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510(k) Data Aggregation

    K Number
    K151653
    Date Cleared
    2015-08-07

    (50 days)

    Product Code
    Regulation Number
    892.1000
    Reference & Predicate Devices
    Predicate For
    AI/MLSaMDIVD (In Vitro Diagnostic)TherapeuticDiagnosticis PCCP AuthorizedThirdpartyExpeditedreview
    Intended Use

    8ch Foot Ankle Coil manufactured by RFT is a receive-only RF surface coil designed for use with the SIGNA Pioneer only. 8ch Foot Ankle Coil is indicated to use for foot and ankle imaging. The nucleus excited is hydrogen.

    Device Description

    The 8ch Foot Ankle Coil is a surface coil used for Magnetic Resonance Imaging. It's tuned to image Proton nuclei in a receive-only configuration. It is comprised of 8 individual Phased Array coil elements which receive the signal from patient's foot or ankle. Preamplifiers are integrated in the coil. The geometry is optimized for use with parallel imaging techniques.

    The 8ch Foot Ankle Coil receives foot or ankle signal through 8-element phased array under 3T static magnetic field and presents the foot or ankle images based on the above mentioned theory.

    The 8ch Foot Ankle Coil comprises the coil and the base plate. The coil conforms to patients' anatomy, accommodating various foot contours while minimizing patient discomfort. The base plate separated from the coil part is used to place the patients' anatomy on the table.

    The associated accessories include:

    • -1 cable
    • 1 baseplate, -
    • -1 ankle pad,
    • -1 foot pad,
    • 1 ramp pad, -
    • 1 knee pad support, -
    • 1 strap. -
    AI/ML Overview

    The provided document is a 510(k) summary for the Shenzhen RF Tech Co., Ltd.'s 8ch Foot Ankle Coil. It details the device's characteristics, comparison to a predicate device, and performance data used to support its substantial equivalence. However, it does not contain specific acceptance criteria, detailed study results proving the device meets those criteria, or information on reader studies, ground truth establishment for AI models, or AI training data.

    The document focuses on non-clinical performance data (biocompatibility, electrical safety/EMC, and bench testing) and a qualitative mention of "clinical tests" demonstrating anatomical equivalence, rather than quantitative performance metrics for disease detection or diagnostic accuracy.

    Therefore, many of the requested details about acceptance criteria, study specifics, and AI-related information cannot be extracted from this document.

    Here's a breakdown of what can be inferred or explicitly stated based on the provided text:

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

    The document does not provide a table of acceptance criteria with specific quantitative targets and corresponding reported performance values for diagnostic accuracy or clinical outcomes. Instead, it lists types of tests conducted:

    Acceptance Criteria (Implied by Test Type)Reported Device Performance
    Biocompatibility:
    CytotoxicityNon-cytotoxic
    SensitizationNot a sensitizer
    IrritationNot an irritant
    Electrical Safety & EMC:
    Compliance with IEC 60601-1Complies with standard
    Compliance with IEC 60601-1-2Complies with standard
    Bench Testing (Functionality/Safety):
    Blocking Network analysis effectivenessMet requirements
    Surface temperature (normal condition)Met requirements
    Surface temperature (unplugged condition)Met requirements
    Elements signal checkMet requirements
    max B1Met requirements
    Clinical Tests (Image Quality - Qualitative):
    Visualization of anatomies in sagittal, coronal, and axial planesShowed substantial equivalence to predicate coil anatomies

    2. Sample sized used for the test set and the data provenance (e.g. country of origin of the data, retrospective or prospective)

    • Sample Size for Clinical Tests: Not specified. The document only mentions "Analyses in sagittal, coronal, and axial planes were run on the 8ch Foot Ankle Coil to show that anatomies of the submitted and predicate coils have substantial equivalence." This suggests a small, qualitative visual comparison rather than a large, statistically powered clinical study.
    • Data Provenance: Not specified.
    • Retrospective or Prospective: Not specified.

    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 applicable. The document describes a medical device (MRI coil), not an AI algorithm requiring expert-established ground truth for diagnostic accuracy. The "clinical tests" described seem to be about visual comparison of image quality, not disease diagnosis.

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

    Not applicable. As above, this is for image interpretation/diagnosis, not a hardware device's performance evaluation.

    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 is for a medical device (MRI coil), not an AI-powered diagnostic tool. No MRMC study was mentioned.

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

    Not applicable. This is a hardware device.

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

    For the "clinical tests," the ground truth was visual comparison of anatomical visualization/image quality, likely against the predicate device's images, to demonstrate "substantial equivalence." There is no mention of pathology, outcomes data, or disease-specific expert consensus as the primary ground truth for this device's evaluation. For biocompatibility and electrical safety, the "ground truth" is compliance with established standards and test protocols.

    8. The sample size for the training set

    Not applicable. This is not an AI device.

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

    Not applicable. This is not an AI device.

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