Dataset Information

Monitoring cerebral autoregulation after brain injury: multimodal assessment of cerebral slow-wave oscillations using near-infrared spectroscopy.

ABSTRACT: Continuous monitoring of cerebral autoregulation might provide novel treatment targets and identify therapeutic windows after acute brain injury. Slow oscillations of cerebral hemodynamics (0.05-0.003 Hz) are visible in multimodal neuromonitoring and may be analyzed to provide novel, surrogate measures of autoregulation. Near-infrared spectroscopy (NIRS) is an optical neuromonitoring technique, which shows promise for widespread clinical applicability because it is noninvasive and easily delivered across a wide range of clinical scenarios. The aim of this study is to identify the relationship between NIRS signal oscillations and multimodal neuromonitoring, examining the utility of near infrared derived indices of cerebrovascular reactivity.Twenty-seven sedated, ventilated, brain-injured patients were included in this observational study. Intracranial pressure, transcranial Doppler-derived flow velocity in the middle cerebral artery, and ipsilateral cerebral NIRS variables were continuously monitored. Signals were compared using wavelet measures of phase and coherence to examine the spectral features involved in reactivity index calculations. Established indices of autoregulatory reserve such as the pressure reactivity index (PRx) and mean velocity index (Mx) and the NIRS indices such as total hemoglobin reactivity index (THx) and tissue oxygen reactivity index (TOx) were compared using correlation and Bland-Altman analysis.NIRS indices correlated significantly between PRx and THx (rs = 0.63, P < 0.001), PRx and TOx (r = 0.40, P = 0.04), and Mx and TOx (r = 0.61, P = 0.004) but not between Mx and THx (rs = 0.26, P = 0.28) and demonstrated wide limits between these variables: PRx and THx (bias, -0.06; 95% limits, -0.44 to 0.32) and Mx and TOx (bias, +0.15; 95% limits, -0.34 to 0.64). Analysis of slow-wave activity throughout the intracranial pressure, transcranial Doppler, and NIRS recordings revealed statistically significant interrelationships, which varied dynamically and were nonsignificant at frequencies <0.008 Hz.Although slow-wave activity in intracranial pressure, transcranial Doppler, and NIRS is significantly similar, it varies dynamically in both time and frequency, and this manifests as incomplete agreement between reactivity indices. Analysis informed by a priori knowledge of physiology underpinning NIRS variables combined with sophisticated analysis techniques has the potential to deliver noninvasive surrogate measures of autoregulation, guiding therapy.

SUBMITTER: Highton D

PROVIDER: S-EPMC4957667 | biostudies-literature | 2015 Jul

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Monitoring cerebral autoregulation after brain injury: multimodal assessment of cerebral slow-wave oscillations using near-infrared spectroscopy.

Highton David D Ghosh Arnab A Tachtsidis Ilias I Panovska-Griffiths Jasmina J Elwell Clare E CE Smith Martin M

Anesthesia and analgesia 20150701 1

<h4>Background</h4>Continuous monitoring of cerebral autoregulation might provide novel treatment targets and identify therapeutic windows after acute brain injury. Slow oscillations of cerebral hemodynamics (0.05-0.003 Hz) are visible in multimodal neuromonitoring and may be analyzed to provide novel, surrogate measures of autoregulation. Near-infrared spectroscopy (NIRS) is an optical neuromonitoring technique, which shows promise for widespread clinical applicability because it is noninvasive ...[more]

PMID: 25993387

Similar Datasets

Project description:Individualizing mean arterial blood pressure (MAP) based on cerebral blood flow (CBF) autoregulation monitoring during cardiopulmonary bypass (CPB) holds promise as a strategy to optimize organ perfusion. The purpose of this study was to evaluate the accuracy of cerebral autoregulation monitoring using microcirculatory flow measured with innovative ultrasound-tagged near-infrared spectroscopy (UT-NIRS) noninvasive technology compared with transcranial Doppler (TCD).Sixty-four patients undergoing CPB were monitored with TCD and UT-NIRS (CerOx™). The mean velocity index (Mx) was calculated as a moving, linear correlation coefficient between slow waves of TCD-measured CBF velocity and MAP. The cerebral flow velocity index (CFVx) was calculated as a similar coefficient between slow waves of cerebral flow index measured using UT-NIRS and MAP. When MAP is outside the autoregulation range, Mx is progressively more positive. Optimal blood pressure was defined as the MAP with the lowest Mx and CFVx. The right- and left-sided optimal MAP values were averaged to define the individual optimal MAP and were the variables used for analysis.The Mx for the left side was 0.31 ± 0.17 and for the right side was 0.32 ± 0.17. The mean CFVx for the left side was 0.33 ± 0.19 and for the right side was 0.35 ± 0.19. Time-averaged Mx and CFVx during CPB had a statistically significant "among-subject" correlation (r = 0.39; 95% confidence interval [CI], 0.22-0.53; P < 0.001) but had only a modest agreement within subjects (bias 0.03 ± 0.20; 95% prediction interval for the difference between Mx and CFVx, -0.37 to 0.42). The MAP with the lowest Mx and CFVx ("optimal blood pressure") was correlated (r = 0.71; 95% CI, 0.56-0.81; P < 0.0001) and was in modest within-subject agreement (bias -2.85 ± 8.54; 95% limits of agreement for MAP predicted by Mx and CFVx, -19.60 to 13.89). Coherence between ipsilateral middle CBF velocity and cerebral flow index values averaged 0.61 ± 0.07 (95% CI, 0.59-0.63).There was a statistically significant correlation and agreement between CBF autoregulation monitored by CerOx compared with TCD-based Mx.

Project description:Cerebral perfusion may be altered in sepsis patients. However, there are conflicting findings on cerebral autoregulation (CA) in healthy participants undergoing the experimental endotoxemia protocol, a proxy for systemic inflammation in sepsis. In the current study, a newly developed near-infrared spectroscopy (NIRS)-based CA index is investigated in an endotoxemia study population, together with an index of focal cerebral oxygenation. Methods: Continuous-wave NIRS data were obtained from 11 healthy participants receiving a continuous infusion of bacterial endotoxin for 3 h (ClinicalTrials.gov NCT02922673) under extensive physiological monitoring. Oxygenated-deoxygenated hemoglobin phase differences in the (very)low frequency (VLF/LF) bands and the Tissue Saturation Index (TSI) were calculated at baseline, during systemic inflammation, and at the end of the experiment 7 h after the initiation of endotoxin administration. Results: The median (inter-quartile range) LF phase difference was 16.2° (3.0-52.6°) at baseline and decreased to 3.9° (2.0-8.8°) at systemic inflammation (p = 0.03). The LF phase difference increased from systemic inflammation to 27.6° (12.7-67.5°) at the end of the experiment (p = 0.005). No significant changes in VLF phase difference were observed. The TSI (mean ± SD) increased from 63.7 ± 3.4% at baseline to 66.5 ± 2.8% during systemic inflammation (p = 0.03) and remained higher at the end of the experiment (67.1 ± 4.2%, p = 0.04). Further analysis did not reveal a major influence of changes in several covariates such as blood pressure, heart rate, PaCO2, and temperature, although some degree of interaction could not be excluded. Discussion: A reversible decrease in NIRS-derived cerebral autoregulation phase difference was seen after endotoxin infusion, with a small, sustained increase in TSI. These findings suggest that endotoxin administration in healthy participants reversibly impairs CA, accompanied by sustained microvascular vasodilation.

Project description:BackgroundCerebral blood flow (CBF) is maintained over a range of blood pressures through cerebral autoregulation (CA). Blood pressure outside the range of CA, or impaired autoregulation, is associated with adverse patient outcomes. Regional oxygen saturation (rSO2) derived from near-infrared spectroscopy (NIRS) can be used as a surrogate CBF for determining CA, but existing methods require a long period of time to calculate CA metrics. We have developed a novel method to determine CA using cotrending of mean arterial pressure (MAP) with rSO2that aims to provide an indication of CA state within 1 minute. We sought to determine the performance of the cotrending method by comparing its CA metrics to data derived from transcranial Doppler (TCD) methods.MethodsRetrospective data collected from 69 patients undergoing cardiac surgery with cardiopulmonary bypass were used to develop a reference lower limit of CA. TCD-MAP data were plotted to determine the reference lower limit of CA. The investigated method to evaluate CA state is based on the assessment of the instantaneous cotrending relationship between MAP and rSO2 signals. The lower limit of autoregulation (LLA) from the cotrending method was compared to the manual reference derived from TCD. Reliability of the cotrending method was assessed as uptime (defined as the percentage of time that the state of autoregulation could be measured) and time to first post.ResultsThe proposed method demonstrated minimal mean bias (0.22 mmHg) when compared to the TCD reference. The corresponding limits of agreement were found to be 10.79 mmHg (95% confidence interval [CI], 10.09-11.49) and -10.35 mmHg (95% CI, -9.65 to -11.05). Mean uptime was 99.40% (95% CI, 99.34-99.46) and the mean time to first post was 63 seconds (95% CI, 58-71).ConclusionsThe reported cotrending method rapidly provides metrics associated with CA state for patients undergoing cardiac surgery. A major strength of the proposed method is its near real-time feedback on patient CA state, thus allowing for prompt corrective action to be taken by the clinician.

Dataset Information

Monitoring cerebral autoregulation after brain injury: multimodal assessment of cerebral slow-wave oscillations using near-infrared spectroscopy.

Publications

Monitoring cerebral autoregulation after brain injury: multimodal assessment of cerebral slow-wave oscillations using near-infrared spectroscopy.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure