RadOncAI
by Informai (for RadOncAI product) / Global Network for AI in Radiation Oncology (for RadoncAI.net)
· Based in United States →
— AI-guided dose prediction from CT simulation and clinician-defined treatment-planning structures for adult head-and-neck malignant or benign disease (for RadOncAI product) / A Global Platform Advancing AI in Radiation Oncology (for RadoncAI.net)
Overview
RadOncAI, developed by Informai, is an artificial intelligence solution specifically designed to optimize and enhance various aspects of radiation oncology workflows. It aims to improve efficiency, accuracy, and patient outcomes in the complex field of radiation therapy.
The tool leverages advanced AI algorithms to assist radiation oncologists and their teams with tasks such as treatment planning, contouring, and quality assurance. By automating repetitive or time-consuming processes, RadOncAI allows clinicians to focus more on critical decision-making and patient care.
Key features often include AI-powered auto-contouring for organs-at-risk and target volumes, dose prediction, and treatment plan evaluation. This can lead to more consistent and personalized treatment plans, potentially reducing planning time and improving the precision of radiation delivery.
Reviewed by Pouyan Golshani, MD — Interventional Radiologist
Key Features
- AI-powered auto-contouring
- Treatment plan optimization
- Dose prediction
- Quality assurance support
- Workflow automation
Use Cases
- Automated contouring for radiation therapy planning
- Optimizing radiation treatment plans
- Improving efficiency in radiation oncology workflows
- Enhancing precision in radiation delivery
- Assisting with quality assurance in radiotherapy
What Physicians Need to Know
Key Capabilities
RadOncAI provides AI-guided dose prediction from CT simulation and clinician-defined treatment-planning structures for adult head-and-neck malignant or benign disease. It generates optimized treatment dose plans that target tumors while minimizing exposure to adjacent healthy tissues. The software is designed to assist radiation oncologists, medical physicists, and dosimetrists in radiotherapy planning.
Clinical Utility
RadOncAI aims to help radiation oncologists generate high-quality dose plans more efficiently. It can assist clinicians in delivering optimized, clinically achievable dose plans in a fraction of the time required by existing clinical processes, potentially leading to substantial clinical productivity and cost savings. The software is intended for use in radiation-oncology planning and review environments within hospitals or other professional treatment facilities.
Integration Options
RadOncAI accepts CT or MR treatment-planning images, target structures, and organs-at-risk information as input. It exports DICOM RT Dose to compatible treatment-planning or DICOM-RT workflows.
Compliance Status
RadOncAI has received 510(k) clearance from the U.S. Food and Drug Administration (FDA) for radiotherapy planning imaging. This indicates it has met rigorous safety and efficacy standards.
Pricing Model
No exact product price was found in the available evidence. Organizations are advised to obtain a written quote covering license or hardware basis, implementation, interfaces, infrastructure, training, service, upgrades, renewal, downtime, and exit costs.
User Experience
The software is designed as a clinician co-pilot. A radiation oncologist, physicist, or dosimetrist must review, revise, and approve the output; the software is not a diagnosis, autonomous treatment decision, or radiation-delivery system.
Support Quality
Post-deployment monitoring, drift thresholds, alerting, and revalidation commitments for the exact configuration require vendor and site confirmation.
Implementation Complexity
Deployment details for the exact cleared configuration are not established in the public FDA decision material. Local technical, clinical, privacy, security, and workflow acceptance remains necessary. Implementation of complex technologies in radiation oncology often requires a rigorous quality assurance program.
Evidence Base
The FDA clearance was based on manufacturer-submitted retrospective regulatory validation with an independent clinician-review component, not independent clinical validation. The exact FDA decision material reports a 500-case adult head-and-neck radiotherapy validation with PTV and OAR acceptance testing and clinician review. Clinical acceptability was judged in 50 cases reviewed by 3 board-certified radiation oncologists (150 assessments).
Physician Tip
Always verify the authorized purpose of RadOncAI and how it fits your specific service line and reading workflow. Conduct local technical, clinical, privacy, security, and workflow acceptance testing. Define stop-use, escalation, rollback, and revalidation triggers before production use. Remember that the software is a clinician co-pilot and requires review, revision, and approval of its output by a qualified healthcare professional.
Ensure thorough testing of interoperability, including representative identifiers, orientation, geometry, measurements, units, routing, failure handling, and round trips, when integrating RadOncAI with existing CT/MR treatment planning systems and DICOM RT Dose workflows.
Details
| Category | Oncology AI, Radiology & Imaging AI |
| Pricing |
Unknown
|
| Deployment | Deployment details for the exact cleared configuration are not established in the public FDA decision material. |
| Mobile App | Yes (Radonc, for educational purposes) |
| Data Export | Unknown |
| Training | Unknown |
| Target Size | Radiation-oncology planning and review environments within hospitals or other professional treatment facilities. |
| Compliance | |
| BAA Available | Unknown AI-estimated |
| HIPAA Compliant | Unknown AI-estimated |
| FDA Status |
Unknown AI-estimated RadOncAI is FDA-cleared (K253050) for AI-guided dose prediction from CT simulation and clinician-defined treatment-planning structures for adult head-and-neck malignant or benign disease. It accepts CT simulation, target, and organ-at-risk inputs and exports DICOM RT Dose to a compatible treatment-planning or DICOM-RT workflow. The FDA decision material reports a 500-case adult head-and-neck radiotherapy validation with PTV and OAR acceptance testing and clinician review. |
| Integrations | |
| EHR | Not specified |
| Specialties | Medical Oncology, Radiation Oncology, Radiology |
Social Proof
| Customers | unknown |
| Notable | The Global Network for AI in Radiation Oncology (RadoncAI.net) has 41+ affiliated institutions worldwideincluding Stanford University Medical CenterPrincess Margaret Cancer CentreGerman Cancer Research Center (DKFZ)Royal Marsden NHS Foundation TrustNational Cancer Center JapanPeking Union Medical College HospitalInstituto Nacional de Cancerologíaand Lagos University Teaching Hospital. |
Support & Reliability
| Training Provided | Unknown |
What the Web Says
RadOncAI is an FDA-cleared AI tool designed for radiotherapy planning, specifically for adult head-and-neck malignant or benign disease. It provides AI-guided dose prediction from CT simulation and clinician-defined treatment-planning structures. While the product is relatively new, initial feedback from radiologists using a related product (Rad AI Impressions) has been positive.
Overall: MixedStrengths
- FDA-cleared for radiotherapy planning in head-and-neck cases
- Provides AI-guided dose prediction
- Compatible with existing DICOM RT Dose workflows
- Positive initial feedback from radiologists on a related AI product
- Actively moderated and updated (for a related educational platform)
- Can be useful for both junior and senior residents (for a related educational platform)
Limitations
- Deployment details for the exact cleared configuration are not publicly established
- Security controls, hosting boundaries, audit behavior, identity management, and incident commitments are not publicly established
- Software is not a diagnosis, autonomous treatment decision, or radiation-delivery system; requires review and approval by a radiation oncologist, physicist, or dosimetrist
- Difficult to get meaningful feedback on the newer, complete reporting product due to its recent market entry
- Some companies may inflate usage statistics for marketing purposes
- Concerns about AI tools in healthcare regarding data privacy and accuracy of information without human supervision
Based on reviews from: Informai radiology AI profile, Reddit (r/radiationoncology), Reddit (r/breastcancer), Reddit (r/PACSAdmin)
Last updated: 2026-09-24
Ratings & Reviews
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Press & Coverage
EIN Presswire
InformAI Receives FDA 510(k) Clearance for RadOncAI Radiation Therapy Dose Planning Software
InformAI, Inc. announced it received 510(k) approval from the U.S. FDA for RadOncAIu2122, an AI-enabled software for radiation therapy dose planning, designed to optimize treatment for head & neck cancer patients.
2026-07
InformAI
InformAI Receives FDA 510K Clearance
InformAI has received 510k-Clearance for its RadOncAI radiation dose treatment planning software-as-a-medical-device (SaMD), which generates optimized radiation plans to target tumors while minimizing exposure to healthy tissues.
2026-07
Innolitics
Q2 2026 AI/ML FDA Clearances and De Novos
This article lists RadOncAI as one of the 86 AI/ML devices authorized by the FDA in Q2 2026, specifically a 510(k) clearance for radiology in optimizing head and neck treatment plans.
2026-07
FDA
List of Artificial Intelligence-Enabled Medical Devices
The FDA's list of AI-enabled medical devices includes RadOncAI by InformAI, categorized under radiology with a 510(k) clearance date of June 18, 2026.
2026-09
InformAI
RadOncAI | Informai radiology AI profile
RadOncAI is an FDA-cleared radiology AI listing for Radiotherapy Planning Imaging, providing AI-guided dose prediction from CT simulation for adult head-and-neck malignant or benign disease.
2026-09
Mayo Clinic Platform
Accelerate June 2026 Cohort Landing Page
InformAI's flagship product, RadOncAI, is highlighted for accelerating radiation therapy dose planning workflows, generating plans in minutes compared to hours, and is now a standard of care at a premier cancer center.
2026-06
InformAI
InformAI Receives Supplemental CPRIT Grant for Product Commercialization
InformAI received a supplemental product development grant of $465,188 from the Cancer Prevention and Research Institute of Texas (CPRIT) to support the commercialization of RadOncAI, its AI-guided dose prediction platform for radiation oncology.
2025-10
Built In
AI in Healthcare: Uses, Examples & Benefits
InformAI's RadOncAI tool is featured as an example of AI in healthcare, using AI to create radiation therapy plans that precisely target tumors while minimizing exposure to healthy tissues.
2026-08
Videos
Product demos, reviews, and walkthroughs for RadOncAI.
No videos found. Search YouTube directly
Frequently Asked Questions
RadOncAI is an FDA-cleared AI tool designed for radiotherapy planning, specifically for adult head-and-neck malignant or benign diseases. It provides AI-guided dose prediction from CT simulations and clinician-defined treatment-planning structures, assisting radiation oncologists, medical physicists, and dosimetrists in planning and reviewing radiotherapy.
RadOncAI is an FDA-cleared radiology AI listing for radiotherapy planning imaging. When implementing, it's crucial to define stop-use, escalation, rollback, and revalidation triggers before production use. A radiation oncologist, physicist, or dosimetrist must always review, revise, and approve the output, as the software is not intended for autonomous diagnosis, treatment decisions, or radiation delivery.
Yes, several alternatives exist. Some notable examples include DeepBT Detector-Plus for initial gross-tumor-volume contours, ARIA Oncology Information System, MOSAIQ Radiation Oncology, and Radformation software, which focuses on automation and AI-based contouring.
While an exact product price for RadOncAI was not found in the available evidence, the economic evaluation of such tools typically involves modeling capital and recurring costs against net staff time after review, throughput, repeat imaging or rework, room time, consumables, infrastructure, training, service, downtime, upgrade, and replacement costs. Radiation oncology costs in general can vary widely depending on location and insurance, with a single session potentially billed at over $10,000 in the U.S. and total treatment courses ranging from $20,000-$73,000 without insurance.
While AI offers significant benefits in radiation oncology, such as increased productivity and improved quality, it's important to remember that AI software like RadOncAI is not a diagnosis, autonomous treatment decision, or radiation-delivery system; human oversight is always required. General limitations of radiomics, a subdiscipline of AI in this field, include the long latency between radiation exposure and cancer manifestation, limitations of animal models, and the complexity of human trials to demonstrate effectiveness.
RadOncAI requires CT or MR treatment-planning images, target structures, organs-at-risk information, and other labeled planning inputs. While specific security controls and hosting boundaries for RadOncAI are not established in public FDA decision material, other AI models like RadOnc-GPT have been fine-tuned on large datasets of patient records with no patient data shared outside of a secure network, and all studies approved by an institutional review board.
RadOncAI's performance evidence includes a validation cohort of 500 adult head-and-neck patients. It demonstrated 9 tests meeting the +/-300 cGy equivalence margin for PTV equivalence and 21 metrics within the +300 cGy non-inferiority margin for OAR achievability. Clinical acceptability was reported at 100 percent, and OAR achievability at 98.7 percent.
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| Last Verified: 2026-09-23 | First Added: 2026-09-23