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Virtual Journal for Biomedical Optics

Virtual Journal for Biomedical Optics

| EXPLORING THE INTERFACE OF LIGHT AND BIOMEDICINE

  • Editors: Andrew Dunn and Anthony Durkin
  • Vol. 6, Iss. 4 — May. 4, 2011
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In vivo three-dimensional optical coherence elastography

Brendan F. Kennedy, Xing Liang, Steven G. Adie, Derek K. Gerstmann, Bryden C. Quirk, Stephen A. Boppart, and David D. Sampson  »View Author Affiliations


Optics Express, Vol. 19, Issue 7, pp. 6623-6634 (2011)
http://dx.doi.org/10.1364/OE.19.006623


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Abstract

Abstract: We present the first three-dimensional (3D) data sets recorded using optical coherence elastography (OCE). Uni-axial strain rate was measured on human skin in vivo using a spectral-domain optical coherence tomography (OCT) system providing >450 times higher line rate than previously reported for in vivo OCE imaging. Mechanical excitation was applied at a frequency of 125 Hz using a ring actuator sample arm with, for the first time in OCE measurements, a controlled static preload. We performed 3D-OCE, processed in 2D and displayed in 3D, on normal and hydrated skin and observed a more elastic response of the stratum corneum in the hydrated case.

© 2011 OSA

Data sets associated with this article are available at http://hdl.handle.net/10376/1561. Links such as View 1 that appear in figure captions and elsewhere will launch custom data views if ISP software is present.

1. Introduction

It is well known that pathological tissue is often stiffer than healthy tissue [1

1. Y. C. Fung, Biomechanics: Mechanical Properties of Living Tissue (Springer-Verlag, 1993).

]. Much research has focused on using the elastic properties of tissue as a contrast mechanism to form images, a technique known as elastography [2

2. J. F. Greenleaf, M. Fatemi, and M. Insana, “Selected methods for imaging elastic properties of biological tissues,” Annu. Rev. Biomed. Eng. 5(1), 57–78 (2003). [CrossRef] [PubMed]

,3

3. M. Fatemi, A. Manduca, and J. F. Greenleaf, “Imaging elastic properties of biological tissues by low-frequency harmonic vibration,” Proc. IEEE 91(10), 1503–1519 (2003). [CrossRef]

]. Initial elastography techniques used ultrasound [4

4. J. Ophir, I. Céspedes, H. Ponnekanti, Y. Yazdi, and X. Li, “Elastography: a quantitative method for imaging the elasticity of biological tissues,” Ultrason. Imaging 13(2), 111–134 (1991). [CrossRef] [PubMed]

] and magnetic resonance imaging (MRI) [5

5. R. Muthupillai, D. J. Lomas, P. J. Rossman, J. F. Greenleaf, A. Manduca, and R. L. Ehman, “Magnetic resonance elastography by direct visualization of propagating acoustic strain waves,” Science 269(5232), 1854–1857 (1995). [CrossRef] [PubMed]

] as the underlying imaging modalities and in vivo elastography has been proposed for clinical applications in the diagnosis of breast cancer [6

6. A. Itoh, E. Ueno, E. Tohno, H. Kamma, H. Takahashi, T. Shiina, M. Yamakawa, and T. Matsumura, “Breast disease: clinical application of US elastography for diagnosis,” Radiology 239(2), 341–350 (2006). [CrossRef] [PubMed]

,7

7. A. L. McKnight, J. L. Kugel, P. J. Rossman, A. Manduca, L. C. Hartmann, and R. L. Ehman, “MR elastography of breast cancer: preliminary results,” AJR Am. J. Roentgenol. 178(6), 1411–1417 (2002). [PubMed]

], prostate cancer [8

8. D. L. Cochlin, R. H. Ganatra, and D. F. R. Griffiths, “Elastography in the detection of prostatic cancer,” Clin. Radiol. 57(11), 1014–1020 (2002). [CrossRef] [PubMed]

], cirrhosis of the liver [9

9. J. Foucher, E. Chanteloup, J. Vergniol, L. Castéra, B. Le Bail, X. Adhoute, J. Bertet, P. Couzigou, and V. de Lédinghen, “Diagnosis of cirrhosis by transient elastography (FibroScan): a prospective study,” Gut 55(3), 403–408 (2006). [CrossRef]

], brain tumors [10

10. S. A. Kruse, G. H. Rose, K. J. Glaser, A. Manduca, J. P. Felmlee, C. R. Jack Jr, and R. L. Ehman, “Magnetic resonance elastography of the brain,” Neuroimage 39(1), 231–237 (2008). [CrossRef]

] and atherosclerosis [11

11. C. L. de Korte, G. Pasterkamp, A. F. W. van der Steen, H. A. Woutman, and N. Bom, “Characterization of plaque components with intravascular ultrasound elastography in human femoral and coronary arteries in vitro,” Circulation 102(6), 617–623 (2000). [PubMed]

].

The first optical elastography to have been developed is optical coherence elastography (OCE), which uses optical coherence tomography (OCT) as the underlying imaging modality [12

12. J. M. Schmitt, “OCT elastography: imaging microscopic deformation and strain of tissue,” Opt. Express 3(6), 199–211 (1998). [CrossRef] [PubMed]

23

23. S. G. Adie, X. Liang, B. F. Kennedy, R. John, D. D. Sampson, and S. A. Boppart, “Spectroscopic optical coherence elastography,” Opt. Express 18(25), 25519–25534 (2010). [CrossRef] [PubMed]

]. The spatial resolution of OCE, as set by OCT, is typically 1-10 μm; at least an order of magnitude higher than ultrasound- and MRI-based elastography. OCE has been proposed for application in dermatology [12

12. J. M. Schmitt, “OCT elastography: imaging microscopic deformation and strain of tissue,” Opt. Express 3(6), 199–211 (1998). [CrossRef] [PubMed]

,19

19. S. G. Adie, B. F. Kennedy, J. J. Armstrong, S. A. Alexandrov, and D. D. Sampson, “Audio frequency in vivo optical coherence elastography,” Phys. Med. Biol. 54(10), 3129–3139 (2009). [CrossRef] [PubMed]

21

21. X. Liang and S. A. Boppart, “Biomechanical properties of in vivo human skin from dynamic optical coherence elastography,” IEEE Trans. Biomed. Eng. 57(4), 953–959 (2010). [CrossRef]

], atherosclerosis [13

13. R. C. Chan, A. H. Chau, W. C. Karl, S. Nadkarni, A. S. Khalil, N. Iftimia, M. Shishkov, G. J. Tearney, M. R. Kaazempur-Mofrad, and B. E. Bouma, “OCT-based arterial elastography: robust estimation exploiting tissue biomechanics,” Opt. Express 12(19), 4558–4572 (2004). [CrossRef] [PubMed]

,14

14. J. Rogowska, N. A. Patel, J. G. Fujimoto, and M. E. Brezinski, “Optical coherence tomographic elastography technique for measuring deformation and strain of atherosclerotic tissues,” Heart 90(5), 556–562 (2004). [CrossRef] [PubMed]

], tissue engineering [15

15. H. J. Ko, W. Tan, R. Stack, and S. A. Boppart, “Optical coherence elastography of engineered and developing tissue,” Tissue Eng. 12(1), 63–73 (2006). [CrossRef] [PubMed]

], and tumor margin [18

18. X. Liang, A. L. Oldenburg, V. Crecea, E. J. Chaney, and S. A. Boppart, “Optical micro-scale mapping of dynamic biomechanical tissue properties,” Opt. Express 16(15), 11052–11065 (2008). [CrossRef] [PubMed]

,22

22. X. Liang, S. G. Adie, R. John, and S. A. Boppart, “Dynamic spectral-domain optical coherence elastography for tissue characterization,” Opt. Express 18(13), 14183–14190 (2010). [CrossRef] [PubMed]

,23

23. S. G. Adie, X. Liang, B. F. Kennedy, R. John, D. D. Sampson, and S. A. Boppart, “Spectroscopic optical coherence elastography,” Opt. Express 18(25), 25519–25534 (2010). [CrossRef] [PubMed]

]. The ability to perform routine in vivo measurements is a key prerequisite for the clinical application of OCE. To date, however, there have been only three demonstrations of in vivo OCE imaging [12

12. J. M. Schmitt, “OCT elastography: imaging microscopic deformation and strain of tissue,” Opt. Express 3(6), 199–211 (1998). [CrossRef] [PubMed]

,19

19. S. G. Adie, B. F. Kennedy, J. J. Armstrong, S. A. Alexandrov, and D. D. Sampson, “Audio frequency in vivo optical coherence elastography,” Phys. Med. Biol. 54(10), 3129–3139 (2009). [CrossRef] [PubMed]

,20

20. B. F. Kennedy, T. R. Hillman, R. A. McLaughlin, B. C. Quirk, and D. D. Sampson, “In vivo dynamic optical coherence elastography using a ring actuator,” Opt. Express 17(24), 21762–21772 (2009). [CrossRef] [PubMed]

]. In the first, in vivo images of human skin were recorded with a TD-OCT system at maximum line rates of 11 Hz [12

12. J. M. Schmitt, “OCT elastography: imaging microscopic deformation and strain of tissue,” Opt. Express 3(6), 199–211 (1998). [CrossRef] [PubMed]

]. Due to the large preload applied, at least one minute was required to allow internal strain dissipation prior to imaging. More recently, an audio-frequency sub-micron excitation technique has been reported, which overcame the need to allow strain dissipation [19

19. S. G. Adie, B. F. Kennedy, J. J. Armstrong, S. A. Alexandrov, and D. D. Sampson, “Audio frequency in vivo optical coherence elastography,” Phys. Med. Biol. 54(10), 3129–3139 (2009). [CrossRef] [PubMed]

,20

20. B. F. Kennedy, T. R. Hillman, R. A. McLaughlin, B. C. Quirk, and D. D. Sampson, “In vivo dynamic optical coherence elastography using a ring actuator,” Opt. Express 17(24), 21762–21772 (2009). [CrossRef] [PubMed]

]. It was also demonstrated on human skin using a TD-OCT system, and the line rate was limited to ~1 Hz. Such long acquisition times are impractical for in vivo imaging in a clinical setting and result in large motion artifacts.

In this paper, we perform for the first time in vivo OCE imaging using a spectral-domain OCT (SD-OCT) system. This technique, similar to Doppler SD-OCT [24

24. R. Leitgeb, L. Schmetterer, W. Drexler, A. F. Fercher, R. J. Zawadzki, and T. Bajraszewski, “Real-time assessment of retinal blood flow with ultrafast acquisition by color Doppler Fourier domain optical coherence tomography,” Opt. Express 11(23), 3116–3121 (2003). [CrossRef] [PubMed]

], is based on a dynamic OCE technique recently proposed [22

22. X. Liang, S. G. Adie, R. John, and S. A. Boppart, “Dynamic spectral-domain optical coherence elastography for tissue characterization,” Opt. Express 18(13), 14183–14190 (2010). [CrossRef] [PubMed]

]. Here, we report its operation at a line rate of 5 kHz; >450 times higher than in vivo OCE imaging reported to date. The use of SD-OCT provides rapid acquisition whilst maintaining high signal-to-noise [25

25. R. Leitgeb, C. K. Hitzenberger, and A. F. Fercher, “Performance of fourier domain vs. time domain optical coherence tomography,” Opt. Express 11(8), 889–894 (2003). [CrossRef] [PubMed]

,26

26. J. F. de Boer, B. Cense, B. H. Park, M. C. Pierce, G. J. Tearney, and B. E. Bouma, “Improved signal-to-noise ratio in spectral-domain compared with time-domain optical coherence tomography,” Opt. Lett. 28(21), 2067–2069 (2003). [CrossRef] [PubMed]

], thus, enabling three-dimensional (3D) imaging [27

27. M. Wojtkowski, T. Bajraszewski, P. Targowski, and A. Kowalczyk, “Real-time in vivo imaging by high-speed spectral optical coherence tomography,” Opt. Lett. 28(19), 1745–1747 (2003). [CrossRef] [PubMed]

,28

28. N. Nassif, B. Cense, B. Park, M. Pierce, S. Yun, B. Bouma, G. Tearney, T. Chen, and J. de Boer, “In vivo high-resolution video-rate spectral-domain optical coherence tomography of the human retina and optic nerve,” Opt. Express 12(3), 367–376 (2004). [CrossRef] [PubMed]

]. 3D imaging of such features as pathological regions of tissue has the potential to greatly increase the utility and impact of OCE in a clinical setting. We combine this approach with two key practical requirements required for in vivo imaging. We employ a ring actuator sample arm [20

20. B. F. Kennedy, T. R. Hillman, R. A. McLaughlin, B. C. Quirk, and D. D. Sampson, “In vivo dynamic optical coherence elastography using a ring actuator,” Opt. Express 17(24), 21762–21772 (2009). [CrossRef] [PubMed]

], enabling mechanical excitation to be introduced to tissue from the same side as the OCT beam. Using a custom-built force sensor, we apply a controlled preload to tissue to avoid the large variations in strain that have been reported as a function of preload [29

29. T. A. Krouskop, T. M. Wheeler, F. Kallel, B. S. Garra, and T. Hall, “Elastic moduli of breast and prostate tissues under compression,” Ultrason. Imaging 20(4), 260–274 (1998).

]. Constant preload is important if an accurate comparison is to be made between images recorded from different locations. We demonstrate in vivo 3D-OCE imaging on both normal and hydrated skin and report a more elastic response of the stratum corneum in hydrated skin.

2. Experimental setup

The 3D-OCE system reported here is based on an SD-OCT system operating with line rate of 5 kHz and B-scan rate in the range 0.7-2.5 Hz. A schematic diagram of the system is presented in Fig. 1(a)
Fig. 1 (a) Schematic diagram of the OCE system; C: CCD camera, L1-L5: lenses, G: diffraction grating, PC1-PC4: polarization controllers, FC: 50/50 fiber coupler, M: mirror, FS: force sensor, SC: Scancube, SA: sample arm. A schematic of the sample arm is presented in the inset; (b) Photograph of the sample arm; and (c) Contrast ratio (ratio of strain rate magnitude) between stratum corneum and epidermis versus preload.
. The optical source comprised a Nd:YVO4-pumped titanium-sapphire laser (pulse width ~100 fs, repetition rate 80 MHz), with a center wavelength of 800 nm and a 3 dB bandwidth of 100 nm, providing a theoretical axial resolution of 2.8 μm. The average power incident on skin was 7 mW. The sample arm contained a triplet lens to focus the optical beam through a 2 mm-thick glass window fixed to the surface of a piezoelectric ring actuator. This arrangement provided a theoretical lateral resolution of 15 μm. Lateral scanning was performed using a Scancube®7 (Scanlab AG, Puchheim, Germany) x-y galvanometer mirror pair. The spectrometer consisted of a 100 mm-focal-length lens, an 830 lines/mm diffraction grating, and a CCD line camera (1024 pixels). Data were recorded on a PC with a 3.2 GHz Intel Xeon processor and 2 GB of RAM. The measured sensitivity was 94 dB at a depth of 280 μm, rolling off to 81 dB at a depth of 1 mm and the axial measurement range was 2 mm. The phase noise was measured to be 53 mrad, for an SNR of 44 dB. The phase noise was calculated using a method described previously [30

30. B. H. Park, M. C. Pierce, B. Cense, S.-H. Yun, M. Mujat, G. J. Tearney, B. E. Bouma, and J. F. de Boer, “Real-time fiber-based multi-functional spectral-domain optical coherence tomography at 1.3 microm,” Opt. Express 13(11), 3931–3944 (2005). [CrossRef] [PubMed]

].

Dynamic uni-axial compressive loading was applied to skin by bringing it into contact with the ring actuator. The glass window compressed the skin against the underlying bone, which acted as a rigid body, operating from the same side as the illumination beam. The ring actuator had an aperture of 9 mm, maximum stroke of 12 μm, stiffness of 250 N/μm and resonance frequency of 45 kHz. A sinusoidal excitation signal was introduced to skin with unloaded amplitude in the range 1-6 μm and frequency in the range 50-250 Hz. No variation in skin elasticity was measured over these ranges. Given this observation, an amplitude of 4 μm and frequency of 125 Hz were arbitrarily chosen for all subsequent measurements.

A schematic of the ring actuator sample arm is presented in the inset of Fig. 1(a). The lens, ring actuator and glass window were fixed in a two-section aluminum casing of 30 mm diameter and 45 mm total height. The lens was fixed in the first section and the ring actuator was fixed to the base of the second section using epoxy. The two sections were coupled with an adjustable thread allowing the beam to be focused to different depths within the sample. A photograph of the sample arm is presented in Fig. 1(b).

3. Experimental method

The method used to generate OCE B-scan images has been presented in detail previously [22

22. X. Liang, S. G. Adie, R. John, and S. A. Boppart, “Dynamic spectral-domain optical coherence elastography for tissue characterization,” Opt. Express 18(13), 14183–14190 (2010). [CrossRef] [PubMed]

], so only a brief description is provided here. OCT B-scans of skin were recorded during external dynamic excitation. Local skin displacement as a function of depth was determined at each lateral position by calculating the phase difference, Δϕ, between consecutive A-scans, resulting in a 2D phase-difference map modulated at the excitation frequency. To generate OCE images, strain rate was calculated. Strain rate, εm (s−1), is the rate at which deformation occurs and is commonly used in presenting images in ultrasound elastography [31

31. J. D’hooge, A. Heimdal, F. Jamal, T. Kukulski, B. Bijnens, F. Rademakers, L. Hatle, P. Suetens, and G. R. Sutherland, “Regional strain and strain rate measurements by cardiac ultrasound: principles, implementation and limitations,” Eur. J. Echocardiogr. 1(3), 154–170 (2000). [CrossRef]

], as well as in OCE [16

16. R. K. Wang, Z. H. Ma, and S. J. Kirkpatrick, “Tissue Doppler optical coherence elastography for real time strain rate and strain mapping of soft tissue,” Appl. Phys. Lett. 89(14), 144103 (2006). [CrossRef]

,17

17. S. J. Kirkpatrick, R. K. Wang, and D. D. Duncan, “OCT-based elastography for large and small deformations,” Opt. Express 14(24), 11585–11597 (2006). [CrossRef] [PubMed]

,22

22. X. Liang, S. G. Adie, R. John, and S. A. Boppart, “Dynamic spectral-domain optical coherence elastography for tissue characterization,” Opt. Express 18(13), 14183–14190 (2010). [CrossRef] [PubMed]

], in order to differentiate tissues based on elastic properties. It may be defined as:
εm'(z,t)=1z0ΔdΔt=Δφ(z,t)λ4πnΔtz0,
(1)
where Δd is the displacement and Δt is the time interval between successive A-scans, λ is the mean wavelength of the light source, n is the refractive index of the sample, assumed to be 1.4 for human skin, and z0 is the original thickness of the sample. For measurements of the fingertip, z0 is the distance to the underlying bone, assumed to be 2 mm in the results presented here [12

12. J. M. Schmitt, “OCT elastography: imaging microscopic deformation and strain of tissue,” Opt. Express 3(6), 199–211 (1998). [CrossRef] [PubMed]

].

In the technique reported here, the value of each pixel in an image is equal to the strain rate magnitude introduced to the sample at that location [22

22. X. Liang, S. G. Adie, R. John, and S. A. Boppart, “Dynamic spectral-domain optical coherence elastography for tissue characterization,” Opt. Express 18(13), 14183–14190 (2010). [CrossRef] [PubMed]

]. Each pixel, therefore, represents one excitation cycle. To optimize the OCE axial resolution, Δz OCE, the excitation amplitude should be less than the OCT axial resolution. The OCE lateral resolution, Δx OCE, corresponds to the distance scanned by the optical beam in one excitation cycle. It may be defined as the ratio of lateral scan range, SRl, to the number of excitation cycles, PN, introduced in one B-scan. For optimum resolution, this ratio should be less than the lateral resolution of the OCT system:
SRlPN<ΔxOCT,
(2)
where ΔxOCT corresponds to the OCT system lateral resolution. PN in Eq. (2) also determines the OCE B-scan acquisition time. For example, in the OCE results presented in Fig. 3
Fig. 3 (a) OCT; (b) OCE; and (c) overlaid images of in vivo skin on the middle finger. In (a), the stratum corneum (SC), living epidermis (LE), imaging plate and a sweat gland are labeled. Image dimensions are 1.4 mm × 1.4 mm.
below, 175 excitation cycles were introduced across a lateral range of 2 mm. For an excitation frequency of 125 Hz, this corresponds to a B-scan acquisition time of 1.4 s. In Fig. 2(a)
Fig. 2 Axial and lateral resolution of OCE images. (a) Strain rate image recorded on human skin in vivo (image dimensions (x-z) are 600 μm × 800 μm); (b) Strain rate measured at depth 150 μm, indicated by black line in (a); (c) Highlighted region of (b) indicating how axial and lateral resolutions in OCE images are determined.
, a strain rate image measured from human skin in vivo is presented. Modulation of the strain rate image due to dynamic excitation at 125 Hz is visible. In Fig. 2(b), a plot of the strain rate introduced at a depth of 150 μm, indicated by the black line in (a), is presented. The OCE image resolution is determined by measuring the amplitude (axial resolution) and period (lateral resolution) of this modulation, as illustrated in Fig. 2(c).

A lateral displacement of the probing light beam in the range 0.2-1 μm was introduced between each A-scan. This oversampling with respect to the lateral resolution of the OCT system minimized phase error due to lateral scanning. The phase error is also dependent on the SNR of the OCT signal [30

30. B. H. Park, M. C. Pierce, B. Cense, S.-H. Yun, M. Mujat, G. J. Tearney, B. E. Bouma, and J. F. de Boer, “Real-time fiber-based multi-functional spectral-domain optical coherence tomography at 1.3 microm,” Opt. Express 13(11), 3931–3944 (2005). [CrossRef] [PubMed]

]. The excitation frequency and amplitude selected ensured the phase difference caused by sample motion between A-scans was always less than |π|, setting an upper limit for strain rate measurement of ~0.35 s−1. In regions of the image with low SNR, phase wrapping errors can lead to inaccurate measurement of strain rate. To ameliorate this problem, we thresholded the OCT signal prior to calculating the phase difference [17

17. S. J. Kirkpatrick, R. K. Wang, and D. D. Duncan, “OCT-based elastography for large and small deformations,” Opt. Express 14(24), 11585–11597 (2006). [CrossRef] [PubMed]

], using a threshold of 10 dB above the noise floor. This corresponds to a phase sensitivity of 0.3 rad and a minimum measurable strain rate of 0.03 s−1. A digital 30-Hz band-pass filter centered at the excitation frequency of 125 Hz was applied to the phase difference data to further reduce noise.

In all results presented in Section 4, the OCT and OCE images were generated from the same complex OCT data sets acquired under mechanical excitation. This minimized acquisition time and ensured that each pair of OCT and OCE images were recorded from the same region of tissue.

4. Results

A significant improvement in OCE image resolution is visible in Fig. 3 in comparison to in vivo OCE images previously presented [12

12. J. M. Schmitt, “OCT elastography: imaging microscopic deformation and strain of tissue,” Opt. Express 3(6), 199–211 (1998). [CrossRef] [PubMed]

,19

19. S. G. Adie, B. F. Kennedy, J. J. Armstrong, S. A. Alexandrov, and D. D. Sampson, “Audio frequency in vivo optical coherence elastography,” Phys. Med. Biol. 54(10), 3129–3139 (2009). [CrossRef] [PubMed]

,20

20. B. F. Kennedy, T. R. Hillman, R. A. McLaughlin, B. C. Quirk, and D. D. Sampson, “In vivo dynamic optical coherence elastography using a ring actuator,” Opt. Express 17(24), 21762–21772 (2009). [CrossRef] [PubMed]

]. This is largely due to the faster acquisition speed obtained by using the SD-OCT system, which results in significantly reduced motion artifacts.

3D-OCT and OCE images of skin from the middle finger of the same subject are presented in Fig. 4
Fig. 4 3D visualization of in vivo skin from the middle finger of a male subject. (a) OCT, (b) OCE, and (c) overlay, from first perspective view; (d) OCT, (e) OCE, and (f) overlay, from second perspective view; (g) OCT, (h) OCE and (i) overlay, from en face view of skin surface; (j) OCT, (k) OCE and (l) overlay, from en face view at depth of 300 μm. The arrows in (j) indicate shadow artifacts due to overlying sweat glands. Volume dimensions (xyz) are 2 mm × 1 mm × 1 mm. Full 3D data sets also available, View 1 (OCT) and View 2 (OCE).
. OCE B-scans at each y-position were generated using the technique described above. The total acquisition time for a 3D-OCE data set was 5 min for images with dimensions (xyz) of 2 mm × 1 mm × 1 mm. To reduce motion artifacts, the finger was strapped in position prior to each measurement. To keep the acquisition time as short as possible, only 50 excitation cycles per B-scan were used; reducing the B-scan acquisition time to 0.4 s. This was achieved by reducing the number of A-scans per B-scan from 7,000 to 2,000; resulting in a lateral resolution of 40 μm in the x-direction. The reduction of spatial resolution is visible in Fig. 4. In the z-direction, there are 1,024 pixels and in the y-direction, 100 pixels (1-mm range). The raw OCE and OCT data sets were cropped and transformed within an image processing package [34

34. “Fiji is just ImageJ,” http://pacific.mpi-cbg.de/wiki/index.php/.

] and then normalized so that the intensity range was 0.0-1.0 [35

35. S. I. O’Donoghue, A.-C. Gavin, N. Gehlenborg, D. S. Goodsell, J.-K. Heriche, C. B. Nielsen, C. North, A. J. Olson, J. B. Procter, D. W. Shattuck, T. Walter, and B. Wong, “Visualizing biological data-now and in the future,” Nat. Methods 7(3), S1–S4 (2010). [CrossRef]

]. The data sets were then imported into a volume exploration and presentation tool [36

36. A. Limaye, “Drishti-volume exploration and presentation tool,” IEEE Visual., Baltimore, USA (2006).

], and reconstructed into 3D data sets at full resolution. The corresponding visualizations were produced from view-aligned, slice-based rendering. Final pixel contributions were defined by applying a two-dimensional transfer function that weighted the opacity and color of each voxel based on the intensity and gradient value in the volumetric data sets.

In Figs. 4(a) and 4(d), two perspective views of the OCT data are presented, with one corner cut away to a depth of 300 μm, revealing internal structure. In Figs. 4(b) and 4(e), the OCE signal is displayed and, in Figs. 4(c) and 4(f), the OCE data is overlaid on the OCT data, as in Fig. 3(c). In these images, the highest OCE signal is visible in the living epidermis and the sweat glands, consistent with the result presented in Fig. 3. In Figs. 4(g)-4(i) en face views from the surface of the tissue are presented. In the OCT image, presented in Fig. 4(g), sweat glands are visible as regions of high signal intensity. Large variations in the strain rate magnitude are visible in Fig. 4(h) in the regions corresponding to sweat glands in Fig. 4(g). Additional regions of high OCE signal in Fig. 4(h) may correspond to sweat glands not visible in the OCT data. The OCE signal overlaid on the OCT signal is presented in Fig. 4(i). A second en face view is presented in Figs. 4(j)-4(l) at a depth of 300 μm. The regions of high OCT signal at this depth correspond to the living epidermis. Shadows of the sweat glands are visible in Fig. 4(j). Several of these shadow artifacts are indicated in the figure (white arrows). In the OCE images presented in Fig. 4(k), the living epidermis is represented by regions of high OCE signal. This is consistent with the result presented in Fig. 3. The OCE signal overlaid on the OCT signal is presented in Fig. 4(l). The full 3D data sets are also available, View 1 (OCT) and View 2 (OCE).

The skin on the middle finger of the same subject was hydrated in warm water for 30 min and then imaged with the same acquisition settings, preload, excitation amplitude and frequency, and median filtering as for the images presented in Fig. 3. An OCT image of the hydrated skin is presented in Fig. 5(a)
Fig. 5 (a) OCT; (b); OCE and; (c) overlaid images of the in vivo hydrated skin on the middle finger. Image dimensions are 1.4 mm × 1.4 mm.
. The imaging plate, stratum corneum and living epidermis are readily distinguished. The OCE image is presented in Fig. 5(b). The contrast between stratum corneum and living epidermis is reduced in comparison to the results presented in Fig. 3(b). This is attributed to a more elastic response of the stratum corneum in the hydrated case [37

37. R. O. Potts and D. A. Chrisman, Jr., andE. M. Buras, Jr., “The dynamic mechanical properties of human skin in vivo,” J. Biomech. 16(6), 365–372 (1983). [CrossRef] [PubMed]

]. An artifact is visible in Fig. 5 – the surface of the imaging plate appears not to be perfectly flat. We believe that this is caused by a variation in the thickness of the index-matching glycerol used, which results in a slight variation in the optical path length. As in Fig. 3(c), in Fig. 5(c) the top 40% of the OCE signal (color map) is overlaid on the OCT signal (grayscale).

3D-OCT and OCE imaging were also performed on the hydrated skin and are presented in Fig. 6
Fig. 6 In vivo 3D visualizations of hydrated skin from the middle finger of a male subject. (a) OCT, (b) OCE, and (c) overlay, from first perspective view; (d) OCT, (e) OCE, and (f) overlay, from second perspective view; (g) OCT, (h) OCE and (i) overlay, from en face view of skin surface; (j) OCT, (k) OCE and (l) overlay, from en face view at depth of 300 μm. Volume dimensions (xyz) are 2 mm × 1 mm × 1 mm. Full 3D data sets also available, View 3 (OCT) and View 4 (OCE).
. In the hydrated 3D-OCE case, 250 excitation cycles were introduced across a lateral range of 2 mm, compared with 50 excitation cycles across the same distance in Fig. 4. This resulted in the lateral resolution in the x-direction being determined by the lateral resolution of the OCT system. The trade-off is that the acquisition time increased by a factor of five, resulting in an acquisition time of 25 min, and motion artifacts became more prominent and were manifested by geometrical distortion of skin features.

In a similar manner to the results presented in Figs. 4(a) and 4(d), in Figs. 6(a) and 6(d) perspective views of the OCT data from the hydrated skin are presented, with one corner cut away to a depth of 300 μm, revealing internal structure. In Figs. 6(b) and 6(e), the OCE signal is displayed and, in Figs. 6(c) and 6(f), the OCE data is overlaid on the OCT data. On average the OCE signal is higher in the hydrated stratum corneum when compared with the unhydrated stratum corneum shown in Figs. 4(b) and 4(e), suggesting a more elastic response. In Figs. 6(g)-6(i), en face views from the surface of the tissue are presented. In comparison to Fig. 4(g), the hydrated en face OCT image from the skin surface (Fig. 6(g)) appears relatively uniform. The sweat glands are not visible in the hydrated case. However, large variations in the OCE image are visible in Fig. 6(h). We speculate that this is due to variations in the hydration state of the skin. A second en face view is presented in Figs. 6(j)-6(l) at a depth of 300 μm. Large variations in the OCE signal, possibly due to changes in hydration level, are also visible at this depth. The full 3D data sets are also available, View 3 (OCT) and View 4 (OCE).

5. Discussion

In OCE results presented to date, both the strain and the strain rate have been used to quantify the elastic properties of samples. In this paper, we presented strain rate images, consistent with recent reports on OCE [17

17. S. J. Kirkpatrick, R. K. Wang, and D. D. Duncan, “OCT-based elastography for large and small deformations,” Opt. Express 14(24), 11585–11597 (2006). [CrossRef] [PubMed]

,18

18. X. Liang, A. L. Oldenburg, V. Crecea, E. J. Chaney, and S. A. Boppart, “Optical micro-scale mapping of dynamic biomechanical tissue properties,” Opt. Express 16(15), 11052–11065 (2008). [CrossRef] [PubMed]

,22

22. X. Liang, S. G. Adie, R. John, and S. A. Boppart, “Dynamic spectral-domain optical coherence elastography for tissue characterization,” Opt. Express 18(13), 14183–14190 (2010). [CrossRef] [PubMed]

]. Since strain rate is the time rate of change of strain, the strain may be determined from it by integration over time.

Minimizing the impact of phase noise is an important consideration for OCE processing. In regions where the magnitude of the phase difference between A-scans is close to π, the addition of phase noise can result in phase wrapping errors that shift the effective frequency content of the vibration signal. In practice, the problem of phase wrapping induced by noise when the phase difference is close to π can be addressed by increasing the A-scan rate or reducing the actuator drive amplitude. Since phase noise increases with decreasing SNR, we utilized an SNR threshold as in [17

17. S. J. Kirkpatrick, R. K. Wang, and D. D. Duncan, “OCT-based elastography for large and small deformations,” Opt. Express 14(24), 11585–11597 (2006). [CrossRef] [PubMed]

], in which velocities corresponding to low SNR pixels were set to zero. Future investigations will examine post-processing techniques to minimize the impact of phase noise for large vibration amplitudes, particularly in regions with low SNR. In future work, we will also investigate using averaging and filtering techniques previously developed for Doppler OCT flow measurements [42

42. A. Szkulmowska, M. Szkulmowski, A. Kowalczyk, and M. Wojtkowski, “Phase-resolved Doppler optical coherence tomography--limitations and improvements,” Opt. Lett. 33(13), 1425–1427 (2008). [CrossRef] [PubMed]

].

The use of the force sensor demonstrated here is important because it enables repeatable measurements to be performed and ensures that the elastic properties of different samples are investigated under the same preload. Notably, large variations in the measured strain in tissues have been reported for relatively moderate increases in preload [29

29. T. A. Krouskop, T. M. Wheeler, F. Kallel, B. S. Garra, and T. Hall, “Elastic moduli of breast and prostate tissues under compression,” Ultrason. Imaging 20(4), 260–274 (1998).

]. For in vivo skin measurements, comparable results were obtained on several subjects, as well as on the same subject on different days (data not presented).

The ring actuator sample arm presented in this work could be used as the basis for a handheld probe for use in vivo. This could be readily achieved by fixing the cantilever force sensor to the scan cube casing.

6. Conclusions

We have presented the first 3D-OCE images. Experiments were performed on in vivo human skin with a constant preload applied by a custom-built ring actuator and integrated force sensor. Use of an SD-OCT system for image acquisition allowed >450-times higher line rate than previously reported for in vivo OCE imaging. 3D-OCE data, processed in 2D and displayed in 3D, were presented for both normal and hydrated human skin. OCE images showed strong correlation with the underlying OCT images. The strain rate of the hydrated stratum corneum was measured to be higher than that of the unhydrated stratum corneum, confirming a more elastic response, as expected. The results in this paper support the continued investigation of OCE as a technique for probing the elastic properties of tissue in vivo.

Acknowledgements

We would like to acknowledge the technical contributions of Dr. Robert McLaughlin, Dr. Haohua Tu, Dr. Renu John, Vasilica Crecea, and Yuan Liu to this paper. B.F.K. acknowledges funding support from a UWA Research Collaboration Award. This research was supported in part by grants from the National Institutes of Health (1 RC1 CA147096, S.A.B.) and the National Science Foundation (CBET 08-52658 ARRA, S.A.B.).

References and links

1.

Y. C. Fung, Biomechanics: Mechanical Properties of Living Tissue (Springer-Verlag, 1993).

2.

J. F. Greenleaf, M. Fatemi, and M. Insana, “Selected methods for imaging elastic properties of biological tissues,” Annu. Rev. Biomed. Eng. 5(1), 57–78 (2003). [CrossRef] [PubMed]

3.

M. Fatemi, A. Manduca, and J. F. Greenleaf, “Imaging elastic properties of biological tissues by low-frequency harmonic vibration,” Proc. IEEE 91(10), 1503–1519 (2003). [CrossRef]

4.

J. Ophir, I. Céspedes, H. Ponnekanti, Y. Yazdi, and X. Li, “Elastography: a quantitative method for imaging the elasticity of biological tissues,” Ultrason. Imaging 13(2), 111–134 (1991). [CrossRef] [PubMed]

5.

R. Muthupillai, D. J. Lomas, P. J. Rossman, J. F. Greenleaf, A. Manduca, and R. L. Ehman, “Magnetic resonance elastography by direct visualization of propagating acoustic strain waves,” Science 269(5232), 1854–1857 (1995). [CrossRef] [PubMed]

6.

A. Itoh, E. Ueno, E. Tohno, H. Kamma, H. Takahashi, T. Shiina, M. Yamakawa, and T. Matsumura, “Breast disease: clinical application of US elastography for diagnosis,” Radiology 239(2), 341–350 (2006). [CrossRef] [PubMed]

7.

A. L. McKnight, J. L. Kugel, P. J. Rossman, A. Manduca, L. C. Hartmann, and R. L. Ehman, “MR elastography of breast cancer: preliminary results,” AJR Am. J. Roentgenol. 178(6), 1411–1417 (2002). [PubMed]

8.

D. L. Cochlin, R. H. Ganatra, and D. F. R. Griffiths, “Elastography in the detection of prostatic cancer,” Clin. Radiol. 57(11), 1014–1020 (2002). [CrossRef] [PubMed]

9.

J. Foucher, E. Chanteloup, J. Vergniol, L. Castéra, B. Le Bail, X. Adhoute, J. Bertet, P. Couzigou, and V. de Lédinghen, “Diagnosis of cirrhosis by transient elastography (FibroScan): a prospective study,” Gut 55(3), 403–408 (2006). [CrossRef]

10.

S. A. Kruse, G. H. Rose, K. J. Glaser, A. Manduca, J. P. Felmlee, C. R. Jack Jr, and R. L. Ehman, “Magnetic resonance elastography of the brain,” Neuroimage 39(1), 231–237 (2008). [CrossRef]

11.

C. L. de Korte, G. Pasterkamp, A. F. W. van der Steen, H. A. Woutman, and N. Bom, “Characterization of plaque components with intravascular ultrasound elastography in human femoral and coronary arteries in vitro,” Circulation 102(6), 617–623 (2000). [PubMed]

12.

J. M. Schmitt, “OCT elastography: imaging microscopic deformation and strain of tissue,” Opt. Express 3(6), 199–211 (1998). [CrossRef] [PubMed]

13.

R. C. Chan, A. H. Chau, W. C. Karl, S. Nadkarni, A. S. Khalil, N. Iftimia, M. Shishkov, G. J. Tearney, M. R. Kaazempur-Mofrad, and B. E. Bouma, “OCT-based arterial elastography: robust estimation exploiting tissue biomechanics,” Opt. Express 12(19), 4558–4572 (2004). [CrossRef] [PubMed]

14.

J. Rogowska, N. A. Patel, J. G. Fujimoto, and M. E. Brezinski, “Optical coherence tomographic elastography technique for measuring deformation and strain of atherosclerotic tissues,” Heart 90(5), 556–562 (2004). [CrossRef] [PubMed]

15.

H. J. Ko, W. Tan, R. Stack, and S. A. Boppart, “Optical coherence elastography of engineered and developing tissue,” Tissue Eng. 12(1), 63–73 (2006). [CrossRef] [PubMed]

16.

R. K. Wang, Z. H. Ma, and S. J. Kirkpatrick, “Tissue Doppler optical coherence elastography for real time strain rate and strain mapping of soft tissue,” Appl. Phys. Lett. 89(14), 144103 (2006). [CrossRef]

17.

S. J. Kirkpatrick, R. K. Wang, and D. D. Duncan, “OCT-based elastography for large and small deformations,” Opt. Express 14(24), 11585–11597 (2006). [CrossRef] [PubMed]

18.

X. Liang, A. L. Oldenburg, V. Crecea, E. J. Chaney, and S. A. Boppart, “Optical micro-scale mapping of dynamic biomechanical tissue properties,” Opt. Express 16(15), 11052–11065 (2008). [CrossRef] [PubMed]

19.

S. G. Adie, B. F. Kennedy, J. J. Armstrong, S. A. Alexandrov, and D. D. Sampson, “Audio frequency in vivo optical coherence elastography,” Phys. Med. Biol. 54(10), 3129–3139 (2009). [CrossRef] [PubMed]

20.

B. F. Kennedy, T. R. Hillman, R. A. McLaughlin, B. C. Quirk, and D. D. Sampson, “In vivo dynamic optical coherence elastography using a ring actuator,” Opt. Express 17(24), 21762–21772 (2009). [CrossRef] [PubMed]

21.

X. Liang and S. A. Boppart, “Biomechanical properties of in vivo human skin from dynamic optical coherence elastography,” IEEE Trans. Biomed. Eng. 57(4), 953–959 (2010). [CrossRef]

22.

X. Liang, S. G. Adie, R. John, and S. A. Boppart, “Dynamic spectral-domain optical coherence elastography for tissue characterization,” Opt. Express 18(13), 14183–14190 (2010). [CrossRef] [PubMed]

23.

S. G. Adie, X. Liang, B. F. Kennedy, R. John, D. D. Sampson, and S. A. Boppart, “Spectroscopic optical coherence elastography,” Opt. Express 18(25), 25519–25534 (2010). [CrossRef] [PubMed]

24.

R. Leitgeb, L. Schmetterer, W. Drexler, A. F. Fercher, R. J. Zawadzki, and T. Bajraszewski, “Real-time assessment of retinal blood flow with ultrafast acquisition by color Doppler Fourier domain optical coherence tomography,” Opt. Express 11(23), 3116–3121 (2003). [CrossRef] [PubMed]

25.

R. Leitgeb, C. K. Hitzenberger, and A. F. Fercher, “Performance of fourier domain vs. time domain optical coherence tomography,” Opt. Express 11(8), 889–894 (2003). [CrossRef] [PubMed]

26.

J. F. de Boer, B. Cense, B. H. Park, M. C. Pierce, G. J. Tearney, and B. E. Bouma, “Improved signal-to-noise ratio in spectral-domain compared with time-domain optical coherence tomography,” Opt. Lett. 28(21), 2067–2069 (2003). [CrossRef] [PubMed]

27.

M. Wojtkowski, T. Bajraszewski, P. Targowski, and A. Kowalczyk, “Real-time in vivo imaging by high-speed spectral optical coherence tomography,” Opt. Lett. 28(19), 1745–1747 (2003). [CrossRef] [PubMed]

28.

N. Nassif, B. Cense, B. Park, M. Pierce, S. Yun, B. Bouma, G. Tearney, T. Chen, and J. de Boer, “In vivo high-resolution video-rate spectral-domain optical coherence tomography of the human retina and optic nerve,” Opt. Express 12(3), 367–376 (2004). [CrossRef] [PubMed]

29.

T. A. Krouskop, T. M. Wheeler, F. Kallel, B. S. Garra, and T. Hall, “Elastic moduli of breast and prostate tissues under compression,” Ultrason. Imaging 20(4), 260–274 (1998).

30.

B. H. Park, M. C. Pierce, B. Cense, S.-H. Yun, M. Mujat, G. J. Tearney, B. E. Bouma, and J. F. de Boer, “Real-time fiber-based multi-functional spectral-domain optical coherence tomography at 1.3 microm,” Opt. Express 13(11), 3931–3944 (2005). [CrossRef] [PubMed]

31.

J. D’hooge, A. Heimdal, F. Jamal, T. Kukulski, B. Bijnens, F. Rademakers, L. Hatle, P. Suetens, and G. R. Sutherland, “Regional strain and strain rate measurements by cardiac ultrasound: principles, implementation and limitations,” Eur. J. Echocardiogr. 1(3), 154–170 (2000). [CrossRef]

32.

T. Gambichler, G. Moussa, M. Sand, D. Sand, P. Altmeyer, and K. Hoffmann, “Applications of optical coherence tomography in dermatology,” J. Dermatol. Sci. 40(2), 85–94 (2005). [CrossRef] [PubMed]

33.

H. Fruhstorfer, U. Abel, C.-D. Garthe, and A. Knüttel, “Thickness of the stratum corneum of the volar fingertips,” Clin. Anat. 13(6), 429–433 (2000). [CrossRef] [PubMed]

34.

“Fiji is just ImageJ,” http://pacific.mpi-cbg.de/wiki/index.php/.

35.

S. I. O’Donoghue, A.-C. Gavin, N. Gehlenborg, D. S. Goodsell, J.-K. Heriche, C. B. Nielsen, C. North, A. J. Olson, J. B. Procter, D. W. Shattuck, T. Walter, and B. Wong, “Visualizing biological data-now and in the future,” Nat. Methods 7(3), S1–S4 (2010). [CrossRef]

36.

A. Limaye, “Drishti-volume exploration and presentation tool,” IEEE Visual., Baltimore, USA (2006).

37.

R. O. Potts and D. A. Chrisman, Jr., andE. M. Buras, Jr., “The dynamic mechanical properties of human skin in vivo,” J. Biomech. 16(6), 365–372 (1983). [CrossRef] [PubMed]

38.

A. Gabrielli, E. V. Avvedimento, and T. Krieg, “Scleroderma,” N. Engl. J. Med. 360(19), 1989–2003 (2009). [CrossRef] [PubMed]

39.

J. De Rigal and J. L. Leveque, “In vivo measurement of the stratum corneum elasticity,” Bioeng. Skin 1, 13–23 (1985).

40.

F. M. Hendriks, D. Brokken, C. W. J. Oomens, and F. P. T. Baaijens, “Influence of hydration and experimental length scale on the mechanical response of human skin in vivo, using optical coherence tomography,” Skin Res. Technol. 10(4), 231–241 (2004). [CrossRef] [PubMed]

41.

S. Makita, Y. Hong, M. Yamanari, T. Yatagai, and Y. Yasuno, “Optical coherence angiography,” Opt. Express 14(17), 7821–7840 (2006). [CrossRef] [PubMed]

42.

A. Szkulmowska, M. Szkulmowski, A. Kowalczyk, and M. Wojtkowski, “Phase-resolved Doppler optical coherence tomography--limitations and improvements,” Opt. Lett. 33(13), 1425–1427 (2008). [CrossRef] [PubMed]

OCIS Codes
(110.4500) Imaging systems : Optical coherence tomography
(290.5820) Scattering : Scattering measurements
(170.6935) Medical optics and biotechnology : Tissue characterization

ToC Category:
Medical Optics and Biotechnology

History
Original Manuscript: January 4, 2011
Revised Manuscript: February 28, 2011
Manuscript Accepted: March 15, 2011
Published: March 23, 2011

Virtual Issues
Vol. 6, Iss. 4 Virtual Journal for Biomedical Optics

Citation
Brendan F. Kennedy, Xing Liang, Steven G. Adie, Derek K. Gerstmann, Bryden C. Quirk, Stephen A. Boppart, and David D. Sampson, "In vivo three-dimensional optical coherence elastography," Opt. Express 19, 6623-6634 (2011)
http://www.opticsinfobase.org/vjbo/abstract.cfm?URI=oe-19-7-6623


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References

  1. Y. C. Fung, Biomechanics: Mechanical Properties of Living Tissue (Springer-Verlag, 1993).
  2. J. F. Greenleaf, M. Fatemi, and M. Insana, “Selected methods for imaging elastic properties of biological tissues,” Annu. Rev. Biomed. Eng. 5(1), 57–78 (2003). [CrossRef] [PubMed]
  3. M. Fatemi, A. Manduca, and J. F. Greenleaf, “Imaging elastic properties of biological tissues by low-frequency harmonic vibration,” Proc. IEEE 91(10), 1503–1519 (2003). [CrossRef]
  4. J. Ophir, I. Céspedes, H. Ponnekanti, Y. Yazdi, and X. Li, “Elastography: a quantitative method for imaging the elasticity of biological tissues,” Ultrason. Imaging 13(2), 111–134 (1991). [CrossRef] [PubMed]
  5. R. Muthupillai, D. J. Lomas, P. J. Rossman, J. F. Greenleaf, A. Manduca, and R. L. Ehman, “Magnetic resonance elastography by direct visualization of propagating acoustic strain waves,” Science 269(5232), 1854–1857 (1995). [CrossRef] [PubMed]
  6. A. Itoh, E. Ueno, E. Tohno, H. Kamma, H. Takahashi, T. Shiina, M. Yamakawa, and T. Matsumura, “Breast disease: clinical application of US elastography for diagnosis,” Radiology 239(2), 341–350 (2006). [CrossRef] [PubMed]
  7. A. L. McKnight, J. L. Kugel, P. J. Rossman, A. Manduca, L. C. Hartmann, and R. L. Ehman, “MR elastography of breast cancer: preliminary results,” AJR Am. J. Roentgenol. 178(6), 1411–1417 (2002). [PubMed]
  8. D. L. Cochlin, R. H. Ganatra, and D. F. R. Griffiths, “Elastography in the detection of prostatic cancer,” Clin. Radiol. 57(11), 1014–1020 (2002). [CrossRef] [PubMed]
  9. J. Foucher, E. Chanteloup, J. Vergniol, L. Castéra, B. Le Bail, X. Adhoute, J. Bertet, P. Couzigou, and V. de Lédinghen, “Diagnosis of cirrhosis by transient elastography (FibroScan): a prospective study,” Gut 55(3), 403–408 (2006). [CrossRef]
  10. S. A. Kruse, G. H. Rose, K. J. Glaser, A. Manduca, J. P. Felmlee, C. R. Jack, and R. L. Ehman, “Magnetic resonance elastography of the brain,” Neuroimage 39(1), 231–237 (2008). [CrossRef]
  11. C. L. de Korte, G. Pasterkamp, A. F. W. van der Steen, H. A. Woutman, and N. Bom, “Characterization of plaque components with intravascular ultrasound elastography in human femoral and coronary arteries in vitro,” Circulation 102(6), 617–623 (2000). [PubMed]
  12. J. M. Schmitt, “OCT elastography: imaging microscopic deformation and strain of tissue,” Opt. Express 3(6), 199–211 (1998). [CrossRef] [PubMed]
  13. R. C. Chan, A. H. Chau, W. C. Karl, S. Nadkarni, A. S. Khalil, N. Iftimia, M. Shishkov, G. J. Tearney, M. R. Kaazempur-Mofrad, and B. E. Bouma, “OCT-based arterial elastography: robust estimation exploiting tissue biomechanics,” Opt. Express 12(19), 4558–4572 (2004). [CrossRef] [PubMed]
  14. J. Rogowska, N. A. Patel, J. G. Fujimoto, and M. E. Brezinski, “Optical coherence tomographic elastography technique for measuring deformation and strain of atherosclerotic tissues,” Heart 90(5), 556–562 (2004). [CrossRef] [PubMed]
  15. H. J. Ko, W. Tan, R. Stack, and S. A. Boppart, “Optical coherence elastography of engineered and developing tissue,” Tissue Eng. 12(1), 63–73 (2006). [CrossRef] [PubMed]
  16. R. K. Wang, Z. H. Ma, and S. J. Kirkpatrick, “Tissue Doppler optical coherence elastography for real time strain rate and strain mapping of soft tissue,” Appl. Phys. Lett. 89(14), 144103 (2006). [CrossRef]
  17. S. J. Kirkpatrick, R. K. Wang, and D. D. Duncan, “OCT-based elastography for large and small deformations,” Opt. Express 14(24), 11585–11597 (2006). [CrossRef] [PubMed]
  18. X. Liang, A. L. Oldenburg, V. Crecea, E. J. Chaney, and S. A. Boppart, “Optical micro-scale mapping of dynamic biomechanical tissue properties,” Opt. Express 16(15), 11052–11065 (2008). [CrossRef] [PubMed]
  19. S. G. Adie, B. F. Kennedy, J. J. Armstrong, S. A. Alexandrov, and D. D. Sampson, “Audio frequency in vivo optical coherence elastography,” Phys. Med. Biol. 54(10), 3129–3139 (2009). [CrossRef] [PubMed]
  20. B. F. Kennedy, T. R. Hillman, R. A. McLaughlin, B. C. Quirk, and D. D. Sampson, “In vivo dynamic optical coherence elastography using a ring actuator,” Opt. Express 17(24), 21762–21772 (2009). [CrossRef] [PubMed]
  21. X. Liang and S. A. Boppart, “Biomechanical properties of in vivo human skin from dynamic optical coherence elastography,” IEEE Trans. Biomed. Eng. 57(4), 953–959 (2010). [CrossRef]
  22. X. Liang, S. G. Adie, R. John, and S. A. Boppart, “Dynamic spectral-domain optical coherence elastography for tissue characterization,” Opt. Express 18(13), 14183–14190 (2010). [CrossRef] [PubMed]
  23. S. G. Adie, X. Liang, B. F. Kennedy, R. John, D. D. Sampson, and S. A. Boppart, “Spectroscopic optical coherence elastography,” Opt. Express 18(25), 25519–25534 (2010). [CrossRef] [PubMed]
  24. R. Leitgeb, L. Schmetterer, W. Drexler, A. F. Fercher, R. J. Zawadzki, and T. Bajraszewski, “Real-time assessment of retinal blood flow with ultrafast acquisition by color Doppler Fourier domain optical coherence tomography,” Opt. Express 11(23), 3116–3121 (2003). [CrossRef] [PubMed]
  25. R. Leitgeb, C. K. Hitzenberger, and A. F. Fercher, “Performance of fourier domain vs. time domain optical coherence tomography,” Opt. Express 11(8), 889–894 (2003). [CrossRef] [PubMed]
  26. J. F. de Boer, B. Cense, B. H. Park, M. C. Pierce, G. J. Tearney, and B. E. Bouma, “Improved signal-to-noise ratio in spectral-domain compared with time-domain optical coherence tomography,” Opt. Lett. 28(21), 2067–2069 (2003). [CrossRef] [PubMed]
  27. M. Wojtkowski, T. Bajraszewski, P. Targowski, and A. Kowalczyk, “Real-time in vivo imaging by high-speed spectral optical coherence tomography,” Opt. Lett. 28(19), 1745–1747 (2003). [CrossRef] [PubMed]
  28. N. Nassif, B. Cense, B. Park, M. Pierce, S. Yun, B. Bouma, G. Tearney, T. Chen, and J. de Boer, “In vivo high-resolution video-rate spectral-domain optical coherence tomography of the human retina and optic nerve,” Opt. Express 12(3), 367–376 (2004). [CrossRef] [PubMed]
  29. T. A. Krouskop, T. M. Wheeler, F. Kallel, B. S. Garra, and T. Hall, “Elastic moduli of breast and prostate tissues under compression,” Ultrason. Imaging 20(4), 260–274 (1998).
  30. B. H. Park, M. C. Pierce, B. Cense, S.-H. Yun, M. Mujat, G. J. Tearney, B. E. Bouma, and J. F. de Boer, “Real-time fiber-based multi-functional spectral-domain optical coherence tomography at 1.3 microm,” Opt. Express 13(11), 3931–3944 (2005). [CrossRef] [PubMed]
  31. J. D’hooge, A. Heimdal, F. Jamal, T. Kukulski, B. Bijnens, F. Rademakers, L. Hatle, P. Suetens, and G. R. Sutherland, “Regional strain and strain rate measurements by cardiac ultrasound: principles, implementation and limitations,” Eur. J. Echocardiogr. 1(3), 154–170 (2000). [CrossRef]
  32. T. Gambichler, G. Moussa, M. Sand, D. Sand, P. Altmeyer, and K. Hoffmann, “Applications of optical coherence tomography in dermatology,” J. Dermatol. Sci. 40(2), 85–94 (2005). [CrossRef] [PubMed]
  33. H. Fruhstorfer, U. Abel, C.-D. Garthe, and A. Knüttel, “Thickness of the stratum corneum of the volar fingertips,” Clin. Anat. 13(6), 429–433 (2000). [CrossRef] [PubMed]
  34. “Fiji is just ImageJ,” http://pacific.mpi-cbg.de/wiki/index.php/ .
  35. S. I. O’Donoghue, A.-C. Gavin, N. Gehlenborg, D. S. Goodsell, J.-K. Heriche, C. B. Nielsen, C. North, A. J. Olson, J. B. Procter, D. W. Shattuck, T. Walter, and B. Wong, “Visualizing biological data-now and in the future,” Nat. Methods 7(3), S1–S4 (2010). [CrossRef]
  36. A. Limaye, “Drishti-volume exploration and presentation tool,” IEEE Visual., Baltimore, USA (2006).
  37. R. O. Potts and D. A. Chrisman, Jr., andE. M. Buras, Jr., “The dynamic mechanical properties of human skin in vivo,” J. Biomech. 16(6), 365–372 (1983). [CrossRef] [PubMed]
  38. A. Gabrielli, E. V. Avvedimento, and T. Krieg, “Scleroderma,” N. Engl. J. Med. 360(19), 1989–2003 (2009). [CrossRef] [PubMed]
  39. J. De Rigal and J. L. Leveque, “In vivo measurement of the stratum corneum elasticity,” Bioeng. Skin 1, 13–23 (1985).
  40. F. M. Hendriks, D. Brokken, C. W. J. Oomens, and F. P. T. Baaijens, “Influence of hydration and experimental length scale on the mechanical response of human skin in vivo, using optical coherence tomography,” Skin Res. Technol. 10(4), 231–241 (2004). [CrossRef] [PubMed]
  41. S. Makita, Y. Hong, M. Yamanari, T. Yatagai, and Y. Yasuno, “Optical coherence angiography,” Opt. Express 14(17), 7821–7840 (2006). [CrossRef] [PubMed]
  42. A. Szkulmowska, M. Szkulmowski, A. Kowalczyk, and M. Wojtkowski, “Phase-resolved Doppler optical coherence tomography--limitations and improvements,” Opt. Lett. 33(13), 1425–1427 (2008). [CrossRef] [PubMed]

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