uMR Ultra

K243547

Shanghai United Imaging Healthcare Co., Ltd. · cleared 2025-07-17 · product code LNH · Radiology

Premarket evidence — what FDA accepted

Device typehardware
source quote (p.6)
“uMR Ultra is a 3T superconducting magnetic resonance diagnostic device with a 70cm size patient bore and 2 channel RF transmit system. 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. uMR Ultra is designed to conform to NEMA and DICOM standards.”
AlgorithmThe device incorporates multiple AI-based algorithms for image processing and workflow features, such as AI-assisted Compressed Sensing (ACS) for acceleration reconstruction, DeepRecon for image de-noising and super-resolution, EasyScan for automatic slice group location, t-ACS for dynamic MR imaging, AiCo for motion correction, SparkCo for spark artifact detection, ImageGuard for motion artifact monitoring, EasyCrop for automatic image cropping, EasyFACT for automatic ROI placement, Auto TI Scout for TI frame detection, Inline MOCO for motion correction, Inline Cardiac Function for ED/ES Phases Recognition, Inline ECV for segmentation, and EasyRegister for height/weight estimation.
source quote (p.17)
“ACS (AI-assisted Compressed Sensing) is an acceleration reconstruction technique. By adding one more regularization term from AI module, ACS is a slight extension of CS (Compressed Sensing).”
Adaptive (vs locked)FDA source did not state this
PCCPFDA source did not state this
Cybersecurity addressedYes
source quote (p.16)
“Content of Premarket Submissions for Management of Cybersecurity in Medical Devices”

Validation studies (17)

Retrospective clinical

n=25 patients

standards: ANSI/AAMIES60601-1: 2005/ (R) 2012+A1:2012+C1:2009/(R)2012+A2:2010/(R)2012) [IncludingAmendment2(2021)] Medical electrical equipment - Part 1: General requirements for basic safety and essential performance, IEC 60601-1-2:2014+A1:200, Medical electrical equipment - Part 1-2: General requirements for basic safety and essential performance - Collateral standard: Electromagnetic disturbances - Requirements and tests, IEC 60601-2-33 Ed. 4.0:2022 Medical Electrical Equipment - Part 2-33: Particular Requirements for The Basic Safety and Essential Performance of Magnetic Resonance Equipment for Medical Diagnostic, IEC 60825-1: 2014, Edition 3.0, Safety of laser products - Part 1: Equipment classification and requirements., IEC 60601-1-6:2010+A1:2013+A2:2020, Edition 3.2, Medical electrical equipment - Part 1-6: General requirements for basic safety and essential performance - Collateral standard: Usability., IEC 62304:2006+AMD1:2015 CSV Consolidated version, Medical device software - Software life cycle processes, IEC 62464-1 Edition 2.0: 2018-12, Magnetic resonance equipment for medical imaging Part 1: Determination of essential image quality parameters., NEMA MS 1-2008(R2020), Determination of Signal-to-Noise Ratio (SNR) in Diagnostic Magnetic Resonance Images, NEMA MS 2-2008(R2020), Determination of Two-Dimensional Geometric Distortion in Diagnostic Magnetic Resonance Images, NEMA MS 3-2008(R2020), Determination of Image Uniformity in Diagnostic Magnetic Resonance Images, NEMA MS 4-2023, Acoustic Noise Measurement Procedure for Diagnosing Magnetic Resonance Imaging Devices, NEMA MS 5-2018, Determination of Slice Thickness in Diagnostic Magnetic Resonance Imaging, NEMA MS 6-2008(R2014, R2020), Determination of Signal-to-Noise Ratio and Image Uniformity for Single-Channel Non-Volume Coils in Diagnostic MR Imaging, NEMA MS 8-2016, Characterization of the Specific Absorption Rate (SAR) for Magnetic Resonance Imaging Systems, NEMA MS 9-2008(R2020), Standards Publication Characterization of Phased Array Coils for Diagnostic Magnetic Resonance Images, NEMA MS 14-2019, Characterization of Radiofrequency (RF) Coil Heating in Magnetic Resonance Imaging Systems, IEC /TR 60601-4-2: 2024, Medical electrical equipment - Part 4-2: Guidance and interpretation - Electromagnetic immunity: performance of medical electrical equipment and medical electrical systems, NEMA PS 3.1-3.20(2022d): Digital Imaging and Communications in Medicine (DICOM), Guidance for the Content of Premarket Submissions for Software Contained in Medical Devices, Content of Premarket Submissions for Management of Cybersecurity in Medical Devices, ISO 10993-5: 2009, Edition 3.0, Biological evaluation of medical devices - Part 5: Tests for in vitro cytotoxicity., ISO 10993-10: 2021, Edition 4.0, Biological evaluation of medical devices - Part 10: Tests for skin sensitization., ISO 10993-23: 2021, Edition 1.0, Biological evaluation of medical devices - Part 10: Tests for irritation., Use of International Standard ISO 10993-1, "Biological evaluation of medical devices - Part 1: Evaluation and testing within a risk management process", ISO 14971: 2019, Edition 3.0, Medical Devices – Application of risk management to medical devices, Code of Federal Regulations, Title 21, Part 820 - Quality System Regulation, Code of Federal Regulations, Title 21, Subchapter J - Radiological Health

Retrospective clinical

n=25 patients

Retrospective clinical

n=116 patients

endpoints: No Fail cases and auto position success rate P1/(P1+P2+F) exceeds 80%

Retrospective clinical

n=60 patients

endpoints: A better consistency between t-ACS and the reference than that between CS and the reference was shown in all t-ACS application types.; No large structural difference appeared between t-ACS and the reference in all t-ACS application types.; The motion-time curves and Bland-Altman analysis showed the consistency between t-ACS and the reference based on simulated and real acquired data in all t-ACS application types.

Retrospective clinical

n=24 patients

Retrospective clinical

n=15 patients

endpoints: The average detection accuracy need be larger than 90%

Retrospective clinical

n=80 patients

endpoints: Success rate P/(P+F) exceeds 90%

Retrospective clinical

n=65 patients

endpoints: No Fail cases and pass rate P1/ (P1+P2 +F) exceeds 90%

Retrospective clinical

n=25 patients

endpoints: Satisfied and Acceptable ratio (S+A)/(S+A+F) exceeds 95%

Retrospective clinical

n=27 patients

endpoints: The average frame difference between the frame of auto-calculated TI and the gold standard frame is less than or equal to 1 frame, and the maximum frame difference is less than or equal to 2 frames.

Retrospective clinical

n=60 patients

endpoints: The average Dice coefficient of the left ventricular myocardium after motion correction is greater than 0.87.

Retrospective clinical

n=33 patients

endpoints: The average Dice coefficient of the left ventricular myocardium after motion correction is 0.96, which is greater than 0.87.

Retrospective clinical

n=56 patients

endpoints: The average error does not exceed 1 frame.

Retrospective clinical

n=28 patients

endpoints: no failure cases, satisfaction rate S/(S+A+F) exceeding 95%

Retrospective clinical

n=63 patients · 4 site(s)

endpoints: PH5(Percentage of height error within 5%); PH15(Percentage of height error within 15%); MEAN_H (Average error of height)

Retrospective clinical

n=63 patients · 4 site(s)

endpoints: PW10(Percentage of weight error within 10%); PW20(Percentage of weight error within 20%); MEAN_W (Average error of weight)

Retrospective clinical

n=20 patients

endpoints: No Fail cases and success rate P1+P2/(P1+P2+F) exceeds 100%

Reported performance (3 observations)

accuracyas written: “SparkCo average detection accuracy”0.94
source quote (p.28)
“The average detection accuracy is 94%.”
diceas written: “Inline MOCO Cardiac Perfusion Images average Dice coefficient”0.92CI > 0.87
source quote (p.37)
“The average Dice coefficient of the left ventricular myocardium after motion correction is 0.92, which is greater than 0.87.”
diceas written: “Inline MOCO Cardiac Dark Blood Images average Dice coefficient”0.96CI > 0.87
source quote (p.38)
“The average Dice coefficient of the left ventricular myocardium after motion correction is 0.96, which is greater than 0.87.”

Each value carries its own analysis unit and task — never compare or pool across devices. Source: 510(k) summary PDF.

Predicate network

Postmarket — what happened after clearance

100
recalls in product code, 24mo
510
MAUDE reports in code, 12mo
+5%
vs code's own 3-yr baseline
3
drift signals on this device
  • re_clearance

    The FDA AI/ML device list shows a newer 510(k) K252371 (decision 2025-09-25) from Shanghai United Imaging Healthcare Co., Ltd. for a matching device line ("uMR 680") — a new clearance for the same line is a change event.

    first seen 2026-07-08 · k_number:K252371

  • recall_reason_pattern

    Software/algorithm-related recall in product code LNH (Philips North America, initiated 2026-04-14): "The potential for stiffness value errors when a specific range of image reconstruction parameters is used in combination with Resoundant's algorithm, leading to the reconstruction " Recalling firm is another firm in the same product code.

    first seen 2026-07-08 · recall res_event_number:98779

  • recall_reason_pattern

    Software/algorithm-related recall in product code LNH (Philips North America, initiated 2025-12-03): "The potential for stiffness value errors when viewing exported MR Elastography (MRE) stiffness maps to viewer Picture Archiving and Communication System (PACS)." Recalling firm is another firm in the same product code.

    first seen 2026-07-08 · recall res_event_number:98111

Recall and MAUDE counts are product-code-level (reports aren't reliably attributable to one device). Signals are descriptive observables with sources — never a judgment that the device is unsafe or drifting. Snapshot 2026-07-08.

Reimbursement — how devices like this got paid

Not yet tracked — no payment pathway indexed for this clearance (the reimbursement corpus is a growing seed set).

RIGOR™ Precedent · public FDA/CMS data · descriptive decision-support, not regulatory or reimbursement advice. Share this page: radar.healthai.com/precedent/device/K243547