A comparison framework for breathing motion estimation methods from 4-d imaging
A comparison framework for breathing motion estimation methods from 4-d imaging
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DOI：
10.1109/tmi.2007.901006
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发表时间：
2007-12-01
影响因子：
10.6
通讯作者：
Clarysse, Patrick
中科院分区：
文献类型：
--
作者：
Sarrut, David;Delhay, Bertrand;Clarysse, Patrick
运动估计是运动器官放射治疗中的一个重要问题。特别地，来自4-D成像的运动估计可以用于计算治疗照射期间吸收剂量的分布。我们提出了一个战略和标准，将时空信息，以评估基于模型的方法捕捉呼吸运动的4-D CT图像的准确性。该评估依赖于医学专家对4-D CT图像上的标志的识别和跟踪。三位不同的专家为三名患者选择了肺部4-D CT图像中的500多个标志。在呼气阶段的四个时刻进行地标跟踪。提出了两种评价运动估计模型跟踪性能的指标。第一个度量累积了四个瞬间的地标定位误差。第二度量根据界标时空轨迹的先验呼吸模型在时间间隔上积分误差。后一种度量更好地考虑了运动的动态性。本文的第二个目的是评估与仅使用极端阶段（吸气末和呼气末）相比，考虑呼吸周期的几个阶段的影响。三个运动估计模型（两个图像配准为基础的方法和生物力学方法）的准确性进行了比较，通过建议的指标和统计工具。本文指出了考虑更多帧以可靠地跟踪呼吸运动的兴趣。
Motion estimation is an important issue in radiation therapy of moving organs. In particular, motion estimates from 4-D imaging can be used to compute the distribution of an absorbed dose during the therapeutic irradiation. We propose a strategy and criteria incorporating spatiotemporal information to evaluate the accuracy of model-based methods capturing breathing motion from 4-D CT images. This evaluation relies on the identification and tracking of landmarks on the 4-D CT images by medical experts. Three different experts selected more than 500 landmarks within 4-D CT images of lungs for three patients. Landmark tracking was performed at four instants of the expiration phase. Two metrics are proposed to evaluate the tracking performance of motion-estimation models. The first metric cumulates over the four instants the errors on landmark location. The second metric integrates the error over a time interval according to an a priori breathing model for the landmark spatiotemporal trajectory. This latter metric better takes into account the dynamics of the motion. A second aim of this paper is to estimate the impact of considering several phases of the respiratory cycle as compared to using only the extreme phases (end-inspiration and end-expiration). The accuracy of three motion estimation models (two image registration-based methods and a biomechanical method) is compared through the proposed metrics and statistical tools. This paper points out the interest of taking into account more frames for reliably tracking the respiratory motion.