Auto Segmentation

K230082

GE Medical Systems, LLC · cleared 2023-05-04 · product code QKB · Radiology

Premarket evidence — what FDA accepted

Device typesamd
source quote (p.5)
“Auto Segmentation is a post-processing software designed to automatically generate contours of organ(s) at risk (OARs) from Computed Tomography (CT) images in the form of a DICOM Radiotherapy Structure Set (RTSS) series.”
Algorithmdeep learning algorithms
source quote (p.5)
“Auto Segmentation uses deep learning algorithms to generate organ at risk contours for the head and neck, thorax, abdomen and pelvis regions from CT images across 40 organ(s) or organ subregion(s).”
Adaptive (vs locked)FDA source did not state this
PCCPNo
Cybersecurity addressedNo

Validation studies (2)

Retrospective clinical

n=302 patients

endpoints: DICE similarity coefficient (DSC)

standards: ISO 13485

Reader study (MRMC)

sample size not stated

endpoints: adequacy of contours for radiotherapy planning use (Likert scale)

Reported performance (1 observation)

diceas written: “Dice Mean (Adrenal Left)”0.7868CI 76.63% (Lower CI95)
source quote (p.8)
“Adrenal Left 78.68% 76.63%”

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); 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/K230082