Explore random sampling for dose reduction and scatter removal in cone beam CT

项目总结 锥形束计算机断层扫描(CBCT)通常用于图像引导放射治疗(IGRT) 患者的体位目的。需要频繁和准确的CBCT，以确保设置的重复性，这是 对于计划目标体积边缘的减少，从而减少对正常组织的剂量并允许 剂量递增。CBCT还在适应性放射治疗(ART)中发挥关键作用，支持最新的 用于治疗重新计划的患者几何形状。阻碍CBCT在IGRT和IGRT中广泛应用的两大问题 艺术。1)影像剂量过大。每个疗程高达100~300cGy射线的成像剂量会增加 继发性癌症和基因缺陷。2)图像质量较低，主要原因是散布。散射的x射线光子在 该图像探测器降低了CBCT对比度，并引入了高达350HU的图像误差。除了降级 患者设置的准确性、散布伪影阻碍了CBCT在ART中的定量应用，例如CT到CBCT 可变形配准和剂量计算。多年来，这两个问题一直是分开的 地址。迭代算法，特别是压缩传感(CS)类型的迭代算法在重建方面显示出希望 具有欠采样数据的CBCT。然而，仅靠它不能解决分散问题。虽然 基于测量的方法使用光束阻挡器直接探测散射，准确且稳健，部分 丢失主数据会导致较大的重建误差。在本项目中，我们提出要解决这两个问题 在一个统一的框架中。具体地说，我们将使用一种创新设计的旋转光束阻挡器来随机 阻止每个投影内的X射线测量。生成的阴影区域允许散布测量 和移除。随机欠采样产生具有良好数学特性的投影矩阵 允许在CS框架下进行高质量的CBCT重建。初步研究表明， 这一方法的可行性和有效性。该项目的目标是开发和优化建议的 并展示其在减少剂量方面的优势(与临床标准相比超过90% 扫描)和质量改进(&lt；20Hu错误)，以及其对IGRT和ART的临床影响。我们将继续追查 三个具体目标(SA)。SA1.开发一个软件系统来支持提议的工作流程。SA2.研究， 通过蒙特卡罗模拟和体模实验，设计和优化了波束阻挡器。SA3.评估 对患者研究的临床影响。与传统方法分开处理 成像剂量和散射问题，我们的方法将在统一的框架内无缝地解决它们 结合了两种最先进的技术的优点，同时消除了它们的缺点。它将支持IGRT 和ART具有新颖而实用的CBCT方法，大大提高了图像质量并减少了 成像剂量。虽然专注于放射治疗中的CBCT，但该方法可以演变为一种标准解决方案 其他体积CT系统。对于非癌症患者，在减少成像剂量的同时，更关键的是 保持图像质量。因此，我们的工作有望惠及几乎所有的放射科患者。

PROJECT SUMMARY Cone beam computed tomography (CBCT) is routinely used in image-guided radiation therapy (IGRT) for patient positioning purpose. Frequent and accurate CBCT is desired to ensure setup reproducibility, which is critical for planning target volume margin reduction and hence reducing dose to normal tissue and permitting dose escalations. CBCT also plays a key role in adaptive radiotherapy (ART) by supporting the up-to-date patient geometry for treatment replanning. Two major issues hinder wide applications of CBCT in IGRT and ART. 1) Excessive imaging dose. The imaging dose up to 100~300 cGy per treatment course elevates risks of secondary cancer and genetic defects. 2) Low image quality mainly due to scatter. Scattered x-ray photons at the image detector reduce CBCT contrasts and introduce image errors up to 350 HU. Besides degrading patient setup accuracy, scatter artifacts prevent CBCT from quantitative applications in ART, e.g. CT-to-CBCT deformable registration and dose calculations. Over the years, these two problems have been separately addressed. Iterative algorithms, particularly of compressed sensing (CS) type, show promise on reconstructing CBCT with undersampled data. It alone, however, cannot address the scatter problem. Although measurement-based methods using a beam blocker directly probe scatter accurately and robustly, partially missing primary data causes large reconstruction errors. In this project, we propose to solve the two problems in a unified framework. Specifically, we will use an innovatively designed rotating beam blocker to randomly block x-ray measurements within each projection. The generated shadow area allows scatter measurement and removal. The random undersampling yields a projection matrix with favorable mathematical properties that permit high-quality CBCT reconstruction under CS framework. Preliminary studies have demonstrated the feasibility and effectiveness of this approach. The goal of this project is to develop and optimize the proposed system and to demonstrate its advantages in dose reduction (more than 90% compared to the clinical standard scan) and quality improvement (<20 HU error), as well as its clinical impacts on IGRT and ART. We will pursue three Specific Aims (SAs). SA1. Develop a software system to support the proposed workflow. SA2. Research, design and optimize the beam blocker via Monte Carlo simulations and phantom experiments. SA3. Evaluate clinical impacts in patient studies. In contrast to conventional approaches that separately addressed the imaging dose and scatter problems, our method will solve them in a unified framework with seamlessly combined strengths of two state-of-the-art techniques while eliminating their drawbacks. It will empower IGRT and ART with a novel and practical CBCT approach with substantially improved image quality and reduced imaging dose. Although focusing on CBCT in radiotherapy, the method can evolve into a standard solution for other volumetric CT systems. For non-cancer patients, it is more crucial to reduce imaging dose while maintaining image quality. As such, our work is expected to benefit almost all radiology patients.