Electrical Engineering Department, Stanford University, Stanford, CA 94305, USA. Department of Radiation Oncology, Stanford University, Stanford, CA 94305, USA.
Phys Med Biol. 2013 Nov 7;58(21):7777-89. doi: 10.1088/0031-9155/58/21/7777. Epub 2013 Oct 18.
Non-coplanar beams are important for treatment of both cranial and noncranial tumors. Treatment verification of such beams with couch rotation/kicks, however, is challenging, particularly for the application of cone beam CT (CBCT). In this situation, only limited and unconventional imaging angles are feasible to avoid collision between the gantry, couch, patient, and on-board imaging system. The purpose of this work is to develop a CBCT verification strategy for patients undergoing non-coplanar radiation therapy. We propose an image reconstruction scheme that integrates a prior image constrained compressed sensing (PICCS) technique with image registration. Planning CT or CBCT acquired at the neutral position is rotated and translated according to the nominal couch rotation/translation to serve as the initial prior image. Here, the nominal couch movement is chosen to have a rotational error of 5° and translational error of 8 mm from the ground truth in one or more axes or directions. The proposed reconstruction scheme alternates between two major steps. First, an image is reconstructed using the PICCS technique implemented with total-variation minimization and simultaneous algebraic reconstruction. Second, the rotational/translational setup errors are corrected and the prior image is updated by applying rigid image registration between the reconstructed image and the previous prior image. The PICCS algorithm and rigid image registration are alternated iteratively until the registration results fall below a predetermined threshold. The proposed reconstruction algorithm is evaluated with an anthropomorphic digital phantom and physical head phantom. The proposed algorithm provides useful volumetric images for patient setup using projections with an angular range as small as 60°. It reduced the translational setup errors from 8 mm to generally <1 mm and the rotational setup errors from 5° to <1°. Compared with the PICCS algorithm alone, the integration of rigid registration significantly improved the reconstructed image quality, with a reduction of mostly 2-3 folds (up to 100) in root mean square image error. The proposed algorithm provides a remedy for solving the problem of non-coplanar CBCT reconstruction from limited angle of projections by combining the PICCS technique and rigid image registration in an iterative framework. In this proof of concept study, non-coplanar beams with couch rotations of 45° can be effectively verified with the CBCT technique.
非共面射束对于治疗颅内外肿瘤都很重要。然而,对于带有床面旋转/踢动的这种射束,治疗验证具有挑战性,尤其是对于锥形束 CT(CBCT)的应用。在这种情况下,为了避免机架、床面、患者和机载成像系统之间的碰撞,只能采用有限的非常规成像角度。本研究的目的是为接受非共面放射治疗的患者开发一种 CBCT 验证策略。我们提出了一种图像重建方案,该方案将基于先验图像的约束压缩感知(PICCS)技术与图像配准相结合。根据名义床面旋转/平移,将在中立位置采集的计划 CT 或 CBCT 旋转和平移,作为初始先验图像。这里,名义床面运动的选择是在一个或多个轴或方向上存在 5°的旋转误差和 8mm 的平移误差。所提出的重建方案在两个主要步骤之间交替进行。首先,使用基于总变差最小化和同时代数重建的 PICCS 技术来重建图像。其次,通过在重建图像和前一个先验图像之间应用刚性图像配准来校正旋转/平移设置误差,并更新先验图像。PICCS 算法和刚性图像配准交替迭代,直到配准结果低于预定阈值。使用人体数字体模和物理头部体模对所提出的重建算法进行了评估。该方法使用角度范围小至 60°的投影即可为患者设置提供有用的容积图像。它将平移设置误差从 8mm 降低到通常<1mm,将旋转设置误差从 5°降低到<1°。与单独的 PICCS 算法相比,刚性配准的集成大大提高了重建图像的质量,重建图像误差的均方根降低了 2-3 倍(高达 100 倍)。该算法通过在迭代框架中结合 PICCS 技术和刚性图像配准,为解决有限角度投影的非共面 CBCT 重建问题提供了一种解决方案。在本概念验证研究中,使用床面旋转 45°的非共面射束可以有效地用 CBCT 技术进行验证。