(27 days)
PACSmate MMD=4300C/4300CX is intended to be used in displaying and viewing digital images for diagnosis of X-ray or MRI, etc. by trained medical practitioners. PACSmate MMD-4300C/4300CX does not support the display of mammography images for diagnosis.
The PACSmate MMD-4300C/4300CX is a 30" monochrome/color LCD display for medical image viewing.4 Mega pixel medical grade LCD monitor with high resolutions.
The provided document describes a 510(k) summary for the PACSmate MMD-4300C/4300CX medical display. This device is a monitor used for displaying medical images, not an AI-powered diagnostic tool. Therefore, many of the requested categories related to AI performance, such as sample sizes for test sets, expert adjudication, MRMC studies, standalone performance, and ground truth establishment for AI models, are not applicable to this submission.
The "study that proves the device meets the acceptance criteria" refers to bench testing demonstrating the device's conformance to applicable standards and its substantial equivalence to a predicate device.
1. Table of Acceptance Criteria and Reported Device Performance
| Acceptance Criteria Category | Specific Criteria/Standard | Reported Device Performance |
|---|---|---|
| Operating Specification | Conformance to applicable operating specifications | Meets applicable standards |
| Safety | Conformance to IEC 60601-1 | Conforms to IEC 60601-1 |
| EMC Requirements | Conformance to IEC 60601-1-2 | Conforms to IEC 60601-1-2 |
| Intended Use | Displaying and viewing digital images for diagnosis of X-ray or MRI etc. (excluding mammography) | Same as predicate device |
| Technological Characteristics | Similar to predicate device (COLOR LCD MONITOR, FLEXSCAN MX300W K073340) | Any differences do not raise new questions of safety or effectiveness |
2. Sample size used for the test set and the data provenance (e.g. country of origin of the data, retrospective or prospective)
Not applicable. This is a medical display device, not an AI diagnostic algorithm that processes image data from a test set. The performance evaluation is based on engineering specifications and adherence to standards, not analysis of clinical images.
3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts (e.g. radiologist with 10 years of experience)
Not applicable. Ground truth for clinical images is not established for this type of device. The assessment is based on technical specifications and safety standards.
4. Adjudication method (e.g. 2+1, 3+1, none) for the test set
Not applicable. Adjudication methods are relevant for evaluating diagnostic accuracy using human readers or AI algorithms on clinical cases, which is not the purpose of this device's submission.
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. An MRMC study was not done as this is a medical display device and does not involve AI assistance for human readers in a diagnostic capacity.
6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done
No. This device is a display monitor and does not involve any standalone algorithm performance.
7. The type of ground truth used (expert concensus, pathology, outcomes data, etc)
Not applicable. The "ground truth" for this device's performance evaluation is based on engineering specifications, recognized industry standards (IEC 60601-1, IEC 60601-1-2), and comparison to a legally marketed predicate device's characteristics.
8. The sample size for the training set
Not applicable. This device does not use a training set as it is not an AI algorithm.
9. How the ground truth for the training set was established
Not applicable. This device does not use a training set.
§ 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).