(51 days)
20.1-inch (51cm) Color LCD Monitor CDL2009A (CCL204) is to be used in displaying and viewing medical images for diagnosis by trained medical practitioners. It is not meant to be used for digital mammography.
CDL2009A has a multi-displaying function corresponding to the resolution from VGA 640 x 480 to UXGA 1600 x 1200. This is also compliant with VESA standard display mode.
This document describes the 510(k) premarket notification for the TOTOKU 20.1-inch (51cm) Color LCD Monitor CDL2009A (CCL204). It is important to note that this is a submission for a display device, not an Artificial Intelligence (AI) enabled device. Therefore, many of the requested categories related to AI performance, ground truth, and expert evaluation are not applicable.
Here's an analysis of the provided information:
1. A table of acceptance criteria and the reported device performance
For a medical display device, acceptance criteria typically revolve around image quality, luminance, uniformity, resolution, and adherence to display standards for diagnostic viewing. The provided document, being a 510(k) summary, does not detail specific acceptance criteria values or a direct side-by-side comparison with reported performance. Instead, it focuses on demonstrating substantial equivalence to a predicate device.
However, based on the nature of the device (a color LCD monitor for medical image display), the following are implied or commonly expected performance aspects for such a device. The "Reported Device Performance" column indicates what the summary states about the device's capabilities, rather than specific measured values against a numerical criterion.
| Acceptance Criteria (Implied/Standard for Medical Displays) | Reported Device Performance (from 510(k) Summary) |
|---|---|
| Displaying medical images for diagnosis | "to be used in displaying and viewing medical images for diagnosis by trained medical practitioners." |
| Contrast and Resolution suitable for diagnostic viewing | "multi-displaying function corresponding to the resolution from VGA 640 x 480 to UXGA 1600 x 1200." |
| Compliance with industry display standards (e.g., DICOM Part 14 Grayscale Standard Display Function for grayscale; color calibration for color) | "compliant with VESA standard display mode." (While VESA is a standard, DICOM Part 14 is generally more critical for medical image display but not explicitly mentioned here.) |
| Luminance and Uniformity | Not explicitly stated in the provided summary, but implied by substantial equivalence to a predicate medical display. |
| Color Accuracy | Not explicitly stated, but critical for color displays for medical use. |
| Absence of artifacts or defects | Implied by the need to be suitable for diagnostic viewing. |
| Power consumption and safety (electrical, emissions) | Implied by regulatory submission and general device requirements. |
2. Sample size used for the test set and the data provenance
For a medical display device, there isn't typically a "test set" of images in the same way an AI algorithm is tested. Instead, performance testing involves:
- Physical measurements: Using calibration tools and specialized equipment to measure luminance, contrast, uniformity, resolution, color accuracy, and other display characteristics.
- Observer studies (human factors): In some cases, human observers (e.g., radiologists) might evaluate the display for ergonomic factors, clarity, and image quality, though this is less common for substantial equivalence submissions for monitors if the technical specifications are benchmarked.
The provided 510(k) summary does not specify a sample size for image quality evaluation (as it's not an AI model). The evaluation of the device features and performance would have been based on technical specifications, engineering tests, and possibly human factors evaluations against predefined technical standards and predicate device performance.
Data provenance: Not applicable in the context of image data for an AI model. The "data" here refers to the device's technical specifications and measurement results.
3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts
Not applicable. "Ground truth" for a display device is established by objective, measurable technical specifications and industry standards for display performance (e.g., luminance, contrast ratios, color gamut). It does not involve expert medical readers establishing ground truth on cases.
4. Adjudication method for the test set
Not applicable. There is no "test set" of medical cases requiring adjudication for a display device.
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 is a display device, not an AI-enabled system or a diagnostic tool that assists human readers.
6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done
Not applicable. This is a display device, not an algorithm.
7. The type of ground truth used
The "ground truth" for a medical display is its physical and optical performance characteristics measured against established industry standards (e.g., DICOM Part 14 for grayscale, various color calibration standards, VESA display modes) and the specifications of an identified predicate device. These are objective engineering measurements rather than subjective expert consensus or pathology results.
8. The sample size for the training set
Not applicable. This is a hardware device, not an AI model. There is no "training set" in this context.
9. How the ground truth for the training set was established
Not applicable. There is no "training set" or "ground truth for a training set" 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).