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510(k) Data Aggregation
(264 days)
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
Acceptance Criteria | Device Performance (OptikView GUP2103CMI) | Supporting Information |
---|---|---|
DICOM Conformance | Passed DICOM Conformance Test | The device successfully passed a DICOM conformance test, demonstrating compliance with DICOM Part 14 GSDF standard. |
AAPM TG18 Conformance (Acceptance Test) | Passed AAPM TG18 Acceptance Test | The device successfully passed an AAPM TG18 acceptance test, indicating compliance with the AAPM TG18 standard and suitability for primary category display for medical image interpretation. |
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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