uMR Omega
K243122Shanghai United Imaging Healthcare Co., Ltd. · cleared 2025-05-21 · product code LNH · Radiology
Premarket evidence — what FDA accepted
source quote (p.4)
“The uMR Omega 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. SparkCo (Spark artifact Correction) is an algorithm that can detect and correct spark artifacts in MRI images, which will help to restore spark-free image for clinical review when encountering spark artifacts on MRI images. The spark detection module of SparkCo is based on the AI algorithm, however, it won't change the image directly, and it only provides the K-space location of spark points.”
source quote (p.13)
“SparkCo (Spark artifact Correction) is an algorithm that can detect and correct spark artifacts in MRI images, which will help to restore spark-free image for clinical review when encountering spark artifacts on MRI images. The spark detection module of SparkCo is based on the AI algorithm, however, it won't change the image directly, and it only provides the K-space location of spark points. Then, the spark correction module based on traditional parallel imaging reconstruction algorithm will utilize the spark detection results to remove spark points and restore the full-sampled K-space. Through this two-step process, SparkCo can correct spark artifacts and restore the spark-free image.”
source quote (p.14)
“The training dataset for the AI module in SparkCo was generated by simulating spark artifacts from spark-free raw data. The spark detection module of SparkCo is designed to classify and locate the spark signals with abnormally high amplitude in the K-space data. These spark signals exhibit similar characteristics across different human ethnicity, so no testing was conducted on other human ethnicity.”
source quote (p.13)
“Content of Premarket Submissions for Management of Cybersecurity in Medical Devices”
Validation studies (2)
Retrospective clinical
n=15 patients
endpoints: spark detection accuracy; average PSNR of spark-corrected images; image quality improvement
Retrospective clinical
n=28 patients
endpoints: satisfaction rate S/(S+A+F) exceeding 95%
Reported performance (1 observation)
source quote (p.15)
“The average detection accuracy is 94%.”
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
- 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
- re_clearance
The FDA AI/ML device list shows a newer 510(k) K243397 (decision 2025-07-16) 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:K243397
- 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).