Positron emission tomography (PET) has been widely used for the diagnosis of serious diseases including cancer and Alzheimer's disease, based on the uptake of radiolabelled molecules that target certain pathological signatures. Recently, a novel imaging mode known as positronium lifetime imaging (PLI) has been shown possible with time-of-flight (TOF) PET as well. PLI is also of practical interest because it can provide complementary disease information reflecting conditions of the tissue microenvironment via mechanisms that are independent of tracer uptake. However, for the present practical systems that have a finite TOF resolution, the PLI reconstruction problem has yet to be fully formulated for the development of accurate reconstruction algorithms. This paper addresses this challenge by developing a statistical model for the PLI data and deriving from it a maximum-likelihood algorithm for reconstructing lifetime images alongside the uptake images. By using realistic computer simulation data, we show that the proposed algorithm can produce quantitatively accurate lifetime images.

翻译：正电子发射断层扫描（PET）已被广泛应用于包括癌症和阿尔茨海默病在内的严重疾病诊断，其原理基于特定病理标志物靶向的放射性标记分子的摄取。近年来，一种被称为正电子素寿命成像（PLI）的新型成像模式已被证实可利用飞行时间（TOF）PET实现。由于PLI能够通过独立于示踪剂摄取的机制反映组织微环境状态并提供互补性病变信息，因此具有重要的临床应用价值。然而，对于现有具有有限TOF时间分辨率的实用系统而言，PLI重建问题尚未被完整地公式化以开发精确的重建算法。本文通过构建PLI数据的统计模型，并由此推导出同时重建寿命图像与摄取图像的最大似然算法，解决了这一挑战。利用真实计算机仿真数据，我们验证了所提算法能够生成定量精确的寿命图像。