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The Fundus Photo Digital Imaging System Model CFD-440 Model is intended to capture, archive, and display digital images of the retina and surrounding areas of the eye.

The Fundus Photo Digital Imaging System Model CFD-440 is an automated imaging device used in conjunction with an ophthalmic fundus camera that requires minimal intervention during the capture of an image. The system is simple to use and requires nominal training for a user to become proficient. Like the predicate device, the Fundus Photo Digital Imaging System Model CFD-440 is an accessory attachment comprised of a digital imaging camera or cameras, computer hardware and software platform intended to capture, store, archive, and display images acquired by the fundus camera.

The provided text describes the Fundus Photo Digital Imaging System Model CFD-440, a device intended to capture, archive, and display digital images of the retina and surrounding areas of the eye. It is an accessory attachment that works with existing ophthalmic fundus cameras. The 510(k) summary focuses on demonstrating substantial equivalence to a predicate device (Zeta Diagnostic Retinal Imaging System, K02216), rather than detailing specific acceptance criteria in terms of clinical performance metrics for the CFD-440 itself.

The document states: "Fundus Photo has performed software verification, validation and performance tests. The results indicate that the Fundus Photo Digital Imaging System Model CFD-440 is substantially equivalent to the software standards exhibited by the predicate device." However, no specific performance metrics, acceptance criteria, or the details of these performance tests are provided beyond this general statement.

Therefore, many of the requested details about acceptance criteria and the study proving the device meets them cannot be extracted from this document, as the submission focuses on demonstrating equivalence in intended use, principles of operation, and technological characteristics rather than quantitative performance against defined acceptance criteria.

Here's a breakdown of what can and cannot be answered based on the provided text:

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

• Acceptance Criteria: Not explicitly stated in the document in terms of quantitative performance metrics (e.g., resolution, accuracy, sensitivity, specificity). The primary "acceptance criteria" for the 510(k) submission appears to be demonstrating substantial equivalence to the predicate device.
• Reported Device Performance: No specific quantitative performance data is provided. The document states that "software verification, validation and performance tests" were done and "the results indicate that the Fundus Photo Digital Imaging System Model CFD-440 is substantially equivalent to the software standards exhibited by the predicate device."

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

• Not specified in the provided text.

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/Not specified as no such test set or ground truth establishment is detailed in the submission.

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

• Not applicable/Not specified.

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, as this device is a digital imaging system, not an AI or diagnostic aid that assists human readers.

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

• Not applicable. The device is an imaging system, not a standalone diagnostic algorithm. Its performance is tied to the images it captures, stores, and displays, which are then interpreted by a human user.

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

• Not applicable/Not specified. The submission focuses on substantial equivalence in function and technical characteristics, not diagnostic accuracy against a ground truth.

8. The sample size for the training set

• Not applicable/Not specified. The device is not an AI/ML algorithm that requires a "training set" in the conventional sense. Its development involved software verification and validation, but not machine learning training.

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

• Not applicable/Not specified.

In summary, the provided 510(k) submission for the Fundus Photo Digital Imaging System Model CFD-440 is focused on demonstrating substantial equivalence to a predicate device based on intended use, principles of operation, and technological characteristics (hardware and software functions). It does not present detailed performance studies against specific clinical acceptance criteria, nor does it involve aspects like AI algorithms, human-reader studies, or ground truth establishment in the context of diagnostic accuracy.

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