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510(k) Data Aggregation

    K Number
    K222219
    Date Cleared
    2022-12-06

    (134 days)

    Product Code
    Regulation Number
    892.1750
    Reference & Predicate Devices
    Why did this record match?
    Device Name :

    R2 Studio Q/RCT820

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

    R2 STUDIO Q/RCT820 is CBCT and panoramic x-ray imaging system with cephalometric. Which is intended to radiographic examination of the dento-maxillofacial, sinus, TMJ, Airway for diagnostic support for adult and pediatric patients. And a model scan is included as an option. Cephalometric image is also includes wrist to obtain carpus images for growth and maturity assessment for orthodontic treatment. The device is to be operated and used by dentists or other legally qualified health care professionals. This device is not intended for use on patients less than approximately 21 kg (46 lb) in weight and 113 cm (44.5 in) in height; these height and weight measurements approximately correspond to that of an average 5 year old.

    Device Description

    R2 STUDIO Q/RCT820 is 3D computed tomography for scanning hard tissues like bone and teeth. By rotating the c-arm which is embedded with high voltage generator all-in-one x-ray tube and a detector on each end, CBCT images of dental maxillofacial is attained by recombining data from the same level that are scanned from different angle. Panoramic image scanning function for attaining image of whole teeth, cephalometric scanning option for attaining cephalic image are included. and Model Scan option for attaining dental model CBCT image are included.

    AI/ML Overview

    The provided document is a 510(k) premarket notification for the R2 STUDIO Q/RCT820 dental X-ray system. Here's a breakdown of the requested information:

    1. Table of Acceptance Criteria and Reported Device Performance

    The document does not explicitly state acceptance criteria in a quantitative table format alongside reported performance for specific imaging metrics. Instead, it states that "All test results were satisfactory" following performance testing. The comparison table (page 5) lists various technical specifications for the proposed device and two predicate devices but does not provide specific performance values against pre-defined acceptance limits.

    2. Sample size used for the test set and the data provenance

    The document mentions "clinical evaluation report" but does not specify the sample size for any clinical test sets. The data provenance (country of origin, retrospective/prospective) is not explicitly stated.

    3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts

    This information is not provided in the document.

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

    This information is not provided in the document.

    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

    The document does not mention any multi-reader multi-case (MRMC) comparative effectiveness study or any studies involving AI assistance. This device is an imaging system, not an AI-powered diagnostic tool.

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

    This information is not applicable as the device is an imaging system and not designed for standalone algorithmic performance without human-in-the-loop.

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

    The document mentions "clinical evaluation report" and that "Sample images with a clinical evaluation report is provided to support the intended use of the device." However, it does not specify the type of ground truth used for this evaluation.

    8. The sample size for the training set

    The document does not mention a "training set" in the context of device performance, as it is describing an imaging system rather than an AI/ML model that requires training data.

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

    This information is not applicable as the document does not refer to a "training set" for an AI/ML model.

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