(29 days)
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.
| Measurements | Acceptance Criteria (Implied by FDA Guidance) | Reported Device Performance |
|---|---|---|
| a. Spatial resolution | Meet FDA guidance standards | Pass |
| b. Pixel defects | Meet FDA guidance standards | Pass |
| c. Artifacts | Meet FDA guidance standards | Pass |
| d. Temporal response | Meet FDA guidance standards | Pass |
| e. Luminance | Meet FDA guidance standards | Pass |
| f. Conformance to a grayscale-to-luminance function | Meet FDA guidance standards | Pass |
| g. Luminance at 30° and 45° in diagonal, horizontal, and vertical directions at center and four corners | Meet FDA guidance standards | Pass (for 31HN713D, 32HQ713D) / N/A (for 21HQ513D, 32HL512D) |
| h. Luminance uniformity or Mura test | Meet FDA guidance standards | Pass (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 standards | Pass (for 31HN713D, 32HQ713D) / N/A (for 21HQ513D, 32HL512D) |
| j. Spatial noise | Meet FDA guidance standards | Pass (for 31HN713D, 32HQ713D) / N/A (for 21HQ513D, 32HL512D) |
| k. Reflection coefficient | Meet FDA guidance standards | Pass (for 31HN713D, 32HQ713D) / N/A (for 21HQ513D, 32HL512D) |
| l. Veiling glare or small-spot contrast | Meet FDA guidance standards | Pass (for 31HN713D, 32HQ713D) / N/A (for 21HQ513D, 32HL512D) |
| m. Color tracking | Meet FDA guidance standards | Pass |
| n. Gray tracking | Meet FDA guidance standards | Pass (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.
§ 892.2050 Medical image management and processing system.
(a)
Identification. A medical image management and processing system is a device that provides one or more capabilities relating to the review and digital processing of medical images for the purposes of interpretation by a trained practitioner of disease detection, diagnosis, or patient management. The software components may provide advanced or complex image processing functions for image manipulation, enhancement, or quantification that are intended for use in the interpretation and analysis of medical images. Advanced image manipulation functions may include image segmentation, multimodality image registration, or 3D visualization. Complex quantitative functions may include semi-automated measurements or time-series measurements.(b)
Classification. Class II (special controls; voluntary standards—Digital Imaging and Communications in Medicine (DICOM) Std., Joint Photographic Experts Group (JPEG) Std., Society of Motion Picture and Television Engineers (SMPTE) Test Pattern).