Targeted Imaging in Helical cone-beam CT

描述(由申请人提供)：在该项目中，我们建议开发、优化和转换用于螺旋锥束计算机断层扫描(CBCT)图像重建的先进的、精确的算法。近似重建算法已经被应用于临床螺旋CT，它们已经被优化，并且在许多临床病例中效果良好。然而，放射科医生每天也会遇到包含临床上重要伪影的CBCT图像，达到干扰准确诊断的水平。最近开发的精确算法有可能消除或减轻伪影，同时还可以减少辐射剂量。为了将这些算法转化为临床应用，必须克服许多技术障碍。在这一点上，我们认为解决这些技术问题实际上比进一步纯粹的理论算法开发更重要。解决这些具有临床意义的技术问题还将提供一个范例和路线图，如果引入重大的新硬件开发，未来的研究工作可以遵循这些范例和路线图。提出的研究旨在填补重要的空白，将理论上精确的算法转化为提高图像质量，减少成像剂量，并通过解决这些问题来实现螺旋CBCT的新成像功能。为了实现将新开发的精确算法转化为实际螺旋CBCT的总体目标，我们设计了四个具体目标：(1)开发和实现针对实际螺旋CBCT的重建算法；(2)开发和优化定量CT的精确重建算法；(3)使用数值和物理模型数据测试和评估算法；以及(4)在模型和观察者研究中测试和评估算法。前两个目标集中在(A)开发、优化和翻译可显著减少当前螺旋CBCT临床应用中的图像伪影的精确算法和(B)研究和利用数据冗余以减少螺旋CBCT的成像剂量和图像伪影。最后两个目标是为了在实际应用中彻底评估算法的性能。评估研究的一个关键动机是为目标1和目标2中的任务提供指导。我们相信，该项目具有很高的科学和临床意义，因为它可以加快精确算法的翻译，以提高图像质量和减少成像剂量。它还可以产生新的见解，对开发新的CBCT成像能力具有重要意义。该项目在解决算法转化为临床应用中的关键问题以及调查和使用数据冗余以提高图像质量和降低成像剂量方面具有多方面的高创新性。 公共卫生相关性：该项目的目标是研究、开发和翻译螺旋锥束计算机断层扫描(CBCT)的创新重建算法和成像配置。这项研究不仅可以提高目前许多临床方案的诊断准确性，而且还可以为新的应用开发一系列潜在的新方案。该项目还可以揭示对进一步改进先进的CBCT和其他用于或正在开发用于临床和临床前研究的断层成像模式的重大影响的新见解。

DESCRIPTION (provided by applicant): In the project, we propose to develop, optimize, and translate advanced, exact algorithms for image reconstruction in helical cone-beam computed tomography (CBCT). Approximate reconstruction algorithms have been used for clinical helical CBCT, and they have been optimized, and work well, for many clinical cases. However, on a daily basis, radiologists also encounter CBCT images containing clinically significant artifacts, attaining levels that interfere with accurate diagnosis. The recently developed exact algorithms have the potential to eliminate or mitigate the artifacts while also reducing radiation dose. In order to translate these algorithms into clinic applications, many technical hurdles must be overcome. At this point, we believe that tackling these technical issues is actually more important than pursuing further purely theoretical algorithm development. Working through these technical problems of clinical significance will also provide a paradigm and roadmap that can be followed by research effort in the future if and when major new hardware developments are introduced. The proposed research is intended to fill in important gaps toward translating the theoretically exact algorithms to improving image quality, reducing imaging dose, and enabling new imaging capabilities in helical CBCT by tackling the issues. To achieve the overall objective of translating the newly developed exact algorithms to practical helical CBCT, we have designed four specific aims: (1) to develop and implement reconstruction algorithms tailored to practical helical CBCT; (2) to develop and optimize exact reconstruction algorithms for quantitative CT; (3) to test and evaluate the algorithms by using numerical and physical phantom data; and (4) to test and evaluate the algorithms in model- and human-observer studies. The first two aims focus on (a) the development, optimization, and translation of the exact algorithms that can significantly reduce the image artifacts in current clinical application of helical CBCT and (b) the investigation and exploitation of data redundancy for reducing the imaging dose and image artifacts in helical CBCT. The last two aims are designed for thorough evaluation of the algorithm performance in practical applications. A key motivation for the evaluation studies is to provide guidance for the tasks in Aims 1 and 2. We believe that the project is of high scientific and clinical significance in that it can expedite the translation of exact algorithms for improving image quality and reducing imaging dose. It can also produce new insights of significant implications for developing new CBCT imaging capability. The project has multiple facets of high innovation for addressing critical issues in the algorithms' translation to clinical applications and for investigating and using data redundancy for improving the image quality and lowering the imaging dose. PUBLIC HEALTH RELEVANCE: The objective of the project is to investigate, develop, and translate innovative reconstruction algorithms and imaging configurations for helical cone-beam computed tomography (CBCT). The research can lead not only to an improved diagnostic accuracy for many of the current clinical protocols and but also to a host of potentially new protocols for new applications. The project can also reveal new insights of significant implications for further improving advanced CBCT and other tomographic imaging modalities that are used in, or are under development for, clinical and pre-clinical studies.