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510(k) Data Aggregation

    K Number
    K092728
    Date Cleared
    2010-11-19

    (441 days)

    Product Code
    Regulation Number
    892.2050
    Reference & Predicate Devices
    Why did this record match?
    Reference Devices :

    K063198

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

    20.1-inch (51cm) Color LCD Monitor CCL208 (CDL2013A) is intended to be used in displaying and viewing medical images for diagnosis by trained medical practitioners. It is not meant to be used in digital mammography.

    Device Description

    CCL208 (CDL2013A) is a 20.1-inch (51 cm) Color LCD monitor whose display resolution is 1200 x 1600 (landscape), 1600 x 1200 (portrait) supporting DVI (digital visual interface).

    AI/ML Overview

    This document is a 510(k) summary for the TOTOKU 20.1-inch (51 cm) Color LCD Monitor CCL208 (CDL2013A), a medical display device. The primary purpose of the submission is to demonstrate substantial equivalence to a predicate device.

    The document does not describe any study that proves the device meets specific acceptance criteria in terms of performance for image interpretation or diagnostic accuracy. This is because the device is a monitor, and its "performance" is primarily related to display characteristics and technical specifications rather than diagnostic performance.

    Therefore, many of the requested elements for a study proving device performance are not applicable to this submission. I will provide the information that is available in the document.

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

    The document does not explicitly state "acceptance criteria" in the context of diagnostic performance that would typically be described with metrics like sensitivity, specificity, accuracy, etc. Instead, the substantial equivalence argument relies on meeting technical specifications comparable to the predicate device.

    The "performance" of this device is implicitly its ability to display medical images. The acceptance criteria would be that it functions as a display comparable to its predicate. The document states:
    "CCL208 (CDL2013A) shares the same characteristics with our predicate devices, CCL202 (CDL2005A) (K063198) except for power supply, LCD panel, main board (driver board and sub board), tilt-stand, I/O position and inverter PWB for LCD backlight."

    This implies that despite these component changes, the performance (i.e., its function as a display) is considered equivalent. The common elements like intended use for "displaying and viewing medical images for diagnosis" are the basis for equivalence.

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

    Not applicable. This is not a study assessing diagnostic performance on a dataset of medical images. The "test set" would refer to the monitor itself undergoing technical evaluation.

    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, as this is not a diagnostic performance study where ground truth needs to be established by experts.

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

    Not applicable.

    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 device is a monitor, not an AI or a diagnostic aid that would participate in an MRMC study.

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

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

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

    Not applicable. The ground truth for a monitor would be its technical specifications meeting design requirements, not a diagnostic ground truth.

    8. The sample size for the training set

    Not applicable. This is not a machine learning device that requires a training set.

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

    Not applicable.

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