Li Pan, Malsch Urban, Bendl Rolf
German Cancer Research Center, Medical Physics in Radiation Oncology (E040), In Neuemheimfeld 280, 69120 Heidelberg, Germany.
Phys Med Biol. 2008 Sep 7;53(17):4621-37. doi: 10.1088/0031-9155/53/17/011. Epub 2008 Aug 11.
Modern techniques of radiotherapy like intensity modulated radiation therapy (IMRT) make it possible to deliver high dose to tumors of different irregular shapes at the same time sparing surrounding healthy tissue. However, internal tumor motion makes precise calculation of the delivered dose distribution challenging. This makes analysis of tumor motion necessary. One way to describe target motion is using image registration. Many registration methods have already been developed previously. However, most of them belong either to geometric approaches or to intensity approaches. Methods which take account of anatomical information and results of intensity matching can greatly improve the results of image registration. Based on this idea, a combined method of image registration followed by 3D modeling and simulation was introduced in this project. Experiments were carried out for five patients 4DCT lung datasets. In the 3D simulation, models obtained from images of end-exhalation were deformed to the state of end-inhalation. Diaphragm motions were around -25 mm in the cranial-caudal (CC) direction. To verify the quality of our new method, displacements of landmarks were calculated and compared with measurements in the CT images. Improvement of accuracy after simulations has been shown compared to the results obtained only by intensity-based image registration. The average improvement was 0.97 mm. The average Euclidean error of the combined method was around 3.77 mm. Unrealistic motions such as curl-shaped deformations in the results of image registration were corrected. The combined method required less than 30 min. Our method provides information about the deformation of the target volume, which we need for dose optimization and target definition in our planning system.
现代放射治疗技术，如调强放射治疗（IMRT），使得在向不同形状不规则的肿瘤输送高剂量辐射的同时，能够保护周围健康组织。然而，肿瘤内部的运动使得精确计算所输送的剂量分布具有挑战性。这就使得对肿瘤运动进行分析成为必要。描述目标运动的一种方法是使用图像配准。此前已经开发了许多配准方法。然而，它们大多要么属于几何方法，要么属于强度方法。考虑解剖信息和强度匹配结果的方法能够极大地改善图像配准的结果。基于这一理念，本项目引入了一种先进行图像配准，然后进行三维建模和模拟的组合方法。对五名患者的4DCT肺部数据集进行了实验。在三维模拟中，将从呼气末图像获得的模型变形为吸气末状态。横膈膜在头足方向的运动约为-25毫米。为了验证我们新方法的质量，计算了地标点的位移，并与CT图像中的测量值进行了比较。与仅通过基于强度的图像配准获得的结果相比，模拟后精度有所提高。平均提高了0.97毫米。组合方法的平均欧几里得误差约为3.77毫米。图像配准结果中诸如卷曲状变形等不现实的运动得到了纠正。组合方法所需时间不到30分钟。我们的方法提供了有关目标体积变形的信息，这是我们在计划系统中进行剂量优化和目标定义所需要的。
