Noninvasive cerebral oximetry: Is there light at the end of the tunnel?

Department of Neurocritical Care, The National Hospital for Neurology and Neurosurgery, University College London Hospitals, Queen Square, London, UK.
Current opinion in anaesthesiology (Impact Factor: 1.98). 10/2010; 23(5):576-81. DOI: 10.1097/ACO.0b013e32833e1536
Source: PubMed


There is increasing interest in the application of near infrared spectroscopy (NIRS) as a noninvasive monitor of cerebral oxygenation. This review will briefly describe the principles of NIRS and examine current evidence for its clinical application as a monitor of the adequacy of cerebral oxygenation in adults.
There has been a recent surge of interest in the clinical application of NIRS following studies that have quantified the benefits of NIRS-guided management of cerebral oxygenation during cardiopulmonary bypass. However, there are limited data to support its widespread application in other clinical scenarios. New NIRS systems are being introduced to the market and technological advancements have improved their accuracy and extended the range of variables measured.
NIRS offers noninvasive monitoring of cerebral oxygenation over multiple regions of interest in a wide range of clinical scenarios. It has many potential advantages over other neuromonitoring techniques, but further technological advances are necessary before it can be introduced more widely into clinical practice.

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    • "Furthermore, as compared to fMRI, fNIRS provides a more direct measure of changes in HbO, HbR, and total hemoglobin (HbT), and the time series are sampled at high temporal resolution . It has therefore proved to be an effective tool for studying physiological mechanisms in the healthy brain and in cerebrovascular disease (Highton et al., 2010; Wolf et al., 2012; Obrig, 2014). It is also finding unique applications in clinical areas, including bedside monitoring of infants, and studies of auditory and language systems (Lloyd-Fox et al., 2010; Eggebrecht et al., 2014). "
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    ABSTRACT: Functional near-infrared spectroscopy (fNIRS) is an emerging technique for measuring changes in cerebral hemoglobin concentration via optical absorption changes. Although there is great interest in using fNIRS to study brain connectivity, current methods are unable to infer the directionality of neuronal connections. In this paper, we apply Dynamic Causal Modelling (DCM) to fNIRS data. Specifically, we present a generative model of how observed fNIRS data are caused by interactions among hidden neuronal states. Inversion of this generative model, using an established Bayesian framework (variational Laplace), then enables inference about changes in directed connectivity at the neuronal level. Using experimental data acquired during motor imagery and motor execution tasks, we show that directed (i.e., effective) connectivity from supplementary motor area to primary motor cortex is negatively modulated by motor imagery, and this suppressive influence causes reduced activity in primary motor cortex during motor imagery. These results are consistent with findings of previous functional magnetic resonance imaging (fMRI) studies, suggesting that the proposed method enables one to infer directed interactions in the brain mediated by neuronal dynamics from measurements of optical density changes. Copyright © 2015 The Authors. Published by Elsevier Inc. All rights reserved.
    NeuroImage 02/2015; 8. DOI:10.1016/j.neuroimage.2015.02.035 · 6.36 Impact Factor
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    • "Conversely to the commercially available devices, they supply measures of HbO 2 and HbH in addition to rSO 2 through nonadhesive sensors that can be more easily placed in various regions of the head. The use of these various instruments or systems makes it difficult to interpret findings between studies (Highton et al., 2010). Nonetheless, the Invos 5100B and Niro 300 devices have been shown to produce very similar results with overall bias of À2.1% (limits of agreement of AE14.7%) (Thavasothy, Broadhead, 523 Innovating in Pain Assessment of the Critically Ill Elwell, Peters, & Smith, 2002). "
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    ABSTRACT: Nurses play a crucial role in the evaluation and treatment of pain in the critically ill patient. This responsibility is all the more critical with this particular population because many may not be able to self-report their pain level and the typical behavioral signs of pain may be subtle or absent. According to recent recommendations, vital signs should not be used as primary indicators of pain but rather considered as a cue to begin further assessment. Other than vital signs, human brain reactivity to pain has been extensively studied with the use mainly of magnetic resonance imaging and positron-emission tomography. However, the use of these sophisticated methods may be unrealistic in the critically ill. Of interest to assessing these patients in a clinical setting is the noninvasive measurement of regional cerebral tissue oxygenation with the near-infrared spectroscopy (NIRS) technique. There are indications that NIRS is capable of detecting the cerebral hemodynamic changes associated with sensory stimuli, including pain. The objective of this review paper is to provide nurses with a better understanding of NIRS technology, including a review of the literature on functional studies that have used NIRS in critically ill populations, and how it could be used in both research and practice. Current NIRS techniques have well recognized limitations which must be considered carefully during the measurement and interpretation of signals. Thus, its clinical use is yet to be fully established. Nonetheless, cerebral NIRS technique as an approach to assess brain activity in response to pain should not be abandoned.
    Pain management nursing: official journal of the American Society of Pain Management Nurses 06/2014; 15(2):519-529. DOI:10.1016/j.pmn.2012.03.005 · 1.53 Impact Factor
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    • "Currently, several NIRS devices are commercially available for clinical use, with lack of standardization among them [2, 16, 19, 21]. In fact, although the various models are mostly based on spatial resolution spectroscopy [16, 22], they differ in numerous important aspects related to the acquisition of their cerebral oxygen saturation measurements, including the algorithms adopted, the type of light source, the wavelengths of light emitted and the distance between the various light emitters and detectors [19]. "
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    ABSTRACT: Introduction Several near-infrared spectroscopy oximeters are commercially available for clinical use, with lack of standardization among them. Accordingly, cerebral oxygen saturation thresholds for hypoxia/ischemia identified in studies conducted with INVOSTM models do not necessarily apply to other devices. In this study, the measurements made with both INVOSTM and EQUANOXTM oximeters on the forehead of 10 patients during conventional cardiac surgery are directly compared, in order to evaluate the interchangeability of these two devices in clinical practice. Methods Cerebral oxygen saturation measurements were collected from both INVOSTM 5100C and EQUANOXTM 7600 before anesthetic induction (baseline), two minutes after tracheal intubation, at cardiopulmonary bypass onset/offset, at aortic cross-clamping/unclamping, at the end of surgery and whenever at least one of the two devices measured a reduction in cerebral oxygen saturation equal to or greater than 20% of the baseline value. Bland-Altman analysis was used to compare the bias and limits of agreement between the two devices. Results A total of 140 paired measurements were recorded. The mean bias between INVOSTM and EQUANOXTM was -5.1%, and limits of agreement were ±16.37%. Considering the values as percent of baseline, the mean bias was -1.43% and limits of agreement were ±16.47. A proportional bias was observed for both absolute values and changes from baseline. Conclusions INVOSTM and EQUANOXTM do not seem to be interchangeable in measuring both absolute values and dynamic changes of cerebral oxygen saturation during cardiac surgery. Large investigations, with appropriate design, are needed in order to identify any device-specific threshold.
    03/2014; 6(3):197-203.
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