AutoContour Model RADAC V3

K230685

Radformation, Inc. · cleared 2023-04-14 · product code QKB · Radiology

Premarket evidence — what FDA accepted

Device typesamd
source quote (p.16)
“AutoContour is a pure software device and is not supplied sterile because the device doesn't come in contact with the patient. AutoContour is a pure software device and does not have a Shelf Life.”
Algorithmdeep-learning based structure models; CNN architecture
source quote (p.7)
“The deep-learning based structure models are trained using imaging datasets consisting of anatomical organs of the head and neck, thorax, abdomen and pelvis for adult male and female patients”
Adaptive (vs locked)FDA source did not state this
PCCPNo
Cybersecurity addressedNo

Validation studies (4)

Standalone

n=50 images

endpoints: Mean Dice Similarity Coefficient (DSC)

Retrospective clinical

sample size not stated

endpoints: Dice Similarity Coefficient (DSC); qualitative clinical appropriateness

Standalone

sample size not stated

endpoints: mean training DSC

Retrospective clinical

sample size not stated

endpoints: Dice Similarity Coefficient (DSC); qualitative clinical appropriateness

Reported performance (4 observations)

diceas written: “Mean Dice Similarity Coefficient (DSC) for CT Structure models (large, medium, small)”stated without value
source quote (p.18)
“For CT Structure models large, medium and small structures resulted in a mean DSC of 0.88+/-0.06, 0.88+/-0.08, and 0.75+/-0.12 respectively.”
diceas written: “Mean Dice Similarity Coefficient (DSC) for CT External Clinical Dataset (small, medium, large)”stated without value
source quote (p.21)
“All structures passed the minimum DSC criteria for small, medium and large structures with a mean DSC of 0.79+/-0.11, 0.83+/-0.12, and 0.90+/-0.09 respectively”
diceas written: “Mean Dice Similarity Coefficient (DSC) for MR Structure models (medium, small)”stated without value
source quote (p.26)
“For MR Structure models, a mean training DSC of 0.87+/-0.07 was found for medium models and 0.74+/-0.07 for small models.”
diceas written: “Mean Dice Similarity Coefficient (DSC) for MR External Clinical Dataset (small, medium)”stated without value
source quote (p.27)
“All structures passed the minimum DSC criteria for small and medium structures with a mean DSC of 0.74+/-0.07, 0.87+/-0.07 respectively”

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
2
drift signals on this device
  • re_clearance

    The FDA AI/ML device list shows a newer 510(k) K260509 (decision 2026-03-19) from Radformation, Inc. for a matching device line ("AutoContour (RADAC V5)") — a new clearance for the same line is a change event.

    first seen 2026-07-08 · k_number:K260509

  • re_clearance

    The FDA AI/ML device list shows a newer 510(k) K242729 (decision 2024-12-09) from Radformation, Inc. for a matching device line ("AutoContour (Model RADAC V4)") — a new clearance for the same line is a change event.

    first seen 2026-07-08 · k_number:K242729

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/K230685