The Alzheimer's Disease Neuroimaging Initiative (ADNI) provides a comprehensive multimodal neuroimaging resource for studying aging and Alzheimer's disease (AD). Since its second wave, ADNI has increasingly collected resting-state functional MRI (rs-fMRI), a valuable resource for discovering brain connectivity changes predictive of cognitive decline and AD. A major barrier to its use is the considerable variability in acquisition protocols and data quality, compounded by missing imaging sessions and inconsistencies in how functional scans temporally align with clinical assessments. As a result, many studies only utilize a small subset of the total rs-fMRI data, limiting statistical power, reproducibility, and the ability to study longitudinal functional brain changes at scale. Here, we describe a pipeline for ADNI rs-fMRI data that encompasses the download of necessary imaging and clinical data, temporally aligning the clinical and imaging data, preprocessing, and quality control. We integrate data curation and preprocessing across all ADNI sites and scanner types using a combination of open-source software (Clinica, fMRIPrep, and MRIQC) and bespoke tools. Quality metrics and reports are generated for each subject and session to facilitate rigorous data screening. All scripts and configuration files are available to enable reproducibility. The pipeline, which currently supports ADNI-GO, ADNI-2, and ADNI-3 data releases, outputs high-quality rs-fMRI time series data adhering to the BIDS-derivatives specification. This protocol provides a transparent and scalable framework for curating and utilizing ADNI fMRI data, empowering large-scale functional biomarker discovery and integrative multimodal analyses in Alzheimer's disease research.

翻译：阿尔茨海默病神经影像学倡议（ADNI）为研究衰老与阿尔茨海默病（AD）提供了全面的多模态神经影像资源。自第二阶段起，ADNI持续收集静息态功能磁共振成像（rs-fMRI）数据，该资源对于发现预测认知衰退与AD的脑连接变化具有重要价值。然而，其应用面临的主要障碍在于采集方案与数据质量存在显著差异，且存在影像会话缺失、功能扫描与临床评估时间轴不一致等问题。因此，许多研究仅能利用总体rs-fMRI数据中的一小部分，限制了统计效力、可重复性以及大规模纵向脑功能变化研究的能力。本文提出一套针对ADNI rs-fMRI数据的处理流程，涵盖必要影像与临床数据下载、临床与影像数据时间对齐、预处理及质量控制环节。我们整合了跨所有ADNI研究中心与扫描仪类型的数据管理与预处理工作，采用开源软件（Clinica、fMRIPrep与MRIQC）与定制化工具相结合的方式。为每个受试者及会话生成质量指标与报告，以支持严格的数据筛选。所有脚本与配置文件均已公开以确保可重复性。该流程目前支持ADNI-GO、ADNI-2与ADNI-3数据版本，输出符合BIDS-derivatives规范的高质量rs-fMRI时间序列数据。本方案为ADNI fMRI数据的规范化管理与应用提供了透明且可扩展的框架，有助于推动阿尔茨海默病研究中的大规模功能生物标志物发现与多模态整合分析。