VBrain

K203235

Vysioneer Inc. · cleared 2021-03-19 · product code QKB · Radiology

Premarket evidence — what FDA accepted

Device typesamd

source quote (p.3)

“VBrain is a software device intended to assist trained medical professionals, during their clinical workflows of radiation therapy treatment planning, by providing initial object contours of known (diagnosed) brain tumors (i.e., region of interest, ROI) on axial T1 contrast-enhanced brain MRI images.”

Algorithmartificial intelligence algorithm (i.e., deep learning neural networks)

source quote (p.5)

“VBrain uses an artificial intelligence algorithm (i.e., deep learning neural networks) to contour (segment) brain tumor on MRI images for trained medical professionals' attention, which is meant for informational purposes only and not intended for replacing their current standard practice of manual contouring process.”

Adaptive (vs locked)No

source quote (p.5)

“VBrain uses an artificial intelligence algorithm (i.e., deep learning neural networks) to contour (segment) brain tumor on MRI images for trained medical professionals' attention, which is meant for informational purposes only and not intended for replacing their current standard practice of manual contouring process. VBrain does not alter the original MRI image, nor does it intend to be used to detect tumors for diagnosis. VBrain is intended only for generating Gross Tumor Volume (GTV) contours of brain metastases, meningiomas, and acoustic neuromas on axial T1 contrast-enhanced MRI images; It is not intended to be used with images of other brain tumors. The user must know the tumor type when they use VBrain. VBrain is intended to be used on adult patients only. Medical professionals must finalize (confirm or modify) the contours generated by VBrain, as necessary, using an external platform available at the facility that supports DICOM-RT viewing/editing functions, such as image visualization software and treatment planning system.”

PCCPFDA source did not state this

Cybersecurity addressedFDA source did not state this

Validation studies (1)

Retrospective clinical

n=116 cases · 4 site(s)

endpoints: lesion-wise sensitivity; false-positive rate; lesion-wise Dice coefficient; average Hausdorff distance; average centroid distance

Reported performance (2 observations)

sensitivity0.903CI 86.1-93.7%

source quote (p.12)

“Specifically, lesion-wise sensitivity of VBrain was observed to be 90.3% (95% CI: 86.1-93.7%)”

diceas written: “lesion-wise Dice similarity coefficient (DSC)”0.793CI 0.775-0.811

source quote (p.12)

“They were observed to be lesion-wise DSC: 0.793 (95% CI: 0.775-0.811)”

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

MAUDE reports in code, 12mo

—

vs code's own 3-yr baseline

drift signals on this device

re_clearance
The FDA AI/ML device list shows a newer 510(k) K213628 (decision 2021-12-16) from Vysioneer Inc. for a matching device line ("VBrain") — a new clearance for the same line is a change event.
first seen 2026-07-08 · k_number:K213628
re_clearance
The FDA AI/ML device list shows a newer 510(k) K212116 (decision 2021-10-12) from Vysioneer Inc. for a matching device line ("VBrain-OAR") — a new clearance for the same line is a change event.
first seen 2026-07-08 · k_number:K212116

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).