Open Access
1 May 2009 In-vivo Fourier domain optical coherence tomography as a new tool for investigation of vasodynamics in the mouse model
Sven Meissner, Gregor Müller, Julia Walther, Henning Morawietz, Edmund Koch
Author Affiliations +
Abstract
In-vivo imaging of the vascular system can provide novel insight into the dynamics of vasoconstriction and vasodilation. Fourier domain optical coherence tomography (FD-OCT) is an optical, noncontact imaging technique based on interferometry of short-coherent near-infrared light with axial resolution of less than 10 μm. In this study, we apply FD-OCT as an in-vivo imaging technique to investigate blood vessels in their anatomical context using temporally resolved image stacks. Our chosen model system is the murine saphenous artery and vein, due to their small inner vessel diameters, sensitive response to vasoactive stimuli, and advantageous anatomical position. The vascular function of male wild-type mice (C57BL/6) is determined at the ages of 6 and 20 weeks. Vasoconstriction is analyzed in response to dermal application of potassium (K+), and vasodilation in response to sodium nitroprusside (SNP). Vasodynamics are quantified from time series (75 sec, 4 frames per sec, 330×512 pixels per frame) of cross sectional images that are analyzed by semiautomated image processing software. The morphology of the saphenous artery and vein is determined by 3-D image stacks of 512×512×512 pixels. Using the FD-OCT technique, we are able to demonstrate age-dependent differences in vascular function and vasodynamics.

1.

Introduction

Cardiovascular disease is the major cause of death in the industrialized world.1 Cardiovascular risk factors and inflammation can ultimately lead to life-threatening complications2, 3, 4 by contributing to endothelial dysfunction and atherosclerotic plaque formation on vessel walls.5, 6 Impaired vasodynamics is considered to be a symptom of early atherosclerotic changes in the vessel wall. Such changes limit the response to vasoactive stimuli and increase vascular stiffness.7 Current vasodynamic studies are mainly performed by isometric force measurement of isolated vessels in organ chambers. This approach provides information about different parameters, e.g., concentration-response curves of pharmacological interventions, but only in the ex-vivo situation. To better understand the pathogenesis of atherosclerosis, in-vivo measurement of vasodynamics would be a useful diagnostic tool.

In-vivo measurement of vasodynamics is not well established for small vessels, because imaging techniques are limited by the high resolution needed. Current commercial ultrasound technology only provides a resolution of about 50μm , which does not allow imaging of structures approximately 100μm in diameter. Optical coherence tomography (OCT)8 could be a suitable novel technique to measure vasodynamics in small vessels in vivo due to its contactless imaging and superior resolution of less than 10μm . This high resolution of OCT facilitates the generation of 2-D cross sections and 3-D tomograms of subsurface tissue. Recently, intravascular catheter OCT has been used to characterize atherosclerotic plaque formation in human vessels.9 However, due to the large diameter of the catheters, this technique is not applicable to the small vessels in mouse models.

Here, we describe a novel in-vivo approach that allows high-speed transluminal studies of impaired vasodynamics in the mouse at early stages of atherosclerosis, before visible plaque formation. Transluminal imaging of the vessels has the advantage of avoiding microtraumata in the endothelium. Additionally, compared to established ex-vivo methods, our approach allows the vessels to remain in their proper anatomical and physiological context with continuous blood flow, blood pressure, and innervation.10

2.

Methods and Materials

2.1.

Experimental Setup

A Fourier domain OCT (FD-OCT)11 system was developed with a center wavelength of 840nm , a spectral width (FWHM) of 45nm , and an optical power of 1mW . A broadband superluminescent diode (SLD) served as the light source. Light was transmitted by a fiber coupler to the scanner head (Fig. 1 ), in which the light was collimated into a free-space beam of 2.4mm in diameter (1e2) and divided by a beamsplitter cube into a reference and a sample beam. The sample beam was deflected by two galvanometer scanners in the x and y direction. Deflected light was focused onto the sample by an achromatic lens (L2) with a focal length of 25.4mm and a diameter of 15mm . Because of the much larger diameter of L2 compared to the sample beam diameter, the effective NA of 0.05 of the objective is determined by the focal length of the collimator, the NA of the fiber, and the focal length of L2. Backscattered light from the probe was superimposed with the reference beam and again coupled into the single-mode fiber. Interfered light was coupled into the spectrometer by a collimator with a focal length of 40mm , and was spectrally resolved by a diffraction grating with 1200linesmm before being focused onto the complimentary metal oxide semiconductor (CMOS) line detector ( 1024pixels , 7.8×125μm ) by an achromatic lens with a 75-mm focal length. This OCT system allows the measurement of complex biological tissue in a range of 2mm , with an axial resolution of 8μm in air ( 6μm in tissue with refractive index n=1.33 ), a lateral resolution of about 7μm , and a scanning rate of 1.2kHz (A-scan rate). Although the measurement range is 2mm , its sensitivity range is limited to a range of 370μm by the Rayleigh length of the sample beam. A schematic of the experimental setup and beam course in the scanner head is shown in Fig. 1. The camera, which is coupled by a dichroic mirror, allowed orientation on the sample surface, and can be used with additional optics for microscopy. Optimal position in relation to the sample was achieved by mounting the scanner head on a three-axis translation stage.

Fig. 1

Experimental setup to investigate in-vivo vasodynamics in the mouse model. Near-infrared (NIR) light is transmitted by fiber optics [single mode fiber (SMF)] and coupled by a collimator (C) with a focal length of 12mm into the scanner head (SH). The light beam is divided by a beamsplitter (BS) cube into a reference and sample beam. The sample beam is then deflected by two galvanometer scanners ( xy GU) into x and y directions for plane scanning of the sample. The sample beam is focused on the sample by an achromatic lens (L2) with a focal length of 25.4mm . The reference light is focused L1 to the reference mirror (RM). Backscattered light from the sample is superposed with the reference light at the beamsplitter cube. This interference signal is transmitted into the spectrometer and spectrally resolved by a diffraction grating (1200linesmm) . The interference spectrum is acquired by a silicon line detector. Using a fast Fourier transformation (FFT), the interference signal is converted into the corresponding depth information. Additionally, in the course of the sample beam, a dichroitic mirror (DM) is inserted for adaptation of a video camera (VC). Further abbreviations: IU is illumination unit for VC; λ is the wavelength; z is the depth; I is the Intensity; and A is log. Amplitude is in decibels.

034027_1_031903jbo1.jpg

2.2.

Mouse Model

All experiments were performed in accordance with the Guide for the Care and Use of Laboratory Animals (Institute of Laboratory Animal Resources, 7th edition, National Academy Press, Washington, D.C., 1996). The study was approved by the governmental animal care and use committee. The murine saphenous artery and vein of the right hind leg in C57BL/6 mice aged 6 or 20weeks was investigated. Anesthesia was delivered by peritoneal application of a mixture of 95% Ketanest (10mgml) and 5% Xylazin (20mgml) using a dose of 10-μlg body weight. Before imaging, the skin covering the saphenous artery was incised and a 5×5-mm2 skin flap was removed to obtain access to the vessel area. Phosphate-buffered saline (PBS) containing 80-mM K+ was used to induce vasoconstriction (VC). Vasodilation (VD) was induced with 1-mM sodium nitroprusside solution (PBS+SNP) . The solutions were applied on the outer vessel wall. During investigation, the mouse was fixed to a temperature-controlled operation table for small rodents.

2.3.

Two-Dimensional Image Acquisition—Vasodynamics

Throughout the image acquisition procedure, the vessel-containing area was covered with buffer (PBS) to prevent the tissue from drying out. To measure vasodynamics, images of the inner vessel diameter were taken at identical lateral positions and recorded by performing B-scans consisting of 300 A-scans. An image acquisition rate of 4 B-scans per second was used. VC and VD were documented by initial 30 B-scans to determine the unaffected vessel diameter. Next, image acquisition was stopped and the buffer was exchanged for a buffer solution containing vasoactive stimuli (VC: PBS+K+ ; VD: PBS+SNP ). Resultant changes in diameter were imaged by additional 300 B-scans. The final values of the inner diameter after VC and VD were determined using the last 50 images (equivalent to the last 12sec of the time-resolved image stack) of the OCT image stack acquired during VC and VD. The time-resolved image stacks of the static and dynamic portion of each stimulus represent a period of approximately 75sec .

2.4.

Three-Dimensional Image Acquisition—Morphology

The investigated area was also mapped by 3-D image stacks (2×2×2mm3) , under control conditions and after completion of VC and VD.

2.5.

Image Quantification

Flowing blood was seen in these OCT images as a specific black shadow, caused by the movement of scattering objects, e.g., blood cells. This movement reduced the interference signal by fringe washout.12, 13 The saphenous artery was seen in OCT images as a black semicircular structure (Figs. 2 and 3 ). The pronounced border between the dark blood and bright vessel wall was used to quantify the inner diameter of the artery. Quantification was carried out using existing algorithms from commercially available software, National Instruments Vision Assistant 8.2.1 (NIV), in combination with National Instruments LabVIEW protocols. In the first B-scan of the time-resolved stack, the user defined the region of interest (ROI), which included the saphenous artery, by a rectangle. The border between the dark lumen and bright vessel wall was detected with NIV routine cycle detection. The protocol was modified to detect the visible semicircular structure representing the saphenous artery lumen. The inner diameter of the semicircle and the coordinates of the center point detected in the first B-scan diameter were used to define the ROI in the following B-scan. The ROI was defined by the user only in the first B-scan. All subsequent B-scans in the time-resolved image stack were analyzed automatically. The detected inner diameters and the corresponding times were saved as spreadsheet files. To characterize the dynamics of inner diameter change in response to vasoactive stimuli, a sigmoid function [Eq. 1] was fitted to the measured dataset of time-dependent inner diameter d(t) . The coefficient Δd describes the total change of inner diameter, t12 the elapsed time for half of inner diameter change, τ the time constant of diameter change, d0 the initial diameter, and “ t ” the time.

Eq. 1

d(t)=Δd[1+exp((tt12)τ)]1+d0.

Fig. 2

(a), (b), and (c) 2-D cross sectional OCT images and (e) and (f) volume rendering illustrations of the investigated area under (a) and (d) control conditions, (b) and (e) VC, and (c) and (f) VD. The saphenous vein (white arrow), the saphenous artery (black arrow), and the nervus vastus medialis (gray arrow) are indicated. Vessel wall thickness wt of the saphenous artery is highlighted by double arrows. The resolution of our OCT system is sufficient to image the lipid-filled vacuoles of perivascular adipocytes (lv).

034027_1_031903jbo2.jpg

Fig. 3

Temporal changes of the inner diameter after induction of vasoconstriction (K+) and vasodilation (SNP). Left side: 2-D cross sectional OCT image taken at resting conditions of saphenous vein (white arrow) and saphenous artery (black arrow). Right: cross sectional images of the acquired time-resolved stacks. The white line in the left image marks the cutting plane through the time-resolved stacks. The temporal resolution of the inner diameter of the saphenous artery and vein are visible as black bands in the right image. After application of K+ , the inner diameter decreases, whereas SNP application enlarges the vessel diameter.

034027_1_031903jbo3.jpg

Vascular function dynamics were characterized by the time to half maximum t12 (inflection point of the fitted function) during VC and VD, and the velocity of inner diameter change at the inflection point. The maximum velocity vmax of VC and VD corresponds to the slope at t=t12 , where the second time derivative of Eq. 1 is null and is given by:

Eq. 2

vmax=Δd4τ.
The wall thickness wt of the saphenous artery and vein was manually quantified using ImageJ software (ImageJ 1.37v). Statistical analysis was carried out with Graph Pad Prism 5 using the unpaired t-test.

3.

Results

3.1.

Morphology

To investigate in-vivo vascular function in small vessels, we chose the murine saphenous artery and vein of the right hind leg because of its advantageous anatomical position beneath the skin on the musculus vastus medialis, its suitable inner diameter of approximately 100μm , and its rapid response to vasoactive stimuli. Figure 2a is a representative OCT grayscale cross section of a murine artery and vein, as well as the surrounding tissue and other structures including nerves. The surrounding tissue consists of perivascular fat and appears as a foamy structure. Lipid containing vacuoles (lv; left arrow) in perivascular adipocytes (approximately 80μm in diameter) are visible beneath the surface, which is represented by connecting tissue of muscle fascia. The distinctive ring structures encircling the vessel lumens are the arterial and venous vessel walls. Vessel wall thickness wt is indicated by a double arrow. The lumen and vessel wall of the saphenous vein (white arrow) and artery (black arrow), as well as the nerve (nervus vastus medialis; gray arrow), are shown under control conditions [Fig. 2a], and after VC [Fig. 2b] and VD [Fig. 2c]. Morphology is revealed by 3-D volume rendering of murine tissue containing the same structures before [Fig. 2d] and after VC [Fig. 2e] and VD [Fig. 2f].

3.2.

Vasodynamics

The morphological vessel parameters used to characterize vessel dynamics of mice aged 6 (6w) and 20 (20w) weeks were: 1. the inner diameter d as determined from the blood-filled lumen confined by the vessel wall, and 2. the vessel wall thickness wt of the saphenous artery and vein. During vasoconstriction (VC) and vasodilation (VD), these parameters ( dVC , dVD , wtVC , and wtVD ) differ from resting conditions ( dres , wtres ). To define vessel reactions to vasoactive stimuli, we determined the dynamic range dr=dVDdVC and dynamic ratio (dVCdVD) as a degree of vessel stiffness. The relative wall thickness wtrel=wtres(dres2) characterized the vessel type. In previous studies, the relative wall thickness of the aorta was characterized by a value of 0.2, which increased to 0.5 in arteries and to 1.0 in arterioles.14 This increase was found to be more moderate in the venous bloodstream, starting at 0.1 for the vena cava, 0.2 in veins, and 0.3 in venules. The maximum velocity vmax of inner diameter change provides information about how fast the vessel reacts to vasoactive stimuli, and the time to half maximum diameter change t12 indicates how long it takes until these reactions are finished.

Changes in the inner diameter of the saphenous artery and vein during VC and VD were recorded in a quantitative manner using the FD-OCT technique (Table 1 ). Analyzing the saphenous vein, we detected only slight inner diameter and wall thickness changes between both age groups in response to vasoactive stimuli. In contrast, the inner diameter of the saphenous artery of 6-week -old mice altered from 122±6μm under resting conditions to 10±3μm after VC (dVC) and 227±4μm after VD (dVD) . At 20weeks of age, the inner diameter of the saphenous artery had increased due to the growth of the animal to 172±9μm (resting conditions), 38±7μm (dVC) , and 245±8μm (dVD) . While the dynamic range of the vessel diameter did not change with age ( 6w=217±5μm and 20w=207±9μm ), the vessel wall stiffness increased significantly by a factor of 4 from 0.04±0.01 (6w) to 0.16±0.03 after 20weeks of age. In both age groups, the arterial vessel wall was always thicker than the venous vessel wall. Arterial wall thickness in 6-week -old mice increased from 24±1μm at resting conditions to 38±2μm after VC, and decreased to 18±1μm after VD. In 20-week -old mice, wt changed from 22±1μm during resting conditions to 46±2μm after VC and 18±1μm after VD. The wtVC and wtrel of 6-week -old mice showed significant differences compared to 20-week -old animals. The relative wall thickness wtrel of the arteries changed from a value of 0.44 (6w) to 0.27 (20w). The measured wtrel for arteries is in the range of the relative wall thickness described in the literature.14

Table 1

Quantification of the inner diameter d and vessel wall thickness wt of the saphenous artery and vein under resting condition dres and wtres , after vasoconstriction (VC) dVC and wtVC , and after vasodilation (VD) dVD and wVD . Dynamic range dr=∣dVD−dVC∣ and dynamic ratio dVC∕dVD , and the relative wall thickness wtrel=wtres∕(dres∕2) were compared between mice aged 6 (6w) and 20 (20w) weeks. p*<0.05 ; p**<0.01 ; p***<0.001 versus 6w.

ArteryVein
6w (n=30) 20w (n=14) 6w (n=30) 20w (n=14)
Inner diameter [μm]
dres 122±6 172±9*** 225±8 208±10
dVC 10±3 38±7*** 224±6 221±10
dVD 227±4 245±8* 244±9 228±12
dr 217±5 207±8 25±7 17±6
dVDdVC 0.04±0.01 0.16±0.03*** 0.93±0.03 0.98±0.03
Wall thickness [μm]
wtres 23.9±0.8 22.0±1.1 16.8±0.5 16.1±0.5
wtVC 37.6±1.7 46.1±1.7** 17.3±0.6 16.5±0.9
wtVD 18.3±0.8 17.7±1.0 15.4±0.7 14.3±0.9
Relative wall thickness
wtrel 0,44±0.03 0.27±0.02*** 0.15±0.01 0.16±0.01

Figure 3 shows a representative image of changes in the saphenous artery inner diameter over time (black arrow). Here, cross sections from the time-resolved image stacks under control, VC, and VD conditions were sequentially combined to clearly demonstrate inner diameter changes after the application of vasoactive stimuli. In the saphenous artery lumen, an alternating light and dark pattern was observed after VD. This likely represents the detection of blood cells with reduced flow velocity during the diastolic part of the cardiac cycle by the OCT system.

Figure 4 shows an example of changes in the saphenous artery inner diameter during VC and the corresponding graph of the fitted sigmoid function. Inner diameter was determined by the algorithm described in the image quantification section of the methods. The dynamic parameters vmax and t12 during VC and VD for the saphenous arteries in each age cohort are shown in Table 2 . Dynamic responses were not detectable for the saphenous vein. Although the reaction velocity (vmax) was faster in response to VD than VC in both age groups, comparison of t12 indicates that VC progressed more rapidly ( 6w=4.5±0.4s ; 20w=6.5±0.4s ) than VD ( 6w=8.5±1.2s ; 20w=9.8±0.5s ).

Fig. 4

Time course of inner diameter change during vasoconstriction (VC) measured by FD-OCT (gray circles) and the fitted sigmoid function (black line). At time t0 , the vasoconstrictor K+ was applied. Δd indicates the change from the initial inner diameter d0 to the final inner diameter dVC during VC. The dynamics of inner diameter change were quantified using the time of half VC t12 and the maximum velocity vmax of inner diameter change, reflecting the slope at the inflection point. VD dynamics were analyzed in a similar manner.

034027_1_031903jbo4.jpg

Table 2

Quantification of maximum velocity vmax in μm∕s of inner diameter change and time to half maximum VC or VD t1∕2 in s during VC and VD in 6-week (6w) and 20-week -old (20w) mice. No dynamic behavior was detected in the saphenous vein (n.d.). p**<0.01 versus 6w.

vmax [μm∕s] ArteryVein
6w20w6w20w
VC 16.1±2.0 14.6±1.4 n.d.n.d.
VD 20.2±2.6 19.4±1.6 n.d.n.d.
t(12) [s]n.d.n.d.
VC 4.5±0.4 6.5±0.4** n.d.n.d.
VD 8.5±1.2 9.8±0.5 n.d.n.d.

4.

Discussion and Conclusion

Here we demonstrate that FD-OCT is a novel technique that is highly suitable for in-vivo investigation of the vasodynamics of arteries and veins in the mouse model. We show that FD-OCT facilitates contactless imaging of the saphenous artery and vein with 2-D cross sectional images and 3-D tomograms. FD-OCT allows quantification of vessel wall thickness and inner diameter of the saphenous artery and vein, and is a means to follow the time course of inner diameter change during VC and VD. Importantly, FD-OCT mediated analysis largely leaves physiological parameters such as blood flow, blood pressure, and nerval innervations intact. It also has the advantage of avoiding the preparation trauma associated with traditional methods that rely on isometric force measurements of vessel rings in organ chambers. Use of FD-OCT in vivo in the mouse represents a novel opportunity to investigate vasodynamics in a physiological context.

We demonstrate that the resolution and A-scan rate of our FD-OCT system are sufficient to detect significant differences in inner vessel diameter and wall thickness. FD-OCT has an advantage over wire myography because it allows replicate interventions, as evidenced by our analysis of the same animals at 6 and 20weeks of age. This offers the opportunity to analyze long-term changes in the vasculature and to study, e.g., pharmaceutical effects, over a time course without sacrificing the animals.15 Our detection of physiological changes in vessel wall thickness in response to vasoactive stimuli agrees with previous histological investigations.16 The observed progressive limitation of vessel dynamics might be able to facilitate the genesis of cardiovascular diseases caused by reduced elasticity of the vessel wall. Especially during systolic peak pressure, the limited elasticity of the vessel wall results in an increased wall tension, and finally leads to an endothelial dysfunction and cardiovascular disease in old age.

In conclusion, we demonstrate that our FD-OCT system with an A-scan rate of 1.2kHz allows vasodynamics in murine vasculature to be quantified with an improved temporal resolution. Use of this novel system will reduce the number of mice required, because experiments can be carried out at multiple time points with the same animal. Furthermore, the many transgenic and knock-out mouse strains available makes this model a very useful tool for biomedical research. High-resolution OCT systems facilitate the characterization of vascular structure and function. Further development of an OCT system with higher acquisition rates will enable Doppler OCT measurement17, 18 of blood flow in different vessel types throughout the entire cardiac cycle. Based on blood flow data, the blood velocity and the biomechanical stress it imparts to the vascular wall can be calculated. Higher acquisition rates may also reveal time-resolved changes of inner diameter and wall thickness caused by the heartbeat (600bpm) , thus contributing to our understanding of vascular wall elastic properties. Our innovative in-vivo application of FD-OCT in the mouse model will be an attractive alternative to classic isometric force measurements for investigating vascular function and dynamics.

Acknowledgments

This study was supported by grants from MeDDrive38 programs 2007 and 2008 of the Faculty of Medicine Carl Gustav Carus of the Dresden University of Technology (Müller), the German Federal Ministry of Education and Research (BMBF) program NBL3 of the Dresden University of Technology (Morawietz, Professorship of Vascular Endothelium and Microcirculation; Koch, Professorship of Clinical Sensoring and Monitoring). We are grateful to Mirko Mehner for excellent technical assistance and to Dana Niegsch for proofreading the manuscript.

References

1. 

Guidelines subcommittee, “World Health Organization-International Society of Hypertension guidelines for the management of hypertension,” J. Hypertens., 17 151 –183 (1999). 0263-6352 Google Scholar

2. 

P. K. Shah, “Mechanisms of plaque vulnerability and rupture,” J. Am. Coll. Cardiol., 41 (4), 15 –22 (2003). https://doi.org/10.1016/S0735-1097(02)02834-6 0735-1097 Google Scholar

3. 

E. Falk, P. K. Shah, and V. Fuster, “Coronary plaque disruption,” Circulation, 92 (3), 657 –671 (1995). 0009-7322 Google Scholar

4. 

P. Greenland, S. S. Gidding, and R. P. Tracy, “Commentary: lifelong prevention of atherosclerosis: the critical importance of major risk factor exposures,” Int. J. Epidemiol., 31 (6), 1129 –1134 (2002). https://doi.org/10.1093/ije/31.6.1129 0300-5771 Google Scholar

5. 

R. Ross, “Atherosclerosis-an inflammatory disease,” N. Engl. J. Med., 340 (2), 115 –126 (1999). https://doi.org/10.1056/NEJM199901143400207 0028-4793 Google Scholar

6. 

G. K. Hansson, “Inflammation, atherosclerosis, and coronary artery disease,” N. Engl. J. Med., 352 (16), 1685 –1695 (2005). https://doi.org/10.1056/NEJMra043430 0028-4793 Google Scholar

7. 

Y. S. Chatzizisis, A. U. Coskun, M. Jonas, E. R. Edelman, C. L. Feldman, and P. H. Stone, “Role of endothelial shear stress in the natural history of coronary atherosclerosis and vascular remodeling,” J. Am. Coll. Cardiol., 49 2379 –2393 (2007). https://doi.org/10.1016/j.jacc.2007.02.059 0735-1097 Google Scholar

8. 

A. F. Fercher, W. Drexler, C. K. Hitzenberger, and T. Lasser, “Optical coherence tomography-principles and applications,” Rep. Prog. Phys., 66 (2), 239 –303 (2003). https://doi.org/10.1088/0034-4885/66/2/204 0034-4885 Google Scholar

9. 

J. A. Schaar, F. Mastik, E. Regar, C. A. den Uil, F. J. Gijsen, J. J. Wentzel, P. W. Serruys, and A. F. van der Stehen, “Current diagnostic modalities for vulnerable plaque detection,” Curr. Pharm. Des., 13 (10), 995 –1001 (2007). https://doi.org/10.2174/138161207780487511 1381-6128 Google Scholar

10. 

J. A. Angus and C. E. Wright, “Techniques to study the pharmacodynamics of isolated large and small blood vessels,” J. Pharmacol. Toxicol. Methods, 44 (2), 395 –407 (2000). https://doi.org/10.1016/S1056-8719(00)00121-0 1056-8719 Google Scholar

11. 

G. Haeusler and M. W. Lindner, “Coherence radar and spectral radar new tools for dermatological diagnosis,” J. Biomed. Opt., 3 (1), 21 –31 (1998). https://doi.org/10.1117/1.429899 1083-3668 Google Scholar

12. 

S. H. Yun, G. J. Tearney, J. F. de Boer, and B. E. Bouma, “Motion artefacts in optical coherence tomography with frequency-domain ranging,” Opt. Express, 12 (13), 2977 –2998 (2004). https://doi.org/10.1364/OPEX.12.002977 1094-4087 Google Scholar

13. 

J. Walther, A. Krueger, M. Cuevas, and E. Koch, “Effects of axial, transverse and oblique sample motion in FD OCT in systems with global or rolling shutter line detector,” J. Opt. Soc. Am. A, 25 (11), 2791 –2802 (2008). https://doi.org/10.1364/JOSAA.25.002791 0740-3232 Google Scholar

14. 

P. Gaehtgens, “Das Kreislaufsystem,” Lehrbuch der Physiologie, 145 –188 Thieme, Stuttgart, New York (2001). Google Scholar

15. 

K. Holemans, R. Gerber, K. Meurrens, F. De Clerck, L. Poston, and F. A. Van Assche, “Maternal food restriction in the second half of pregnancy affects vascular function but not blood pressure of rat female offspring,” Br. J. Nutr., 81 (1), 73 –79 (1999). 0007-1145 Google Scholar

16. 

R. L. Van Citters, B. M. Wagner, and R. F. Rushmer, “Architecture of small arteries during vasoconstriction,” Circ. Res., 10 668 –675 (1962). 0009-7330 Google Scholar

17. 

C. J. Chang and K. H. Hou, “High-resolution optical Doppler tomography for in vitro and in vivo fluid flow dynamics,” Chang Keng I Hsueh, 26 (6), 403 –411 (2003). 0255-8270 Google Scholar

18. 

J. Walther, G. Mueller, H. Morawietz, and E. Koch, “Analysis of in vitro and in vivo bidirectional flow velocities by phase-resolved Doppler Fourier-domain OCT,” Sens. Actuators, A, (0924-4247) https://doi.org/10.1016/j.sna.2009.02.025 Google Scholar
©(2009) Society of Photo-Optical Instrumentation Engineers (SPIE)
Sven Meissner, Gregor Müller, Julia Walther, Henning Morawietz, and Edmund Koch "In-vivo Fourier domain optical coherence tomography as a new tool for investigation of vasodynamics in the mouse model," Journal of Biomedical Optics 14(3), 034027 (1 May 2009). https://doi.org/10.1117/1.3149865
Published: 1 May 2009
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Cited by 11 scholarly publications.
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KEYWORDS
Virtual colonoscopy

Arteries

Optical coherence tomography

Veins

In vivo imaging

Mouse models

Tissues

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