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VitreaView is a medical image viewing and information application that provides access, through the Internet and within the enterprise, to multi-modality softcopy medical images, reports and other patient-related information, that may be hosted within disparate archives and repositories for review, communication and reporting of DICOM and non-DICOM data. VitreaView is not intended for primary diagnosis.

Display monitors used for reading medical images for diagnostic purposes must comply with applicable regulatory approvals and with quality control requirements for their use and maintenance.

Lossy compressed mammographic images and digitized film screen images must not be reviewed for primary image interpretations. Mammographic images may only be interpreted using an FDA approved monitor that offers at least 5 MP resolution and meets other technical specifications reviewed and accepted by FDA.

VitreaView is a cross-browser, cross-platform zero-footprint universal image viewer solution capable of displaying both DICOM and non-DICOM medical images. VitreaView enables referring clinicians and other medical professionals with access to patients' medical images in a seamless way, with integrations into their Electronic Health Record (EHR), Electronic Medical Record (EMR), and Health Information Exchange (HIE)

VitreaView offers medical professionals a universal viewer for accessing imaging data in context with reports from enterprise patient health information databases, fosters collaboration, and provides workflows and interfaces appropriate for referring physicians and clinicians. IT departments will not have to incur time to install client systems, due to the zero-footprint, zero download nature of VitreaView. VitreaView offers scalability to add new users as demand grows, may be deployed in a virtualized environment, and is designed to be integrated with enterprise patient health information databases.

Some of the general features include:

• 2D multi-modality review of data .
• . Basic 2D review tools (zoom, pan, measure)
• Easy study navigation .
• Comparative review .
• Displays of DICOM and non-DICOM images .
• A scalable, virtualizable infrastructure .
• Cross-platform viewing capabilities (Windows, Mac OS, etc.) .
• Leveraging of next-generation protocols for image viewing (i.e. MINT) .
• Single sign-on . .
• EMR integration ●

The provided text is a 510(k) summary for VitreaView, a medical image viewing software. However, it does not contain specific acceptance criteria, a detailed study protocol for performance claims, or quantitative data demonstrating device performance against such criteria.

Instead, the document focuses on:

• Substantial Equivalence: Arguing that VitreaView is substantially equivalent to a predicate device (Cedara WebAccess™) based on similar indications for use and "essentially identical technological characteristics."
• Design and Testing Philosophy: Stating that the software was "designed, developed and tested according to written procedures" and that "Software testing was completed to insure the new feature function according to the requirements and interacts without impact to existing functionality."

Since the document explicitly states, "The test results support a determination of substantial equivalence," but does not provide a summary of said test results, specific acceptance criteria, or performance metrics, I cannot fulfill most of your requests directly from the provided text.

Here's what I can extract and what I cannot:

1. Table of Acceptance Criteria and Reported Device Performance:

2. Sample Size Used for the Test Set and Data Provenance:

• Sample Size: Not specified.
• Data Provenance: Not specified (e.g., country of origin, retrospective/prospective).

3. Number of Experts Used to Establish Ground Truth and Qualifications:

• Number of Experts: Not specified.
• Qualifications of Experts: Not specified.

4. Adjudication Method:

• Not specified.

5. Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study:

• Not mentioned or implied. The document focuses on the device's functionality and equivalence to a predicate, not comparative effectiveness with human readers.

6. Standalone Performance Study (Algorithm Only):

• This is an image viewer and information distribution application, not an AI algorithm for diagnosis. Therefore, a "standalone algorithm performance" study as typically understood for AI diagnostic tools would not be applicable or expected. The document implies functional testing of the software itself.

7. Type of Ground Truth Used:

• Given it's a viewer that integrates with EHR/EMR and displays DICOM/non-DICOM data, the "ground truth" for its functional testing would likely revolve around:
  • Correct display of various image formats (DICOM, non-DICOM).
  • Accurate functionality of basic 2D review tools (zoom, pan, measure).
  • Successful navigation and comparative review.
  • Integration capabilities (EMR, HIE).
  • Data integrity during transfer and display.
• However, the document does not explicitly state the type of ground truth used for performance validation.

8. Sample Size for the Training Set:

• As a viewer and not an AI/ML algorithm that learns from data, there isn't a "training set" in the conventional sense for this device. Functional testing would involve various types of medical images and data, but not a dataset for model training.

9. How Ground Truth for the Training Set Was Established:

• Not applicable for a non-AI/ML device.

In summary: The provided 510(k) document is a regulatory submission focused on demonstrating substantial equivalence. It confirms that internal software testing was performed to ensure functionality, but it does not provide the detailed public study results, acceptance criteria, or performance metrics typically requested for a detailed AI/ML device analysis. The device itself is a medical image viewer, not an AI diagnostic tool, so many of the questions (e.g., training set, reader studies) are not directly applicable.

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