Assessment of Autoregulation by Means of Periodic Changes in Blood Pressure

Birch, Alexander A.; Dirnhuber, M. J.; Hartley-Davies, R.; Iannotti, Fausto; Neil‐Dwyer, G.

doi:10.1161/01.str.26.5.834

Cited by 183 publications

(147 citation statements)

References 7 publications

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“…The BP-BFV phase shifts were similar to those observed during the Valsalva maneuver obtained from the MMPF method [17]. Such positive phase shift has been also reported using Fourier transform methods during head-up tilt, and was interpreted as a faster recovery of BFV mediated by the compensatory cerebral autoregulatory mechanisms [8,12,14,50]. Our previous studies showed that the reduction of the MMPF derived BP-BFV phase shifts was associated with impaired cerebral autoregulation in stroke and hypertensive subjects and in patients with traumatic brain injuries [17,51], indicating that MMPF results reflect dynamics of cerebral autoregulation.…”

Section: A Assessment Of Nonlinear Interactions Between Nonstatisupporting

confidence: 75%

“…A transfer function is typically used to explore the relationship between blood pressure (BP) and blood flow velocity (BFV) by calculating gain and phase shift between the BP and BFV power spectra [2,8,[10][11][12][13][14][15][16]. In this approach, it is presumed that signals are stationary, and are composed of superimposed sinusoidal oscillations of constant amplitude and period at a pre-determined frequency range.…”

Section: Introductionmentioning

confidence: 99%

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Altered phase interactions between spontaneous blood pressure and flow fluctuations in type 2 diabetes mellitus: Nonlinear assessment of cerebral autoregulation

Peng

Huang

et al. 2008

Physica A: Statistical Mechanics and its Applications

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Cerebral autoregulation (CA) is an important mechanism that involves dilation and constriction in arterioles to maintain relatively s cerebral blood flow in response to changes of systemic blood pressure. Traditional assessments of CA focus on the changes of cerebral blood flow velocity in response to large blood pressure fluctuations induced by interventions. This approach is not feasible for patients with impaired autoregulation or cardiovascular regulation. Here we propose a newly developed technique-the multimodal pressure-flow (MMPF) analysis, which assesses CA by quantifying nonlinear phase interactions between spontaneous oscillations in blood pressure and flow velocity during resting conditions. We show that CA in healthy subjects can be characterized by specific phase shifts between spontaneous blood pressure and flow velocity oscillations, and the phase shifts are significantly reduced in diabetic subjects. Smaller phase shifts between oscillations in the two variables indicate more passive dependence of blood flow velocity on blood pressure, thus suggesting impaired cerebral autoregulation. Moreover, the reduction of the phase shifts in diabetes is observed not only in previously-recognized effective region of CA (<0.1Hz), but also over the higher frequency range from ~0.1 to 0.4Hz. These findings indicate that Type 2 diabetes alters cerebral blood flow regulation over a wide frequency range and that this alteration can be reliably assessed from spontaneous oscillations in blood pressure and blood flow velocity during resting conditions. We also show that the MMPF method has better performance than traditional approaches based on Fourier transform, and is more sui for the quantification of nonlinear phase interactions between nonstationary biological signals such as blood pressure and blood flow.

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Section: A Assessment Of Nonlinear Interactions Between Nonstatisupporting

confidence: 75%

Section: Introductionmentioning

confidence: 99%

Altered phase interactions between spontaneous blood pressure and flow fluctuations in type 2 diabetes mellitus: Nonlinear assessment of cerebral autoregulation

Peng

Huang

et al. 2008

Physica A: Statistical Mechanics and its Applications

View full text Add to dashboard Cite

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“…The response to this input will be denominated as the pressure-pulseresponse (PPR). Figure 2B and 3A show the expected left-shift (phase lead) in the PPR [7] resulting from the high-pass characteristics of the autoregulatory response [5,14]. Results from preliminary work [13] based on simulations using Tiecks model [15] and recorded data showed that the PPR at 1.5 seconds (A1.5) and the amplitude at 7 seconds (A7) (as shown in Fig.…”

Section: Selection Of Autoregulatory Parametersmentioning

confidence: 88%

“…Most of the studies of CA focus on linear methods [5,[7][8][9][10] with the more recent inclusion of some nonlinear approaches [8,[10][11][12][13]. Although nonlinear techniques can provide improved model fits, their benefit in assessing CA is still unclear with few studies having systematically compared them to linear alternatives.…”

Section: Introductionmentioning

confidence: 99%

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Optimising the assessment of cerebral autoregulation from black box models

Angarita-Jaimes

Kouchakpour

Liu

et al. 2014

Medical Engineering & Physics

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Cerebral autoregulation (CA) mechanisms maintain blood flow approximately stable despite changes in arterial blood pressure. Mathematical models that characterise this system have been used extensively in the quantitative assessment of function/impairment of CA. Using spontaneous fluctuations in arterial blood pressure (ABP) as input and cerebral blood flow velocity (CBFV) as output, the autoregulatory mechanism can be modelled using linear and nonlinear approaches, from which indexes can be extracted to provide an overall assessment of CA. Previous studies have considered a single -or at most a couple of measures, making it difficult to compare the performance of different CA parameters. We compare the performance of established autoregulatory parameters and propose novel measures. The key objective is to identify which model and index can best distinguish between normal and impaired CA. To this end twenty-six recordings of ABP and CBFV from normocapnia and hypercapnia (which temporarily impairs CA) in 13 healthy adults were analysed. In the absence of a 'gold' standard for the study of dynamic CA, lower inter-and intra-subject variability of the parameters in relation to the difference between normo-and hypercapnia were considered as criteria for identifying improved measures of CA. Significantly improved performance compared to some conventional approaches was achieved, with the simplest method emerging as probably the most promising for future studies.

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Cerebral blood flow velocities monitored by transcranial Doppler during cardiac catheterizations in children

Rodriguez

Hosking

Duncan

et al. 1998

Cathet. Cardiovasc. Diagn.

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Transcranial Doppler (TCD) was used to evaluate brain circulation during cardiac catheterizations in 32 children requiring pulmonary (n=10) or aortic balloon dilatations (n=2), ductus arteriosus coil insertions (n=5), or angiography (n=15). Cerebral blood flow velocity (CBFV) in the middle cerebral artery was measured before (baseline), during, and after each procedure (mean ± 95%ci). High‐intensity transient signals (HITS) were also detected during these maneuvers. Balloon angioplasty decreased CBFV by 63 ± 11% from baseline (P < 0.01). Shorter durations of the inflation cycle resulted in earlier CBFV recovery (r=0.78). During angiography, CBFV increased by 11 ± 4% (P < 0.01) in all except one case that showed retrograde diastolic flow. Mean total HITS count was 44 (95%ci.limits:27,74). These signals were more frequently found in septal defects or systemic arterial manipulations. Pediatric cardiac catheterization may impose transient fluctuations in brain perfusion as indicated by TCD, but their clinical implications are uncertain. CBFV changes during balloon angioplasty emphasize the importance of rapid inflation/deflation cycles. TCD can monitor such changes and evaluate preventive measures. Cathet. Cardiovasc. Diagn. 43:282–290, 1998. © 1998 Wiley‐Liss, Inc.

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Assessment of Autoregulation by Means of Periodic Changes in Blood Pressure

Abstract: The results support our hypothesis and may lead to a technique for assessing the competence of cerebral autoregulation.

Cited by 183 publications

References 7 publications

Altered phase interactions between spontaneous blood pressure and flow fluctuations in type 2 diabetes mellitus: Nonlinear assessment of cerebral autoregulation

Altered phase interactions between spontaneous blood pressure and flow fluctuations in type 2 diabetes mellitus: Nonlinear assessment of cerebral autoregulation

Optimising the assessment of cerebral autoregulation from black box models

Cerebral blood flow velocities monitored by transcranial Doppler during cardiac catheterizations in children

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