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510(k) Data Aggregation

    K Number
    K072286
    Date Cleared
    2007-11-20

    (96 days)

    Product Code
    Regulation Number
    882.1400
    Reference & Predicate Devices
    Why did this record match?
    Device Name :

    BIS EEG VISTA MONITOR SYSTEM AND BISX

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

    A. Indications for use for BIS EEG Monitor System (VISTA Monitor and BISx4): The BIS EEG VISTA Monitor System is intended for use under the direct supervision of a licensed healthcare practitioner or by personnel trained in their proper use. The system, and all its associated parameters, is intended for use on adult and pediatric patients within a hospital or medical facility providing patient care to monitor the state of the brain by data acquisition of EEG signals. The BIS Index, one of the VISTA Monitor output parameters, may be used as an aid in monitoring the effects of certain anesthetic agents; and its usage with certain anesthetic agents may be associated with a reduction in primary anesthetic use and a reduction in emergence and recovery time. Use of the BIS Index for monitoring to help guide anesthetic administration may be associated with the reduction of incidence of awareness with recall in adults during general anesthesia and sedation. B. Indications for use for BISx device: The BISx is intended for use under the direct supervision of a licensed healthcare practitioner or by personnel trained in their proper use. The BISx, and all its associated parameters, is intended for use on adult and pediatric patients within a hospital or medical facility providing patient care to monitor the state of the brain by data acquisition of EEG signals. The BIS Index, one of the BISx output parameters, may be used as an aid in monitoring the effects of certain anesthetic agents; and its usage with certain anesthetic agents may be associated with a reduction in primary anesthetic use and a reduction in emergence and recovery time. Use of the BIS Index for monitoring to help guide anesthetic administration may be associated with the reduction of incidence of awareness with recall in adults during general anesthesia and sedation.

    Device Description

    A. BIS EEG VISTA Monitor System: The BIS EEG VISTA Monitor System, is comprised of the BISx4, the VISTA Monitor, and associated cables. When the System is connected to a BIS Sensor (which is applied to the patient's forehead, acquires EEG signals from the brain, and is 510(k) cleared) the monitor displays 2 channels of EEG. When the System is connected to a BIS Bilateral Sensor (also 510(k) cleared), the monitor displays 4 channels of EEG. The BISx4 houses the digital signal converter as well as the BIS algorithm (it has no display or user interface), and it performs the computations necessary to produce the Bispectral Index (BIS). It also calculates SQI, EMG, Burst count and Suppression Ratio. The BISx4 may be distributed to business partners that have the ability to display BIS on their patient monitors. The Monitor displays a maximum of 4 channels of EEG, as well as SQI, EMG, Burst Count, Suppression Ratio and a BIS value. The BIS value is acquired using 2 channels of EEG. The Monitor has secondary trend and trend review screens, as well as results of self tests. In addition to the above, when connected to a Bilateral Sensor, the System provides additional capability as follows: BISx4 calculates DSA, Asymmetry, sBIS, and sEMG. The Monitor displays DSA, Asymmetry, sBIS, and sEMG numerically and graphically. B. BISx device: The BISx is a component that processes up to 2 channels of EEG and computes BIS and other EEG parameters (same as the cleared BISx device). The BISx connects to Aspect sensors on one side and the Aspect Monitor or OEM patient monitoring systems on the other, allowing them to display BIS on their integrated patient monitoring systems. The OEMs are responsible for the regulatory pathway to integrate the BISx in their systems. The software is a moderate level of concern. This submission is updating the indications for use statement for the BISx device, to reflect the addition of clinical benefits added at FDA request to the BIS EEG VIEW Monitor, 510(k) (K#062613, recently cleared on 6/18/07). No change is being made to the cleared BISx device (#K040183).

    AI/ML Overview

    The provided text does not contain detailed information about specific acceptance criteria, device performance metrics, or a study that rigorously proves the device meets those criteria in a quantitative sense suitable for a table. The submission is a 510(k) summary, which focuses on substantial equivalence to predicate devices rather than independent performance validation against predefined clinical acceptance criteria.

    The "Summary of Testing" section (in {3}) states: "The following tests/analyses have been completed for the BIS EEG VISTA Monitor System: Software Validation, Hazard Analysis and Risk Assessment. Results indicate the device meets its performance specifications and validation test requirements, and is safe for its intended use."

    This statement confirms that internal tests were conducted to ensure the device performs as intended and is safe, but it does not provide details on:

    • Specific performance specifications or acceptance criteria.
    • Quantitative results from these tests.
    • Methodology of how these criteria were established or evaluated.
    • Any clinical study (e.g., MRMC, standalone) involving human readers or a comparison against a clinical ground truth.

    Therefore, I cannot provide the requested table or detailed study information based on the given text.

    Here's an assessment of the other requested points based on the provided document:

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

      • Not provided in the document. The document states "Results indicate the device meets its performance specifications and validation test requirements," but does not list these specifications or the corresponding performance outcomes.
    2. Sample size used for the test set and the data provenance:

      • Not provided in the document. The document mentions "Software Validation" and "Hazard Analysis and Risk Assessment" as completed tests, but does not specify any test set size or data provenance for these. This typically implies internal engineering and software testing rather than a clinical trial with patient data.
    3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts:

      • Not provided in the document. Since no clinical test set is detailed, information about experts and ground truth establishment is absent.
    4. Adjudication method (e.g., 2+1, 3+1, none) for the test set:

      • Not applicable/Not provided. No clinical test set or adjudication process is described.
    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, an MRMC study was not described. The document focuses on substantial equivalence and safety/performance specifications, not on comparative effectiveness with human readers.
    6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done:

      • Implied, but details not provided. The BISx4 and BISx calculate the Bispectral Index (BIS) and other parameters algorithmically. The "Software Validation" mentioned implies testing of this algorithm's performance against its specifications, which is a form of standalone testing. However, no specific metrics, methods, or results of this standalone performance are given beyond a general statement of meeting specifications.
    7. The type of ground truth used (expert consensus, pathology, outcomes data, etc.):

      • Not provided in the document. Without details on specific performance tests, the type of ground truth used to validate the algorithms (e.g., against reference EEG signals or clinically established states of anesthesia) is not mentioned.
    8. The sample size for the training set:

      • Not applicable/Not provided. This device calculates physiological parameters based on established algorithms (e.g., for EEG signal processing, Bispectral Index). It's unlikely to be a machine learning model that requires a distinct "training set" in the modern sense. The algorithms are likely fixed based on biomedical engineering principles and prior research.
    9. How the ground truth for the training set was established:

      • Not applicable/Not provided. (See point 8).
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