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一种基于兆伏级(MV)和千伏级(kV)同步成像的实时图像引导调强放射治疗(IMRT)的基准检测算法。

A fiducial detection algorithm for real-time image guided IMRT based on simultaneous MV and kV imaging.

作者信息

Mao Weihua, Riaz Nadeem, Lee Louis, Wiersma Rodney, Xing Lei

机构信息

Department of Radiation Oncology, Stanford University School of Medicine, Stanford, California 94305-5847, USA.

出版信息

Med Phys. 2008 Aug;35(8):3554-64. doi: 10.1118/1.2953563.

Abstract

The advantage of highly conformal dose techniques such as 3DCRT and IMRT is limited by intrafraction organ motion. A new approach to gain near real-time 3D positions of internally implanted fiducial markers is to analyze simultaneous onboard kV beam and treatment MV beam images (from fluoroscopic or electronic portal image devices). Before we can use this real-time image guidance for clinical 3DCRT and IMRT treatments, four outstanding issues need to be addressed. (1) How will fiducial motion blur the image and hinder tracking fiducials? kV and MV images are acquired while the tumor is moving at various speeds. We find that a fiducial can be successfully detected at a maximum linear speed of 1.6 cm/s. (2) How does MV beam scattering affect kV imaging? We investigate this by varying MV field size and kV source to imager distance, and find that common treatment MV beams do not hinder fiducial detection in simultaneous kV images. (3) How can one detect fiducials on images from 3DCRT and IMRT treatment beams when the MV fields are modified by a multileaf collimator (MLC)? The presented analysis is capable of segmenting a MV field from the blocking MLC and detecting visible fiducials. This enables the calculation of nearly real-time 3D positions of markers during a real treatment. (4) Is the analysis fast enough to track fiducials in nearly real time? Multiple methods are adopted to predict marker positions and reduce search regions. The average detection time per frame for three markers in a 1024 x 768 image was reduced to 0.1 s or less. Solving these four issues paves the way to tracking moving fiducial markers throughout a 3DCRT or IMRT treatment. Altogether, these four studies demonstrate that our algorithm can track fiducials in real time, on degraded kV images (MV scatter), in rapidly moving tumors (fiducial blurring), and even provide useful information in the case when some fiducials are blocked from view by the MLC. This technique can provide a gating signal or be used for intra-fractional tumor tracking on a Linac equipped with a kV imaging system. Any motion exceeding a preset threshold can warn the therapist to suspend a treatment session and reposition the patient.

摘要

诸如三维适形放疗(3DCRT)和调强放疗(IMRT)等高度适形剂量技术的优势受到分次治疗期间器官运动的限制。一种获取体内植入基准标记物近实时三维位置的新方法是分析同步的机载千伏(kV)射线束和治疗兆伏(MV)射线束图像(来自荧光透视或电子射野影像装置)。在我们能够将这种实时图像引导用于临床三维适形放疗和调强放疗治疗之前,有四个突出问题需要解决。(1)基准标记物的运动会如何使图像模糊并妨碍对其进行追踪?千伏和兆伏图像是在肿瘤以不同速度移动时采集的。我们发现,在最大线性速度为1.6厘米/秒时仍能成功检测到基准标记物。(2)兆伏射线束散射如何影响千伏成像?我们通过改变兆伏射野大小和千伏源到成像器的距离来对此进行研究,发现常规治疗兆伏射线束不会妨碍在同步千伏图像中检测基准标记物。(3)当兆伏射野由多叶准直器(MLC)进行调整时,如何在三维适形放疗和调强放疗治疗射线束的图像上检测基准标记物?所呈现的分析能够从阻挡的多叶准直器中分割出兆伏射野并检测可见的基准标记物。这使得在实际治疗期间能够计算标记物的近实时三维位置。(4)该分析速度是否足够快以近乎实时地追踪基准标记物?采用了多种方法来预测标记物位置并缩小搜索区域。在1024×768图像中对三个标记物的每帧平均检测时间缩短至0.1秒或更短。解决这四个问题为在整个三维适形放疗或调强放疗治疗过程中追踪移动的基准标记物铺平了道路。总的来说,这四项研究表明,我们的算法能够在退化的千伏图像(兆伏散射)中、在快速移动的肿瘤(基准标记物模糊)中实时追踪基准标记物,甚至在一些基准标记物被多叶准直器遮挡而无法看到的情况下也能提供有用信息。这项技术可以提供门控信号,或用于配备千伏成像系统的直线加速器上的分次内肿瘤追踪。任何超过预设阈值的运动都可以警告治疗师暂停治疗疗程并重新对患者进行定位。

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