Deformable image registration and reconstruction for radiotherapy applications

描述（由申请人提供）：图像引导的适应性放疗是一种新兴的范例，旨在处理患者在治疗期间经历的解剖变化。这些变化包括器官的变形和相对运动，肿瘤缩小，组织肿胀以及其他改变辐射与解剖结构相互作用方式的现象。更改可以在以天、小时或秒为单位的时间尺度上发生。通过调整原始治疗计划以适应这些变化，图像引导放射治疗有可能在治疗过程中的任何时刻提供肿瘤和关键结构的最佳描绘和靶向。然而，这需要获取和处理大量的患者成像数据。该项目的科学目标是研究新的方法，将CT成像数据序列压缩成患者解剖结构在治疗过程中变化的统一时间表示。实际目标是创建一套图像处理工具，使图像引导的自适应放疗技术在临床中的常规应用成为可能。健康益处将是更精确的剂量靶向，使剂量增强和改善肿瘤控制。日常适应性治疗需要快速、最少监督的重新计算和在非刚性解剖图像之间传输治疗计划数据。该项目的第一个目标是为此目的开发一个快速和自动的可变形图像配准过程。在第二个目标中，该项目将使用这些可变形配准概念和工具来研究通过将变形模型与平面图像投影序列相匹配来重建时间相关CT图像的新方法。这将使人们能够在常规3D成像不切实际的情况下监测解剖变化，同时减少成像的补充辐射剂量。该项目的第三个目标是开发测量和验证程序，以评估这些新型图像配准和重建技术的准确性和可靠性。

DESCRIPTION (provided by applicant): Image-guided adaptive radiotherapy is an emerging paradigm intended to deal with the anatomical changes that a patient undergoes during treatment. These changes can include deformation and relative movement of organs, tumor shrinkage, tissue swelling, and other phenomena that alter the way radiation interacts with the anatomy. The changes can occur on a timescale of days, hours, or seconds. By adapting the original treatment plan to these changes, image-guided radiotherapy has the potential to provide optimal delineation and targeting of tumors and critical structures at any moment during treatment. However, this requires acquiring and working with a large volume of patient imaging data. The scientific objective of this project is to investigate novel methods to condense sequences of CT imaging data into a unified temporal representation of the patient's anatomy as it changes during the treatment process. The practical goal is to create a suite of image processing tools that will enable the routine application of image-guided adaptive radiotherapy techniques in the clinic. The health benefit will be more precise dose targeting, enabling dose intensification and improving tumor control. Daily adaptive therapy requires rapid, minimally-supervised recalculation and transfer of treatment planning data between images of non-rigid anatomy. The first aim of this project is to develop a fast and automatic deformable image registration process for this purpose. In its second aim, the project will use these deformable registration concepts and tools to investigate novel methods to reconstruct time-dependent CT images by matching deformation models to sequences of planar image projections. This will enable one to monitor anatomical change under conditions where conventional 3D imaging is impractical and at the same time will enable a reduction in the supplemental radiation dose from imaging. The third aim of the project is to develop measurement and validation procedures to assess the accuracy and reliability of these novel image registration and reconstruction techniques.