(149 days)
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.
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
Here's a breakdown of the acceptance criteria and study information based on the provided document, addressing each of your points.
It's important to note that this document is a 510(k) summary for a medical monitor (32HL512D) intended for displaying radiological images. It is not an AI/algorithm-based diagnostic device. Therefore, many of your questions related to AI performance, ground truth, expert consensus, MRMC studies, and training sets will not be applicable to this submission. The "device" in this context is a monitor, not a diagnostic algorithm.
Acceptance Criteria and Device Performance for LG 32HL512D Medical Monitor
The acceptance criteria for this device (a medical monitor) are primarily related to its technical specifications for displaying medical images and compliance with electrical safety and EMC standards. The "performance" is demonstrated by meeting these specifications and showing compliance.
1. Table of Acceptance Criteria and Reported Device Performance
| Parameter | Acceptance Criteria (from predicate or general medical display requirements) | Reported Device Performance (LG 32HL512D) |
|---|---|---|
| Indications for Use | Display radiological images for review, analysis, and diagnosis by trained medical practitioners. Not intended for mammography. | 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. (Matches exactly) |
| Electrical Safety | Compliance with IEC 60601-1:2005/AMD1:2012 | Complies with IEC 60601-1:2005/AMD1:2012 |
| Electromagnetic Compatibility (EMC) | Compliance with IEC 60601-1-2 Edition 4.0:2014 | Complies with IEC 60601-1-2 Edition 4.0:2014 |
| Usability | Compliance with IEC 60601-1-6:2010/A1:2013 | Complies with IEC 60601-1-6:2010/A1:2013 |
| Software Validation (if applicable) | Designed and developed according to a software development process; verified and validated (for MODERATE level of concern software) | Software was designed and developed according to a software development process and was verified and validated. (MODERATE level of concern) |
| Resolution | (Implied comparison to predicate/PACS needs) | 3,840 x 2,160 pixels |
| Screen Size | (Implied comparison to predicate/PACS needs) | 718.2 x 414.3 mm (or 31.5" diagonal through module description) |
| Display Technology | TFT LCD with specific display capabilities for medical images. | TFT Liquid Crystal Display module with LED Backlight unit, 30-pin eDP port, 4 lane eDP interface, supports 3840 x 2160 UHD mode, 10-bit drivers. |
| Pixel Pitch | (Implied comparison to predicate/PACS needs) | 0.18159 x 0.18159 mm |
| Input Video Signals | Standard video inputs for medical imaging systems. | DisplayPort x 2, HDMI x 1 |
Note: The document focuses on demonstrating substantial equivalence to a predicate device rather than setting explicit quantifiable acceptance thresholds for all performance parameters in the context of a new, unique claim. Its performance is accepted if it is shown to be as safe and effective as the predicate, despite technological differences. The "reported device performance" are its specifications and compliance with standards.
Regarding the Study Proving Device Meets Acceptance Criteria:
The document states: "No clinical studies were considered necessary and performed." This is crucial. This is a submission for a medical display monitor, not a diagnostic algorithm or device that makes a clinical determination. Therefore, the "study" proving it meets acceptance criteria is primarily non-clinical testing and a comparison to a predicate device.
2. Sample Size Used for the Test Set and Data Provenance:
- Sample Size: Not applicable in the context of patient data or algorithm performance. The "test set" for a monitor would be the monitor itself undergoing various electrical, EMC, and display characteristic tests.
- Data Provenance: Not applicable. The testing is on the physical monitor, not a dataset.
3. Number of Experts Used to Establish Ground Truth for the Test Set and Their Qualifications:
- Not applicable. There is no "ground truth" to establish in the sense of medical diagnoses for this device. The device itself is the display. The "experts" involved would be engineers and metrologists conducting the technical measurements and ensuring compliance with display standards and safety regulations.
4. Adjudication Method for the Test Set:
- Not applicable. This concept pertains to resolving discrepancies in expert interpretations of medical data, which is not relevant for a medical monitor.
5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study was done:
- No, not performed. This type of study is relevant for evaluating the impact of AI algorithms or new diagnostic methods on human reader performance. As this is a medical monitor, an MRMC study is not part of its substantial equivalence demonstration.
6. If a Standalone (i.e., algorithm only without human-in-the-loop performance) was done:
- No, not applicable. This device is a monitor, not a standalone diagnostic algorithm.
7. The Type of Ground Truth Used:
- Not applicable. There is no 'ground truth' in the clinical diagnostic sense for a medical display monitor. The "ground truth" for its performance is its measured technical specifications and compliance with relevant industry and safety standards (e.g., DICOM Part 14 for display characteristics, IEC standards for safety).
8. The Sample Size for the Training Set:
- Not applicable. This device does not use a training set as it is not an AI/machine learning algorithm.
9. How the Ground Truth for the Training Set Was Established:
- Not applicable. No training set exists for this device.
§ 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).