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510(k) Data Aggregation

    K Number
    K201969
    Date Cleared
    2021-02-25

    (225 days)

    Product Code
    Regulation Number
    892.1550
    Reference & Predicate Devices
    Why did this record match?
    Device Name :

    SonoEye P6/ SonoEye V6/ SonoEye G6 Digital Color Doppler Palm Ultrasound System

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

    The Digital Color Doppler Palm Ultrasound System is intended for diagnostic ultrasound imaging in B (2D), B/M, CFM, Combined(B+CFM), Pulsed Wave and Fusion Harmonic Imaging modes. It is indicated for Cardiac, Abdomen. The Digital Color Doppler Palm Ultrasound System is intended for use in environments where healthcare is provided by healthcare professionals.

    Device Description

    The SonoEye P6/SonoEye V6/SonoEye G6 Digital Color Doppler Palm Ultrasound System is a mobile, general purpose, softwarecontrolled, diagnostic ultrasound system. Its function is to acquire ultrasound data and to display the data in various modes of operation. The SonoEye P6/SonoEye V6/SonoEye G6 is a portable system facilitating point of care ultrasound applications. The Digital Color Doppler Palm Ultrasound System includes: - A commercial off-the-shelf (COTS) Android mobile device. - CHISON Ultrasound software is running as an app (Android) on the COTS device. - The SonoEye P6/SonoEye V6/SonoEye G6 support Convex array transducer.

    AI/ML Overview

    This is a 510(k) summary for a medical device (SonoEye P6/SonoEye V6/SonoEye G6 Digital Color Doppler Palm Ultrasound System) and does not contain information about acceptance criteria or a study that specifically proves the device meets those criteria in the way typically found for an AI/ML medical device.

    The document focuses on demonstrating substantial equivalence to existing predicate devices rather than proving performance against specific acceptance criteria for a novel AI function. As such, many of the requested fields cannot be filled.

    Here's an attempt to answer the questions based only on the provided text, highlighting what is not available:


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

    The document does not present a table of specific quantitative acceptance criteria or reported performance for the SonoEye P6/SonoEye V6/SonoEye G6 Digital Color Doppler Palm Ultrasound System in terms of diagnostic accuracy (e.g., sensitivity, specificity for detecting particular conditions). Instead, it establishes substantial equivalence by comparing its features and compliance with safety standards to predicate devices.

    The comparisons provided are primarily focused on:

    • Indications for Use: The submitted device has a more limited set of indications (Cardiac, Abdomen) compared to the predicate devices, but these are "Same" as a subset of the predicate's indications.
    • Design and Operating Controls: Features like color processing, Doppler processing, probe types, cine playback, image archiving, gain, focus, ROI adjustment, freeze control, and operation modes are largely deemed "Same" or comparable in design. Differences in value ranges for depth and power requirements are noted but considered substantially equivalent due to compliance with relevant electrical and medical standards.
    • Safety Compliance: The device conforms to the same international safety standards (ANSI/AAMI ES60601-1, IEC 60601-1, IEC 60601-2-37, IEC 60601-1-2, ISO 10993-1) as the predicate devices.
    • Acoustic Output: All devices are Track 3 and have similar maximum ISPTA.3 (≤ 720 mW/cm²) and MI (≤ 1.9), and TI (≤ 6.0 in the submission device's case, continuously displayed for one predicate, but generally aligned within safety limits).

    Since this is a substantial equivalence submission for a diagnostic ultrasound system (not an AI/ML algorithm with specific diagnostic performance tasks), direct quantitative "acceptance criteria" for diagnostic accuracy are not presented in this document. The "acceptance criteria" are implicitly the demonstration that the device's characteristics and performance are comparable to (substantially equivalent to) legally marketed predicate devices, particularly concerning safety and effectiveness according to established standards.

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

    Not applicable. The document explicitly states: "No clinical testing was required." Therefore, there is no test set for clinical performance mentioned. The "tests" performed were non-clinical (electrical, mechanical, thermal, electromagnetic compatibility, biocompatibility, and acoustic output).

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

    Not applicable, as no clinical testing was performed for this submission.

    4. Adjudication method for the test set

    Not applicable, as no clinical testing was performed for this submission.

    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 Digital Color Doppler Palm Ultrasound System, not an AI-assisted diagnostic tool in the sense of an AI/ML algorithm for image interpretation that would enhance human reader performance. No MRMC study or AI assistance effect size is mentioned.

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

    Not applicable. This device is a diagnostic ultrasound system, which inherently involves a human operator acquiring and interpreting images. It is not an "algorithm only" device within the context of AI/ML performance.

    7. The type of ground truth used

    Not applicable, as no clinical testing for diagnostic performance was conducted. The "ground truth" referenced in the provided text relates to compliance with engineering and safety standards, where the "truth" is whether the device meets the specified technical and safety requirements.

    8. The sample size for the training set

    Not applicable. This document does not describe the development or training of an AI/ML algorithm.

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

    Not applicable. This document does not describe the development or training of an AI/ML algorithm.

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