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The 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 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 for transfer of diagnostic images (the x-ray generator and the computer are not part of the submission). The functions of the YosemiteView 4343W/ YosemiteView 3643W are supported by software and the software is of Moderate level of concern. The main function of software is image acquisition and transfer. The detectors can be used for dynamic imaging (fluoroscopy) that is same as Predicate Device.

The provided document is a 510(k) Summary for the CareRay Digital Medical Technology Co., Ltd. YosemiteView 4343W/YosemiteView 3643W X-ray Flat Panel Detectors. It aims to demonstrate substantial equivalence to a predicate device, the EverestView 4343X.

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

1. Table of Acceptance Criteria and Reported Device Performance

The document does not explicitly state "acceptance criteria" in a table format with performance targets. Instead, it provides a "Comparison with the predicate device" table that lists technical specifications for both the proposed device and the predicate device. The implied acceptance is that the proposed device's performance is, at least, equivalent to or better than the predicate device.

*Note on MTF: The proposed device reports MTF at 2lp/mm (≥35) which the predicate does not. For 1lp/mm, both are ≥65. For 3lp/mm, the proposed is ≥20 while the predicate is also ≥20. The predicate reports 5lp/mm (≥7) which the proposed does not. Based on available comparable points, the proposed device meets or exceeds the predicate's reported MTF.

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

The document states "Nonclinical and clinical considerations A: The proposed devices and predicate device share most of primary product specifications including intended use, technology, material, and imaging principle, power supply method etc. The only difference is the wireless function and dimension. The difference of wireless function and dimension don't affect the technological parameters and clinical images."

This statement, coupled with the lack of details on a separate clinical image test set, suggests that a dedicated clinical image test set for comparing performance (e.g., diagnostic accuracy) was likely not used for the substantial equivalence demonstration, beyond confirming the effect of the new features (wireless function and dimension) on "technological parameters and clinical images." The report focuses heavily on technical specifications and electrical safety.

Therefore, information on sample size, country of origin, or retrospective/prospective nature of a clinical test set is not provided.

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

Given the lack of details on a dedicated clinical image test set (as discussed in point 2), there is no information provided about the number or qualifications of experts used to establish ground truth for such a set. The submission relies on "Nonclinical and clinical considerations" that attribute no significant impact from the changes.

4. Adjudication method for the test set

Similarly, because details of a clinical image test set are absent, the adjudication method is not mentioned.

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

The document describes the device as an X-ray Flat Panel Detector, which captures images. There is no mention of an AI component or a multi-reader multi-case (MRMC) comparative effectiveness study. The device's function is "image acquisition and transfer" (page 5).

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

The device is an imaging hardware component; it is not an algorithm that performs standalone diagnostic tasks. Therefore, a standalone algorithm performance study was not applicable and not performed/reported.

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

As noted in point 2, a specific clinical image test set with established ground truth types (expert consensus, pathology, outcomes data) is not detailed in this document. The submission relies on demonstrating substantial equivalence based on technical specifications and the assertion that differences in wireless function and dimension do not affect technological parameters or clinical images.

8. The sample size for the training set

The device is a hardware component (X-ray Flat Panel Detector), not an AI algorithm requiring a training set in the conventional sense. While there might have been internal testing and calibration data, the document does not refer to a "training set" in the context of machine learning, nor does it provide a sample size for such.

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

As there is no mention of an AI training set, this information is not applicable or provided.

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The 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 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 for transfer of diagnostic images. The functions of the EverestView 4343X are supported by software and the software is of Moderate level of concern. The main function of software is image acquisition and transfer and it doesn't have functions of image post-processing. The detectors can be used for dynamic imaging (fluoroscopy) that is same as Predicate Device.

The provided text does not contain information about acceptance criteria and a study proving the device meets those criteria. The document is a 510(k) summary for an X-ray Flat Panel Detector (EverestView 4343X) and focuses on demonstrating substantial equivalence to a predicate device (CareView 1800RF) based on technological characteristics and safety testing.

It does include a comparison table of technical specifications between the proposed and predicate devices, which could be interpreted as comparative performance metrics, but these are not explicitly presented as acceptance criteria for a study proving clinical effectiveness.

Therefore, I cannot provide a table of acceptance criteria and reported device performance or information regarding specific studies (sample size, data provenance, expert ground truth, adjudication methods, MRMC studies, standalone performance, training set details) as this information is not present in the provided text.

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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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