(30 days)
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.
| Measurements | Acceptance Criteria | Reported Device Performance (32HL512D, 31HN713D, 32HQ713D) |
|---|---|---|
| a. Conformance to a grayscale-to-luminance function | Conformance to a grayscale-to-luminance function (implied by FDA guidance requirements) | Pass |
| b. Luminance uniformity or Mura test | Luminance 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 noise | Spatial noise (implied by FDA guidance requirements) | Pass |
| e. Veiling glare or small-spot contrast | Veiling 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.
§ 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).