OnQ Neuro

K210831

CorTechs Labs, Inc · cleared 2021-11-19 · product code QIH · Radiology

Premarket evidence — what FDA accepted

Device typesamd

source quote (p.3)

“OnQ Neuro is a fully automated post-processing medical device software intended for analyzing and evaluating neurological MR image data. The OnQ Neuro is a stand-alone medical device software package that is designed to be installed in the cloud or within a hospital's IT infrastructure on a server or PC-based workstation.”

Algorithmautomated segmentation and volumetric quantification of brain tumors, automatic post-acquisition analysis of diffusion-weighted magnetic resonance imaging (DWI) data, automated fusion of derived image data with anatomical MR images, and comparison of derived image metrics from multiple time-points

source quote (p.5)

“It accepts DICOM images using supported protocols and performs 1) automatic segmentation and volumetric quantification of brain tumors, which are known/confirmed to be pathologically diagnosed cancer, 2) automatic post-acquisition analysis of diffusion-weighted magnetic resonance imaging (DWI) data and optional automated fusion of derived image data with anatomical MR images, and 3) comparison of derived image metrics from multiple time-points.”

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)

Retrospective clinical

sample size not stated

endpoints: Dice similarity coefficient; squared correlation coefficient (R²)

Reported performance (1 observation)

diceas written: “Dice similarity coefficient”stated without value

source quote (p.8)

“Comparisons to expert segmentations are quantified using the Dice similarity coefficient (extent of software-derived vs. ground truth overlap), and squared correlation coefficient (R²) of segmented region of interest volumes. Acceptance criteria are set such that OnQ Neuro v1.1 model performance is consistent (95% percent performance) with expert rater manual segmentation performance and meets minimum clinically acceptable levels. The results of the segmentation performance testing on an independent test dataset demonstrate that OnQ Neuro v1.1.0 segments brain tumor ROIs with an accuracy that passed the product's acceptance 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

recalls in product code, 24mo

MAUDE reports in code, 12mo

—

vs code's own 3-yr baseline

drift signals on this device

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).