(258 days)
The uMR 680 system is indicated for use as a magnetic resonance diagnostic device (MRDD) that produces sagittal, transverse, coronal, and oblique cross sectional images, and spectroscopic 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 interest of the scan.
The uMR 680 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 680 Magnetic Resonance Diagnostic Device is designed to conform to NEMA and DICOM standards.
This traditional 510(k) is to request modifications for the cleared uMR 680(K240744). The modifications performed on the uMR 680 in this submission are due to the following changes that include:
(1) Addition of RF coils and corresponding accessories: Breast Coil -12, Biopsy Configuration, Head Coil-16, Positioning Couch-top, Coil Support.
(2) Deletion of VSM (Wireless UIH Gating Unit REF 453564324621, ECG module Ref 989803163121, SpO2 module Ref 989803163111).
(3) Modification of the dimensions of Detachable table: from width 826mm, height 880mm,2578mm to width 810mm, height 880mm, length 2505mm.
(4) Addition and modification of pulse sequences
a) New sequences: gre_snap, gre_quick_4dncemra, gre_pass, gre_mtp, gre_trass, epi_dwi_msh, epi_dti_msh, svs_hise.
b) Added associated options for certain sequences: fse(add Silicone-Only Imaging, MicroView, MTC, MultiBand), fse_arms(add Silicone-Only Imaging), fse_ssh(add Silicone-Only Imaging), fse_mx(add CEST, T1rho, MicroView, MTC), fse_arms_dwi(add MultiBand), asl_3d(add multi-PLD), gre(add T1rho, MTC, output phase image), gre_fsp(add FSP+), gre_bssfp(add CASS, TI Scout), gre_fsp_c(add 3D LGE, DB/GB PSIR), gre_bssfp_ucs(add real time cine), gre_fq(add 4D Flow), epi_dwi(add IVIM), epi_dti(add DKI, DSI).
c) Added additional accessory equipment required for certain sequences: gre_bssfp(add Virtual ECG Trigger).
d) Name change of certain sequences: gre_fine(old name: gre_bssfp_fi).
e) Added applicable body parts: gre_ute, gre_fine, fse_mx.
(5) Addition of imaging reconstruction methods: AI-assisted Compressed Sensing (ACS), Spark artifact Correction (SparkCo).
(6) Addition of imaging processing methods: Inline Cardiac Function, Inline ECV, Inline MRS, Inline MOCO, 4D Flow, SNAP, CEST, T1rho, FSP+, CASS, PASS, MTP.
(7) Addition of workflow features: TI Scout, EasyCrop, ImageGuard, Mocap, EasyFACT, Auto Bolus tracker, Breast Biopsy and uVision.
(8) Modification of workflow features: EasyScan(add applicable body parts)
The modification does not affect the intended use or alter the fundamental scientific technology of the device.
The provided FDA 510(k) clearance letter and summary for the uMR 680 Magnetic Resonance Imaging System outlines performance data for several new features and algorithms.
Here's an analysis of the acceptance criteria and the studies that prove the device meets them for the AI-assisted Compressed Sensing (ACS), SparkCo, Inline ED/ES Phases Recognition, and Inline MOCO algorithms.
1. Table of Acceptance Criteria and Reported Device Performance
| Feature/Algorithm | Evaluation Item | Acceptance Criteria | Reported Performance |
|---|---|---|---|
| AI-assisted Compressed Sensing (ACS) | AI Module Verification Test | The ratio of error: NRMSE(output)/ NRMSE(input) is always less than 1. | Pass |
| Image SNR | ACS has higher SNR than CS. | Pass (ACS shown to perform better than CS in SNR) | |
| Image Resolution | ACS has higher (standard deviation (SD) / mean value(S)) values than CS. | Pass (ACS shown to perform better than CS in resolution) | |
| Image Contrast | Bland-Altman analysis of image intensities acquired using fully sampled and ACS was shown with less than 1% bias and all sample points falls in the 95% confidence interval. | Pass (less than 1% bias, all sample points within 95% confidence interval) | |
| Image Uniformity | ACS achieved significantly same image uniformities as fully sampled image. | Pass | |
| Structure Measurement | Measurements differences on ACS and fully sampled images of same structures under 5% is acceptable. | Pass | |
| Clinical Evaluation | All ACS images were rated with equivalent or higher scores in terms of diagnosis quality. | "All ACS images were rated with equivalent or higher scores in terms of diagnosis quality" (implicitly, it passed) | |
| SparkCo | Spark Detection Accuracy | The average detection accuracy needs to be larger than 90%. | The average detection accuracy is 94%. |
| Spark Correction Performance (Simulated) | The average PSNR of spark-corrected images needs to be higher than the spark images. Spark artifacts need to be reduced or corrected. | The average PSNR of spark-corrected images is 1.6 dB higher than the spark images. The images with spark artifacts were successfully corrected after enabling SparkCo. | |
| Spark Correction Performance (Real-world) | Spark artifacts need to be reduced or corrected (evaluated by one experienced evaluator assessing image quality improvement). | The images with spark artifacts were successfully corrected after enabling SparkCo. | |
| Inline ED/ES Phases Recognition | Error between algorithm and gold standard | The average error does not exceed 1 frame. | The error between the frame indexes calculated by the algorithm for the ED and ES of all test data and the gold standard frame index is 0.13 frames, which does not exceed 1 frame. |
| Inline MOCO | Dice Coefficient (Left Ventricular Myocardium after Motion Correction) Cardiac Perfusion Images | The average Dice coefficient of the left ventricular myocardium after motion correction is greater than 0.87. | The average Dice coefficient of the left ventricular myocardium after motion correction is 0.92, which is greater than 0.87. Subgroup analysis also showed good generalization: |
- Age: 0.92-0.93
- Gender: 0.92
- Ethnicity: 0.91-0.92
- BMI: 0.91-0.95
- Magnetic field strength: 0.92-0.93
- Disease conditions: 0.91-0.93 |
| | Dice Coefficient (Left Ventricular Myocardium after Motion Correction) Cardiac Dark Blood Images | The average Dice coefficient of the left ventricular myocardium after motion correction is greater than 0.87. | The average Dice coefficient of the left ventricular myocardium after motion correction is 0.96, which is greater than 0.87. Subgroup analysis also showed good generalization: - Age: 0.95-0.96
- Gender: 0.96
- Ethnicity: 0.95-0.96
- BMI: 0.96-0.98
- Magnetic field strength: 0.96
- Disease conditions: 0.96-0.97 |
2. Sample Size Used for the Test Set and Data Provenance
- AI-assisted Compressed Sensing (ACS):
- Sample Size: 1724 samples from 35 volunteers.
- Data Provenance: Diverse demographic distributions (gender, age groups, ethnicity, BMI) covering various clinical sites and separated time periods. Implied to be prospective or a carefully curated retrospective set, collected specifically for validation on the uMR 680 system, and independent of training data.
- SparkCo:
- Simulated Spark Testing Dataset: 159 spark slices (generated from spark-free raw data).
- Real-world Spark Testing Dataset: 59 cases from 15 patients.
- Data Provenance: Real-world data acquired from uMR 1.5T and uMR 3T scanners, covering representative clinical protocols. The report specifies "Asian" for 100% of the real-world dataset's ethnicity, noting that performance is "irrelevant with human ethnicity" due to the nature of spark signal detection. This is retrospective data.
- Inline ED/ES Phases Recognition:
- Sample Size: 95 cases from 56 volunteers.
- Data Provenance: Includes various ages, genders, field strengths (1.5T, 3.0T), disease conditions (NOR, MINF, DCM, HCM, ARV), and ethnicities (Asian, White, Black). The data is independent of the training data. Implied to be retrospective from UIH MRI systems.
- Inline MOCO:
- Sample Size: 287 cases in total (105 cardiac perfusion images from 60 patients, 182 cardiac dark blood images from 33 patients).
- Data Provenance: Acquired from 1.5T and 3T magnetic resonance imaging equipment from UIH. Covers various ages, genders, ethnicities (Asian, White, Black, Hispanic), BMI, field strengths (1.5T, 3.0T), and disease conditions (Positive, Negative, Unknown). The data is independent of the training data. Implied to be retrospective from UIH MRI systems.
3. Number of Experts Used to Establish the Ground Truth for the Test Set and the Qualifications of Those Experts
- AI-assisted Compressed Sensing (ACS):
- Number of Experts: More than one (plural "radiologists" used).
- Qualifications: American Board of Radiologists certificated physicians.
- SparkCo:
- Number of Experts: One expert for real-world SparkCo evaluation.
- Qualifications: "one experienced evaluator." (Specific qualifications like board certification or years of experience are not provided for this specific evaluator).
- Inline ED/ES Phases Recognition:
- Number of Experts: Not explicitly stated for ground truth establishment ("gold standard phase indices"). It implies a single, established method or perhaps a consensus by a team, but details are missing.
- Inline MOCO:
- Number of Experts: Three licensed physicians.
- Qualifications: U.S. credentials.
4. Adjudication Method for the Test Set
- AI-assisted Compressed Sensing (ACS): Not explicitly stated, but implies individual review by "radiologists" to rate diagnostic quality.
- SparkCo: For the real-world dataset, evaluation by "one experienced evaluator."
- Inline ED/ES Phases Recognition: Not explicitly stated; "gold standard phase indices" are referenced, implying a pre-defined or established method without detailing a multi-reader adjudication process.
- Inline MOCO: "Finally, all ground truth was evaluated by three licensed physicians with U.S. credentials." This suggests an adjudication or confirmation process, but the specific method (e.g., 2+1, consensus) is not detailed beyond "evaluated by."
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 explicitly described to evaluate human reader improvement with AI assistance. The described studies focus on the standalone performance of the algorithms or a qualitative assessment of images by radiologists for diagnostic quality.
6. If a Standalone (i.e., algorithm only without human-in-the-loop performance) Was Done
- Yes, standalone performance was done for all listed algorithms.
- ACS: Evaluated quantitatively (SNR, Resolution, Contrast, Uniformity, Structure Measurement) and then qualitatively by radiologists. The quantitative metrics are standalone.
- SparkCo: Quantitative metrics (Detection Accuracy, PSNR) and qualitative assessment by an experienced evaluator. The quantitative metrics are standalone.
- Inline ED/ES Phases Recognition: Evaluated quantitatively as the error between algorithmic output and gold standard. This is a standalone performance metric.
- Inline MOCO: Evaluated using the Dice coefficient, which is a standalone quantitative metric comparing algorithm output to ground truth.
7. The Type of Ground Truth Used
- AI-assisted Compressed Sensing (ACS):
- Quantitative: Fully-sampled k-space data transformed to image space.
- Clinical: Radiologist evaluation ("American Board of Radiologists certificated physicians").
- SparkCo:
- Spark Detection Module: Location of spark points (ground truth for simulated data).
- Spark Correction Module: Visual assessment by "one experienced evaluator."
- Inline ED/ES Phases Recognition: "Gold standard phase indices" (method for establishing this gold standard is not detailed, but implies expert-derived or a highly accurate reference).
- Inline MOCO: Left ventricular myocardium segmentation annotated by a "well-trained annotator" and "evaluated by three licensed physicians with U.S. credentials." This is an expert consensus/pathology-like ground truth.
8. The Sample Size for the Training Set
- AI-assisted Compressed Sensing (ACS): 1,262,912 samples (from a variety of anatomies, image contrasts, and acceleration factors).
- SparkCo: 24,866 spark slices (generated from 61 spark-free cases from 10 volunteers).
- Inline ED/ES Phases Recognition: Not explicitly provided, but stated to be "independent of the data used to test the algorithm."
- Inline MOCO: Not explicitly provided, but stated to be "independent of the data used to test the algorithm."
9. How the Ground Truth for the Training Set Was Established
- AI-assisted Compressed Sensing (ACS): Fully-sampled k-space data were collected and transformed to image space as the ground-truth. All data were manually quality controlled.
- SparkCo: "The training dataset for the AI module in SparkCo was generated by simulating spark artifacts from spark-free raw data... a total of 24,866 spark slices, along with the corresponding ground truth (i.e., the location of spark points), were generated for training." This indicates a hybrid approach using real spark-free data to simulate and generate the ground truth for spark locations.
- Inline ED/ES Phases Recognition: Not explicitly provided.
- Inline MOCO: Not explicitly provided.
§ 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.