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EFAI PACS PRO is intended to be used as a Digital Imaging and Communications in Medicine (DICOM) and non-DICOM information and data management system. The EFAI PACS PRO displays, processes, stores, and transfers medical data from original equipment manufacturers (OEMs) that support the DICOM standard, with the exception of mammography. It provides the capability to store images and patient information from OEM equipment, and perform filtering, digital manipulation and quantitative measurements. The client software is designed to run on standard personal and business computers. The product is intended to be used by trained medical professionals, including but not limited to radiologists, oncologists, and physicians. It is intended to provide image and related information that is interpreted by a trained professional to render findings and/or diagnosis, but it does not directly generate any diagnosis or potential findings.

The software is a stand-alone software as medical device (Stand-alone SaMD) which provides instant services for clinicians able to use web browsers at client stations to search and view medical data of desired patients which is stored in the software. The software also provides the following visualization, annotation and quantification functionalities which can be applied to the images on the web browser at client stations.

The provided text describes a 510(k) premarket notification for the EFAI PACS PRO device. However, it does not contain specific acceptance criteria, detailed performance data, or information regarding a study design (like sample sizes, ground truth establishment, expert qualifications, or MRMC studies) that would typically be associated with proving a device meets acceptance criteria.

The document primarily focuses on demonstrating substantial equivalence to a predicate device (EFAI PACS K211257) based on its intended use, technological characteristics, and conformance to general software and usability standards.

Here's a breakdown of the requested information based on the provided text, highlighting what is present and what is missing:

1. Table of Acceptance Criteria and Reported Device Performance

This information is not explicitly stated in the provided document in the form of a table with specific quantitative acceptance criteria or reported performance metrics (e.g., accuracy, sensitivity, specificity).

The "Performance Data - Non-Clinical" section states: "Results confirm that the design inputs and performance specifications for the device are met. The EFAI PACS PRO passed the testing in accordance with internal requirements, national standards, and international standards shown below, supporting its safety and effectiveness, and its substantial equivalence to the predicate device."

However, it does not detail:

• What those "design inputs and performance specifications" are (i.e., the acceptance criteria).
• The actual "results" or specific performance values achieved by the device against these criteria.

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

This information is not provided in the document. The document mentions "non-clinical tests" but does not detail the datasets used for these tests.

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

This information is not provided. The document does not describe the establishment of a ground truth for a test set, nor does it mention any experts involved in such a process.

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

This information is not provided. There is no description of an adjudication method, as no specific test set and ground truth establishment process are detailed.

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

This information is not provided. The document makes no mention of an MRMC study or any assessment of human reader performance improvement with AI assistance. The device is described as a PACS system for displaying, processing, storing, and transferring medical data, and does not directly generate diagnoses or findings, suggesting it may not involve an AI component that directly aids in human reader interpretation for diagnostic tasks in the way an AI-CAD device might.

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

This information is not provided. The device is described as a "stand-alone software as medical device" (SaMD) and offers functionalities like visualization, annotation, and quantification. However, it is a PACS system; it is not an algorithm designed to perform diagnostic tasks independently. Thus, a "standalone" performance evaluation in the context of an AI algorithm predicting an outcome is not applicable here. The "standalone" refers to the entire software system existing on its own, not an AI component's diagnostic performance.

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

This information is not provided. There is no mention of ground truth in the document, as no specific diagnostic performance study is detailed.

8. The sample size for the training set

This information is not provided. Since no AI/ML algorithm requiring a training set for diagnostic purposes is described, details about a training set are absent.

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

This information is not provided for the same reason as point 8.

Summary of what the document does provide regarding "performance":

The document indicates that adherence to the following standards supports its safety and effectiveness and substantial equivalence:

• Software verification and validation per IEC 62304/FDA Guidance
• Application of usability engineering to medical devices Part 1 per IEC 62366-1
• Guidance on the application of usability engineering to medical devices per IEC 62366-2

This implies that the "acceptance criteria" were met through compliance with these general software development, validation, and usability standards, rather than specific quantitative diagnostic performance metrics. The device is a "Medical Image Management And Processing System" (PACS), not a CAD (Computer-Aided Detection/Diagnosis) device, which would typically require extensive clinical performance studies with specific accuracy metrics.

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