Supplemental transmission aided attenuation correction for high performance quantitative PET imaging

项目摘要 来自组合PET-CT和PET-MR的定量示踪剂图像越来越多地用于放射学检查。 决策和临床试验。基于CT和MR的PET光子衰减数据校正，通常 对示踪剂定量的最大影响，可能导致对受试者的辐射剂量增加或需要长时间的 额外的专用MR扫描。使用PET信号的人工智能算法 仅从受试者开始估计衰减已经显示出有希望的早期结果，但是， 当应用于与训练数据不同的检查时，性能降低。重建方法， 从受检者PET信号联合估计测量的衰减和示踪剂对比度两者表示 可行的替代方案，但迄今为止，未能与CT方法的量化相匹配。因此，没有 用于PET衰减校正的单一方法，其始终产生高量化，并且不 目前存在危及患者安全或吞吐量的问题。这是一个重要的问题，因为研究和 临床研究结果必须平衡这些实际问题与数据质量。本建议的总体目标是 开发和表征高性能衰减校正方案，该方案利用PET 来自受试者的信号和可变活动外部源。核心假设是， 与使用PET的重建算法相比， 信号仅源自受试者，独立于成像研究。这两个具体目标包括： 开发和验证用于校正PET图像的光子的基于补充传输的算法 以及2）原型设计和表征能够 动态变化的外部源活动。目标1的结果将是重建算法， 优化以生成一些最常见的临床PET研究的定量PET数据。在目标2下，a 原型设备，可以重复性地改变外部源活动，以最大限度地提高示踪剂 在最大程度上减少了由量化引起的对患者示踪剂图像噪声的不可避免的退化的同时， 任何外部来源的介绍，将产生。本发明是一种衰减校正策略， 大大减轻了以前的关节重建方法提供定量PET诊断的局限性 其预期匹配银标准CT方法的那些。这一点很重要，因为 接受脑部和心脏PET-CT扫描的患者，预计所提出的方法将受益， 稳步增长。对于PET-MR，该方法可以改善MR受限的示踪剂量化。 通过消除对非诊断性仅衰减MR的需求， 收购。因此，所提出的策略具有很大的潜力，以显着改善放射性决策- 制造和临床试验结果依赖于定量PET摄取测量。

PROJECT SUMMARY Quantitative tracer images from combined PET-CT and PET-MR are increasingly being utilized for radiological decision-making and clinical trials. CT and MR based data corrections for PET photon attenuation, typically the largest impact on tracer quantification, can lead to increased radiation dose to the subject or require lengthy additional dedicated MR scans, respectively. Artificial intelligence algorithms that use the PET signal originating from the subject alone to estimate attenuation have shown promising early results, but, can have reduced performance when applied to exams different from the training data. Reconstruction methods that jointly estimate both the measured attenuation and tracer contrast from the subject PET signal represent a viable alternative, but, to date, have failed to match the quantification of CT approaches. Consequently, no single approach for PET attenuation correction that consistently produces high quantification and does not compromise patient safety or throughput currently exists. This is an important problem, since research and clinical findings must balance these practical issues with data quality. The overall objective of this proposal is to develop and characterize a high performance attenuation correction scheme that utilizes both the PET signal from the subject and a variable activity external source. The central hypothesis is that the proposed reconstruction method will have significantly improved performance over reconstruction algorithms using PET signal originating from the subject alone, independent of the imaging study. The two specific aims include: 1) developing and validating a supplemental transmission-based algorithm for correcting PET images for photon attenuation during commercial PET imaging and 2) prototyping and characterizing a device capable of dynamically varying external source activity. The result of Aim 1 will be a reconstruction algorithm that is optimized to produce quantitative PET data for some of the most common clinical PET studies. Under Aim 2, a prototype device that can repeatability vary the external source activity in order to maximize tracer quantification while minimizing the unavoidable degradation to patient tracer image noise, caused by the introduction of any external source, will be produced. The innovation is an attenuation correction strategy that greatly mitigates the limitations of previous joint reconstruction methods to deliver quantitative PET diagnostics that are expected to match those of silver standard CT approaches. This is significant because the number of patients receiving brain and cardiac PET-CT scans, exams the proposed method is expected to benefit, is steadily increasing. For PET-MR, the method may improve tracer quantification where MR has limited performance and increase patient throughput by eliminating the need for non-diagnostic attenuation-only MR acquisitions. Thus, the proposed strategy has great potential to significantly improve radiological decision- making and clinical trial findings that rely on quantitative PET uptake measurements.