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Validity of transcranial Doppler ultrasonography-determined dynamic cerebral autoregulation estimated using transfer function analysis.

Authors :
Watanabe H
Washio T
Saito S
Hirasawa A
Suzuki R
Shibata S
Brothers RM
Ogoh S
Source :
Journal of clinical monitoring and computing [J Clin Monit Comput] 2022 Dec; Vol. 36 (6), pp. 1711-1721. Date of Electronic Publication: 2022 Jan 24.
Publication Year :
2022

Abstract

Transcranial Doppler ultrasonography (TCD) is used widely to evaluate dynamic cerebral autoregulation (dCA). However, the validity of TCD-determined dCA remains unknown because TCD is only capable of measuring blood velocity and thus only provides an index as opposed to true blood flow. To test the validity of TCD-determined dCA, in nine healthy subjects, dCA was evaluated by transfer function analysis (TFA) using cerebral blood flow (CBF) or TCD-measured cerebral blood velocity during a perturbation that induces reductions in TCD-determined dCA, lower body negative pressure (LBNP) at two different stages: LBNP - 15 mmHg and - 50 mmHg. Internal carotid artery blood flow (ICA Q) was assessed as an index of CBF using duplex Doppler ultrasound. The TFA low frequency (LF) normalized gain (ngain) calculated using ICA Q increased during LBNP at - 50 mmHg (LBNP50) from rest (P = 0.005) and LBNP at - 15 mmHg (LBNP15) (P = 0.015), indicating an impaired dCA. These responses were the same as those obtained using TCD-measured cerebral blood velocity (from rest and LBNP15; P = 0.001 and P = 0.015). In addition, the ICA Q-determined TFA LF ngain from rest to LBNP50 was significantly correlated with TCD-determined TFA LF ngain (r = 0.460, P = 0.016) despite a low intraclass correlation coefficient. Moreover, in the Bland-Altman analysis, the difference in the TFA LF ngains determined by blood flow and velocity was within the margin of error, indicating that the two measurement methods can be interpreted as equivalent. These findings suggest that TCD-determined dCA can be representative of actual dCA evaluated with CBF.<br /> (© 2022. The Author(s), under exclusive licence to Springer Nature B.V.)

Details

Language :
English
ISSN :
1573-2614
Volume :
36
Issue :
6
Database :
MEDLINE
Journal :
Journal of clinical monitoring and computing
Publication Type :
Academic Journal
Accession number :
35075510
Full Text :
https://doi.org/10.1007/s10877-022-00817-1