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Storage, management, and display of patient data, diagnostic data, videos, and images from computerized ophthalmic diagnostic imaging devices.

AXIS Image Management System is a browser-based ophthalmic image management system designed for storage, retrieval, and review of images, videos, and reports originating from ophthalmic imaging devices.

AXIS Image Management System and the predicate device are software systems that work on standard network infrastructure provided by the user. Such infrastructure may include a server, network, and computing devices.

AXIS Image Management System provides a central database of patient information and exam image history. The AXIS software resides on a server provided by the user and interfaces with networked imaging instruments. Users utilize their existing browser to access the AXIS software to review images, videos, and reports.

Images can be obtained from diagnostic devices in a variety of industry-standard formats including PDF, JPEG, DCM, and AVI.

This document is a 510(k) premarket notification for the AXIS Image Management System. It primarily outlines the substantial equivalence to a predicate device and does not contain detailed acceptance criteria and study results in the typical format for performance studies of AI-powered medical devices.

Here's an analysis based on the provided text, addressing the points where information is available or noting its absence:

1. Table of Acceptance Criteria and Reported Device Performance

The document does not provide a table of acceptance criteria for specific performance metrics (e.g., sensitivity, specificity, accuracy) because the device is an Image Management System, not a diagnostic or AI-powered analytical tool. Its performance is assessed functionally and through its compliance with standards.

The closest equivalent to "acceptance criteria" are the functional characteristics and compliance with industry standards, which are met by the device.

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

Not applicable. This device is an image management system, not one that performs analysis on a dataset of patient images requiring performance metrics like sensitivity/specificity. The "test set" would refer to the testing done during software verification and validation, which is typically a functional and system-level test, not a clinical data test set. The document does not specify details of the samples used in such testing.

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

Not applicable. As this device is not performing a diagnostic task, there is no "ground truth" to be established by experts in the context of clinical performance like disease detection. The "ground truth" for its functionality would be whether it performs its stated functions (storage, retrieval, display, etc.) correctly according to its design specifications.

4. Adjudication method

Not applicable, for the same reasons as points 2 and 3.

5. If a multi-reader multi-case (MRMC) comparative effectiveness study was done

No, an MRMC comparative effectiveness study was not done. The document explicitly states: "Clinical Performance Data: None required or submitted." As this is an image management system, its primary function is to store, manage, and display data, not to interpret or diagnose, and therefore, it does not involve human readers interpreting cases with or without AI assistance in the way a diagnostic AI would.

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

This refers to the performance of a diagnostic or analytical algorithm. The AXIS Image Management System is not such an algorithm; it is an infrastructure system. Its "standalone" performance refers to its ability to perform its specified functions (e.g., DICOM compliance, data storage, retrieval) without human intervention in the data processing flow, but this is a functional test, not a diagnostic performance test. The document states that "Performance testing was conducted on AXIS Image Management System as part of the software verification and validation and was found to perform as intended," which implies standalone functional testing.

7. The type of ground truth used

For an image management system, the "ground truth" is typically its functional correctness and adherence to standards. For example, a successful ground truth for a storage function would be that data stored can be retrieved accurately and completely. For DICOM compliance, the ground truth is successful interoperability as per the standard. The document states it is "DICOM-compliant as stipulated in its DICOM Conformity Statement" and that it "was found to perform as intended" through software verification and validation.

8. The sample size for the training set

Not applicable. The AXIS Image Management System is not an AI/ML device that requires training data.

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

Not applicable, as there is no training set for this type of device.

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