Simulation Tools for 3D and 4D CT and Dosimetry

摘要 光子计数CT(PCCT)是CT成像的一项重大技术进步。使用光子计数来代替 目前的能量集成探测器，PCCT在空间分辨率、伪影等方面具有优异的性能 减少，最值得注意的是，材料分解。PCCT的能源差异化实用程序提供了更多 准确区分不同材料，优化和扩大造影剂在CT中的应用。有了这些 能力，PCCT可以显著促进定量成像，减少辐射暴露，并使 在功能和生理成像方面超越现有CT技术的革命性新应用。 为了充分发挥PCCT在临床实践中的潜力，该技术需要全面的评估和 基于应用程序的优化。PCCT的有效设计和部署依赖于许多设计和使用 考虑到最终的临床效用，应该做出的选择。做出这些选择需要很大的规模 在实际病人身上进行试验。然而，考虑到需要做出许多决定，这样的试验具有挑战性。 在原型开发之前，目前可用的PCCT扫描仪原型数量有限，以及通常未知的 病人图像中的事实真相。即使对于现有的原型系统，许多决策也需要重复试验 通过多次收购。考虑到辐射安全问题和成本，这是不道德和不切实际的。 这些挑战可以通过利用虚拟成像试验(VIT)来克服，使用计算机化的患者和 成像模型。VITS提供了一种确定最有效和最优化设计的有效手段 以及完全控制研究设计的成像技术的使用。 在我们之前的资助项目中，我们开发了一个VIT框架来评估标准的能量集成探测器CT 技术。在本项目中，我们将该框架的适用性扩展到光子计数探测器CT。 具体地说，我们增强了计算xCAT模体，以模拟必要的更高分辨率的细节 包括正常和异常的组织不均质性和器官内对比灌注多样性 人口(目标1)。为了对模型进行成像，我们开发了第一个能够模拟现有模型的PCCT模拟器 和新兴原型(目标2)。经优化的自愿退休计划框架将提供重要的基础， 全面评估和优化PCCT技术和应用。在目标3中，我们评估和 优化使用PCCT进行形态、纹理和成分的量化 心脏应用，在美国，PCCT可以提供显著影响的两种主要健康危害。结果是 将是第一个全面评估PCCT任务型优点和能力的机构， 确定癌症和心脏病变患者PCCT成像的最佳剂量 斑块/狭窄，并帮助建立PCCT在临床护理中的有效用途。

Abstract Photon-counting CT (PCCT) is a major technological advance in CT imaging. Using photon-counting instead of current energy-integrating detectors, PCCT can offer superior performance in terms of spatial resolution, artifact reduction, and most notably, material decomposition. PCCT’s energy differentiation utility offers an ability to more precisely distinguish different materials and optimize and expand the use of contrast agents in CT. With these abilities, PCCT can significantly facilitate quantitative imaging, reduce radiation exposure, and enable revolutionary new applications in functional and physiological imaging beyond existing CT techniques. To realize the full potential of PCCT in clinical practice, the technology needs comprehensive assessments and application-based optimizations. Effective design and deployment of PCCT depends on many design and use choices that should be made in view of the eventual clinical utility. Making these choices requires large scale trials on actual patients. However, such trials are challenging, considering the need to make many decisions prior to prototyping, the limited numbers of prototype PCCT scanners available today, and the often-unknown ground-truth in the patient images. Even for existing prototype systems, many decisions require repetitive trials with multiple acquisitions. This is both unethical and impractical considering radiation safety concerns and costs. These challenges can be overcome by utilizing virtual imaging trials (VITs) using computerized patients and imaging models. VITs provide an efficient means with which to determine the most effective and optimized design and use of imaging technologies with complete control over the study design. In our prior funded project, we developed a VIT framework to evaluate standard energy-integrating detector CT technologies. In this project, we expand the applicability of this framework to photon-counting detector CT. Specifically, we enhance our computational XCAT phantoms to model the necessary higher-resolution detail including normal and abnormal tissue heterogeneities and intra-organ contrast perfusion diversity across populations (Aim 1). To image the phantoms, we develop the first PCCT simulator capable of mimicking existing and emerging prototypes (Aim 2). The enhanced VIT framework will provide the essential foundation with which to comprehensively evaluate and optimize PCCT technologies and applications. In Aim 3, we assess and optimize the use of PCCT for morphological, textural, and compositional quantification in select oncologic and cardiac applications, two leading health detriments in the US where PCCT can offer a notable impact. The results will be the first of their kind in comprehensively evaluating the task-based merits and capabilities of PCCT, determining optimum dose per patient size for PCCT imaging of patients for cancerous lesions and cardiac plaque/stenoses, and helping to establish the effective utility of PCCT in clinical care.