(61 days)
The RadiForce RX240 is intended to be used in displaying and viewing digital images for diagnosis of X-ray or MRI, etc. by trained medical practitioners. The device does not support the display of mammography images for diagnosis.
The RadiForce RX240 is a color LCD monitor for viewing medical images other than those of mammography. The matrix size (or resolution) of the panel is 1200 x 1600 pixels (2MP) with a pixel pitch of 0.270 mm. Since factory calibrated display modes, each of which is characterized by a specific tone curve (including DICOM GSDF), a specific luminance range and a specific color temperature, are stored in lookup tables within the monitor, the tone curve is e.g. DICOM compliant regardless of the display controller used. RadiCS is application software to be installed in each workstation offering worry-free quality control of the diagnostic monitors including RX240 based on several QC guidelines. The RadiCS and its subset, RadiCS LE are included in this 510(k) submission as an accessory to the RadiForce RX240.
The provided text describes a 510(k) submission for a medical monitor, the EIZO RadiForce RX240. However, it does not contain information about acceptance criteria for device performance, nor a study proving it meets such criteria in the context of AI/human reader performance or standalone algorithm efficacy.
The document focuses on demonstrating substantial equivalence to a predicate device (RadiForce RS210) based on technological characteristics and intended use. The performance testing mentioned is "bench testing" comparing image quality characteristics of the proposed device with the predicate device, and validation of the overall design against safety and EMC standards. It explicitly states: "None of the tests revealed behaviors inconsistent with the expected performance."
Therefore, based on the provided input, I cannot fill out the requested table or sections related to acceptance criteria, AI performance studies, or ground truth establishment for such studies.
Here's a breakdown of what can be extracted and what is missing:
1. Table of Acceptance Criteria and Reported Device Performance
| Acceptance Criteria | Reported Device Performance |
|---|---|
| Not provided in the document. The document states "None of the tests revealed behaviors inconsistent with the expected performance," which is a general statement rather than specific, measurable acceptance criteria. | Technological Characteristics Comparison with Predicate Device: |
- Matrix size: 1200 x 1600 pixels (same)
- Active area: 324.0 mm x 432.0 mm (same)
- DICOM calibrated luminance: 400 cd/m² (higher than predicate's 150 cd/m²)
- Typical maximum luminance: 760 cd/m² (higher than predicate's 300 cd/m²)
- Backlight: LED (newly employed, mercury-free, less power, slower deterioration)
- Image display: In accordance with DICOM GSDF
- Interface: Digital (DVI or DisplayPort only, no analog)
- QC Software: Same as predicate
- Backlight Sensor (BS): Same as predicate
- Built-in Front Sensor (IFS): Enables automatic grayscale calibration (new feature)
- Overall design: Validated in accordance with internationally recognized safety and EMC standards by independent and in-house facilities. |
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 / Not provided. This information is relevant for studies involving medical image data and diagnostic performance (e.g., AI algorithms). The provided document describes a hardware device (monitor) and its quality control software. The performance testing mentioned is at the device specification level (e.g., luminance, resolution, compliance with standards), not clinical performance or diagnostic accuracy using a test set of medical 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 / Not provided. As above, this pertains to clinical validation studies involving diagnostic interpretation, which is not the focus of this 510(k) submission for a medical display monitor.
4. Adjudication method (e.g. 2+1, 3+1, none) for the test set
- Not applicable / Not provided.
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. The document does not describe an MRMC study or any AI component designed to assist human readers. The device is a display monitor.
6. If a standalone (i.e. algorithm only without human-in-the loop performance) was done
- No. The document does not describe an algorithm for standalone performance.
7. The type of ground truth used (expert consensus, pathology, outcomes data, etc)
- Not applicable / Not provided. The "ground truth" for this device's performance relates to its technical specifications and compliance with display standards (e.g., DICOM GSDF, safety/EMC standards), not clinical diagnostic accuracy.
8. The sample size for the training set
- Not applicable / Not provided.
9. How the ground truth for the training set was established
- Not applicable / Not provided.
§ 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).