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Abstract
The changes of biomechanical properties, especially the elasticity of the ocular tissues, are closely related to some ophthalmic diseases. Currently, the ophthalmic optical coherence elastography (OCE) systems are dedicated either to the anterior segment or to the retina. The elasticity measurements of the whole eye remain challenging. Here we demonstrated an acoustic radiation force optical coherence elastography (ARF-OCE) method to quantify the elasticity of the cornea and the retina. The experiment results show that the Young’s moduli of the cornea and the retina were 16.66 ± 6.51 kPa and 207.96 ± 4.75 kPa, respectively. Our method can measure the elasticity of the anterior segment and the posterior segment, and provides a powerful tool to enhance ophthalmology research.
© 2022 Optica Publishing Group under the terms of the Optica Open Access Publishing Agreement
1. Introduction
The eye, consisting of several components with unique biomechanical properties, is an essential organ for visual perception. Ophthalmic diseases, such as glaucoma, cataract, and age-related macular degeneration, will cause changes in the biomechanical properties of the ocular tissues [1–3]. In this case, measurement of these properties is particularly critical for physiology and pathology study of the eye. Several elastography modalities for biological tissues have been developed, including magnetic resonance imaging, ultrasonography, and optical coherence tomography (OCT) [4–9]. However, the insufficient resolution limits the application of magnetic resonance and ultrasound elastography in ophthalmology [10,11]. OCE is suitable for detecting the mechanical properties of ocular tissues due to its high resolution and sensitivity [12–15].
To assess the elasticity with OCE, some excitation methods have been proposed, such as acoustic radiation force (ARF), air-puff pulse, laser pulse, needle probe, and mechanical excitation. The ARF excitation, with its unique advantages of noncontact and noninvasive, has been widely used in elasticity detection of ocular tissues, especially in cornea, lens, and retina [16–20]. Qu et al. realized the assessment of the retinal elasticity using ARF-OCE in a porcine eye after the anterior segment was removed [21]. He et al. quantified retinal elasticity by analyzing the propagation of shear waves in the retina using ARF-OCE in the ex vivo porcine eyes without anterior segments [22]. Singh et al. estimated corneal elasticity and analyzed the relationship between corneal elasticity and intraocular pressure using OCE [23]. Previous ARF-OCE methods were developed to image either the anterior or the posterior segments due to the limitation of the OCT imaging depth. Therefore, the ARF-OCE method for assessing the biomechanical properties of the whole eye still presents challenges.
Studies on whole eye imaging using the OCT system have been reported in recent years. In 2015, Fan et al. developed a dual band dual focus spectral-domain optical coherence tomography for the whole eye imaging, which achieved an imaging depth of 36.71 mm in the air [24]. In 2018, Ireneusz et al. used an electrically tunable lens in the swept-source OCT (SS-OCT) system for versatile 3D in vivo imaging of the anterior segment and the retina of the human eye [25]. Although the SS-OCT system can achieve structural imaging of the whole eye, there are still few reports about the OCE methods for evaluating the biomechanical properties of the whole eye.
In this study, the ipsilateral coaxial ARF-OCE system was developed to quantitatively estimate the biomechanical properties of the anterior and posterior segments of the ex vivo porcine eye. Specifically, the ultrasonic transducer was used to excite the eye tissue, and the shear-wave propagation was detected by an SS-OCT system. An electrically tunable lens was used to expand the imaging depth of the SS-OCT system for the whole eye imaging. The Young’s moduli of the cornea and the retina were analyzed by shear wave velocities. The feasibility of the ARF-OCE method for the elasticity measurement of the whole eye was verified.
2. MATERIALS & METHODS
2.1 ARF-OCE system design
The ARF-OCE system consisted of an SS-OCT system and an ARF excitation module, as shown in Fig. 1. The center wavelength of the SS-OCT was 1060 nm, and the repetition A-line speed was 100 kHz. In the SS-OCT, a 90:10 optical fiber coupler was used to split the output light into the sample arm and the reference arm. In the reference arm, the light was reflected by a mirror after passing through a fiber circulator, a collimator, a 5 mm water cell, and a focusing lens. The water cell in the reference arm was used to compensate for the dispersion caused by the ocular tissue. In the sample arm, there were a collimator, a two-axial galvo mirror, an electrically tunable lens, and an objective scan lens. The current of the electrically tunable lens (EL-10-30-CI, Optotune, Switzerland) was adjusted between 0 mA to 300 mA for changing the imaging focus [25]. The back-reflected and backscattered light, respectively from the reference arm and the sample arm, interfered in a 50/50 fiber coupler. Then the interference signals were detected by a balanced photodetector. The lateral and axial resolutions of the SS-OCT system are about 18 µm and 8 µm in air, respectively. The imaging depth of ARF-OCE system is 22 mm with measured.
Fig. 1. Schematic of the ARF-OCE system, including an SS-OCT system and an ARF excitation module. An electrically tunable lens was used to expand the OCT imaging depth and a 4.5 MHz annular ultrasonic transducer with a focal length of 30 mm was used to provide the ARF. The ultrasound beam and the OCT beam were coaxial. The height of the ultrasonic transducer was changed by a mechanical lifting stage. SL: scan lens, UT: annular ultrasonic transducer.
In the ARF excitation module, a 4.5 MHz annular ultrasonic transducer with a focal length of 30 mm was used to provide the excitation force. The diameter of the through-hole in the center of the annular ultrasonic transducer is 12 mm. A mechanical lifting platform was used to change the height of the annular ultrasonic transducer so that the ultrasound can be focused on the anterior or posterior segments of the porcine eye, respectively. The light in the sample arm passed through the central hole of the transducer and entered the ocular tissue in the focus area, which overlapped with the acoustic zone of the transducer. The acoustic and optical axes were co-aligned.
2.2 Scanning protocol
An M-B scan model was used to capture the OCT data for the visualization of the shear wave propagation in ocular tissue. Figure 2 illustrates the scanning protocol. Specifically, 500 A-lines were recorded at each position to analyze the phase changes over time. The OCT imaging process and the ARF excitation process were triggered simultaneously. The trigger signals of the swept-source laser were used to synchronize a function generator, which produced a group of 4.5 MHz sine waves. After amplification, the sine waves drove the ultrasonic transducer to output the ARF. The excitation force was generated for 350 µs in the time between the 101st and 135th A-line scans. Then the galvanometer scanner moves the probe beam to the adjacent location, and the same M-mode scanning protocol was repeated.
Fig. 2. The M-B mode scanning protocol for the ARF-OCE. The OCT trigger signal of the laser, in black, was used for the synchronization of data acquisition. Each M-scan image consists of 500 A-lines. The trigger signal of the annular ultrasonic transducer shown in green synchronized the ARF excitation. The signals for controlling the X-axis galvanometer scanner were shown in purple.
2.3 Agar phantom and the ex vivo porcine eye preparation
To validate the ARF-OCE system, some phantom has been prepared. The phantom with 0.5% agar contains 0.06% intralipid to increase the backscattered signals. And this phantom was immersed 20 mm below the liquid level of water. Moreover, the porcine eye with surrounding muscles removed was used for the experiment within 24 hours of death. The eyeball was fixed with a 10 mm high, 25 mm diameter polyethylene container, in which exists a 20 mm diameter through-hole at the bottom for shape maintain. For the ex vivo experiment, the porcine eye was immersed 20 mm below the liquid level in the sterile phosphate-buffered saline (PBS).
2.4 Biomechanical characteristic analysis
The following equation can be used to analyze a temporal phase profile at the samples from M-mode OCT images [26]:
The relationship between the shear wave velocity ${{V}_{s}}$ and the shear modulus $\mathrm{\mu}$ can be described by Eq. (3), and the Young’s modulus ${E}$ can be calculated by Eq. (4) [22,28]:
The densities $\mathrm{\rho }$ of the porcine cornea and the porcine retina were 1062 ${kg/}{{m}^{3}}$ and 1000 ${kg/}{{m}^{3}}$, respectively [22,29].
3. RESULTS
The ARF-OCE system was tested by the measurements of the 0.5% (w/v) agar phantom as shown in Fig. 3. The phantom contains 0.06% (v/v) intralipid for light scattering. Figure 3(a) shows the OCT B-scan image of the phantom. Shear wave propagation in the phantom was visualized in Doppler OCT B-scan images, as shown in Fig. 3(b)-(g). The temporal-spatial Doppler OCT image is shown in Fig. 3(h). The propagation velocity of the shear wave is determined by the slope of the wave propagation trajectory, which was 1.69 ± 0.07 m/s in the 0.5% agar phantom. The corresponding Young’s modulus was estimated to be 8.54 ± 0.01 kPa using Eq. (4). To verify the accuracy of our OCE method, a mechanical stress test in a quasi-statically way was performed to quantify the Young’s modulus of the phantom [30]. The Young’s modulus of the 0.5% agar phantom was 13.58 ± 1.96 kPa. During the mechanical stress test, the compression load was applied to the phantom at the speed of 100 mm/min.
Fig. 3. The elastography of the 0.5% agar phantom. (a) OCT B-scan image of the phantom. (b)-(g) Doppler OCT B-scan images of the phantom at 0.1 ms, 0.4 ms, 0.7 ms, 1.0 ms, 1.3 ms, and 1.6 ms. (h) Temporal-spatial Doppler OCT image of the phantom.
Then an ex vivo porcine whole eye was measured to quantify the elasticity of the anterior and posterior segments. The focal length of the electrically tunable lens was adjusted by controlling the current. Figure 4(a) and 4(b) shows OCT B-scan images of the cornea in the anterior segment and the retina in the posterior segment, respectively. The whole eye OCT B-scan image was constructed based on the relationship between image depth and axis length, as shown in Fig. 4(c). From Fig. 4, the cornea and the layer structure of the retina can be visualized clearly. The SS-OCT system with an electrically tunable lens can obtain high-quality OCT images of the anterior and posterior segments.
Fig. 4. The anterior and posterior segment images acquired by the SS-OCT with an electrically tunable lens. (a) OCT B-scan image of the cornea. (b) OCT B-scan image of the retina. (c) Reconstructed OCT image of the whole eye.
The OCE measurements of the cornea and the retina were performed by the coaxial excitation ARF-OCE system. For the corneal elastography, the OCT beam and the ultrasonic beam focused on the cornea after the current of the electrically tunable lens was adjusted, and the annular ultrasonic transducer was moved. Figure 5(a) shows the OCT B-scan image of the porcine cornea. Shear wave propagation from the center to the sides can be visualized in the Doppler OCT images using the M-B mode scanning protocol, as shown in Fig. 5(b)-(g). Figure 5(h) shows the temporal-spatial wave propagation. The shear wave velocity was determined by calculating the ratio of the travel distance to the time, which was 2.39 ± 0.17 m/s. The corresponding Young’s modulus was estimated to be 18.27 ± 0.10 kPa in the porcine cornea from 20 measurements of the slopes.
Fig. 5. The elastography of the ex vivo porcine cornea. (a) OCT B-scan image of the cornea. (b)-(g) Time-lapse Doppler OCT B-scan images of the cornea at 0.1 ms, 0.3 ms, 0.5 ms, 0.7 ms, 0.9 ms, and 1.1 ms. (h) Temporal-spatial Doppler OCT image of the cornea.
For the retinal elastography, the current of the electrically tunable lens was re-adjusted to change the focal plane, and the annular ultrasonic transducer was moved downwards to focus on the retina. The OCT image of the retina is shown in Fig. 6(a). The thickness of the retina is approximately 500 µm, which is close to the previous study [21]. The shear wave propagation in the retina was shown in Fig. 6(b)-(g). The temporal-spatial Doppler OCT image is shown Fig. 6(h). The shear wave velocity in the retina was 8.59 ± 0.87 m/s, and the corresponding Young's modulus was 221.43 ± 2.29 kPa. The feasibility of the ARF-OCE for detecting the mechanical properties of the anterior and posterior segments has been confirmed.
Fig. 6. The elastography of the ex vivo porcine retina. (a) The OCT B-scan image of the retina. (b)-(g) Time-lapse Doppler OCT B-scan images of the retina at 0.1 ms, 0.3 ms, 0.5 ms, 0.7 ms, 0.9 ms, and 1.1 ms. (h) Temporal-spatial Doppler OCT image of the retina.
In addition, the elasticity measurements of the cornea and retina in three porcine eyes were performed. The mean and standard deviation of the three groups of data were calculated, and the average Young’s moduli of cornea and retina was 16.66 ± 6.51 kPa and 207.96 ± 4.75 kPa respectively, shown in Table 1. The feasibility of ARF-OCE for measuring the elastic properties of the cornea and retina has been further confirmed.
Table 1. Elasticity measurements of corneas and retinas from three different eyes
4. CONCLUSIONS
In this study, we developed an ARF-OCE method for measuring and quantifying the biomechanical characteristics of the whole eye. The OCT system with an electrically tunable lens enables imaging of the anterior and posterior segments. The coaxial design of the ultrasonic beam and the optical beam improves the sensitivity of the elastic wave detection. We demonstrated the feasibility of the ARF-OCE method by measuring the elasticity of the agar phantom. Then the elasticity of the cornea and the retina were quantified by the ARF-OCE system. The elasticity measurements of the whole eye have potentials for the pathological research and clinical diagnosis in ophthalmology.
Funding
National Natural Science Foundation of China (61975019); Beijing Municipal Natural Science Foundation (7192049); Research Project of the Beijing Municipal Education Commission (KZ202011232050).
Disclosures
The authors declare no conflicts of interest.
Data availability
Data underlying the results presented in this paper are not publicly available at this time but may be obtained from the authors upon reasonable request.
References
1. C. Wu, S. R. Aglyamov, Z. L. Han, M. Singh, C. H. Liu, and K. V. Larin, “Assessing the biomechanical properties of the porcine crystalline lens as a function of intraocular pressure with optical coherence elastography,” Biomed. Opt. Express 9(12), 6455–6466 (2018). [CrossRef]
2. Y. Ambekar, M. Singh, J. T. Zhang, A. Nair, S. R. Aglyamov, G. Scarcelli, and K. V. Larin, “Multimodal quantitative optical elastography of the crystalline lens with optical coherence elastography and Brillouin microscopy,” Biomed. Opt. Express 11(4), 2041–2051 (2020). [CrossRef]
3. Y. L. Zhang, Y. T. Ling, D. Zhang, M. K. Wang, C. Purslow, Y. Yang, C. H. Li, and Z. H. Huang, “Quantitative measurement of mechanical properties in wound healing processes in a corneal stroma model by using vibrational optical coherence elastography (OCE),” Biomed. Opt. Express 12(1), 588–603 (2021). [CrossRef]
4. X. Zhang, Q. Wang, L. Zhen, X. Gao, P. Zhang, H. Lin, Y. Guo, T. Wang, S. Chen, and X. Chen, “Noninvasive assessment of age-related stiffness of crystalline lenses in a rabbit model using ultrasound elastography,” BioMed Eng OnLine 17(1), 75 (2018). [CrossRef]
5. M. A. Kirby, I. Pelivanov, S. Song, Ł. Ambrozinski, S. J. Yoon, L. Gao, D. Li, T. T. Shen, R. K. Wang, and M. O’Donnell, “Optical coherence elastography in ophthalmology,” J. Biomed. Opt. 22(12), 1 (2017). [CrossRef]
6. Y. Feng, E. H. Clayton, Y. Chang, R. J. Okamoto, and P. V. Bayly, “Viscoelastic properties of the ferret brain measured in vivo at multiple frequencies by magnetic resonance elastography,” Journal of Biomechanics 46(5), 863–870 (2013). [CrossRef]
7. K. Chen, A. P. Rowley, and J. D. Weiland, “Elastic properties of porcine ocular posterior soft tissues,” J. Biomed. Mater. Res., Part A 9999A(93A), NA (2009). [CrossRef]
8. R. Muthupillai, D. Lomas, P. Rossman, J. Greenleaf, A. Manduca, and R. Ehman, “Magnetic resonance elastography by direct visualization of propagating acoustic strain waves,” Science 269(5232), 1854–1857 (1995). [CrossRef]
9. T. R. Friberg and J. W. Lace, “A comparison of the elastic properties of human choroid and sclera,” Exp. Eye Res. 47(3), 429–436 (1988). [CrossRef]
10. J. Ryan and A. Dewall, “Ultrasound elastography: principles, techniques, and clinical applications,” Crit Rev Biomed Eng 41(1), 1–19 (2013). [CrossRef]
11. K. J. Glaser, A. Manduca, and R. L. Ehman, “Review of MR elastography applications and recent developments,” J. Magn. Reson. Imaging 36(4), 757–774 (2012). [CrossRef]
12. R. F. Bu, S. Balakrishnan, H. Price, C. Zdanski, S. Mitran, and A. L. Oldenburg, “Localized compliance measurement of the airway wall using anatomic optical coherence elastography,” Opt. Express 27(12), 16751–16766 (2019). [CrossRef]
13. N. Leartprapun, Y. C. Lin, and S. G. Adie, “Microrheological quantification of viscoelastic properties with photonic force optical coherence elastography,” Opt. Express 27(16), 22615–22630 (2019). [CrossRef]
14. P. P. Wang, Z. J. Chen, and D. Xing, “Multi-parameter characterization of atherosclerotic plaques based on optical coherence tomography, photoacoustic and viscoelasticity imaging,” Opt. Express 28(9), 13761–13774 (2020). [CrossRef]
15. F. Zvietcovich, A. Nair, Y. S. Ambekar, M. Singh, S. R. Aglyamov, M. D. Twa, and K. V. Larin, “Confocal air-coupled ultrasonic optical coherence elastography probe for quantitative biomechanics,” Opt. Lett. 45(23), 6567–6570 (2020). [CrossRef]
16. R. Matthew, William Ford, J. Dupps Jr., M. Andrew, and Rollins, “Method for optical coherence elastography of the cornea,” J. Biomed. Opt. 16(1), 016005 (2011). [CrossRef]
17. S. Song, N. M. Le, Z. Huang, T. Shen, and R. K. Wang, “Quantitative shear-wave optical coherence elastography with a programmable phased array ultrasound as the wave source,” Opt. Lett. 40(21), 5007 (2015). [CrossRef]
18. A. Ramier, B. Tavakol, and S. H. Yun, “Measuring mechanical wave speed, dispersion, and viscoelastic modulus of the cornea using optical coherence elastography,” Opt. Express 27(12), 16635–16649 (2019). [CrossRef]
19. H. Zhang, C. Wu, M. Singh, A. Nair, S. Aglyamov, and K. Larin, “Optical coherence elastography of cold cataract in porcine lens,” J. Biomed. Opt. 24(03), 1–7 (2019). [CrossRef]
20. H. Kang, X. Qian, R. Chen, R. Wodnicki, and Q. Zhou, “2-D Ultrasonic Array-Based Optical Coherence Elastography,” IEEE Trans. Ultrason., Ferroelect., Freq. Contr. 68(4), 1096–1104 (2021). [CrossRef]
21. Y. Qu, Y. He, Y. Zhang, T. Ma, and Z. Chen, “Quantified elasticity mapping of retinal layers using synchronized acoustic radiation force optical coherence elastography,” Biomed. Opt. Express 9(9), 4054 (2018). [CrossRef]
22. Y. He, Y. Qu, J. Zhu, Y. Zhang, A. Saidi, T. Ma, Q. Zhou, and Z. Chen, “Confocal Shear Wave Acoustic Radiation Force Optical Coherence Elastography for Imaging and Quantification of the In Vivo Posterior Eye,” IEEE J. Select. Topics Quantum Electron. 25(1), 1–7 (2019). [CrossRef]
23. M. Singh, Z. Han, A. Nair, A. Schill, M. Twa, and K. V. Larin, “Applanation optical coherence elastography: noncontact measurement of intraocular pressure, corneal biomechanical properties, and corneal geometry with a single instrument,” J. Biomed. Opt. 22(02), 1 (2017). [CrossRef]
24. S. H. Fan, L. Li, Q. Li, C. X. Dai, Q. S. Ren, S. L. Jiao, and C. Q. Zhou, “Dual band dual focus optical coherence tomography for imaging the whole eye segment,” Biomed. Opt. Express 6(7), 2481–2493 (2015). [CrossRef]
25. I. Grulkowski, S. Manzanera, L. Cwiklinski, F. Sobczuk, and P. Artal, “Swept source optical coherence tomography and tunable lens technology for comprehensive imaging and biometry of the whole eye,” Optica 5(1), 52–59 (2018). [CrossRef]
26. Y. Zhao, Z. Chen, C. Saxer, S. Xiang, and J. S. Nelson, “Phase-resolved optical coherence tomography and optical Doppler tomography for imaging blood flow in human skin with fast scanning speed and high velocity sensitivity,” Opt. Lett. 25(2), 114–116 (2000). [CrossRef]
27. G. Lan, M. Singh, K. V. Larin, and M. Twa, “Common-path phase-sensitive optical coherence tomography provides enhanced phase stability and detection sensitivity for dynamic elastography,” Biomed. Opt. Express 8(11), 5253 (2017). [CrossRef]
28. M. Razani, A. Mariampillai, C. Sun, T. Luk, V. Yang, and M. C. Kolios, “Feasibility of optical coherence elastography measurements of shear wave propagation in homogeneous tissue equivalent phantoms,” Biomed. Opt. Express 3(5), 972 (2012). [CrossRef]
29. Y. Li, J. Zhu, J. J. Chen, J. Yu, and Z. Chen, “Simultaneously imaging and quantifying in vivo mechanical properties of crystalline lens and cornea using optical coherence elastography with acoustic radiation force excitation,” APL Photonics 4(10), 106104 (2019). [CrossRef]
30. B. F. Kennedy, P. Wijesinghe, and D. D. Sampson, “The emergence of optical elastography in biomedicine,” Nat. Photonics 11(4), 215–221 (2017). [CrossRef]
