DrAid™ for Liver Segmentation

K241543

VinBrain Joint Stock Company · cleared 2024-12-06 · product code QIH · Radiology

Premarket evidence — what FDA accepted

Device typesamd
source quote (p.4)
“DrAid™ for Liver Segmentation is a web-based software, non-invasive image analysis application designed for the visualization, evaluation, and reporting of liver and physician identified lesions using multiphase images (with slice thickness <= 3.0mm) of patients aged and older than 22 years old obtained from CT scanners. The software provides a range of tools for image viewing, processing, and reporting. The software enables professionals, including physicians and technicians, to review and analyze multiphase volume datasets of the liver. DrAid™ for Liver Segmentation operates in a semiautomated quantitative imaging function, utilizing an Al algorithm to generate liver segmentation that is then editable by the physician if necessary. Additionally, the device provides tools for manual segmentation within user input of seed points and boundary editing for physician-identified lesions within the liver. Professionals can assess liver volume (mm³), liver lesion volume (mm³), and maximum lesion diameter (mm), position, thereby aiding in evaluation and treatment planning. It is important to note that the software is intended for use by trained professionals, including physicians and technicians. The image source for analysis is DICOM, allowing compatibility with standard medical imaging data formats. Note: DrAid™ for Liver Segmentation does not generate diagnoses or potential findings directly. The interpretation of the image data and the clinical decision-making process should be performed by qualified healthcare professionals. The installation and deployment of the software medical device should be carried out by VinBrain and trained technicians. Caution: Federal law restricts this device to sale by or on the order of a physician.”
AlgorithmAI algorithms for semi-automated liver segmentation
source quote (p.5)
“The software utilizes AI algorithms for semi-automated liver segmentation, combined with manual editing capabilities.”
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

n=150 patients

Reported performance (1 observation)

diceas written: “Dice score”0.9649CI [0.9631, 0.9667]
source quote (p.9)
“1) Dice score: + Mean 1std: 0.9649 0.0195 + 95% CI Dice: 0. 9649 [0.9631, 0.9667]”

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
3
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); 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/K241543