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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.

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.

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.

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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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.

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.

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.

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

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

The provided text describes the 510(k) submission for the LG Electronics 32HQ713D Medical Monitor, a device indicated for displaying radiological images. It's important to note that this document does not contain a study proving the device meets acceptance criteria in the way a clinical or AI performance study would. Instead, it demonstrates substantial equivalence to predicate devices through technical comparisons and non-clinical performance testing.

The acceptance criteria are implicitly defined by the functional characteristics and performance parameters expected of a medical monitor for radiological images, particularly for mammography and digital breast tomosynthesis. The performance is demonstrated by comparing these characteristics to established predicate devices and by confirming adherence to relevant standards and guidance documents.

Here's the information extracted and organized as requested:

1. Table of Acceptance Criteria and Reported Device Performance

The "acceptance criteria" here are framed as demonstrating equivalence to predicate devices and compliance with relevant standards and guidance. The reported performance is the claim of equivalence based on the measurements.

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

• Sample Size: Not applicable in the context of an "AI test set." This submission describes the testing of a medical monitor (hardware/software), not an AI algorithm. The tests conducted (e.g., spatial resolution, luminance) are on the physical device itself. The document does not specify the number of units tested, but this would typically be a small, representative sample of manufactured devices.
• Data Provenance: Not applicable as there is no patient data involved in these non-clinical performance tests of a display monitor. The tests are based on standard test patterns and measurement methodologies.

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

Not applicable. Ground truth in the context of a medical display's performance relates to its physical characteristics and adherence to technical specifications and industry standards (e.g., DICOM Part 14 for Grayscale Standard Display Function). These are objectively measurable and do not require expert human interpretation to establish a "ground truth" in the way an AI diagnostic model would.

4. Adjudication Method for the Test Set

Not applicable. See point 3.

5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study was done, and if so, what was the effect size of how much human readers improve with AI vs without AI assistance

No MRMC study was performed or described. This submission is for a medical monitor, not an AI-based diagnostic aid that assists human readers.

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

Not applicable. As noted, this is a medical display, not an AI algorithm. Its "performance" is its ability to accurately and consistently render images, which is tested directly.

7. The Type of Ground Truth Used

The "ground truth" for this device's performance is objective technical specifications and industry standards for medical displays. These include:

• Physical measurements (e.g., luminance, resolution, pixel defects).
• Compliance with electrical safety, EMC, and usability standards (e.g., IEC 60601 series).
• Conformance to display functions like the Greyscale Standard Display Function (implicitly referenced through the "conformance to a grayscale-to-luminance function" test).
• The performance of legally marketed predicate devices, which serve as a benchmark for "substantial equivalence."

8. The Sample Size for the Training Set

Not applicable. This device is a medical monitor, not an AI system that requires a "training set" of data.

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

Not applicable. See point 8.

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