Cerebral autoregulation (CA) is a complex mechanism stabilizing cerebral blood flow (CBF) against arterial pressure (AP) changes. CBF is commonly surrogated with the CBF velocity (CBFV) recorded via transcranial Doppler device from the middle cerebral artery. Most of the studies evaluating CA compute mean CBFV (MCBFV) on a beat-to-beat basis along with mean AP (MAP), but there is not a standard approach to derive MCBFV. In this study, we compare three different strategies to calculate MCBFV: i) between two consecutive diastolic points detected on the CBFV signal (MCBFVCBFV); ii) between two consecutive diastolic points detected on the AP signal (MCBFVAP); iii) between two consecutive R-wave peaks detected on the ECG (MCBFVECG). We analyzed ECG, noninvasive AP and CBFV signals recorded from 23 subjects (age: 28 ± 9 yrs, 13 female) at rest in supine position (REST) and during head-up tilt at 60° (TILT). While means were similar regardless of the considered strategy, variances significantly varied with MCBFVCBFV and MCBFVECG strategy producing the largest and the smallest variance respectively. This result stresses the need to standardize the approach for MCBFV computation to reduce the variability of the results solely due to the method adopted for its computation and favor clinical applications of CA assessment.

Vaini E., Bari V., Tonon D., Cairo B., De Maria B., Faes L., et al. (2019). Computation of Mean Cerebral Blood Flow Velocity for the Assessment of Cerebral Autoregulation: Comparison of Different Strategies. In Computing in Cardiology. IEEE Computer Society [10.23919/CinC49843.2019.9005741].

Computation of Mean Cerebral Blood Flow Velocity for the Assessment of Cerebral Autoregulation: Comparison of Different Strategies

Faes L.;Porta A.
2019-01-01

Abstract

Cerebral autoregulation (CA) is a complex mechanism stabilizing cerebral blood flow (CBF) against arterial pressure (AP) changes. CBF is commonly surrogated with the CBF velocity (CBFV) recorded via transcranial Doppler device from the middle cerebral artery. Most of the studies evaluating CA compute mean CBFV (MCBFV) on a beat-to-beat basis along with mean AP (MAP), but there is not a standard approach to derive MCBFV. In this study, we compare three different strategies to calculate MCBFV: i) between two consecutive diastolic points detected on the CBFV signal (MCBFVCBFV); ii) between two consecutive diastolic points detected on the AP signal (MCBFVAP); iii) between two consecutive R-wave peaks detected on the ECG (MCBFVECG). We analyzed ECG, noninvasive AP and CBFV signals recorded from 23 subjects (age: 28 ± 9 yrs, 13 female) at rest in supine position (REST) and during head-up tilt at 60° (TILT). While means were similar regardless of the considered strategy, variances significantly varied with MCBFVCBFV and MCBFVECG strategy producing the largest and the smallest variance respectively. This result stresses the need to standardize the approach for MCBFV computation to reduce the variability of the results solely due to the method adopted for its computation and favor clinical applications of CA assessment.
2019
Vaini E., Bari V., Tonon D., Cairo B., De Maria B., Faes L., et al. (2019). Computation of Mean Cerebral Blood Flow Velocity for the Assessment of Cerebral Autoregulation: Comparison of Different Strategies. In Computing in Cardiology. IEEE Computer Society [10.23919/CinC49843.2019.9005741].
File in questo prodotto:
File Dimensione Formato  
A64-CinC2019-Vaini.pdf

Solo gestori archvio

Tipologia: Versione Editoriale
Dimensione 201.16 kB
Formato Adobe PDF
201.16 kB Adobe PDF   Visualizza/Apri   Richiedi una copia

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/10447/435952
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 0
  • ???jsp.display-item.citation.isi??? ND
social impact