School of Biomedical Engineering, Capital Medical University, Beijing, People's Republic of China.
Phys Med Biol. 2012 Dec 21;57(24):8455-69. doi: 10.1088/0031-9155/57/24/8455. Epub 2012 Nov 30.
A novel real-time adaptive MV-kV imaging framework for image-guided radiation therapy is developed to reduce the thoracic and abdominal tumor targeting uncertainty caused by respiration-induced intrafraction motion with ultra-low patient imaging dose. In our method, continuous stereoscopic MV-kV imaging is used at the beginning of a radiation therapy delivery for several seconds to measure the implanted marker positions. After this stereoscopic imaging period, the kV imager is switched off except for the times when no fiducial marker is detected in the cine-MV images. The 3D time-varying marker positions are estimated by combining the MV 2D projection data and the motion correlations between directional components of marker motion established from the stereoscopic imaging period and updated afterwards; in particular, the most likely position is assumed to be the position on the projection line that has the shortest distance to the first principal component line segment constructed from previous trajectory points. An adaptive windowed auto-regressive prediction is utilized to predict the marker position a short time later (310 ms and 460 ms in this study) to allow for tracking system latency. To demonstrate the feasibility and evaluate the accuracy of the proposed method, computer simulations were performed for both arc and fixed-gantry deliveries using 66 h of retrospective tumor motion data from 42 patients treated for thoracic or abdominal cancers. The simulations reveal that using our hybrid approach, a smaller than 1.2 mm or 1.5 mm root-mean-square tracking error can be achieved at a system latency of 310 ms or 460 ms, respectively. Because the kV imaging is only used for a short period of time in our method, extra patient imaging dose can be reduced by an order of magnitude compared to continuous MV-kV imaging, while the clinical tumor targeting accuracy for thoracic or abdominal cancers is maintained. Furthermore, no additional hardware is required with the proposed method.
开发了一种用于图像引导放射治疗的新型实时自适应 MV-kV 成像框架,以降低因呼吸诱导的分次内运动导致的胸部和腹部肿瘤靶向不确定性,同时使用超低患者成像剂量。在我们的方法中,在放射治疗开始时连续进行几秒钟的立体 MV-kV 成像,以测量植入标记物的位置。在这个立体成像周期之后,kV 成像仪除了在电影 MV 图像中未检测到基准标记物的时间之外关闭。通过结合 MV 2D 投影数据和从立体成像周期建立并随后更新的标记运动方向分量之间的运动相关性,来估计 3D 时变标记位置;特别是,假设最可能的位置是到前轨迹点构建的第一主分量线段的投影线上的位置。利用自适应窗口自回归预测来预测稍后(在本研究中为 310 ms 和 460 ms)的标记位置,以允许跟踪系统的延迟。为了证明所提出方法的可行性并评估其准确性,使用来自 42 名接受胸部或腹部癌症治疗的患者的 66 小时回顾性肿瘤运动数据,对弧形和固定龙门输送进行了计算机模拟。模拟结果表明,使用我们的混合方法,在 310 ms 或 460 ms 的系统延迟下,可以分别实现小于 1.2mm 或 1.5mm 的均方根跟踪误差。由于在我们的方法中 kV 成像仅在短时间内使用,与连续 MV-kV 成像相比,可以将患者额外的成像剂量减少一个数量级,同时保持对胸部或腹部癌症的临床肿瘤靶向准确性。此外,所提出的方法不需要额外的硬件。