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510(k) Data Aggregation
(106 days)
5MP MONOCHROME LCD MONITOR, RADIFORCE GX530
The RadiForce GX530 is intended to be used in displaying digital images including those of digital mammography for review and analysis by trained medical practitioners.
The RadiForce GX530 is a 5MP monochrome LCD monitor for viewing medical images including those of digital mammography. The monochrome panel employs in-plane switching (IPS) technology allowing wide viewing angles. The matrix size (or resolution) of the panel is 2560 x 2048 pixel pitch is 0.165 mm, both of which are the same as those of displays approved so far for digital mammography including the predicate device, RadiForce GS10. Since factory calibrated display modes, each of which is characterized by a specific tone curve (including DICOM GSDF) and a specific luminance range, 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 GX530 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 GX530.
The provided document is a 510(k) summary for the EIZO RadiForce GX530 5MP Monochrome LCD Monitor. This document is a premarket notification to the FDA to demonstrate substantial equivalence to a predicate device, not a study evaluating the performance of AI. Therefore, it does not contain information typically found in a study that proves a device meets acceptance criteria related to AI performance.
The document discusses the technical characteristics and intended use of the monitor and compares it to a predicate device (RadiForce GS510, K062054) to establish substantial equivalence.
Here's an breakdown of the information provided, framed against your request for acceptance criteria and study details, highlighting what is and isn't present:
Context: This document is about a medical display monitor, not an AI algorithm. Therefore, many of your requested items regarding AI performance, training sets, ground truth methodology, and expert adjudication are not applicable or present in this filing.
1. Table of Acceptance Criteria and Reported Device Performance
The document does not explicitly present a table of "acceptance criteria" for a study in the way one would for an AI algorithm. Instead, it focuses on demonstrating that the RadiForce GX530 meets performance requirements by being substantially equivalent to its predicate device.
The performance characteristics discussed are primarily related to monitor specifications and functionality:
| Feature/Characteristic | Acceptance Criteria (Implicitly, by showing equivalence to predicate) | Reported Device Performance (RadiForce GX530) |
|---|---|---|
| Matrix Size (Resolution) | Must be equivalent to predicate to display digital mammography (2560 x 2048 pixels) | 2560 x 2048 pixels (Same as predicate) |
| Pixel Pitch | Must be equivalent to predicate (0.165 mm) | 0.165 mm (Same as predicate) |
| Active Area Size | Must be equivalent to predicate (337.9 mm x 422.4 mm) | 337.9 mm x 422.4 mm (Same as predicate) |
| Tone Curve Compliance | Must display images in accordance with DICOM GSDF by default | DICOM GSDF compliant, utilizing factory calibrated display modes stored in lookup tables |
| Input Video Signal | Support for DVI (predicate) | Supports DVI and DisplayPort (new, but digitally equivalent) |
| Quality Control Software | Use of appropriate QC software (RadiCS) | Same QC software (RadiCS/RadiCS LE) used as predicate, included in submission. |
| Backlight Stabilization | Implementation of Backlight Sensor (BS) | Same implementation of Backlight Sensor (BS) |
| Automatic Grayscale Calibration | Functionality for calibration, with or without human intervention | Built-in Front Sensor (IFS) enables automatic grayscale calibration, reducing human intervention. (Precision data for calibration with external vs IFS sensor provided as validation data, though specific results are not detailed here). |
| Safety and EMC Standards | Compliance with internationally recognized standards | Overall design validated in accordance with internationally recognized safety and EMC standards by independent and in-house facilities. |
| System and Performance Tests | No behaviors inconsistent with expected performance | Performed a range of system and performance tests; none revealed inconsistencies. |
2. Sample size used for the test set and the data provenance
- Not Applicable. This document describes a medical monitor, not an AI device evaluated with a test set of data. The "test set" in this context refers to the monitor's functionality and compliance, not diagnostic image data.
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 diagnostic images is not a concept applied to the evaluation of a display monitor in this context. The "truth" here relates to the monitor's adherence to technical specifications and ability to display images correctly.
4. Adjudication method for the test set
- Not Applicable. No expert adjudication of diagnostic interpretations is described, as this is a hardware device 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. This is not an AI device, so MRMC studies involving AI assistance are not relevant or present in this document.
6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done
- Not Applicable. No algorithm performance is being evaluated.
7. The type of ground truth used
- Technical Specifications and Regulatory Standards: The "ground truth" for this device's evaluation is its adherence to technical specifications, industry standards (like DICOM GSDF), and safety/EMC regulations. The basis for comparison is the predicate device's established performance. The document states "precision data of the calibration with an external sensor and with the IFS is provided as one of the validation data," indicating measurements against known photometric standards.
8. The sample size for the training set
- Not Applicable. There is no "training set" as this is not an AI algorithm.
9. How the ground truth for the training set was established
- Not Applicable. No training set for an AI algorithm exists for this device.
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