一适用于所有情况的自适应放射治疗计划智能体：基于每日锥束CT引导的放射治疗基础框架
One-for-All Adaptive Radiotherapy Planning Agent: A Foundation Framework for Daily CBCT-guided Radiotherapy
浏览论文内容
中文总结 AI 辅助
介绍一适用于所有情况的自适应放射治疗计划智能体，它基于统一基础模型，能从每日锥束CT执行在线自适应计划，自主预测关键组件并设计临床计划，经多数据集评估，其准确性和计划质量与临床方案相当，为放射治疗带来新机遇。
中文摘要 AI 辅助
在本研究中，我们介绍了一适用于所有情况的自适应放射治疗计划智能体，这是一个基于统一基础模型的系统，可在两分钟内直接从每日锥束CT执行完整的、针对特定治疗的在线自适应计划。该智能体首先自主预测所有关键计划组件，包括合成CT生成、多模态对齐以及肿瘤/器官分割。然后，它智能地利用这些输出执行最终临床计划设计，为每日治疗提供全面的自动化解决方案。我们还证明，该智能体使临床医生能够有意地定义计划并在关键决策点进行干预，确保在最终批准前生成可接受计划的“人在回路”框架。在跨越头颈、肺部、腹部和前列腺癌的多个数据集上进行评估，同时使用光子和质子治疗，所提出的框架实现了与临床生成的治疗计划相当的临床可接受准确性和计划质量，目标剂量误差（D98）通常在参考计划的2.0 Gy范围内。一适用于所有情况的智能体的强大性能突出了统一基础模型方法的前景，并为跨多种临床场景的快速、可扩展和全自动在线自适应放射治疗开辟了机会。
英文摘要
In this work, we introduce the One-for-All Adaptive Radiotherapy Planning Agent, a unified foundation-model-based system that performs complete, treatment-specific online adaptive planning directly from daily cone-beam CT in under two minutes. The agent first autonomously predicts all essential planning components, including synthetic CT generation, multimodal alignment, and tumor/organ segmentation. It then intelligently leverages these outputs to execute the final clinical plan design, providing a comprehensive, automated solution for daily treatment. We also demonstrate that the agent enables clinicians to define planning with intent and intervene at critical decision points, ensuring a "human-in-the-loop" framework that generates acceptable plans before final approval. Evaluated on multiple datasets spanning head-and-neck, lung, abdominal, and prostate cancers with both photon and proton therapy, the proposed framework achieves clinically acceptable accuracy and plan quality comparable to clinically generated treatment plans, with target dose errors (D98) generally within 2.0 Gy of the reference plan. The strong performance of the One-for-All agent highlights the promise of a unified foundation-model approach and opens opportunities for fast, scalable, and fully automated online adaptive radiotherapy across diverse clinical scenarios.
