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低频生理校正对静息态功能磁共振成像指标(功能连接、低频振幅和局部一致性)的可重复性和特异性的影响

The Effect of Low-Frequency Physiological Correction on the Reproducibility and Specificity of Resting-State fMRI Metrics: Functional Connectivity, ALFF, and ReHo.

作者信息

Golestani Ali M, Kwinta Jonathan B, Khatamian Yasha B, Chen J Jean

机构信息

Rotman Research Institute at Baycrest Centre, University of Toronto, Toronto, ON, Canada.

Department of Medical Biophysics, Faculty of Medicine, University of Toronto, Toronto, ON, Canada.

出版信息

Front Neurosci. 2017 Oct 5;11:546. doi: 10.3389/fnins.2017.00546. eCollection 2017.

Abstract

The resting-state fMRI (rs-fMRI) signal is affected by a variety of low-frequency physiological phenomena, including variations in cardiac-rate (CRV), respiratory-volume (RVT), and end-tidal CO (PETCO). While these effects have become better understood in recent years, the impact that their correction has on the quality of rs-fMRI measurements has yet to be clarified. The objective of this paper is to investigate the effect of correcting for CRV, RVT and PETCO on the rs-fMRI measurements. Nine healthy subjects underwent a test-retest rs-fMRI acquisition using repetition times (TRs) of 2 s (long-TR) and 0.323 s (short-TR), and the data were processed using eight different physiological correction strategies. Subsequently, regional homogeneity (ReHo), amplitude of low-frequency fluctuation (ALFF), and resting-state connectivity of the motor and default-mode networks are calculated for each strategy. Reproducibility is calculated using intra-class correlation and the Dice Coefficient, while the accuracy of functional-connectivity measures is assessed through network separability, sensitivity and specificity. We found that: (1) the reproducibility of the rs-fMRI measures improved significantly after correction for PETCO; (2) separability of functional networks increased after PETCO correction but was not affected by RVT and CRV correction; (3) the effect of physiological correction does not depend on the data sampling-rate; (4) the effect of physiological processes and correction strategies is network-specific. Our findings highlight limitations in our understanding of rs-fMRI quality measures, and underscore the importance of using multiple quality measures to determine the optimal physiological correction strategy.

摘要

静息态功能磁共振成像(rs-fMRI)信号受到多种低频生理现象的影响,包括心率变化(CRV)、呼吸量(RVT)和呼气末二氧化碳(PETCO)。虽然近年来对这些影响有了更好的理解,但它们的校正对rs-fMRI测量质量的影响尚未明确。本文的目的是研究校正CRV、RVT和PETCO对rs-fMRI测量的影响。九名健康受试者使用2秒(长TR)和0.323秒(短TR)的重复时间进行了重测rs-fMRI采集,并使用八种不同的生理校正策略对数据进行处理。随后,针对每种策略计算区域同质性(ReHo)、低频波动幅度(ALFF)以及运动和默认模式网络的静息态连接性。使用组内相关性和骰子系数计算可重复性,同时通过网络可分离性、敏感性和特异性评估功能连接性测量的准确性。我们发现:(1)校正PETCO后,rs-fMRI测量的可重复性显著提高;(2)PETCO校正后功能网络的可分离性增加,但不受RVT和CRV校正的影响;(3)生理校正的效果不依赖于数据采样率;(4)生理过程和校正策略的效果具有网络特异性。我们的研究结果突出了我们对rs-fMRI质量测量理解的局限性,并强调了使用多种质量测量来确定最佳生理校正策略的重要性。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9859/5633680/6de4bff5c887/fnins-11-00546-g0001.jpg

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