LiverMultiScan (LMSv3)

K190017

Perspectum Diagnostics Ltd · cleared 2019-06-27 · product code LNH · Radiology

Premarket evidence — what FDA accepted

Device typesamd
source quote (p.4)
LiverMultiScan (LMSv3) is a standalone software application for displaying 2D Magnetic Resonance (MR) medical image data acquired from compatible MR Scanners.
AlgorithmNoise Determination Algorithms, T1 mapping Algorithms, T2* mapping Algorithms, Unwrapping Phase Image Algorithms, Creation of cT1 image Algorithms, Water and Fat Mapping Algorithms, IDEAL Processing Algorithms, MAGO Processing Algorithms, Quality Check for Shimming, Automatic Liver Segmentation Algorithms, Segmentation Mapping to T2*/PDFF algorithms
source quote (p.8)
Previously cleared algorithms: Noise Determination Algorithms T1 mapping Algorithms T2* mapping Algorithms Unwrapping Phase Image Algorithms Creation of cT1 image Algorithms Water and Fat Mapping Algorithms New algorithms: IDEAL Processing Algorithms MAGO Processing Algorithms Quality Check for Shimming Automatic Liver Segmentation Algorithms Segmentation Mapping to T2*/PDFF algorithms
Adaptive (vs locked)FDA source did not state this
PCCPFDA source did not state this
Cybersecurity addressedFDA source did not state this

Validation studies (2)

Bench

sample size not stated

endpoints: Accuracy of T1, T2*, DIXON PDFF, IDEAL PDFF measurements; Repeatability of T1, T2*, DIXON PDFF, IDEAL PDFF measurements; Reproducibility of T1, T2*, DIXON PDFF, IDEAL PDFF measurements

standards: IEC 62304:2006, ISO 13485:2016, 21 CFR 820, DICOM standard

Retrospective clinical

sample size not stated

endpoints: Precision of LMSv3; Inter-operator variability of cT1, T2*, DIXON PDFF, IDEAL PDFF measurements; Intra-operator variability of cT1, T2*, DIXON PDFF, IDEAL PDFF measurements; Worst-case variability of cT1, T2*, DIXON PDFF, IDEAL PDFF measurements

standards: IEC 62304:2006, ISO 13485:2016, 21 CFR 820, DICOM standard

Reported performance (6 observations)

accuracyas written: “Phantom Accuracy T1stated without valueCI Up to 18.89% lower to the ground truth
source quote (p.13)
Up to 18.89% lower to the ground truth
accuracyas written: “Phantom Accuracy T2*stated without valueCI -9.31% to 7.53% of the ground truth
source quote (p.13)
-9.31% to 7.53% of the ground truth
accuracyas written: “Phantom Accuracy DIXON PDFF < 30%stated without valueCI -7.37% to 1.72%
source quote (p.13)
-7.37% to 1.72%
accuracyas written: “Phantom Accuracy DIXON PDFF > 30%stated without valueCI -28.93% to 6.83%
source quote (p.13)
-28.93% to 6.83%
accuracyas written: “Phantom Accuracy IDEAL PDFF < 30%stated without valueCI -1.17% to 1.43%
source quote (p.13)
-1.17% to 1.43%
accuracyas written: “Phantom Accuracy IDEAL PDFF > 30%stated without valueCI -5.05% to 10.70%
source quote (p.13)
-5.05% to 10.70%

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
2
drift signals on this device
  • 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/K190017