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510(k) Data Aggregation

    K Number
    DEN140025
    Date Cleared
    2014-11-17

    (89 days)

    Product Code
    Regulation Number
    882.1450
    Type
    Direct
    Reference & Predicate Devices
    N/A
    Why did this record match?
    Device Name :

    BrainScope Ahead 100

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

    The Ahead® 100, consisting of two models, i.e., the Ahead® M-100 and the Ahead® CV-100, is indicated for use as an adjunct to standard clinical practice to aid in the evaluation of patients who are being considered for a head CT, but should not be used as a substitute for a CT scan. This device is to be used for this purpose in patients who sustained a closed head injury within 24 hours, clinically present as a mild traumatic brain injury with a Glasgow Coma Scale score (GCS) of 13-15, and are between the ages of 18-80 years.

    A negative BrainScope® Classification may correspond to brain electrical activity consistent with no structural brain injury visible on head CT in patients presenting as a mild traumatic brain injury, within 24 hours of injury.
    A positive BrainScope® Classification corresponds to brain electrical activity that may be present in both patients with or without a structural brain injury visible on head CT. A positive BrainScope® Classification does not establish the presence of a structural brain injury visible on head CT.
    The Ahead® 100 device is intended to record, measure, analyze, and display brain electrical activity utilizing the calculation of standard quantitative EEG (qEEG) parameters from frontal locations on a patient's forehead. The Ahead® 100 calculates and displays raw measures for the following standard qEEG measures: Absolute and Relative Power, Asymmetry, Coherence and Fractal Dimension. These raw measures are intended to be used for post hoc analysis of EEG signals for interpretation by a qualified user.
    The Ahead® M-100 model additionally stores and displays an electronic version of the Military Acute Concussion Evaluation (MACE) cognitive assessment and user-entered responses to the MACE questions. There is no interaction between EEG-related functionality, including analyzing and displaying brain electrical activity, and the function of storing and displaying MACE information.
    The Ahead® 100 is intended for use by physicians, or under the direction of a physician, who have been trained in the use of the device.
    The Ahead® 100 is a prescription use device.

    Device Description

    The Ahead 100 is a portable EEG system consisting of two models: the Ahead M-100 and the Ahead CV-100. As stated in the Indications for Use above, the only functional difference between the M-100 model and the CV-100 model is that the M-100 stores and displays an electronic version of the Military Acute Concussion (MACE) cognitive assessment and user-entered responses to the MACE questions in addition to all other device functionality as discussed below.

    The Ahead 100 device is comprised of the following main components:

    1. The Ahead 100 Handheld Unit
    2. The Electrode Headset
    3. The Patient Interface Cable
    4. The Compact Flash Card (CF Card)

    The Handheld Unit, Patient Interface Cable, and Electrode Headset interface together to facilitate the collection of EEG data from the patient. The Electrode Headset includes 8 wet gel electrodes integrated into a single use, disposable headset that allows for electrode placement over the following frontal locations: Fp1, Fp2, Fpz, AFz, F7, F8, A1, and A2 as defined by the standardized International 10-20 Electrode Placement System. The Patient Interface Cable connects the Electrode Headset to the Handheld Unit and contains a preamplifier that prepares the electrical signals measured by the Electrode Headset for processing by the Handheld Unit.

    The Handheld Unit employs a color, touch-screen user interface and utilizes proprietary software to perform real-time analyses of the collected EEG data. Using the Handheld Unit, the user is able to review the raw EEG data, view spectral plots, and view a number of calculated quantitative EEG (qEEG) measures including Absolute and Relative Power, Asymmetry, Coherence and Fractal Dimension.

    The software utilized by the Handheld Unit also processes the collected raw EEG to produce the final Ahead 100 classification. This data analysis includes filtering the raw EEG, performing artifact reduction, computation of a variety of qEEG features across specific frequency bands, normalization of these computed features, a quality check to identify potential outliers, integration of these features to determine the appropriate classification, and finally a graphical display of this classification to the user. The algorithm used to integrate the computed features and determine a classification was pre-established in a separate study, prior to validation in the B-AHEAD II study.

    The Ahead 100 device provides one of two potential classifications of the patient's recorded EEG data:

    1. "May correspond to brain electrical activity consistent with no structural brain injury visible on head CT in patients presenting as a mild traumatic brain injury, within 24 hours of injury." or,
    2. "Corresponds to brain electrical activity that may be present in both patients with or without a structural brain injury visible on head CT. A positive result does not establish the presence of a structural brain injury visible on head CT."
    AI/ML Overview

    Acceptance Criteria and Device Performance for BrainScope AHEAD 100

    1. Table of Acceptance Criteria and Reported Device Performance

    Performance MetricAcceptance Criteria (Lower one-sided 95% CI)Reported Device Performance (Estimate)95% Confidence IntervalResult
    Sensitivity> 78%78.5% (91/116)(69.9%, 85.5%)Met
    Specificity> 50%48.6% (212/436)(43.8%, 53.4%)Not Met

    Note: The clinical study "failed to meet the predefined primary endpoints" for specificity, though sensitivity was met.

    2. Sample Size and Data Provenance for the Test Set

    • Sample Size (Test Set): 552 subjects were included in the analysis of diagnostic accuracy per the intended use.
    • Data Provenance: The study was a prospective, controlled, non-randomized, pivotal study conducted at 11 study sites in the US.

    3. Number and Qualifications of Experts for Ground Truth

    • Number of Experts: 3 blinded neuroradiologists.
    • Qualifications of Experts: Neuroradiologists (specific years of experience not mentioned).

    4. Adjudication Method for the Test Set

    • The final head CT readings were reviewed by a panel of 3 blinded neuroradiologists, and classification was determined by a majority of the panel. This implies a 3-reader consensus method, likely 2+1 or 3-reader agreement.

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

    • It is not explicitly stated that a Human-in-the-Loop MRMC comparative effectiveness study was done to measure human reader improvement with AI assistance. The study focuses on the standalone performance of the device against clinical classification (CT findings). The device is intended as an adjunct to standard clinical practice, suggesting it would be used by physicians, but the study design described does not quantify the improvement of human readers using the AI.

    6. Standalone (Algorithm Only) Performance

    • Yes, a standalone performance study was done. The provided acceptance criteria and performance results (sensitivity, specificity, PPV, NPV) are for the "Ahead 100 classification," which is the algorithm's output. The study design states, "All treating physicians were to be blinded to the output of the Ahead 100 device," indicating the device's output was assessed independently.

    7. Type of Ground Truth Used

    • The primary ground truth used was structural brain injury on CT scan (CT+), as determined by a panel of 3 blinded neuroradiologists.
    • For subjects with GCS=15, the New Orleans Criteria (NOC) was used for truth assessment if a CT was not performed. If a CT was performed for such subjects, the CT results were used.

    8. Sample Size for the Training Set

    • The document states, "The algorithm used to integrate the computed features and determine a classification was pre-established in a separate study, prior to validation in the B-AHEAD II study." However, the sample size for this "separate study" (training set) is not provided in the given text.

    9. How Ground Truth for the Training Set Was Established

    • The document implies that an algorithm was developed and established prior to the pivotal B-AHEAD II study. However, how the ground truth for this separate study (training set) was established is not detailed in the provided text. It would likely have involved similar methods to the validation study (e.g., expert-adjudicated CT scans), but this is not explicitly stated.
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