Department of Electrical and Computer Systems Engineering, Monash University, Melbourne, Victoria, Australia; Department of Computer Science and Engineering, IIT Bombay, Mumbai, India; IITB-Monash Research Academy, Mumbai, India.
Monash Biomedical Imaging, Monash University, Melbourne, Victoria, Australia.
Neuroimage. 2021 Jun;233:117928. doi: 10.1016/j.neuroimage.2021.117928. Epub 2021 Mar 11.
Functional positron emission tomography (fPET) imaging using continuous infusion of [18F]-fluorodeoxyglucose (FDG) is a novel neuroimaging technique to track dynamic glucose utilization in the brain. In comparison to conventional static or dynamic bolus PET, fPET maintains a sustained supply of glucose in the blood plasma which improves sensitivity to measure dynamic glucose changes in the brain, and enables mapping of dynamic brain activity in task-based and resting-state fPET studies. However, there is a trade-off between temporal resolution and spatial noise due to the low concentration of FDG and the limited sensitivity of multi-ring PET scanners. Images from fPET studies suffer from partial volume errors and residual scatter noise that may cause the cerebral metabolic functional maps to be biased. Gaussian smoothing filters used to denoise the fPET images are suboptimal, as they introduce additional partial volume errors. In this work, a post-processing framework based on a magnetic resonance (MR) Bowsher-like prior was used to improve the spatial and temporal signal to noise characteristics of the fPET images. The performance of the MR guided method was compared with conventional denosing methods using both simulated and in vivo task fPET datasets. The results demonstrate that the MR-guided fPET framework denoises the fPET images and improves the partial volume correction, consequently enhancing the sensitivity to identify brain activation, and improving the anatomical accuracy for mapping changes of brain metabolism in response to a visual stimulation task. The framework extends the use of functional PET to investigate the dynamics of brain metabolic responses for faster presentation of brain activation tasks, and for applications in low dose PET imaging.
使用连续输注 [18F]-氟脱氧葡萄糖 (FDG) 的功能正电子发射断层扫描 (fPET) 成像是一种新型的神经影像学技术，可用于追踪大脑中葡萄糖的动态利用。与传统的静态或动态团注 PET 相比，fPET 使血浆中的葡萄糖保持持续供应，从而提高了测量大脑中动态葡萄糖变化的敏感性，并能够在基于任务和静息状态的 fPET 研究中对大脑的动态活动进行映射。然而，由于 FDG 浓度低和多环 PET 扫描仪的灵敏度有限，在时间分辨率和空间噪声之间存在折衷。来自 fPET 研究的图像受到部分容积误差和残留散射噪声的影响，这可能导致大脑代谢功能图出现偏差。用于对 fPET 图像进行去噪的高斯平滑滤波器不是最优的，因为它们会引入额外的部分容积误差。在这项工作中，使用基于磁共振 (MR) Bowsher 先验的后处理框架来改善 fPET 图像的空间和时间信号噪声特性。使用模拟和体内任务 fPET 数据集比较了 MR 引导方法与传统去噪方法的性能。结果表明，MR 引导的 fPET 框架可以对 fPET 图像进行去噪，并改善部分容积校正，从而提高识别大脑激活的灵敏度，并提高响应视觉刺激任务的大脑代谢变化的解剖准确性。该框架扩展了功能 PET 的应用范围，用于研究大脑代谢反应的动力学，以更快地呈现大脑激活任务，并应用于低剂量 PET 成像。
