(52 days)
The Nio 2MP Medical Flat Panel Display System is intended to be used in displaying and viewing digital images, excluding digital mammography, for review by trained medical practitioners.
The Nio 2MP Medical Flat Panel Display System is intended to be used as a tool in displaying and viewing digital images (excluding digital mammography) for review and analysis by trained medical practitioners.
The Nio 2MP device is a digital image display system
The Nio 2MP device consists of components to provide high resolution visualization of digital images.
The provided K042660 document is a 510(k) summary for the Barco Nio 2MP Medical Flat Panel Display System, which is an image display system. The document establishes substantial equivalence to a predicate device (Nio 2MP Medical Grayscale Display System, K040039).
This type of device (a medical image display system) does not typically undergo clinical studies with human subjects or AI performance evaluations against a ground truth in the same way an AI-powered diagnostic device would. Its performance is primarily assessed through technical specifications related to image quality and display functionality. The "acceptance criteria" for a display system are typically defined by industry standards and technical performance metrics rather than clinical accuracy metrics like sensitivity or specificity.
Therefore, many of the requested points regarding clinical study design, ground truth, expert adjudication, MRMC studies, and training set information are not applicable to this type of device based on the provided document.
Here's an analysis based on the information available:
1. Table of Acceptance Criteria and Reported Device Performance:
The document does not explicitly list "acceptance criteria" in a table format with corresponding "reported device performance." However, for a medical display system, the performance is typically assessed against technical specifications to ensure it can accurately display medical images. The critical "performance" for a display device revolves around its ability to present images with sufficient resolution, luminance, contrast, and stability.
The substantial equivalence argument implies that its technical performance is comparable to the predicate device (K040039). Key performance characteristics for a display system like this would typically include:
| Acceptance Criteria/Performance Metric (Implied) | Reported Device Performance (Implied from substantial equivalence and device type) |
|---|---|
| Resolution | 2MP (Megapixels), as per device name "Nio 2MP" |
| Display Type | Flat Panel Display System |
| Display Modalities | Digital images (excluding digital mammography) |
| Intended Use Environment | Review by trained medical practitioners |
| Image Quality / Gray Scale Resolution | Comparable to predicate device K040039 (Nio 2MP Medical Grayscale Display System) |
| Stability and Consistency | Expected to meet industry standards for medical displays |
| Compliance with Standards | Expected to comply with relevant medical device and display standards |
2. Sample size used for the test set and the data provenance:
- Not Applicable. This is a medical image display system, not a diagnostic algorithm. Performance is assessed through technical measurements and comparison to established display standards, not through a "test set" of medical images for diagnostic accuracy.
3. 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" established by experts for a display system in the context of diagnostic accuracy. Its function is to clearly and accurately display existing medical images.
4. Adjudication method (e.g., 2+1, 3+1, none) for the test set:
- Not Applicable. No test set or expert adjudication for diagnostic performance.
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:
- Not Applicable. This device is a display system, not an AI-powered diagnostic tool. There is no AI component, and thus no MRMC study to assess the impact of AI assistance on human readers.
6. If a standalone (i.e., algorithm only without human-in-the-loop performance) was done:
- Not Applicable. This is a hardware display system, not a standalone algorithm.
7. The type of ground truth used (expert consensus, pathology, outcomes data, etc.):
- Not Applicable. The "ground truth" for a display system's functionality relates to its technical specifications and proper calibration for medical image viewing, not diagnostic accuracy based on clinical findings.
8. The sample size for the training set:
- Not Applicable. This is a display system, not a machine learning algorithm requiring a training set.
9. How the ground truth for the training set was established:
- Not Applicable. This is a display system, not a machine learning algorithm.
Summary of the Study (Implied from the 510(k) and Device Type):
The "study" for a device like the Nio 2MP Medical Flat Panel Display System would primarily consist of technical performance verification and validation against technical specifications and existing industry standards for medical image displays. The 510(k) process relies on demonstrating substantial equivalence to a predicate device (K040039, Nio 2MP Medical Grayscale Display System). This means that Barco would have provided data to FDA demonstrating that the Nio 2MP Medical Flat Panel Display System met comparable technical specifications for image quality, resolution, luminance, contrast, uniformity, and stability as the predicate device, ensuring it is safe and effective for its intended use of displaying digital medical images (excluding mammography). This typically involves:
- Bench testing: Measuring technical parameters like luminance, contrast ratio, uniformity, color accuracy (if applicable), viewing angles, and spatial resolution.
- Compliance with standards: Demonstrating adherence to relevant standards such as DICOM Part 14 (Grayscale Standard Display Function) to ensure consistent image presentation.
- Comparison to predicate device: Providing evidence that the new device's technical specifications and performance are equivalent to the legally marketed predicate device.
The provided document does not contain details of such technical studies, as it is a summary for the 510(k) clearance, which confirms substantial equivalence rather than detailing the full technical report.
§ 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).