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The GE CardiacVX for MRI is an analytical software tool, which provides reproducible tools for the review and reporting of medical images. CardiacVX can import medical images from a MR system and display them in a viewing area on the computer screen. The viewing area allows the access to multiple studies and series of multi-slice, multi-phase images. Multi-phase sequences of images can be displayed in a cine mode to facilitate visualization.

A report input interface is also available. Measurement tools on the report interface make it possible to quickly and reliably fill out a complete clinical report of an imaging exam. Available tools include: point, distance, area, and volume measurement tools such as ejection fraction, cardiac output, end-diastolic volume, end-systolic volume, and volume flow measurements.

Semi-automatic tools are available for left ventricular contour detection, valve plane detection, vessel contour detection for flow analysis, signal intensity analysis for myocardium and infarct sizing measurement, and T2 star analysis.

The results of the measurement tools are interpreted by the physician and can be communicated to referring physicians.

When interpreted by a trained physician these tools may be useful in supporting the determination of a diagnosis.

CardiacVX is a post-processing analytical software application, which provides tools for the review and reporting of cardiac MR datasets. Measurement tools on the report interface include: point, distance, area, and volume measurements (including ejection fraction, cardiac output, end-diastolic volume, end-systolic volume, and volume flow measurements). Semi-automatic tools are available for left ventricular contour detection, valve plane detection, vessel contour detection for flow analysis, signal intensity analysis for myocardium and infarct sizing measurement, T2 Star analysis, and patent foramen ovale (PFO) analysis.

The GE CardiacVX for MRI is an analytical software tool, which provides reproducible tools for the review and reporting of medical images. Cardiac VX can import medical images from a MR system and display them in a viewing area on the computer screen. The viewing area allows the access to multiple studies and series of multi-slice, multiphase images. Multi-phase sequences of images can be displayed in a cine mode to facilitate visualization.

A report input interface is also available. Measurement tools on the report interface make it possible to quickly and reliably fill out a complete clinical report of an imaging exam. Available tools include: point, distance, area, and volume measurement tools such as ejection fraction, cardiac output, end-diastolic volume, end-systolic volume, and volume flow measurements.

Semi-automatic tools are available for left ventricular contour detection, valve plane detection, vessel contour detection for flow analysis, signal intensity analysis for myocardium and infarct sizing measurement, and T2 Star analysis.

The provided text describes a 510(k) premarket notification for the GE Healthcare CardiacVX device, a post-processing analytical software application for cardiac MR datasets. However, it does not contain specific acceptance criteria, reported device performance metrics, or details of a comprehensive study proving the device meets acceptance criteria.

The document primarily focuses on establishing substantial equivalence to predicate devices and detailing the device's description, indications for use, and non-clinical tests (quality assurance measures).

Therefore, based only on the provided text, I cannot complete the requested tables and information.

Here's a breakdown of what can be extracted and what is missing:

What can be extracted:

• Non-Clinical Tests / Quality Assurance Measures: The document lists several quality assurance measures applied to the development, which are considered non-clinical tests. These include Risk Analysis, Requirements Reviews, Design Reviews, Testing on unit level (Module verification), Integration testing (System verification), Performance testing (Verification), Safety testing (Verification), and Simulated use testing (Validation). However, specific performance metrics or acceptance criteria for these tests are not provided.
• Data Provenance for Clinical Images (used for verification and validation testing):
  • Images from GE Healthcare facilities under a non-significant risk investigation for internal volunteer scanning.
  • Multi-vendor anonymized MR contrast-enhanced images obtained from a third-party clinical research study.
• Type of Ground Truth used for Clinical Images: Not explicitly stated, but for "internal volunteer scanning" and "third-party clinical research study," it's generally assumed that expert interpretation or a gold standard (e.g., pathology, clinical outcome for some studies, or expert consensus) would be used. However, the document does not specify how the ground truth was established for these particular images or their purpose beyond "verification and validation testing."
• Ground Truth for Training Set (implicitly): The document mentions "clinical images that were used for the completion of verification and validation testing." It's possible these same images or a subset were used for training/development, but the document doesn't explicitly state a "training set" or how its ground truth was established.

What is missing and cannot be provided from the text:

• A table of acceptance criteria and the reported device performance: This is the most significant missing piece. The document states "Performance testing (Verification)" was done, but gives no details about what performance was measured, what the acceptance criteria were, or what the results were.
• Sample sizes used for the test set: While it mentions "clinical images" were used, it doesn't quantify the sample size of these images for testing.
• Number of experts used to establish the ground truth for the test set and their qualifications: Not mentioned.
• Adjudication method for the test set: Not mentioned.
• Multi reader multi case (MRMC) comparative effectiveness study information: Not mentioned. The document only mentions the device being interpreted by a trained physician, but not a study comparing performance with and without AI assistance.
• Standalone (algorithm-only) performance: While the device is a "software application," the performance details are not provided in a standalone manner. The indications for use state "The results of the measurement tools are interpreted by the physician," implying human-in-the-loop.
• Sample size for the training set: Not mentioned.
• How the ground truth for the training set was established: Not mentioned.

Conclusion based on provided text:

While the document confirms that verification and validation testing using clinical images were performed and that quality assurance measures were applied, it does not provide the specific details required to answer the prompt regarding acceptance criteria, reported performance, sample sizes for training/test sets, ground truth establishment, expert qualifications, or comparative effectiveness studies. These details would typically be found in a more comprehensive study report or a different section of the 510(k) submission, not in this 510(k) summary.

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