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510(k) Data Aggregation

    K Number
    K093783
    Manufacturer
    Date Cleared
    2010-08-23

    (257 days)

    Product Code
    Regulation Number
    876.1500
    Reference & Predicate Devices
    Why did this record match?
    Device Name :

    INNOVIA INNOPORT LAPAROSCOPIC ACCESS PORT

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

    The Innovia InnoPort™ Laparoscopic Access Device is a sterile, single use device intended for use as a multiple instrument and/or camera port during minimally invasive laparoscopic abdominal surgery.

    Device Description

    The InnoPort Laparoscopic Access Port is a sterile, single use laparoscopic access device comprised of flexible polymer and a rigid plastic plate. The InnoPort forms a truncated cone approximately 5.0 centimeters long (not including instrument ports), with three individual laparoscopic instrument ports at the larger end. A fourth port connects to the infor system to provide intra-abdominal pneumoperitoneum, and a fifth port coulties of the insunprocedural smoke removal. The instrument ports are designed to accommodate 5 mm dinerer laparoscopic instruments while allowing full maneuverability without loss of neumperioneum. The complete device is designed to be inserted through a single incision into the abdominal cavity for the duration of surgery.

    AI/ML Overview

    The prompt asks for acceptance criteria and study details related to a medical device's performance. However, the provided document is a 510(k) summary for the "InnoPort™ Laparoscopic Access Port," which is a physical medical device, not an AI or software-based device.

    Therefore, many of the requested categories in the prompt, such as "number of experts used to establish ground truth," "adjudication method," "MRMC comparative effectiveness study," "standalone performance," "training set sample size," and "ground truth for training set," are not applicable to this type of medical device and its associated 510(k) submission.

    The document focuses on demonstrating substantial equivalence to a predicate device through bench and in vivo tests, verifying its mechanical performance and safety, rather than evaluating an algorithm's diagnostic accuracy against a ground truth.

    Here's an attempt to answer the applicable parts of the prompt based only on the provided text, while explicitly stating when information is not available or not applicable:


    Acceptance Criteria and Device Performance Study Details for Innovia InnoPort™ Laparoscopic Access Port

    1. Table of Acceptance Criteria and Reported Device Performance:

    The 510(k) summary does not explicitly list quantitative acceptance criteria in a table format with corresponding performance metrics. Instead, it broadly states the device was tested to verify its ability to meet performance specifications related to the intended use.

    Acceptance Criteria CategoryReported Device Performance
    Maintain PneumoperitoneumWith minimal leakage
    Instrument Introduction & ManipulationAllows introduction and maneuverability of instruments
    Overall Performance & SafetyMeets performance specifications; introduces no new safety or effectiveness issues when used as instructed

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

    • Test Set Sample Size: Not explicitly stated in the provided document. The document mentions "bench and in vivo tests" but does not quantify the number of tests, devices, or subjects used.
    • Data Provenance: Not explicitly stated (e.g., country of origin). The testing included "bench and in vivo tests," which implies a combination of laboratory testing and potentially animal or human studies, but the specifics are not detailed. It is a prospective study in the sense that the testing was conducted specifically for this 510(k) submission.

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

    • Not Applicable. This device is a physical laparoscopic access port, not an AI or diagnostic software. Ground truth in the context of expert consensus or diagnostic accuracy is not relevant for its performance evaluation in this 510(k) submission. The performance tests would likely involve engineers and possibly surgeons in simulated or live surgical settings, but not for "establishing ground truth" in a diagnostic sense.

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

    • Not Applicable. As a physical device, adjudication methods for diagnostic output are not relevant. Performance was likely determined by direct observation, measurement, and functional assessment during bench and in vivo testing.

    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. An MRMC study is relevant for evaluating the impact of AI on human diagnostic performance. This device is a surgical instrument and does not involve "human readers" or AI assistance in the way an MRMC study evaluates.

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

    • Not Applicable. This refers to the standalone performance of an algorithm. The InnoPort™ is a physical surgical device. Its "standalone performance" refers to its mechanical and functional integrity in isolation, which was assessed through bench testing and its in vivo behavior, but not as an algorithm.

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

    • Not explicitly stated in these terms, but inferred: For a physical medical device like this, the "ground truth" for its performance would implicitly be defined by engineering specifications, material standards, biocompatibility requirements, recognized surgical practices, and the functional capabilities demonstrated by the predicate device. The in vivo tests would assess real-world functionality and safety. The performance is compared to the predicate device's established safety and effectiveness profile.

    8. The sample size for the training set:

    • Not Applicable. This concept applies to machine learning models. This device is a physical product, not an AI algorithm, so there is no "training set."

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

    • Not Applicable. There is no training set for this type of device.
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