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510(k) Data Aggregation

    K Number
    K063373
    Manufacturer
    Date Cleared
    2006-11-17

    (9 days)

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

    The intended use of the Flex Loop Coil Set 3 T is, in conjunction with a Magnetic Resonance Scanner, the MR examination of the human body.

    Used in the MAGNETOM 3 T Trio, a Tim System, the Flex Loop Coils are indicated for use as a diagnostic imaging device to produce transversal, sagittal, coronal and oblique images of the internal structures of the body. The images produced by the MAGNETOM 3 T Trio, a Tim System with the Flex Loop Coils reflect the spatial distribution of protons (hydogen nuclei) exhibiting magnetic resonance.

    When interpreted by a trained physician, these images provide information that can be useful in determining a diagnosis.

    The intended use of the MAGNETOM 3 T Trio, a Tim System is not affected in any way by the use of the new Flex Loop Coil Set 3 T.

    Device Description

    The Flex Loop Coil Set 3 T consists of five receive-only coils and one interface, which contains the preamplifiers, cable traps and a combiner network. The coils are two 4-channel flexible coils (Flex Coil Large and Flex Coil Small) and three linear polarized (LP) flexible coils (Loop Coil 4 cm, 7 cm and 11 cm).

    AI/ML Overview

    Here's a breakdown of the acceptance criteria and study information for the Flex Loop Coil Set 3 T, based on the provided 510(k) summary:

    1. Table of Acceptance Criteria and Reported Device Performance

    Acceptance Criteria CategorySpecific ParameterAcceptance Criteria (Stated or Implied by Equivalence Claim)Reported Device Performance (Summary)
    SafetyMaximum Static FieldUnaffected by modificationMeets safety standards (implied by "unaffected" claim)
    Rate of Change of Magnetic FieldUnaffected by modificationMeets safety standards (implied by "unaffected" claim)
    RF Power DepositionUnaffected by modificationMeets safety standards (implied by "unaffected" claim)
    Acoustic Noise LevelUnaffected by modificationMeets safety standards (implied by "unaffected" claim)
    BiocompatibilityNo new materials, therefore no new biocompatibility issuesBiocompatibility equivalent to predicate devices
    PerformanceGeometric DistortionUnaffected by modificationPerformance equivalent to predicate devices
    Slice Profile, Thickness & GapUnaffected by modificationPerformance equivalent to predicate devices
    High Contrast Spatial ResolutionUnaffected by modificationPerformance equivalent to predicate devices
    Signal to Noise Ratio (SNR)Equivalent to predicate devices (per NEMA MS-6 standard)Equivalent to predicate devices (per NEMA MS-6 standard)
    Image UniformityEquivalent to predicate devices (per NEMA MS-6 standard)Equivalent to predicate devices (per NEMA MS-6 standard)

    Important Note: The document consistently states that the new device's safety and performance parameters are unaffected by the modifications described or that they are equivalent to predicate devices. Specific numerical acceptance thresholds are not explicitly provided in this 510(k) summary, as the nature of a 510(k) submission is to demonstrate substantial equivalence to a legally marketed predicate device rather than to establish new performance benchmarks. The "acceptance criteria" here are essentially the demonstration of equivalence to the predicate.

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

    The 510(k) summary does not specify a distinct "test set" in the context of clinical images or patient data. The testing mentioned appears to be primarily laboratory and physical performance testing of the coils themselves.

    • Sample Size: Not applicable in terms of patient numbers. The testing was on the device itself.
    • Data Provenance: The testing was "Laboratory and clinical testing," which typically means internal studies conducted by the manufacturer, Siemens AG, in Germany. It does not specify whether this involved human subjects, but the nature of the tests (SNR, image uniformity, etc.) suggests physical measurements on a scanner. It is prospective in the sense that these tests were performed on the new device to support its 510(k) submission.

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

    Not applicable. The ground truth for the performance parameters (SNR, image uniformity, geometric distortion, etc.) is established by technical measurements and adherence to standards (e.g., NEMA MS-6), not by human expert interpretation of a clinical test set.

    4. Adjudication Method for the Test Set

    Not applicable, as the evaluation was based on objective technical measurements and comparison to standards/predicate device performance, not on human interpretation requiring adjudication.

    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

    No, an MRMC comparative effectiveness study was not done. The device is a hardware component (MRI coils), not an AI-powered diagnostic tool. Therefore, the concept of human reader improvement with/without AI assistance is not relevant here.

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

    Not applicable. This is a hardware device (MRI coil), not an algorithm.

    7. The Type of Ground Truth Used

    The ground truth used for the performance parameters was objective technical measurements and established engineering/physics standards (e.g., SNR and image uniformity tested according to the NEMA MS-6 standard). For safety, the ground truth refers to established safety limits and regulations for MRI devices.

    8. The Sample Size for the Training Set

    No training set is mentioned or applicable, as this is a new hardware device rather than a machine learning algorithm.

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

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

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