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ARXIV:2603.09448 · MEDICAL AI · SUBMITTED 02 APR · 02:30 UTC · FRESHNESS STALE
ARXIV:2603.09448MEDICAL AISUBMITTED 02 APR · 02:30 UTCFRESHNESS STALEarXiv
OncoAgent is a guideline-aware AI agent that automates target volume delineation in radiotherapy without the need for retraining.
Opportunity summary
Pain OncoAgent is a guideline-aware AI agent that automates target volume delineation in radiotherapy without the need for retraining.
Evidence 0 refs | 0 sources | 17% coverage
Blocker Evidence unverified
OncoAgent is a guideline-aware AI agent that automates target volume delineation in radiotherapy without the need for retraining. While deep learning models automate this process, their rigid reliance on expert-annotated data requires costly retraining…
Delineating the clinical target volume (CTV) in radiotherapy involves complex margins constrained by tumor location and anatomical barriers. While deep learning models automate this process, their rigid reliance on expert-annotated data requires costly retraining…
ScienceToStartup currently rates this 8.0/10 on the public viability pass. Evaluated on esophageal cancer cases, the agent achieves a zero-shot Dice similarity coefficient of 0.842 for the CTV and 0.880 for the planning target…
Medical AI moved forward this cycle; last verified April 2026. Public score 8.0/10.
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OncoAgent is a guideline-aware AI agent that automates target volume delineation in radiotherapy without the need for retraining.
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10.48550/arXiv.2603.09448OncoAgent is a guideline-aware AI agent that automates target volume delineation in radiotherapy without the need for retraining.
Abstract
Delineating the clinical target volume (CTV) in radiotherapy involves complex margins constrained by tumor location and anatomical barriers. While deep learning models automate this process, their rigid reliance on expert-annotated data requires costly retraining whenever clinical guidelines update. To overcome this limitation, we introduce OncoAgent, a novel guideline-aware AI agent framework that seamlessly converts textual clinical guidelines into three-dimensional target contours in a training-free manner. Evaluated on esophageal cancer cases, the agent achieves a zero-shot Dice similarity coefficient of 0.842 for the CTV and 0.880 for the planning target volume, demonstrating performance highly comparable to a fully supervised nnU-Net baseline. Notably, in a blinded clinical evaluation, physicians strongly preferred OncoAgent over the supervised baseline, rating it higher in guideline compliance, modification effort, and clinical acceptability. Furthermore, the framework generalizes zero-shot to alternative esophageal guidelines and other anatomical sites (e.g., prostate) without any retraining. Beyond mere volumetric overlap, our agent-based paradigm offers near-instantaneous adaptability to alternative guidelines, providing a scalable and transparent pathway toward interpretability in radiotherapy treatment planning.
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Proof status
unverified0 refs; 0 sources; 17% coverage.
What was readable
Derived fallback: Estimated from adjacent evidence; not verified from source.
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Dimensions overall score 8.0
PROBLEM
OncoAgent is a guideline-aware AI agent that automates target volume delineation in radiotherapy without the need for retraining. While deep learning models automate this process, their rigid reliance on expert-annotated data requires costly retraining whenever clinical guidelin...
METHOD
Delineating the clinical target volume (CTV) in radiotherapy involves complex margins constrained by tumor location and anatomical barriers. While deep learning models automate this process, their rigid reliance on expert-annotated data requires costly retraining whenever clinic...
RESULT
ScienceToStartup currently rates this 8.0/10 on the public viability pass. Evaluated on esophageal cancer cases, the agent achieves a zero-shot Dice similarity coefficient of 0.842 for the CTV and 0.880 for the planning target volume, demonstrating performance highly comparable...
WHY NOW
Medical AI moved forward this cycle; last verified April 2026. Public score 8.0/10.
we introduce OncoAgent, a novel guideline-aware AI agent framework that seamlessly converts textual clinical guidelines into three-dimensional target contours in a training-free manner.
This is a core claim explicitly stated in the abstract describing the proposed framework.
partial
the agent achieves a zero-shot Dice similarity coefficient of 0.842 for the CTV
This is a specific, quantifiable result directly stated in the abstract.
partial
and 0.880 for the planning target volume
This is a specific, quantifiable result directly stated in the abstract.
partial
demonstrating performance highly comparable to a fully supervised nnU-Net baseline.
The abstract directly compares OncoAgent's performance to a supervised baseline, indicating comparability.
partial
in a blinded clinical evaluation, physicians strongly preferred OncoAgent over the supervised baseline
This is a strong qualitative result directly stated in the abstract based on clinical evaluation.
partial
Furthermore, the framework generalizes zero-shot to alternative esophageal guidelines and other anatomical sites (e.g., prostate) without any retraining.
This claim highlights the generalization capability of the framework, explicitly stated in the abstract.
partial
our agent-based paradigm offers near-instantaneous adaptability to alternative guidelines
The abstract emphasizes the speed of adaptation as a key benefit.
partial
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OncoAgent is a guideline-aware AI agent that automates target volume delineation in radiotherapy without the need for retraining.
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Medical AI
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8.0/10 public viability
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