Search Filters

Search Results

Found 1 results

510(k) Data Aggregation

    K Number
    K122704
    Manufacturer
    Date Cleared
    2013-01-09

    (127 days)

    Product Code
    Regulation Number
    892.5730
    Reference & Predicate Devices
    Predicate For
    Why did this record match?
    Reference Devices :

    K912170

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

    The device is indicated as "single-use sterile device". Best Localization Needle with I-125 Seed is indicated in the use for Breast Localization purpose under the direct supervision of a qualified physician.

    Device Description

    "Best" Localization Needle with I-125 Seed" contains low activity Iodine seed (Best I-125- K912170). The lodine-125 seed is loaded as loose or as stranded inside the needle. Most commonly, 18 giuge 5cm to 20 cm needles are used as a breast localization needle to facilitate the introduction of radionuclide seed into the breast cancer area. The devices are packaged in a pouch with label and provided sterile.

    AI/ML Overview

    The provided document is a 510(k) summary for the "Best® Localization Needle with I-125 Seed." The primary purpose of this document is to establish substantial equivalence to a predicate device, not to detail the results of a primary clinical study proving performance against acceptance criteria. Therefore, most of the requested information regarding acceptance criteria, study design, and performance metrics is not available in this document.

    The document states that the new device is "substantially equivalent" to the predicate device, "BrachySciences Radioactive Seed Localization Needle with AnchorSeed (K111979)." This equivalence is based on similar technological characteristics and intended use.

    Here's a breakdown of the requested information, indicating what is not available:


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

    • Not available. The document does not specify performance acceptance criteria or report specific performance metrics for the device. The 510(k) process focuses on demonstrating substantial equivalence to a legally marketed predicate device rather than fulfilling specific performance acceptance criteria from a new clinical study.

    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. No new clinical study data or test set information is provided in this 510(k) summary.

    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. No test set or ground truth establishment details are provided.

    4. Adjudication method (e.g., 2+1, 3+1, none) for the test set

    • Not available. No adjudication method is mentioned as no specific test set data is discussed.

    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 medical needle with an I-125 seed, not an AI-assisted diagnostic or therapeutic tool. Therefore, an MRMC study comparing human readers with and without AI assistance is not relevant to this product.

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

    • Not applicable. This device is a physical medical instrument, not an algorithm. Standalone algorithm performance is not relevant.

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

    • Not available. No ground truth information is mentioned because no primary clinical data for performance assessment is presented.

    8. The sample size for the training set

    • Not applicable. This device is a physical medical product, not a machine learning algorithm that requires a training set.

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

    • Not applicable. As above, this is not a machine learning algorithm.
    Ask a Question

    Ask a specific question about this device

    Page 1 of 1