Search Filters

Search Results

Found 1 results

510(k) Data Aggregation

    K Number
    K133034
    Device Name
    LOGIQ F SERIES
    Manufacturer
    Date Cleared
    2014-01-31

    (127 days)

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

    LOGIQ F SERIES

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

    The LOGIQ F SERIES are general purposed ultrasound imaging and analysis systems providing digital acquisition, processing and display capability, clinical applications including: Abdominal. Obstetrical. Gynecological, Small parts, Vascular/Peripheral Vascular, Transcranial. Pediatric, Musculoskeletal. Urological, Cardiac, Transvaginal

    Device Description

    The LOGIQ F Series is the full featured general purpose diagnostic ultrasound system which consists of a mobile console (Approximately 72 cm wide. 80 cm deep and 145 cm high) that provides digital acquisition, processing and display capability. The user interface includes a computer keyboard, color LCD image display and touch panel.

    AI/ML Overview

    The provided text is a 510(k) Premarket Notification Submission for the GE Healthcare LOGIQ F Series ultrasound system. It primarily focuses on demonstrating substantial equivalence to predicate devices, referencing safety and performance standards, and outlining intended uses.

    Based on the provided document, here's an analysis of the acceptance criteria and study information:

    Description of Acceptance Criteria and Study to Prove Device Meets Criteria

    1. Table of Acceptance Criteria and Reported Device Performance

    The document does not explicitly present a table of acceptance criteria with corresponding device performance metrics in the way one might see for a diagnostic AI algorithm (e.g., sensitivity, specificity thresholds). Instead, the "acceptance criteria" are implied by adherence to recognized medical device safety standards and by demonstrating substantial equivalence to previously cleared predicate devices.

    The reported device performance, therefore, is primarily in terms of compliance and substantial equivalence:

    Acceptance Criterion (Implied)Reported Device Performance
    Safety: Acoustic output within FDA limits, biocompatibility."The systems have acoustic power levels which are below the applicable FDA limits."
    "The systems are manufactured with materials which have been evaluated and found to be safe for the intended use of the device."
    "Transducer material and other patient contact materials such as needle guidance kits are biocompatible."
    Electrical and Physical Safety: Compliance with standards."The LOGIQ F SERIES has been evaluated for acoustic output, biocompatibility, cleaning and disinfection effectiveness as well as thermal, electrical, electromagnetic, and mechanical safety, and have been found to conform with applicable medical device safety standards."
    "The LOGIQ F Series and predicate systems have been designed in compliance with approved electrical and physical safety standards." (References: AAMI/ANSI ES60601-1, IEC60601-1-2, IEC60601-2-37)
    Performance: Similar imaging capabilities and technological characteristics to predicate devices."The LOGIQ F Series and predicate systems have similar clinical intended use and similar imaging modes."
    "The LOGIQ F SERIES employs the same fundamental scientific technology as its predicate devices."
    Some specific features like Elastography, TVI/TVD, Auto IMT, and Quantitative Analysis are noted as "previously cleared on the LOGIQ S8 (K131527)."
    Risk Management: Application of risk management processes."The following quality assurance measures were applied to the development of the system: Risk Analysis, Requirements Reviews, Design Reviews, Testing on unit level (Module verification), Integration testing (System verification), Performance testing (Verification), Safety testing (Verification), Simulated use testing (Validation)." (References: ISO14971)
    Quality System: Adherence to design and development controls.Covered by the various quality assurance measures listed above.

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

    The document explicitly states: "The subject of this premarket submission, LOGIQ F Scries, did not require clinical studies to support substantial equivalence."

    Therefore, there is no "test set" in the context of clinical performance evaluation (like for an AI algorithm). The evaluation for safety and effectiveness relies on non-clinical tests and comparison to predicate devices.

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

    As no clinical studies were performed, there was no "test set" requiring ground truth established by experts.

    4. Adjudication Method for the Test Set

    Not applicable, as no clinical studies were performed.

    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 is for a general-purpose ultrasound system, not an AI-assisted diagnostic tool. No clinical studies, let alone MRMC studies, were performed.

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

    Not applicable. This device is an ultrasound system, not a standalone algorithm.

    7. The Type of Ground Truth Used (expert consensus, pathology, outcomes data, etc.)

    Not applicable, as no clinical studies were performed that would require ground truth establishment in this manner. The "ground truth" for the device's substantial equivalence is its demonstrated compliance with electrical, mechanical, and safety standards, and its technological similarity to predicate devices already cleared by the FDA.

    8. The Sample Size for the Training Set

    Not applicable. This document describes a traditional ultrasound system, not a machine learning or AI-driven device that requires training data.

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

    Not applicable, as there is no training set for this type of device.

    Ask a Question

    Ask a specific question about this device

    Page 1 of 1