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510(k) Data Aggregation

    K Number
    K102047
    Manufacturer
    Date Cleared
    2011-11-01

    (468 days)

    Product Code
    Regulation Number
    868.1880
    Reference & Predicate Devices
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    Device Name :

    LCI OPTION FOR INNOCOR

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

    The LCI Option for Innocor is intended to measure the Lung Clearance Index (LCI), which is the cumulative expired volume required to clear an inert gas from the lungs during normal breathing in a multiple-breath washout (MBW) test divided by the Functional Residual Capacity (FRC).

    Device Description

    Innocor is a compact point-of-care device intended to be used for non-invasive measurement of a) cardiac output (CO) and other hemodynamic parameters utilizing inert gas rebreathing (IGR) technology, b) metabolic parameters including oxygen uptake by means of a breath-by-breath gas exchange method, c) spirometry parameters by means of forced respiratory maneuvers, and d) peripheral airway function by means of multiple-breath inert gas washout.

    The basic Innocor provides cardiac output (CO) as the principal measured parameter. Utilizing inert gas rebreathing, Innocor measures the relative levels of two inhaled gases of differing blood solubility over approximately 3-4 respirations. The disappearance curve for the blood soluble gas is used to calculate pulmonary blood flow (PBF), which in the absence of a significant intrapulmonary shunt is equal to cardiac output. The functional residual capacity (FRC) is determined from the dilution of the relatively insoluble gas during the same maneuver.

    The LCI Option for Innocor, used alone or in conjunction with the entire Innocor system, provides information on lung volume and peripheral airway function.

    The LCI is calculated as the cumulative expired volume (VcE) required to clear the inert tracer gas from the lungs during normal breathing, minus the product of the number of wash-out breaths and the external dead space outside the lips. divided by the subject's Functional Residual Capacity (FRC). FRC is the amount of air that stays in the lungs (up to the lips) after a normal expiration. In other words, LCI represents the number of lung volume turnovers (i.e. FRCs) that the subject must breathe to clear the inert tracer gas from the lungs (by convention, to an end-tidal concentration of 1/40th of the starting concentration over three subsequent breaths).

    Innocor uses a combination of two techniques to determine the LCI, using SF6 as the inert tracer gas:

    Inert gas rebreathing (IGR) is used for rapid wash-in of a very small amount of SF% until an even concentration is obtained in the lungs before the wash-out can start. This allows accurate determination of the functional residual capacity (FRC) by gas analysis alone.

    This is followed by multiple-breath wash-out (MBW) for determination of the cumulative expired volume (VCF) required to clear the SF6 from the lungs. The Innocor device is a compact and portable point-of-care device. The hardware in the LCI Option for Innocor is identical to that used in the Innocor Diagnostic Programmable Computer (K051907) and the Cardiopulmonary Exercise Testing Option to Innocor (K071911). The combined rebreathing/multiple breath wash-out test performed with the LCI Option for Innocor requires accurate measurements of the respiratory flow and the concentration of SF6 at the mouth during inspiration (inhalation) and expiration (exhalation). The Innocor device measures the flow and SF6 concentration by means of of a pneumotachometer and a photoacoustic infrared gas analyzer, respectively, while the patient takes multiple breaths over a period of time through a pneumatically activated respiratory valve unit (RVU). The rebreathing gas mixture for wash-in of SF6 is filled into a rubber bag prior to testing.

    AI/ML Overview

    Here's an analysis of the acceptance criteria and study information for the LCI Option for Innocor, based on the provided text:

    1. Table of Acceptance Criteria and Reported Device Performance

    The document does not explicitly state numerical acceptance criteria for LCI or FRC measurements, nor does it present a direct comparison of the device's performance against such criteria. Instead, the performance evaluation is framed as demonstrating "substantial equivalence" to predicate devices and adherence to relevant guidelines.

    The performance data described focuses on:

    • FRC determination: Evaluated against a calibration syringe.
    • LCI determination: Evaluated using data from a simulation model.

    The summary states: "Performance data demonstrates that the hardware and software of the LCI Option for Innocor is as safe, as effective, and performs as well as or better than the predicate devices and thus that the device is substantially equivalent to the predicate devices."

    Since specific numerical acceptance criteria and a detailed breakdown of the device's measured performance against them are not provided, I cannot create a table with specific numbers. The document relies on a qualitative statement of substantial equivalence.

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

    • Sample Size: The document does not specify a sample size for the test set. It mentions evaluation against a "calibration syringe" for FRC and "data from simulation" for LCI. This implies bench testing rather than human subject testing for primary performance evaluation for equivalence.
    • Data Provenance: The data provenance is from "bench testing" using a "calibration syringe" and "simulation." This suggests laboratory-based data, not human patient data, and therefore no country of origin or retrospective/prospective designation in the conventional sense for clinical studies.

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

    There is no mention of experts being used to establish ground truth for the test set. The ground truth for FRC assessment appears to be the known volume of the calibration syringe, and for LCI, it's derived from a simulation model. This is typical for bench testing where the 'ground truth' is a controlled, known quantity.

    4. Adjudication Method for the Test Set

    No adjudication method is mentioned or relevant, as the testing described is bench testing against known physical or simulated values, not human expert interpretation.

    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

    • No MRMC comparative effectiveness study was done.
    • This device is a measurement instrument for physiological parameters (LCI, FRC), not an AI-assisted diagnostic tool that would involve human readers or AI assistance for interpretation. Therefore, human reader improvement with/without AI assistance is not applicable.

    6. If a Standalone (i.e., algorithm only without human-in-the-loop performance) Was Done

    Yes, a standalone performance evaluation was done. The device, which functions as a "Pulmonary function data calculator," directly measures and calculates LCI and FRC. Its performance was evaluated on its own ("against a calibration syringe for FRC determination and data from simulation for LCI determination") without human operators interpreting results to determine its accuracy. The "software is different from previous models," indicating that the algorithm's performance is primary.

    7. The Type of Ground Truth Used

    • FRC: Calibration syringe (known, controlled volume).
    • LCI: Data from a simulation model.

    8. The Sample Size for the Training Set

    The document does not mention a training set sample size. This is consistent with a device that is essentially a physiological measurement calculator, where the calculations are based on established scientific principles rather than a machine learning model that requires a "training set" in the typical sense. The "software is different from previous models" but this likely refers to implemented algorithms for calculation, not machine learning.

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

    As no training set is mentioned in the context of machine learning, there is no discussion of how ground truth for a training set was established.

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