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Current Directions in Biomedical Engineering

Joint Journal of the German Society for Biomedical Engineering in VDE and the Austrian and Swiss Societies for Biomedical Engineering

Editor-in-Chief: Dössel, Olaf

Editorial Board: Augat, Peter / Buzug, Thorsten M. / Haueisen, Jens / Jockenhoevel, Stefan / Knaup-Gregori, Petra / Kraft, Marc / Lenarz, Thomas / Leonhardt, Steffen / Malberg, Hagen / Penzel, Thomas / Plank, Gernot / Radermacher, Klaus M. / Schkommodau, Erik / Stieglitz, Thomas / Urban, Gerald A.


CiteScore 2018: 0.47

Source Normalized Impact per Paper (SNIP) 2018: 0.377

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2364-5504
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Measuring different oxygenation levels in a blood perfusion model simulating the human head using NIRS

Preliminary results of model evaluation measurements

K. Rackebrandt
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  • Graduate School for Computing in Medicine and Life Sciences, Universität zu Lübeck, Ratzeburger Allee 160 23552 Lübeck Germany, +49 451 500 3730
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/ H. Gehring
  • Departement of Anesthesiology and Intensive Care, University Medical Center, Lübeck, Germany Ratzeburger Allee 160, 23562 Lübeck, Germany
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Published Online: 2015-09-12 | DOI: https://doi.org/10.1515/cdbme-2015-0091

Abstract

The oxygenation, perfusion and metabolism of the brain - segmented in both hemispheres - can be estimated from the oxygenation and hemoglobin levels of the venous blood in the cerebral efferent vessels.

We present a phantom based model to simulate the anatomical target region which was connected to hemodynamic perfusion circuit to provide different oxygenation rates inside of the simulated target vessel (measurement cell) reproducible. A triple-wavelength (770, 808 and 850 nm) multi-distance NIRS sensor (6 photodiodes, linearly arranged, separated 6 mm each) was used to detect these different saturation levels.

The results illustrate the capability to measure the optical property variation of hemoglobin due to oxygenation and deoxygenation processes in a specific vessel. Based on these first results a series of measurements is introduced to correlate the amount of reflected light to the actual oxygen saturation of the blood.

Keywords: Near-infrared spectroscopy (NIRS); Oxygenation; Multi-distance (MD) Sensor; Phantom model

1 Introduction

Several non-invasive near-infrared spectroscopy (NIRS) monitoring systems were developed to determine blood oxygenation in the human head. In this context the oxygen content of the cerebral efferent vessels is a physiological parameter for the estimation of the perfusion and the metabolism of the brain.

The oxygen content of the venous blood is defined as,

Cvo2=(k1×tHb×Svo2)+(k1×Pvo2)(1)

where k1 is the Hüfner’s constant, tHb is the total hemoglobin concentration, SvO2 is the venous oxygen saturation, k2 is the solubility coefficient of oxygen and PvO2 is the venous partial pressure of oxygen [1].

The NIRS systems measure the amounts of oxygenated and deoxygenated hemoglobin (O2Hb & HHb) for the estimation of tHb and SvO2. To identify these hemoglobin derivates these systems need a light source with at least three wavelengths, the first one at the isosbestic point of O2Hb and HHb (about 800 nm), the second one below and the third one above of this point. At different oxygenation levels the amount of O2Hb and HHb vary and therefore the optical properties as well. The diagnostic window ranges from 600-1000 nm (Figure 1). Only in this wavelength region light can penetrate the scalp and the skull with a sufficient depth to sense the target vessel (sigmoid sinus) [2]. For a reflective multi-distance NIRS system the irradiated light can be expected to follow a curved path through the head for each source detector pair [3]. The penetration depth of the light corresponds with the wavelength as well as the source and detector separation. The optical properties of the tissue are linked with the amount of reflected and transmitted light and they are mainly characterized by the absorption coefficient µa 1/mm, the reduced scattering coefficient µs’ 1/mm and the anisotropy g (g = <cos(θ)>; θ = Deflection angle).

Absorption spectra of oxygenated (O2Hb) and deoxygenated (HHb) hemoglobin (Based on [10]).
Figure 1

Absorption spectra of oxygenated (O2Hb) and deoxygenated (HHb) hemoglobin (Based on [10]).

The anatomical target region consists of four layers, the scalp (Layer1, 4-8 mm), the skull (Layer 2, 4-10 mm), the blood inside of the sigmoid sinus (Layer 3, Ř 5 mm) and the brain tissue (Layer 4) in the depth [5, 6].

2 Methods

2.1 Model setup

The model setup is based on a similar model presented by [7]. Two glass beakers made from DURAN (DURAN Group GmbH), with a transmission of 99% in the interesting wavelength region, were arranged non-concentrically. The thickness of the gap between these beakers were 8 mm (Figure 2). A measurement cell was attached to the inner side of the inner beaker, simulating the target vessel (Layer 3 – Blood inside of the cell). The cell was connected to the perfusion circuit, to generate realistic optical property changes in the sample volume.

Layered phantom model. Layer 1: Scalp; Layer 2: Skull; Layer 3: Blood inside the sigmoid sinus; Layer 4: Brain.
Figure 2

Layered phantom model. Layer 1: Scalp; Layer 2: Skull; Layer 3: Blood inside the sigmoid sinus; Layer 4: Brain.

The phantom model consists mainly of two intralipid based phantoms, simulating the scalp & skull (Layer1+2) and the brain (Layer 4). The scalp & skull phantom was placed in the gap (8 mm) between the glass beakers and the brain phantom inside of the inner beaker. The manufacturing process of these phantoms is presented elsewhere [8].

The layered structure and the calculated optical properties of the phantoms are visualized in Table 1. The optical properties were determined with the usage of a double integrating sphere setup and the IAD algorithm [9]. The whole setup was covered with a black box made from black POM and neoprene to avoid the interference of the ambient light.

Table 1

Phantom structure and optical properties of the different Layers.

2.2 Perfusion circuit

The perfusion circuit consists of a pump (Bio-Medicus 540 Bio Console centrifugal pump 120 V, 60 Hz., Medtronic GmbH, 1000 rpm) to generate a venous flow, a heating unit (D8-G, Thermo Haake) to ensure a blood temperature of about 37 °C and an oxygenator (D901 Dideco LiLLiPut, Sorin Group Italia) with an included blood reservoir, which was connected to the gas supply, to provide defined oxygenation levels. By adjusting the inflow of oxygen and nitrogen the amounts of oxygenated and deoxygenated hemoglobin could be varied and therefore the optical properties of the blood.

A schematic overview of the designed perfusion circuit is visualized in Figure 3. Two sample ports were integrated to collect the blood samples in front of and behind of the oxygenator to ensure its functionality. Additionally a reference measurement unit, consisting of a white light source (SL1, Stellarnet Inc.) and a detector (EPP2000, Stellarnet Inc.)) recording the spectrum of the blood, was attached. For the experiments erythrocyte concentrate was diluted with sodium chloride (Sterofundin ISO 1/1 E ISO, B. Braun Melsungen AG) until the total hemoglobin concentration (tHb) was equal to 12 g/dl.

Schematic of the perfusion circuit connected to model setup.
Figure 3

Schematic of the perfusion circuit connected to model setup.

2.3 Hardware and software setup

The hardware for the reflective sensor can be divided into a light source and a receiving unit (Figure 4). The former was equipped with three LEDs (Series 330 – 1206, OSA Opto Light GmbH) 770, 808 and 850 nm and a power of about 2 mW driven in continuous mode. The light sources were operated with 2 V DC. The latter consists of 6 photo diodes (PD) (BP 104 S, OSRAM Opto Semiconcutors GmbH) separated 6 mm each with peak sensitivity at 850 nm. Each PD had a sensitive area of 4.8 mm2.

Sensor configuration and target vessel position.
Figure 4

Sensor configuration and target vessel position.

The signals were acquired with a data acquisition card (USB 6259, National Instruments, TX, USA) at a sampling rate of 1 kHz. A low-pass filter (5th order Sallen-Key) with a cut-off frequency of 30 Hz was implemented in the hardware circuit to cut off noise from the power supply before further signal processing.

3 Results

To identify the needed distances of the photodiodes and the light source to measure exactly the sample volume (Layer 3), the results for all six PDs were analyzed separately. The measurements M1-M3 were separated in two parts, the inflow of oxygen and the inflow of nitrogen. In the Figures 57 the detected signals for PD3 are visualized since an SDS of 18 mm is approx. equal to a penetration depth of about 9 mm, which is within the simulated target vessel. The solid black lines in the images mark the change of the gas inflow and the dashed ones the points of the reference measurements.

Oxygenation changes at 770 nm.
Figure 5

Oxygenation changes at 770 nm.

Oxygenation changes at 808 nm.
Figure 6

Oxygenation changes at 808 nm.

Oxygenation changes at 850 nm.
Figure 7

Oxygenation changes at 850 nm.

The results from the series of measurements are visualized in Table 2.

4 Discussion

The results of the experiments proved the capability to detect the optical property variation of hemoglobin due to oxygenation and deoxygenation processes in the anatomical target region (Layer 3) with the presented setup.

For all three wavelengths the signal intensity changes seemed reasonable under the consideration of the associated absorption coefficients for O2Hb and HHb at these points. Since the inflow of oxygen increased the amount of O2Hb the measured signal intensity for 770 nm was heightened and for 850 nm reduced. The amount of HHb was increased by the inflow of nitrogen which raised the signal intensity at 850 nm and lowered it at 770 nm.

Table 2

Overview of the measurements, results and conclusions.

Figure 6 revealed a small intensity change for a wavelength of 808 nm, although it should be constant at the isosbestic point of both substances. This will be investigated in further measurements to verify if this signal intensity change is noise or if it’s a systematic issue linked to the setup model and the perfusion circuit. Since a small change in the tHb concentration (12-10 g/dl) was determined during the experiments with Co-Oximeter, this might be the reason for the signal variation at 808 nm.

5 Conclusion

Based on these first results a series of measurements (n=10) is planned to verify the results of the preliminary experiments. Since the three wavelength were investigated consecutively there might be a slide variation of the model setup & hemodynamic circuit properties. For the planned experiments the three LEDs will be driven in a pulsed mode to avoid any property shift during the measurements. The main objective is the correlation of the amount of reflected light to the oxygen saturation of the blood in the target volume.

The preliminary results revealed a small variation of the tHb in the perfusion circuit which will be cancelled out by increasing the pre-experimental time to get a completely mixed system upfront.

Acknowledgement

This publication is a result of the ongoing research within the LUMEN research group, which is funded by the German Federal Ministry of Education and Research (BMBF, FKZ 13EZ1140A/B). LUMEN is a joint research project of Lübeck University of Applied Sciences and Universität zu Lübeck and represents an own branch of the Graduate School for Computing in Medicine and Life Sciences of Universität zu Lübeck.

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About the article

Published Online: 2015-09-12

Published in Print: 2015-09-01


Author's Statement

Conflict of interest: Authors state no conflict of interest. Material and Methods: Informed consent: Informed consent has been obtained from all individuals included in this study. Ethical approval: The research related to human use has been complied with all the relevant national regulations, institutional policies and in accordance the tenets of the Helsinki Declaration, and has been approved by the authors’ institutional review board or equivalent committee.


Citation Information: Current Directions in Biomedical Engineering, Volume 1, Issue 1, Pages 371–375, ISSN (Online) 2364-5504, DOI: https://doi.org/10.1515/cdbme-2015-0091.

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