Ortega-Gutiérrez, SantiagoPetersen, NilsMasurkar, ArjunReccius, AndrésHuang, AmyLi, MinChoi, JaeMarshall, Randolph2017-03-142017-03-142014J Neuroimaging. 2014 ; 24(4) p:379–386http://hdl.handle.net/11447/1023http://dx.doi.org/10.1111/jon.12019Background: Cerebral autoregulation (CA) enables the brain to maintain stable cerebral blood flow (CBF). CA can be assessed non-invasively by determining correlations between cerebral blood flow velocity (CBFV) and spontaneous changes in blood pressure. Post-recording signal analysis methods have included both frequency- and time-domain methods. However, the testretest reliability, cross-validation, and determination of normal values have not been adequately established. Methods:In 53 healthy volunteers a transfer function analysis was applied to calculate phase shift (PS) and gain in the low frequency range (0.06-0.12 Hz) where CA is most apparent. Correlation analysis was used to derive mean velocity index (Mx). Intra-class correlation and bivariate correlation coefficients were applied to assess asymmetry, cross-validity, and test-retest. Results:The bihemispheric average PS, gain and Mx means were 45.99+/−14.24 degrees, 0.62+/−0.38 cm/sec/mm Hg and 0.41+/− 0.13 respectively. Gain exhibited a difference by age (p=0.03). PS, gain and Mx values showed excellent inter-hemispheric correlation (r>0.8; p<0.001). PS and gain showed good reliability (R ICC=0.632, L ICC=0.576; p<0.001). PS and Mx showed fair correlation (r=−.37; p<0.001). Conclusions: CA parameters obtained by time- and frequency-domain methods correlate well, and show good inter-hemispheric and test-retest reliability. Group means from healthy controls may provide adequate norms for determining abnormal CA in cerebrovascular patients.17en-UScerebral autoregulationtranscranial doppler phase shiftautoregulatory indexgainArtículo