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用于基于人群的神经成像的通用MRI采集与处理方案。

Versatile MRI acquisition and processing protocol for population-based neuroimaging.

作者信息

Koch Alexandra, Stirnberg Rüdiger, Estrada Santiago, Zeng Weiyi, Lohner Valerie, Shahid Mohammad, Ehses Philipp, Pracht Eberhard D, Reuter Martin, Stöcker Tony, Breteler Monique M B

机构信息

Population Health Sciences, German Center for Neurodegenerative Diseases (DZNE), Bonn, Germany.

MR Physics, German Center for Neurodegenerative Diseases (DZNE), Bonn, Germany.

出版信息

Nat Protoc. 2025 May;20(5):1223-1245. doi: 10.1038/s41596-024-01085-w. Epub 2024 Dec 13.

Abstract

Neuroimaging has an essential role in studies of brain health and of cerebrovascular and neurodegenerative diseases, requiring the availability of versatile magnetic resonance imaging (MRI) acquisition and processing protocols. We designed and developed a multipurpose high-resolution MRI protocol for large-scale and long-term population neuroimaging studies that includes structural, diffusion-weighted and functional MRI modalities. This modular protocol takes almost 1 h of scan time and is, apart from a concluding abdominal scan, entirely dedicated to the brain. The protocol links the acquisition of an extensive set of MRI contrasts directly to the corresponding fully automated data processing pipelines and to the required quality assurance of the MRI data and of the image-derived phenotypes. Since its successful implementation in the population-based Rhineland Study (ongoing, currently more than 11,000 participants, target participant number of 20,000), the proposed MRI protocol has proved suitable for epidemiological and clinical cross-sectional and longitudinal studies, including multisite studies. The approach requires expertise in magnetic resonance image acquisition, in computer science for the data management and the execution of processing pipelines, and in brain anatomy for the quality assessment of the MRI data. The protocol takes ~1 h of MRI acquisition and ~20 h of data processing to complete for a single dataset, but parallelization over multiple datasets using high-performance computing resources reduces the processing time. By making the protocol, MRI sequences and pipelines available, we aim to contribute to better comparability, interoperability and reusability of large-scale neuroimaging data.

摘要

神经影像学在脑健康、脑血管疾病和神经退行性疾病的研究中发挥着重要作用,这需要通用的磁共振成像(MRI)采集和处理协议。我们设计并开发了一种用于大规模和长期人群神经影像学研究的多用途高分辨率MRI协议,该协议包括结构、扩散加权和功能MRI模态。这个模块化协议的扫描时间将近1小时,除了最后的腹部扫描外,完全专注于脑部。该协议将大量MRI对比的采集直接与相应的全自动数据处理流程以及MRI数据和图像衍生表型所需的质量保证联系起来。自其在基于人群的莱茵兰研究(正在进行,目前有超过11,000名参与者,目标参与者数量为20,000名)中成功实施以来,所提出的MRI协议已被证明适用于流行病学和临床横断面及纵向研究,包括多中心研究。该方法需要磁共振图像采集方面的专业知识、用于数据管理和处理流程执行的计算机科学专业知识以及用于MRI数据质量评估的脑解剖学专业知识。对于单个数据集,该协议需要约1小时的MRI采集和约20小时的数据处理才能完成,但使用高性能计算资源对多个数据集进行并行处理可减少处理时间。通过提供该协议、MRI序列和处理流程,我们旨在促进大规模神经影像学数据更好的可比性、互操作性和可重用性。

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