Open Access
Add to BibSonomyAbstract
A noninvasive optoacoustic technique could be a clinically useful alternative to existing, invasive methods for cerebral oxygenation monitoring. Recently we proposed to use an optoacoustic technique for monitoring cerebral blood oxygenation by probing large cerebral and neck veins including the superior sagittal sinus and the internal jugular vein. In these studies we used a multi-wavelength optoacoustic system with a nanosecond optical parametric oscillator as a light source and a custom-made optoacoustic probe for the measurement of the optoacoustic signals in vivo from the area of the sheep neck overlying the external jugular vein, which is similar in diameter and depth to the human internal jugular vein. Optoacoustic signals induced in venous blood were measured with high resolution despite the presence of a thick layer of tissues (up to 10 mm) between the external jugular vein and the optoacoustic probe. Three wavelengths were chosen to provide accurate and stable measurements of blood oxygenation: signals at 700 nm and 1064 nm demonstrated high correlation with actual oxygenation measured invasively with CO-Oximeter (“gold standard”), while the signal at 800 nm (isosbestic point) was independent of blood oxygenation and was used for calibration.
©2007 Optical Society of America
1. Introduction
In the United States, an estimated 1.4 million traumatic brain injuries occur each year [1]. Of these cases, approximately 6% result in permanent disability, and 3.6% result in death. Current treatment strategies are aimed at minimizing additional brain damage due to secondary mechanisms such as cerebral edema, cerebral ischemia, and systemic hypoxemia and hypotension. In the intensive care unit, secondary injury is detected through monitoring of cerebral hemodynamics, electrical activity, and brain tissue oxygen tension or cerebral venous blood oxygenation (oxyhemoglobin saturation).
One method of monitoring global cerebral oxygenation is accomplished by insertion of a catheter in the jugular bulb of the internal jugular vein (IJV) to measure jugular venous oxygen saturation (SjvO2). The IJV is a major vein in the neck with a diameter of ~10–20 mm. There are two IJVs located symmetrically, one on each side of the neck lateral to the trachea. Their function is to drain blood from the brain. Although they contain some amount of extra-cerebral blood (from the head, neck, and face), the blood oxygenation measurement in the IJV can be used to monitor cerebral blood oxygenation [2]. The catheter measurements are based on infrared spectroscopy, which utilizes the significant change in absorption coefficient of hemoglobin upon binding with oxygen [5, 6]. Continuous monitoring of SjvO2 allows the detection of a decrease of blood oxygenation that worsens clinical outcome [3]. SjvO2 values less than 50% are associated with poor clinical outcome in traumatic brain injury patients including permanent disability and death [4]. While invasive monitoring of SjvO2 may provide valuable information to guide treatment, it has several limitations. Central line placement is associated with complications (bleeding, carotid artery puncture, infections, etc). Also, inappropriate placement of the catheter may generate misleading SjvO2 data. A catheter that is proximally displaced into the IJV will detect the saturation of mixed facial and cerebral venous blood, giving a higher SjvO2 value that could be falsely interpreted as evidence for adequate cerebral oxygenation. In addition, damage to the catheter tip may alter the SjvO2 readings.
The optoacoustic technique combines high optical contrast and high spatial resolution due to the insignificant scattering of laser-induced ultrasonic waves in tissue. The optoacoustic effect (generation of sound by light) was first discovered by Alexander Graham Bell [7]. The optoacoustic monitoring system for measurement of blood oxygenation is based on time-resolved detection of optoacoustic waves generated by short pulses of light [8]. It therefore combines the high optical contrast of spectroscopic measurements with the spatial resolution of ultrasound. Currently the optoacoustic technique is used in laboratory settings for a variety of projects including cancer detection [9,10], vascular imaging [11,12] and port wine stain depth determination [13]. Some of these projects utilize the change in the optical properties of blood with various levels of blood oxygenation. Our group proposed to use the optoacoustic technique for the measurement of blood oxygenation and total hemoglobin concentration [8,14–18]. Recently, Laufer, et. al., demonstrated high correlation of optoacoustic signal amplitude with blood oxygenation and hemoglobin concentration in vitro in optically thin model blood vessels embedded in tissue phantoms [19]. In this paper, we performed in vivo optoacoustic measurements of blood oxygenation in reflection (backward) mode with a triple-wavelength optoacoustic system in the external jugular vein (EJV) of sheep, which is similar in depth and diameter to the IJV of humans. We simultaneously took blood samples through a jugular catheter from the same location and measured actual blood oxygenation with a CO-Oximeter. This allows the in vivo validation of the optoacoustic measurements with the gold standard invasive technique.
2. Materials and methods
The optoacoustic system developed and built for noninvasive measurement of blood oxygenation consisted of an optical parametric oscillator (OPO) system (Opolette 532 II, Opotek Inc., Carlsbad, CA) capable of generating nanosecond pulses in a range from 690 to 2400 nm. The OPO system uses the second harmonic of a Q-switched Nd:YAG laser (Ultra CFR, Big Sky Technologies, Inc., Bozeman, MT) to pump a nonlinear crystal for frequency conversion. The OPO generates 10-ns pulses with a repetition rate of 20 Hz and is controlled by a laptop (Dell Inspiron 8200, Dell Inc., Round Rock, TX) using a LabView (National Instruments Corp., Austin, TX) based software. The light delivery and detection of the optoacoustic signal was performed by an optoacoustic probe designed and built in our laboratory. The probe combined four optical fibers for light delivery and a broadband piezoelectric transducer for the detection of ultrasonic signals. The center frequency of the piezo-transducer used for the construction of the probe is 2 MHz. The signal was amplified using pre- and secondary amplifiers and then acquired with a 100 MHz digitizer (National Instruments Corp., Austin, TX) and stored on the laptop computer using a LabView program developed in our laboratory.
The Institutional Animal Care and Use Committee of UTMB approved all procedures on animals. The sheep were anesthetized using 2.5% isoflurane in oxygen. Afterwards, animals were intubated and mechanically ventilated with a mixture of isoflurane in oxygen. The optoacoustic probe was attached to the surface of the sheep skin overlying the EJV. The position could be varied using a 3-D translation stage. The best position was determined by adjusting the transducer to the position where the optoacoustic signal reaches the maximal amplitude at 800 nm. The acoustic contact was provided by ultrasound gel (Aquasonic 100: Parker Laboratories Inc., Fairfield, NJ).
The measurements were performed on EJV of eight adult sheep at 3 wavelengths: 700, 800, and 1064 nm. The 800 nm (the isosbestic point) wavelength was chosen for calibration because at this wavelength the absorption coefficients of oxygenated and deoxygenated blood are equal. In contrast, the two other wavelengths were chosen due to the significant difference between the absorption coefficients of oxygenated and deoxygenated blood. To minimize the influence of electronic noise and possible motion artifacts on the results, 400 signals were averaged for every record requiring about 20 s. The whole set of measurements at three wavelengths required less than 3 minutes. The laser fluence at the site of probing was below the Maximal Permissible Exposure (MPE) for ocular tissues in the specified spectral range [20].
Blood oxygenation in the EJV was changed by varying the fraction of inspired oxygen (FiO2) in the inhaled gas mixture. The oxygenation of arterial blood (real-time assessment of changes in oxygen level during the experiment) was monitored by a pulse-oximeter (Surgivet, Smith Medical PM, Inc, Waukesha, WI) that was attached to the tongue of the sheep. Accurate measurements of the EJV oxygen saturation level were performed with the COOximeter (IL 813 Instrumentation Laboratories, Lexington, MA) by taking blood samples using the Swan-Ganz catheter inserted into the vein.
3. Results
Figure 1 shows typical raw optoacoustic signals recorded from the EJV at three different wavelengths (700, 800, and 1064 nm) and at three different levels of blood oxygenations (91.9%, 54.5%, and 19.0%). The first peak represents the signal induced in the skin. The second, greater peak was induced in the EJV.
With a decrease in oxygenation, the amplitude of the optoacoustic signal from the EJV at 700 nm increased, as a consequence of an increase in desaturated hemoglobin, while the signal at 1064 nm decreased, as a consequence of a decrease in saturated hemoglobin. The signals at 800 nm are to be independent of oxyhemoglobin saturation, but varied due to changes in the incident laser power. The laser energy output of the OPO varies for different wavelengths and is not stable throughout the experiment due to heating of the OPO.
Figure 2 shows the time course of the optoacoustic signal amplitudes as the blood oxygenation was varied in the EJV. Variation of FiO2 resulted in changes in the blood oxygenation in the EJV and in changes in the optoacoustic signal amplitudes at 700 and 1064 nm. The optoacoustic signal amplitude increases at 1064 nm (empty triangles) and decreases at 700 nm (filled circles) with blood oxygenation (empty squares). We performed 2 cycles in which we reduced blood oxygenation and then increased it again.
Fig. 1. Optoacoustic signals measured at 700, 800, and 1064 nm and blood oxygenations of 91.9%, 54.6%, and 19.0%.
Figure 3 shows the dependence of the optoacoustic signal amplitudes on the blood oxygenation in the EJV in one representative sheep with both cycles (a - first cycle, b - second cycle). The optoacoustic signal amplitudes were normalized to the signal generated at 800 nm. These measurements show good correlation between the optoacoustic signal amplitude and the blood oxygenation in the EJV. However, the amplitudes of the optoacoustic signals are dependent on tissue optical properties and thickness, probe alignment, and laser pulse energy. This does not allow for a universal calibration. The correlation between amplitude and blood oxygenation would have to be established for every test subject and alignment. Monitoring of blood oxygenation by using only the amplitude measurements, therefore, would not be accurate and practical. A clinically practical algorithm must be independent on these factors.
Fig. 2. Time course of blood oxygenation (squares) and optoacoustic signal amplitudes at 700 nm (filled circles) and 1064 nm (triangles).
Fig. 3. Optoacoustic signal amplitudes at 700 nm (filled circles) and 1064 nm (empty squares) normalized to signal amplitude at 800 nm for two cycles (a - first cycle, b - second cycle).
We analyzed the temporal profile of the optoacoustic signals to determine its dependence on blood oxygenation using an algorithm recently described in our publication [21]. The algorithm is based on correlation of optoacoustic signal temporal profile with absorption coefficient in reflection (backward) mode [22]. The minimal value of the bipolar optoacoustic signal generated in the EJV was selected and then normalized to 1. To reduce the effect of oscillations of the transducer, the signal was integrated starting from the normalized minimum. Then the value of the integral was determined within 3-µs interval from the minimum. The 3-µs interval corresponds to a depth of 4.5 mm into the EJV (3 µs×1.5 mm/µs=4.5 mm, where 1.5 mm/µs is the speed of sound). At this depth nearly all light is absorbed in blood. The inverse value of the integral linearly increases with effective attenuation coefficient. This is because higher effective attenuation coefficient returns the signal more quickly to the baseline. Figure 4 shows the time course of the inverse integral calculated with this algorithm for optoacoustic signals measured at 700 and 1064 nm.
Fig. 4. Time course of blood oxygenation (open squares) and inverse integral of optoacoustic signals for 700 nm (solid circles) and 1064 nm (open triangles).
To eliminate the influence of variation of total hemoglobin and laser power, the values of the integral were then normalized using the values of integral obtained at the wavelength of 800 nm. Figure 5 shows the correlation of the normalized values of the inverse integral with blood oxygenation (a - first cycle, b - second cycle).
To obtain a universal calibration we calculated a ratio of the integrals at 1064 nm and 700 nm (Fig. 6). This ratio follows the ratio of the computationally derived optoacoustic signals for corresponding wavelengths and oxygenations using Monte Carlo simulation for a cylindrical geometry. Briefly, we modeled optoacoustic signals generated by light with 700 nm and 1064 nm for planar geometry with embedded cylindrical object. We used our Monte Carlo code described in our previous work [23]. We assumed that the vessel has a diameter of 8 mm (typical value for sheep EJV) and located 3 mm below the skin. To estimate the influence of blood oxygenation, we varied concentrations of oxyhemoglobin from 10% to 90%. The absorption coefficients for each wavelength were calculated from literature data [24] by linear interpolation of molar extinction coefficients of oxyhemoglobin and deoxyhemoglobin. The scattering coefficients were found using the effective attenuation coefficient measured in vitro [16]. The anisotropy factor g was considered constant (g=0.99) for both of the wavelengths [25,26].
The modeled signals were processed with the same algorithm that was applied to the in vivo sheep data. First, we normalized the signals so that minima of the signals had equal values. Then we integrated the signal over time starting at the minimum. For each wavelength, we calculated the value of the integrals at 3 µs from the minimum. Finally, we calculated the ratios of the integrals at 700 nm and 1064 nm. The obtained results are presented in Fig. 6. The difference between the experimental and modeling results were associated with the limited frequency bandwidth of the optoacoustic probe and its finite dimensions. Our computer modeling also demonstrated that for such large blood vessels the inverse integrals of the optoacoustic signals did not depend on vessel diameter, depth, and optical properties (absorption and scattering coefficients) of surrounding tissue.
Fig. 5. Correlation of the inverse integrals with blood oxygenation at 700 nm (solid circles) and 1064 nm (open squares) for two cycles (a - first cycle, b - second cycle).
Fig. 6. Ratio of optoacoustic signal integrals obtained at 1064 and 700 nm from experimental data (solid circles) and from computer modeling using Monte Carlo simulation and optoacoustic theory (open squares). The lines represent second order polynomial fits.
4. Discussion
The obtained results indicate that there is a strong correlation between the amplitude of the optoacoustic signals and actual blood oxygenation measured by taking blood samples using a catheter. However, the amplitudes of the signals cannot be used for monitoring blood oxygenation because amplitudes are dependent on: the laser fluence reaching the blood vessel which varies between test subjects. The correlation between amplitude and oxygenation would have to be established for every test subject and alignment. Therefore, monitoring of oxygenation using only the amplitude measurements would not be practical.
The new approach based on the integration of normalized optoacoustic signal provides good correlation with oxygenation and may be used for robust monitoring of blood oxygenation. The better correlation of the integral at 1064 nm resulted from the time delay between optoacoustic measurement and blood sampling. Optoacoustic measurements were generally taken first at 700 nm, then at 800 nm, and last at 1064 nm. The blood sample was taken immediately after the measurement at 1064 nm. Blood oxygenation in the sheep changes quicker by varying FiO2 compared to changes in blood oxygenation typical for patients.
The piezo-ceramic transducer is very sensitive (40 µV/Pa). It was capable of accurately recording optoacoustic signals at incident laser pulse energies of 60 µJ, which is below the maximal permissible exposure for ocular exposure. This high sensitivity allows the use of the optoacoustic system without safety goggles. Moreover, this high sensitivity may allow the use of less powerful laser diodes that will make the system cheaper and highly portable.
We found a strong correlation between the actual blood oxygenation in the EJV and the temporal profile measured with the optoacoustic probe. The EJV proves a good model to test the functionality of the optoacoustic technique for blood oxygenation monitoring.
5. Conclusion
In this study we measured blood oxygenation in the EJV in sheep, which is anatomically similar to the IJV in humans. The optoacoustic signal amplitude and the changes in the temporal profile measured in vivo correlates well with actual blood oxygenation measured invasively by using a catheter inserted in the EJV. The measurement of the integral of normalized optoacoustic signal can provide robust monitoring of blood oxygenation in large blood vessels. The optoacoustic technique may become a valuable tool for noninvasive and accurate monitoring of blood oxygenation in large vessels in real time.
Acknowledgments
This work is supported in part by the National Institutes of Health (Research Grant # R01 EB00763 from the National Institute of Biomedical Imaging and Bioengineering and Research Grant # R01 NS044345 from the National Institute of Neurological Disorders and Stroke).
References and links
1. J. A. Langlois and R. W. Sattin, “Traumatic brain injury in the United States: Research and programs of the Centers for Disease Control and Prevention (CDC) - Preface,” J. Head Trauma Rehab. 20, 187–188 (2005). [CrossRef]
2. W. Stevens, “Multimodal monitoring: head injury management using SjvO2 and LICOX,” J. Neurosci Nurs. 36, 332–339 (2004). [CrossRef]
3. P. R. Smythe and S. K. Samra, “Monitors of cerebral oxygenation,” Anes. Clin. N. Am. 20, 293–313 (2002). [CrossRef]
4. A. K. Gupta, “Monitoring the injured brain in the intensive care unit,” J. Postgrad. Med. 48, 218–225 (2002). [PubMed]
5. S. Wray, M. Cope, D.T. Deply, J.S. Wyatt, and E.O.R. Reynolds. “Characterization of the near infrared absorption spectra of cytochrome aa3 and hemoglobin for the non-invasive monitoring of cerebral oxygenation,” Biochem. et Biophys. Acta 933, 184–192 (1988). [CrossRef]
6. A. Roggan, M. Friebel, K. Dorschel, A. Hahn, and G. Muller, “Optical properties of circulating human blood in the wavelength range 400–2500 nm,” J. Biomed. Opt. 4, 36–46 (1999). [CrossRef]
7. A. G. Bell, “On the Production and Reproduction of Sound by Light: the Photophone,” Am. J. Sci. 3, 305–324 (1880).
8. R. O. Esenaliev, I. V. Larina, K. V. Larin, D. J. Deyo, M. Motamedi, and D. S. Prough, “Optoacoustic technique for noninvasive monitoring of blood oxygenation: a feasibility study,” Appl. Opt. 41, 4722–4731 (2002). [CrossRef] [PubMed]
9. J. A. Copland, M. Eghtedari, V. L. Popov, N. Kotov, N. Mamedova, M. Motamedi, and A. A. Oraevsky, “Bioconjugated gold nanoparticles as a molecular based contrast agent: Implications for imaging of deep tumors using optoacoustic tomography,” Mol. Imaging Biol. 6, 341–349 (2004). [CrossRef] [PubMed]
10. M. Eghtedari, M. Motamedi, V. L. Popov, N. A. Kotov, and A. A. Oraevsky, “Optoacoustic imaging of gold nanoparticles targeted to breast cancer cells,” Proc. SPIE 5320, 21–28 (2004). [CrossRef]
11. J. J. Niederhauser, M. Jaeger, R. Lemor, P. Weber, and M. Frenz, “Combined ultrasound and optoacoustic system for real-time high-contrast vascular imaging in vivo,” IEEE Trans. Med. Imaging 24, 436–440 (2005). [CrossRef] [PubMed]
12. X. D. Wang, Y. J. Pang, G. Ku, G. Stoica, and L. H. V. Wang, “Three-dimensional laser-induced photoacoustic tomography of mouse brain with the skin and skull intact,” Opt. Lett. 28, 1739–1741 (2003). [CrossRef] [PubMed]
13. J. A. Viator, G. Au, G. Paltauf, S. L. Jacques, S. A. Prahl, H. W. Ren, Z. P. Chen, and J. S. Nelson, “Clinical testing of a photoacoustic probe for port wine stain depth determination,” Laser Surg. Med. 30, 141–148 (2002). [CrossRef]
14. R. O. Esenaliev, Y. Y. Petrov, O. Hartrumpf, D. J. Deyo, and D. S. Prough, “Continuous, noninvasive monitoring of total hemoglobin concentration by an optoacoustic technique,” Appl. Opt. 43, 3401–3407 (2004). [CrossRef] [PubMed]
15. I. Patrikeev, Y.Y. Petrov, I.Y. Petrova, D.S. Prough, and R.O. Esenaliev, “Monte Carlo modeling of optoacoustic signals from large veins: implication for noninvasive monitoring of cerebral blood oxygenation,” in Biomedical Digest (Optical Society of America, 2006), paper SH64.
16. Y. Y. Petrov, D. S. Prough, D. J. Deyo, I. Y. Petrova, M. Motamedi, and R. O. Esenaliev, “In vivo noninvasive monitoring of cerebral blood oxygenation with optoacoustic technique,” in Proceedings of the 26th Intern. Conf. of IEEE EMBS, San Francisco, CA , Sept. 1–5, 2004, 2052–2054.
17. Y. Y. Petrov, D. S. Prough, D. J. Deyo, M. Klasing, M. Motamedi, and R. O. Esenaliev, “Optoacoustic, noninvasive, real-time, continuous monitoring of cerebral blood oxygenation: An in vivo study in sheep,” Anesthesiology 102, 69–75 (2005). [CrossRef]
18. I. Y. Petrova, R. O. Esenaliev, Y. Y. Petrov, H. P. Brecht, C. H. Svensen, J. Olsson, D. J. Deyo, and D. S. Prough, “Optoacoustic monitoring of blood hemoglobin concentration: a pilot clinical study,” Opt. Lett. 30, 1677–1679 (2005). [CrossRef] [PubMed]
19. J. Laufer, D. Delpy, C. Elwell, and P. Beard, “Quantitative spatially resolved measurement of tissue chromophore concentrations using photoacoustic spectroscopy: application to the measurement of blood oxygenation and haemoglobin concentration,” Phys. Med. Biol. 52, 141–168, (2007). [CrossRef]
20. “ANSI Z136.1 - 2000” in American national standard for safe use of lasers, (The Laser Institute of America, Orlando, FL2000).
21. Y. Y. Petrov, I. Y. Petrova, I. A. Patrikeev, R. O. Esenaliev, and D. S. Prough, “Multiwavelength optoacoustic system for noninvasive monitoring of cerebral venous oxygenation: a pilot clinical test in the internal jugular vein,” Opt. Lett. 31, 1827–1829 (2006). [CrossRef] [PubMed]
22. A. A. Karabutov, E. V. Savateeva, N. B. Podymova, and A. A. Oraevsky, “Backward mode detection of laser-induced wide- band ultrasonic transients with optoacoustic transducer,” J. Appl. Phys. 87, 2003–2014 (2000). [CrossRef]
23. I. Patrikeev, Y. Y. Petrov, I. Y. Petrova, D. S. Prough, and R. O. Esenaliev, “Monte Carlo modeling of optoacoustic signals from human internal jugular veins,” Appl. Opt. 46, 4820–4827 (2007). [CrossRef] [PubMed]
24. S. Prahl, “Optical Absorption of Hemoglobin,” http://omlc.ogi.edu/spectra/hemoglobin/index.html.
25. W. F. Cheong, S. A. Prahl, and A. J Welch, “A review of the optical properties of biological tissues” IEEE Trans. Med. Imaging 26, 2166–2185 (1990).
26. A. N. Yaroslavsky, I. V. Yarovslavsky, T Goldbach, and G. H. Sembrosk, “The Optical Properties of blood in the near infrared spectral range,” Proc. SPIE 2678, 314–324 (1996). [CrossRef]
