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The DELL UP3017 with QUBYX PerfectLum is intended to be used for displaying and viewing medical images, for review and analysis by trained medical practitioners.

The DELL UP3017 can be used only in conjunction with QUBYX PerfectLum.

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 does not contact with the patient.

The device is intended for prescription use.

The DELL UP3017 with QUBYX PerfectLum is a 30" color display for medical viewing. It provides 2560 x 1600 resolution with an adjustable Look Up Table and a 10 bit panel. 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.

Here's the breakdown of the acceptance criteria and study information based on the provided text:

1. Table of Acceptance Criteria and Reported Device Performance

2. Sample Sized Used for the Test Set and Data Provenance

• Sample Size (Test Set): Not explicitly stated. The text mentions "the display device" (singular) having passed the tests, implying testing was performed on one or more units of the DELL UP3017. However, no specific number is provided for how many individual displays were tested.
• Data Provenance: The tests were performed by QUBYX Software Technologies Inc. The University of Arizona also verified compliance for both current and predicate devices, suggesting some level of independent verification or historical data. The data is prospective, generated specifically for this submission.

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

• Number of Experts: Not explicitly stated. For the visual components of the AAPM TG18 test, the text mentions "the user analyzed test patterns." This "user" could be a single technician or multiple, but details on their qualifications are not provided.
• Qualifications of Experts: Not explicitly stated.

4. Adjudication Method for the Test Set

• Adjudication Method: Not applicable. The tests are objective measurements and visual assessments against a standard, not a consensus-based adjudication of subjective findings from multiple readers. The software analyzes results against defined target values.

5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study was Done

• MRMC Study: No, an MRMC comparative effectiveness study was not done. This submission focuses on the display device's technical compliance with standards, not its impact on human reader performance with or without AI assistance.

6. If a Standalone (Algorithm Only Without Human-in-the-Loop Performance) Study was Done

• Standalone Study: Yes, in effect. The DICOM and AAPM compliance tests are standalone evaluations of the display's technical performance and adherence to established standards, without a human interpretation loop as the primary measure of effectiveness. The "algorithm" here refers to the display and the PerfectLum software's ability to render images and perform calibrations/verifications according to specifications.

7. Type of Ground Truth Used

• Ground Truth: Industry standards and specifications:
  • DICOM Part 14 GSDF (Grayscale Standard Display Function) for luminance response and image fidelity.
  • AAPM TG18 (American Association of Physicists in Medicine Task Group 18) for display quality control and acceptance testing, which includes measurement and visual criteria.

8. Sample Size for the Training Set

• Sample Size (Training Set): Not applicable. This device is a medical display and calibration software, not an AI algorithm that undergoes a "training" phase with a dataset in the typical machine learning sense. The software's functionality is based on programmed algorithms and calibration profiles, not learned from a training set.

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

• Ground Truth for Training Set: Not applicable, as there is no "training set" in the context of an AI algorithm. The display and software are designed and verified against established industry standards (DICOM, AAPM) which serve as the reference for correct performance.

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