Skip to main content

Advertisement

How I monitor cerebral autoregulation

Article metrics

Cerebrovascular pressure autoregulation (CAR) protects the brain against changes in cerebral perfusion pressure (CPP) by adjusting the vascular resistance, to ensure a steady cerebral blood flow (CBF). The role of impaired CAR is well-described in the pathophysiology of traumatic brain injury (TBI), stroke, subarachnoid hemorrhage (SAH), and prematurity-related intracranial hemorrhage [1], but also in sepsis-associated brain dysfunction [2]. A clinical tool to assess CAR in real time may improve our understanding of the role of disturbed CBF in brain injury and systemic insults and open the door for personalized arterial blood pressure (ABP) manipulation to remain within the limits of active CAR [3].

To evaluate CAR, CBF changes in response to induced or spontaneous CPP fluctuations have to be analyzed. Intact CAR implies that changes in CPP will not be reflected in CBF changes. Direct assessment of global CBF is a challenge, while regional CBF can be assessed with a laser Doppler flow (LDF) probe. For the purpose of CAR monitoring, surrogate signals are often used (Fig. 1), such as intracranial pressure (ICP), or brain tissue oxygenation (PbtO2). Because these techniques involve inserting a probe in the brain, they cannot be applied in non-brain injury, for instance in sepsis or during anesthesia. Interestingly, and most promising, non-invasive signals that react on CBF changes can also be used, such as transcranial Doppler (TCD) or regional cerebral oxygenation as measured by near-infrared spectroscopy [2, 4].

Fig. 1
figure1

Dynamic autoregulation modeling. CBF, cerebral blood flow; TCD, transcranial Doppler; NIRS, near-infrared spectroscopy; LDF, laser Doppler flow; ICP, intracranial pressure; PRx, pressure reactivity index; LAx, low-frequency autoregulation index, Mx, TCD-based reactivity index between cerebral blood flow velocity and arterial blood pressure; Lx, autoregulation index based on LDF; COx, cerebral oxygenation index; THx, total hemoglobin index; PbtO2, brain tissue oxygenation; ORx, oxygen reactivity index

A distinction is made between static and dynamic CAR. Static CAR is assessed by analyzing changes in CBF in response to an ABP challenge, over a timescale of minutes (to hours), and reflects a steady-state response. Dynamic CAR does not require such formal CPP challenge, but analyzes changes in CBF in response to spontaneous CPP fluctuations over seconds or even heartbeats, by using computational techniques. Linear and nonlinear methods, using either time or frequency domain analysis, have been developed to evaluate this pressure-flow relationship [5]. The lower signal-to-noise ratio is compensated by performing multiple sequential estimates. There is a good correlation between measures of static and dynamic CAR [6]. In clinical practice, we use both.

When patients are on the steep part of the intracranial volume-pressure curve, sudden changes in cerebral blood volume induced by CBF are reflected as changes in ICP due to the reduced compliance in the rigid skull, as described by the Monro-Kellie hypothesis. This can be exploited in a dynamic as well as a static way to assess CAR. The pressure reactivity index (PRx) is based on high-frequency moving time series Pearson correlations between ICP and slow wave fluctuations of arterial blood pressure (ABP) and is available as a software package (ICM+®, Cambridge Enterprise, University of Cambridge, UK) that is frequently used for this purpose [7], including in our center. PRx thresholds for active and passive CAR have been based on retrospective studies [8] and may vary. Roughly, a more positive PRx indicates passive pressure reactivity (when a rise in ABP leads to passive vasodilation with an increased intracranial volume), while a negative or close to zero PRx indicates intact pressure reactivity. ICM+® is able to use other signals, such as PbtO2 for the oxygen reactivity index (ORx) [9], or a non-invasive signal such as the TCD measured CBF velocity (CBFV) for the mean velocity index (Mx) [10] or the systolic flow index (Sx) [11]. However, and importantly, the ICM+® software is currently not licensed as a medical device and should be considered research software. When high-frequency waveform data are not available, which is typically the case in most patient data management systems, the low-frequency autoregulation index (LAx) can be used. LAx uses minute-by-minute ABP-ICP correlations to calculate CAR [12].

A very elegant technique to assess static CAR at the bedside that does not require additional software and can be used in all patients where a surrogate CBF signal is being monitored, in a single or multimodal way, as described above, is the application of an ABP challenge. In this procedure, the mean ABP is raised 10 mmHg by increasing the vasopressor dose, while assessing ICP, PbtO2, and/or CBFV, after 10–20 min. A decrease, or no change, in ICP, indicates intact CAR, while an increase in ICP demonstrates the absence of CAR. Inherently, a successful ABP challenge indicating intact CAR will increase CPP. Typically, in response to this higher CPP, PbtO2 will improve. CBFV changes can be interpreted in the same way (should remain constant or increase when CAR is intact, should decrease because of vasodilation when CAR is impaired). When brain hyperperfusion is suspected, a reverse ABP challenge, where ABP is decreased by 10 mmHg, can also be considered. In our ABP challenge protocol, we are cautious when going outside CPP ranges of 60–80 mmHg, and will never recommend CPP outside 50–90 mmHg.

In summary, it is important to realize that no ‘gold-standard’ clinical CAR monitor exists, and basic physiological research to support the theory behind different monitoring techniques and improve our understanding is highly needed [13]. Our current CAR monitoring protocol is based on the multimodal combination of different static and dynamic measures. Severe TBI patients, for instance, are routinely monitored with an intraparenchymal ICP probe, and in selected patients, a PbtO2 probe is added. Dynamic CAR is monitored using ICM+® software, recognizing the limitations described above [14]. We consider an ABP challenge as second-tier therapy for isolated elevated ICP, or for intracranial hypertension combined with low PbtO2, only after correction of other first-tier level factors [15]. In these cases, when ICM+® indicates that the zone of optimal CPP might lie outside the 60–70 range, this can be interpreted as a clinical predictor of a potentially successful ABP challenge. This relatively simple test can be performed by an experienced intensivist, at the bedside, provided caution is applied when leaving the CPP range of 60–80 mmHg, and provided the situation is re-evaluated frequently. Currently, there is insufficient evidence to advice the use of one single bedside monitoring technique.

Abbreviations

ABP:

Arterial blood pressure

CAR:

Cerebrovascular pressure autoregulation

CBF:

Cerebral blood flow

CBFV:

Cerebral blood flow velocity

COx:

Cerebral oxygenation index

CPP:

Cerebral perfusion pressure

ICM:

Intensive Care Monitor plus software

ICP:

Intracranial pressure

LAx:

Low-frequency autoregulation index

LDF:

Laser Doppler flow

Lx:

Autoregulation index based on LDF

Mx:

Mean arterial blood flow velocity index

ORx:

Oxygen reactivity index

PbtO2 :

Brain tissue oxygenation

PRx:

Pressure reactivity index

SAH:

Subarachnoid hemorrhage

Sx:

Systolic blood flow velocity index

TBI:

Traumatic brain injury

TCD:

Transcranial Doppler

THx:

Total hemoglobin index

References

  1. 1.

    Iadecola C. Neurovascular regulation in the normal brain and in Alzheimer’s disease. Nat Rev Neurosci. 2004;5:347–60.

  2. 2.

    Crippa IA, Subirà C, Vincent JL, et al. Impaired cerebral autoregulation is associated with brain dysfunction in patients with sepsis. Crit Care. 2018;22(1):327.

  3. 3.

    Steiner LA, Czosnyka M, Piechnik SK, et al. Continuous monitoring of cerebrovascular pressure reactivity allows determination of optimal cerebral perfusion pressure in patients with traumatic brain injury. Crit Care Med. 2002;30:733–8.

  4. 4.

    Joshi B, Ono M, Brown C, et al. Predicting the limits of cerebral autoregulation during cardiopulmonary bypass. Anesth Analg. 2012;114:503–10.

  5. 5.

    Panerai RB. Cerebral autoregulation: from models to clinical applications. Cardiovasc Eng. 2008;8:42–59.

  6. 6.

    Willie CK, Tzeng Y-C, Fisher JA, Ainslie PN. Integrative regulation of human brain blood flow. J Physiol. 2014;592:841–59.

  7. 7.

    Czosnyka M, Smielewski P, Kirkpatrick P, Laing RJ, Menon D, Pickard JD. Continuous assessment of the cerebral vasomotor reactivity in head injury. Neurosurgery. 1997;41:11–7 discussion 17-9.

  8. 8.

    Sorrentino E, Diedler J, Kasprowicz M, Budohoski KP, Haubrich C, Smielewski P, et al. Critical thresholds for cerebrovascular reactivity after traumatic brain injury. Neurocrit Care. 2012;16:258–66.

  9. 9.

    Jaeger M, Schuhmann MU, Soehle M, Meixensberger J. Continuous assessment of cerebrovascular autoregulation after traumatic brain injury using brain tissue oxygen pressure reactivity. Crit Care Med. 2006;34:1783–8.

  10. 10.

    Zeiler FA, Donnelly J, Calviello L, Menon DK, Smielewski P, Czosnyka M. Pressure autoregulation measurement techniques in adult traumatic brain injury, part I: a scoping review of intermittent/semi-intermittent methods. J Neurotrauma. 2017;34:3207–23.

  11. 11.

    Zeiler FA, Smielewski P, Stevens A, et al. Non-invasive pressure reactivity index using Doppler systolic flow parameters: a pilot analysis. J Neurotrauma. 2019;36(5):713–20.

  12. 12.

    Depreitere B, Güiza F, Van den Berghe G, Schuhmann MU, Maier G, Piper I, et al. Pressure autoregulation monitoring and cerebral perfusion pressure target recommendation in patients with severe traumatic brain injury based on minute-by-minute monitoring data. J Neurosurg. 2014;120:1451–7.

  13. 13.

    Tan CO, Taylor AJ. Integrative physiologic and computational approaches to understand autonomic control of cerebral autoregulation. Exp Physiol. 2014;99:3–15.

  14. 14.

    Guendling K, Smielewski P, Czosnyka M, et al. Use of ICM+ software for on-line analysis of intracranial and arterial pressures in head-injured patients. Acta Neurochir. 2006;96:108–13.

  15. 15.

    Okonkwo DO, Shutter LA, Moore C, et al. Brain tissue oxygen monitoring and management in severe traumatic brain injury (BOOST-II): a phase II randomized trial. Crit Care Med. 2017;45(11):1907–14.

Download references

Acknowledgements

Not applicable

Funding

S.P. Klein and B. Depreitere are supported in part by a Johnson & Johnson Research Chair in Profound analysis of cerebrovascular pressure autoregulation and associated physiological variables in severe traumatic brain injury at KU Leuven University. G. Meyfroidt is supported as a senior clinical researcher by the Research Foundation, Flanders (FWO), and receives funding by the KU Leuven (C2) for his work on neuromonitoring.

Availability of data and materials

Not applicable

Author information

All authors equally contributed to the manuscript. All authors read and approved the final manuscript.

Correspondence to Geert Meyfroidt.

Ethics declarations

Ethics approval and consent to participate

Not applicable

Consent for publication

All authors gave their final approval.

Competing interests

The authors declare that they have no competing interests.

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Klein, S.P., Depreitere, B. & Meyfroidt, G. How I monitor cerebral autoregulation. Crit Care 23, 160 (2019) doi:10.1186/s13054-019-2454-1

Download citation

Keywords

  • Cerebrovascular autoregulation
  • Monitoring
  • Brain
  • Cerebral blood flow
  • Cerebral perfusion pressure