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The Supernova C5 is intended for use as a diagnostic imaging device which can produce transverse, sagittal, coronal and oblique cross-sectional images of the internal structure of the human head, body or extremities. The images produced by MRI system reflect the spatial distribution of protons (hydrogen nuclei) exhibiting magnetic resonance. The NMR properties that determine the image appearance are proton density, spin-lattice relaxation time (T1), spin-spin relaxation time (T2), and flow. When interpreted by a trained physician, these images provide information that can be useful in diagnosis determination

The Supernova C5 is a 0.35T permanent magnet MRI system. It is composed of Magnet and Magnet Enclosure, RF Coils , Patient Couch, System Cabinet, computer system. The system software based on Windows XP or Windows 7 is an interactive program with user-friendly interface. Its functions cover scanning control, image reconstruction and image/archive management and maintenance.

The provided text is a 510(k) summary for the Supernova C5 MRI System. This document focuses on demonstrating substantial equivalence to a predicate device rather than presenting specific acceptance criteria and detailed study results in the manner requested. The document does not contain the level of detail needed to complete all aspects of the request.

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

1. Table of Acceptance Criteria and Reported Device Performance:

The document doesn't explicitly state quantitative acceptance criteria for image quality or clinical performance that the device must meet beyond compliance with recognized consensus standards. It lists various standards (IEC 60601-1, IEC 60601-2-33, MS 1-2008 to MS 9-2008, NEMA PS3.1-3.20 (2011)) that the device has been designed to comply with. These standards often contain performance requirements (e.g., for SNR, geometric distortion, uniformity, acoustic noise, SAR, dB/dt).

The reported performance is primarily relative to the predicate device and the safety parameters:

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

• Test Set Sample Size: "Sample clinical images were obtained for all receive coils and pulse sequences included with the system." This is not a specific number of cases or subjects. It confirms that data was collected for testing, but not the size of the test set.
• Data Provenance: Not specified. It's unclear if the data was retrospective or prospective, or the country of origin.

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

This information is not provided in the document. The statement "When interpreted by a trained physician, these images provide information that can be useful in diagnosis determination" refers to the general use of MRI, not to the expert review for the device's validation study.

4. Adjudication method for the test set:

This information is not provided.

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:

This is not applicable. The Supernova C5 is an MRI system, not an AI-powered diagnostic algorithm. The document describes a comparison of the system's overall performance and safety to a predicate MRI system, not an AI assistance tool.

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

This is not applicable. As stated above, this is an MRI system, not a standalone algorithm.

7. The type of ground truth used:

The type of ground truth is not explicitly stated for the validation of image quality, beyond an implicit comparison to the images produced by the predicate device and the general expectation that "trained physicians" can interpret the images for diagnosis. For technical performance aspects (like SNR, geometric distortion, SAR), the ground truth would be physical measurements against accepted standards.

8. The sample size for the training set:

This information is not provided. The document describes "Design Controls" and various stages of testing, but it does not mention a "training set" in the context of an AI/machine learning model.

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

This is not applicable as there is no mention of a "training set" for an AI/ML model for this MRI system.

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