Scatter Correction for Cone-Beam CT to Improve Radiation Therapy Treatments

描述（由申请人提供）：图像引导放射治疗（IGRT）为肿瘤提供准确的放射治疗，通常用于各种癌症部位。在过去的10-15年里，图像制导技术出现了爆炸式增长。机载X射线成像从二维发展到三维，锥形束计算机断层扫描（CBCT）越来越多地在放射治疗机上实施。尽管如此，CBCT目前的使用受到其主要由于散射伪影导致的较差图像质量的极大阻碍，并且临床应用仅限于治疗设置。具有高HU精度的定量CBCT图像对于剂量验证和自适应放射治疗特别重要，但仍然无法实现。X射线散射污染随着照射体积的大小增加而增加。锥形束投影中的大散射信号导致CT图像中的对比度降低和严重的阴影/条纹伪影，这被认为是CBCT图像质量的基本限制。散射校正是近二十年来一个非常活跃的研究领域。该问题在人体成像中是具有挑战性的，因为散射与初级比（SPR）大并且成像对象具有高异质性。一个标准的解决方案仍然不清楚。为了方便CBCT在放射治疗中的应用，我们提出了一种新的散射校正方法的基础上的一个独特的辐射治疗。由于固有散射信号小得多，诊断性多探测器CT（MDCT）可获得准确的CT图像，并常规用于治疗计划。使用MDCT图像作为患者的“自由”先验信息，我们使用简单而有效的图像处理技术估计和校正CBCT投影中的散射。我们的方法是不同于其他CBCT校准方法，它完全依赖于MDCT图像提供病人的解剖细节。我们使用有限的患者信息的MDCT图像，CBCT为基础的治疗监测的优点，因此保留。我们在一个良好表征的桌面系统上进行的初步体模研究表明，所提出的散射校正将CT数误差从~350 HU降低到~5 HU，并大大提高了低对比度物体的可见性。本研究计划的总体目标是扩展和优化我们在桌面系统上的方法，并证明我们可以在临床CBCT系统上对患者实现20 HU的CT数准确度，并使用改进的CBCT进行准确的肿瘤勾画和剂量计算。我们的方法有可能成为一种颠覆性的技术，消除了高性能IGRT和自适应放射治疗准确剂量监测的障碍。 公共卫生相关性：该项目旨在为基本物理过程之一X射线散射提供校正解决方案，X射线散射限制了锥形束计算机断层扫描（CBCT）成像的质量及其在当前放射治疗中的图像引导应用。如果我们的方法被证明是有效的，它可以消除CBCT图像中的阴影和条纹伪影，使小的和低对比度的肿瘤更明显。该项目非常重要，因为它可能导致对肿瘤上的辐射剂量的准确监测的突破，这使得许多新的放射治疗技术的实施成为可能。

DESCRIPTION (provided by applicant): Image-guided radiation therapy (IGRT) provides accurate radiation delivery to the tumor and is being commonly used for various cancer sites. The last 10-15 years have witnessed an explosion of techniques for image guidance. On-board x-ray imaging evolves from two-dimensional to three-dimensional, and cone-beam computed tomography (CBCT) is being increasingly implemented on radiation therapy machines. Nonetheless, the current use of CBCT is greatly hindered by its poor image quality mainly due to scatter artifacts, and the clinical applications are limited to treatment setup. Quantitative CBCT images with high HU accuracy, which are particularly important for dose verification and adaptive radiation therapy, are still not achievable. The x-ray scatter contamination increases as the size of the irradiated volume increases. The large scatter signals in cone-beam projections lead to a contrast reduction and severe shading/streak artifacts in the CT images, which is considered the fundamental limitation of CBCT image quality. Scatter correction has been a very active research area in the last twenty years. The problem is challenging in human imaging since the scatter- to-primary ratio (SPR) is large and the imaged object has high heterogeneity. A standard solution still remains unclear. To facilitate the applications of CBCT in radiation therapy, we propose a new scatter correction method based on a unique feature of radiation therapy. With much smaller inherent scatter signals, diagnostic multi-detector CT (MDCT) obtains accurate CT images and is routinely used for treatment planning. Using the MDCT images as the "free" prior information of the patient, we estimate and correct for scatter in CBCT projections using simple and efficient image processing techniques. Our approach is distinct from other CBCT calibration methods, which totally rely on the MDCT image for providing the patient anatomic details. We use limited patient information from the MDCT image, and the merit of CBCT-based treatment monitoring is therefore retained. Our preliminary phantom study on a well-characterized tabletop system has shown that the proposed scatter correction reduces the CT number error from ~350 HU to ~5 HU and substantially increases the visibility of low-contrast objects. The overall goal of this research program is to extend and optimize our approach on the tabletop system, and to demonstrate that we can achieve a CT number accuracy of 20 HU on patients on a clinical CBCT system and use the improved CBCT for accurate tumor delineation and dose calculation. Our method has a potential to be a disruptive technology that removes hurdles toward high- performance IGRT and accurate dose monitoring for adaptive radiation therapy. PUBLIC HEALTH RELEVANCE: The project aims to provide a correction solution to one of the fundamental physical processes, x-ray scatter, which limits the quality of cone-beam Computed Tomography (CBCT) imaging and its applications of image guidance in the current radiation therapy. If our method proves to be effective, it can remove the shading and streak artifacts in a CBCT image and make small and low-contrast tumors more visible. This project is very significant in that it could lead to a breakthrough toward accurate monitoring of delivered radiation dose on the tumor, which makes implementations of many new radiation therapy techniques possible.