Super-Resolution PET Using Stepping of a Deliberately Misaligned Bed

使用故意错位床的步进进行超分辨率 PET

• 批准号: 8569816
• 负责人: SCOTT DEAN METZLER
• 金额: $ 20万
• 依托单位: UNIVERSITY OF PENNSYLVANIA
• 依托单位国家: 美国
• 财政年份: 2013
• 资助国家: 美国
• 起止时间: 2013-07-15 至 2015-06-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8569816
• 关键词: Address; Algorithms; Animals; Beds; Biological Models; Brain; Characteristics; Clinical; Code; Computer software; Couples; Data; Drops; Evaluation; Evolution; Future; Image; Laboratories; Lesion; Manufacturer Name; Measures; Mechanics; Methods; Metric; Modeling; Morphologic artifacts; Motion; Motor; Movement; Noise; Patients; Pattern; Positioning Attribute; Positron-Emission Tomography; Radial; Recovery; Relative (related person); Research; Resolution; Sampling; Scanning; Side; Signal Transduction; Simulate; Solutions; Structure; System; Techniques; Testing; Time; Vendor; body system; clinically relevant; cost; data acquisition; design; detector; improved; novel; pre-clinical; public health relevance; reconstruction; response; retinal rods; simulation; statistics; wasting

DESCRIPTION (provided by applicant): The objective of this proposal is to test two hypotheses of the imaging characteristics of positron emission tomography (PET): (1) that substantial improvements in reconstruction accuracy can be obtained for whole-body PET systems by super-sampling voxels during acquisition through the near-continuous motion of the patient bed along a direction intentionally - but carefully and accurately - misaligned with respect to the scanner's axial direction; and (2) that super-sampling will allow resolution improvement with iterative algorithms using resolution-recovery techniques, beyond what those algorithms can achieve without super-sampling. Super-resolution through wobbling is a technique historically used in early brain PET systems to improve the sampling, which would typically improve resolution and reduce artifacts. With the introduction of block detectors and whole-body systems, wobbling disappeared because its mechanical cumbersomeness and added expense were not justified since the impact on reconstruction was negligible. This is because the block detectors greatly reduced the crystal size, reducing the importance of crystal size on overall system resolution in comparison with other effects such as acolinearity and signal distortions in readout. Thus, the sampling improved disproportionately to the resolution. Two significant changes have occurred since wobbling was removed from scanners: (1) 3D acquisitions greatly increased the count statistics, which supports the accurate reconstruction of smaller features; and (2) resolution-recovery iterative algorithms have become commonplace. We believe that improving sampling will result in increased accuracy and resolution of modern reconstructions while artifacts will be reduced because resolutions are once again becoming better in comparison to the sampling. We propose a novel method for increasing sampling, including axial sampling, that does not require additional hardware, making the solution possibly attractive to vendors for future systems and as low-cost upgrades to existing systems, if the hypotheses of this proposal are confirmed. The method introduces a small angle in the bed alignment combined with the use of existing bed motors to super-sample the object, requiring no additional scan time. When the bed moves axially, a small transaxial shift results. The specific aims of this proposal include: (i) determining through simulation the optimal stepping pattern and bed-alignment angle; (ii) modifying existing reconstruction software to incorporate the bed-position information; and (iii) experimentally test the method on a TOF research scanner, LaPET, that is in our laboratory. These aims will allow us to fully address the hypotheses of this proposal.

描述（由申请人提供）：该提案的目的是测试两个假设的假设，即正电子发射断层扫描（PET）的成像特征（PET）：（1）可以通过在脚步和准确的方向上依次依次依次依次依靠，通过方向进行临时，可以通过超级放样的素食来获得全身PET系统的重建精度，从而获得全身PET系统的实质性提高 - （2）超级采样将使用分辨率回收技术通过迭代算法进行分辨率改进，而不是这些算法在没有超级采样的情况下可以实现的目标。超级分辨率通过摇摆是一种历史上用于改善抽样的早期脑宠物系统中的技术，通常会改善分辨率并减少工件。随着块探测器和全身系统的引入，摇摆不定，因为它的机械性麻烦和增加的费用是没有道理的，因为对重建的影响可以忽略不计。这是因为与其他效果相比，块检测器大大降低了晶体尺寸，从而降低了晶体大小对整体系统分辨率的重要性，例如读读量中的丙氨酸和信号扭曲。因此，采样改善了分辨率。自从扫描仪中撤离摇摆以来，发生了两个重大变化：（1）3D采集大大增加了计数统计，这支持了准确重建较小的特征； （2）分辨率恢复迭代算法已变得司空见惯。我们认为，改进采样将导致现代重建的准确性和分辨率提高，而工件将减少，因为与采样相比，分辨率再次变得更好。我们提出了一种增加采样（包括轴向采样）的新方法，该方法不需要其他硬件，如果确认了该提案的假设，则该解决方案可能会吸引供应商的未来系统，并将其作为对现有系统的低成本升级。该方法在床对齐中引入了一个小角度，并使用现有的床电动机将物体进行超级样本，不需要额外的扫描时间。当床轴向移动时，会产生较小的持续移动。该提案的具体目的包括：（i）通过模拟确定最佳的踏脚模式和床对准角度； （ii）修改现有的重建软件以合并床位信息； （iii）在我们的实验室中，对TOF研究扫描仪（TOF）研究扫描仪进行实验测试。这些目标将使我们能够充分解决该提案的假设。