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The CareView 1800RF detector is indicated for digital imaging solution designed for providing general radiographic diagnosis of human anatomy. It is intended to replace radiographic film/screen systems in all general-purpose diagnostic procedures. This product is not intended for mammography applications.

The CareView 1800RF detector is a class of radiography X-ray flat panel detector that has an imaging area of 434 mm × 434 mm. The detector communicates by a wired connection (Giga-bit Ethernet communication mode).

The detector functions by intercepting X-ray photons. Then the scintillator emits visible spectrum photons that illuminate an array of photo detectors (a-Si) that create electrical signals. The electrical signals are then digitally converted to display an image on the monitor.

The detector should be connected to a computer and X-ray generator to digitize X-ray images and transfer radiography diagnostics. The x-ray generator, an essential part of a full x-ray system, is not part of the subject medical device.

The CareView 1800RF detector can be used for dynamic imaging (fluoroscopy).

The provided document is a 510(k) premarket notification for the CareView 1800RF X-ray Flat Panel Detector. It aims to demonstrate substantial equivalence to a predicate device, CareView 1800Le (K193173), and a reference device, 1717FCC (K210985).

The document states that clinical images are not necessary for the current submission, and that successful results of bench testing should be sufficient to show substantial equivalence for the subject device. This implies that the acceptance criteria are primarily based on non-clinical performance benchmarks and that no clinical study involving human subjects or expert readers was conducted for this submission to prove device performance against acceptance criteria in a clinical context.

Therefore, many of the requested details about acceptance criteria derived from clinical studies, expert involvement, and ground truth establishment cannot be extracted from this document because such studies were explicitly stated as not necessary for this 510(k) submission.

However, the document does provide information regarding the technical specifications of the device and its predicate/reference devices, which implicitly serve as performance benchmarks for substantial equivalence based on bench testing.

Here's a breakdown of the information that can be extracted:

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

Since no clinical study with explicit acceptance criteria for diagnostic performance is provided, the closest relevant information is the comparison of technical specifications between the proposed device and its predicate/reference devices. The "acceptance criteria" here are essentially "comparable technical specifications."

2. Sample size used for the test set and the data provenance (e.g. country of origin of the data, retrospective or prospective):

Not applicable. The submission explicitly states "Clinical images are not necessary for the current submission. Successful results of bench testing should be sufficient...". Therefore, no clinical test set was used. The substantial equivalence is based on bench testing for electrical safety, EMC, and comparison of technical specifications.

3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts (e.g. radiologist with 10 years of experience):

Not applicable. No clinical test set or human evaluation study was conducted.

4. Adjudication method (e.g. 2+1, 3+1, none) for the test set:

Not applicable. No clinical test set.

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:

Not applicable. The device is a flat panel detector, not an AI-powered diagnostic tool. Furthermore, no clinical studies were performed.

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

Not applicable. The device is a flat panel detector, not an algorithm, and no clinical studies were done.

7. The type of ground truth used (expert consensus, pathology, outcomes data, etc):

Not applicable. No clinical studies were done, so no ground truth for diagnostic accuracy was established. The "ground truth" for the technical comparisons would be the specifications and performance characteristics of the predicate and reference devices, as determined by their respective manufacturers and validated through their own testing protocols.

8. The sample size for the training set:

Not applicable. This is a hardware device (X-ray Flat Panel Detector), not an AI algorithm requiring a training set.

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

Not applicable. No training set was used.

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