Challenges in the reproducibility of clinical studies with resting state fMRI: An example in early Parkinson's disease.
Challenges in the reproducibility of clinical studies with resting state fMRI: An example in early Parkinson's disease.
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DOI：
10.1016/j.neuroimage.2015.09.021
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发表时间：
2016-01-01
期刊：
影响因子：
5.7
通讯作者：
Mackay CE
中科院分区：
文献类型：
--
作者：
Griffanti L;Rolinski M;Szewczyk-Krolikowski K;Menke RA;Filippini N;Zamboni G;Jenkinson M;Hu MTM;Mackay CE
静息态功能磁共振成像（rfMRI）因其易于获得和具有良好的临床应用前景而日益受到人们的欢迎。然而，rfMRI研究，特别是那些涉及临床组，仍然缺乏重现性，主要是由于不同的分析设置。这对于成像生物标志物的开发尤其重要。这项工作的目的是评估我们最近关于早期帕金森病（PD）中基底神经节网络的功能连接性的研究的可重复性（Szewczyk-Krolikowski et al.，2014年）。特别是，我们系统地分析了两个rfMRI分析步骤对结果的影响：fMRI数据的个体清洗（伪影去除）和用于二元回归的独立成分（模板）集的选择。我们的经验表明，使用基于单个受试者独立成分分析的清除方法，该方法消除了个体间变异性的非神经相关来源，有助于提高临床结果的重现性。建议使用一组独立的健康对照生成的模板用于目的是检测来自"健康"大脑的差异的研究，而不是来自相同数量的患者和对照的"平均"模板。虽然探索性分析（例如测试多个静息状态网络）应用于制定新的假设，但在有希望的发现转化为有用的生物标志物之前，需要仔细验证。临床结果的再现对于成像生物标志物的开发至关重要。我们讨论了rfMRI中不同分析设置对再现性的影响。基于ICA的rfMRI数据清洗提高了再现性。二元回归的模板选择的效果进行了评估。
Resting state fMRI (rfMRI) is gaining in popularity, being easy to acquire and with promising clinical applications. However, rfMRI studies, especially those involving clinical groups, still lack reproducibility, largely due to the different analysis settings. This is particularly important for the development of imaging biomarkers. The aim of this work was to evaluate the reproducibility of our recent study regarding the functional connectivity of the basal ganglia network in early Parkinson's disease (PD) (Szewczyk-Krolikowski et al., 2014). In particular, we systematically analysed the influence of two rfMRI analysis steps on the results: the individual cleaning (artefact removal) of fMRI data and the choice of the set of independent components (template) used for dual regression. Our experience suggests that the use of a cleaning approach based on single-subject independent component analysis, which removes non neural-related sources of inter-individual variability, can help to increase the reproducibility of clinical findings. A template generated using an independent set of healthy controls is recommended for studies where the aim is to detect differences from a “healthy” brain, rather than an “average” template, derived from an equal number of patients and controls. While, exploratory analyses (e.g. testing multiple resting state networks) should be used to formulate new hypotheses, careful validation is necessary before promising findings can be translated into useful biomarkers. Reproducibility of clinical findings is crucial for imaging biomarker development. We addressed the impact on reproducibility of different analysis settings in rfMRI. ICA-based cleaning of rfMRI data increases reproducibility. The effect of the template choice for dual regression is evaluated.