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CloudVue is a software application that displays medical image data to aid in diagnosis for healthcare professionals. It performs operations relating to the transfer, storage, display, and measurement of image data.

CloudVue allows users to perform image manipulations, including window/level, rotation, measurement and markup.

CloudVue provides 2D display, Multi-Planar Reformatting and 3D visualization of medical image data, and mobile access to images.

CloudVue displays both lossless and lossy compressed images. For lossy images, the medical professional user must determine if the level of loss is acceptable for their purposes. Display monitors or mobile devices used for reading medical images for diagnostic purposes must comply with applicable regulatory approvals and with quality control requirements for their use and maintenance. For mobile diagnostic usage only when a full workstation is not available.

Usage for mammography is for reference and referral only.

CloudVue is a software application that allows for the display of medical image data within a web browser without installing client software. Conceptually, the application comprises two components: the web viewer and the web server. The server is installed on any computer that meets the minimum system requirements and is configured to communicate with a DICOM archive. The server is capable of DICOM and DICOMweb communication, which allows the connected DICOM archive to exist on a physical server or in the cloud, giving institutions the flexibility to choose a system infrastructure that is best suited to their needs.

CloudVue provides fast and secure access to full-fidelity CR, CT, DX, HC, IVUS, MR, NM, OP, OPT, OT, PT, SC, US, and XA images using Chrome, Safari, Firefox, or Edge web browsers. With interactive features, such as: multi-study viewing, multi-monitor support, customized screen and tool layouts, annotation saving and loading, measurement drawing and calibration, reference lines, key images, multi-planar reformatting (MPR), MIP, VR rendering, and image link sharing, CloudVue is a feature-rich solution that informs diagnostic decision-making by healthcare professionals.

CloudVue also supports these same features across the following devices: Windows 10 and higher, macOS X and higher, iPad Pro 200 generation and higher, and higher. This level of portability allows healthcare professionals to access their medical image data anytime, anywhere.

The display is not part of the subject device, CloudVue, however, is an essential component of a fullyfunctional imaging system. The end user will view the medical images on the display monitor of their choice.

The provided text is a 510(k) summary for the CloudVue device. It states that no clinical testing was required to support the safety and effectiveness of the subject device. Therefore, there is no study provided in this document that proves the device meets specific acceptance criteria based on clinical performance.

The document focuses on demonstrating substantial equivalence to a predicate device (eUnity) based on technological characteristics and intended use.

Here's an analysis of the information provided within the scope of the request, acknowledging the absence of a clinical study:

1. Table of Acceptance Criteria and Reported Device Performance:

Since no clinical study was conducted for establishing acceptance criteria related to a specific diagnostic performance outcome, there isn't a table in the traditional sense for acceptance criteria. The "performance" described pertains to functional and technical equivalence.

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

• Sample Size: Not applicable. No clinical test set was used for a performance study. "Verification and validation activities" were conducted, but specific sample sizes for these internal tests are not detailed as they were not clinical performance studies.
• Data Provenance: Not applicable. No patient data or clinical data provenance is mentioned as part of a performance study.

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

• Not applicable. As no clinical performance study was conducted, there was no independent test set requiring ground truth establishment by experts.

4. Adjudication method for the test set:

• Not applicable. No clinical test set was used for a performance study.

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:

• No. The document explicitly states "No clinical testing was required to support safety and effectiveness of the subject device." The CloudVue device is a "medical image processing software" that aids in, but does not provide, a diagnosis. It does not incorporate AI for diagnostic assistance, therefore, an MRMC comparative effectiveness study comparing human readers with and without AI assistance was not performed and is not relevant to this device's stated function.

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

• No. This device is an image display and manipulation software, not an AI algorithm that provides a standalone diagnostic output. Its function is to provide tools for healthcare professionals to aid in diagnosis.

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

• Not applicable. For the verification and validation activities mentioned, the "ground truth" would have been defined by engineering requirements and expected functional outputs, not by clinical expert consensus, pathology, or outcomes data, as it was not a diagnostic accuracy study.

8. The sample size for the training set:

• Not applicable. The CloudVue device is described as medical image processing software for display and manipulation, not a machine learning or AI model that requires a training set of data.

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

• Not applicable. As there is no training set for an AI/ML model, there's no ground truth to establish for it.

In summary: The provided document is a 510(k) summary for a Picture Archiving and Communications System (PACS) component (medical image display software). It demonstrates substantial equivalence to a predicate device based on technical and functional characteristics, and explicitly states that no clinical performance testing was required. Therefore, the detailed information requested regarding clinical studies, experts, ground truth, and AI performance metrics is not present in this submission.

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