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XoranConnect is a medical imaging software system intended to display, edit, review, store, print and distribute images acquired from imaging devices such as Computed Tomography (CT), Magnetic Resonance (MR), Computed Radiography (CR), Ultrasound (US), Nuclear Medicine (NM), and other devices.

XoranConnect™ is a web-based service designed to complement point-of-care medical imaging systems by providing point-of-expertise viewing and interpretation tools. XoranConnect™ runs on standard offthe-shelf PC and networking hardware, all of which has been manufactured by third party reputable manufacturers.

The system performs these major functions.

• Off-site data storage allows user studies to be stored off-site. .
• Study viewer allows studies to be visualized and manipulated in 3D, multiplanar and other forms. .

To accommodate the major functions, the overall system architecture includes the following distinct components:

• XoranVault™ storage system (storage servers, dispatcher) .
• XoranConnect™ viewing system (study server, web server, web client) .

The storage (backup) system consists of one or more servers designed to store and serve stored imaging content on a RAID5 storage device. Imaging modality negotiates the connection and transfers study to the storage server.

Once stored, imaging data is ready to be served to the requesting clients. When a user logs into the system by visiting a XoranConnect web page, study server begins to serve the data, which in turn is displayed in the user's web browser window. Any storage server may simultaneously serve multiple requests for images.

It is the user's responsibility to ensure that the appropriate PC hardware and display device are used to run the XoranConnect™ software application. XoranConnect™ requires at all times an active Internet connection to operate. It is the user's responsibility to ensure that the connection that is being used provides the speed, stability and reliability required to utilize XoranConnect™ for any given purpose or application.

The provided text describes XoranConnect™, a web-based service for medical imaging, and its 510(k) premarket notification. However, the document does NOT contain information about specific acceptance criteria for device performance, nor does it detail any study that proves the device meets such criteria.

The 510(k) summary focuses on demonstrating substantial equivalence to predicate devices (Visage PACS/CS and NovaPACS) based on similar functions and intended use, rather than presenting a performance study with defined acceptance criteria.

Therefore, most of the requested information cannot be extracted from the provided text.

Here's a breakdown of what can be inferred from the document regarding a "study":

1. Table of acceptance criteria and reported device performance:
Not present in the document. The submission is based on substantial equivalence, not on head-to-head performance against specific criteria.

2. Sample size used for the test set and the data provenance:
Not applicable. No performance study with a test set is described.

3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts:
Not applicable. No performance study with ground truth establishment is described.

4. Adjudication method (e.g., 2+1, 3+1, none) for the test set:
Not applicable. No performance study is described.

5. Multi reader multi case (MRMC) comparative effectiveness study:
No, an MRMC comparative effectiveness study is not mentioned. The submission focuses on functional equivalence to predicate devices.

6. Standalone (i.e., algorithm only without human-in-the-loop performance) study:
Not applicable. XoranConnect™ is a PACS system designed for human interpretation, and no standalone algorithmic performance study is described.

7. The type of ground truth used:
Not applicable. No performance study requiring ground truth is described.

8. The sample size for the training set:
Not applicable. XoranConnect™ is a PACS system, not an AI/ML algorithm that typically requires a training set.

9. How the ground truth for the training set was established:
Not applicable.

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