Predicting respiratory tumor motion with multi-dimensional adaptive filters and support vector regression
Predicting respiratory tumor motion with multi-dimensional adaptive filters and support vector regression
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DOI：
10.1088/0031-9155/54/19/005
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发表时间：
2009-10-07
影响因子：
3.5
通讯作者：
Xing, Lei
中科院分区：
文献类型：
--
作者：
Riaz, Nadeem;Shanker, Piyush;Xing, Lei
分次内肿瘤跟踪方法可以改善放射治疗期间的放射递送。用于肿瘤跟踪的图像采集和随后利用门控或射束跟踪对治疗射束的调整引入了时间延迟，并且需要预测肿瘤的未来位置。本研究评估了使用多维线性自适应滤波器和支持向量回归来预测在30 Hz下跟踪的肺肿瘤的运动。我们扩展了其他小组的先前工作，他们使用多输入单输出（MISO）自适应系统的一般框架来研究自适应滤波器，该系统使用多个相关信号来预测肿瘤的运动。我们比较了这两种新方法与传统方法如线性回归和单输入单输出自适应滤波器的性能。在400 ms的潜伏期的平均均方根误差（RMSE）的14个疗程研究使用无预测，线性回归，单输出自适应滤波器，MISO和支持向量回归分别为2.58，1.60，1.58，1.71和1.26毫米。在1 s时，RMSE分别为4.40、2.61、3.34、2.66和1.93 mm。我们发现，支持向量回归最准确地预测未来的肿瘤位置的方法研究，可以提供一个小于2mm的RMSE在1秒的延迟。而且，多维自适应滤波器框架提供了优于单维自适应滤波器的改进的性能。目前正在努力将这两个框架联合收割机结合起来，以提高性能。
Intra-fraction tumor tracking methods can improve radiation delivery during radiotherapy sessions. Image acquisition for tumor tracking and subsequent adjustment of the treatment beam with gating or beam tracking introduces time latency and necessitates predicting the future position of the tumor. This study evaluates the use of multi-dimensional linear adaptive filters and support vector regression to predict the motion of lung tumors tracked at 30 Hz. We expand on the prior work of other groups who have looked at adaptive filters by using a general framework of a multiple-input single-output (MISO) adaptive system that uses multiple correlated signals to predict the motion of a tumor. We compare the performance of these two novel methods to conventional methods like linear regression and single-input, single-output adaptive filters. At 400 ms latency the average root-mean-square-errors (RMSEs) for the 14 treatment sessions studied using no prediction, linear regression, single-output adaptive filter, MISO and support vector regression are 2.58, 1.60, 1.58, 1.71 and 1.26 mm, respectively. At 1 s, the RMSEs are 4.40, 2.61, 3.34, 2.66 and 1.93 mm, respectively. We find that support vector regression most accurately predicts the future tumor position of the methods studied and can provide a RMSE of less than 2mm at 1 s latency. Also, a multi-dimensional adaptive filter framework provides improved performance over single-dimension adaptive filters. Work is underway to combine these two frameworks to improve performance.