AI 中文总结
研究针对宫颈癌放疗自动轮廓勾画问题，提出BAT-RM混合架构，集成多种技术。该架构在多机构数据实验中性能卓越，提升了初级肿瘤学家的交并比并减少轮廓勾画时间，临床部署后缩短患者等待时间，体现了严格研究流程对患者的益处。
AI 中文摘要
我们提出了一种用于宫颈癌放疗计划的临床部署端到端自动轮廓勾画系统，以具有区域感知曼巴的边界感知变换器（BAT-RM）为基础，这是一种混合架构，集成了Sobel门控边界注意力、用于长程上下文的线性时间多向曼巴模块和边界骨架引导融合门。该设计实现了长程上下文建模的线性时间复杂度，避免了全空间自注意力的二次成本。完整流程涵盖多机构数据收集、严格的评分者间质量保证、独立队列中的外部验证以及与Varian、RayStation和Monaco原生兼容的基于网络的临床界面。与四个基线相比，BAT-RM在七个解剖类别上实现了卓越性能，在包括GTV和CTV的靶体积以及直肠和膀胱等危及器官方面有统计学显著改善。一项涉及13名放射肿瘤学家的前瞻性多中心读者研究表明，人工智能辅助将初级肿瘤学家的交并比从0.899提高到0.965，接近高级水平准确性，同时将轮廓勾画时间减少80%以上。该系统还降低了专家咨询率并提高了读者间一致性，反映了效率和质量保证方面的提升。在合作医院临床部署后，该系统在无需额外人员配置的情况下将患者等待时间从数天缩短至数小时，使常规病例能够当天或次日开始治疗。BAT-RM表明，从数据管理到临床部署的严格研究流程可以在放疗需求远超专家能力的资源受限环境中直接转化为可衡量的患者受益。
英文摘要
We present a clinically deployed end-to-end auto-contouring system for cervical cancer radiotherapy planning, anchored by the Boundary-Aware Transformer with Region-Aware Mamba (BAT-RM), a hybrid architecture that integrates Sobel-gated boundary attention, a linear-time, multi-directional Mamba module for long-range context, and a boundary-skeleton-guided fusion gate. This design achieves linear-time complexity for long-range context modeling, avoiding the quadratic cost of full spatial self-attention. The full pipeline spans multi-institutional data collection, rigorous inter-rater quality assurance, external validation in an independent cohort, and a web-based clinical interface natively compatible with Varian, RayStation, and Monaco. Against four baselines, BAT-RM achieves superior performance across seven anatomical classes, with statistically significant improvements in target volumes, including GTV and CTV, and in organs at risk such as the rectum and bladder. A prospective multi-center reader study involving 13 radiation oncologists demonstrated that AI assistance elevates junior oncologists' IoU from 0.899 to 0.965, approaching senior-level accuracy, while reducing contouring time by more than 80%. The system also reduced expert consultation rates and improved inter-reader consistency, reflecting gains in both efficiency and quality assurance. Following clinical deployment at a partner hospital, the system reduced patient wait times from days to hours without additional staffing, enabling same-day or next-day initiation of treatment for routine cases. BAT-RM demonstrates that a rigorous research pipeline, from data curation to clinical deployment, can translate directly into measurable patient benefit in resource-constrained settings where the demand for radiotherapy far exceeds specialist capacity.
