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This Product is indicated for use in displaying radiological images for review, analysis, and diagnosis by trained medical practitioners. The display is not intended for mammography.

RadiForce MX217 is a color LCD monitor for viewing medical images other than those of mammography. The color panel employs in-plane switching (IPS) technology allowing wide viewing angles and the matrix size (or resolution) is 1,200 x 1,600 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 the RadiForce MX217 based on the QC standards and guidelines and is capable of quantitative tests and visual tests defined by them. The RadiCS and its subset, RadiCS LE, are included in this 510(k) submission as an accessory to the RadiForce MX217. RadiCS is of Minor level of concern and that it's being used unchanged from the predicate software. RadiCS supports the functions of the monitor RadiForce MX217 and it's not a medical imaging software.

The provided text is a 510(k) summary for the EIZO RadiForce MX217 display device. This document focuses on demonstrating substantial equivalence to a predicate device (RadiForce MX216) rather than proving the device meets specific acceptance criteria based on a study with a test set, ground truth, or expert consensus in the way an AI/CADe device would.

The document discusses performance testing of the monitor itself, which involves technical measurements of display characteristics. It does not describe a study involving medical images, human readers, or AI algorithms for diagnostic purposes.

Therefore, many of the requested items (e.g., sample size for test set, number of experts, adjudication method, MRMC study, standalone performance, ground truth for training/test set) are not applicable to this document as it pertains to a display device, not a diagnostic AI or image processing software that produces a diagnostic output.

However, I can extract the information related to the device's technical specifications and the bench tests conducted to show its performance regarding those specifications.

Here's an attempt to answer the questions based only on the provided text, highlighting where the information is not available or not applicable given the nature of the device (a display monitor):

1. A table of acceptance criteria and the reported device performance

The document states:
"The test results showed that the RadiForce MX217 has display characteristics equivalent to those of the predicate device, RadiForce MX216."
And:
"Besides, the display characteristics of the RadiForce MX217 meet the pre-defined criteria when criteria are set."

However, it does not explicitly list the "pre-defined criteria" or "acceptance criteria" in a quantitative table with corresponding performance values for each criterion. It only lists the types of tests performed.

Types of Bench Tests Performed:

2. Sample size used for the test set and the data provenance

• Sample Size: Not applicable. This is a display device, not an AI/CADe system. The "test set" would be the device itself undergoing various physical and photometric measurements. The document refers to "bench tests" performed on the RadiForce MX217.
• Data Provenance: Not applicable. The "data" are measurements from the device, not clinical imaging 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 in the context of clinical images or diagnostic outcomes is not relevant for testing a display monitor's technical performance. The "ground truth" for these tests would be the established technical standards (e.g., TG18 guidelines, DICOM GSDF) that the device is measured against.

4. Adjudication method for the test set

• Not applicable. Adjudication methods (e.g., 2+1, 3+1) are used for resolving discrepancies in expert interpretations of clinical data, which is not relevant for the technical testing of a display monitor.

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 a display device, not an AI/CADe system. An MRMC study is not relevant.

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 (expert consensus, pathology, outcomes data, etc)

• The "ground truth" for the performance tests of this display device refers to established industry standards and guidelines for display quality, such as:
  • "Guidance for Industry and FDA Staff: Display Devices for Diagnostic Radiology" (September 28, 2022)
  • "Assessment of Display Performance for Medical Imaging Systems by AAPM Task Group 18 (TG18 guideline)"
  • DICOM GSDF (Grayscale Standard Display Function)

8. The sample size for the training set

• Not applicable. This is a display device, not an AI/machine learning model. There is no concept of a "training set" in this context.

9. How the ground truth for the training set was established

• Not applicable. As there's no training set, there's no ground truth to establish for it.

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