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. LiverMultiScan (LMSv3) is a post-processing, standalone software device which has no direct or indirect contact with the human body.”
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 addressedNo

Validation studies (2)

Bench

sample size not stated

endpoints: Accuracy; Repeatability; Reproducibility

Retrospective clinical

sample size not stated

endpoints: Precision; Inter-operator variability; Intra-operator variability; Worst-case variability

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

Reported performance (6 observations)

accuracyas written: “T1 Accuracy”stated 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: “T2* Accuracy”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: “DIXON PDFF < 30% Accuracy”stated without valueCI -7.37% to 1.72%
source quote (p.13)
“-7.37% to 1.72%”
accuracyas written: “DIXON PDFF > 30% Accuracy”stated without valueCI -28.93% to 6.83%
source quote (p.13)
“-28.93% to 6.83%”
accuracyas written: “IDEAL PDFF < 30% Accuracy”stated without valueCI -1.17% to 1.43%
source quote (p.13)
“-1.17% to 1.43%”
accuracyas written: “IDEAL PDFF > 30% Accuracy”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); a recall is shown as device-attributed only when the recall record itself lists this clearance number. 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).

Applicable FDA guidance — what the submission is measured against

FDA guidance documents and guiding principles applicable to 510(k) AI/ML devices in the Radiology panel. A curated reference index, not legal or regulatory advice — each item states its own status, and a draft is never binding.

Applicability is derived from the device's FDA advisory panel and pathway — cross-cutting guidances apply to every AI/ML device; panel-specific ones are flagged. Titles, dates, and links verified against fda.gov as of July 2026.

Constat Precedent · public FDA/CMS data · descriptive decision-support, not regulatory or reimbursement advice. Share this page: constat.dev/precedent/device/K190017