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Erroneous Resting-State fMRI Connectivity Maps Due to Prolonged Arterial Arrival Time and How to Fix Them

机译:由于延长的动脉到达时间而导致的错误的静息状态fMRI连接图及其修复方法

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摘要

In resting-state functional MRI (rs-fMRI), functional networks are assessed utilizing the temporal correlation between spontaneous blood oxygen level-dependent signal fluctuations of spatially remote brain regions. Recently, several groups have shown that temporal shifts are present in rs-fMRI maps in patients with cerebrovascular disease due to spatial differences in arterial arrival times, and that this can be exploited to map arrival times in the brain. This suggests that rs-fMRI connectivity mapping may be similarly sensitive to such temporal shifts, and that standard rs-fMRI analysis methods may fail to identify functional connectivity networks. To investigate this, we studied the default mode network (DMN) in Moyamoya disease patients and compared it with normal healthy volunteers. Our results show that using standard independent component analysis (ICA) and seed-based approaches, arterial arrival delays lead to inaccurate incomplete characterization of functional connectivity within the DMN in Moyamoya disease patients. Furthermore, we propose two techniques to correct these errors, for seed-based and ICA methods, respectively. Using these methods, we demonstrate that it is possible to mitigate the deleterious effects of arterial arrival time on the assessment of functional connectivity of the DMN. As these corrections have not been applied to the vast majority of >200 prior rs-fMRI studies in patients with cerebrovascular disease, we suggest that they be interpreted with great caution. Correction methods should be applied in any rs-fMRI connectivity study of subjects expected to have abnormally delayed arterial arrival times.
机译:在静止状态功能性MRI(rs-fMRI)中,利用空间遥远的大脑区域的自发性血氧水平依赖性信号波动之间的时间相关性来评估功能网络。最近,几组研究表明,由于动脉到达时间的空间差异,rs-fMRI图存在脑血管疾病患者的时间变化,并且可以利用它来绘制大脑中的到达时间。这表明rs-fMRI连接映射可能对此类时间偏移同样敏感,并且标准rs-fMRI分析方法可能无法识别功能连接网络。为了对此进行调查,我们研究了Moyamoya病患者的默认模式网络(DMN),并将其与正常健康志愿者进行了比较。我们的研究结果表明,使用标准的独立成分分析(ICA)和基于种子的方法,动脉到达延迟会导致Moyamoya病患者DMN内部功能连接的不准确表征。此外,针对基于种子的方法和ICA方法,我们分别提出了两种纠正这些错误的技术。使用这些方法,我们证明可以减轻DMN功能连接性评估中的动脉到达时间的有害影响。由于这些校正方法尚未应用于脑血管疾病患者的200多项先前的rs-fMRI研究中,因此建议我们谨慎行事。校正方法应用于任何预期具有异常延迟的动脉到达时间的受试者的rs-fMRI连通性研究中。

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