An in vitro hemodynamic tissue model to study the variations in flow using near infrared spectroscopy

Transcription

1 An in vitro hemodynamic tissue model to study the variations in flow using near infrared spectroscopy Raghavender Ranga, Dheerendra Kashyap, Khosrow Behbehani, Hanli Liu University of Texas at Arlington & University of Texas Southwestern Medical Center at Dallas ABSTRACT Determination of blood flow changes will be helpful for evaluation of tumor prognosis and therapy. Our study is to develop an in vitro hemodynamic phantom model, which allows us to show the feasibility of using near infrared spectroscopy (NIRS) to determine flow changes as a dynamic imaging modality to monitor tumor responses to therapy. In the hemodynamic phantom model, both single and multiple, transparent, plastic tubes were used to pass through a cylindral glass chamber. The chamber was filled with either an Intralipid solution or a soft gelatin phantom, while the tube or tubes were pumped with either an Intralipid-ink mixture or animal whole blood to simulate the tumor vasculature. The Intralipid solutions that were filled in the chamber and tubes had optical scattering and absorption properties similar to those of tumor tissues and tumor vasculature. A single-channel, broadband, NIRS system with a tungsten light source and a CCD-array spectrometer was used to quantify the changes in optical density (OD) of the intralipid-ink mixture with variations in flow rate and concentration. A single-exponential curve fit has been used to determine the time constant (τ) from the change in OD to estimate the flow rate. The obtained preliminary results show a strong correlation between changing rates of concentration and flow; a multivariable dynamic mathematical model may be also established to relate changes of Hb, HbO and blood volume with blood flow. 1. INTRODUCTION Near Infrared spectroscopy (NIRS) has been effectively used to non-invasively monitor tumor vascular oxygen changes under respiratory interventions 1. Similarly, determination of tumor blood flow under oxygenation changes using NIRS could be helpful in tumor prognosis and diagnosis. In principle, the circulatory functions of tumor vessels could be effectively used for cancer diagnosis and therapy. It would be especially important to elucidate blood flow and tumor oxygenation for better efficacy of most forms of cancer therapy. The characteristics of microcirculation in the early stages of tumor growth suggest a possible mechanism for the enhancement of chemotherapy and immunotherapy 2. Similarly, the efficacy of the radiation therapy depends greatly on the oxygen concentration of the tumor, which is governed by tumor blood flow. It is known that hypoxic cells are three times more resistant to radiation induced killing than normal cells 3. Several studies have shown that poorly perfused regions of tumor and hypoxic regions are indispensable factors determining the tumor response to radiation therapy 4, 5. It is imperative that proper knowledge on the hemodynamic parameters before and during the course of therapy may have the potential for optimal selection of therapy. There has been a great interest in the estimation of tumor blood flow (TBF) and tumor oxygenation. Enhancement of these factors can improve the radio sensitivity of the tumor cells. A particular emphasis has been given to the characterization of tumor blood flow. Many studies 6-8 on tumor blood flow have shown that with the increase in tumor mass, there is a significant reduction in the perfusion rate. Pathogenetic mechanisms have been considered as one of the factors responsible for the decline in the blood flow with several structural and functional abnormalities. Decrease in tumor blood flow could also be caused by the development of the necrotic regions as the oxygen consumption is significantly lowered with increasing tumor size. Decreases of the TBF with increases of tumor size may indicate that the oxygen delivery to the tumor is restricted or limited by the decreased TBF, leading to further hypoxia of tumor cells. Then, the hypoxic cells will greatly decrease the radiotherapy sensitivity for the tumor tissue. Therefore, both oxygenation and blood flow of the tumor play essential roles for tumor responses to radiation therapy and several other tumor therapies. Thus, tumor oxygenation and TBF could serve as indicators or markers for better tumor prognosis and treatment planning. 366 Optical Tomography and Spectroscopy of Tissue VI, edited by Britton Chance, Robert R. Alfano, Bruce J. Tromberg, Mamoru Tamura, Eva M. Sevick-Muraca, Proc. of SPIE Vol (SPIE, Bellingham, WA, 25) /5/$15 doi: /

2 Moreover, several different invasive and noninvasive techniques, such as functional magnetic resonance imaging (fmri) using gradient recalled echo MR, have been used to measure blood flow and oxygenation in tumor tissue 9, 1. Hemodynamic models using BOLD signal of fmri have also been developed to correlate changes in hemoglobin concentration with blood flow and blood volume 11, 12. However, the measurements obtained through these methods have been confounded by changes in both oxygenated and deoxygenated hemoglobin with blood flow. Therefore, similar studies were performed using NIRS to correlate the changes in hemoglobin concentration with variations in blood flow of the brain. This correlation offers a unique ability to derive the changes in blood flow from the direct measurement of the changes in hemoglobin concentration in the brain 13. The goal of our study given in this paper is to develop tissue equivalent phantoms 14-16, which can be used to associate the rate of change in hemoglobin concentration with the blood flow, which can further serve as an important parameter/marker in assessment of tumor therapy. 2. METHODS AND MATERIALS 2.1 Single Tube Phantom Preparation The hemodynamic, tissue-simulating phantom was built in a cylindrical glass tube of 15cm 4.5cm (length x diameter). In the first generation, the tissue vasculature was simulated by a single tube, which passed through the center of the glass tube. Namely, a transparent tygon tube (Cole Parmer, IL, USA) of 9.5 mm diameter passed through the center of the cylindrical glass tube. The small tygon tubing was surrounded by an Intralipid (Baxter 2% Intralipid, IV fat emulsion) solution diluted from 2% to 1% to yield optical properties similar to those of tissue. The two figures shown in Figs. 1(a) and 1(b) are the schematic diagram and the photo of the first generation of dynamic phantoms cm cylindrical glass tube Tissue simulating phantom Blood Simulating liquid Source and detector Figure 1(a) Peristaltic pump Figure 1(b) 2.2 Multi Tube Phantom Preparation L NIR monitor tumor vasculature manifold 4.5 cm Tissue-simulating liquid Pump Figure 2(a). dynamic tissue phantom Oxygenation chamber A Doppler flow meter O 2 N 2 Dymanic phantom with multi-tubes imbedded. Figure 2(b) Proc. of SPIE Vol

3 In the second generation of dynamic phantom development, the imbedded single tube was replaced by several small tubes that were distributed throughout the glass tube to more realistically resemble the tissue vasculature. The small tubes were transparent tygon tubes (Cole Parmer, IL, USA) with 1.3 mm for inner diameter. Also, these small tubes were surrounded by the Intralipid solution within the glass tube, in the way similar to that used in the single tube case. A circular manifold distributed the fluid from a single,.375 tygon tube into the small, multiple tygon tubes imbedded within the phantom by a peristaltic pump (Master Flex, Cole Parmer, IL, USA). Similarly, another manifold at the other end of the phantom reunited the small tubes into one single tube and collected the fluid into the reservoir. Figures 2(a) and 2(b) are the schematic diagram and the photo of the second generation of dynamic vascular phantoms. 2.3 The Broadband NIRS System A single-channel, broadband, NIRS system consists of a 6-µm probe as the source fiber and a 4-µm probe as the detector fiber. The measurements taken from the simulated phantom were recorded when a tungsten-halogen, continuous wave, broadband light (HL 2 Ocean Optics) was delivered and detected through a CCD array spectrometer (USB 2 Ocean Optics), as shown in Fig. 1(a). The continuous wave system provided us with a spectrum of 45 nm to 9 nm for the quantification of absorption and scattering properties of the simulated rat tumor brain. 2.4 Experimental Preparation Two kinds of experimental studies were conducted to study the flow variations using NIRS. In the single-tube phantom studies, an intralipid-ink solution was used as the circulating fluid, and the India ink was utilized as an optical absorber within the solution. In the multi-tube phantom study, both the intralipid-ink solution and whole sheep blood were used for the circulating fluid. 2.5 Blood Preparation Defibrinated sheep blood (Hemostat, CA) was diluted with phosphate buffer saline in a 1:1 ratio. The diluted blood was then poured into the conical flask for oxygenation and deoxygenation. 2.6 Experiment Protocol The changes in optical density (O.D.) were calculated using the Beer-Lambert law for varying absorption, as follows: O.D. = ln (I b /I t ), (1) where I b was the spectral slope in the range of 7 nm 85 nm during the steady state condition, and I t was the slope during the transient state. The dynamic studies were conducted by firstly obtaining the baseline readings at the steady state, then followed by the external flow perturbation during the transient state, when the dynamic spectral changes were also recorded. Then, the corresponding O.D. values can be estimated, giving rise to a dynamic profile of O.D., for which a single exponential equation, eq. (2), was used to fit a time constant, τ, to the OD data. This time constant would be directly associated with the flow rate. Y=a (1-exp (-(to-t)/τ)). (2) where a is a constant parameter, not closely related to the flow rate. When the Intralipid-ink solution was used in the measurement, the baseline was obtained by passing the intralipid without ink. The dynamic measurements were then conducted by introducing external perturbation by adding a certain concentration of ink into the intralipid solution and pumped it through the glass tube. Different sets of experiments were performed by changing concentrations of ink and by varying the flow rate. For the multi-tube phantom experiments, deoxygenated sheep blood (Lot # S61986, Sheep Blood, Hemostat, CA) was used as an initial state for the baseline readings, followed by fully oxygenated blood as an external perturbation with a chosen flow rate to circulate through the glass tube. In this way, we were able to record the dynamic changes in light intensity due to a perturbed flow of oxygenated blood. A hundred percent of nitrogen and oxygen gases were used to deoxygenate and oxygenate the animal blood in the process, respectively. The blood was oxygenated and deoxygenated in a conical flask. The rate of oxygenation was regulated by adjusting the oxygen flow rate and deoxygenation by nitrogen gas. 368 Proc. of SPIE Vol. 5693

4 3. RESULTS With the single-tube phantoms, several spectra were taken at different ink concentrations to study the spectral variations through the phantoms, as shown in Figure 3. The spectral intensities reached maximum when there was no ink in the Intralipid mixture, and they decreased as the concentration of ink increased in the Intralipid solution. Intensity (A.U) intralipid low conc of ink high conc of ink Wavelength (nm) Figure 3. Spectra taken at different ink concentrations mixed with the Intralipid solution. Figure 4 shows the dynamic changes in OD readings as the ink concentration was changed at a fixed flow rate. Due to the exponential nature of the dynamic changes in OD, an exponential equation, eq. (2), was used to fit the data. The experiment was repeated for different flow rates to associate the time constant, τ, with the flow rate as shown in Figure 5. It is seen that as the flow rate increases, the time constant decreases. Similar results were also obtained at different sets of ink concentrations and with different flow rates; the data are summarized in Figure 6. This figure clearly demonstrates that the obtained time constant is independent of the concentration of the ink added to the intralipid mixture Normalized OD (A.U) Time (sec) Figure 4. Single exponential fit to the dynamic changes in OD readings, y =.89[1-exp (-t-217.5) /71] with R =.97. Time Constant sec T im e c o n s t a n t ( s e c ) Flow Rate (ml/min) Figure 5. Time constant obtained with different flow rates, Using the Intralipid-ink mixture. Proc. of SPIE Vol

5 Time Constant sec Ul of ink 9 Ul of ink 12 Ul of ink Flow Rate ml/min Time Constant sec Flow rate ml/min Figure 6. Time constants obtained at different flow rates with different sets of ink concentrations: i.e., 6, 9, and 12 µl of ink added into the Intralipid solutions. Figure 7. Time constants obtained at different flow rates using animal whole blood in the circulation tubes. The experiments were repeated using animal whole blood in the multi-tube phantom. By evaluating the flow rate of the oxygenated blood, the time constants were obtained at different flow rates, as shown in Figure 7. These results show the possibility of using dynamic changes in optical signals to estimate flow rate. 4. DISCUSSION AND CONCLUSION This study demonstrates the feasibility of using an in vitro dynamic phantom model for blood flow dynamic studies. The data show the ability of using dynamic changes in optical signals to estimate a flow rate. This methodology provides us with a technique for estimating a flow rate using NIRS. The model was originally designed to simulate the rat brain containing a tumor. Although this dynamic model was a simplified version as the tumor vasculature is very complex 2 to mimic, the phantom model was designed taking much of the physiological aspects into consideration. The volume fraction of the blood vessels was similar to the tumor vessels (~14%). One of the critical parameters taken into consideration was the optical properties of the phantom model that were maintained similar to those of realistic tissues. In the first generation of phantom designs, a single-tube model was developed to mimic a group of vessels. The spectral signals were noisy, dominantly due to large absorption of the single tube and limited intensity of the light source. Later on, in the second generation of phantom development, the experiments were conducted with a much stronger light source and with distributed smaller tubes. The spectra shown in Figure 3 demonstrate the ability to detect the changes in optical density of a flowing liquid through the tubes. The dynamic phantom was later rebuilt with the inclusion of multiple small tubes, mimicking tissue vascular structure to a certain extent. The circulating fluid was further replaced with whole animal blood. In general, the dynamic phantom design was made according to the volume fraction of the tumor tissue (~14%). The data given in this study show the feasibility of using these dynamic phantoms to characterize the flow of the tumor tissue. The advantage of these phantoms is their stability to measurements and their ability to be reused several times with the same and controlled experimental conditions, unlike the tumor tissue whose characteristic features vary. A more quantitative relationship has to be established through modeling techniques to quantify the flow rate with different vascular volumes in the phantoms. The modeling techniques can be implemented in the animal studies using the rat brain tumor models, and we are currently working in this direction. Acknowledgement We would like to thank the support from NIH (-R21CA1198-1). 37 Proc. of SPIE Vol. 5693

6 REFERENCES 1. H. Liu, Y. Song, K. L. Worden, X. Jiang and A. Constantinescu, "Non Invasive investigation of blood oxygenation dynamics of tumors by near infrared spectroscopy", Applied Optics, 39, , 2 2. M. Suzuki., K. Hori., I. Abe., S. Saito. and H. Sa., "Functional Characterization of the microcirculation in tumors", Cancer Metastasis Reviews3, , R. S. Bush and R. D. T. Jenkin, "Definitive Evidence for hypoxic cells influencing cure in cancer therapy", British Journal of Cancer, 37, 32-36, J. Evans and P. Bergso, "The influence of anemia and results of radiotherapy in carcinoma of the cervix", Radiology, 48, , I. F. Tannock, "Oxygen and the distribution of cellular radiosensitivity in tumors", British Journal of Radiology, 45, , F. Kallinowski, K. H. Schlenger and S. Runkel, "Blood Flow, metabolism, cellular microenvironment and growth rate of human tumor xenografts", Cancer Research, 49, , P. Vaupel, H. P. Fortmeyers, S. Runkel and F. Kallinowski, "Blood flow, oxygen consumption, and tissue oxygenation of human breast cancer xenografts in nude rats", Cancer Research, 47, , R. K. Jain, "Determinants of Tumor Blood Flow: A Review", Cancer Research, 48, , F. A. Howe and S. P. Robinson, "Discrimination of blood flow and oxygenation changes in rat tumors in response to carbogen breathing", Proceedings of the 3rd Annual Meeting of society of Magnetic Resonance, 64, S. P. Robinson, F. A. Howe, L. M. Rodrigues, M. Stubbs. and J. R. Griffiths, "Magnetic Resonance Imaging Techniques for monitoring changes in tumor oxygenation and blood flow", Seminars in Radiation Oncology, 8, , R. B. Buxton and L. R. Frank, "A model for coupling between cerebral blood flow and oxygen metabolism during neural stimulation", J. Cereb. Blood Flow Metab, 17, 64-72, R. B. Buxton, E. C. Wong and L. R. Frank, "Dynamics of blood flow and oxygenation changes during brain activation: The balloon model", Magnetic Resonance Medicine, 39, , D. A. Boas, G. Jasdzweski, G. Strangman, J. P. Culver and R. Poldrack, "Modeling of the Hemodynamic response function for event related Motor and Visual Stimuli as measured by NIRS", Proceedings of the Optical Society of America, C. D. Kurth, H. Liu., W. S. Thayer and B. Chance, "A dynamic phantom brain model for near infra red spectroscopy", Phys. Med. Biol, 4, , S. J. Madsen, M. S. Patterson and B. C. Wilson, "The use of India ink as an optical absorber in tissue simulating phantoms", Phys. Med. Biol, 37, , Y. Mendelson and J. C. Kent, "An in vitro tissue model for evaluating the effect of carboxyhemoglobin concentration on pulse oximetry", IEEE Trans. On biom. Eng, 36, , 1989 Proc. of SPIE Vol