Department of Physics and Astronomy, University of Manitoba, Winnipeg, MB, R3T 2N2, Canada.
Division of Medical Physics, CancerCare Manitoba, 675 McDermot Avenue, Winnipeg, MB, R3E 0V9, Canada.
Med Biol Eng Comput. 2019 Aug;57(8):1657-1672. doi: 10.1007/s11517-019-01981-4. Epub 2019 May 14.
Accurate tracking of organ motion during treatment is needed to improve the efficacy of radiation therapy. This work investigates the feasibility of tracking an uncontoured target using the motion detected within a moving treatment aperture. Tracking was achieved with a weighted optical flow algorithm, and three different techniques for updating the reference image were evaluated. The accuracy and susceptibility of each approach to the accumulation of position errors were verified using a 3D-printed tumor (mounted on an actuator) and a virtual treatment aperture. Tumor motion up to 15.8 mm (peak-to-peak) taken from the breathing patterns of seven lung cancer patients was acquired using an amorphous silicon portal imager at ~ 7.5 frames/s. The first approach (INI) used the initial image detected, as a fixed reference, to determine the target motion for each new incoming image, and performed the best with the smallest errors. This method was also the most robust against the accumulation of position errors. Mean absolute errors of 0.16, 0.32, and 0.38 mm were obtained for the three methods, respectively. Although the errors are comparable to other tracking methods, the proposed method does not require prior knowledge of the tumor shape and does not need a tumor template or contour for tracking. Graphical abstract.
为了提高放射治疗的疗效，需要在治疗过程中准确跟踪器官运动。本工作研究了使用运动治疗孔径内检测到的运动来跟踪未轮廓化目标的可行性。使用加权光流算法进行跟踪，并评估了三种不同的更新参考图像的技术。使用安装在执行器上的 3D 打印肿瘤（安装在执行器上）和虚拟治疗孔径来验证每种方法的准确性和对位置误差积累的敏感性。使用非晶硅门控成像仪以约 7.5 帧/秒的速度从 7 例肺癌患者的呼吸模式中获取高达 15.8 毫米（峰峰值）的肿瘤运动。第一种方法（INI）使用初始检测到的图像作为固定参考，为每个新传入的图像确定目标运动，并且具有最小的误差，表现最好。这种方法对位置误差的积累也最具鲁棒性。三种方法的平均绝对误差分别为 0.16、0.32 和 0.38 毫米。尽管误差与其他跟踪方法相当，但所提出的方法不需要肿瘤形状的先验知识，也不需要肿瘤模板或轮廓进行跟踪。
