K-numberK243397
Device nameuMR 680
ApplicantShanghai United Imaging Healthcare Co., Ltd.
Product codeLNH
Device classClass II
Decision dateJul 16, 2025
DecisionSubstantially Equivalent
Regulation892.1000
AI Summary extracted from FDA summary PDF · never regenerated
Intended use

The uMR 680 is a 1.5T superconducting magnetic resonance diagnostic device with a 70cm patient bore that produces sagittal, transverse, coronal, and oblique cross-sectional and spectroscopic images to display internal anatomical structure and function of the head, body, and extremities. It is intended for use in diagnostic imaging where images and derived physical parameters, when interpreted by trained physicians, may assist in diagnosis.

Technological characteristics

The proposed device maintains identical fundamental specifications to the predicate device: 1.5T superconducting magnet, 70cm bore, 45mT/m max gradient amplitude, 200T/m/s max slew rate, and up to 96 receive channels. Key additions include new RF coils (Breast Coil-12, Head Coil-16), modified table dimensions, new pulse sequences (gre_snap, epi_dwi_msh, svs_hise, etc.), and new imaging processing features (AI-assisted Compressed Sensing, SparkCo artifact correction, Inline ECV/MOCO, 4D Flow, CEST, T1rho, and workflow enhancements).

Test standards cited

IEC 60601-2-33 (MR equipment safety), IEC 60601-1-2 (EMC), NEMA MS 1-9 and MS 14 (SNR, geometric distortion, uniformity, SAR, slice thickness, RF coil heating), IEC 62304 (software lifecycle), ISO 10993 (biocompatibility), and ISO 14971 (risk management).

Substantial equivalence argument

The device employs the same basic MR operating principles and fundamental magnet/RF/gradient system specifications as the predicate device with identical indications for use. All new features (coils, sequences, reconstruction algorithms, processing functions) are either incremental additions to existing capabilities or have predicate equivalents in reference devices. Clinical image quality was verified by board-certified radiologists, and machine learning algorithms (ACS, SparkCo, Inline ECV/MOCO) underwent performance validation showing safety and effectiveness profiles similar to existing cleared technologies, with no new safety or effectiveness concerns raised by the modifications.

Extracted by AI from the official FDA summary PDF →
Source

View the full FDA submission: accessdata.fda.gov

Researching this as a predicate?
Want a transparent AI-ranking score, AI-discovered related predicates, ongoing safety and warning-letter monitoring, full predicate chain lineage, and a drafted SE rationale — all saved to your own project? That's what an account adds.
Start free trial →

Everything you need for a 510(k) submission. Nothing you don't.

14-day free trial. No setup. Cancel anytime.

Start free trial →
Building an AI or ML-enabled device? Predicate search, PCCP tracking, and AI-specific FDA intelligence — built exclusively for AI/ML devices. Try AIFDA Intel →