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

Luca Faes, Vlasta Bari, Gianluca Rossato, Davide Tonon, Beatrice De Maria, Beatrice Cairo, Emanuele Vaini, Alberto Porta

Research output: Chapter in Book/Report/Conference proceedingConference contribution


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.
Original languageEnglish
Title of host publicationComputing in Cardiology
Number of pages4
Publication statusPublished - 2019

All Science Journal Classification (ASJC) codes

  • Computer Science(all)
  • Cardiology and Cardiovascular Medicine

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