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Imagys (KSNRMAVWRxx, KSNERDxx) is a medical solution for the upload, the secure transfer, the management, the viewing, the reviewing, the storage and archiving of imaging data, and the related documentations, acquired from a variety of imaging devices. Imagys can also support the management of the imaging parts of a clinical trial workflow including the following steps : quality control, data processing and audit trails. Imagys runs on any standard PC and servers compliant with the Imagys specifications. Typical end users are trained medical professionals and clinical trial actors.

The imaging data can be CT (Computed Tomography), MR (Magnetic Resonance), CR (Computed Radiography), NM (Nuclear Medecine), PET (Positon Emission Tomography), SC (Secondary Capture), US (Ultrasound), XA (Angiographic), video and more DICOM, or others imaging standards, data accepted by the Imagys solution.

It is the user responsibility to check that the ambient luminosity conditions, the images compression ratio and the interpretation monitor specifications are consistent with a clinical diagnostic use of the data.

This device is not indicated for mammography use. Lossy compressed mammography-images and digitized film screen images must not be used for primary image interpretations. Mammography images may only be interpreted using an FDA approved monitor that offers at least 5 mega pixel resolution and meets other technical specifications approved by the FDA.

Imagys is a computing and software solution designed by experts in medical imaging and telecommunications for the collection, quality control, processing, analysis and visualization of imaging data. Imagys can help to execute olinical trials with secure transfer, management, viewing, printing, storage and archiving of data.

Based on the provided text, the Keosys Imagys device is a Picture Archiving and Communication System (PACS). The 510(k) summary focuses on its functionality for managing, viewing, and archiving medical imaging data, particularly for clinical trials.

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

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

The provided 510(k) summary does not explicitly state specific acceptance criteria (e.g., quantitative metrics like sensitivity, specificity, or image quality thresholds) or specific reported device performance metrics in a formal table or detailed section.

The document refers to "specifications that are documented in a Software Test Plan" and mentions "Performance and functional testing are an integral part of Keosys's software development process." However, these specifications and their outcomes are not detailed in this public summary.

Therefore, for this device (a PACS system), the "acceptance criteria" appear to be broadly focused on its ability to:

• Collect, quality control, process, analyze, and visualize imaging data.
• Securely transfer, manage, view, print, store, and archive data.
• Support clinical trial workflows (quality control, data processing, audit trails).
• Run on standard PCs and servers compliant with Imagys specifications.
• Handle various DICOM and other imaging standards data (CT, MR, CR, NM, PET, SC, US, XA, video).

The "reported device performance" is implicitly that the device meets these functional requirements as evidenced by the FDA's substantial equivalence determination to predicate devices. There are no quantitative performance metrics such as accuracy, precision, or processing speed reported in the document.

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

The document does not specify the sample size of any test set used in a performance study, nor does it provide details on the data provenance (country of origin, retrospective/prospective). It generally discusses "Performance and functional testing" without outlining the datasets used.

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)

The document does not mention the use of experts to establish ground truth for any test set, nor does it specify their number or qualifications. The device is a PACS for data management and visualization, not an AI diagnostic tool requiring expert ground truth for diagnostic accuracy.

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

The document does not describe any adjudication method as no expert evaluation requiring adjudication is mentioned for establishing ground truth on a 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

The document does not mention a multi-reader multi-case (MRMC) comparative effectiveness study. This is consistent with the device being a PACS system for data management, not an AI-powered diagnostic aid meant to improve human reader performance.

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

The document does not describe any standalone algorithm performance testing. The Imagys is described as a "computing and software solution" for data management and visualization, implying human interaction for its intended use, rather than a standalone AI algorithm generating diagnostic outputs.

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

Given that Imagys is a PACS system designed for data management and viewing, rather than a diagnostic tool, the concept of "ground truth" for its performance evaluation would likely relate to the integrity and accuracy of data storage, retrieval, display, and transfer. For example, ensuring that an image stored is identical to an image retrieved, or that image metadata is correctly handled. However, the document does not explicitly define the type of ground truth used for its testing, beyond stating "Imagys is tested according to the specifications that are documented in a Software Test Plan."

8. The sample size for the training set

The document does not mention a training set sample size. This device is a PACS system, which typically relies on software engineering principles and functional testing rather than machine learning training sets.

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

Since no training set is mentioned (as the device is not an AI diagnostic model), there is no information on how ground truth for a training set was established.

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