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The OptikView GUP2103CMI with QUBYX PerfectLum is intended to be used for displaying and viewing medical images, for review and analysis by trained medical practitioners.
The device can NOT be used in primary image diagnosis in mammography.
The device can NOT be used for a life-support system.
The device is intended for prescription use.

The OptikView GUP2103CMI with QUBYX PerfectLum is a 21" color display for medical viewing.
It is combined with QUBYX PerfectLum and PerfectLum remote management, a userfriendly DICOM calibration and AAPM TG18 verification software suite. The software allows setting the display function to DICOM, displaying test pattern and performing acceptance and constancy tests.

The provided document outlines the acceptance criteria and the study performed for the OptikView GUP2103CMI display device.

Here's a breakdown of the requested information:

1. Table of acceptance criteria and reported device performance

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

The document describes tests performed on the OptikView GUP2103CMI device itself. It doesn't refer to a "test set" of medical images or patient data. The tests are focused on the display's technical performance and compliance with standards. Therefore:

• Sample size for the test set: Not applicable in the context of medical images/patient data. The "sample" is the device under test.
• Data provenance: Not applicable. The tests involve measuring the display's inherent characteristics.

3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts

• Number of experts: Not applicable. Ground truth for the display's technical performance is based on established technical standards (DICOM, AAPM TG18) and objective measurements.
• Qualifications of those experts: Not applicable. The "ground truth" is defined by the standards and measurement devices. While a user interacted with the visual steps of the AAPM TG18 test, their role was to observe and respond based on the test patterns, not to establish medical ground truth.

4. Adjudication method for the test set

• Adjudication method: Not applicable. The compliance is determined by the software analyzing measurement results against predefined target values from the DICOM and AAPM TG18 standards. For the visual steps of the AAPM TG18 test, the software recorded the user's answers.

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, a multi-reader multi-case (MRMC) comparative effectiveness study was not conducted. This device is a display monitor, not an AI-powered diagnostic tool. The study focuses on the display's technical specifications and adherence to imaging standards, not on reader performance or AI assistance.

6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done

• This is not an algorithm-only device. It is a medical display. The tests performed are on the display's ability to conform to specific technical and display standards, which includes both automated measurements and visual checks by a user for certain AAPM TG18 criteria.

7. The type of ground truth used

• Ground Truth: The ground truth for the device's performance is based on established technical standards:
  • DICOM Part 14 Grayscale Standard Display Function (GSDF) for DICOM conformance.
  • AAPM Task Group 18 (TG18) standards for display acceptance and quality control.
    These standards define the expected performance and characteristics of a medical display.

8. The sample size for the training set

• Sample size for the training set: Not applicable. This device is a display monitor, not a machine learning algorithm that requires a training set of data.

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

• How the ground truth for the training set was established: Not applicable, as there is no training set for this device.

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The DIVA ZSP2105CMI with QUBYX PerfectLum is intended to be used for displaying and viewing medical images, including those of mammography, for review, analysis and diagnosis by trained medical practitioners.

The DIVA ZSP2105CMI can be used only in conjunction with QUBYX PerfectLum.

The device can not be used for a life-support system.

The device does not contact with the patient.

The device is intended for prescription use.

The DIVA ZSP2105CMI with QUBYX PerfectLum is a 21.3" monochrome display for medical viewing. It can be used for diagnostic viewing or normal reviewing purpose of medical images like computed tomography images, digitalized x-ray images, etc. It is combined with QUBYX PerfectLum and PerfectLum Remote Management, a user-friendly DICOM calibration and AAPM TG18 verification software suite. The software allows setting the display function to DICOM GSDF, displaying test patterns and performing acceptance and constancy tests according to AAPM TG18.

Here's an analysis of the provided text regarding the acceptance criteria and study for the DIVA ZSP2105CMI with QUBYX PerfectLum bundle:

1. Table of Acceptance Criteria and Reported Device Performance:

The document describes the device's compliance with two key standards rather than setting specific numerical acceptance criteria for a clinical study with patients. The performance is reported as meeting these standards.

2. Sample Size Used for the Test Set and Data Provenance:

• Sample Size: The document does not specify a "sample size" in the context of patients or medical images. The testing described focuses on a single instance of the DIVA ZSP2105CMI with QUBYX PerfectLum device.
• Data Provenance: Not applicable in the traditional sense of patient data. The tests were performed using software-generated patterns and measurements on the device itself. The tests were performed by QUBYX and verified by the University of Arizona.

3. Number of Experts Used to Establish the Ground Truth for the Test Set and Qualifications of Those Experts:

• Number of Experts: The document does not mention the use of experts to establish "ground truth" for a test set of medical images. The ground truth for the technical performance was established by measurement devices and software comparing device output to defined standards (DICOM, AAPM).
• Qualifications of Experts: Not applicable. For the visual steps of the AAPM TG18 test, it mentions "the user analyzed test patterns," but it doesn't specify if this user was a medical expert or their qualifications.

4. Adjudication Method for the Test Set:

• Adjudication Method: Not applicable. The "test set" in this context refers to the device's technical specifications and adherence to standards, which are evaluated by measurement tools and software against predefined targets, not by a panel of human adjudicators.

5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study Was Done, and Effect Size of How Much Human Readers Improve with AI vs Without AI Assistance:

• MRMC Study: No, an MRMC comparative effectiveness study was not done. The device is a medical display, not an AI algorithm designed to assist human readers directly.
• Effect Size: Not applicable.

6. If a Standalone (i.e., algorithm only without human-in-the-loop performance) Was Done:

• Standalone Performance: Not applicable. The device itself is a display monitor and calibration software. Its performance is evaluated on its ability to accurately display images according to standards, not as an AI algorithm that produces an output on its own.

7. The Type of Ground Truth Used (Expert Consensus, Pathology, Outcomes Data, etc.):

• Type of Ground Truth: The ground truth used was conformance to established technical standards:
  • DICOM Part 14 GSDF Standard: For grayscale display function.
  • AAPM TG18 Standard: For diagnostic display quality and acceptance testing.
    These standards define objective criteria for luminance, contrast, uniformity, and resolution.

8. The Sample Size for the Training Set:

• Sample Size for Training Set: Not applicable. This device is not an AI algorithm that requires a training set of data.

9. How the Ground Truth for the Training Set Was Established:

• Ground Truth for Training Set: Not applicable.

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