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510(k) Data Aggregation

    K Number
    K083001
    Date Cleared
    2008-10-22

    (14 days)

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

    K080640, K072164, K061129, K072797, K060949, K042540

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

    The device is intended for use by a qualified physician for ultrasound evaluation of abdominal, cardiac, small parts (breast, testes, thyroid, etc.), peripheral vascular, fetal, transrectal, transvaginal, intraoperative (abdominal, thoracic, and vascular etc.), pediatric, neonatal cephalic, musculoskeletal (general and superficial).

    Device Description

    The M5 Diagnostic Ultrasound System is a general purpose, mobile, software controlled, ultrasound diagnostic system. Its function is to acquire and display ultrasound images in B-Mode, M-Mode, Color mode, PW mode, CW mode, Power mode, DirPower mode or the combined mode (i.e. B/M Mode). This system is a Track 3 device that employs an array of probes that include linear array, convex array and phased array with a frequency range of approximately 2.0 MHz to 12.0 MHz.

    AI/ML Overview

    The provided text describes a 510(k) Pre-Market Notification for the KOS-3001 M5 Diagnostic Ultrasound System. It asserts substantial equivalence to predicate devices and describes the intended use and safety considerations. However, it does not contain any information regarding acceptance criteria or a specific study proving the device meets those criteria.

    The document mainly focuses on:

    • Device Identification: Name, submitter, date prepared.
    • Classification: Regulatory class, review category, product codes.
    • Marketed Devices: Listing predicate devices for substantial equivalence.
    • Device Description: General description, modes of operation, probe types, and frequency range.
    • Intended Use: Clinical applications for which the device is intended.
    • Safety Considerations: Compliance with FDA guidance and medical device safety standards (NEMA UD 2, NEMA UD 3, IEC 60601-1, etc.).
    • FDA Clearance Letter: Formal letter from the FDA stating substantial equivalence and listing cleared transducers and their clinical applications.

    Therefore, I cannot provide a table of acceptance criteria and reported device performance, nor details about a study proving these criteria are met, as this information is not present in the provided text.

    To answer your specific questions in the context of this document:

    1. A table of acceptance criteria and the reported device performance: Not available in the provided text. The document asserts safety and effectiveness through compliance with standards and substantial equivalence to predicate devices, but no specific performance criteria or results are listed.
    2. Sample size used for the test set and the data provenance (e.g. country of origin of the data, retrospective or prospective): Not available in the provided text.
    3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts (e.g. radiologist with 10 years of experience): Not available in the provided text.
    4. Adjudication method (e.g. 2+1, 3+1, none) for the test set: Not available in the provided text.
    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 available in the provided text. This device is a diagnostic ultrasound system, not an AI-powered image analysis tool.
    6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done: Not applicable as there is no mention of an algorithm for standalone performance.
    7. The type of ground truth used (expert consensus, pathology, outcomes data, etc.): Not available in the provided text.
    8. The sample size for the training set: Not applicable as there is no mention of a training set for an AI algorithm.
    9. How the ground truth for the training set was established: Not applicable.
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