Search Results

The Virtue software receives image data from medical scanning devices, such as CT or MRI, or from image archives and performs viewing, image manipulation, communication, printing and quantification of images.

The Diagnosoft Virtue is software that runs on Windows-based operating systems to view and analyze MR images of the heart in DICOM format.

Here's an analysis of the provided text regarding the acceptance criteria and study for the Diagnosoft, Inc. Virtue device:

Based on the provided K111833 510(k) summary, the device Virtue is a software for viewing and analyzing MR images of the heart. The document does not contain specific acceptance criteria or details of a study that proves the device meets such criteria in terms of clinical performance or diagnostic accuracy. Instead, it focuses on demonstrating substantial equivalence to predicate devices for its intended use as a "Picture archiving and communications system" that performs viewing, image manipulation, communication, printing, and quantification of images.

Here's a breakdown of the requested information based on the provided text:

Acceptance Criteria and Reported Device Performance

Study Information

1. 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 provide any details about a test set, its sample size, or the provenance of any data used for testing.

2. 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 any test set, experts, or ground truth establishment.

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

   • The document does not mention any test set or adjudication method.

4. 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:

   • A MRMC study was not conducted or reported. The Virtue device is described as software for viewing and analysis, not an AI-assisted diagnostic tool in the sense of providing an interpretation or assisting a reader in making a diagnosis beyond image manipulation and quantification.

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

   • This document does not describe a standalone performance study. The device is a "Picture archiving and communications system" designed for human interaction.

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

   • The document does not describe the use of any ground truth, as no clinical performance study for diagnostic accuracy is detailed.

7. The sample size for the training set:

   • The document does not mention any training set, as it's not describing an AI/machine learning model in the context of diagnostic assistance.

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

   • The document does not mention a training set or ground truth establishment for it.

Summary of what the document focuses on:

The K111833 submission for Diagnosoft, Inc. Virtue is a "traditional 510(k)" for a Picture Archiving and Communications System (PACS) software. The evidence provided and accepted by the FDA for this type of device typically revolves around demonstrating "substantial equivalence" to existing legally marketed predicate devices in terms of:

• Intended Use: The Virtue's intended use is broad, covering viewing, image manipulation, communication, printing, and quantification of images from CT or MRI.
• Technological Characteristics: Its operational and fundamental characteristics are compared to predicate devices like the Philips Easy Vision Workstation and Harp 2.06.
• Safety and Effectiveness: The conclusion is that "any differences do not affect the product's safety or effectiveness." This often relies on software verification and validation activities (V&V) to ensure functions work as designed, adhere to software engineering best practices, and don't introduce new risks, rather than a clinical performance study with diagnostic endpoints.

Therefore, for this specific device and submission type, the absence of detailed clinical study performance data, acceptance criteria, and ground truth information is expected as it falls under a different regulatory pathway than novel diagnostic AI algorithms.

Ask a specific question about this device