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510(k) Data Aggregation

    K Number
    K232127
    Date Cleared
    2023-08-15

    (29 days)

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

    21HQ513D, 32HL512D, 31HN713D, 32HQ713D

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

    21HQ513D, 32HL512D: This Medical Monitor is indicated for use in displaying radiological images for review, analysis, and diagnosis by trained medical practitioners. The display is not intended for mammography.
    31HN713D, 32HO713D: This Medical Monitor is indicated for use in displaying radiological images (including full-field digital mammography and digital breast tomosynthesis) for review, analysis, and diagnosis by trained medical practitioners.

    Device Description

    The Medical monitor is intended to provide high resolution color and grayscale medical imaging for PACS and Radiology system. This Medical Monitor is intended to be used by trained medical practitioners for displaying, reviewing, and analysis of medical images.

    AI/ML Overview

    The provided document describes the acceptance criteria and the results of the study for the medical monitors 21HQ513D, 32HL512D, 31HN713D, and 32HQ713D.

    Here's the requested information:

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

    The document refers to the "performance items suggested in the FDA guidance 'Display Devices for Diagnostic Radiology'" as the acceptance criteria. The performance for each measurement is uniformly reported as "Pass" for the tested items.

    MeasurementsAcceptance Criteria (Implied by FDA Guidance)Reported Device Performance
    a. Spatial resolutionMeet FDA guidance standardsPass
    b. Pixel defectsMeet FDA guidance standardsPass
    c. ArtifactsMeet FDA guidance standardsPass
    d. Temporal responseMeet FDA guidance standardsPass
    e. LuminanceMeet FDA guidance standardsPass
    f. Conformance to a grayscale-to-luminance functionMeet FDA guidance standardsPass
    g. Luminance at 30° and 45° in diagonal, horizontal, and vertical directions at center and four cornersMeet FDA guidance standardsPass (for 31HN713D, 32HQ713D) / N/A (for 21HQ513D, 32HL512D)
    h. Luminance uniformity or Mura testMeet FDA guidance standardsPass (for 31HN713D, 32HQ713D) / N/A (for 21HQ513D, 32HL512D)
    i. Stability of luminance and chromaticity response with temperature and time of operation (on-time)Meet FDA guidance standardsPass (for 31HN713D, 32HQ713D) / N/A (for 21HQ513D, 32HL512D)
    j. Spatial noiseMeet FDA guidance standardsPass (for 31HN713D, 32HQ713D) / N/A (for 21HQ513D, 32HL512D)
    k. Reflection coefficientMeet FDA guidance standardsPass (for 31HN713D, 32HQ713D) / N/A (for 21HQ513D, 32HL512D)
    l. Veiling glare or small-spot contrastMeet FDA guidance standardsPass (for 31HN713D, 32HQ713D) / N/A (for 21HQ513D, 32HL512D)
    m. Color trackingMeet FDA guidance standardsPass
    n. Gray trackingMeet FDA guidance standardsPass (for 31HN713D, 32HQ713D) / N/A (for 21HQ513D, 32HL512D)

    Note: The "N/A" for certain measurements for models 21HQ513D and 32HL512D might indicate that these tests were not applicable or not performed for these specific models, possibly due to their differing indications for use (not intended for mammography, unlike 31HN713D and 32HQ713D). The document does not explicitly state the acceptance numerical values for each criterion but implies compliance with the FDA guidance "Display Devices for Diagnostic Radiology".

    2. Sample size used for the test set and the data provenance
    The document does not specify a "test set" in terms of patient data or images. The study described is a non-clinical bench test on the display devices themselves. The sample size for the test set would be the number of devices tested, which is implied to be one of each model (21HQ513D, 32HL512D, 31HN713D, and 32HQ713D). The data provenance is not applicable in the typical sense of clinical data, as it's a technical performance test of hardware.

    3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts
    This information is not applicable. The study is a non-clinical bench test of display performance against predefined technical standards and FDA guidance, not a study involving expert interpretation of medical images.

    4. Adjudication method for the test set
    This information is not applicable. There was no expert adjudication process as it was a technical performance test.

    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 MRMC comparative effectiveness study was done. The device is a medical monitor, not an AI-powered diagnostic tool. The document explicitly states: "No clinical studies were considered necessary and performed."

    6. If a standalone (i.e., algorithm only without human-in-the-loop performance) was done
    This is not applicable as the device is a medical monitor, not an algorithm or AI system. The study focused on the technical performance of the monitors.

    7. The type of ground truth used
    For the bench test, the ground truth was based on the performance items suggested in the FDA guidance "Display Devices for Diagnostic Radiology." This refers to quantifiable technical specifications and standards for medical image displays.

    8. The sample size for the training set
    This is not applicable. The device is a medical monitor, not a machine learning algorithm that requires a training set. The software components underwent validation according to IEC 62304.

    9. How the ground truth for the training set was established
    This is not applicable, as there was no training set for an AI algorithm. The validation of the software was done according to IEC 62304, which involves verifying the software against its design specifications and requirements.

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    K Number
    K230845
    Date Cleared
    2023-04-27

    (30 days)

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

    32HL512D, 31HN713D, 32HQ713D

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

    32HL512D: This Medical Monitor is indicated for use in displaying radiological images for review, analysis, and diagnosis by trained medical practitioners. The display is not intended for mammography.

    31HN713D, 32HQ713D: This Medical Monitor is indicated for use in displaying radiological images (including full-field digital mammography and digital breast tomosynthesis) for review, analysis, and diagnosis by trained medical practitioners.

    Device Description

    The Medical monitor is intended to provide high resolution color and grayscale medical imaging for PACS and Radiology system. This Medical Monitor is intended to be used by trained medical practitioners for displaying, reviewing, and analysis of medical images.

    AI/ML Overview

    The provided text describes a medical monitor device (32HL512D, 31HN713D, 32HQ713D) and its associated software, "LG Calibration Studio Medical," which is used for calibration. The acceptance criteria and the study performed relate to the performance of the medical monitor and the calibration software, not an AI algorithm for image analysis. Therefore, there is no information about AI-specific aspects such as training sets, ground truth establishment for AI, or comparative effectiveness studies with human readers assisted by AI.

    Here's the information derived from the text regarding the device and its software:

    1. Table of Acceptance Criteria and Reported Device Performance

    The acceptance criteria for the medical monitors are derived from the FDA guidance "Display Devices for Diagnostic Radiology." The reported performance for all three models (32HL512D, 31HN713D, 32HQ713D) is that they "Pass" all tested measurements.

    MeasurementsAcceptance CriteriaReported Device Performance (32HL512D, 31HN713D, 32HQ713D)
    a. Conformance to a grayscale-to-luminance functionConformance to a grayscale-to-luminance function (implied by FDA guidance requirements)Pass
    b. Luminance uniformity or Mura testLuminance uniformity or Mura test (implied by FDA guidance requirements)Pass
    c. Stability of luminance and chromaticity response with temperature and time of operation (on-time)Stability of luminance and chromaticity response with temperature and time of operation (on-time) (implied by FDA guidance requirements)Pass
    d. Spatial noiseSpatial noise (implied by FDA guidance requirements)Pass
    e. Veiling glare or small-spot contrastVeiling glare or small-spot contrast (implied by FDA guidance requirements)Pass

    Note: The document states, "All display characteristics of the 32HL512D, 31HN713D and 32HQ713D have met the predefined criteria. Therefore, the performance of 32HL512D, 31HN713D and 32HQ713D were verified through the performance test." The FDA guidance "Display Devices for Diagnostic Radiology" serves as the basis for these predefined criteria.

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

    • Test Set Sample Size: Not explicitly stated as the testing is on the physical device's characteristics rather than a dataset of medical images. The tests were performed on one or more units of each model (32HL512D, 31HN713D, 32HQ713D).
    • Data Provenance: Not applicable in the context of device performance testing. The "data" here refers to measurements taken directly from the physical monitors during bench testing. The tests adhere to international standards (e.g., IEC standards) and FDA guidance for medical display devices.

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

    Not applicable. The ground truth for the performance of the medical monitors is established by objective physical measurements against established technical standards and FDA guidance, not by expert interpretation of images.

    4. Adjudication Method for the Test Set

    Not applicable. Adjudication methods like 2+1 or 3+1 are typically used for expert consensus in image interpretation. This study involves objective technical measurements.

    5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study Was Done

    No. There is no mention of an MRMC study. The devices are medical monitors for displaying images, not AI algorithms.

    6. If a Standalone Study (Algorithm Only Without Human-in-the-Loop Performance) Was Done

    A standalone performance test was done for the device, focusing on its technical display characteristics. The "LG Calibration Studio Medical" software (a moderate level of concern software) was also verified and validated, but this is a calibration tool, not an image analysis algorithm. Therefore, "standalone (i.e. algorithm only without human-in-the-loop performance)" is applicable to the technical performance of the monitor as a device, and to the verification and validation of the calibration software, but not in the context of AI for medical image interpretation.

    7. The Type of Ground Truth Used

    The ground truth used for the device's performance testing is based on objective physical measurements and technical specifications set forth by international standards (e.g., IEC 60601-1, IEC 60601-1-2, IEC 62304) and the FDA guidance "Display Devices for Diagnostic Radiology."

    8. The Sample Size for the Training Set

    Not applicable, as this is not an AI algorithm for image analysis. The "LG Calibration Studio Medical" is software, validated according to IEC 62304, but the text does not describe a "training set" in the machine learning sense for this calibration software.

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

    Not applicable. There is no training set for an AI algorithm mentioned in relation to the devices or their calibration software.

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    K Number
    K201777
    Device Name
    31HN713D
    Date Cleared
    2020-10-08

    (101 days)

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

    31HN713D

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

    This Medical Monitor is indicated for use in displaying radiological images (including full-field digital mammography and digital breast tomosynthesis) for review, analysis, and diagnosis by trained medical practitioners.

    Device Description

    The Medical monitor is intended to provide high resolution color and grayscale medical imaging for PACS and Radiology system. This Medical Monitor is intended to be used by trained medical practitioners for displaying, reviewing, and analysis of medical images

    AI/ML Overview

    This document describes the 510(k) premarket notification for the LG Electronics 31HN713D Medical Monitor. The submission aims to demonstrate substantial equivalence to a predicate device (BARCO N.V. MDMC-12133, K141428) for displaying radiological images, including full-field digital mammography and digital breast tomosynthesis.

    Here's an analysis of the provided information regarding acceptance criteria and the study:


    1. Table of Acceptance Criteria and Reported Device Performance

    The acceptance criteria are implied by the non-clinical tests performed in accordance with FDA guidance for "Display Devices for Diagnostic Radiology." The reported device performance is indicated by the outcome of these tests being deemed "Equivalent" or "Same" to the predicate device, suggesting the device met the necessary performance standards to be considered substantially equivalent.

    Acceptance Criterion (Implied by Test Item)Description of TestReported Device Performance (SE Note)
    Spatial resolutionMeasurements of the transfer of information from the image data to the luminance fields at different spatial frequencies, typically by reporting the modulation transfer function. Non-isotropic resolution properties characterized by 2D measurements or along at least two representative axes (Using TG18 QC Test Pattern).Equivalent
    Pixel defectsMeasurements (count, types (e.g., sub-pixel or entire pixel, always-on, always-off), and locations (map) of pixel defects. Provided as a tolerance limit. Pixel defects can interfere with the visibility of small details.Equivalent
    ArtifactsEvaluate for image artifacts such as ghosting and/or image sticking from displaying a fixed test pattern for a period of time (Using 5x5 mosaic pattern, 64Gray / 127 Gray judgment).Same
    Temporal responseMeasurements of the temporal behavior of the display in responding to changes in image values from frame to frame. Rise and fall time constants are needed. Slow displays can alter details and contrast when large image stacks are browsed or in video, panning, and zooming modes.Equivalent
    LuminanceMeasurements of the maximum and minimum luminance that the device outputs under recommended conditions and achievable values if set to expand the range to the limit.Same
    Conformance to a grayscale-to-luminance functionMeasurements of the mapping between image values and the luminance output following a target model response for 256 or more levels.Equivalent
    Luminance at 30° and 45° in diagonal, horizontal, and vertical directions at center and four cornersMeasurements of the luminance response at off-normal viewing related to the target model for the luminance response.Equivalent
    Luminance uniformity or Mura testMeasurements of the uniformity of the luminance across the display screen.Equivalent
    Stability of luminance and chromaticity response with temperature and time of operation (on-time)Measurements of the change in luminance and chromaticity response with temperature and use time.Same
    Spatial noiseMeasurements of the spatial noise level as represented by the noise power spectrum using an appropriate ratio of camera and display pixels. Spatial noise and resolution affect how images are presented and can alter features relevant to interpretation.Equivalent
    Reflection coefficientMeasurements of the reflection coefficients of the display device. Specular and diffuse reflection coefficients can be used as surrogates for the full bidirectional reflection distribution function.Same
    Veiling glare or small-spot contrastMeasurements of the contrast obtained for small targets.Equivalent
    Color trackingChromaticity at different luminance levels of primary colors as indicated by the color coordinates in an appropriate units system (e.g., CIE u'v') and the color gamut enveloped by the primary colors.Equivalent
    Gray trackingChromaticity at different luminance levels of gray shades, including the white point, as indicated by the color coordinates in an appropriate units system.Equivalent

    2. Sample Size and Data Provenance (Test Set)

    • Sample Size: Not applicable. The "study" described is a series of non-clinical, technical performance tests on the device itself, rather than a study involving patient data or human readers. The tests involve the physical display unit.
    • Data Provenance: Not applicable. The tests are conducted on the device hardware and its performance characteristics.

    3. Number of Experts and Qualifications (Ground Truth for Test Set)

    • Number of Experts: Not applicable. There is no involvement of experts establishing ground truth for a test set in the traditional sense, as this is a device performance test. The "ground truth" for these tests comes from established industry standards and guidance (e.g., TG18 QC Test Pattern) and the technical specifications required for medical diagnostic displays.
    • Qualifications of Experts: Not applicable.

    4. Adjudication Method (Test Set)

    • Adjudication Method: Not applicable. There is no adjudication in the context of the described non-clinical performance tests. The results are based on direct measurements against predefined technical specifications or comparisons to the predicate device's expected performance.

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

    • MRMC Study Done: No. The document explicitly states: "No clinical studies were considered necessary and performed." This submission focuses on demonstrating substantial equivalence through non-clinical technical performance testing.
    • Effect Size: Not applicable, as no MRMC study was conducted.

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

    • Standalone Study Done: Yes, in a way. The tests performed are inherent to the device's standalone performance characteristics as a display monitor. The device itself (the monitor) is tested as a standalone product to ensure it meets the technical specifications for displaying medical images. While it's not an "algorithm," it assesses the fundamental output quality of the device without human interpretation being part of the performance metric.

    7. Type of Ground Truth Used

    • Type of Ground Truth: The ground truth for these non-clinical tests is derived from technical specifications, industry standards, and regulatory guidance. Specifically, reference is made to:
      • IEC 60601-1:2005/AMD1:2012 (Electrical Basic Safety and Essential Performance)
      • IEC 60601-1-2 Edition 4.0:2014 (Electromagnetic Compatibility)
      • IEC 60601-1-6:2010/A1:2013 (Usability)
      • FDA guidance: "Display Devices for Diagnostic Radiology – Guidance for Industry and Food and Drug Administration Staff, issued on October 2, 2017"
      • Specific test patterns like TG18 QC Test Pattern and 5x5 mosaic patterns are mentioned for certain measurements.

    8. Sample Size for the Training Set

    • Sample Size: Not applicable. This document pertains to the submission of a medical monitor (hardware), not an AI algorithm that requires a training set. The software validation mentioned is for the display's internal operating software, not for image analysis.

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

    • Ground Truth Establishment: Not applicable, as there is no training set for an AI algorithm discussed in this submission.
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