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510(k) Data Aggregation

    K Number
    K060486
    Manufacturer
    Date Cleared
    2006-03-23

    (27 days)

    Product Code
    Regulation Number
    892.1200
    Reference & Predicate Devices
    Predicate For
    N/A
    AI/MLSaMDIVD (In Vitro Diagnostic)TherapeuticDiagnosticis PCCP AuthorizedThirdpartyExpeditedreview
    Intended Use

    The Cyclone is an emission computed tomography system intended to detect the location and distribution of gamma ray emitting radionuclides in the body and produce cross-sectional images through computer reconstruction of the data. The data can then be transmitted to, or retrieved by, existing commercially available image processing software packages and accompanying computer equipment.

    The Cyclone intended use is for cardiac applications. The Cyclone supports radionuclides within the energy of 50-200keV.

    Device Description

    The Cyclone camera is a dedicated Gamma Camera for nuclear cardiology. The intended use of Cyclone is to detect the location and distribution of gamma ray emitting radionuclides in the body and store the image data. This device includes accessories such as signal analysis and display equipment, patient and equipment supports. radionuclide anatomical markers, component parts, and accessories. Radiopharmaceuticals are administered intravenously. The Cyclone records the distribution of the tracer in vivo. Gamma rays are emitted from the tracer. A collimator is used to accept only the gamma rays with defined orientations, usually parallel for detection. The collimator is actually analogous to a camera lens. The gamma rays admitted into the scintillation camera detector interact with a scintillating crystal, causing a very small flash of light at each point of interaction. The crystal is large, flat and thin (see specifications for size). The pattern of light flashes is detected by photomultiplier tubes that convert the light into electrical signals, each signal proportional to the energy of the gamma ray and also carrying precise positional information. Only gamma rays with the correct energy for the tracer used and with meaningful orientation to the patient are imaged.

    The Cyclone camera consists of a base which supports a wall or track that in turn supports and guides a fixed 90 degree dual head around a patient chair. The motions and set-up of the camera can be controlled with the hand control. Detector motions are controlled by software and are initiated by the hand control.

    AI/ML Overview

    Here's a breakdown of the acceptance criteria and the study information based on the provided document:

    1. Table of Acceptance Criteria and Reported Device Performance

    The device (Cyclone maiCAM180 Gamma Camera System) demonstrates substantial equivalence to the predicate device (3D, Danish Diagnostic Development Virgo K031825) by meeting or exceeding performance metrics. The acceptance criteria essentially align with the performance of the predicate device, or improved upon it.

    Feature/SpecAcceptance Criteria (Predicate - Virgo)Reported Device Performance (Cyclone)
    Energy range (keV)60 - 17050 - 200
    Count rate (Kcps)290300
    Energy resolution (% FWHM)≤9.49.2
    Intrinsic uniformity (integral)≤2.5≤2.5
    Intrinsic uniformity (differential)≤1.5≤1.5
    Intrinsic spatial resolution (FWHM)≤3.7 mm≤3.0 mm
    Intrinsic spatial resolution (FWTM)≤7.6 mm≤6.2 mm

    2. Sample Size for Test Set and Data Provenance

    The document does not explicitly state a "test set" in the context of image data or patient data. Instead, the performance evaluation is based on technical specifications and physical measurements of the device's capabilities, compared against industry standards.

    • Sample Size for Test Set: Not applicable in the context of a typical clinical test set with patient data. The evaluation is focused on the inherent physical and electronic performance of the gamma camera itself.
    • Data Provenance: Not applicable for device performance specifications derived from NEMA standards testing. These tests are conducted on the device in a controlled laboratory environment. The country of origin of the data would be where Spectrica performed its NEMA-compliant testing, presumably Canada based on the applicant's address.

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

    This information is not provided in the document. The performance metrics are objective physical measurements based on established NEMA standards, not on expert interpretation of images or clinical outcomes.

    4. Adjudication Method for the Test Set

    This is not applicable. The "test set" here refers to the device's technical specifications, which are assessed against standardized measurement protocols (NEMA NU 1-2001) rather than adjudicated by experts.

    5. Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study

    No, an MRMC comparative effectiveness study was not done or at least not reported in this 510(k) summary. This submission focuses on the technical and performance equivalence of the gamma camera system itself, not on the diagnostic accuracy of human readers using images generated by the device, with or without AI assistance. The document predates widespread AI integration in medical imaging.

    6. Standalone (Algorithm Only Without Human-in-the-Loop Performance) Study

    No, a standalone algorithm-only study was not done. This device is a gamma camera hardware system, not an AI algorithm.

    7. Type of Ground Truth Used

    The "ground truth" for the acceptance criteria and performance evaluation is based upon NEMA Standards (NU 1-2001, Performance Measurements of Scintillation Cameras). These standards define the methods for measuring key performance parameters (e.g., energy range, count rate, spatial resolution, uniformity) of gamma cameras. The predicate device's performance, which the new device aims to meet or exceed, also acts as a reference.

    8. Sample Size for the Training Set

    This is not applicable. The Cyclone maiCAM180 is a physical gamma camera system, not an AI model that requires a training set.

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

    This is not applicable, as there is no AI model or training set involved in this 510(k) submission.

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