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基于实时电磁跟踪信号的小波分解的呼吸诱发前列腺运动。

Respiratory-induced prostate motion using wavelet decomposition of the real-time electromagnetic tracking signal.

机构信息

Tu and Yuen Center for Functional Onco-Imaging, Department of Radiological Sciences, University of California, Irvine, California, USA.

出版信息

Int J Radiat Oncol Biol Phys. 2013 Oct 1;87(2):370-4. doi: 10.1016/j.ijrobp.2013.05.018. Epub 2013 Jul 18.

Abstract

PURPOSE

The objective of this work is to characterize and quantify the impact of respiratory-induced prostate motion.

METHODS AND MATERIALS

Real-time intrafraction motion is observed with the Calypso 4-dimensional nonradioactive electromagnetic tracking system (Calypso Medical Technologies, Inc. Seattle, Washington). We report the results from a total of 1024 fractions from 31 prostate cancer patients. Wavelet transform was used to decompose the signal to extract and isolate the respiratory-induced prostate motion from the total prostate displacement.

RESULTS

Our results show that the average respiratory motion larger than 0.5 mm can be observed in 68% of the fractions. Fewer than 1% of the patients showed average respiratory motion of less than 0.2 mm, whereas 99% of the patients showed average respiratory-induced motion ranging between 0.2 and 2 mm. The maximum respiratory range of motion of 3 mm or greater was seen in only 25% of the fractions. In addition, about 2% patients showed anxiety, indicated by a breathing frequency above 24 times per minute.

CONCLUSIONS

Prostate motion is influenced by respiration in most fractions. Real-time intrafraction data are sensitive enough to measure the impact of respiration by use of wavelet decomposition methods. Although the average respiratory amplitude observed in this study is small, this technique provides a tool that can be useful if one moves to smaller treatment margins (≤5 mm). This also opens ups the possibility of being able to develop patient specific margins, knowing that prostate motion is not unpredictable.

摘要

目的

本研究旨在描述并量化呼吸运动对前列腺运动的影响。

方法与材料

采用 Calypso 4D 非放射性电磁跟踪系统(Calypso Medical Technologies,Inc.,西雅图,华盛顿)实时观察分次内运动。我们报告了 31 例前列腺癌患者共 1024 个分次的结果。采用小波变换分解信号,从前列腺整体位移中提取并分离呼吸运动引起的前列腺运动。

结果

我们的研究结果显示,68%的分次中可观察到平均大于 0.5mm 的呼吸运动。只有不到 1%的患者表现出平均呼吸运动小于 0.2mm,而 99%的患者表现出的呼吸诱发的平均运动幅度在 0.2mm 至 2mm 之间。只有 25%的分次中出现 3mm 或更大的最大呼吸运动范围。此外,约 2%的患者表现出焦虑,呼吸频率超过 24 次/分钟。

结论

大多数分次中前列腺运动受呼吸影响。实时分次内数据足够敏感,可采用小波分解方法测量呼吸的影响。尽管本研究中观察到的平均呼吸幅度较小,但该技术提供了一种有用的工具,如果将治疗边缘缩小至(≤5mm),这一技术将更具优势。这也为开发基于患者个体的边缘提供了可能,因为前列腺运动并非不可预测。

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本文引用的文献

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The non-Gaussian nature of prostate motion based on real-time intrafraction tracking.基于实时分次内跟踪的前列腺运动的非高斯性质。
Int J Radiat Oncol Biol Phys. 2013 Oct 1;87(2):363-9. doi: 10.1016/j.ijrobp.2013.05.019. Epub 2013 Jul 9.
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Observations on real-time prostate gland motion using electromagnetic tracking.利用电磁跟踪对前列腺实时运动的观察。
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