A finite state model for respiratory motion analysis in image guided radiation therapy
A finite state model for respiratory motion analysis in image guided radiation therapy
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DOI：
10.1088/0031-9155/49/23/012
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发表时间：
2004-12
影响因子：
3.5
通讯作者：
Huanmei Wu;G. Sharp;B. Salzberg;D. Kaeli;H. Shirato;Steve B. Jiang
中科院分区：
文献类型：
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作者：
Huanmei Wu;G. Sharp;B. Salzberg;D. Kaeli;H. Shirato;Steve B. Jiang
对移动肿瘤进行有效的图像引导放射治疗需要充分的呼吸运动特征信息。对于边缘扩张，光束跟踪和呼吸门控，肿瘤运动必须量化预处理计划和在线监测。我们提出了呼吸运动分析的有限状态模型，它捕捉了我们对呼吸阶段的自然理解。在这个模型中，一个正常的呼吸周期由呼气、呼气末和吸气三个线段来表示，而异常的呼吸则由不规则的呼吸状态来表示。此外，我们还描述了该模型在一维上的在线实现。我们发现这个模型可以准确地描述各种各样的病人呼吸模式。应用该模型对峰间运动大于7 mm的23例患者的呼吸运动进行了描述。所有患者的平均均方根误差小于1 mm，没有患者的误差大于1.5 mm。我们的模型提供了一种方便的工具来量化呼吸运动特征，如频率变化和幅度变化的模式，并且可以应用于内部或外部运动，包括内部肿瘤位置，腹部表面，隔膜，肺活量测定和其他替代品。
Effective image guided radiation treatment of a moving tumour requires adequate information on respiratory motion characteristics. For margin expansion, beam tracking and respiratory gating, the tumour motion must be quantified for pretreatment planning and monitored on-line. We propose a finite state model for respiratory motion analysis that captures our natural understanding of breathing stages. In this model, a regular breathing cycle is represented by three line segments, exhale, end-of-exhale and inhale, while abnormal breathing is represented by an irregular breathing state. In addition, we describe an on-line implementation of this model in one dimension. We found this model can accurately characterize a wide variety of patient breathing patterns. This model was used to describe the respiratory motion for 23 patients with peak-to-peak motion greater than 7 mm. The average root mean square error over all patients was less than 1 mm and no patient has an error worse than 1.5 mm. Our model provides a convenient tool to quantify respiratory motion characteristics, such as patterns of frequency changes and amplitude changes, and can be applied to internal or external motion, including internal tumour position, abdominal surface, diaphragm, spirometry and other surrogates.