(27 days)
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 images when interpreted by a trained physician yield information that may assist the diagnosis. Contrast agents may be used depending on the region 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 predicate device is uMR 570 (K200024) and the modification to the predicate device in this submission is the addition of a new pulse sequence, gre senc spiral which also exists in reference device of Philips Ingenia, Ingenia CX, Ingenia Elition, and Ingenia Ambition MR Systems (K183063) .
The modification performed on the predicate uMR 570 (K200024) in this submission is due to the addition of a new pulse sequence, gre_senc_spiral. The modification, which does not affect the intended use nor alters the fundamental scientific technology of the device, is as the following:
Introduce gre senc spiral as a new pulse sequence
The provided text is a 510(k) Summary for the uMR 570 Magnetic Resonance Diagnostic Device. It focuses on demonstrating substantial equivalence to a predicate device, primarily due to the addition of a new pulse sequence called "gre_senc_spiral."
Here's an analysis of the acceptance criteria and study information based on the provided text:
1. Table of Acceptance Criteria and Reported Device Performance:
The document does not explicitly state quantitative acceptance criteria or detailed device performance metrics for the new pulse sequence. Instead, it focuses on qualitative comparisons and safety compliance. The claim is that the device "performs as expected" and is "substantially equivalent" to the predicate.
| Acceptance Criteria Category | Acceptance Criteria (Not explicitly stated quantitatively for the new feature, but implied by "substantial equivalence" and safety compliance) | Reported Device Performance (as stated or implied) |
|---|---|---|
| For new pulse sequence (gre_senc_spiral): | Intended use remains the same as predicate. | The modification (gre_senc_spiral) "does not affect the intended use nor alters the fundamental scientific technology of the device." Images are stored in DICOM format and suitable for 3rd party strain analysis. |
| Does not introduce new potential hazards or safety risks. | "It does not introduce new potential hazards or safety risks." Tested for Electrical Safety (Comply with ES60601-1), EMC (Comply with IEC60601-1-2), Max SAR (Comply with IEC 60601-2-33), Max dB/dt (Comply with IEC 60601-2-33), Biocompatibility (ISO 10993-5, ISO 10993-10). | |
| Overall Device: | Maintain technological characteristics similar to the predicate. | "has the same technological characteristics" as the predicate uMR 570 (K200024) in terms of magnet, gradient, RF system, coils, patient table, and safety, except for the new pulse sequence. |
| Performs as expected. | "The test results demonstrated that the device performs as expected." |
2. Sample size used for the test set and the data provenance:
- Test Set Sample Size: Not explicitly stated. The "Performance Evaluation Report SENC A" is mentioned but no details about its contents or the number of cases/patients used are provided.
- Data Provenance: Not explicitly stated. Given it's a performance evaluation for a 510(k) submission, it's likely internal company data, but the country of origin and whether it was retrospective or prospective are not mentioned.
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 mentions "images... when interpreted by a trained physician," implying physician involvement in diagnosis, but not specifically for establishing ground truth of a test set for the device's performance evaluation.
4. Adjudication method (e.g., 2+1, 3+1, none) for the test set:
- This information is not provided in the document.
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:
- No MRMC comparative effectiveness study was done. The device itself is a Magnetic Resonance Diagnostic Device (MRDD), an imaging system, not an AI-based interpretation tool. The new pulse sequence (
gre_senc_spiral) is for acquiring SENC cardiac images, which are then "processed by 3rd party software for strain analysis and report." This submission is for the imaging device and the new acquisition sequence, not for the AI analysis of these images.
6. If a standalone (i.e., algorithm only without human-in-the-loop performance) was done:
- Not applicable / Not done for this device as an AI algorithm. This submission is for an MRI system and a new pulse sequence. The "3rd party software for strain analysis" is separate and not part of this 510(k) submission.
7. The type of ground truth used (expert consensus, pathology, outcomes data, etc.):
- This information is not provided for the performance evaluation of the
gre_senc_spiralsequence. The purpose of this 510(k) is to demonstrate that the new sequence produces images that can be interpreted like those from an equivalent predicate, and that it's safe. It's not about evaluating diagnostic accuracy against a specific ground truth.
8. The sample size for the training set:
- Not applicable. This submission is for a hardware (MRI system) and a new pulse sequence (software component for acquisition). There is no mention of an AI algorithm being trained by the manufacturer for this device, nor a training set for the performance testing mentioned.
9. How the ground truth for the training set was established:
- Not applicable. As above, there is no mention of a training set or AI algorithm training within this submission.
§ 892.1000 Magnetic resonance diagnostic device.
(a)
Identification. A magnetic resonance diagnostic device is intended for general diagnostic use to present images which reflect the spatial distribution and/or magnetic resonance spectra which reflect frequency and distribution of nuclei exhibiting nuclear magnetic resonance. Other physical parameters derived from the images and/or spectra may also be produced. The device includes hydrogen-1 (proton) imaging, sodium-23 imaging, hydrogen-1 spectroscopy, phosphorus-31 spectroscopy, and chemical shift imaging (preserving simultaneous frequency and spatial information).(b)
Classification. Class II (special controls). A magnetic resonance imaging disposable kit intended for use with a magnetic resonance diagnostic device only is exempt from the premarket notification procedures in subpart E of part 807 of this chapter subject to the limitations in § 892.9.