Literature DB >> 28885752

Dual-echo ASL contributes to decrypting the link between functional connectivity and cerebral blow flow.

Silvia F Storti1, Ilaria Boscolo Galazzo1, Stefania Montemezzi2, Gloria Menegaz1, Francesca B Pizzini2.   

Abstract

Arterial spin labeling (ASL) MRI with a dual-echo readout module (DE-ASL) enables noninvasive simultaneous acquisition of cerebral blood flow (CBF)-weighted images and blood oxygenation level dependent (BOLD) contrast. Up to date, resting-state functional connectivity (FC) studies based on CBF fluctuations have been very limited, while the BOLD is still the method most frequently used. The purposes of this technical report were (i) to assess the potentiality of the DE-ASL sequence for the quantification of resting-state FC and brain organization, with respect to the conventional BOLD (cvBOLD) and (ii) to investigate the relationship between a series of complex network measures and the CBF information. Thirteen volunteers were scanned on a 3 T scanner acquiring a pseudocontinuous multislice DE-ASL sequence, from which the concomitant BOLD (ccBOLD) simultaneously to the ASL can be extracted. In the proposed comparison, the brain FC and graph-theoretical analysis were used for quantifying the connectivity strength between pairs of regions and for assessing the network model properties in all the sequences. The main finding was that the ccBOLD part of the DE-ASL sequence provided highly comparable connectivity results compared to cvBOLD. As expected, because of its different nature, ASL sequence showed different patterns of brain connectivity and graph indices compared to BOLD sequences. To conclude, the resting-state FC can be reliably detected using DE-ASL, simultaneously to CBF quantifications, whereas a single fMRI experiment precludes the quantitative measurement of BOLD signal changes. Hum Brain Mapp 38:5831-5844, 2017.
© 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.

Keywords:  BOLD; DE-ASL; functional connectivity; graph theory; resting state

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Year:  2017        PMID: 28885752      PMCID: PMC6866770          DOI: 10.1002/hbm.23804

Source DB:  PubMed          Journal:  Hum Brain Mapp        ISSN: 1065-9471            Impact factor:   5.038


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