Positron emission tomography (PET) imaging is widely used in a number of clinical applications, including cancer and Alzheimer's disease (AD) diagnosis, monitoring of disease development, and treatment effect evaluation. Statistical modeling of PET imaging is essential to address continually emerging scientific questions in these research fields, including hypotheses related to evaluation of effects of disease modifying treatments on amyloid reduction in AD and associations between amyloid reduction and cognitive function, among many others. In this paper, we provide background information and tools for statisticians interested in developing statistical models for PET imaging to pre-process and prepare data for analysis. We introduce our novel pre-processing and visualization tool TRAECR (Template registration, MRI-PET co-Registration, Anatomical brain Extraction and COMBAT/RAVEL harmonization) to facilitate data preparation for statistical analysis.

翻译：正电子发射断层扫描（PET）成像广泛应用于多种临床领域，包括癌症与阿尔茨海默病（AD）诊断、疾病进展监测及治疗效果评估。PET成像的统计建模对于应对这些研究领域中不断涌现的科学问题至关重要，例如评估疾病修饰治疗对AD患者淀粉样蛋白减少的影响、探究淀粉样蛋白减少与认知功能之间的关联等。本文为有意开发PET成像统计模型的统计学家提供了背景信息与工具，以支持数据的预处理与分析准备工作。我们介绍了新型预处理与可视化工具TRAECR（模板配准、MRI-PET协同配准、解剖学脑部提取及COMBAT/RAVEL标准化），旨在为统计分析的数据准备提供便利。