Velacur

K233977

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

Premarket evidence — what FDA accepted

Device typehardware with ml

source quote (p.5)

“The device includes two algorithms designed to help users detect good quality shear waves and identify liver tissue. From the scan data, the device calculates tissue stiffness and attenuation. Machine Learning Validation for Organ Guide Extension Machine Learning Validation for Wave Quality Guide”

Algorithmtwo algorithms designed to help users detect good quality shear waves and identify liver tissue; VDFF algorithm combines ultrasound attenuation measurements and a computed backscatter coefficient (BSC); The Wave Quality Guide is an algorithm to measure the area of good quality waves within the image or volume.

source quote (p.5)

“The device includes two algorithms designed to help users detect good quality shear waves and identify liver tissue. From the scan data, the device calculates tissue stiffness and attenuation. The same as UDFF, the VDFF algorithm combines ultrasound attenuation measurements and a computed backscatter coefficient (BSC). The Wave Quality Guide is an algorithm to measure the area of good quality waves within the image or volume.”

Adaptive (vs locked)FDA source did not state this

PCCPFDA source did not state this

Cybersecurity addressedFDA source did not state this

Validation studies (3)

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

Retrospective clinical

n=21 patients

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

Retrospective clinical

n=36 patients

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

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

recalls in product code, 24mo

344

MAUDE reports in code, 12mo

-40%

vs code's own 3-yr baseline

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). 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).