Fourier-based Methods for Image Reconstruction in PET

基于傅立叶的 PET 图像重建方法

• 批准号: 8054849
• 负责人: SAMUEL MATEJ
• 金额: $ 39.05万
• 依托单位: UNIVERSITY OF PENNSYLVANIA
• 依托单位国家: 美国
• 财政年份: 2002
• 资助国家: 美国
• 起止时间: 2002-04-01 至 2013-03-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8054849
• 关键词: Achievement; Attention; Automatic Data Processing; Back; Characteristics; Clinical; Clinical Data; Clinical Research; Computing Methodologies; Data; Databases; Deposition; Development; Discipline of Nuclear Medicine; Disease; Environment; Evaluation; Evaluation Studies; Event; Financial compensation; Generations; Goals; Grouping; Health; Human; Image; Imaging Device; Lead; Lesion; Location; Measures; Methods; Monitor; Nature; Outcome; Patients; Performance; Photons; Positron-Emission Tomography; Process; Property; Protocols documentation; Public Health; Running; Sampling; Simulate; System; Techniques; Testing; Time; Work; attenuation; base; cancer diagnosis; clinically relevant; comparative; computing resources; data space; design; detector; image reconstruction; improved; novel; novel strategies; operation; reconstruction; response; treatment planning; validation studies

DESCRIPTION (provided by applicant): The overall objective of this project is to improve the quality of images obtained by positron emission tomography (PET) for human studies in clinical nuclear medicine. This will be done by developing a fast and accurate computer method for generating images from basic photon-count data acquired by PET scanners having detectors with time-of-flight (TOF) capability. Data from TOF-PET systems contain additional information that permits better spatial localization of coincidence events, compared to conventional (non-TOF) scanners. TOF-PET scanners have been shown to yield significantly better images, especially for large patients; however, the full benefit of TOF has not yet been achieved in the clinical environment due to the relatively slow reconstruction techniques available for TOF-PET data. The proposed work involves the development and testing of an iterative computer method for statistical image reconstruction that makes specific use of the localized nature of TOF-PET data. The method is called DIRECT, short for Direct Image Reconstruction for TOF, and it involves grouping the TOF-PET data based on a novel combination of angular intervals in data space and voxel-like partitions in image space. The hypothesis is that this method will achieve high quantitative accuracy, combined with high computational efficiency, which is critical for obtaining these quantitative images in the clinical environment. High computational efficiency is needed for human studies, since a large amount of data is collected, the image space is sampled on a fine grid, and many iterations are required to accurately recover the activity levels at all locations in the body. Multi-frame studies (e.g., dual time point imaging, dynamic studies) involve multiple runs of the image reconstruction process for which a fast reconstruction technique is essential. In the DIRECT method, the novel grouping of TOF-PET data leads to high efficiency for many of the reconstruction operations; in particular, this grouping enables the operations of forward-projection and back-projection to be done using efficient Fourier-based methods. Achievement of high accuracy combined with high computational efficiency would be a significant step towards realizing the full potential of TOF-PET in the clinical environment, since in current practice performance is compromised for efficiency in order to complete routine whole-body studies in a practical time. Specific aim 1 is designed to formulate, implement, and investigate the DIRECT method for iterative image reconstruction in TOF-PET, focusing on the core components of the method. Specific aim 2 is designed to formulate, implement, and investigate those components of the DIRECT method that involve compensation for the non-ideal characteristics of measured data, including attenuation, scatter, randoms, and detector normalization. Specific aim 3 involves evaluation of the performance of DIRECT in comparison with other TOF-PET reconstruction techniques. PUBLIC HEALTH RELEVANCE: Positron emission tomography is now well established as a valuable imaging tool for the diagnosis of cancer and other diseases and for the planning and monitoring of treatment. The proposed work involves new methods for computer processing of data from a technically advanced generation of PET scanner; the new computer methods are designed to enable these scanners to reach their full potential, leading to improved accuracy of PET images. The proposed work is relevant to public health, since an improvement in the accuracy of PET images would lead to more accurate diagnosis of cancer and other diseases, more accurate planning of treatment, and more accurate monitoring of the response to therapy, leading in turn to better patient outcomes.

描述（由申请人提供）：本项目的总体目标是提高正电子发射断层扫描（PET）获得的图像质量，用于临床核医学中的人体研究。这将通过开发一种快速准确的计算机方法来实现，该方法用于从具有飞行时间（TOF）能力的探测器的PET扫描仪采集的基本光子计数数据生成图像。与传统（非TOF）扫描仪相比，来自TOF-PET系统的数据包含允许更好地空间定位符合事件的附加信息。TOF-PET扫描仪已被证明可以产生更好的图像，特别是对于体型较大的患者;然而，由于TOF-PET数据的重建技术相对较慢，TOF的全部益处尚未在临床环境中实现。拟议的工作涉及开发和测试的迭代计算机方法的统计图像重建，使具体使用的本地化性质的TOF-PET数据。该方法被称为DIRECT，是Direct Image Reconstruction for TOF的缩写，它涉及基于数据空间中的角度间隔和图像空间中的体素样分区的新颖组合对TOF-PET数据进行分组。假设该方法将实现高定量准确度，结合高计算效率，这对于在临床环境中获得这些定量图像至关重要。人体研究需要高计算效率，因为需要收集大量数据，在精细网格上对图像空间进行采样，并且需要多次迭代才能准确恢复体内所有位置的活动水平。多框架研究（例如，双时间点成像、动态研究）涉及图像重建过程的多次运行，快速重建技术对于该过程是必不可少的。在DIRECT方法中，TOF-PET数据的新颖分组导致许多重建操作的高效率;特别地，这种分组使得能够使用有效的基于傅立叶的方法来完成前向投影和反向投影的操作。实现高精度与高计算效率相结合将是实现TOF-PET在临床环境中的全部潜力的重要一步，因为在当前实践中，为了在实际时间内完成常规全身研究，性能会受到效率的影响。具体目标1旨在制定、实施和研究用于TOF-PET中迭代图像重建的DIRECT方法，重点关注该方法的核心组件。具体目标2旨在制定、实施和研究DIRECT方法中涉及补偿测量数据非理想特性的组件，包括衰减、散射、随机和探测器归一化。具体目标3涉及DIRECT与其他TOF-PET重建技术相比的性能评价。公共卫生关系：正电子发射断层摄影术现在已经被公认为是一种有价值的成像工具，用于癌症和其他疾病的诊断以及治疗的规划和监测。拟议的工作涉及计算机处理技术先进的一代PET扫描仪数据的新方法;新的计算机方法旨在使这些扫描仪能够充分发挥其潜力，从而提高PET图像的准确性。拟议的工作与公共卫生有关，因为PET图像准确性的提高将导致更准确地诊断癌症和其他疾病，更准确地规划治疗，更准确地监测对治疗的反应，从而导致更好的患者结果。