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Back-directional Gated Spectroscopic Imaging for Diffuse Light Suppression in High Anisotropic Media and Its Preclinical Applications for Microvascular Imaging Zhengbin Xu, Jingjing Liu, Dae Ho Hong, Viet Quoc Nguyen, Mi Ran Kim, Sulma I. Mohammed, and Young L. Kim
Abstract—There is emerging evidence that microvascular alterations may occur early, even at early stages of carcinogenesis, as indispensable participants in tumor growth. However, the exact spatial extents of such alterations remain unclear, in part, because detailed microvascular alterations in relatively deep tissue over a relative large area are not easily visualized. Due to the heterogeneous nature of tissue microvasculature, microscopic evaluations with a small field of view often fail to provide a representative assessment. On the other hand, conventional whole-body small-animal optical imaging techniques suffer from unwanted diffuse light, which would otherwise deteriorate image contrast and resolution. To fill such a gap, we take advantage of the high anisotropic property of biological tissue by implementing backdirectional gating into an imaging platform to suppress unwanted diffuse light. We further combine a spectral analysis of microvascular hemoglobin (Hb) absorption with back-directional gated imaging to improve image resolution, contrast, and penetration depth that are required for subcutaneous mouse xenograft models. In tissue phantom and pilot animal studies, we demonstrate that our diffuse-light-suppressed spectroscopic imaging platform can be a simple, yet effective, imaging setup to visualize subcutaneous microvascular Hb content over a relatively large area. Index Terms—Diffusion suppression, hemoglobin (Hb) absorption, microvasculature, spectroscopic imaging, tumor xenograft.
I. INTRODUCTION HE DETECTION of alterations in microvasculature and microcirculation such as vessel density, blood flow, blood content, and oxygen saturation plays a critical role in examining various diseases including diabetes, hypertension, sepsis, and
T
Manuscript received July 31, 2009; revised November 1, 2009; accepted October 18, 2009. Date of publication December 22, 2009; date of current version August 6, 2010. This project was supported in part by the Translational Research Acceleration Collaboration internal pilot grant mechanism of the Indiana University Simon Cancer Center, in part by an American Cancer Society Institutional Research Grant IRG-58-006-47 to the Purdue Cancer Center, and in part by a grant from the Purdue Research Foundation. Z. Xu, J. Liu, V. Q. Nguyen, and Y. L. Kim are with the Weldon School of Biomedical Engineering, Purdue University, West Lafayette, IN 47907 USA (e-mail:
[email protected];
[email protected];
[email protected];
[email protected]). D. H. Hong is with the Department of Bioengineering, University of Pittsburgh, Pittsburgh, PA 15260 USA (e-mail:
[email protected]). M. R. Kim and S. I. Mohammed are with the School of Veterinary Medicine and Purdue Cancer Center, Purdue University, West Lafayette, IN 47907 USA (e-mail:
[email protected];
[email protected]). Color versions of one or more of the figures in this paper are available online at http://ieeexplore.ieee.org. Digital Object Identifier 10.1109/JSTQE.2009.2037160
cancer. In this respect, several optical spectroscopic or imaging technologies have been intensively investigated. Point measurements using diffuse reflectance and light scattering spectroscopy have been successfully used to characterize tissue biochemical composition [1]–[8]. For example, optical-fiberbased diffuse light spectroscopy has been used for assessments of drug concentrations [2], vascular blood content, and oxygenation levels [3]. Among promising technologies, the visualization of microvasculature with the capability of its quantitative assessment has received considerable attention. Intravital microscopy has been the gold standard for the assessment of microvascular morphology and physiology primarily in animal studies [9]. Similar to conventional fluorescence microscopy, intravital microscopy, however, requires fluorescence labeling and a transmission-mode configuration, thus making it not adequate for clinical use. To overcome the limitations of intravital microscopy for clinical applications, orthogonal polarization spectral microscopic imaging was developed [10] and was commercialized as Cytoscan video microscope for clinical use in humans. Because microvasculature is often heterogeneous in a large tissue area, examining a small area can fail to provide a representative assessment. To overcome such site-to-site variability, laser Doppler imaging [11] or laser speckle imaging [12], [13] have been used to visualize heterogeneous blood flow in a relatively large tissue area. Doppler optical coherence tomography [14], [15] has also shown to visualize the functional information of blood flow in a relatively deeper region on a complementary structural image of optical coherence tomography. Instead of the blood flow measurements, multispectral imaging has been recently developed to quantitatively monitor blood volume and oxygen saturation with a large field of view of approximately 250 mm2 with relatively low resolution [16]. Recently, photoacoustic microscopy and computed tomography have been developed to visualize microvasculature in the skin and the brain of mice with an imaging depth up to 30 mm [17]. Indeed, optical microvascular imaging has the potential to revolutionize drug development by providing noninvasive preclinical testing platforms. In particular, xenografts of human tumors grown athymic mice, severe combined immunodeficiency (SCID) mice, or other immunocompromised mice have consistently been used to develop and evaluate new drugs before human clinical studies [18]. In these preclinical studies, there
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is a critical need to bridge the gap between microscopic imaging and whole-body small-animal imaging. Because the size of typical tumor implantation can be large, extending to 5–10 mm in diameter, either microscopic imaging or whole-body imaging are not adequate for imaging such an area with high resolution. In the subcutaneous (i.e., beneath all the layers of the skin) mouse xenograft models, it is also extremely important to visualize microvascular alterations through the entire dorsal skin, including the epidermis, the dermis, and the subcutaneous tissue (also called the hypodermis). Since the total thickness is as thick as 0.5–1 mm [19], the detailed spatial information about subcutaneous microvasculature can be masked. Overall, although recent advances in optical imaging have demonstrated its great potential for microvascular imaging, to date, there still remain hurdles for widespread utilization of optical techniques to quantify microvascular abnormalities in relatively deep tissue over a relatively large area. In our previous study, we demonstrated that back-directional gating can be an effective method for removing a significant amount of unwanted diffuse light, and thus, improving the contrast of an object embedded in high anisotropic scattering media, such as biological tissue [20]. A unique optical property of biological tissue is high anisotropy with the anisotropy factor g = 0.8–0.95 [21]. However, such an intrinsic property of biological tissue had not been used to significantly suppress unwanted diffuse light. Because ballistic or snake-like light propagates along the direction of the incident light [22], back-directional gating allows us to remove a substantial amount of diffuse light that exits in the medium at oblique angles with respect to the optical axis. In this case, the high anisotropic property of the surrounding medium serves as a waveguide and improves image contrast of an object embedded at a moderate depth. Thus, this can be a simple, yet effective, imaging approach to substantially remove unwanted diffuse light and to improve the visualization of subcutaneous microvascularity, thus allowing representative assessments of microvascularity. In this paper, we further hypothesize that the combination of a spectral analysis with diffuse-light-suppressed imaging increases imaging depth that is required to visualize microvasculature in relatively deep tissue. We report that back-directional gated spectroscopic imaging is a simple, yet effective, imaging platform to visualize subcutaneous microvascularity. In Section II, we discuss the effects of back-directional gating angle on diffuse light suppression in high anisotropic media and our simple spectral analysis to quantify total microvascular hemoglobin (Hb) content. In Sections III and IV, we show results from a series of experiments including a color target located at a relatively deep depth inside scattering media. We demonstrate our simple, yet effective, algorithm for mapping the microvascular Hb content in a relatively large area within a relatively short time. Furthermore, we apply diffuse-light-suppressed spectroscopic imaging to two different subcutaneous mouse xenograft models as a pilot study. Finally, we exemplify that our imaging platform has potential to effectively image neoangiogenesis and provide the exact spatial extent of this critical tissue process.
Fig. 1. Schematic of the experimental setup. Back-directional gating allows the suppression of diffuse light in high anisotropic media. Along the entrance slit of the imaging spectrograph, the CCD records a matrix of y and λ at a given position of x, while the entrance slit is scanned along the x-axis of the image plane with a step size of 50 µm. The (x, y) unit area is 50 µm × 52 µm (=13 µm × 4 pixels).
II. METHODS A. Experimental Setup A schematic diagram of our experimental setup is shown in Fig. 1. A beam from a 1000 W xenon arc lamp (Newport, Irvine, CA) is collimated using a 4-f system that consists of two lenses (f = 75 and 200 mm) and an aperture. The xenon arc lamp provides a full visibility to near IR range spectrum, while its high power reduces the acquisition time. The beam size is adjusted to 15 mm in diameter to image a large area. A mirror deflects the beam through a beam splitter and onto the sample. The beam is incident upon the sample at a 15◦ angle to remove specular reflection. After the beam contacts the sample, light backscattered from the sample travels back through the beam splitter and is collected by the second 4-f system. The equalfocal configuration (f = 75 mm) in this 4-f system forms 1:1 images of the illuminated surface. A small aperture in the detection 4-f system of our system collects nearly exact backscattered light from the sample within a small angular cone of 2◦ . The detection system consists of a spectrograph (Princeton Instruments, Trenton, NJ) coupled to a charge-coupled device (CCD) camera (Princeton Instrument) and a translational stage (Zaber Technologies, Inc., Vancouver, British Columbia, Canada). The entrance slit of the spectrograph is positioned on the image plane of the sample with a width of 50 µm. A spectrograph allows the acquisition of a spectral image with a full visible to near IR range of spectral variation (400 ∼ 900 nm). Our current slit width provides a spectral resolution of 2 nm. The entrance slit of the imaging spectrograph scans along the x-axis of the image plane with a step size of the slit width. Thus, we construct a 3-D dataset, a matrix of scattered intensity as a function of x and y at each wavelength. For each sample, its 3-D dataset is normalized by the one from a reflectance standard (Labsphere, Inc., North Sutton, NH) to correct the nonuniformities of the light source and the wavelength response of the detection system. We synchronize the detection components and acquire images from a custom interface written in Lab-VIEW (short for Laboratory Virtual Instrumentation Engineering Workbench, version 8.2, National Instruments).
XU et al.: BACK-DIRECTIONAL GATED SPECTROSCOPIC IMAGING FOR DIFFUSE LIGHT SUPPRESSION IN HIGH ANISOTROPIC MEDIA
Fig. 2. FWHM of LSF over different back-directional gating angle θ in the numerical experiments of the same anisotropy factor. This shows the resolving power (i.e., sample resolution) of the bottom layer in the presence of the thick top scattering medium. Small back-directional angles (θ < 15◦ ) achieve higher image resolution of the embedded target than do large angles (θ > 35◦ ). The inset shows the sample in the numerical experiment.
B. Back-directional Gating in High Anisotropic Media for Improving Image Resolution A unique optical property of biological tissue is the tendency for light to be scattered in the same direction as the incident direction. This overall directional tendency of the scattered light is quantified by the anisotropy factor g, which is the average cosine of the scattering angle. Most of biological tissue including the mouse skin has an anisotropy factor g = 0.8–0.95 [21]. This anisotropic property of biological tissue is often considered to deteriorate image contrast and resolution. However, the high anisotropic property implies that the isolation of light reflected in the exact backward direction allows us to select the light that is reflected along the optical axis and that slightly deviates from its original optical axis. Thus, in back-directional gating, this high anisotropic property of the surrounding scattering medium can serve as a waveguide to deliver the incident light to an embedded object and to isolate the ballistic or snake-like light backscattered from the object. To demonstrate the effect of back-directional gating angle (i.e., solid angles in the backward direction θ) on diffuse light suppression in high anisotropic scattering media, we briefly show results of numerical experiments using Monte Carlo simulations and nonsequential ray tracing in ZEMAX (ZEMAX Development Corporation, Bellevue, WA). This numerical study allows us to simply implement large numerical aperture (NA) lenses to achieve a large back-directional angle. In a numerical imaging setup, similar to the experimental setup shown in Fig. 1, we use high NA lenses of NA = 0.45 in the 4-f system of the detection arm. By adjusting the aperture size in the 4-f system, we achieve large back-directional angles up to 40◦ . As a sample [see Fig. 2 (inset)], a reflectance target consisting of two areas (half with 0% absorption and the other half with 30% absorption, g = 0, and τ = 100) is embedded at the optical thickness τ = 15 (the scattering coefficient µs is 7.5 mm−1 ) in a high anisotropic scattering medium of g = 0.9. In our Monte Carlo simulations, Henyey–Greenstein phase function is used and ∼108 photons are launched. We record images at several back-directional angles from 2◦ –40◦ . We estimate the details of the two-area target embedded (i.e., sample image resolution) using the full-width at half-maximum (FWHM)
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of line spread functions (LSF) [23]. The resolving power of the embedded object only (i.e., sample resolution) is approximately 1 mm at θ = 32◦ . Fig. 2 shows the FWHMs of the LSFs over different back-directional angle θ for the bottom layer with the top scattering medium. Unexpectedly from a Fourier optics standpoint, as θ increases, the FWHM of the LSF increases, showing higher NA in the detection yields lower image resolution. This result supports the idea that simple back-directional gating in high anisotropic turbid media removes a significant portion of unwanted diffuse light, minimizes crosstalk among adjacent pixels, and enhances the image resolution of an embedded object. Since diffuse light tends to exit turbid scattering media with an oblique backscattered angle, a large NA collects more diffuse light than does a small back-directional angle, and subsequently, deteriorates the image resolution of the embedded target. Given that most biological tissue is highly anisotropic, it is obvious that such back-directional gating can offer an imaging platform for improving imaging resolution in a relatively large area. C. Spectral Analysis With Absorption Spectral Area The combination of spectroscopic measurements with diffuse-light-suppressed imaging can further increase imaging depth and contrast to allow accurate quantification of the absorbance content embedded in a relatively thick scattering medium. This is because an absorption spectral analysis in a broad range of the wavelengths can permit accumulation of the contrast improvement at each wavelength. In biological tissue, Hb is the primary absorber in the wavelength range of 400– 600 nm. In this range, both oxygenated Hb (oxyHb) and deoxygenated Hb (deoxyHb) have unique absorption spectral patterns, while absorption from other major absorbance contents, such as melanin and bulirubin are minimal. For in vivo imaging of animals, it is difficult to obtain the spectral shape only from the scattering contribution in the absence of any absorbers. However, when broadband absorption patterns are applied to assess Hb absorption content, light-scattering spectra can be modeled as a monotonous declining function of the wavelength such as an exponential decay or a power-law decay, as shown in previous spectroscopic analyses (e.g., point measurement over a large volume of tissue) [4], [5], [24], [25]. For example, the spectrum can be fitted to the following expression: I = (C0 λ−c 1 )e−(C H b O 2 ∈H b O 2 +C H b ∈H b )
(1)
where CHbO 2 and CHb are the concentrations of oxyHb and deoxyHb, respectively, multiplied by the path length of light in the medium [6]. ∈HbO 2 and ∈Hb are the wavelength-dependent absorption coefficients of oxyHb and deoxyHb, respectively. c0 describes the overall intensity of the spectrum and c1 is the scatter power. Total Hb concentration can be estimated from CHbO 2 + CHb . The algorithms in the previous spectroscopic technologies would not be appropriate for our microvascular imaging, due to the significant data size generated by our imaging platform (e.g., ∼60 000 spectral analyses for one image). Thus, we implement a simple pattern-recognition method to assess the total Hb level in each unit (x, y) position, based
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on the approximation that the scattering contribution from the tissue can be modeled as a smooth decay function of the wavelength. We estimate the scattering contribution from the tissue as a smooth polynomial function of the wavelength. Spectrum at each position of x and y is fitted to a second polynomial function in the range of 440–900 nm as 2
Im odel (λ) = aλ + bλ + c
(2)
where a, b, and c are fitting coefficients. Then, we define the absorption spectral area as the summation of all data points in the difference between the model spectrum and the original spectrum within the spectral range of 500–625 nm. Within a typical range of tissue-scattering properties, the absorption spectral area can serve as a relatively accurate quantification of the microvascular Hb content at each pixel. We also validate the simple algorithm with the conventional spectral analysis using (1). Due to reduced crosstalk among adjacent pixels derived from back-directional gating in high anisotropic media, our spectral analyses can provide accurate absorption levels attributed to Hb content at individual pixels. III. MATERIALS AND EXPERIMENTS A. Color Target Experiments for Spectral Image Contrast Improvement To demonstrate the effect of surrounding anisotropic properties on spectral image contrast formed by the same backdirectional gating angle, we conducted tissue phantom studies using aqueous suspensions of polystyrene microspheres and a color target (Edmund Optics, Inc., Barrington, NJ). In our tissue phantoms, the color (magenta) target provided a unique spectral pattern and the aqueous suspensions of polystyrene microspheres served as an avascular scattering tissue. The square color target was placed under the thick scattering medium, covering approximately half of the imaging area. We fixed the backdirectional gating angle θ = 2◦ and changed the value of g as follows: For the top scattering media, we varied the value of g by using different sizes of microspheres of nominal diameters of 0.24 (Bangs Laboratories, Fishers, IN), 0.33 (Duke Scientific Corporation, Palo Alto, CA), and 0.76 µm (Bangs Laboratories), which corresponded to g = 0.51, 0.72, and 0.90 at λ = 600 nm, respectively. The scattering medium of g = 0.90 is considered to be close to most biological tissue, in particular to the skin. The optical thickness τ = 15 of the scattering media was kept identical for each g to mimic the mouse skin of ∼1 mm. We calculated the optical properties of the scattering media using Mie theory [26]. We collected the scattering spectra before placing the color target underneath to avoid modeling of the scattering spectra in these experiments. The absorption band of the magenta target covers 500–600 nm, similar to the Hb absorption bands in tissue. In order to visualize the absorbance content embedded in the scattering media, we reduced the 3-D dataset into a 2-D spectroscopic image using the following spectral analysis: at each position of x and y, we quantified a spectral area between the scattering spectrum (i.e., in the absence of the color target) and the spectrum of the color target embedded in the
scattering medium. After all the spectral analyses for the pixels, we generated images of magenta color content.
B. Quantification of Microvascular Hb Concentration In order to extract the value of total Hb concentration from the absorption spectral area, we need to convert the absorption spectral area to Hb concentration. In a series of tissue phantom studies, we used aqueous suspensions of polystyrene microspheres to mimic different scattering properties of biological tissue. We calculated the scattering properties (i.e., transport mean free path length ls∗ and anisotropy factor g) of the scattering media using Mie theory. For the aqueous suspensions of polystyrene microspheres with a nominal size of 0.36 µm (Duke Scientific Corporation) (g = 0.80 at wavelength 488 nm), we varied the scattering properties of the media by changing ls∗ = 350, 500, and 673 µm. At ls∗ = 673 µm, we also used different sizes of polystyrene microspheres, 0.36 and 0.50 µm (Duke Scientific Corporation), which corresponded to different anisotropy factors g = 0.80 and 0.87, respectively. For each aforementioned scattering medium, we increased the Hb concentration by adding the solution of lyophilized Hb powder (Sigma-Aldrich, St. Louis, MO) into the suspension at a step of approximately 0.20 mg/mL up to 3.0 mg/mL. At each step, we recorded spectral signals of the tissue phantom. In addition, we repeated the experiment using the scattering media of ls∗ = 673 µm and g = 0.80 for oxyHb and deoxyHb. OxyHb was achieved by exposure of Hb in the atmosphere and for deoxyHb, we used sodium dithionite (Na2 S2 O4 ) to deplete oxygen. We confirmed the oxygenation level of Hb using an oxygen meter (Microelectrodes, Inc., Bedford, New Hampshire).
C. Blood Vessel Phantom Experiments To validate the ability of our system to visualize the microvascular blood content underneath a thick scattering medium (i.e., the whole skin of mice), we conducted vessel phantom experiments. In this phantom, we filled Hb solution of 100 mg/mL into a micropolyurethane tubing (Scientific commodities, Inc., Lake Havasu City, AZ) with 0.64-mm inner diameter and 1.02-mm outer diameter. This phantom vessel was embedded between a suspension of polystyrene microspheres and a diffusive agarose background with microspheres. In this experiment, we used such a high Hb concentration, because the top scattering medium was thick to demonstrate that our imaging approach can reveal a hidden objective that would otherwise be masked by the strong scattering medium. We used the microspheres of 0.76 µm diameter in the suspension and also in the agarose background. On top of the vessel, the scattering medium had an optical thickness of τ = 10 to mimic the mouse skin. We used the tubing filled with Hb to mimic the microvasculature underneath the hypodermis of mouse skin. To validate our spectral analysis, we also used the conventional spectral analysis [i.e., (1)]. In addition, for the top scattering medium, we used a patch of excised mouse dorsal skin that included the epidermis, the dermis, and the subcutaneous fatty tissue.
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D. Pilot Animal Studies To test the feasibility of our imaging approach to accurately visualize subcutaneous microvascular Hb content, we conducted a pilot animal study using xenografts of human tumors. Melanoma cell line SK-MEL-5 (ATCC no. HTB-70) was obtained from American Type Culture Collection (Rockville, MD) specifically for these experiments. Cells were cultured in minimum essential medium eagle (Sigma, St. Louis, MO) with 10% fetal bovine serum (Invitrogen, Carlsbad, CA), 1-mM sodium pyrovate, and 2-mM L-glutamine and were grown at 37 ◦ C in the presence of 5% carbon dioxide (CO2 ). For our pilot imaging study, we used six SCID mice and five athymic nu/nu mice bearing the human melanoma cancer xenografts in compliance with National Institutes of Health (NIH) animal experiment guidelines (Principles of Laboratory Animal Care, NIH Publication No. 86–23, revised 1985) and approved by Purdue University Animal Care and Use Committee. SCID and athymic nu/nu mice were purchased from National Cancer Institute (NCI) at 5–6 weeks of age. The mice were subcutaneously implanted with 5 × 106 cells of melanoma human cancer cells. We euthanized the mice immediately before imaging using CO2 and imaged the mice within 1–2 h postmortem. For imaging the SCID mice, we shaved the dorsal skin using a clipper and a depilatory cream. The image acquisition time for each aforementioned experiment was typically less than 10 min for the entire 3-D dataset. IV. RESULTS A. Color Target Experiments for Spectral Image Contrast Improvement Fig. 3 shows images from the color target embedded in three different anisotropic media at the fixed back-directional angle of θ = 2◦ . As shown in the white light images (i.e., images containing all the wavelengths from 400 to 900 nm) in the insets of Fig. 3, the color target underneath the scattering medium is barely visible because it is masked by the diffuse light and the scattering intensity outside the absorption spectral band is significant. However, in the spectroscopic images, the color target is apparent through the scattering media, because the quantification of the spectral pattern reflected from the color target further reduces the contribution of the scattering media to image formation. Thus, the simple absorption spectral analysis increases the visibility at the imaging depth of τ = 15. Importantly, the color target is more visible through the scattering medium of g = 0.90 than that of g = 0.51 and 0.72 in our imaging configuration (θ = 2◦ ). In Fig. 3(d), we quantified the contrast of the spectroscopic image of the color target embedded in the thick scattering media with different anisotropy factors. The image contrast is defined as (Ihigh − Ilow )/(Ihigh + Ilow ), where Ihigh and Ilow were the average intensities of the area within and outside the color target area, respectively. The contrast increases when the anisotropy factor of the scattering medium increases. In particular, through back-directional gating, when the value of g reaches 0.9, which is close to most of biological tissue, the image contrast is close to 1. Indeed, back-directional gating enhances the absorption
Fig. 3. (a)–(c) Spectroscopic images of the color target embedded in the scattering media at the fixed back-directional gating angle (θ = 2◦ ) with different anisotropy factors g = 0.51, 0.72, and 0.90, respectively. The insets are white light images obtained from our imaging platform. (d) Image contrast of the color target over different g. The error bar represents a standard deviation. The spectroscopic image contrast increases as the value of g of the scattering medium.
spectral analysis and provides high contrast in high anisotropic scattering media. Therefore, an absorption spectral analysis in an optimized back-directional gating for biological tissue allows us to use the surrounding avascular tissue as a waveguide to deliver the incident light to microvessels and to isolate the ballistic or snake-like light reflected/absorbed from it, thus serving as an ideal platform for large-area microvascular imaging at relatively deep depth. B. Quantification of Microvascular Hb Concentration In the tissue phantom experiments, we examined whether in the typical range of the scattering properties of the mouse skin, our spectral analysis can serve as relatively accurate quantification of microvascular Hb content with an estimated level of error. The Hb absorption spectral areas were plotted in Fig. 4(a)– (c) as a function of Hb concentrations for the different tissue phantoms. The Hb absorption spectral areas were compared in Fig. 4(a) between oxyHb and deoxyHb in the scattering media of ls∗ = 673 µm and g = 0.80. Fig. 4(a) shows that oxygenation of Hb has minimal influence on the quantification of the absorption spectral area in our Hb spectral analyses. Especially when the Hb concentration is less than 2 mg/mL, the samples with deoxyHb and oxyHb yield the same absorption spectral areas. Our simple algorithm can provide the quantification of the total Hb concentration in turbid media without being strongly sensitive to oxygen levels. The Hb absorption spectral areas obtained from the tissue phantoms with two different g are depicted in Fig. 4(b). The Hb absorption spectral areas were relatively the same at each Hb concentration for g = 0.80 and 0.87, which can be considered to be typical g of the mouse skin. In other words, the effect of g on our spectral analysis is minimal. In Fig. 4(c), we plotted the Hb absorption spectral area over
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Fig. 5. Spectroscopic images of the vessel phantoms. (a) Hb content map generated from the simple absorption spectral analysis [see (2)]. The inset is the white light image obtained from our imaging platform. (b) Hb content map generated from the conventional model-based algorithm [see (1)]. Our absorption spectral analysis shows a similar Hb content map obtained from the conventional spectral analysis.
Fig. 4. (a)–(c) Hb absorption spectral area as a function of Hb concentration. (a) Our simple algorithm provides the quantification of the total Hb concentration without being strongly sensitive to oxygen levels. (b) Anisotropy factor g has minimal effect on our Hb absorption spectral area. (c) Using the data generated from the different ls∗ , we obtain the calibration curve between true and measured Hb concentrations. (d) We estimate levels of error of the Hb measurement. Upper and lower bounds correspond to ls∗ = 350 and 673 µm, respectively. The gray area indicates the measurement error due to the changes in the scattering properties.
ls∗
different Hb concentrations for = 350, 500, and 673 µm, which can be considered to be within the typical range of the mouse skin [27]. In order to extract the Hb concentration from the Hb absorption spectral area using the data generated from the different ls∗ , we fitted the data points with different scattering properties to a two-term exponential function (R2 = 0.99). The calibration curve [i.e., fitted curve in Fig. 4(c)] can be used to convert the Hb absorption spectral area to Hb concentration. We further quantified the error in the calibration as the maximum deviation of the measured Hb concentration in this phantom study. In particular, we estimated the error in the calibration curve using the data with ls∗ = 350 and 673 µm. As shown in Fig. 4(d), the measured Hb concentration is accurate when the concentration is less than 1 mg/mL, regardless of the scattering properties. As the Hb concentration increases, the measurement error increases up to 20% at Hb = 3 mg/mL. At a measured Hb concentration, the true value can reside in the gray region between the two boundaries for ls∗ = 350 and 673 µm. In the typical range of the scattering properties of the mouse skin, the simple spectral analysis can estimate a Hb concentration with an estimated level of error. C. Blood Vessel Phantom Experiments In the vessel phantom experiment, we embedded a single tubing filled with Hb solution in the scattering medium (τ = 10 under the sample surface). In the white light image [see Fig. 5(a) inset], the embedded vessel is not visible through the scatter-
Fig. 6. Images of the vessel phantoms under the patch of the mouse dorsal skin. (a) White light image obtained from our imaging platform. (b) Hb content map generated from our absorption spectral analysis.
ing medium. However, our Hb map generated from our spectral analysis clearly depicts the location of the vessel embedded in the medium. To validate our algorithm, we also applied the conventional model-based algorithm to the dataset of this vessel phantom experiment [6], [7]. We fit the spectrum of each pixel from 500 to 630 nm using (1). To increase the fitting accuracy and to reduce the computational time, we also set Hb to be completely oxygenated (i.e., we only include the absorption coefficient of oxyHb ∈HbO 2 ), because the Hb solution was exposed to air. Fig. 5(b) shows that the Hb content map obtained from the conventional algorithm depicts the location of the embedded vessel, as similar as our algorithm. Both the Hb content maps have similar concentration distributions. Therefore, this validation supports the idea that our absorption spectral analysis is an easy and effective method to map the Hb content for a large data size. To further demonstrate that a blood vessel can be clearly visualized through the entire skin, we used a patch of mouse dorsal skin in the vessel phantom experiment. Although the vessel is visible through the skin in the white light image [see Fig. 6(a)], there is no quantitative information about the Hb content. The Hb content map [see Fig. 6(b)] generated by our algorithm enhances the image contrast of the phantom blood vessel and clearly depicts the vessel underneath the skin, thus providing a quantitative assessment of Hb content.
XU et al.: BACK-DIRECTIONAL GATED SPECTROSCOPIC IMAGING FOR DIFFUSE LIGHT SUPPRESSION IN HIGH ANISOTROPIC MEDIA
Fig. 7. Images of the SCID mice with human melanoma xenografts. Images of each row are from the same SCID mouse. (a) White light images of human melanoma assays in the SCID mice obtained from our imaging platform. (b) Corresponding microvascular Hb content images generated from our absorption spectral analysis.
D. Pilot Animal Studies To further test microvascular imaging system, we used xenograft assays in SCID mice (see Fig. 7) and athymic nude mice (see Fig. 8) and implanted ∼5 × 106 human melanoma cells (SK-MEL-5) subcutaneously in the upper back region of the mice. We imaged the SCID mice and athymic nude mice 8 weeks and 6–7 weeks after the subcutaneous tumor cell implantation, respectively. In Figs. 7 and 8, white light images (left panels) show the locations of the melanoma xenografts, while microvascular Hb images (right panels) show physical maps of subcutaneous microvascular Hb content through the mouse skin. Overall, our microvascular images reveal that the spatial extents of microvascular Hb content are significantly larger than the tumor sizes that can be estimated from routine visual examination. Interestingly, although the microvascular images show highly elevated in microvascular blood content on the tumor implantation as expected, tumor microvasculature is extremely heterogeneous. Given that microvascular alterations are indispensable participants in tumor growth, our detailed Hb images can be used to investigate the exact spatial extent of this critical tissue process. V. DISCUSSION Our imaging approach can potentially compromise two typical hyperspectral imaging methods to image relatively large tissue areas: 1) full-field illumination and 2) probe scanning [28], [29]. In the full-field illumination approach, light scattered from tissue is collected after its 3-D propagation within the tissue, which in turn generates crosstalk among adjacent pixels. As
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Fig. 8. Images of the athymic nude mice with human melanoma xenografts. Images of each row are from the same nude mouse. (a) White light images of human melanoma assays in the athymic nude mice obtained from our imaging platform. (b) Corresponding microvascular Hb images generated from our absorption spectral analysis.
a result, local optical properties can be averaged out. Although raster scanning of a probe can cover a large area and avoid the crosstalk between each location, its large individual sampling size (∼1 mm) does not allow imaging detailed alterations. In addition, different illumination-collection geometry of the fiberoptic probe can render the disparity of the spectral line shape between full-illumination and probe scanning methods [30]. On the other hand, in our imaging platform, back-directional gating allows the high anisotropic property of tissue to serve as the waveguide to exclude a significant amount of diffuse light. Therefore, simple back-directional gating offers reduced crosstalk among adjacent pixels, taking advantage of the intrinsic property of biological tissue. In addition, a small aperture in back-directional gating yields a large depth of field, and subsequently, improves the image quality over a relatively large area, which is indispensable for imaging an uneven surface, such as xenograft animal models. Given that the implementation of back-directional gating is straightforward, we expect that this concept can be applied to other full-field optical imaging modalities. In our imaging approach, the spectral algorithms in the previous spectroscopic technologies would not be appropriate, because approximately 60 000 spectral analyses are required to generate one spectroscopic image. The conventional modelbased spectral analyses (e.g., point measurements) are typically performed using high SNR spectral signals that are recorded over a relatively large volume. In this case, the SNR of spectral signals is high. However, our spectral signals are relatively
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noisy, because our detection volume at each (x, y) location is relatively small. To overcome this limitation, our absorption spectral analysis uses a large spectral span and a broadband absorption band to quantify the absorption content, and thus, it is less sensitive to spectral noise resulting from the relatively small detection volume. For example, in our vessel phantom experiments, the Hb content map generated by the conventional spectral analysis shows a distorted outline of the phantom vessel [see Fig. 5(b)], while our spectral analysis shows the actual straight profile of the vessel [see Fig. 5(a)]. Although our spectral analysis is slightly affected by the optical properties of the tissue within a typical range of the scattering properties, it can provide a relatively accurate spatial extent of Hb content over a relatively large area with a known level of the error. The precision of our spectral analysis at a low level of Hb concentration is high, which would be beneficial for accurate detection of microvascular alterations during early carcinogenesis. More importantly, compared to the conventional model-based algorithm, our absorption spectral analysis offers a significantly fast processing time for a large 3-D dataset. With our 3-D dataset (e.g., ∼250 × 250 × 250 in double precision floatingpoint format), our absorption spectral analysis requires less than 2 min using MATLAB (version 7.8 64-bit, the Mathworks) on a Sun Ultra 27 workstation (MS Windows XP Professional x64 Edition, Quad-Core Intel Xeon W3570 Processor 3.2 GHz, and 12 GB RAM), while the conventional spectral analysis requires nearly 3 h. A limitation of our pilot animal study is that we did not compare our microvascular images with images from other optical imaging modalities, in part, because our imaging system intends to fill the gap between microscopic imaging and whole-body small-animal imaging. Another limitation in our visualization of microvascular Hb content is that the localized Hb content is averaged over the bulk volume. To overcome this limitation, polarization-sensitive illumination and detection could be used to have enhanced depth-selectivity [8], [31], [32]. For example, in our imaging platform, cross-polarized detection could potentially target the subcutaneous depth of the mice. VI. CONCLUSION We have developed a large-area spectroscopic imaging platform to quantify subcutaneous microvascular Hb concentration through high anisotropic scattering media, such as the mouse skin. The main characteristics of our imaging methodology include 1) diffuse light suppression by back-directional gating using the intrinsic property of highly anisotropic biological tissue; 2) a simple absorption spectral analysis for instantaneous imaging of microvascular Hb content in a relatively large tissue; and 3) the combination of back-directional gating and the spectral analyses for improving imaging resolution, contrast, and depth. We have demonstrated the feasibility of our imaging platform to rapidly map subcutaneous microvascular Hb content of xenografts of human tumors in the athymic nude mice and the SCID mice. Our imaging approach has potential to be used for evaluating the spatial and temporal extents of microvascular alterations, thus offering a representative assessment for
angiogenesis for anticancer drug development and evaluation. Indeed, our simple, but effective, imaging platform can facilitate widespread utilization of optical techniques to quantify microvascular abnormalities in preclinical settings. In addition, back-directional gating can be implemented into other full-field optical imaging modalities, such as whole-body fluorescence imaging. REFERENCES [1] I. Georgakoudi and J. Van Dam, “Characterization of dysplastic tissue morphology and biochemistry in Barrett’s esophagus using diffuse reflectance and light scattering spectroscopy,” Gastrointest. Endosc. Clin. N. Amer., vol. 13, pp. 297–308, 2003. [2] R. Reif, M. Wang, S. Loshi, O. A’Amar, and I. J. Bigio, “Optical method for real-time monitoring of drug concentrations facilitates the development of novel methods for drug delivery to brain tissue,” J. Biomed. Opt., vol. 12, pp. 034036-1–034036-5, May/Jun. 2007. [3] J. Q. Brown, L. G. Wilke, J. Geradts, S. A. Kennedy, G. M. Palmer, and N. Ramanujam, “Quantitative optical spectroscopy: A robust tool for direct measurement of breast cancer vascular oxygenation and total hemoglobin content in vivo,” Cancer Res., vol. 69, pp. 2919–2926, Apr. 2009. [4] C. Lau, O. Scepanovic, J. Mirkovic, S. Mcgee, C. C. Yu, S. Fulghum, M. Wallace, J. Tunnell, K. Bechtel, and M. Feld, “Re-evaluation of modelbased light-scattering spectroscopy for tissue spectroscopy,” J. Biomed. Opt., vol. 14, pp. 024031-1–024031-9, Mar./Apr. 2009. [5] J. C. Finlay and T. H. Foster, “Effect of pigment packaging on diffuse reflectance spectroscopy of samples containing red blood cells,” Opt. Lett., vol. 29, pp. 965–967, May 2004. [6] J. R. Mourant, T. M. Powers, T. J. Bocklage, H. M. Greene, M. H. Dorin, A. G. Waxman, M. M. Zsemlye, and H. O. Smith, “In vivo light scattering for the detection of cancerous and precancerous lesions of the cervix,” Appl. Opt., vol. 48, pp. D26–D35, Apr. 2009. [7] J. R. Mourant, T. J. Bocklage, T. M. Powers, H. M. Greene, K. L. Bullock, L. R. Marr-Lyon, M. H. Dorin, A. G. Waxman, M. M. Zsemlye, and H. O. Smith, “In vivo light scattering measurements for detection of precancerous conditions of the cervix,” Gynecol. Oncol., vol. 105, pp. 439–445, May 2007. [8] M. P. Siegel, Y. L. Kim, H. K. Roy, R. K. Wali, and V. Backman, “Assessment of blood supply in superficial tissue by polarization-gated elastic light-scattering spectroscopy,” Appl. Opt., vol. 45, pp. 335–342, 2006. [9] R. K. Jain, L. L. Munn, and D. Fukumura, “Dissecting tumour pathophysiology using intravital microscopy,” Nat. Rev. Cancer, vol. 2, pp. 266–276, Apr. 2002. [10] W. Groner, J. W. Winkelman, A. G. Harris, C. Ince, G. J. Bouma, K. Messmer, and R. G. Nadeau, “Orthogonal polarization spectral imaging: A new method for study of the microcirculation,” Nat. Med., vol. 5, pp. 1209–1213, Oct. 1999. [11] A. K. Murray, A. L. Herrick, and T. A. King, “Laser Doppler imaging: A developing technique for application in the rheumatic diseases,” Rheumatol. (Oxford), vol. 43, pp. 1210–1218, Oct. 2004. [12] B. Choi, N. M. Kang, and J. S. Nelson, “Laser speckle imaging for monitoring blood flow dynamics in the in vivo rodent dorsal skin fold model,” Microvasc. Res., vol. 68, pp. 143–146, Sep. 2004. [13] A. K. Dunn, T. Bolay, M. A. Moskowitz, and D. A. Boas, “Dynamic imaging of cerebral blood flow using laser speckle,” J. Cereb. Blood Flow Metab., vol. 21, pp. 195–201, Mar. 2001. [14] M. A. Choma, A. K. Ellerbee, S. Yazdanfar, and J. A. Izatt, “Doppler flow imaging of cytoplasmic streaming using spectral domain phase microscopy,” J. Biomed. Opt., vol. 11, pp. 024014-1–024014-8, Mar./Apr. 2006. [15] Y. C. Ahn, W. Jung, and Z. Chen, “Quantification of a three-dimensional velocity vector using spectral-domain Doppler optical coherence tomography,” Opt. Lett., vol. 32, pp. 1587–1589, Jun. 2007. [16] A. Vogel, V. V. Chernomordik, J. D. Riley, M. Hassan, F. Amyot, B. Dasgeb, S. G. Demos, R. Pursley, R. F. Little, R. Yarchoan, Y. Tao, and A. H. Gandjbakhche, “Using noninvasive multispectral imaging to quantitatively assess tissue vasculature,” J. Biomed. Opt., vol. 12, pp. 0516041–051604-13, Sep./Oct. 2007. [17] L. V. Wang, “Tutorial on photoacoustic microscopy and computed tomography,” IEEE J. Sel. Topics Quantum Electron., vol. 14, no. 1, pp. 171–179, Jan./Feb. 2008.
XU et al.: BACK-DIRECTIONAL GATED SPECTROSCOPIC IMAGING FOR DIFFUSE LIGHT SUPPRESSION IN HIGH ANISOTROPIC MEDIA
[18] E. A. Sausville and A. M. Burger, “Contributions of human tumor xenografts to anticancer drug development,” Cancer Res., vol. 66, pp. 3351–3354, Apr. 2006. [19] L. Azzi, M. El-Alfy, C. Martel, and F. Labrie, “Gender differences in mouse skin morphology and specific effects of sex steroids and dehydroepiandrosterone,” J. Invest. Dermatol., vol. 124, pp. 22–27, Jan. 2005. [20] Z. Xu, J. Liu, and Y. L. Kim, “Diffuse light suppression of back-directional gating imaging in high anisotropic media,” J. Biomed. Opt., vol. 14, pp. 030510-1–030510-3, 2009. [21] W. F. Cheong, S. A. Prahl, and A. J. Welch, “A review of the optical properties of biological tissues,” IEEE J. Quantum Electron., vol. 26, no. 12, pp. 2166–2185, Dec. 1990. [22] L. Wang, P. P. Ho, C. Liu, G. Zhang, and R. R. Alfano, “Ballistic 2-D imaging through scattering walls using an ultrafast optical Kerr gate,” Science, vol. 253, pp. 769–771, 1991. [23] A. P. Tzannes and J. M. Mooney, “Measurement of the modulation transfer-function of infrared cameras,” Opt. Eng., vol. 34, pp. 1808–1817, Jun. 1995. [24] M. Hunter, V. Backman, G. Popescu, M. Kalashnikov, C. W. Boone, A. Wax, V. Gopal, K. Badizadegan, G. D. Stoner, and M. S. Feld, “Tissue self-affinity and polarized light scattering in the Born approximation: A new model for precancer detection,” Phys. Rev. Lett., vol. 97, pp. 1381021–138102-4, 2006. [25] A. Amelink, D. J. Robinson, and H. J. C. M. Sterenborg, “Confidence intervals on fit parameters derived from optical reflectance spectroscopy measurements,” J. Biomed. Opt., vol. 13, pp. 054044-1–054044-14, Sep./Oct. 2008. [26] Y. L. Kim, Y. Liu, R. K. Wali, H. K. Roy, M. J. Goldberg, A. K. Kromin, K. Chen, and V. Backman, “Simultaneous measurement of angular and spectral properties of light scattering for characterization of tissue microarchitecture and its alteration in early precancer,” IEEE J. Sel. Topics Quantum Electron., vol. 9, no. 2, pp. 243–256, Mar./Apr. 2003. [27] S. Ravikant, L. J. Steven, and C. Paul, “Optical properties of mutant versus wild-type mouse skin measured by reflectance-mode confocal scanning laser microscopy (rCSLM),” J. Biomed. Opt., vol. 13, pp. 041309-1– 041309-7, 2008. [28] T. Vo-Dinh, D. L. Stokes, M. B. Wabuyele, M. E. Martin, J. M. Song, R. Jagannathan, E. Michaud, R. J. Lee, and X. G. Pan, “A hyperspectral imaging system for in vivo optical diagnosis,” IEEE Eng. Med. Biol. Mag., vol. 23, no. 5, pp. 40–49, Sep./Oct. 2004. [29] C. C. Yu, C. Lau, G. O’Donoghue, J. Mirkovic, S. McGee, L. Galindo, A. Elackattu, E. Stier, G. Grillone, K. Badizadegan, R. R. Dasari, and M. S. Feld, “Quantitative spectroscopic imaging for non-invasive early cancer detection,” Opt. Exp., vol. 16, pp. 16227–16239, Sep. 2008. [30] S. C. Gebhart, S. K. Majumder, and A. Mahadevan-Jansen, “Comparison of spectral variation from spectroscopy to spectral imaging,” Appl. Opt., vol. 46, pp. 1343–1360, Mar. 2007. [31] Y. Liu, Y. L. Kim, X. Li, and V. Backman, “Investigation of depth selectivity of polarization gating for tissue characterization,” Opt. Exp., vol. 13, pp. 601–611, Jan. 2005. [32] V. M. Turzhitsky, A. J. Gomes, Y. L. Kim, Y. Liu, A. Kromine, J. D. Rogers, M. Jameel, H. K. Roy, and V. Backman, “Measuring mucosal blood supply in vivo with a polarization-gating probe,” Appl. Opt., vol. 47, pp. 6046– 6057, Nov. 2008.
Zhengbin Xu received the B.S. degree in electronics engineering from Peking University, Beijing, China, in 2007. He is currently working toward the Ph.D. degree with the Weldon School of Biomedical Engineering, Purdue University, West Lafayette, IN. His research interests include quantifying the biochemical compositions in biological tissue and characterizing living tissue for histopathological and surgical guidance using spectroscopic technologies.
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Jingjing Liu received the B.S. degree in biomedical engineering from Tianjin University, Tianjin, China. She is currently with the Weldon School of Biomedical Engineering, Purdue University, West Lafayette, IN, where she is engaged in low-coherenceenhanced backscattering and low-coherence interferometry for histopathological guidance of preclinical studies.
Dae Ho Hong received the B.S. degree from the School of Electrical and Computer Engineering, Purdue University, West Lafayette, IN, in 2009. He is currently working toward the Ph.D. degree in biomaterials with the University of Pittsburgh, Pittsburgh, PA. His current research interest is on biodegradable Mg-Ca alloy and non-viral gene delivery using nano-structured calcium phosphates (NanoCaPs).
Viet Quoc Nguyen is currently a Senior undergraduate student in biomedical optics with the Weldon School of Biomedical Engineering, Purdue University, West Lafayette, IN. His research interests include clinical investigation, human physiology, and medical imaging.
Mi Ran Kim received the M.S. degree in pathology from Seoul National University, Seoul, South Korea, in 2000. She is currently a Postdoctoral Research Associate with School of Veterinary Medicine, Purdue University, West Lafayette, IN. Her research interests include identification of new cancer biomarkers using RNA microarray and protein finger printing, development of anticancer drug, cell proliferation assay, and in vivo experiments with new potential anticancer candidates.
Sulma I. Mohammed received the Ph.D. degree in microbiology from Purdue University, West Lafayette, IN, in 1991. She is currently an Associate Professor of cancer biology with Purdue University, where she was the Director with Purdue Drug Discovery Shared Resource. Her research interests include identification of specific and sensitive biomarkers for early detection of cancer, using laser capture microdissection, proteomics, and nanotechnologies, and developing protein biomarkers for early detection and as targets for prevention.
Young L. Kim received the Ph.D. degree in biomedical engineering and the M.S. degree in clinical investigation from Northwestern University, Evanston, IL, in 2005 and 2007, respectively. Since 2007, he has been an Assistant Professor with the Weldon School of Biomedical Engineering, Purdue University, West Lafayette, IN. His research interests include understanding light propagation in biological tissue, developing novel biophotonics technologies for the quantification of physiological conditions and diseases such as cancer, and further translating promising technologies to clinical settings and epidemiologic studies.