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510(k) Data Aggregation

    K Number
    K061755
    Manufacturer
    Date Cleared
    2006-08-07

    (47 days)

    Product Code
    Regulation Number
    892.1560
    Reference & Predicate Devices
    Why did this record match?
    Device Name :

    MYLAB15/20 NEW INDICATIONS ULTRASOUND SYSTEM

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

    Esaote's MyLab15/MyLab20 is a compact console ultrasound system intended to be used by a physician to perform general diagnostic ultrasound studies including Fetal, Abdominal, Pediatric, Small organ, Neonatal Cephalic, Cardiac, Transrectal, Transvaginal, Peripheral Vascular, Musculoskeletal (Conventional and Superficial), Intraoperative: Abdominal, and Other: Urological.

    Device Description

    The MyLab15/20 is a compact console ultrasound system used to perform general diagnostic ultrasound studies. Its primary modes of operation are: B-Mode, M-Mode, PW Doppler and Color Flow Mapping and Tissue Enhancement Imaging (TEI). MyLab15/20 is able to produce real time 2D images and 3D images (in manual mode) with all probes. The system, in combination with the probe BC432P, offers the possibility to also produce automatic 3D and real time 4D images

    AI/ML Overview

    The provided text is a 510(k) summary for the Esaote MyLab15/20 Ultrasound System (K061755). This document primarily focuses on demonstrating substantial equivalence to predicate devices for new indications and transducer types. It does not contain information about acceptance criteria or a study proving device performance against such criteria in the context of diagnostic accuracy, clinical effectiveness, or AI algorithm performance.

    The document states that the device is an ultrasound imaging system and its performance is implicitly demonstrated through substantial equivalence to other legally marketed ultrasound systems.

    Therefore, most of the requested information (acceptance criteria, study details, sample sizes, expert qualifications, adjudication, MRMC, standalone performance, ground truth types for test/training sets, training set sample size, and ground truth establishment for training set) is not present in the provided text.

    Based on the available information, here's what can be extracted:

    1. Table of Acceptance Criteria and Reported Device Performance

    This information is not provided in the given 510(k) summary. The document focuses on demonstrating substantial equivalence to predicate devices for specific clinical applications and imaging modes, not on presenting acceptance criteria and performance data against those criteria in a quantitative manner (e.g., sensitivity, specificity, accuracy).

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

    This information is not provided in the document. The submission is not related to a clinical study assessing diagnostic performance against a test set. It's a regulatory submission for device clearance based on equivalence.

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

    This information is not provided in the document. No test set or ground truth establishment process is described.

    4. Adjudication Method for the Test Set

    This information is not provided in the document. No test set or adjudication method is described.

    5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study Was Done, and Effect Size

    This information is not provided in the document. The document pertains to an ultrasound imaging system, not an AI-assisted diagnostic tool, and therefore, an MRMC study for AI assistance would not be applicable here.

    6. If a Standalone (Algorithm Only Without Human-in-the-Loop Performance) Was Done

    This information is not provided in the document. The device is an ultrasound imaging system, not an AI algorithm, so standalone algorithm performance is not relevant.

    7. The Type of Ground Truth Used

    This information is not provided in the document. No specific ground truth is mentioned as the basis for performance evaluation in this 510(k) submission.

    8. The Sample Size for the Training Set

    This information is not provided in the document. As this is not an AI/algorithm submission, a "training set" in that context is not relevant.

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

    This information is not provided in the document. Similar to point 8, this is not relevant to the type of device and submission described.

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