Search Results
Found 1 results
510(k) Data Aggregation
(24 days)
Barco N.V.
The display is intended to be used for displaying and viewing digital images (excluding digital mammography) for review and analysis by trained medical practitioners.
The No Color 8MP (MDNC-8132) is a medical computer display designed for general radiology applications. The device can also be used for home reading in radiology. The display is a high-resolution LCD monitor with characteristics that are important for accurate medical image review: high luminance, good luminance uniformity, good luminance stability. The medical display comes with special image-enhancing technologies to ensure consistent brightness over the display, noise-free images (=good luminance uniformity), ergonomic reading and automated compliance with DICOM and other medical image quality standards and guidelines. These technologies help the radiologist to make a swift and accurate diagnosis. The displays can be used optionally with the downloadable QAWeb Enterprise software, listed under D332294 as a class 1 device with product code LHO. QAWeb Enterprise is a calibration software that is intended as a quality assurance software for the displays. QAWeb Enterprise software helps to keep the display DICOM compliant. The display can be used optionally with the downloadable Intuitive Workflow Tools, cleared in K191845 as a class 2 device with product code PGY. The Intuitive Workflow Tools are accessories for image enhancement on diagnostic displays: SpotView and AAM – Application Appearance Manager. The display can be used with or without the Barco MXRT display controller boards.
The provided document is a 510(k) summary for the Barco Nio Color 8MP (MDNC-8132) medical display. It details the device, its intended use, and a comparison to a predicate device (Nio Color 2MP, MDNC-2521) to demonstrate substantial equivalence.
Based on the information provided, here's an analysis of the acceptance criteria and the study proving the device meets them:
Crucially, this document does not describe a study involving AI or human reader performance. It describes a comparison of a medical display device to a predicate device based on technical specifications and bench testing. Therefore, many of the requested points related to AI, human readers, ground truth establishment, and training sets are not applicable to this submission.
Acceptance Criteria and Reported Device Performance
The acceptance criteria for this device appear to be based on demonstrating "similar characteristics" and "equivalence" to the predicate device MDNC-2521 across various physical and performance metrics for a medical display. The general acceptance is that the modifications "did not reveal new issues of safety and performance" compared to the cleared predicate device.
Table of Acceptance Criteria and Reported Device Performance
Acceptance Criteria (Bench Test Category) | Reported Device Performance (MDNC-8132 vs. MDNC-2521) |
---|---|
Spatial resolution MTF | "similar characteristics" / "equivalent" |
Pixel defects, Artifacts | "similar characteristics" / "equivalent" |
Temporal Response | "similar characteristics" / "equivalent" |
Maximum and Minimum Luminance | "similar characteristics" / "equivalent" |
Luminance response, Conformance to DICOM GSDF | "similar characteristics" / "equivalent" |
Angular Dependency of Luminance | "similar characteristics" / "equivalent" |
Luminance uniformity | "similar characteristics" / "equivalent" |
Reflection coefficient Display Reflectance incl. Specular, Diffuse & Haze coefficients | "similar characteristics" / "equivalent" |
Veiling glare or small-spot contrast | "similar characteristics" / "equivalent" |
Color tracking | "similar characteristics" / "equivalent" |
EMC and Safety standards compliance | Compliant |
Environmental tests (climate, mechanical, software) | Passed |
Study Details (as applicable to a medical display submission, not AI)
Given that this is a submission for a medical display device demonstrating substantial equivalence to a predicate, and not an AI/software as a medical device (SaMD), the following points are largely not applicable or interpreted within the context of hardware testing.
-
Sample size used for the test set and the data provenance:
- The test set consists of the Barco Nio Color 8MP (MDNC-8132) device itself. The "sample size" is essentially n=1 (one type of device being tested). There isn't a "data set" in the traditional sense of medical images or patient data.
- Data provenance: Not applicable in the sense of patient data. The tests were performed on the physical device as per "Guidance for Industry and FDA Staff: Display Devices for Diagnostic Radiology", issued in 2022.
-
Number of experts used to establish the ground truth for the test set and the qualifications of those experts:
- Not applicable. There is no "ground truth" to be established by experts in the context of diagnostic performance on images, as this is a display device. The "truth" here is whether the display's physical and photometric characteristics meet predetermined engineering and regulatory standards (e.g., DICOM GSDF conformance) and are equivalent to the predicate. This is typically verified by specialized testing equipment and procedures.
-
Adjudication method (e.g. 2+1, 3+1, none) for the test set:
- Not applicable. Adjudication is relevant for expert agreement on medical findings, not for objective physical measurements of a display.
-
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 was not done. This is a submission for a medical display, not an AI device. The document explicitly states: "No animal testing or clinical testing has been performed."
-
If a standalone (i.e. algorithm only without human-in-the-loop performance) was done:
- No, this was not done. This is a display device, not an algorithm.
-
The type of ground truth used (expert consensus, pathology, outcomes data, etc.):
- Not applicable in the medical context. The "ground truth" for this device's performance are the established technical specifications and performance characteristics outlined in industry standards (like DICOM) and the FDA guidance for display devices. The comparison is made against the performance of a legally marketed predicate device.
-
The sample size for the training set:
- Not applicable. This device does not use a "training set" as it is a hardware display, not an AI algorithm.
-
How the ground truth for the training set was established:
- Not applicable. (See point 7).
Summary of the Study:
The study proving the device meets the acceptance criteria is a series of bench tests conducted on the Nio Color 8MP (MDNC-8132) display. These tests were performed according to the "Physical Laboratory Testing instructions in 'Guidance for Industry and FDA Staff: Display Devices for Diagnostic Radiology'" (2022). The purpose was to demonstrate that the MDNC-8132 possesses "similar characteristics" and is "equivalent" in performance to the predicate device, the Nio Color 2MP (MDNC-2521), across various critical display parameters such as spatial resolution, luminance, uniformity, reflection, and color tracking. The document concludes that these tests "did not reveal new issues of safety and performance" and confirmed its substantial equivalence to the predicate. Additionally, compliance with EMC and Safety standards, and passing environmental tests, contributed to the conclusion of substantial equivalence. No clinical or animal testing was performed, as the
demonstration of equivalence was based solely on technical and performance bench testing.
Ask a specific question about this device
Page 1 of 1