Velacur

K233977

Sonic Incytes · cleared 2024-09-04 · product code IYO · Radiology

Premarket evidence — what FDA accepted

Device typehardware with ml
source quote (p.4)
“Velacur is a portable device intended to non-invasively measure the stiffness and attenuation of the liver via measurement of liver tissue shear modulus and ultrasound attenuation. This is done by measuring the wavelength or wave speed of mechanically created shear waves within the organ of the patient. Attenuation is measured directly via the loss in power of the ultrasound beam. The device includes two algorithms designed to help users detect good quality shear waves and identify liver tissue.”
AlgorithmThe device includes two algorithms designed to help users detect good quality shear waves and identify liver tissue. The VDFF algorithm combines ultrasound attenuation measurements and a computed backscatter coefficient (BSC).
source quote (p.4)
“The device includes two algorithms designed to help users detect good quality shear waves and identify liver tissue. The same as UDFF, the VDFF algorithm combines ultrasound attenuation measurements and a computed backscatter coefficient (BSC).”
Adaptive (vs locked)FDA source did not state this
PCCPNo
Cybersecurity addressedNo

Validation studies (4)

Retrospective clinical

n=70 patients · 3 site(s)

endpoints: correlation coefficient (r) between VDFF and MRI-PDFF; detection of 5% steatosis

standards: IEC 60601-1-2 Edition 4.1, ANSI AAMI 60601-1:2005/(R)2012 And A1:2012, IEC 60601-1-6 Edition 3.1 2013-10, IEC 62304:2006/A1:2015, IEC 60601-2-37 Edition 2.1 2015, IEC 62359: Edition 2.1 2017-09, ISO 14971 Third Edition 2019-12, ISO 10993-1 fifth edition 2018-08

Standalone

n=4,000 images · 36 site(s)

endpoints: Dice Coefficient > 0.7; Pixel accuracy > 80%

standards: IEC 60601-1-2 Edition 4.1, ANSI AAMI 60601-1:2005/(R)2012 And A1:2012, IEC 60601-1-6 Edition 3.1 2013-10, IEC 62304:2006/A1:2015, IEC 60601-2-37 Edition 2.1 2015, IEC 62359: Edition 2.1 2017-09, ISO 14971 Third Edition 2019-12, ISO 10993-1 fifth edition 2018-08

Standalone

sample size not stated

endpoints: Dice Coefficient > 0.7; Sensitivity and Specificity > 80%

standards: IEC 60601-1-2 Edition 4.1, ANSI AAMI 60601-1:2005/(R)2012 And A1:2012, IEC 60601-1-6 Edition 3.1 2013-10, IEC 62304:2006/A1:2015, IEC 60601-2-37 Edition 2.1 2015, IEC 62359: Edition 2.1 2017-09, ISO 14971 Third Edition 2019-12, ISO 10993-1 fifth edition 2018-08

Bench

sample size not stated

standards: IEC 60601-1-2 Edition 4.1, ANSI AAMI 60601-1:2005/(R)2012 And A1:2012, IEC 60601-1-6 Edition 3.1 2013-10, IEC 62304:2006/A1:2015, IEC 60601-2-37 Edition 2.1 2015, IEC 62359: Edition 2.1 2017-09, ISO 14971 Third Edition 2019-12, ISO 10993-1 fifth edition 2018-08

Reported performance (1 observation)

aurocas written: “auc”0.97CI [0.89-0.99]
source quote (p.7)
“The AUC [95% CI] for detection of 5% steatosis, which is the consensus level for the diagnosis of any steatosis, was 0.97 [0.89-0.99].”

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

8
recalls in product code, 24mo
344
MAUDE reports in code, 12mo
-40%
vs code's own 3-yr baseline
1
drift signals on this device
  • recall_reason_pattern

    Software/algorithm-related recall in product code IYO (Civco Medical Instruments Co. Inc., initiated 2026-03-02): "There was an error in inspection and programming of the eTRAX needle sensor for Aurora trackers. The result is a potential for the needle tip position to be incorrectly identified " Recalling firm is another firm in the same product code.

    first seen 2026-07-08 · recall res_event_number:98513

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/K233977