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Imaging of the whole body (including the head, abdomen, heart, pelvis, spine, blood vessels, limbs and extremities), fluid visualization, 2D/3D Imaging, MR Angiography, MR. Fluoroscopy

The VISART™ consists of two model upgrades to the MRT-150A system which provide increased gradient field strength, more ergonomic computer architecture, improved scan parameter specifications and a lighter magnet than the MRT-150A.

This is a pre-amendment 510(k) submission for the VISART™ Magnetic Resonance Device, MRT-150A/H1 and MRT-150A/F1 models. The submission primarily focuses on demonstrating substantial equivalence to an existing device (MRT-150A) by highlighting hardware and software upgrades that improve performance without introducing new safety or effectiveness questions. The provided text, however, does not contain details about a specific study testing device performance against defined acceptance criteria in the manner typically seen for algorithmic or AI-based devices.

The submission describes general increases in imaging performance parameters and safety parameters compared to the predicate device. It also mentions that "Sample phantom images and clinical images were presented for all new sequences demonstrating conformance with consensus standards requirements for Signal-to-Noise ratio Uniformity, Slice Profiles, Geometric Distortion and Slice Thickness/Interslice Spacing." This indicates that some form of evaluation was performed, but the specifics of a structured study with statistical outcomes are not detailed.

Given the information provided, I cannot fully answer your request in the format you've outlined for an AI/algorithm-driven device's acceptance criteria and study. However, I can extract the relevant information as much as possible based on the provided text.

Here's an attempt to address your request based on the available information:

1. Table of Acceptance Criteria and Reported Device Performance

The document doesn't explicitly state "acceptance criteria" for the upgraded models in a quantitative, pass/fail manner. Instead, it highlights improvements over the predicate device (MRT-150A) and states conformance with "consensus standards requirements."

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

The document states: "Sample phantom images and clinical images were presented for all new sequences."

• Sample Size: Not specified. The term "sample" implies a subset, but no numbers are given.
• Data Provenance: Not specified. Given the manufacturing site is in Japan, the clinical images could be from Japan, but this is not stated. It is also not specified if the data was retrospective or prospective.

3. Number of Experts Used to Establish Ground Truth for the Test Set and Qualifications of those Experts

This information is not provided in the summary. The document mentions "consensus standards requirements" for image quality, suggesting that expert review or adherence to established scientific norms formed the basis of evaluation, but details on individual experts are absent.

4. Adjudication Method for the Test Set

This information is not provided in the summary.

5. If a Multi Reader Multi Case (MRMC) Comparative Effectiveness Study was done

No, a multi-reader multi-case (MRMC) comparative effectiveness study was not done or at least not reported in this summary. The submission focuses on hardware and software upgrades and their performance characteristics, not on human reader performance with or without AI assistance.

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

This submission pertains to an MRI device, not an AI algorithm. Therefore, the concept of a "standalone algorithm" performance as typically understood for AI devices does not apply here. The performance evaluation was for the imaging system itself.

7. The Type of Ground Truth Used

For image quality parameters (SNR, Uniformity, Slice Profiles, Geometric Distortion, Slice Thickness/Interslice Spacing), the ground truth was implicitly based on:

• Phantom images: Objective measurements against known phantom properties.
• Clinical images: Presumably evaluated by experts against established diagnostic criteria or visual inspection for quality, demonstrating "conformance with consensus standards requirements." The exact nature of this "ground truth" (e.g., pathology, outcomes data) for clinical images is not specified.

8. The Sample Size for the Training Set

This information is not applicable as the document describes an MR imaging device and its upgrades, not the development of a machine learning algorithm with a training set.

9. How the Ground Truth for the Training Set was Established

This information is not applicable for the same reason as above.

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