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.
|Titolo della pubblicazione ospite||Computing in Cardiology|
|Numero di pagine||4|
|Stato di pubblicazione||Published - 2019|
All Science Journal Classification (ASJC) codes
- Computer Science(all)
- Cardiology and Cardiovascular Medicine