Development of a Model to Aid NIRS Data Interpretation: Results from a Hypercapnia Study in Healthy Adults

Biomedical Optics Research Laboratory, Department of Medical Physics and Bioengineering, University College London, Malet Place Engineering Building, Gower Street, London, WC1E 6BT, UK.
Advances in Experimental Medicine and Biology (Impact Factor: 1.96). 04/2012; 737:293-300. DOI: 10.1007/978-1-4614-1566-4_43
Source: PubMed


The use of a mathematical model of cerebral physiology and metabolism may aid the interpretation of experimentally measured data. In this study, model outputs of tissue oxygen saturation (TOS) and velocity of blood in the middle cerebral artery (Vmca) were compared with experimentally measured signals (TOS using near infrared spectroscopy and Vmca using transcranial Doppler) acquired during hypercapnia in healthy volunteers. Initially, some systematic discrepancies between predicted and measured values of these variables were identified. The model was optimised to best fit the measured data by adjusting model parameters. To improve the fit, three additional model mechanisms were considered. These were: an extracerebral contribution to TOS, a change in venous volume with CO2 levels, and a change in oxygen consumption with CO2 levels. Each mechanism, when used alone, improved the fit of the model to the data, although significant parameter changes were necessary. It is likely that a combination of these mechanisms will improve the success of modelling of TOS and Vmca changes during hypercapnia.

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    • "The hyperventilation task is expected to decrease the arterial concentration of CO2, ultimately inducing a decrease in brain blood flow [40,41]. Importantly, both tasks have been previously suggested to induce a global response [42,43]. By global, we mean that the cerebral and the extra-cerebral (scalp/skull) tissues should both exhibit hemodynamic variations in response to the ventilation tasks, although the magnitude of the flow variation across tissue types might be different. "
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    ABSTRACT: A pilot study explores relative contributions of extra-cerebral (scalp/skull) versus brain (cerebral) tissues to the blood flow index determined by diffuse correlation spectroscopy (DCS). Microvascular DCS flow measurements were made on the head during baseline and breath-holding/hyperventilation tasks, both with and without pressure. Baseline (resting) data enabled estimation of extra-cerebral flow signals and their pressure dependencies. A simple two-component model was used to derive baseline and activated cerebral blood flow (CBF) signals, and the DCS flow indices were also cross-correlated with concurrent Transcranial Doppler Ultrasound (TCD) blood velocity measurements. The study suggests new pressure-dependent experimental paradigms for elucidation of blood flow contributions from extra-cerebral and cerebral tissues.
    Biomedical Optics Express 07/2013; 4(7):978-994. DOI:10.1364/BOE.4.000978 · 3.65 Impact Factor
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    • "However, a differing baseline is more easily explained. Similar observations were made during studies in healthy volunteers [7], but in this case TOS could be explained by adjusting the extracerebral:intracerebral signal weighting to 80:20 or doubling the venous volume, both of which seem unlikely. Studies such as these indicate that accurate prediction and interpretation of TOS might require combined modelling of cerebral physiology and light transport in tissue. "
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    ABSTRACT: Understanding changes in cerebral oxygenation, haemodynamics and metabolism holds the key to individualised, optimised therapy after acute brain injury. Near-infrared spectroscopy (NIRS) offers the potential for non-invasive, continuous bedside measurement of surrogates for these processes. Interest has grown in applying this technique to interpret cerebrovascular pressure reactivity (CVPR), a surrogate of the brain's ability to autoregulate blood flow. We describe a physiological model-based approach to NIRS interpretation which predicts autoregulatory efficiency from a model parameter k_aut. Data from three critically brain-injured patients exhibiting a change in CVPR were investigated. An optimal value for k_aut was determined to minimise the difference between measured and simulated outputs. Optimal values for k_aut appropriately tracked changes in CVPR under most circumstances. Further development of this technique could be used to track CVPR providing targets for individualised management of patients with altered vascular reactivity, minimising secondary neurological insults.
    Advances in Experimental Medicine and Biology 03/2013; 765:87-93. DOI:10.1007/978-1-4614-4989-8_13 · 1.96 Impact Factor
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    ABSTRACT: Noninvasive approaches to measuring cerebral circulation and metabolism are crucial to furthering our understanding of brain function. These approaches also have considerable potential for clinical use "at the bedside". However, a highly nontrivial task and precondition if such methods are to be used routinely is the robust physiological interpretation of the data. In this paper, we explore the ability of a previously developed model of brain circulation and metabolism to explain and predict quantitatively the responses of physiological signals. The five signals all noninvasively-measured during hypoxemia in healthy volunteers include four signals measured using near-infrared spectroscopy along with middle cerebral artery blood flow measured using transcranial Doppler flowmetry. We show that optimising the model using partial data from an individual can increase its predictive power thus aiding the interpretation of NIRS signals in individuals. At the same time such optimisation can also help refine model parametrisation and provide confidence intervals on model parameters. Discrepancies between model and data which persist despite model optimisation are used to flag up important questions concerning the underlying physiology, and the reliability and physiological meaning of the signals.
    PLoS ONE 06/2012; 7(6):e38297. DOI:10.1371/journal.pone.0038297 · 3.23 Impact Factor
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