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Abstract #0167

Accounting for Arterial Transit Delays is Crucial for Identifying Functional Connectivity Networks: a Resting-State fMRI Study of the Default Mode Network in Moyamoya Disease Patients

Hesamoddin Jahanian 1 , Thomas Christen 1 , Michael E Moseley 1 , and Greg Zaharchuk 1

1 Stanford University, Department of Radiology, Stanford, California, United States

In an effort to investigate the effects of regional arterial arrival delays on identification of resting state functional connectivity networks, we studied the default mode network in a group of Moyamoya patients and compared it with normal healthy volunteers. We found that in the presence of significant delays, using standard seed-based method or independent component analysis (ICA), may lead to erroneous identification of functional connectivity networks. To solve this issue, we also propose a modified version of seed-based analysis method that accounts for the transit delays. Our results indicate that accounting for transit delays is crucial for analyzing the rsfMRI data in Moyamoya patients.

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