Synapse PACS (7.5)

K243647

FUJIFILM Healthcare Americas Corporation · cleared 2025-06-30 · product code QIH · Radiology

Premarket evidence — what FDA accepted

Device typesamd
source quote (p.5)
“As a Software as a Medical Device (SaMD), Synapse PACS performs these purposes without being part of a hardware medical device.”
AlgorithmVolume rendering, 3D volume viewing, semi-automatic segmentation (Tumor Boundary Segmentation algorithm), AI algorithm for bone removal.
source quote (p.6)
“The key addition to Synapse PACS 7.5.0 is the ability to perform volume rendering and 3D volume viewing for CT and MR. The algorithm is already cleared and marketed for Synapse 3D (K221677, reference device). The volume rendering algorithms were integrated unchanged into Synapse PACS 7.5.0 (subject device). The 2-point VOI performs is a semi-automatic segmentation of a lesion in CT and MRI images using the line drawn by the user on the lesion. The algorithm implemented is the same as already cleared and marketed algorithms for Synapse 3D (K221677, reference device). In Synapse3D, it is called Tumor Boundary Segmentation algorithm. The algorithm has been integrated into Synapse PACS unchanged compared to Synapse 3D. Comparison with Synapse 3D (K221677, reference device) provides the same results in Synapse PACS 7.5.0 (subject device). Bone Removal is a tool that enhances the visibility of vessels in 3D rendered images by masking out bone regions. The tool is based on an AI algorithm cleared and marketed for Synapse 3D (K221677, reference device). It was improved for Synapse PACS 7.5.0.”
Adaptive (vs locked)FDA source did not state this
PCCPFDA source did not state this
Cybersecurity addressedFDA source did not state this

Validation studies (1)

Bench

n=72 patients · 3 site(s)

endpoints: Dice Similarity Coefficient (DSC); 95% Hausdorff Distance (HD)

Reported performance (1 observation)

diceas written: “Dice Similarity Coefficient (DSC)”0.959CI [0.955 -0.963]
source quote (p.6)
“The mean observed dice overlap coefficient and 95% HD with 95% confidence intervals were 0.959 [0.955 -0.963] and 1.367 mm [1.170 mm - 1.563 mm], respectively, exceeding the predefined acceptance thresholds.”

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/K243647