Open Access
18 May 2016 In vivo photoacoustic microscopy of human cuticle microvasculature with single-cell resolution
Author Affiliations +
Abstract
As a window on the microcirculation, human cuticle capillaries provide rich information about the microvasculature, such as its morphology, density, dimensions, or even blood flow speed. Many imaging technologies have been employed to image human cuticle microvasculature. However, almost none of these techniques can noninvasively observe the process of oxygen release from single red blood cells (RBCs), an observation which can be used to study healthy tissue functionalities or to diagnose, stage, or monitor diseases. For the first time, we adapted single-cell resolution photoacoustic (PA) microscopy (PA flowoxigraphy) to image cuticle capillaries and quantified multiple functional parameters. Our results show more oxygen release in the curved cuticle tip region than in other regions of a cuticle capillary loop, associated with a low of RBC flow speed in the tip region. Further analysis suggests that in addition to the RBC flow speed, other factors, such as the drop of the partial oxygen pressure in the tip region, drive RBCs to release more oxygen in the tip region.

1.

Introduction

The microcirculation comprises microvascular networks of arterioles, capillaries, and venules, which are fundamental for thermoregulation and for transporting nutrients and gases to maintain the metabolism of cells.1 However, under disease states, such as severe hemorrhage, cardiogenic shock, sepsis,1,2 and systemic scleroderma,35 the associated dysfunction of the microcirculation may cause heterogeneous hypoxia, impairing cell functioning in tissues and even causing multiple organ failures.1,2 In other cases, hypertension and diabetes mellitus can cause microvascular complications, such as microvessel rarefaction and retinopathy, respectively.6,7 Tumors will often induce angiogenesis of the microvascular system in their microenvironment.8 To better understand the fundamental mechanisms of these diseases, diagnose them in early stages, and evaluate the effectiveness of various therapies, it is essential to develop tools to monitor important microvascular parameters of blood perfusion. These parameters include function capillary density (which is defined as the total length of capillaries perfused by RBCs per observed area in units of cm1),1 total hemoglobin concentration (CHb), the oxygen saturation of blood (sO2), the directional derivative of sO2 along the blood flow direction (DsO2), and the speed of blood flow (vHb).9

Primary medical imaging modalities, such as single-photon emission computed tomography, functional magnetic resonant imaging, positron emission tomography, ultrasonography, and diffuse optical tomography, have been used for years to image cardiovascular or cerebral blood flow.1014 Additionally, contrast-enhanced ultrasonography, which detects nonlinear oscillation of microbubbles (only a few microns in size) under low mechanical index conditions, has been applied to imaging blood perfusion around focal liver lesions and the renal cortex.1517 Even though these techniques are the best we have to date to image blood flows in organs deep in the body, they are limited by their millimeter-size resolution. Thus, these modalities are not efficient in monitoring microcirculation, which in general contains vessels smaller than 100  μm.1

As an alternative, the cutaneous and sublingual microcirculations have been proposed as a representative model for visceral microcirculation, because they are accessible by optical-based imaging techniques, which provide higher resolution than most other imaging modalities.1820 Patients with chronic diseases such as hypertension, renal disease, and coronary artery disease have been observed to have distinct cutaneous microvascular parameters.6,21,22 Monitoring cutaneous microvascular functioning provides valuable information for evaluating peripheral microvascular diseases, such as Raynaud’s disease and peripheral arterial disease.4,23,24 To this end, optical scattering-based techniques such as laser Doppler imaging,22,25 near-infrared spectroscopy,26,27 and reflectance spectroscopy28,29 are used to detect scattered light from tissues. Over a submillimeter sampling volume, laser Doppler imaging can measure the average speed of flow, and near-infrared spectroscopy and reflectance spectroscopy can measure both the average flow speed and the oxygen saturation. On the wide-field scale, nailfold videomicroscopy,4,30,31 orthogonal polarization spectral imaging,32,33 sidestream dark field imaging,34 and optical coherent tomography35,36 can provide wide-field information about function capillary density and the speed of flow, with lateral resolutions ranging from submicrons to around 15  μm, which covers from the thinnest capillaries to the wider arterioles and venules. The imaging depth can go as deep as 400  μm for nailfold videomicroscopy and around 1 to 3 mm for optical-based techniques. Combined with an endoscope, these modalities can image the gastric or intestinal microcirculation with a tolerable compromise of image quality. However, none of these imaging modalities can provide sO2 and vHb information at the same time.

In recent years, optical resolution photoacoustic microscopy (OR-PAM) has shown promise in in vivo microvascular imaging, with its ability to provide wide-field, capillary-resolving, and hemoglobin-sensitive images.3743 Combined with the flow speed imaging techniques reported previously,4446 OR-PAM has been demonstrated as a powerful tool to acquire such important parameters of the microcirculation as sO2, DsO2, CHb, vHb, and the metabolic rate of oxygen in tissues.47,48 In this study, we implemented dual-wavelength in vivo OR-PAM for investigating oxygen release in cuticle capillaries. This is the first time that oxygen release dynamics in human cuticle capillaries have been monitored. The correlation between oxygen release and the speed of RBCs and between oxygen release and the first-order time-derivative of sO2 have also been analyzed in a cuticle capillary. The spatial- and time-resolved information acquired by OR-PAM may help in early-stage diagnosis of perivascular diseases, such as Raynaud’s syndrome, and in diagnosing heterogeneous microcirculation of interior organs.

2.

Methods

2.1.

Experimental Protocol

Nine healthy, consenting volunteers (with ages ranging from 23 to 30; seven males and two females) were recruited in this study. For each volunteer, we imaged the cuticle capillaries in the fourth finger (the ring finger) of the left hand.36 Before each experiment, the volunteer rested in the temperature-controlled laboratory (at 20°C) for 15 min to adapt to the environmental temperature, since nailfold microcirculation is known to be sensitive to the surrounding temperature. The imaged area was then cleaned with alcohol swabs, and the hand was comfortably put on a homemade hand mount, without occlusion of blood flow, as shown in Fig. 1. During the data acquisition period, the photoacoustic (PA) scanning head was scanned over a single cuticle capillary at a time for three-dimensional imaging, with a 10-Hz C-scan rate (high-speed scanning mode) for about 40 s. At least three cuticle capillaries were recorded for each volunteer. The total experimental time spent on a volunteer was <1.5  h, including rests every 20 min to prevent numbness of the extremities. The human study was approved by the Institutional Review Board of Washington University in St. Louis, and the pulse energies of the excitation lasers used in each experiment were within the American National Standards Institute (ANSI) laser safety limit (20  mJ·cm2).

Fig. 1

Schematic of the single-cell OR-PAM system. BS, beam splitter; CG, coverglass; LSM, linear step motor; PD, photodiode; PH, pin hole; PM, plastic membrane; UG, ultrasound gel; UT, ultrasound transducer; VC, voice coil motor; and WT, water.

JBO_21_5_056004_f001.png

2.2.

System Setup

In order to monitor the real-time microcirculation of a single cuticle, dual-wavelength excitation at 532 nm (SPOT, Elforlight, Northants, United Kingdom) and 559 nm (INNOSLAB, Edgewave, Würselen, Germany) was implemented on a high-speed voice-coil scanning PA microscope,49 shown in Fig. 1. The two short-pulse (<10  ns) excitation beams, with a 10-μs temporal delay between them, were first attenuated, combined, and passed through an optical spatial filter made of a spherical lens and a pinhole (50  μm in diameter; P50C, Thorlabs, Newton, New Jersey); then they were guided into a customized photonic crystal fiber (Thorlabs, Newton, New Jersey). The other end of the fiber was connected to the scanning PA probe. The output beams from the fiber were focused by a lens pair with a numerical aperture of 0.1 in water and were reflected by an acoustic-optical beam combiner made of two right-angle prisms sandwiching a coated aluminum layer on the hypotenuse faces. The emitted PA signals in the reflection direction were collected by an acoustic lens and then detected by a 50-MHz ultrasonic transducer (V214, Olympus NDT, Pennsylvania). The received PA signals were amplified (ZFL-500LN+, Mini-circuits, New York), filtered, and then digitized by a data acquisition (DAQ) system (ATS9350, Alazar Tech. Inc., Quebec, Canada). The optical focusing and the bandwidth of the transducer provided 3-μm lateral resolution and 15-μm axial resolution, respectively. In order to compensate for variations of the optical energy, pulse by pulse, a photodiode was set up after the optical spatial filter. The laser pulse energy on the sample surface was between 35 and 50 nJ in high-speed mode with the laser repetition rate of 20 kHz.

During single cuticle capillary imaging, the PA probe mounted on the voice-coil motor was driven to scan linearly with 100 Hz (B-scan) frequency within a 250-μm range. Combined with an additional linear translational stage (PLS-85, PI miCos, Eschbach, Germany), the system was set to repeatedly acquire 250  μm×40  μm C-scan images at 10 Hz. The lasers, photodiode, and DAQ system were synchronously triggered at 20 kHz by a programmed field-programmable gate array card (PCI-7830R, National Instruments, Austin, Texas). This dual-wavelength high-speed PA microscopy has been previously demonstrated for measuring sO2 and blood flow speed in mouse capillaries.49

2.3.

Principle of Oxygen Saturation of Blood Measurement

After C-scan, images have been acquired with two wavelengths, and the sO2 values can be calculated pixel-by-pixel according to the method in Refs. 50, 51. In short, the PA amplitude P at the i’th wavelength λi from a single pixel is related to the molar extinction coefficients of deoxy- and oxy-hemoglobin [ϵHbR(λi),ϵ(HbO2)  (λi)], the concentrations of deoxy- and oxy-hemoglobin {[HbR],[HbO2]}, and the optical fluence F as follows:

P(λi){ϵHbR(λi)[HbR]+ϵHbO2(λi)[HbO2]}·F(λi).
In order to solve for [HbR] and [HbO2], two wavelengths are selected to build up two independent equations. To calibrate the sO2 calculation, the optical properties of the tissue should be considered as well. We followed the same procedure as in Ref. 50 to calibrate the system. To mimic the optical properties of human tissue, the calibration was done in mouse experiments at a depth similar to that of the cuticle capillaries in human tissue.

3.

Results

3.1.

Monitoring of Oxygen Saturation of Blood Dynamics in Cuticles

Figures 2(a)2(c) show a top view (C-scan) and a cross-sectional view (B-scan) of the typical morphology of finger cuticle capillary loops. The acquisition time of a C-scan image was 75 s. The cuticle capillary loops angle toward the distal nail bed and gradually toward the epidermis. Figure 2(d) shows the result of using the curvature calculated from the C-scan images to quantitatively describe the geometric profile at different positions along the cuticles. The full width at half maximum distance is around 40  μm, which suggests that it is reasonable to define a region ±20  μm from the position with maximal curvature as the tip region of a cuticle. It is also noticeable but not surprising to observe that in most cases the tip positions (0  μm) coincide with the uppermost ends of the cuticles in the B-scan images. In Fig. 2(b), the insets also show pixel-by-pixel calculation of sO2 distribution in different areas of the cuticle capillary network with different color bars. The sO2 reduction across the tip of a cuticle capillary is within 0.2. In high-speed scanning mode, the flow and the sO2 of single RBCs can be resolved, as shown in the snapshots in Fig. 3(a) and Video 1. Figure 3(b) shows the results of time-averaging over all the frames of the sO2 image. Around the cuticle tip (the most curved position along the cuticle), an abrupt drop in sO2 can be observed. Figure 3(c) shows sO2 versus s, where s denotes the displacement along the central axis of a cuticle capillary loop (i.e., the trace of the blood flow). The origin of s is coincident with the cuticle loop tip, and the RBCs flow from the negative coordinates (the upstream side of a cuticle vessel) to the positive coordinates (the downstream side). The sO2 change with distance can be revealed more clearly by plotting the derivative of sO2 with respect to s, which is defined as DsO2(sO2)/s, as shown in Fig. 3(d). The DsO2 values within 15  μm the cuticle loop tips are approximately twice as high as those in regions 25 to 40  μm away from the tip. The paired Student’s t-test between the tip region (yellow) and two sides (green) validates that the cuticle loop tips have significantly greater decreases in sO2 than the sides do.

Fig. 2

(a) Photograph of a finger with the imaged area boxed. (b) Wide-field PA image of cuticle capillaries shown with normalized PA amplitude. The insets show sO2 images of selected cuticles with different color bars. (c) B-scan image of cuticle capillary loops. (d) Curvature along the cuticles (fitting: sum of two Gaussians).

JBO_21_5_056004_f002.png

Fig. 3

(a) Selected time-lapse images of single-RBC sO2 (Video 1, MPEG, 207 KB) [URL: http://dx.doi.org/10.1117/1.JBO.21.5.056004.1]

. (b) Time-averaged images (10  s) of all time-lapse frames of sO2 imaging. (c) Time-averaged sO2 along the length of a cuticle capillary loop (i.e., a trace of the blood flow). (d) Time-averaged directional derivative of sO2 along the length of the loops. (e) Statistics of (d): paired Student’s t-test between the tip region (yellow) and the two side regions (green). NS: not significant (P=0.48), ***P<0.001, and n=21.

JBO_21_5_056004_f003.png

3.2.

Measurement of Red Blood Cell Flow Speed

By mapping the length of a curved cuticle loop s into a straight line l, Fig. 4(a) shows the method we used to measure the speed of RBCs flowing in cuticle capillary loops.45 Based on Fourier analysis of the frames of a specific segment of a capillary loop acquired at different times, the longitudinal flow speeds of different segments in a cuticle can be determined by vHb=(Δs/Δt)=(Δl/Δt)=(Nt/Nl)(ΔFt/ΔFl). Here, Nt and Nl are the sampled temporal and spatial lengths and Ft and Fl are the temporal and spatial frequencies. From Fig. 4(b), we can observe that the time-averaged RBC flow speed within the region of 15  μm around the cuticle tip is approximately one-third lower than that in the regions between 25 to 40  μm away from the cuticle tip. A paired Student’s t-test between the tip and side regions shows a significantly lower RBC flow speed around the tip region.

Fig. 4

(a) Image for speed measurement. (b) Time-averaged RBC flow speeds along the length of a cuticle loop. (c) Statistics of (b): paired Student’s t-test between the tip region (yellow) and the two side regions (green). NS: not significant (P=0.45), ***P<0.001, **P<0.01, and n=18.

JBO_21_5_056004_f004.png

3.3.

Measurement of Hemoglobin Flux in Red Blood Cell Flow and Time Derivative of Oxygen Saturation of Blood

As well as imaging sO2, we can also image the relative concentration of hemoglobin (CHb) by summing the calculated images for oxy- and deoxyhemoglobin. To calculate the time-averaged hemoglobin flux, we assume that the concentration and the speed are independent variables, which means that the time average of the product of the two variables is approximately equal to the product of the two time-averaged variables (in case the variances of CHb and vHb are small), so we have ΦHb¯CHb¯·vHb, where vHb is the time-averaged RBC flow speed around x. Figures 5(a) and 5(c) show a nearly flat trend, and the paired t-tests shown in Figs. 5(b) and 5(d) suggest that the hemoglobin flux in RBC flow is approximately the same along the cuticle capillary loops: the flow of RBCs is conserved. Under steady-state blood flow, [d(sO2)/dt]=DsO2·(ds/dt). Similarly, we assume that both DsO2 and ds/dt are independent variables; we have [d(sO2)/dt]DsO2·vHb. The total time derivative of sO2 along cuticle capillary loops is shown in Fig. 5(e). The p value between the upstream side and the tip is 0.03, and the p value between the downstream side and the tip is 0.07, according to the paired t-test shown in Fig. 5(f).

Fig. 5

(a) Time-averaged relative flow rates along the length of cuticle capillary loops. (b) Statistics of (a): paired Student’s t-test between the tip region (yellow) and the two side regions (green). NS: not significant (up: P=0.24, left: P=0.10, right: P=0.40), n=13. (c) Time-averaging of hemoglobin concentration along the direction of the length of cuticles. (d) Statistics of (c): paired Student’s t-test between the tip region (yellow) and the two side regions (green). NS: not significant (up: P=0.33, left: P=0.45, right: P=0.21), n=18. (e) Time-averaged values of d(sO2)/dt along the length of cuticle capillary loops. (f) Statistics of (e): paired Student’s t-test between the tip region (yellow) and the two side regions (green). *P=0.03, NS: not significant (up: P=0.07, down: P=0.25), n=15.

JBO_21_5_056004_f005.png

4.

Discussion

In this study, we demonstrated the ability of single-cell resolution OR-PAM to monitor the microcirculation in cuticle capillaries with a temporal resolution of 0.1 s. Compared to nailfold videocapillaroscopy and optical computed tomography,36 OR-PAM can not only image the morphology, dimensions, and vessel density of cuticle capillary loops, but also measure multiple hemodynamic parameters, such as sO2, DsO2, CHb, and vHb. Monitoring these functional parameters at the fundamental level of the physiology of oxygen transport can potentially help biologists and physicians to understand the mechanisms of oxygen transport in the skin and to define clinical standards for early-stage diagnosis and evaluation of perivascular diseases, such as Raynaud’s phenomenon and systemic scleroderma, before the capillaries undergo observable changes in morphology.

The time-averaged DsO2 results in Fig. 3(d) indicate that RBCs release more oxygen in the tip region over a length of around 30  μm then they do further down on the two sides. A similar result has been mentioned in one previous work, with no further investigation.52 It is interesting to note that the 30-μm length is approximately equal to the length of a capillary loop in the dermal papillae in the skin outside of the cuticle area.53 Capillary loops in dermal papillae are extensions of the subpapillary plexus in the reticular dermis, and they are responsible for oxygen and nutrient transport to living cells in the epidermis. Because nails are specialized structures of the skin,54 cuticle capillaries and dermal capillaries should be functionally similar parts of the capillary loop system (except that cuticle capillaries extend toward the distal nail bed), it will not be surprising to discover that the tip region of a cuticle capillary releases more oxygen than the other regions.

In Figs. 4(b) and 4(c), the RBC flow speed is reduced in the tip region (around two-thirds of the speed in the side regions). In blood rheology, RBC flow in capillaries is treated as a non-Newtonian fluid because of the special viscoelasticity of erythrocytes, which complicates the RBC flow in a capillary.5557 The reduced RBC flow speed may result from deformation of RBCs and a consequent change of their viscoelasticity while passing through the highly curved pathway of the tip region. Another possibility is that RBCs partially accumulate in the tip region. In order to test this hypothesis, we examined the hemoglobin concentration and the hemoglobin flux along the cuticles. Further, we used a paired t-test to compare the effects of the straight part and the curved part of a cuticle on the hemoglobin flow and concentration. To improve the statistical accuracy, we excluded outlier data points that have large standard deviations (>30%). It can be seen that this hypothesis is not supported by the results in Figs. 5(a)5(d), which show that both the flux of hemoglobin and the time-averaged hemoglobin concentration do not significantly differ between the side regions and the tip. Therefore, RBC flow is shown to be conserved along a cuticle capillary loop. The slower RBC flow in the tip region seems to meet a functional demand which requires a longer transit time of RBCs to release enough oxygen for metabolism. To investigate the relation between DsO2 and RBC flow speed, we calculated the time derivative of sO2 along cuticle capillary loops. Without introducing physical cuffing and compression on the arm imaged, and without any extra physiological stimulation, we assumed that the RBC flow can be considered as in a steady or quasi-steady state, which means [d(sO2)/dt]=DsO2·(ds/dt)+[(sO2)/t]DsO2·(ds/dt).58 Figures 5(e) and 5(f) show that RBCs release more oxygen per unit time in the tip region than in the sides. Although the statistics are not strongly significant (p>0.01), this finding still suggests that there are factors other than RBC flow speed, such as partial oxygen pressure, that can drive RBCs to release more oxygen in the tip region.

In this investigation, our single-cell resolution OR-PAM system performed monitoring of several hemodynamic parameters on nine human volunteers. Cell-by-cell based statistics also provided insights. In the future, OR-PAM promises to help greatly in the early-stage diagnosis of perivascular diseases and to illuminate more fundamental mechanisms in hemodynamics.

5.

Conclusion

In this paper, the cuticle microcirculations of healthy volunteers were monitored by real-time single-cell resolution OR-PAM. Hemodynamic parameters such as CHb, sO2, DsO2, vHb, and relative blood flow rate were extracted from the images. A drop in DsO2 and slower RBC flow were observed in the tip region than in the side regions of a cuticle capillary loop. The conserved blood flow rate in a cuticle capillary loop and the drop in the time-derivative of sO2 in the tip region suggest that the heterogeneity of the RBC flow speed over a cuticle capillary loop is not the only factor that determines the heterogeneity of the oxygen release in the loop.

Acknowledgments

This work was supported in part by the National Institutes of Health Grant Nos. DP1 EB016986 (NIH Director’s Pioneer Award), R01 CA186567 (NIH Director’s Transformative Research Award), and R01 CA159959. L. V. Wang has a financial interest in Microphotoacoustics, Inc., which, however, did not support this work. The authors want to specially thank Chenghung Yeh for suggestions on image processing, and all the volunteers who participated in this study.

References

1. 

D. De Backer et al., “Monitoring the microcirculation in the critically ill patient: current methods and future approaches,” Intensive Care Med., 36 (11), 1813 –1825 (2010). http://dx.doi.org/10.1007/s00134-010-2005-3 ICMED9ICMED9 0342-4642 Google Scholar

2. 

D. De Backer, K. Donadello and D. O. Cortes, “Monitoring the microcirculation,” J. Clin. Monit. Comput., 26 (5), 361 –366 (2012). http://dx.doi.org/10.1007/s10877-012-9383-8 Google Scholar

3. 

E. Carwile Leroy and P. J. Cannon, “Skin capillary blood flow in scleroderma,” J. Clin. Invest., 50 (4), 930 –939 (1971). http://dx.doi.org/10.1172/JCI106565 JCINAOJCINAO 0021-9738 Google Scholar

4. 

A. K. Murray et al., “Preliminary clinical evaluation of semi-automated nailfold capillaroscopy in the assessment of patients with Raynaud’s phenomenon,” Microcirculation, 18 (6), 440 –447 (2011). http://dx.doi.org/10.1111/micc.2011.18.issue-6 MCCRD8MCCRD8 0275-4177 Google Scholar

5. 

D. Rossi et al., “The role of nail-videocapillaroscopy in early diagnosis of scleroderma,” Autoimmun. Rev., 12 (8), 821 –825 (2013). http://dx.doi.org/10.1016/j.autrev.2012.11.006 Google Scholar

6. 

J. Aellen et al., “Preserved capillary density of dorsal finger skin in treated hypertensive patients with or without type 2 diabetes,” Microcirculation, 19 (6), 554 –562 (2012). http://dx.doi.org/10.1111/micc.2012.19.issue-6 MCCRD8MCCRD8 0275-4177 Google Scholar

7. 

B. I. Levy et al., “Impaired tissue perfusion—a pathology common to hypertension, obesity, and diabetes mellitus,” Circulation, 118 (9), 968 –976 (2008). http://dx.doi.org/10.1161/CIRCULATIONAHA.107.763730 CIRCAZCIRCAZ 0009-7322 Google Scholar

8. 

P. Vajkoczy, A. Ullrich and M. D. Menger, “Intravital fluorescence videomicroscopy to study tumor angiogenesis and microcirculation,” Neoplasia, 2 (1–2), 53 –61 (2000). http://dx.doi.org/10.1038/sj.neo.7900062 Google Scholar

9. 

S. Fantini, “Dynamic model for the tissue concentration and oxygen saturation of hemoglobin in relation to blood volume, flow velocity, and oxygen consumption: implications for functional neuroimaging and coherent hemodynamics spectroscopy (CHS),” NeuroImage, 85 (1), 202 –221 (2014). http://dx.doi.org/10.1016/j.neuroimage.2013.03.065 NEIMEFNEIMEF 1053-8119 Google Scholar

10. 

Y. Yonekura et al., “SPECT with [99mTc]-d,l-hexamethyl-propylene amine oxime (HM-PAO) compared with regional cerebral blood flow measured by PET: effects of linearization,” J. Cereb. Blood Flow Metabol., 8 (6), S82 –S89 (1988). http://dx.doi.org/10.1038/jcbfm.1988.36 Google Scholar

11. 

D. J. Heeger and D. Ress, “What does fMRI tell us about neuronal activity?,” Nat. Rev. Neurosci., 3 (2), 142 –151 (2002). http://dx.doi.org/10.1038/nrn730 NRNAANNRNAAN 1471-003X Google Scholar

12. 

J. M. Tarkin, F. R. Joshi and J. H. F. Rudd, “PET imaging of inflammation in atherosclerosis,” Nat. Rev. Cardiol., 11 (8), 443 –457 (2014). http://dx.doi.org/10.1038/nrcardio.2014.80 Google Scholar

13. 

L. W. Dobrucki and A. J. Sinusas, “PET and SPECT in cardiovascular molecular imaging,” Nat. Rev. Cardiol., 7 (1), 38 –47 (2010). http://dx.doi.org/10.1038/nrcardio.2009.201 Google Scholar

14. 

J. P. Culver et al., “Diffuse optical tomography of cerebral blood flow, oxygenation, and metabolism in rat during focal ischemia,” J. Cereb. Blood Flow Metab., 23 (8), 911 –924 (2003). http://dx.doi.org/10.1097/01.WCB.0000076703.71231.BB Google Scholar

15. 

A. G. Schneider et al., “Renal perfusion evaluation with contrast-enhanced ultrasonography,” Nephrol. Dial. Transplant., 27 (2), 674 –681 (2012). http://dx.doi.org/10.1093/ndt/gfr345 NDTREANDTREA Google Scholar

16. 

K. Kalantarinia et al., “Real-time measurement of renal blood flow in healthy subjects using contrast-enhanced ultrasound,” Am. J. Physiol. Renal Physiol., 297 (4), F1129 –F1134 (2009). http://dx.doi.org/10.1152/ajprenal.00172.2009 Google Scholar

17. 

A. G. Schneider et al., “Contrast-enhanced ultrasound evaluation of the renal microcirculation response to terlipressin in hepato-renal syndrome: a preliminary report,” Ren. Fail., 37 (1), 175 –179 (2015). http://dx.doi.org/10.3109/0886022X.2014.977140 REFAE8REFAE8 0886-022X Google Scholar

18. 

Z. A. Awan, T. Wester and K. Kvernebo, “Human microvascular imaging: a review of skin and tongue videomicroscopy techniques and analysing variables,” Clin. Physiol. Funct. Imaging, 30 (2), 79 –88 (2010). http://dx.doi.org/10.1111/cpf.2010.30.issue-2 Google Scholar

19. 

L. A. Holowatz, C. S. Thompson-Torgerson and W. L. Kenney, “Last word on viewpoint: the human cutaneous circulation as a model of generalized microvascular function,” J. Appl. Physiol., 105 (1), 389 (2008). http://dx.doi.org/10.1152/japplphysiol.90436.2008 Google Scholar

20. 

M. Roustit and J. L. Cracowski, “Non-invasive assessment of skin microvascular function in humans: an insight into methods,” Microcirculation, 19 (1), 47 –64 (2012). http://dx.doi.org/10.1111/micc.2011.19.issue-1 MCCRD8MCCRD8 0275-4177 Google Scholar

21. 

F. Jung et al., “Primary and secondary microcirculatory disorders in essential-hypertension,” Clin. Invest., 71 (2), 132 –138 (1993). http://dx.doi.org/10.1007/BF00179994 Google Scholar

22. 

P. Coulon, J. Constans and P. Gosse, “Impairment of skin blood flow during post-occlusive reactive hyperhemy assessed by laser Doppler flowmetry correlates with renal resistive index,” J. Hum. Hypertens., 26 (1), 56 –63 (2012). http://dx.doi.org/10.1038/jhh.2010.117 Google Scholar

23. 

M. Bukhari et al., “Increased nailfold capillary dimensions in primary Raynaud’s phenomenon and systemic sclerosis,” Br. J. Rheumatol., 35 (11), 1127 –1131 (1996). http://dx.doi.org/10.1093/rheumatology/35.11.1127 BJRHDFBJRHDF 1460-2172 Google Scholar

24. 

A. L. Herrick, “The pathogenesis, diagnosis and treatment of Raynaud phenomenon,” Nat. Rev. Rheumatol., 8 (8), 469 –479 (2012). http://dx.doi.org/10.1038/nrrheum.2012.96 Google Scholar

25. 

P. Kvandal et al., “Regulation of human cutaneous circulation evaluated by laser Doppler flowmetry, iontophoresis, and spectral analysis: importance of nitric oxide and prostaglandines,” Microvasc. Res., 65 (3), 160 –171 (2003). http://dx.doi.org/10.1016/S0026-2862(03)00006-2 MIVRA6MIVRA6 0026-2862 Google Scholar

26. 

M. Attas et al., “Visualization of cutaneous hemoglobin oxygenation and skin hydration using near-infrared spectroscopic imaging,” Skin Res. Technol., 7 (4), 238 –245 (2001). http://dx.doi.org/10.1034/j.1600-0846.2001.70406.x Google Scholar

27. 

J. M. Murkin and M. Arango, “Near-infrared spectroscopy as an index of brain and tissue oxygenation,” Br. J. Anaesth., 103 (Suppl. 1), i3 –i13 (2009). http://dx.doi.org/10.1093/bja/aep299 BJANADBJANAD 0007-0912 Google Scholar

28. 

I. Seo, P. R. Bargo and N. Kollias, “Simultaneous assessment of pulsating and total blood in inflammatory skin lesions using functional diffuse reflectance spectroscopy in the visible range,” J. Biomed. Opt., 15 (6), 060507 (2010). http://dx.doi.org/10.1117/1.3524191 JBOPFOJBOPFO 1083-3668 Google Scholar

29. 

B. Schwarz et al., “Effects of norepinephrine and phenylephrine on intestinal oyxgen supply and mucosal tissue oxygen tension,” Intensive Care Med., 27 (3), 593 –601 (2001). http://dx.doi.org/10.1007/s001340100856 ICMED9ICMED9 0342-4642 Google Scholar

30. 

M. Hahn et al., “Hemodynamics in nailfold capillaries of patients with systemic scleroderma: synchronous measurements of capillary blood pressure and red blood cell velocity,” J. Invest. Dermatol., 110 (6), 982 –985 (1998). http://dx.doi.org/10.1046/j.1523-1747.1998.00190.x JIDEAEJIDEAE 0022-202X Google Scholar

31. 

C. C. Wu et al., “Red blood cell velocity measurements of complete capillary in finger nail-fold using optical flow estimation,” Microvasc. Res., 78 (3), 319 –324 (2009). http://dx.doi.org/10.1016/j.mvr.2009.07.002 MIVRA6MIVRA6 0026-2862 Google Scholar

32. 

A. Bauer et al., “Monitoring of the sublingual microcirculation in cardiac surgery using orthogonal polarization spectral imaging,” Anesthesiology, 107 (6), 939 –945 (2007). http://dx.doi.org/10.1097/01.anes.0000291442.69337.c9 ANESAVANESAV 0003-3022 Google Scholar

33. 

O. Genzel-Boroviczeny et al., “Orthogonal polarization spectral Imaging (OPS): a novel method to measure the microcirculation in term and preterm infants transcutaneously,” Pediatr. Res., 51 (3), 386 –391 (2002). http://dx.doi.org/10.1203/00006450-200203000-00019 PEREBLPEREBL 0031-3998 Google Scholar

34. 

C. M. Treu et al., “Sidestream dark weld imaging: the evolution of real-time visualization of cutaneous microcirculation and its potential application in dermatology,” Arch. Dermatol. Res., 303 (2), 69 –78 (2011). http://dx.doi.org/10.1007/s00403-010-1087-7 Google Scholar

35. 

W. J. Choi, H. Q. Wang and R. K. Wang, “Optical coherence tomography microangiography for monitoring the response of vascular perfusion to external pressure on human skin tissue,” J. Biomed. Opt., 19 (5), 056003 (2014). http://dx.doi.org/10.1117/1.JBO.19.5.056003 JBOPFOJBOPFO 1083-3668 Google Scholar

36. 

U. Baran, L. Shi and R. K. K. Wang, “Capillary blood flow imaging within human finger cuticle using optical microangiography,” J. Biophotonics, 8 (1–2), 46 –51 (2015). http://dx.doi.org/10.1002/jbio.201300154 Google Scholar

37. 

S. Hu, K. Maslov and L. V. Wang, “Second-generation optical-resolution photoacoustic microscopy with improved sensitivity and speed,” Opt. Lett., 36 (7), 1134 –1136 (2011). http://dx.doi.org/10.1364/OL.36.001134 OPLEDPOPLEDP 0146-9592 Google Scholar

38. 

S. Hu et al., “Functional transcranial brain imaging by optical-resolution photoacoustic microscopy,” J. Biomed. Opt., 14 (4), 040503 (2009). http://dx.doi.org/10.1117/1.3194136 JBOPFOJBOPFO 1083-3668 Google Scholar

39. 

J. J. Yao et al., “In vivo photoacoustic imaging of transverse blood flow by using Doppler broadening of bandwidth,” Opt. Lett., 35 (9), 1419 –1421 (2010). http://dx.doi.org/10.1364/OL.35.001419 OPLEDPOPLEDP 0146-9592 Google Scholar

40. 

R. Ma et al., “Fast scanning coaxial optoacoustic microscopy,” Biomed. Opt. Express, 3 (7), 1724 –1731 (2012). http://dx.doi.org/10.1364/BOE.3.001724 BOEICLBOEICL 2156-7085 Google Scholar

41. 

X. L. Deán-Ben and D. Razansky, “Functional optoacoustic human angiography with handheld video rate three dimensional scanner,” Photoacoustics, 1 (3–4), 68 –73 (2013). http://dx.doi.org/10.1016/j.pacs.2013.10.002 Google Scholar

42. 

A. P. Jathoul et al., “Deep in vivo photoacoustic imaging of mammalian tissues using a tyrosinase-based genetic reporter,” Nat. Photon., 9 239 –246 (2015). http://dx.doi.org/10.1038/nphoton.2015.22 NPAHBYNPAHBY 1749-4885 Google Scholar

43. 

P. F. Hai et al., “Near-infrared optical-resolution photoacoustic microscopy,” Opt. Lett., 39 (17), 5192 –5195 (2014). http://dx.doi.org/10.1364/OL.39.005192 OPLEDPOPLEDP 0146-9592 Google Scholar

44. 

Y. Zhou et al., “Microcirculatory changes identified by photoacoustic microscopy in patients with complex regional pain syndrome type I after stellate ganglion blocks,” J. Biomed. Opt., 19 (8), 086017 (2014). http://dx.doi.org/10.1117/1.JBO.19.8.086017 JBOPFOJBOPFO 1083-3668 Google Scholar

45. 

L. D. Wang et al., “Fast voice-coil scanning optical-resolution photoacoustic microscopy,” Opt. Lett., 36 (2), 139 –141 (2011). http://dx.doi.org/10.1364/OL.36.000139 OPLEDPOPLEDP 0146-9592 Google Scholar

46. 

C. Yeh et al., “Three-dimensional arbitrary trajectory scanning photoacoustic microscopy,” J. Biophotonics, 8 (4), 303 –308 (2015). http://dx.doi.org/10.1002/jbio.v8.4 Google Scholar

47. 

J. J. Yao et al., “High-speed label-free functional photoacoustic microscopy of mouse brain in action,” Nat. Methods, 12 (5), 407 –410 (2015). http://dx.doi.org/10.1038/nmeth.3336 1548-7091 Google Scholar

48. 

J. J. Yao et al., “Label-free oxygen-metabolic photoacoustic microscopy in vivo,” J. Biomed. Opt., 16 (7), 076003 (2011). http://dx.doi.org/10.1117/1.3594786 JBOPFOJBOPFO 1083-3668 Google Scholar

49. 

L. D. Wang, K. Maslov and L. V. Wang, “Single-cell label-free photoacoustic flowoxigraphy in vivo,” Proc. Natl. Acad. Sci. U. S. A., 110 (15), 5759 –5764 (2013). http://dx.doi.org/10.1073/pnas.1215578110 Google Scholar

50. 

H. F. Zhang, K. Maslov and M. Sivaramakrishnan, “Imaging of hemoglobin oxygen saturation variations in single vessels in vivo using photoacoustic microscopy,” Appl. Phys. Lett., 90 (5), 053901 (2007). http://dx.doi.org/10.1063/1.2435697 APPLABAPPLAB 0003-6951 Google Scholar

51. 

X. Wang et al., “Noninvasive imaging of hemoglobin concentration and oxygenation in the rat brain using high-resolution photoacoustic tomography,” J. Biomed. Opt., 11 (2), 024015 (2006). http://dx.doi.org/10.1117/1.2192804 JBOPFOJBOPFO 1083-3668 Google Scholar

52. 

S. Hu and L. H. V. Wang, “Optical-resolution photoacoustic microscopy: auscultation of biological systems at the cellular level,” Biophys. J., 105 (4), 841 –847 (2013). http://dx.doi.org/10.1016/j.bpj.2013.07.017 Google Scholar

53. 

Y. H. Liao et al., “Quantitative analysis of intrinsic skin aging in dermal papillae by in vivo harmonic generation microscopy,” Biomed. Opt. Express, 5 (9), 3266 –3279 (2014). http://dx.doi.org/10.1364/BOE.5.003266 BOEICLBOEICL 2156-7085 Google Scholar

54. 

R. O’Rahilly and F. Muller, Basic Human Anatomy: A Regional Study of Human Structure, W. B. Saunders Co.(1982). Google Scholar

55. 

W. Dzwinel, K. Boryczko and D. A. Yuen, “A discrete-particle model of blood dynamics in capillary vessels,” J. Colloid Interface Sci., 258 (1), 163 –173 (2003). http://dx.doi.org/10.1016/S0021-9797(02)00075-9 JCISA5JCISA5 0021-9797 Google Scholar

56. 

K. Sriram, M. Intaglietta and D. M. Tartakovsky, “Non-Newtonian flow of blood in arterioles: consequences for wall shear stress measurements,” Microcirculation, 21 (7), 628 –639 (2014). http://dx.doi.org/10.1111/micc.2014.21.issue-7 MCCRD8MCCRD8 0275-4177 Google Scholar

57. 

H. E. A. Baieth, “Physical parameters of blood as a non-Newtonian fluid,” Int. J. Biomed. Sci., 4 (4), 323 –329 (2008). Google Scholar

58. 

Y. Zheng et al., “A model of the hemodynamic response and oxygen delivery to brain,” NeuroImage, 16 (3), 617 –637 (2002). http://dx.doi.org/10.1006/nimg.2002.1078 NEIMEFNEIMEF 1053-8119 Google Scholar

Biography

Hsun-Chia Hsu is currently a graduate student in biomedical engineering at Washington University in St. Louis under the supervision of Dr. Lihong Wang. He received his BS and MS degrees in physics from National Taiwan University. His research focuses on the development and application of optical-resolution photoacoustic microscopy.

Lidai Wang is an assistant professor in department of mechanical and biomedical engineering at City University of Hong Kong since 2015. He worked as a postdoctoral research fellow in Washington University in St. Louis. His research focuses on biophotonics, biomedical imaging, wavefront engineering, instrumentation, and their biomedical applications. He has published 30 articles in peer-reviewed journals and has received four best paper awards from international conferences.

Lihong V. Wang, the Beare Distinguished Professor at Washington University in St. Louis, has published 450 journal articles (h-index = 104, citations > 43,000) and delivered 440 keynote/plenary/invited talks. His laboratory published the first functional photoacoustic CT and 3D photoacoustic microscopy. He received the Goodman Award for his Biomedical Optics textbook, NIH Director’s Pioneer Award, OSA Mees Medal, IEEE Technical Achievement and Biomedical Engineering Awards, SPIE Britton Chance Biomedical Optics Award, and an honorary doctorate from Lund University, Sweden.

© 2016 Society of Photo-Optical Instrumentation Engineers (SPIE) 1083-3668/2016/$25.00 © 2016 SPIE
Hsun-Chia Hsu, Lidai Wang, and Lihong V. Wang "In vivo photoacoustic microscopy of human cuticle microvasculature with single-cell resolution," Journal of Biomedical Optics 21(5), 056004 (18 May 2016). https://doi.org/10.1117/1.JBO.21.5.056004
Published: 18 May 2016
Lens.org Logo
CITATIONS
Cited by 28 scholarly publications and 1 patent.
Advertisement
Advertisement
RIGHTS & PERMISSIONS
Get copyright permission  Get copyright permission on Copyright Marketplace
KEYWORDS
Capillaries

Oxygen

Blood

In vivo imaging

Blood circulation

Photoacoustic microscopy

Image resolution

Back to Top