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The uMR 570 system is indicated for use as a magnetic resonance diagnostic device (MRDD) that produces sagittal, transverse, coronal, and oblique cross sectional images, and that display internal anatomical structure and/or function of the head, body and extremities.

These images and the physical parameters derived from the interpreted by a trained physician yield information that may assist the diagnosis. Contrast agents may be used depending on the region of interest of the scan.

The uMR 570 is a 1.5T superconducting magnetic resonance diagnostic device with a 70cm size patient bore. It consists of components such as magnet, RF power amplifier, RF coils, gradient power amplifier, gradient coils, patient table, spectrometer, computer, equipment cabinets, power distribution system, internal communication system, and vital signal module etc. The uMR 570 Magnetic Resonance Diagnostic Device is designed to conform to NEMA and DICOM standards.

The modification performed on the uMR 570 (K201540) in this submission is due to the following changes that include:

• (1) Addition and modification of pulse sequences
• (2) Addition of MR imaging processing methods: Inline T2 mapping, Cardiac T1 mapping, Cardiac T2 mapping, Cardiac T2* mapping, Flow Quantification, Arterial Spin Labeling (3D ASL).
• (3) Addition of Spectroscopy Sequences and Post Processing Features: SVS MRS (Liver), Prostate MRS, SVS MRS (Breast).
• (4) Addition of New function: Implant mode, Remote Assistance.
• (5) Addition of New Workflow Features: EasyScan.

This FDA 510(k) summary for the uMR 570 Magnetic Resonance Diagnostic Device details hardware and software modifications compared to a predicate device (K201540). The document asserts substantial equivalence without providing detailed acceptance criteria or study results for novel features.

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

1. A table of acceptance criteria and the reported device performance

The document does not explicitly state acceptance criteria in a quantitative manner for most of the new features. It generally confirms that the device "performs as expected" and is "substantially equivalent" to the predicate. For the specific item where a standard is mentioned:

For other features, the acceptance criterion is implicitly that the features function as intended and yield diagnostically useful information, consistent with the foundational technology of MRI.

2. 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 information on the sample size used for the test set or the data provenance (country of origin, retrospective/prospective).

3. 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)

This information is not provided in the document. The general statement is that "physical parameters derived from the images when interpreted by a trained physician yield information that may assist the diagnosis."

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

The document does not specify any adjudication method for establishing ground truth or evaluating test results.

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

The document does not mention any multi-reader multi-case (MRMC) comparative effectiveness study. The device itself is a diagnostic imaging system, not an AI-assisted interpretation tool, so this type of study would not be applicable in this context. The enhancements are primarily in imaging sequences and post-processing capabilities.

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

This is an MRI system, not an AI algorithm for standalone diagnosis. Therefore, a standalone (algorithm only) performance study as typically understood for AI devices would not be relevant or performed. The performance evaluation is for the imaging capabilities and derived parameters.

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

The document does not explicitly state the type of ground truth used. For an MRI system, the "ground truth" for image quality and quantitative parameter accuracy would typically involve phantom studies, comparison to established imaging techniques, and potentially correlation with other diagnostic findings or clinical outcomes, but this is not detailed. The phrase "physical parameters derived from the images when interpreted by a trained physician yield information that may assist the diagnosis" implies clinical utility rather than a specific ground truth mechanism for validation.

8. The sample size for the training set

This information is not applicable as the device is an MRI diagnostic system and not an AI/ML model that would typically have a "training set" in the context of machine learning. The "training" for the system refers to its engineering and calibration.

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

This information is not applicable for the reasons stated above (not an AI/ML model with a "training set").

Summary of the Study that Proves the Device Meets Acceptance Criteria:

The provided 510(k) summary indicates that non-clinical testing and a clinical performance evaluation were conducted.

• Non-clinical testing: This included evaluation against NEMA MS 14-2019 for RF coil heating, which demonstrated the proposed device performs "as well as predicate devices."
• Clinical performance evaluation: This was done for new features such as Flow Quantification, 3D ASL, Inline T2 Mapping, Cardiac T1/T2/T2* Mapping, MARS+, MultiBand, QScan, and Silicon-Only Imaging.
• Performance testing for Spectroscopy: Specific tests were performed for Prostate MRS, SVS MRS (Breast), and SVS MRS (Liver).
• System Validation: Reports for Implant mode, Remote Assistance, and EasyScan were also provided.

The conclusion states that "The test results demonstrated that the device performs as expected and thus, it is substantial equivalent to the predicate devices to which it has been compared." This implies that the performance was deemed acceptable in comparison to the previously cleared predicate device, without detailing specific metrics or thresholds for acceptance for each new feature beyond the general statement of "as expected" and "substantial equivalence."

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