FDA-cleared profile

AutoContour Model RADAC V2

Radformation, Inc.

AutoContour assists radiation treatment planners by generating initial structure contours from medical images for review and modification before radiation-therapy planning. V2 added MR contouring, 58 CT models, six MR models, automatic deformable registration, and a local automatic-contouring processor while retaining the Windows client and DICOM workflow.

Evidence status: each field states its source quality, applicability, and review date. Research pending, information not established, and vendor documentation pending remain distinct outcomes.

Clinical details

What this tool is for

Start with the authorized purpose, then verify how it fits your service line and reading workflow.

Exact purpose
AutoContour assists radiation treatment planners by generating initial structure contours from medical images for review and modification before radiation-therapy planning. V2 added MR contouring, 58 CT models, six MR models, automatic deformable registration, and a local automatic-contouring processor while retaining the Windows client and DICOM workflow.
  • FDA source
  • Exact FDA submission
  • Checked 2026-09-03
Intended users
Radiation treatment planners and qualified radiation-therapy professionals who review, modify, and approve structures before planning use.
  • FDA source
  • Exact FDA submission
  • Checked 2026-09-03
Care setting and population
Radiation-therapy departments in hospitals, clinics, and other qualified treatment-planning facilities.
  • FDA source
  • Exact FDA submission
  • Checked 2026-09-03
Workflow role
Initial contour generation and registration support before radiation-treatment planning
  • Public source
  • Exact FDA submission
  • Checked 2026-09-03
Required input
DICOM CT images for all three releases; RADAC V2 and V3 also support MR for contouring, while MR and PET/CT may be used for release-dependent registration or fusion functions.
  • FDA source
  • Exact FDA submission
  • Checked 2026-09-03
Output and human action
DICOM RT Structure Set contours for review, modification, and import into a radiation-therapy treatment-planning system; registration objects or related outputs depend on the installed release.
  • FDA source
  • Exact FDA submission
  • Checked 2026-09-03
Limitations
Generated contours are initial planning aids and require qualified review and editing. FDA testing was manufacturer-sponsored and does not establish autonomous use or patient outcomes. Performance varies by structure size and model; acceptance should be model-, anatomy-, scanner-, and protocol-specific.
  • FDA source
  • Exact FDA submission
  • Checked 2026-09-03

Regulatory identity

FDA record and catalog context

The FDA listing establishes the regulatory identity. It does not by itself establish local workflow fit, pricing, security, or performance in your environment.

FDA submission
K220598
  • FDA source
  • Exact FDA submission
  • Checked 2026-08-31
Modality
Radiotherapy Planning Imaging
  • FDA source
  • Exact FDA submission
  • Checked 2026-09-03
Anatomy
Multi-region
  • FDA source
  • Exact FDA submission
  • Checked 2026-09-03
Clearance type
510(k)
  • FDA source
  • Exact FDA submission
  • Checked 2026-08-31
Decision date
2022-08-24
  • FDA source
  • Exact FDA submission
  • Checked 2026-08-31
FDA status
FDA-cleared
  • FDA source
  • Exact FDA submission
  • Checked 2026-08-31

Implementation

Questions for IT, informatics, and operations

Use these fields to structure a vendor demo, security review, and implementation estimate.

Integration
Windows client and agent components exchange DICOM images and RT Structure Sets with network storage and treatment-planning systems; later releases add rigid or deformable registration and expanded automatic-routing options.
  • Public source
  • Exact FDA submission
  • Checked 2026-09-03
Deployment and data flow
The cleared lineage uses a Windows client and local agent with a Linux-based cloud contouring service; V2 materials also describe a local automatic-contouring processor. Confirm the installed architecture, data flow, and model inventory rather than transferring current v2.7 claims to an older release.
  • Public source
  • Exact FDA submission
  • Checked 2026-09-03
Security and privacy
Current Radformation terms describe anonymization of selected CT or MR planning data, encryption in transit, and deletion after returned processing, while assigning the customer responsibility for preventing PHI disclosure. These current product-family terms must be confirmed against the older installed release and contract.
  • Vendor supplied
  • Product family
  • Checked 2026-09-03

Request the current security package and contract controls for the proposed deployment.

Training and support
Only trained and qualified radiation-therapy professionals should operate the software and review, correct, and approve its outputs. Local onboarding must include release-specific limitations, failure examples, escalation, and competency documentation.
  • Public source
  • Exact FDA submission
  • Checked 2026-09-03
Monitoring and change control
Monitor by exact software and model version, anatomy, structure, scanner and protocol, patient position, contrast, unusual or postsurgical anatomy, reviewer role, edit time, rejected outputs, DICOM-transfer failures, downstream plan effects, incidents, recalls, and updates. Revalidate after material workflow or model changes.
  • Public source
  • Exact FDA submission
  • Checked 2026-09-03

Release and scope verification

V2 added MR contouring, 58 CT models, six MR models, automatic deformable registration, and a local automatic-contouring processor while retaining the Windows client and DICOM workflow. Procurement should map the installed build, modules, models, anatomies, inputs, and outputs to K220598 before acceptance.

exact submission · checked 2026-09-03

Later product-family features are not evidence that an earlier cleared release includes them.

Interoperability acceptance

Windows client and agent components exchange DICOM images and RT Structure Sets with network storage and treatment-planning systems; later releases add rigid or deformable registration and expanded automatic-routing options.

exact submission · checked 2026-09-03

Test representative imports, exports, identifiers, orientation, geometry, structure names, units, failure handling, and round trips in the local environment.

Clinical acceptance

Use a signed local test set spanning supported anatomies, scanners, protocols, unusual or postsurgical anatomy, and small or complex structures. Measure edit burden, rejection, downstream plan effects, and reviewer agreement rather than relying only on average overlap metrics.

product family · checked 2026-09-03

Define stop-use, escalation, rollback, and revalidation triggers before production use.

Economic evaluation

Model total annual and per-plan cost against hands-on and elapsed time after review, correction, failed transfers, rework, support, upgrades, downtime, and any effect on plan quality or throughput.

product family · checked 2026-09-03

Vendor time-saving results are scenario inputs, not guaranteed local savings.

Lifecycle monitoring

Monitor by exact software and model version, anatomy, structure, scanner and protocol, patient position, contrast, unusual or postsurgical anatomy, reviewer role, edit time, rejected outputs, DICOM-transfer failures, downstream plan effects, incidents, recalls, and updates. Revalidate after material workflow or model changes.

product family · checked 2026-09-03

Trend failures and edits by exact software version, model, anatomy, scanner, protocol, and site.

Evidence

Performance evidence

Metrics are shown only when they are tied to a source, endpoint, population, and tested product version. Candidate literature without exact product and version linkage is not shown as product evidence.

Evidence summary
Exact FDA summaries document independent held-out testing, DSC criteria stratified by structure size, clinical review, and release-specific regression checks. Independent studies of other AutoContour versions show potential time savings and clinically important failure modes; those studies are product-family context, not validation of each submission.
  • Public source
  • Exact FDA submission
  • Checked 2026-09-03
Reported sensitivity
100%; 95%; 90%; 85%
  • FDA source
  • Exact FDA submission
  • Checked 2026-08-13

Values reported in the exact-submission materials. Consult the linked source for endpoint, threshold, population, and confidence interval before comparison.

Reported specificity
85%; 100%; 90%; 80%
  • FDA source
  • Exact FDA submission
  • Checked 2026-08-13

Values reported in the exact-submission materials. Consult the linked source for endpoint, threshold, population, and confidence interval before comparison.

New CT models

58 models

  • EndpointCT contouring models added versus K200323
  • PopulationAutoContour Model RADAC V2 testing described in K220598
  • Tested versionAutoContour Model RADAC V2

CT mean DSC, large structures

0.94 DSC

  • EndpointMean DSC across large CT structures
  • PopulationAutoContour Model RADAC V2 testing described in K220598
  • Tested versionAutoContour Model RADAC V2

CT mean DSC, medium structures

0.82 DSC

  • EndpointMean DSC across medium CT structures
  • PopulationAutoContour Model RADAC V2 testing described in K220598
  • Tested versionAutoContour Model RADAC V2

CT mean DSC, small structures

0.61 DSC

  • EndpointMean DSC across small CT structures
  • PopulationAutoContour Model RADAC V2 testing described in K220598
  • Tested versionAutoContour Model RADAC V2

Older-version mean contouring time saved

36.6 minutes

  • EndpointMean time saved in the timing subset
  • PopulationAutoContour v1.0.25.0 product-family study
  • Tested versionAutoContour v1.0.25.0

K220598 FDA performance package for AutoContour Model RADAC V2

  • DesignManufacturer nonclinical contour-model validation using held-out or independent images, structure-size DSC criteria, expert review, and release-dependent regression testing
  • PopulationRelease-specific CT or MR structures and image sets described in the FDA summary
  • Scopeexact submission
  • Tested versionAutoContour Model RADAC V2
  • IndependenceSponsor or vendor study

K220598

Manufacturer evidence submitted for substantial equivalence. V2 added MR contouring, 58 CT models, six MR models, automatic deformable registration, and a local automatic-contouring processor while retaining the Windows client and DICOM workflow.

Clinical evaluation of five commercial AI contouring systems

  • DesignIndependent retrospective multi-product evaluation with geometric, qualitative, and timing endpoints
  • Population80 radiotherapy patients and 45 structures
  • Scopeproduct family
  • Tested versionAutoContour v1.0.25.0
  • Samplen=80
  • Sites1
  • IndependenceIndependent study

PMID 37601695

The evaluated software differs from later RADAC submissions; reported efficiency cannot be assumed for another version or site.

Costs and setup

Budget and ongoing governance

These are common procurement questions; unknown values remain visible until a source supports them.

Pricing and total cost
Not established in reviewed sources
  • Reviewed sources checked
  • Exact FDA submission
  • Checked 2026-09-03

No public list price for the exact cleared release was found. Obtain a written quote separating license basis, sites or users, enabled modules or models, implementation, interfaces, compute, storage, training, support, upgrades, renewal, and exit costs.

Reimbursement and coding
No separate named-product Medicare payment was identified in the reviewed CMS Radiation Oncology Model material. Evaluate the product within the radiation-therapy planning service line using net staff time after review, plan quality, rework, throughput, implementation cost, and recurring cost.
  • Public source
  • Not applicable
  • Checked 2026-09-03

No product-specific code

No separate named-product payment identified in reviewed CMS material

Centers for Medicare & Medicaid Services · United States

Build a local total-cost and value model; do not infer reimbursement from FDA clearance.

Safety and lifecycle

Postmarket record

Recall and adverse-event records are shown only after product matching. Adverse-event reports do not establish incidence or causality.

Postmarket safety review
The 2026-09-02 openFDA device-recall snapshot contained no record matched to K220598 by exact submission identifier.
  • Public source
  • Exact FDA submission
  • Checked 2026-09-03

A zero-result exact-identifier search does not prove that no recall, correction, adverse-event report, or product-family safety signal exists. Maintain ongoing FDA and vendor surveillance.

Buyer worksheet

Open questions to take to the vendor

Open evaluation checklist

Research record

What has been checked

This audit distinguishes completed source review from fields that have not yet been researched.

Human reviewedStatus
2026-09-04Last searched
24Fields reviewed
10Source classes checked
0Awaiting review PubMed leads
0Awaiting review trial leads
0Unreviewed FDA recall leads

Recovered from the prior exact-submission extraction and normalized under the current provenance rules. Exact FDA decision materials, current product-family materials, directly relevant clinical literature, reimbursement context, and exact-identifier recall candidates were reviewed. Pricing, final security architecture, contracted services, enabled modules or models, interoperability, and local acceptance remain organization-specific evidence. Automated exact-name discovery found 0 PubMed and 0 ClinicalTrials.gov candidate records. Candidates require human product and version matching; zero candidates is not evidence that no studies exist. Native FDA recall identifiers produced 0 postmarket candidate records; 0 have been reviewed (0 published, 0 rejected) and 0 remain unreviewed.

Candidate leads remain unpublished until a human confirms the exact product and tested version.

Source classes: fda ai list, fda decision summary, vendor product page, peer reviewed publication, health technology guidance, reimbursement policy, fda device recall, pubmed, clinical trials, openfda device recall

Sources & history

How this profile was documented

Open the ledger for source dates, scope, and research-record updates.

View source ledger and history

Source ledger

  1. K220598 FDA decision source

    U.S. Food and Drug Administration - Accessed 2026-08-31

    Scope: regulatoryIdentity, purpose, modality, anatomy

  2. Artificial Intelligence-Enabled Medical Devices

    U.S. Food and Drug Administration - Accessed 2026-08-31

    Scope: regulatoryIdentity, modalityContext

  3. PubMed biomedical literature index

    U.S. National Library of Medicine - Accessed 2026-09-01

    Scope: evidenceDiscovery

  4. ClinicalTrials.gov study registry

    U.S. National Library of Medicine - Accessed 2026-09-01

    Scope: evidenceDiscovery, studyStatus

  5. openFDA Device Recall API

    U.S. Food and Drug Administration - Accessed 2026-09-02

    Scope: recallDiscovery, nativeSubmissionMatching

  6. Radiation Oncology Model

    Centers for Medicare & Medicaid Services - Accessed 2026-09-02

    Scope: reimbursement, radiationTherapyPaymentContext

  7. AutoContour v2.7 product page

    Radformation, Inc. - Accessed 2026-09-02

    Scope: productFamily, integration, deployment, pricingResearch, currentCommercialContext, implementationCapabilities

  8. Radformation Software License Agreement and support terms

    Radformation, Inc. - Accessed 2026-09-02

    Scope: security, training, pricing, monitoring, dataGovernance, implementationCapabilities

  9. Artificial intelligence technologies to aid contouring for radiotherapy treatment planning

    National Institute for Health and Care Excellence - Published 2023-09-27 - Accessed 2026-09-02

    Scope: limitations, training, pricing, evidenceSummary, economics, monitoring, implementationCapabilities

  10. A clinical evaluation of the performance of five commercial artificial intelligence contouring systems for radiotherapy

    Frontiers in Oncology - Published 2023-08-08 - Accessed 2026-09-02

    Scope: evidenceSummary, evidenceStudy, evidenceMetrics, economics, implementationCapabilities

  11. Evaluation of multiple-vendor AI autocontouring solutions

    Radiation Oncology - Published 2024-05-31 - Accessed 2026-09-02

    Scope: evidenceSummary, evidenceStudy, evidenceMetrics, implementationCapabilities

  12. Evaluation and failure analysis of four commercial deep learning-based autosegmentation software for abdominal organs at risk

    Journal of Applied Clinical Medical Physics - Published 2025-02-13 - Accessed 2026-09-02

    Scope: limitations, evidenceSummary, evidenceStudy, evidenceMetrics, monitoring, implementationCapabilities

Research history

  1. K220598 FDA decision

    Regulatory record

    510(k)

  2. Source-review record updated

    Research record

    human reviewed

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