MVision AI Segmentation

K212915

MVision AI · cleared 2022-05-03 · product code QKB · Radiology

Premarket evidence — what FDA accepted

Device typesamd
source quote (p.4)
MVision AI Segmentation is a software only medical device which can be used to accelerate region of interest (ROI) delineation in radiotherapy treatment planning by creating automatic segmentation templates on CT images for these ROIs.
Algorithmpre-trained, locked, and static models that are based on deep artificial neural networks
source quote (p.4)
The segmentations are produced by pre-trained, locked, and static models that are based on deep artificial neural networks.
Adaptive (vs locked)No
source quote (p.4)
The segmentations are produced by pre-trained, locked, and static models that are based on deep artificial neural networks.
PCCPFDA source did not state this
Cybersecurity addressedYes
source quote (p.8)
Software verification and validation, performance evaluation for machine learning based algorithms, and implemented Cybersecurity control measures and tests establish that the subject medical device is safe, secure and effective for its user needs and defined intended use.

Validation studies (1)

Retrospective clinical

sample size not stated

endpoints: reducing the upfront effort and time on typical contouring; producing usable contours (ROIs) as a starting point that will save clinicians' time

standards: FDA's Guidance for Industry and FDA Staff, “Guidance for the Content of Premarket Submissions for Software Contained in Medical Devices.”, CFR 21 Part 820, DICOM standard

Reported performance (0 observations)

FDA source did not state a quantitative performance metric — non-reporting is itself the signal.

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
0
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). 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).

RIGOR™ Precedent · public FDA/CMS data · descriptive decision-support, not regulatory or reimbursement advice. Share this page: radar.healthai.com/precedent/device/K212915