Department of Physics, Carleton University, 1125 Colonel By Drive, Ottawa, Ontario K1S 5B6, Canada.
Med Phys. 2011 Feb;38(2):810-9. doi: 10.1118/1.3537206.
Tumor motion due to patient breathing is a factor that limits the accuracy of dose distribution in radiotherapy. One of the methods to improve the accuracy is by applying respiratory gating or tumor tracking. Both techniques require a precise determination of the spatial location of the tumor. We present an experimental evaluation of the performance of PeTrack, a technique that can track internal fiducial markers in real-time for tumor tracking.
PeTrack uses position sensitive detectors to record annihilation coincidence gamma rays from fiducial positron emission markers implanted in or around the tumor. It uses an expectation-maximization clustering algorithm to track the position of the markers. A normalized least mean square adaptive filter was used to predict the position of the markers 100 and 200 ms in the future. We evaluated the performance of the tracking and of the prediction by using a dynamic anthropomorphic thorax phantom to generate three-dimensional (3D) motion of three fiducial markers. The algorithm was run with four different data sets. In the first run, the motion of the markers was based on a sinusoidal model of respiratory motion. Three additional runs were done with motion based on patient breathing data.
In the case of the sinusoidal model, the average 3D root mean square error for all markers was 0.44 mm. For the three runs based on patient breathing data, the precision of the 3D localization was 0.49 mm. At a latency of 100 ms, the average 3D prediction error was 1.3 +/- 0.6 mm for the sinusoidal model and for the three patient breathing runs. At a latency of 200 ms, the average 3D prediction errors were 1.7 +/- 0.8 mm for the sinusoidal model and 1.4 +/- 0.7 mm for the breathing runs.
We conclude that PeTrack can track multiple fiducial markers in real-time with an accuracy and precision smaller than 2 mm. PeTrack can have a direct application in tumor tracking for radiation therapy.
由于患者呼吸导致的肿瘤运动是限制放疗中剂量分布准确性的因素之一。提高准确性的方法之一是应用呼吸门控或肿瘤跟踪。这两种技术都需要精确确定肿瘤的空间位置。我们介绍了一种可实时跟踪肿瘤内部基准标记物的技术 PeTrack 的实验评估。
PeTrack 使用位置敏感探测器记录来自植入肿瘤内或周围的基准正电子发射标记物的湮灭符合伽马射线。它使用期望最大化聚类算法来跟踪标记物的位置。使用归一化最小均方自适应滤波器来预测标记物在未来 100 和 200 毫秒的位置。我们使用动态拟人胸部体模生成三个基准标记物的三维（3D）运动，以评估跟踪和预测的性能。该算法使用四个不同的数据集运行。在第一次运行中，标记物的运动基于呼吸运动的正弦模型。另外进行了三次运行，运动基于患者的呼吸数据。
在正弦模型的情况下，所有标记物的平均 3D 均方根误差为 0.44 毫米。对于基于患者呼吸数据的三个运行，3D 定位的精度为 0.49 毫米。在 100 毫秒的潜伏期时，对于正弦模型和三个患者呼吸运行，平均 3D 预测误差为 1.3 +/- 0.6 毫米。在 200 毫秒的潜伏期时，对于正弦模型和呼吸运行，平均 3D 预测误差分别为 1.7 +/- 0.8 毫米和 1.4 +/- 0.7 毫米。
我们得出结论，PeTrack 可以实时跟踪多个基准标记物，精度和精度小于 2 毫米。PeTrack 可直接应用于放射治疗中的肿瘤跟踪。
