Cardiovascular Engineering

, Volume 8, Issue 1, pp 60–71 | Cite as

Nonlinear Assessment of Cerebral Autoregulation from Spontaneous Blood Pressure and Cerebral Blood Flow Fluctuations

  • Kun HuEmail author
  • C. K. Peng
  • Marek Czosnyka
  • Peng Zhao
  • Vera NovakEmail author
Original Paper


Cerebral autoregulation (CA) is an most important mechanism responsible for the relatively constant blood flow supply to brain when cerebral perfusion pressure varies. Its assessment in nonacute cases has been relied on the quantification of the relationship between noninvasive beat-to-beat blood pressure (BP) and blood flow velocity (BFV). To overcome the nonstationary nature of physiological signals such as BP and BFV, a computational method called multimodal pressure-flow (MMPF) analysis was recently developed to study the nonlinear BP–BFV relationship during the Valsalva maneuver (VM). The present study aimed to determine (i) whether this method can estimate autoregulation from spontaneous BP and BFV fluctuations during baseline rest conditions; (ii) whether there is any difference between the MMPF measures of autoregulation based on intra-arterial BP (ABP) and based on cerebral perfusion pressure (CPP); and (iii) whether the MMPF method provides reproducible and reliable measure for noninvasive assessment of autoregulation. To achieve these aims, we analyzed data from existing databases including: (i) ABP and BFV of 12 healthy control, 10 hypertensive, and 10 stroke subjects during baseline resting conditions and during the Valsalva maneuver, and (ii) ABP, CPP, and BFV of 30 patients with traumatic brain injury (TBI) who were being paralyzed, sedated, and ventilated. We showed that autoregulation in healthy control subjects can be characterized by specific phase shifts between BP and BFV oscillations during the Valsalva maneuver, and the BP–BFV phase shifts were reduced in hypertensive and stroke subjects (P < 0.01), indicating impaired autoregulation. Similar results were found during baseline condition from spontaneous BP and BFV oscillations. The BP–BFV phase shifts obtained during baseline and during VM were highly correlated (R > 0.8, P < 0.0001), showing no statistical difference (paired-t test P > 0.47). In TBI patients there were strong correlations between phases of ABP and CPP oscillations (R = 0.99, P < 0.0001) and, thus, between ABP–BFV and CPP–BFV phase shifts (P < 0.0001, R = 0.76). By repeating the MMPF 4 times on data of TBI subjects, each time on a selected cycle of spontaneous BP and BFV oscillations, we showed that MMPF had better reproducibility than traditional autoregulation index. These results indicate that the MMPF method, based on instantaneous phase relationships between cerebral blood flow velocity and peripheral blood pressure, has better performance than the traditional standard method, and can reliably assess cerebral autoregulation dynamics from ambulatory blood pressure and cerebral blood flow during supine rest conditions.


Spontaneous oscillations Instantaneous phase shift Valsalva maneuver Baseline resting condition Stroke Hypertension Traumatic brain injury 



Blood pressure


Intra-arterial blood pressure


Cerebral perfusion pressure


Intracranial pressure


Blood flow velocity


Brain injury


Autoregulation index


Multimodal pressure-flow


Empirical mode decomposition


Ensemble empirical mode decomposition


Valsalva maneuver





This work was supported by the American Diabetes Association Grant 1-03-CR-23 to V. Novak; NIH Program projects AG004390 and NIH-NINDS R01-NS045745; NIH-NINDS STTR grant 1R41NS053128-01A2 in collaboration with DynaDx, Inc; NIH Older American Independence Center Grant 2P60 AG08812; James S. McDonnell Foundation via award to CK Peng; the Ellison Medical Foundation Senior Scholar in Aging Award; the G. Harold and Leila Y. Mathers Charitable Foundation; Defense Advanced Research Projects Agency; the NIH/National Center for Research Resources (P41RR013622); and Medical Research Council via Program Grant NO. MRC G9439390 to M Czosnyka.


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Copyright information

© Springer Science+Business Media, LLC 2007

Authors and Affiliations

  1. 1.Division of GerontologyBeth Israel Deaconess Medical Center, Harvard Medical SchoolBostonUSA
  2. 2.Division of Interdisciplinary Medicine & Biotechnology and Margret and H.A. Rey Institute for Nonlinear Dynamics in MedicineBeth Israel Deaconess Medical Center/Harvard Medical SchoolBostonUSA
  3. 3.Academic Neurosurgical UnitAddenbrooke’s HospitalCambridgeUK
  4. 4.Division of GerontologyBeth Israel Deaconess Medical Center, Harvard Medical SchoolBostonUSA

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