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510(k) Data Aggregation

    K Number
    K102366
    Device Name
    FINESS ENDOSCOPE
    Date Cleared
    2011-02-15

    (179 days)

    Product Code
    Regulation Number
    874.4760
    Reference & Predicate Devices
    Why did this record match?
    Device Name :

    FINESS ENDOSCOPE

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

    The FinESS Endoscope is intended to provide a means to visualize the maxillary sinus cavity and deliver the FinESS balloon dilation catheter to treat the maxillary sinus ostium and the ethmoid infundibulum in adults with a trans-antral approach. The endoscope is part of the FinESS Sinus Treatment and is inserted via a sterile access sheath through the canine fossa.

    Device Description

    The FinESS Endoscope is a fiber optic based, manually operated, reusable rigid antroscope designed for performing the FinESS Sinus Treatment procedure. It is short, all metal and fully immersible. It is labeled non-sterile and must be cleaned and disinfected or sterilized prior to use. The endoscope is compatible with standard "B" mount camera couplers, and comes with two light post adapters, which allows the endoscope to be compatible with most commonly used light guides. The endoscope also has a working channel that allows for delivery of the FinESS balloon dilation catheter to treat the maxillary ostium and ethmoid infundibulum. The FinESS Endoscope is part of and used with the FinESS Sinus Treatment [K081542] and insertion of the endoscope is performed using a sterile access sheath [K091681].

    AI/ML Overview

    Based on the provided text, the FinESS Endoscope is a medical device that received 510(k) clearance. This means it demonstrated substantial equivalence to a legally marketed predicate device, rather than undergoing a de novo approval process that would typically involve establishing novel acceptance criteria and extensive standalone performance studies for an entirely new device.

    Therefore, the structure of the provided content focuses on showing equivalence rather than proving a device meets predefined acceptance criteria for novel performance claims.

    Here's an analysis of the provided information, noting what is present and what is absent regarding acceptance criteria and study details for AI/ML devices:

    1. Table of Acceptance Criteria and Reported Device Performance

    The submission does not define specific acceptance criteria in terms of numerical performance metrics (e.g., sensitivity, specificity, accuracy) that an AI/ML device would typically be evaluated against. Since this is a traditional medical device (an endoscope) and not an AI/ML device, its performance is assessed against design specifications and intended function rather than diagnostic or analytical performance metrics.

    The "Performance Data" section states: "The testing showed that the device meets design specifications and performs as intended." This is the highest level of detail provided regarding performance.

    2. Sample Size Used for the Test Set and Data Provenance

    • Test Set Sample Size: Not applicable in the context of an AI/ML diagnostic or predictive model. The performance tests mentioned are related to engineering and usability aspects of the endoscope itself.
    • Data Provenance: Not applicable. The "cadaver studies" mentioned are for testing physical performance and usability, not for training or testing an AI model on patient data.

    3. Number of Experts Used to Establish Ground Truth for the Test Set and Qualifications

    Not applicable. "Ground truth" in the AI/ML sense (e.g., expert consensus on image labels) is not relevant for this type of traditional device submission. The verification of design specifications would involve engineers and quality assurance personnel.

    4. Adjudication Method for the Test Set

    Not applicable. There is no concept of adjudication (e.g., 2+1, 3+1) as there are no diagnostic or interpretive outputs being evaluated from the device that would require human expert consensus.

    5. Multi Reader Multi Case (MRMC) Comparative Effectiveness Study

    No. This type of study is not mentioned because it is designed to evaluate human reader performance with and without AI assistance, which is irrelevant for a rigid endoscope.

    6. Standalone Performance Study

    Yes, in a sense, a "standalone" assessment of the device's physical and functional performance was conducted. The "Performance Data" section details various tests that were performed on the device itself to ensure it functions as designed and intended. These include:

    • Biocompatibility testing
    • Dimensional verification
    • Cadaver studies (for physical use and visualization)
    • Manual cleaning validation (utilizing total organic carbon as study endpoint)
    • Manual high level disinfection validation
    • Sterilization validation of STERRAD NX system (per ISO 14937)
    • Compatibility testing
    • Storage and transportation testing

    7. Type of Ground Truth Used

    The ground truth for this device's performance is its adherence to design specifications, industry standards, and regulatory requirements for medical devices (e.g., biocompatibility standards, sterilization efficacy, dimensional accuracy).

    8. Sample Size for the Training Set

    Not applicable. As a traditional medical device, there is no "training set" in the context of machine learning. The device's design is based on engineering principles and predicate device experience, not iterative learning from data.

    9. How the Ground Truth for the Training Set Was Established

    Not applicable.

    Summary of Device Performance Study as Described:

    The study conducted for the FinESS Endoscope was a series of engineering and validation tests demonstrating that the device meets its design specifications and performs its mechanical and functional tasks as intended, particularly in terms of visualization, accessory delivery, and reprocessing. It showed substantial equivalence to its predicate device based on these performance characteristics, ensuring it maintains the same safety and effectiveness profile. No AI/ML components are involved, and thus, typical AI/ML evaluation metrics, studies, and data provenance requirements are not relevant.

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    K Number
    K103213
    Date Cleared
    2011-02-02

    (93 days)

    Product Code
    Regulation Number
    880.6850
    Reference & Predicate Devices
    Why did this record match?
    Device Name :

    FINESS ENDOSCOPE STERILIZATION TRAY

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

    The FinESS Endoscope Sterilization Tray is intended for use to encase and protect the FinESS Endoscope for sterilization in STERRAD 100NX using the standard cycle setting and NX Sterilization Systems using the advanced cycle setting.

    • The sterilization cycle parameters of the STERRAD sterilizers are preset by the manufacturer and are not adjustable.
    • The maximum product load per FinESS Endoscope Sterilization Tray includes 1 FinESS Endoscope and 2 light post adapters.
      The FinESS Endoscope Sterilization Tray is intended to be used with legally marketed, FDA-cleared STERRAD compatible sterilization wrap in order to maintain sterility of the enclosed endoscope.
    Device Description

    The FinESS Endoscope Sterilization Tray is comprised of a bottom, a clear lid, and silicone inserts designed to secure the FinESS Endoscope in place. The lid is clear and secured to the tray with a snap fit mechanism. The FinESS Endoscope Sterilization Tray contains perforations in the base and lid to allow the sterilant to penetrate. The use of commercially available sterilization wrap allows the tray to maintain sterility after sterilization.

    AI/ML Overview

    The FinESS Endoscope Sterilization Tray (K103213) is intended to encase and protect the FinESS Endoscope for sterilization.

    1. Acceptance Criteria and Reported Device Performance:

    Test TypeAcceptance CriteriaReported Device Performance
    Design VerificationDevice and material stability following repeated exposure to sterilization cycles.All results met the acceptance criteria.
    BiocompatibilityAcceptable primary dermal irritation and dermal sensitization post exposure to multiple sterilization cycles.All results met the acceptance criteria.
    Sterilization Efficacy (SAL)An SAL (Sterility Assurance Level) of 10⁻⁶ could be achieved with STERRAD NX and 100NX systems.Achieved an SAL of 10⁻⁶ when used with the STERRAD NX and STERRAD 100NX sterilization systems. Sterilization testing of inoculated FinESS Endoscope Sterilization Tray and similarly inoculated Predicate tray showed that both devices are capable of allowing SAL of 10⁶.

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

    The document does not explicitly state a specific sample size for each test (design verification, biocompatibility, sterilization efficacy).
    The data provenance is not specified (e.g., country of origin, retrospective or prospective), but given the context of a 510(k) submission, it would be laboratory-generated data from the manufacturer (Entellus Medical, Inc.).

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

    This information is not explicitly provided. For sterilization efficacy, ground truth (SAL of 10⁻⁶) is typically established through standardized microbiological testing methods, often performed by trained microbiologists or specialists in sterilization science within a testing laboratory.

    4. Adjudication method for the test set:

    Not applicable. The performance testing involves objective measures (e.g., material integrity, microbiological kill rates) rather than human interpretation requiring adjudication.

    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 a sterilization tray and does not involve AI or human "readers" or diagnostic interpretations.

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

    Not applicable. This device is a physical medical device (sterilization tray), not an algorithm or AI system.

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

    The ground truth for the performance testing included:

    • Design Verification: Established standards for material stability and device integrity after sterilization cycles.
    • Biocompatibility: Established toxicological and irritation thresholds in accordance with relevant standards (e.g., ISO 10993 series).
    • Sterilization Efficacy: A Sterility Assurance Level (SAL) of 10⁻⁶, which is a universally accepted standard for sterilization, demonstrating a one in a million chance of a non-sterile unit. This is determined through biological indicator testing and D-value calculations.

    8. The sample size for the training set:

    Not applicable. This device is a physical medical device, and the testing described is performance validation, not machine learning model training.

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

    Not applicable. There is no training set involved as this is not a machine learning or AI device.

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