用AI驱动的虚拟现实训练高剂量率阴道圆柱放疗,安全又精准。
Agentic AI-driven Immersive Simulation: A Knowledge-Aware Virtual Training Platform forHigh Dose Rate (HDR) Brachytherapy

- 构建基于RAG的智能助手,结合临床指南提供实时指导。
- 系统端到端延迟低,回答准确度与相关性均高于90%。
- 适合放射肿瘤学新手,无需真实设备即可练习复杂操作。
元宇宙与大语言模型驱动的AI代理正推动医疗教育向自主、沉浸式和个性化方向演进。本文提出一种专为癌症治疗中高剂量率(HDR)阴道圆柱(VC)放疗设计的智能代理驱动虚拟仿真平台。通过整合虚拟现实(VR)与移动计算,系统构建了高保真、无风险的训练环境,使学员可在不依赖真实解剖结构或活体放射源的情况下掌握复杂操作技能。核心贡献在于将基于检索增强生成(RAG)的知识感知助手无缝集成,确保代理交互严格遵循权威临床指南。该架构支持自然语言接口与手控操作之外的实时指导。我们通过部署包含Meta Quest 3终端与本地GPU加速后端的原型系统验证了可行性,实验表明系统具备合理的端到端延迟,并在上下文精确度、回答完整性和相关性方面表现优异。
原文摘要 · Abstract (English)
The convergence of the Metaverse and Large Language Model (LLM)-based AI agent is catalyzing a shift toward autonomous, immersive, and personalized pedagogical frameworks in medical education. This paper presents a novel agentic AI-driven immersive simulation specifically designed for High Dose Rate (HDR) vaginal cylinder (VC) brachytherapy in cancer care. By integrating Virtual Reality (VR) and mobile computing, the system establishes a high-fidelity, risk-free environment that allows trainees to master complex procedural skills without the facility or safety constraints posed by physical anatomy or live radioactive sources. A core contribution of this work is the seamless integration of a knowledge-aware assistant leveraging Retrieval-Augmented Generation (RAG) to ground agent interactions in authoritative clinical guidelines. This architecture also enables an interactive agent to provide natural language interfaces and hands-free, real-time guidance during intricate medical maneuvers. We validate the proposed system through a prototype deployment comprising a Meta Quest 3 interface linked to a local GPU-accelerated AI backend, demonstrating a feasible architecture for HDR brachytherapy simulation. Experimental results indicate that the system maintains suitable end-to-end latency and high context precision, answer completeness, and relevance in the RAG-enhanced pedagogical support.
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