College of Physics and Electronics, Shandong Normal University, Ji’nan 250014, China.
J Appl Clin Med Phys. 2011 Nov 15;12(4):3527. doi: 10.1120/jacmp.v12i4.3527.
Incorporating of daily cone-beam computer tomography (CBCT) image into online radiation therapy process can achieve adaptive image-guided radiation therapy (AIGRT). Registration of planning CT (PCT) and daily CBCT are the key issues in this process. In our work, a new multiscale deformable registration method is proposed by combining edge-preserving scale space with the multilevel free-form deformation (FFD) grids for CBCT-based AIGRT system. The edge-preserving scale space, which is able to select edges and contours of images according to their geometric size, is derived from the total variation model with the L1 norm (TV-L1). At each scale, despite the noise and contrast resolution differences between the PCT and CBCT, the selected edges and contours are sufficiently strong to drive the deformation using the FFD grid, and the edge-preserving property ensures more meaningful spatial information for mutual information (MI)-based registration. At last, the deformation fields are gained by a coarse to fine manner. Furthermore, in consideration of clinical application we designed an optimal estimation of the TV-L1 parameters by minimizing the defined offset function for automated registration. Six types of patients are studied in our work, including rectum, prostate, lung, H&N (head and neck), breast, and chest cancer patients. The experiment results demonstrate the significance of the proposed method both quantitatively with ground truth known and qualitatively with ground truth unknown. The applications for AIGRT, including adaptive deformable recontouring and redosing, and DVH (dose volume histogram) analysis in the course of radiation therapy are also studied.
将日常锥形束计算机断层扫描（CBCT）图像纳入在线放射治疗过程中可以实现自适应图像引导放射治疗（AIGRT）。PCT 和每日 CBCT 的配准是该过程中的关键问题。在我们的工作中，提出了一种新的多尺度可变形配准方法，该方法通过结合边缘保持的尺度空间和多尺度自由形态变形（FFD）网格来实现基于 CBCT 的 AIGRT 系统。边缘保持的尺度空间是从具有 L1 范数（TV-L1）的全变差模型中得出的，它能够根据图像的几何大小选择边缘和轮廓。在每个尺度上，尽管 PCT 和 CBCT 之间存在噪声和对比度分辨率差异，但选择的边缘和轮廓足够强，可以使用 FFD 网格驱动变形，并且边缘保持特性确保了基于互信息（MI）的配准更有意义的空间信息。最后，通过粗到细的方式获得变形场。此外，考虑到临床应用，我们通过最小化定义的偏移函数来设计 TV-L1 参数的最佳估计，以实现自动配准。我们的工作研究了六种类型的患者，包括直肠、前列腺、肺、头颈部（H&N）、乳房和胸部癌症患者。实验结果表明，所提出的方法在具有已知地面真实值的定量和具有未知地面真实值的定性方面都具有重要意义。在放射治疗过程中，还研究了 AIGRT 的应用，包括自适应可变形再轮廓和重新剂量以及剂量体积直方图（DVH）分析。
