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510(k) Data Aggregation
(15 days)
The MD322C8 color display is intended to be used for displaying and viewing of digital images for diagnosis by trained physicians. To guarantee the display performance as specified, it must only be used for in Conjunction with NEC approved display controllers. MD322C8 cannot be used for a life-support system. This device must not be used in digital mammography. This device is designed for exclusive interconnection with IEC60601-1-1 certified equipment.
Medical Display, MD322C8 is a 31.5" Color LCD monitor that displays image for medical use. It provides 3840*2160p resolution with adjustable gamma gray scale for more precise diagnose use in CT, MRI, HIS, and PACS.
This document is a 510(k) summary for the NEC Display Solutions MD322C8 31.5" Color LCD Monitor, intended for medical diagnostic imaging. The document primarily focuses on demonstrating substantial equivalence to a predicate device (MD210C3). Therefore, it does not contain a comprehensive description of acceptance criteria met through a standalone study with detailed clinical performance metrics, expert reviews, and sample sizes as typically seen for AI/ML-driven medical devices.
However, based on the provided text, I can extract information related to display performance testing and a comparison to a predicate device.
Here's the breakdown of the information requested, with observations based on the provided text:
Acceptance Criteria and Study to Prove Device Meets Acceptance Criteria
1. A table of acceptance criteria and the reported device performance
The document does not explicitly present quantitative acceptance criteria in a table format with corresponding quantitative device performance results for all tests. It lists specific "Display Testing" categories and then summarizes the outcome qualitatively.
| Acceptance Criteria Category (Implied by Test) | Reported Device Performance (Qualitative) |
|---|---|
| Display Reflection | "Test results showed minor differences between MD322C8 and MD210C3, however these differences are minor and were within the acceptable range of DICOM part 14." (This statement applies to all listed display tests) |
| Luminance Response | "Test results showed minor differences between MD322C8 and MD210C3, however these differences are minor and were within the acceptable range of DICOM part 14." |
| Luminance Uniformity | "Test results showed minor differences between MD322C8 and MD210C3, however these differences are minor and were within the acceptable range of DICOM part 14." |
| Display Resolution | "Test results showed minor differences between MD322C8 and MD210C3, however these differences are minor and were within the acceptable range of DICOM part 14." |
| Display Noise | "Test results showed minor differences between MD322C8 and MD210C3, however these differences are minor and were within the acceptable range of DICOM part 14." |
| Veiling Glare | "Test results showed minor differences between MD322C8 and MD210C3, however these differences are minor and were within the acceptable range of DICOM part 14." |
| Display Chromaticity | "Test results showed minor differences between MD322C8 and MD210C3, however these differences are minor and were within the acceptable range of DICOM part 14." |
| Miscellaneous Tests | "Test results showed minor differences between MD322C8 and MD210C3, however these differences are minor and were within the acceptable range of DICOM part 14." |
| DICOM Conformance | The device conforms to "DICOM part 14" (stated in the comparison table indirectly and explicitly in the summary). Performance was within the acceptable range of DICOM part 14. |
2. Sample size used for the test set and the data provenance
The document does not specify a "sample size" in terms of clinical cases or patient data, as this is a display monitor. The "test set" would refer to the specific unit(s) of the MD322C8 monitor that underwent the listed "Display Testing." The document does not specify the number of monitors tested.
Data provenance is not applicable in the context of this device (a monitor). The tests are performance evaluations of the hardware itself.
3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts
Not applicable. Ground truth, in this context, would involve objective measurements of display characteristics against established technical standards (like DICOM part 14), rather than expert interpretation of medical images. The testing relies on instrumentation and adherence to technical specifications.
4. Adjudication method for the test set
Not applicable. Adjudication methods are relevant for subjective human interpretations, especially in clinical studies or expert consensus. The testing of a display monitor against technical standards does not involve such human-based adjudication.
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. This document pertains to a medical display monitor, not an AI/ML diagnostic or assistive device. Therefore, an MRMC study comparing human readers with and without AI assistance is not relevant and was not conducted.
6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done
Not applicable. This device is a display monitor and does not involve an algorithm with standalone performance. Its function is to accurately render images for human interpretation.
7. The type of ground truth used (expert consensus, pathology, outcomes data, etc.)
The ground truth for the display tests would be established technical standards and specifications, such as DICOM Part 14 for grayscale display function and other industry standards for display performance metrics (e.g., luminance, chromaticity, resolution). These are objective, measurable standards, not medical ground truth derived from expert consensus, pathology, or outcomes data.
8. The sample size for the training set
Not applicable. This device is a display monitor, not a machine learning model, so there is no concept of a "training set" for an algorithm.
9. How the ground truth for the training set was established
Not applicable, as there is no training set for this device.
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