MI View&GO

K254016

Siemens Medical Solutions USA, Inc. · cleared 2026-02-10 · product code QIH · Radiology

Premarket evidence — what FDA accepted

Device typesamd
source quote (p.6)
“MI View&GO is a software-only medical device”
AlgorithmLung lobe segmentation algorithm, PERCIST Liver algorithm
source quote (p.8)
“In addition to verification and validation testing, performance evaluation was conducted in order to ensure the safety and effectiveness of the lung lobe segmentation algorithm compared to the predicate device. The lung lobe segmentation algorithm was re-trained with additional data and is utilized within Auto Lung 3D. Additionally, performance evaluation was conducted for the improved PERCIST Liver algorithm. The algorithm takes as input the PET/CT image together with a binary liver mask and returns the coordinates of the reference region center.”
Adaptive (vs locked)Yes
source quote (p.8)
“The lung lobe segmentation algorithm was re-trained with additional data and is utilized within Auto Lung 3D.”
PCCPFDA source did not state this
Cybersecurity addressedFDA source did not state this

Validation studies (2)

Retrospective clinical

n=20 patients

endpoints: average Dice coefficient per organ; average symmetric surface distance (ASSD) per organ

standards: PS 3.1-3.20 2023e (DICOM Set), 62304 Edition 1.1 2015-06 CONSOLIDATED VERSION, 14971 Third Edition 2019-12, 62366-1 Edition 1.1 2020-06 CONSOLIDATED VERSION, 15223-1 Fourth edition 2021-07, 20417 First edition 2021-04 Corrected version 2021-12

Retrospective clinical

n=129 patients

endpoints: average Dice coefficient; average symmetric surface distance (ASSD); how often the PERCIST VOIs intersected the suspicious uptake masks identified by an expert reader

standards: PS 3.1-3.20 2023e (DICOM Set), 62304 Edition 1.1 2015-06 CONSOLIDATED VERSION, 14971 Third Edition 2019-12, 62366-1 Edition 1.1 2020-06 CONSOLIDATED VERSION, 15223-1 Fourth edition 2021-07, 20417 First edition 2021-04 Corrected version 2021-12

Reported performance (2 observations)

diceas written: “average Dice coefficient (Lung Segmentation)”stated without value
source quote (p.9)
“The average Dice coefficient for the 20 subjects was higher for each lobe in the subject device than in the predicate device, although not greater than a +0.03 difference for all lobes.”
diceas written: “average Dice coefficient (PERCIST Liver)”stated without value
source quote (p.9)
“The acceptance criteria for the liver is an average Dice coefficient greater than 0.8 or an average symmetric surface distance (ASSD) less than 10 mm. The liver met both criteria.”

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

0
recalls in product code, 24mo
3
MAUDE reports in code, 12mo
—
vs code's own 3-yr baseline
0
drift signals on this device

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/K254016