The effect of temporal interference of physiological signals on time-lag effective connectivity, derived from a functional network connectivity tool box (FNC), was examined by a blood-oxygen-level-dependent functional MRI study of action. The known effect of physiological signals on time-lag FNC was verified by (a) comparison of time-lag FNC analyses without and with retrospective image-based correction (RETROICOR) and (b) the other time-lag FNC analysis including the ventricular component related to the cerebrospinal fluid with dominant physiological effects. Twenty-five right-handed normal individuals performed motor task with motor response by the right middle/index fingers. Behavioral data of the reaction time (RT) and physiological signals (electrocardiogram, respiration, and pulsation) were recorded during neuroimaging studies of a 2-s repetition time at 3T. After standard image preprocessing, RETROICOR of the physiological effects and group independent component analysis (ICA), five action-related components were selected from 59 ICA components according to spatial extension involving known functional correlates of visuomotor tasks. Time-lag FNC was constructed by calculating the maximal correlation coefficients among five selected components. Attenuation of the physiological effect at 0.02-0.25 Hz was an average of 0.63 dB after RETROICOR (P<0.0005). Results of FNC analyses without and with RETROICOR were compatible with the action networks using the right hand. On the basis of the time-lag FNC after RETROICOR, the connectivity among the ventricular component and other components of action network attenuated. The FNC map with RETROICOR was more explicable with known action networks, for example interhemispheric inhibition. The effects of physiological signals significantly misled the interpretation of time-lag FNC in terms of direction and connectivity strength.
Purpose
This work investigates the effects of flow acceleration in the superior sagittal sinus on slice‐dependent variations in venous oxygen saturation (SvO2) estimations using susceptibility‐based MR oximetry.
Methods
Three‐dimensional multiple gradient‐echo images, with first‐order flow compensation along the anterior–posterior readout direction for the first echo, were acquired twice from 15 healthy volunteers. For all slices, phases within the superior sagittal sinus were fitted using linear regression across four TEs to obtain the Pearson’s correlation coefficients (PCCs), the largest of which corresponded to minimum acceleration influence. SvO2 derived from odd echoes on this slice was used to assess interscan difference, and compared with the central 15th slice for slice‐dependent difference, both using Bland‐Altman analysis. Within‐scan interslice SvO2 consistency was examined versus PCC. Multislice‐averaged SvO2 values were then computed from slices with PCCs above a certain threshold.
Results
Slice‐dependent difference in SvO2 varied from −16.2% to 21.5% at two SDs, in agreement with a recent report, and about twice larger than interscan differences for the automatically selected slice (−7.5% to 10.3%) and for the central 15th slice (−8.0% to 8.8%). For slices with PCCs higher than −0.98, interslice SvO2 deviations were all found to be less than 5.0%. Multislice‐averaged SvO2 with PCCs higher than −0.98 further reduced interscan difference to −4.7% to 8.2%.
Conclusion
Slice‐dependent variations in SvO2 may partly be explained by the effects of flow acceleration. Our method may enable conventional 3D multiple gradient echo to be used for SvO2 estimations in the presence of pulsatile flow.
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