一个动态重建和运动估计框架用于心肺呼吸运动解析实时体积核磁共振成像 (DREME-MR)
Hua-Chieh Shao1, Xiaoxue Qian2, Guoping Xu3
1Department of Radiation Oncology, The University of Texas Southwestern Medical Center, 2280 Inwood Rd, Dallas, Texas, 75390-9096, UNITED STATES.
Physics in medicine and biology
|August 8, 2025
概括
通过使用一种新的深度学习方法,DREME-MR可实现实时3DMRI和心肺呼吸运动跟踪. 这一进步对于改善MR引导的适应性放射治疗,使用最小的治疗内数据至关重要.
科学领域:
- 医疗成像医学成像
- 人工智能在医学中的应用
- 放射疗法是一种放射治疗.
背景情况:
- 心肺呼吸运动显著影响放射治疗期间磁共振成像 (MR) 的准确性.
- 对这种运动进行准确的实时跟踪对于适应性放射治疗策略至关重要.
研究的目的:
- 开发DREME-MR,一种用于关节重建患者解剖学的系统,以及从3D预治疗MRI扫描中开发出患者特有的心肺呼吸运动模型.
- 为了实现实时体积核磁共振成像和运动跟踪,使用学习运动编码器使用最小的治疗内数据.
主要方法:
- DREME-MR将动态MRI重建和实时成像集成到一个双任务学习框架中,使用时空隐式神经表示 (INR).
- 一个基于多层感知子 (MLP) 的运动编码器经过训练,可以从k空间数据中推断运动系数,以便实时跟踪.
- 心脏和呼吸道运动基础组件 (MBC) 通过频率导向策略脱.
主要成果:
- DREME-MR实现了实时3D心肺呼吸运动跟踪,延迟低于165毫秒.
- 对数字幻影的评估显示,肺瘤 (0.73±0.38mm) 和左心室 (1.69±1.12mm) 的低质量中心跟踪误差.
- 人体扫描数据显示,肝脏 (0.96) 和左心室 (0.65) 之间存在强烈的运动相关性.
结论:
- DREME-MR成功实现了低延迟,实时3DMRI和心肺呼吸运动跟踪.
- 该系统有可能显著推进治疗内MR导向的适应性放射治疗,包括实时多叶合仪跟踪.
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