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510(k) Data Aggregation

    K Number
    K153232
    Device Name
    Cios Select
    Date Cleared
    2016-02-10

    (93 days)

    Product Code
    Regulation Number
    892.1650
    Reference & Predicate Devices
    Why did this record match?
    Reference Devices :

    K963093

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

    The Cios Select is a mobile x-ray system intended for use in Operation room, Traumatology, Endoscopy, Intensive Care Station, Paediatrics, Ambulatory patient care and in Veterinary Medicine. The Clos Select can operate in four different modes, Digital Radiography, Fluoroscopy and Pulsed Fluoroscopy and Cassette exposure which are necessary in performing wide variety of clinical procedures, such as intraoperative bile duct display, fluoroscopic display of intramedullary nail implant in various positions, low dose fluoroscopy in pediatrics, fluoroscopic techniques utilized in pain therapy and positioning of catheters and probes.

    Device Description

    This 510(k) submission, Cios Select is a Mobile Fluoroscopic C-arm X-ray System. The Cios Select is a modification of the Siremobil Compact originally cleared under Premarket Notification K963093 on September 3rd, 1996.

    The Cios Select consists of two major units:

    One is the acquisition unit with the C-arm and movable base containing the generator, power unit, system control, and tube housing assembly on one side of the C-arm and the image intensifier on the opposite side.

    The second unit is the image display station with a moveable trolley for the image processing and storage system, image display and documentation. Both units are connected to each other with a cable. The main unit is connected to the main power outlet and the trolley is connected to a data network.

    AI/ML Overview

    Based on the provided text, the acceptance criteria and the study proving the device meets them are described as follows:

    1. Table of Acceptance Criteria and Reported Device Performance

    The document does not provide a specific table of acceptance criteria with detailed metrics (e.g., sensitivity, specificity, accuracy, precision, etc.) and their corresponding device performance. Instead, it states that "The results of these tests also demonstrate that the Cios Select acceptance criteria are adequate for this intended use."

    The general performance criteria are inferred from the non-clinical testing and verification/validation processes:

    Acceptance Criteria CategoryReported Device Performance (Summary)
    Functional PerformanceAll software specifications met the acceptance criteria.
    SafetyConformance to various safety standards (e.g., IEC 60601-1, IEC 62366, ISO 14971).
    Electromagnetic Compatibility (EMC)Compliance with IEC 60601-1-2 3rd standard for EMC. All tests passed.
    Software PerformanceContinued conformance with special controls for medical devices containing software. Risk control measures implemented.
    CybersecurityConforms to cybersecurity requirements by implementing processes to prevent unauthorized access, modifications, misuse, or denial of use.
    Substantial EquivalenceDemonstrated to be as safe and effective as the predicate device (Siremobil Compact K963093) for the same intended and indications for use.

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

    The document does not explicitly state a "test set" in terms of patient data or images with a specific sample size. The testing described is primarily non-clinical, focusing on hardware, software, electrical safety, EMC, and environmental aspects.

    • Sample Size: Not applicable in the context of patient data for a "test set" as typically understood for AI/algorithm performance. The "test set" refers to the device itself being tested for its functional, safety, and performance aspects.
    • Data Provenance: Not applicable as the testing is non-clinical/device-focused.

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

    This information is not provided because the "acceptance criteria" and "test set" relate to the device's technical specifications and safety/performance standards, rather than the diagnostic accuracy of an AI algorithm based on clinical ground truth.

    4. Adjudication Method for the Test Set

    Not applicable, as the evaluation involves meeting technical specifications and standards, not clinical diagnostic consensus.

    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 involving human readers and AI assistance was not done. The device, Cios Select, is described as a mobile x-ray system, not an AI-based diagnostic tool intended to assist human readers. The clearance is for the X-ray system itself, not an AI algorithm.

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

    This is not applicable. The Cios Select is an "Image-Intensified Fluoroscopic X-Ray System," which is a hardware device with integrated software. It's not a standalone algorithm.

    7. The Type of Ground Truth Used (Expert Consensus, Pathology, Outcomes Data, etc.)

    The "ground truth" for the testing described is primarily defined by:

    • Established industry standards: e.g., IEC 60601 series, ISO 14971 (risk management), IEC 62304 (software life cycle), DICOM standards.
    • Internal specifications: The device's own design and functional requirements.
    • Predicate device characteristics: Substantial equivalence demonstrated against the Siremobil Compact K963093, implying its performance characteristics and safety profile are the "ground truth" reference.

    8. The Sample Size for the Training Set

    Not applicable. The Cios Select is a conventional X-ray system, not an AI/Machine Learning diagnostic algorithm that requires a "training set" of data.

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

    Not applicable, as there is no "training set" for an AI algorithm mentioned in the document.

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