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Virtual Journal for Biomedical Optics

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  • Editors: Andrew Dunn and Anthony Durkin
  • Vol. 8, Iss. 3 — Apr. 4, 2013
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Combination of spectral and fluorescence imaging microscopy for wide-field in vivo analysis of microvessel blood supply and oxygenation

Jennifer A. Lee, Raymond T. Kozikowski, and Brian S. Sorg  »View Author Affiliations


Optics Letters, Vol. 38, Issue 3, pp. 332-334 (2013)
http://dx.doi.org/10.1364/OL.38.000332


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Abstract

Hyperspectral imaging of hemoglobin (Hb) saturation and first-pass fluorescence imaging of blood transit time were combined to analyze the oxygenation of and blood flow through microvessel networks. The combination imaging technique was demonstrated in a mouse dorsal window chamber model of a growing Caki-2 human renal cell carcinoma over time. Data from Hb saturation and blood supply time maps show the formation of arteriovenous malformations and shunting of blood directly from arteries to the tumor core and into veins in the periphery of the tumor. Images and data analysis show these malformations result in an oxygenated environment ideal for a tumor to proliferate.

© 2013 Optical Society of America

Abnormal microvasculature and angiogenesis are characteristics of a wide variety of pathologies, such as diabetes, hypertension, and tumors. In many instances, alteration of the function and morphology of microvessels can lead to the propagation of these diseases [1

1. P. Carmeliet, J. Intern. Med. 255, 538 (2004). [CrossRef]

]. As new treatments targeting pathological microvasculature and angiogenesis are developed, it is of greater importance to utilize small animal models to analyze the relationship between vessel morphology, blood flow, and oxygenation.

Currently there are a variety of methods for the analysis of tumor microvasculature in small animal models [2

2. S. Dufort, L. Sancey, C. Wenk, V. Josserand, and J. L. Coll, Biochim. Biophys. Acta 1798, 2266 (2010). [CrossRef]

]. We present the combination of two wide-field imaging techniques, hyperspectral imaging of hemoglobin (Hb) saturation and first-pass fluorescence (FPF) imaging of blood transit time, to simultaneously characterize the oxygenation of and blood flow through microvessel networks. This combination of imaging techniques enables a unique analysis of oxygen transport in microvessels that highlights the effects of microvessel network connections on oxygen transport. Using a murine dorsal window chamber model, both techniques are easily implemented and repeatable over a period of several days, allowing for serial observations in the same animal model. Hb saturation imaging provides information regarding the oxygenation of blood within the microvessels and is useful on its own for analysis of microvascular pathologies [3

3. M. Wankhede, C. Dedeugd, D. W. Siemann, and B. S. Sorg, Oncol. Rep. 23, 685 (2010). [CrossRef]

]. FPF imaging involves recording the flow of a fluorescent contrast agent as it is injected into the circulation. Imaging the appearance of the agent in the microcirculation gives information regarding blood flow, morphology of microvessels, and network connections through measurement of the blood supply time (BST) [4

4. K. S. Oye, G. Gulati, B. A. Graff, J. V. Gaustad, K. G. Brurberg, and E. K. Rofstad, Microvasc. Res. 75, 179(2008). [CrossRef]

]. This parameter indicates the time it takes for blood to travel to individual microvessels in a network from a common reference supplying artery (SA).

We illustrate the combined imaging techniques in a mouse dorsal skinfold window chamber model of tumor development [5

5. B. S. Sorg, B. J. Moeller, O. Donovan, Y. Cao, and M. W. Dewhirst, J. Biomed. Opt. 10, 044004 (2005). [CrossRef]

]. During surgery, 7.5×103 Caki-2 human renal cell carcinoma cells in phosphate buffered saline were injected subcutaneously in each window to produce a tumor of 3–4 mm diameter in 5–7 days. Hyperspectral imaging of the tumor area was performed first and immediately followed by FPF imaging.

Hb saturation of tumor microvasculature was described in detail previously [3

3. M. Wankhede, C. Dedeugd, D. W. Siemann, and B. S. Sorg, Oncol. Rep. 23, 685 (2010). [CrossRef]

,5

5. B. S. Sorg, B. J. Moeller, O. Donovan, Y. Cao, and M. W. Dewhirst, J. Biomed. Opt. 10, 044004 (2005). [CrossRef]

]. Briefly, a 100 W tungsten halogen lamp was used for transillumination of the window chamber. A liquid-crystal tunable filter (CRI, Cambridge, Massachusetts) with a 400–720 nm transmission range was placed in front of a monochromatic scientific grade CCD camera (DVC Company, Austin, Texas) to acquire spectral image data sets from 500 to 575 nm at 5 nm intervals. Hb saturation imaging was calibrated using freshly harvested pure oxyhemoglobin and deoxyhemoglobin as described previously [5

5. B. S. Sorg, B. J. Moeller, O. Donovan, Y. Cao, and M. W. Dewhirst, J. Biomed. Opt. 10, 044004 (2005). [CrossRef]

].

Fluorescent liposomes were used as the contrast agent for FPF imaging. Liposomes were prepared using the lipid hydration method from a mixture of 1,2-dioleoyl-sn-glycero-3-phosphocholine, 1,2-dioleoyl-sn-glycero-3-phospho-L-serine, 1,2-distearoyl-sn-glycero-3-phosphoethanolamine-N-[methoxy(polyethyleneglycol)-2000], and cholesterol combined at a molar ratio of 47.4:19.7:1:39.7 [6

6. A. D. Bangham, M. M. Standish, and J. C. Watkens, J. Mol. Biol. 13, 238 (1965). [CrossRef]

]. Liposomes were fluorescently labeled with dye in ethanol (2 mM) added to between 0.5 and 1 mol. % of the total phospholipid content. Unilamellar liposomes 100nm in diameter were obtained by repeated extrusion of vesicles through a nucleopore membrane (100 nm pore size).

In order to combine the fluorescence imaging with spectral imaging of Hb absorption, near-IR fluorescent carbocyanine dyes 1,1'-dioctadecyl-3,3,3',3'-tetramethylindodicarbocyanine 4-chlorobenzenesulfonate (DiD; ex644nm/em665nm) and 1,1'-dioctadecyl-3,3,3',3'-tetramethylindotricarbocyanine iodide (DiR; ex750nm/em780nm), were utilized to avoid interference with the absorption range of Hb used. Because of the porous nature of tumor microvasculature, clearance of extravasated dye from the tumor tissue can be a problem when imaging on consecutive days, thus the use of DiD and DiR were alternated to allow for 48 h of respective liposome clearance between imaging sessions.

Following Hb saturation imaging, 50μl of liposomes was administered via tail vein injection for FPF imaging. Seven hundred stacked TIFF images were acquired during liposome injection at a frame exposure time of 0.117 s to capture the transit of liposomes throughout the entire vascular network. Fluorescence images were acquired using an Andor iXon electron multiplying CCD camera. Cyanine 5 (Cy5, ex 640±20nm/em680±30nm; Chroma Technology Corp., Rockingham, Vermont) and cyanine 5 (Cy 7, ex 740± 35 nm/em 795 ±50nm; Chroma Technology Corp., Rockingham, Vermont) filters were used to capture fluorescence from the DiD and DiR labeled liposomes, respectively.

Image processing was performed using MATLAB (MathWorks, Inc., Natick, Massachusetts) and MeVisLab (MeVis Medical Solutions AG, Bremen, Germany). A vascular mask was created for each image stack in MeVisLab using thresholding, Gaussian smoothing, Hessian vesselness and fuzzy c-means algorithms. In MATLAB, each image stack was truncated to the frame at which liposomes first entered the field of view and the frame at which the liposomes completely filled the microvasculature. To create a BST map, every pixel in the vascular mask was designated a BST based on its fluorescence intensity profile over time. The value was determined as the time at which the pixel intensity reached the average of its minimum and maximum value. Vessels that were more rapidly filled with liposomes registered faster BSTs, and vessels that filled with liposomes last had slower BSTs.

Figure 1 shows bright-field images [Fig. 1(a)], Hb saturation [Fig. 1(b)], and BST maps [Fig. 1(c)] of a Caki-2 tumor over 4 days. The Hb saturation maps give microvessel oxygenation data but no information about the behavior of the blood flow. The addition of BST analysis elucidates the direction of blood flow and blood transit time in the tumor, which complements the oxygenation data. Normal, unaffected vessels surrounding the tumor on Day 1 exhibit expected oxygenation and blood flow, with highly oxygenated vessels (i.e., arteries) corresponding to faster BSTs and lower oxygenated vessels (i.e., veins) having slower BSTs. From the BST maps we can see that highly oxygenated vessels of the tumor core have fast BSTs, indicating these vessels are quickly filled with blood from the adjacent SA. These vessels contain arteriovenous (AV) shunts that deliver blood directly from arteries into veins, resulting in a variability of oxygenation and BSTs in the tumor periphery as blood from the systemic flow [arrow head symbol in lower left of (b)] and tumor [arrow symbol in lower left of (b)] converge into the same vein. As the tumor grows and angiogenesis continues, there is evidence of heterogeneity in oxygenation and BST throughout the tumor represented by color changes in the maps.

Fig. 1. Analysis of a Caki-2 tumor over 4 days. (a) Bright-field images. The supplying artery (SA) and draining vein (DV) of interest are indicated. (b) Full Hb saturation and (c) BST maps with magnified region of interest indicate the development of AV malformations. Venous branches carrying blood from systemic flow [arrowhead symbol in lower left of (b)] and shunted tumor blood flow [arrow symbol in lower left of (b)] are indicated.

General observations have been made concerning the formation of new pathological connections; however, their effect on the tumor microenvironment has not been heavily researched [7

7. S. O. Park, M. Wankhede, Y. J. Lee, S. Choe, S. Oh, G. Walter, M. K. Raizada, B. S. Sorg, and S. P. Oh, J. Clin. Invest. 119, 3487 (2009). [CrossRef]

]. Magnified regions of interest in Figs. 1(b) and 1(c) illustrate the utility of using this combination imaging method to analyze AV formations with great detail. Day 1 maps show the left venous branch [arrowhead symbol in lower left of (b)] carries blood from the systemic flow, while the right branch [arrow symbol in lower left of (b)] is supplied with blood via shunts from the tumor. Because of this, the blood from the systemic flow arrives much more slowly compared to the blood flow from the tumor. By Day 4, the tumor has grown such that the newly formed vessels are shunting enough blood to both branches of the draining vein (DV), decreasing the BST and increasing the overall oxygenation of the network with respect to Day 1.

Figure 2 demonstrates region of interest (ROI) analysis for the vascular network seen in Fig. 2(a). Figure 2(b) shows the mean Hb saturation versus mean BST for each ROI from Fig. 2(a) over time. Both the ranges of Hb saturation and BST shortened over time. Day 4 showed the most dramatic change in which the Hb saturation and BST range were both greatly reduced. The overall values of Hb saturation increased and BST values decreased over time with the growing tumor as seen in Fig. 2(c) with ROIs 6, 7, and 8. ROIs 6 and 7 are two sides of the same DV, while ROI 8 represents the entire width of the vein downstream. ROIs 6 and 7 represent flows that come from the systemic flow and tumor as previously shown in Fig. 1. ROI 6 shows the most dramatic changes in BST and Hb saturation as the blood flow originates from the systemic flow and is slowly altered as more AV shunts are formed.

Fig. 2. (a) ROIs chosen for comparison of BST and Hb saturation. (b) Hb saturation versus BST over time (mean ± standard deviation) for ROIs seen in (a). (c) Comparison of mean values of BST and Hb saturation for ROIs 6, 7, and 8 over time (mean ± standard deviation).

This work was supported in part by a grant from the Bankhead-Coley Cancer Research Program, Florida Department of Health.

References

1.

P. Carmeliet, J. Intern. Med. 255, 538 (2004). [CrossRef]

2.

S. Dufort, L. Sancey, C. Wenk, V. Josserand, and J. L. Coll, Biochim. Biophys. Acta 1798, 2266 (2010). [CrossRef]

3.

M. Wankhede, C. Dedeugd, D. W. Siemann, and B. S. Sorg, Oncol. Rep. 23, 685 (2010). [CrossRef]

4.

K. S. Oye, G. Gulati, B. A. Graff, J. V. Gaustad, K. G. Brurberg, and E. K. Rofstad, Microvasc. Res. 75, 179(2008). [CrossRef]

5.

B. S. Sorg, B. J. Moeller, O. Donovan, Y. Cao, and M. W. Dewhirst, J. Biomed. Opt. 10, 044004 (2005). [CrossRef]

6.

A. D. Bangham, M. M. Standish, and J. C. Watkens, J. Mol. Biol. 13, 238 (1965). [CrossRef]

7.

S. O. Park, M. Wankhede, Y. J. Lee, S. Choe, S. Oh, G. Walter, M. K. Raizada, B. S. Sorg, and S. P. Oh, J. Clin. Invest. 119, 3487 (2009). [CrossRef]

OCIS Codes
(170.0110) Medical optics and biotechnology : Imaging systems
(170.3880) Medical optics and biotechnology : Medical and biological imaging
(180.2520) Microscopy : Fluorescence microscopy
(300.6280) Spectroscopy : Spectroscopy, fluorescence and luminescence

ToC Category:
Medical Optics and Biotechnology

History
Original Manuscript: November 16, 2012
Revised Manuscript: December 19, 2012
Manuscript Accepted: December 28, 2012
Published: January 28, 2013

Virtual Issues
Vol. 8, Iss. 3 Virtual Journal for Biomedical Optics
January 28, 2013 Spotlight on Optics

Citation
Jennifer A. Lee, Raymond T. Kozikowski, and Brian S. Sorg, "Combination of spectral and fluorescence imaging microscopy for wide-field in vivo analysis of microvessel blood supply and oxygenation," Opt. Lett. 38, 332-334 (2013)
http://www.opticsinfobase.org/vjbo/abstract.cfm?URI=ol-38-3-332


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References

  1. P. Carmeliet, J. Intern. Med. 255, 538 (2004). [CrossRef]
  2. S. Dufort, L. Sancey, C. Wenk, V. Josserand, and J. L. Coll, Biochim. Biophys. Acta 1798, 2266 (2010). [CrossRef]
  3. M. Wankhede, C. Dedeugd, D. W. Siemann, and B. S. Sorg, Oncol. Rep. 23, 685 (2010). [CrossRef]
  4. K. S. Oye, G. Gulati, B. A. Graff, J. V. Gaustad, K. G. Brurberg, and E. K. Rofstad, Microvasc. Res. 75, 179(2008). [CrossRef]
  5. B. S. Sorg, B. J. Moeller, O. Donovan, Y. Cao, and M. W. Dewhirst, J. Biomed. Opt. 10, 044004 (2005). [CrossRef]
  6. A. D. Bangham, M. M. Standish, and J. C. Watkens, J. Mol. Biol. 13, 238 (1965). [CrossRef]
  7. S. O. Park, M. Wankhede, Y. J. Lee, S. Choe, S. Oh, G. Walter, M. K. Raizada, B. S. Sorg, and S. P. Oh, J. Clin. Invest. 119, 3487 (2009). [CrossRef]

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