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510(k) Data Aggregation

    K Number
    K954028
    Date Cleared
    1996-08-08

    (346 days)

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

    HP SONOS ULTRASOUND IMAGING SYSTEM

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

    This modification has no effect on intended use of the HP ultrasound systems.

    Device Description

    The modification addressed in this submission is a change from analog to digital circuit technology for the front end of the HP ultrasound imaging systems listed above.

    AI/ML Overview

    This document is a 510(k) summary for a modification to an existing ultrasound imaging system. It focuses on demonstrating substantial equivalence to predicate devices for a change from analog to digital circuit technology in the front end. Therefore, it does not contain the detailed performance study information typically found in submissions for novel devices or those requiring clinical efficacy studies with specific acceptance criteria.

    Based on the provided text, here's what can be extracted and what cannot:

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

    The document does not provide a table of acceptance criteria and reported device performance in the way typically expected for a new device's clinical performance. Since this is a modification to an existing device, the "acceptance criteria" discussed are primarily related to safety, compliance with medical device standards, and functional equivalence to predicate devices.

    Acceptance CriteriaReported Device Performance
    Compliance to medical device safety standards (e.g., IEC 601, UL 2601)Stated as "shown by compliance"
    Software safety verified by hazard analysis and software validationStated as "verified by hazard analysis and software validation to ensure performance specifications are met"
    Performance specifications metStated as "ensure performance specifications are met"
    Substantial equivalence to legally marketed predicate devices (ATL HDI 3000, Toshiba SSA-380A) regarding safety, effectiveness, and intended useStated as "demonstrate that the modified HP ultrasound imaging systems are substantially equivalent to legally marketed predicate devices"

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

    Not applicable. This submission is for a technological modification and primarily relies on engineering validation, safety testing, and comparison to predicate devices, not a clinical "test set" with a specific sample size of patient data. There is no mention of patient data being used for this specific filing.

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

    Not applicable. Ground truth for a clinical test set is not discussed as this is a technological modification submission.

    4. Adjudication method for the test set

    Not applicable. There is no mention of a clinical test set or 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 document pertains to an ultrasound imaging system and does not mention AI or MRMC studies.

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

    Not applicable. This is not an algorithm-only device; it's a hardware modification to an imaging system.

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

    Not applicable. Ground truth in the context of clinical data is not discussed. For this submission, the "ground truth" for the claims of safety and equivalence would be the established safety standards, the validated performance specifications of the device, and the characteristics of the predicate devices.

    8. The sample size for the training set

    Not applicable. There is no mention of a training set as this is not a machine learning or AI-driven device.

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

    Not applicable (as above).

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