使用相对Patlak图进行全身参数成像
Total-Body Parametric Imaging Using Relative Patlak Plot
AI总结：
该研究提出相对Patlak（RP）图结合自监督深度核降噪策略，消除对早期输入函数的依赖，从20分钟临床扫描动态数据中生成高质量全身PET参数图像，显著提升病灶对比度并实现心肌可视化。
摘要：
标准Patlak图广泛用于描述动态PET成像中的FDG动力学。由于需要全时输入函数，全身Patlak参数成像仍然受到限制。在这里，我们展示了用于全身参数成像的相对Patlak（RP）图，它消除了对早期时间输入函数的需求，并将其应用于以列表模式获取的临床20分钟扫描。我们证明了RP截距b'相当于相对于血液的标准化摄取值（SUV）的比率，而RP斜率Ki'等于标准Patlak Ki乘以每个受试者的全局缩放因子。将RP应用于短扫描时间（20分钟）的一个挑战是参数图像中的高噪声。我们应用了深度核方法进行降噪。以标准Patlak图为参考，在22名接受1小时动态18F-FDG扫描的人类受试者中，使用uEXPLORER评估了RP方法在全身参数成像中的病灶定量、病灶与背景对比度以及心肌可视化方面的表现。RP方法还应用于两名癌症患者在注射后1小时或2小时从临床标准20分钟扫描重新生成的动态数据。我们证明了使用具有自监督深度核降噪策略的RP图从20分钟动态扫描中获取高质量参数图像是可行的。RP Ki'与病灶和主要器官中的Ki高度相关，证明了其跨受试者的定量潜力。与常规SUV相比，Ki'图像显著提高了病灶对比度，并使心肌可视化成为可能，以进行潜在的心脏评估。将RP参数成像应用于两次临床扫描也显示出类似的益处。使用RP图的全身PET能够从20分钟临床扫描的动态数据中生成参数图像。
英文摘要：
Standard Patlak plot is widely used to describe FDG kinetics for dynamic PET imaging. Whole-body Patlak parametric imaging remains constrained due to the need for a full-time input function. Here, we demonstrate the Relative Patlak (RP) plot, which eliminates the need for the early-time input function, for total-body parametric imaging and its application to clinical 20-min scan acquired in list-mode. We demonstrated that the RP intercept b' is equivalent to a ratio of standardized uptake value relative to the blood, while the RP slope Ki' is equal to the standard Patlak Ki multiplied by a global scaling factor for each subject. One challenge in applying RP to a short scan duration (20 min) is the high noise in parametric images. We applied a deep kernel method for noise reduction. Using the standard Patlak plot as the reference, the RP method was evaluated for lesion quantification, lesion-to-background contrast, and myocardial visualization in total-body parametric imaging with uEXPLORER in 22 human subjects who underwent a 1-h dynamic 18F-FDG scan. The RP method was also applied to the dynamic data regenerated from a clinical standard 20-min scan either at 1-h or 2-h post-injection for two cancer patients. We demonstrated that it is feasible to obtain high-quality parametric images from 20-min dynamic scans using the RP plot with a self-supervised deep-kernel noise reduction strategy. The RP Ki' highly correlated with Ki in lesions and major organs, demonstrating its quantitative potential across subjects. Compared to conventional SUVs, the Ki' images significantly improved lesion contrast and enabled visualization of the myocardium for potential cardiac assessment. The application of RP parametric imaging to two clinical scans also showed similar benefits. Total-body PET with the RP plot is feasible to generate parametric images from the dynamic data of a 20-min clinical scan.
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