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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