Not Applicable. This is a physical device, not an algorithm.

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

    • Type of Ground Truth: Not Applicable / Not Provided. Performance is based on substantial equivalence to predicate devices, not on a ground truth established for diagnostic accuracy.

    8. The sample size for the training set

    • Sample Size for Training Set: Not Applicable / Not Provided. This is a physical device, not an AI/machine learning model that requires a training set.

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

    • Ground Truth Establishment for Training Set: Not Applicable / Not Provided.
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