Four Dimensional Cone Beam CT for Image-guided Radiation Therapy

描述(申请人提供)：近年来，许多临床中心开发了利用诊断CT扫描仪和替代呼吸信号的四维CT(4DCT)成像方案。利用不同呼吸时相的4DCT图像体积，可以提取呼吸运动场，从而可以估计肿瘤的运动轨迹。所提取的运动场可以用于在给定的参考呼吸时相处扭曲图像体积和治疗计划。然而，从治疗计划的时间到治疗的实施时间，运动场和运动轨迹可能会发生变化。因此，重要的是要开发一种方法来监测运动轨迹的潜在变化，以便在实际治疗之前验证治疗计划，或者为治疗重新计划获得必要的信息。这促使研究人员将4DCT的概念和方法扩展到4D锥束CT(4DCBCT)的案例中，在这种情况下，获得的锥束投影使用替代呼吸信号被分类到不同的呼吸期。然而，4DCBCT有两个根本性的挑战，阻碍了它的图像质量的提高，从而阻碍了它的应用。第一个挑战是对香农/奈奎斯特抽样要求的严重违反。当获取的600个投影被选通到8-10个呼吸时相时，仅有60-80个锥束投影可用于重建每个呼吸时相。当标准的图像重建算法，如滤波后向投影(FBP)，应用于高度欠采样的数据集时，重建图像中的条纹伪影非常猖獗。4DCBCT的第二个挑战是给定呼吸时相的锥束投影数据的采样模式远不是最优的。这使得现有60-80个预测的使用效率大大低下。因此，目前的4DCBCT图像质量不足以在常规临床实践中用于提取准确的运动轮廓，无论是为了质量保证还是为了治疗重新计划目的。这项建议的总体目标是开发一种创新的方法来提高4DCBCT的图像质量，并展示其在图像引导放射治疗中的应用。核心使能技术是PI小组最新提出的一种图像重建方案，即先验图像约束压缩感知(PICCS)。使用这种新的方法，初步结果表明，CT图像可以用大约10-20个投影准确地重建，这使得获取的锥束投影能够选通到20-30个呼吸时相。因此，4DCBCT成像可以使用60秒的数据采集来实现，而不是延长4-5分钟的扫描时间。在这项提案中，中心假设是PICCS采集和图像重建方法应该能够重建用于放射治疗应用的高时间分辨率和无条纹的4DCBCT图像。这种新方法被称为PICCS-4DCBCT。该提案的具体目标是：(1)优化PICCS图像重建算法的实施；(2)开发和评估PICCS-4DCBCT数据采集协议；(3)使用PICCS-4DCBCT进行临床评估。该项目完成后，将开发出使用新型PICCS图像重建方法的精确4DCBCT，并将其用于图像引导放射治疗。这项新技术将能够准确地提取肿瘤运动信息，以补偿治疗前和治疗期间与呼吸相关的节内和/或节间运动。

DESCRIPTION (provided by applicant): In recent years, four-dimensional CT (4DCT) imaging protocols utilizing a diagnostic CT scanner and surrogate respiratory signal have been developed at many clinical centers. Using 4DCT image volumes at different respiratory phases, respiratory motion fields can be extracted, thereby allowing estimation of motion trajectory of the tumor. The extracted motion fields can be utilized to warp the image volume and treatment plan at a given reference respiratory phase. However, the motion fields and the motion trajectory may experience changes from the time of treatment planning to the time of treatment delivery. Thus, it is important to develop a method to monitor the potential changes to the motion trajectory to either verify the treatment plan before the actual treatment is delivered or obtain necessary information for treatment replanning. This motivated investigators to extend the 4DCT concept and methodology to the 4D cone-beam CT (4DCBCT) case, in which the acquired cone-beam projections are sorted into different respiratory phases using surrogate respiratory signals. However, there are two fundamental challenges in 4DCBCT that hinder the improvement of its image quality, and thus its applications. The first challenge is a significant violation of the Shannon/Nyquist sampling requirement. When the acquired 600 projections are gated into 8-10 respiratory phases, there are only 60-80 cone-beam projections available to reconstruct each respiratory phase. When standard image reconstruction algorithms, such as Filtered BackProjection (FBP), are applied to highly undersampled data sets, streaking artifacts are rampant in the reconstructed image. The second challenge in 4DCBCT is the sampling pattern of the cone-beam projection data for a given respiratory phase is far from optimal. This makes the use of the available 60-80 projections significantly inefficient. As a consequence, the current 4DCBCT image quality is insufficient to be utilized in routine clinical practice to extract accurate motion profiles either for quality assurance or for treatment replanning purposes. The overall objective of this proposal is to develop an innovative method to improve the 4DCBCT image quality and to demonstrate its use in image-guided radiation therapy. The central enabling technology is a newly proposed image reconstruction scheme by the PI's group, namely Prior Image Constrained Compressed Sensing (PICCS). Using this novel method, preliminary results have demonstrated that CT images can be accurately reconstructed using approximately 10-20 projections, which enables gating of the acquired cone- beam projection into 20-30 respiratory phases. As a result, 4DCBCT imaging can be achieved using a 60- second data acquisition, rather than a prolonged 4-5 minute scan time. In this proposal, the central hypothesis is that the PICCS acquisition and image reconstruction method should enable reconstruction of high temporal resolution and streak-free 4DCBCT images for radiation therapy applications. This new method is referred to as PICCS-4DCBCT. The specific aims of the proposal are to: (1) Optimize the implementation of the PICCS image reconstruction algorithm; (2) Develop and evaluate PICCS-4DCBCT data acquisition protocols; (3) Conduct clinical evaluations using PICCS-4DCBCT. Upon the completion of the project, accurate 4DCBCT using the novel PICCS image reconstruction method will have been developed and validated for image-guided radiation therapy. This new technology will enable accurate extraction of tumor motion information for compensation of the respiratory-related intrafraction and/or interfraction motion before and during treatment delivery.