Wiseman Stewart J, Meijboom Rozanna, Valdés Hernández Maria Del C, Pernet Cyril, Sakka Eleni, Job Dominic, Waldman Adam D, Wardlaw Joanna M
Edinburgh Imaging and Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK.
UK Dementia Research Institute Edinburgh, University of Edinburgh, Edinburgh, UK.
Trials. 2019 Jan 7;20(1):21. doi: 10.1186/s13063-018-3113-6.
Research involving brain imaging is important for understanding common brain diseases. Study endpoints can include features and measures derived from imaging modalities, providing a benchmark against which other phenotypical data can be assessed. In trials, imaging data provide objective evidence of beneficial and adverse outcomes. Multi-centre studies increase generalisability and statistical power. However, there is a lack of practical guidelines for the set-up and conduct of large neuroimaging studies.
We address this deficit by describing aspects of study design and other essential practical considerations that will help researchers avoid common pitfalls and data loss.
The recommendations are grouped into seven categories: (1) planning, (2) defining the imaging endpoints, developing an imaging manual and managing the workflow, (3) performing a dummy run and testing the analysis methods, (4) acquiring the scans, (5) anonymising and transferring the data, (6) monitoring quality, and (7) using structured data and sharing data.
Implementing these steps will lead to valuable and usable data and help to avoid imaging data wastage.
涉及脑成像的研究对于理解常见脑部疾病至关重要。研究终点可以包括从成像模态中得出的特征和测量值，为评估其他表型数据提供一个基准。在试验中，成像数据为有益和不良结果提供客观证据。多中心研究可提高普遍性和统计效力。然而，对于大型神经成像研究的设置和开展，缺乏实用指南。
我们通过描述研究设计的各个方面以及其他重要的实际注意事项来解决这一不足，这些将帮助研究人员避免常见陷阱和数据丢失。
这些建议分为七类：（1）规划，（2）定义成像终点、制定成像手册并管理工作流程，（3）进行预演并测试分析方法，（4）获取扫描数据，（5）对数据进行匿名化处理并传输数据，（6）监测质量，以及（7）使用结构化数据并共享数据。
实施这些步骤将产生有价值且可用的数据，并有助于避免成像数据的浪费。
