(80 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.
The provided text describes a 510(k) premarket notification for a medical monitor, 24HR513C, and its comparison to predicate devices, but it does not contain information about acceptance criteria or a study proving the device meets those criteria in the context of clinical performance or AI algorithm effectiveness.
The document primarily focuses on demonstrating substantial equivalence to predicate medical monitors based on technological characteristics and non-clinical performance (electrical safety, EMC, software validation, and display performance measurements).
Therefore, I cannot provide the requested information for acceptance criteria and a study proving the device meets them, as it is not present in the given text.
Here's what I can extract from the provided text, indicating what is not available:
1. Table of Acceptance Criteria and Reported Device Performance:
No specific "acceptance criteria" for clinical performance are mentioned, nor is there a study reporting device performance against such. The document discusses technological characteristics of the monitor itself and its compliance with certain standards for electrical safety, EMC, and software validation.
The "Measurements" table under "Non-Clinical Test summary" (pages 9-10) describes performance items for the display, but these are general display characteristics and not explicitly stated as "acceptance criteria" with quantitative targets met by a device study. Instead, they are evaluated for "Equivalence" or "Same" to predicate devices.
| Measurements | Description (as in text) | Reported Device Performance / Equivalence Statement |
|---|---|---|
| a. Spatial resolution | Measurements of the transfer of information from the image data to the luminance fields at different spatial frequencies of interest typically done by reporting the modulation transfer function. Non-isotropic resolution properties should be characterized properly by providing two-dimensional measurements or measurements along at least two representative axes. (Using TG18 QC Test Pattern) | Equivalent |
| b. Pixel defects | Measurements (count, types (e.g., sub-pixel or entire pixel, always-on, always-off), and locations (map) of pixel defects. This is typically provided as a tolerance limit. Pixel defects can interfere with the visibility of small details in medical images. | Equivalent |
| c. Artifacts | Evaluate for image artifacts such as ghosting and/or image sticking from displaying a fixed test pattern for a period of time. (Using 5x5 mosaic pattern, 64Gray / 127 Gray judgment) | Same |
| d. Temporal response | Measurements of the temporal behavior of the display in responding to changes in image values from frame to frame. Since these transitions are typically not symmetric, rise and fall time constants are needed to characterize the system. Slow displays can alter details and contrast of the image when large image stacks are browsed or in video, panning, and zooming modes. | Equivalent |
| e. Luminance | Measurements of the maximum and minimum luminance that the device outputs as used in the application under recommended conditions and the achievable values if the device is set to expand the range to the limit. | Same |
| f. Conformance to a grayscale-to-luminance function | Measurements of the mapping between image values and the luminance output following a target model response for 256 or more levels. | Equivalent |
| g. Color tracking | Chromaticity at different luminance levels of primary colors as indicated by the color coordinates in an appropriate units system (e.g., CIE u'v') and the color gamut enveloped by the primary colors. | Equivalent |
2. Sample size used for the test set and data provenance:
- Not Applicable. No test set for clinical performance is mentioned. The non-clinical tests relate to the monitor's display characteristics and software validation. Data provenance for these technical tests is not specified (e.g., country of origin, retrospective/prospective).
3. Number of experts used to establish the ground truth for the test set and qualifications:
- Not Applicable. No clinical test set with ground truth established by experts is mentioned. The device is a medical monitor, not an AI diagnostic tool that requires expert ground truth for image interpretation.
4. Adjudication method for the test set:
- Not Applicable. As no clinical test set is mentioned, no adjudication method is relevant.
5. If a multi-reader multi-case (MRMC) comparative effectiveness study was done, and its effect size:
- No. The document explicitly states: "No clinical studies were considered necessary and performed." This device is a medical monitor, not an AI-powered diagnostic aide, so an MRMC study comparing human readers with and without AI assistance is not relevant to its clearance.
6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done:
- Not Applicable. The device is a medical monitor. This question pertains to AI algorithms, which are not described here.
7. The type of ground truth used:
- Not Applicable. No clinical ground truth (expert consensus, pathology, outcomes data) is mentioned as no clinical studies were performed. The non-clinical tests rely on technical specifications and established standards.
8. The sample size for the training set:
- Not Applicable. There is no mention of a "training set" as this device is a medical monitor, not an AI model requiring a training dataset.
9. How the ground truth for the training set was established:
- Not Applicable. As no training set is mentioned, this information is not relevant.
In summary, the provided document focuses on the technical specifications and non-clinical testing of a medical monitor to demonstrate its substantial equivalence to previously cleared devices. It explicitly states that "No clinical studies were considered necessary and performed," indicating that the type of performance data and acceptance criteria you're asking about (which generally relate to diagnostic accuracy or clinical utility) are not part of this 510(k) submission.
§ 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).