Clippe Sébastien, Sarrut David, Malet Claude, Miguet Serge, Ginestet Chantal, Carrie Christian
Department of Radiotherapy, Centre Léon Bérard, Lyon, France.
Int J Radiat Oncol Biol Phys. 2003 May 1;56(1):259-65. doi: 10.1016/s0360-3016(03)00083-x.
Conformal radiotherapy requires accurate patient positioning with reference to the initial three-dimensional (3D) CT image. Patient setup is controlled by comparison with portal images acquired immediately before patient treatment. Several automatic methods have been proposed, generally based on segmentation procedures. However, portal images are of very low contrast, leading to segmentation inaccuracies. In this study, we propose an intensity-based (with no segmentation), fully automatic, 3D method, associating two portal images and a 3D CT scan to estimate patient setup.
Images of an anthropomorphic phantom were used. A CT scan of the pelvic area was first acquired, then the phantom was installed in seven positions. The process is a 3D optimization of a similarity measure in the space of rigid transformations. To avoid time-consuming digitally reconstructed radiograph generation at each iteration, we used two-dimensional transformations and two sets of specific and pregenerated digitally reconstructed radiographs. We also propose a technique for computing intensity-based similarity measures between several couples of images. A correlation coefficient, chi-square, mutual information, and correlation ratio were used.
The best results were obtained with the correlation ratio. The median root mean square error was 2.0 mm for the seven positions tested and was, respectively, 3.6, 4.4, and 5.1 for correlation coefficient, chi-square, and mutual information.
Full 3D analysis of setup errors is feasible without any segmentation step. It is fast and accurate and could therefore be used before each treatment session. The method presents three main advantages for clinical implementation-it is fully automatic, applicable to all tumor sites, and requires no additional device.
适形放疗需要根据初始三维（3D）CT图像对患者进行精确的定位。通过与患者治疗前即刻获取的射野图像进行比较来控制患者摆位。已经提出了几种自动方法，通常基于分割程序。然而，射野图像的对比度非常低，导致分割不准确。在本研究中，我们提出一种基于强度（无需分割）的全自动三维方法，将两幅射野图像和一次三维CT扫描相结合来估计患者摆位。
使用了一个仿真人体模型的图像。首先获取盆腔区域的CT扫描图像，然后将模型放置在七个位置。该过程是在刚体变换空间中对相似性度量进行三维优化。为避免每次迭代时生成耗时的数字重建射线图像，我们使用二维变换和两组特定的预生成数字重建射线图像。我们还提出了一种计算几对图像之间基于强度的相似性度量的技术。使用了相关系数、卡方、互信息和相关比。
相关比获得了最佳结果。在测试的七个位置，均方根误差的中位数为2.0毫米，而相关系数、卡方和互信息的均方根误差分别为3.6毫米、4.4毫米和5.1毫米。
无需任何分割步骤即可对摆位误差进行完整的三维分析。该方法快速且准确，因此可在每次治疗前使用。该方法在临床应用中有三个主要优点——它是全自动的，适用于所有肿瘤部位，并且无需额外设备。
