Open Access
Add to BibSonomyAbstract
The composition of plaque is a major determinant of coronary-related clinical syndromes. By combining photoacoustic tomography (PAT) and optical coherence tomography (OCT), the optical absorption and scattering properties of vascular plaque can be revealed and subsequently used to distinguish the plaque composition and structure. The feasibility and capacity of the dual-mode PAT-OCT technique for resolving vascular plaque was first testified by plaque composition mimicking experiment. PAT obtained lipid information due to optical absorption differences, while owing to scattering differences, OCT achieved imaging of collagen. Furthermore, by combining PAT and OCT, the morphological characteristic and scattering difference of normal and lipid-rich plaque in the ex vivo rabbit aorta was distinguished simultaneously. The experiments demonstrated that the combined PAT and OCT technique is a potential feasible method for detecting the composition and structure of lipid core and fibrous cap in atherosclerosis.
© 2017 Optical Society of America
1. Introduction
Cardiovascular and cerebrovascular diseases secondary to atherosclerosis is the leading cause of morbidity worldwide [1]. Atherosclerosis is a disease in which plaque builds up on the inner lining of arterial walls, resulting in the thickening of the wall. The vulnerability of the plaques is related to plaque composition, anatomical structure, inflammation and vasa vasorum, etc. It has been shown that the rupture of vulnerable plaque, which is composed of a thin fibrous cap and underlying necrotic core, is the major cause of luminal thrombosis in acute coronary syndromes [2, 3]. Lipid and collagen fiber are the main compositions of lipid core and fibrous cap, respectively. Simultaneously imaging of lipid core and fibrous cap in atherosclerotic vessels will be of crucial importance for diagnosing vulnerable plaques and for understanding their underlying pathology. At present, several biomedical imaging modalities have been used to image the vascular plaques. Nevertheless, each imaging technique has its own inherent limitations. Magnetic resonance imaging (MRI) is performed to study the progression and regression of atherosclerotic plaques over time, however, its resolution is not sufficient to render accurate measurements [4]. Catheter-based near-infrared reflection spectroscopy (NIRS) uses optical absorption to signal the presence of lipid-core plaque in the coronary wall. It is, however, a sensing technology which cannot locate the position of the lipid-core relative to the lumen boundary [5]. Intravascular ultrasound (IVUS) provides structural information about vascular plaques with good penetration depth. However, this approach makes it difficult to distinguish between the lipid and other soft tissues [6]. More importantly, none of these imaging modalities can accurately obtain vascular plaques composition and structure simultaneously. In this regard, a method that can simultaneously image plaques composition and structure is strongly needed.
PAT is an emerging biomedical imaging modality that has the advantage of providing high optical absorption contrast and spatial resolution [7–10]. It utilizes an ultrasound transducer to measure the broadband ultrasound waves generated from thermoelastic effects deriving from a transient temperature rise due to the short pulse light absorption of biological tissue [11–16]. Allen et al. have reported that lipid detection was performed at 1.2μm or 1.7μm range with intravascular spectroscopic photoacoustic imaging [17]. However, the absorption coefficient of water molecules at 750 nm is low, which is much higher in the 1.2 and 1.7 μm wavelength. According to the absorption spectrum in our previous work [18], the lipid absorption band reach its peaks between 750 and 760 nm, which consistent with absorption spectrum of lipid from the previous report of other group [19]. The lipid relative concentration can be extracted by 720 nm and 760 nm dual-wavelength photoacoustic imaging. In addition, the blood absorption is minimized in this wavelength range, which is appropriate for in vivo implementation of PA imaging in the future. The basis for the differentiation of a heterogeneous lesion using photoacoustic imaging is the difference in the optical absorption coefficients of common plaque components (lipid, water, blood, and collagen) in the aortic tissue [20, 21]. Sethuraman et al. [22] performed the lipid and fibrous collagenous components of normal and atherosclerotic rabbit aorta at several wavelengths within 680-900 nm range, whereas the structure of lipid core and fibrous cap cannot identify clearly. A drawback of photoacoustic (PA) imaging is loss of information of the low-absorptive biological tissues, which is required for proper image interpretation. OCT is a widely used imaging technique that measures back-scattered light generated from a light source delivered to the tissue with a high resolution (10 µm to 20 µm) [23–25]. Various optical properties of biological tissues can provide contrasts for OCT, while the light scattering property predominates. Rico-Jimenez et al. [26] presented a novel computational method for automated IV-OCT plaque characterization. The results suggest that this methodology allows automated identification of fibrotic and lipid-containing plaques, but lipid-containing plaques were characterized by signal-poor regions with diffuse borders due to its shallow imaging depth and the low-intensity optical scattering. Because OCT is based on the endogenous contrast of tissue optical scattering properties, OCT technique penetration is limited to 1 mm in tissues [27]. Therefore, PAT and OCT can be complementary to each other with regard to the characterization of tissue structure and its physiological parameter, moreover, PA imaging can make up the deficiency of OCT in imaging depth.
In order to detect more information of vulnerable plaque, many groups have been working on multimodality imaging to study the vulnerable plaque. Li et al. [28] and Yin et al. [29]reported an integrated intravascular OCT and ultrasound imaging probe; Wang et al. [30] and Jansen et al. [31] demonstrated ultrasound guided intravascular photoacoustic imaging system; Zabihian et al. [32] and Berer et al. [33] both introduced the OCT and photoacoustic microscopy to study microvasculature. Yang et al. [34] and Dai et al. [35] integrated OCT, US and PA modalities in a probe. Yoo et al. [36] reported a dual-modality intra-arterial catheter for simultaneous microstructural and molecular imaging in vivo using a combination of optical frequency domain imaging and near-infrared fluorescence imaging. Lorenser et al. [37] presented the needle probe for combined OCT and fluorescence imaging to imaging the excised sheep lung. Jo et al. [38] validated the morphological and biochemical endogenous optical imaging of coronary atherosclerotic plaque with OCT and fluorescence lifetime imaging microscopy. However, these works did not justify that these multimodality technologies can be used to identify the composition and structure of vascular plaque. In this paper, a pilot study on the optical absorption and scattering of plaque composition and structure is presented, which would help to identify vulnerable plaques more accurately.
2. Methods and materials
2.1 Experimental setup
A schematic of the dual-mode imaging experimental setup is shown in Fig. 1. The OCT subsystem consists of a low coherence light source (central wavelength of 1310 nm and spectral bandwidth of 45 nm) and an all-fiber Michelson interferometer (an optical circulator, a 2 × 2 fiber coupler, and a photodetector). The lateral resolution is 12.5 µm, as determined by imaging the sharp edge of a blade. The axial resolution is 18.4 µm, as measured by imaging the air gap between the microscope cover glass and the microscope slide. The OCT subsystem was reported in detail in previous work [39]. The photoacoustic imaging subsystem part includes wavelength-tunable pulsed laser (Vibrant B 532I, OPOTEK, USA), amplifier (Ha2, Precision Acoustics LTD, UK), digital oscilloscopes and photodetector. The laser is used as the radiation source, and the induced photoacoustic waves are detected by a custom-made miniature ultrasonic transducer (Doppler Electronic Technologies Co., Ltd., China) with central frequency of 20 MHz and −6 dB bandwidth of 80%. The optical illumination beam was passed through a fixed holder, and the light spot size is about 20 μm on the sample. The transmitted laser was focused by a 4 × microscope objective (NA = 0.1) to produce a high resolution and illuminate the target. The detected photoacoustic signals were digitized and streamed to the computer by a data acquisition board (NI PCI-5124, National Instruments, USA). The axial resolution of the PAT subsystem is ~100 µm. The lateral resolution of the system is about 20 μm, determined by measuring the edge spread function resulted from a sharp edged metal object. The laser fluence incident on the tissue surface was controlled below 15 mJ/cm2 during the experiments, which is lower than the American National Standards Institute (ANSI) laser safety limits (20 mJ/cm2) [40]. To ensure automatic registration of the two imaging modalities under all circumstances, the timing of the PAT laser triggering and data acquisition, the scanning of the drive motor scanner, and the OCT data acquisition need to be controlled on the same time base. The photoacoustic does not have much heat accumulation, and its thermal effect is feeble. According to the thermal diffusivity of the materials [41], the thermal diffusion time is about eight microseconds, while there is a time gap of thirty microseconds between the acquisition of photoacoustic signal and the OCT signal. That is the heat will have enough time to disperse. Therefore, OCT signal is not affected by the heating induced by the PAT set-up.
Fig. 1 (a) Schematic of the dual-mode photoacoustic and optical coherence tomography experimental system. SLD, superluminescent diode; SMF1,2, single-mode fiber; C1,2, collimator; PD1,2, photodetector; FC, fiber coupler; RSOD, rapid-scanning optical delay line; DM, dichroic mirror; and DAS, data acquisition system. (b) The process of decoding lipid relative concentration. (c) The enlarged view of the indicated area of detail shown in (a). UT, ultrasonic transducer; S, sample; OL,Objective lens; FH, Fixed holder.
2.2 Imaging depth of the PAT-OCT dual-mode system
In atherosclerotic plaques, there are tens microns fibrous cap, and large lipid core. Simultaneous imaging optical absorption and scattering distribution requires sufficient imaging depth in this dual modality system. To demonstrate the imaging depth of the system, an iron wire was inserted into the fat for simulating the lipid. The iron wire diameter is about 0.3mm. According to the light size (20 µm), we calculated that the thermal diffusion time is several microseconds, which is much larger than the pulse width (nanoseconds). Our experimental condition is to meet the thermal closed condition, and photoacoustic signals are not affected by thermal conductivity. Moreover, the iron wire is inserted into the fat, whose refractive index has quite difference with the surrounding medium. The material with a high refractive index shows strong light scattering. Therefore, the iron wire can measure imaging depth of PAT and OCT. The measuring method was shown in the inserted schematic. The signal intensity of PAT and OCT are decreased with increasing imaging depth, as demonstrated in Figs. 2(a) and 2(b), respectively. The inserted schematic in the dotted box shows the measuring method. Obviously, photoacoustic (PA) imaging depth was significantly deeper than OCT, it could image over 3 mm in the fat. This result suggested that the imaging depth of the system can apply to detecting vascular plaques.
Fig. 2 The imaging depth of the dual-mode PAT-OCT system. (a) PA intensity relative to the imaging depth, the inserted schematic in the dotted box shows the measuring method. (b) OCT intensity relative to the imaging depth.
3. Results
3.1 Phantom experiment of dual-mode PAT-OCT system
In order to verify whether the system is capable of imaging the absorption and scattering targets within the vessel-mimicking phantom and to make the phantom, we used a mixture of agar, collagen, and fat to mimic the vascular plaque. This is because lipid and collagen are the main compositions of lipid core and fibrous cap, respectively. The structure of the vessel-mimicking phantom is illustrated in Fig. 3(a), where the top layer consists of collagen and agar mixture to simulate the main composition of fibrous cap. The intermediate layer is the fat layer to simulate lipid. A thick bottom layer was used to fix to sample. The PAT and OCT intensities for the fat and mixture (agar and collagen) are shown in Figs. 3(b) and 3(c), respectively. In Figs. 3(d) and 3(e), these two red dotted circles represent collagen-agar mixture and two white dotted circles indicate fat. Figure 3(b) shows the mean value and standard deviation of the PA intensity, which corresponds to the area of fat and mixture in PAT image. And the same calculated method was used in Fig. 3(c). The PAT and OCT intensities are average value. The results indicated that the PA signal intensity of fat was higher than that of the mixture (agar and collagen). However, OCT intensity of these two substances showed the opposite results with respect to their intensities. Figure 3(d) shows the PAT B-scan image of the vessel-mimicking phantom. Fat is clearly imaged with PAT (white dotted circles); meanwhile, the mixture of agar and collagen is not identified. Photoacoustic imaging could result in a loss of information about the collagen due to the low-absorption of collagen. Whereas the OCT image [Fig. 3(e)] can both visualize collagen and fat, but fat was characterized by signal-poor regions with diffuse borders due to its shallow imaging depth and the low-intensity optical scattering. To register the two B-scan images along the axial direction, we first determined the depth relationship (pixel shift) between the two modalities by imaging the top surface of a printed mesh grid [42, 43]. Then the PAT image was shifted accordingly along the axial direction to register with the OCT image. The combined PAT and OCT image [Fig. 3(f)] can obviously distinguish both mixture and fat. Taken together, experimental results indicated that the dual-mode PAT-OCT technique can be used to simultaneously acquire both optical absorption and optical scattering information.
Fig. 3 Vessel-mimicking phantom imaging in the dual-mode PAT-OCT system. (a) Vessel-mimicking phantom structure. (b) PA signal amplitude. (c) OCT intensity. (d) PAT B-scan image of the phantom. (e) OCT B-scan image of the phantom. (f) Combined PAT and OCT B-scan image of the phantom. Scale bar, 500 µm.
3.2 Vascular plaque phantoms experiment
The dual modality technique subsequently demonstrated the capability to distinguish the plaque composition and structure. Experiments were conducted on three vascular plaque phantoms, which mimic lipid-rich, thick fibrous cap, and thin fibrous cap plaques in blood vessels respectively. In these three phantoms, lipid cores were simulated with the mixture of cholesterol, phospholipid and triglyceride, which are the main component of lipid in vascular plaque, and there is nothing to mimic fibrous cap in the lipid-rich phantom. Simulated thick and thin fibrous cap were contained gelatin, agar and collagen. Simulated vascular wall was made of gelatin and agar in these three phantoms. Photographs of plaque phantoms that were prepared are shown in Figs. 4(a), 4(e) and 4(i), respectively. Figures 4(b), 4(c) and 4(d) show photoacoustic, OCT and combined PAT and OCT images of lipid-rich plaque phantom. Figures 4(a), 4(e) and 4(i) show the Photographs of the vascular phantoms. The red dotted lines represent the scanning position. Corresponding black dashed curves in Figs. 4(b), 4(f) and 4(j) show the profile of simulated lipid core. The distribution of optical absorption and scattering of lipid-rich plaque are in the same area. And lipid was extracted by dual wavelengths, lipid-rich plaque appears as a region of low-intensity optical scattering with irregular and indistinct borders in OCT. Figure 4(f) shows the photoacoustic B-scan map of the thick fibrous cap plaque phantom, which demonstrates the lack of optical absorption about the collagen. As shown in Fig. 4(g), thick fibrous cap was distinguished clearly, but lipid demonstrated decreased signal intensity. Figure 4(h) indicates the combined PAT and OCT image, the strong scattering thick fibrous cap and the weak absorption of lipid are visualized. Figures 4(j) and 4(k) show PAT and OCT B-scan images of thin cap plaque phantom. The strong contrast between lipid-rich core and fibrous regions in OCT images allowed fibrous cap to be easily identified. Because the sample has more lipid content than thick fibrous cap plaque phantom, the PAT image has strong absorption intensity. And the strong absorption lipid core and strong scattering fibrous cap can be seen clearly [Fig. 4(l)]. The experimental results indicated that the dual-mode PAT-OCT technique can be used to simultaneously imaging optical absorption and optical scattering distributions of vascular plaque. And the plaque composition and structure were clearly showed in different stages of vascular plaque phantoms. The results illustrate that the dual-mode PAT-OCT technique can apply vascular imaging at different stages.
Fig. 4 Vascular phantom imaging in the dual-mode PAT-OCT technique. (a), (e) and (i), Photographs of the vascular phantoms. (b), (f) and (j), PAT B-scan maps of the vascular plaque phantom. (c), (g) and (k), OCT B-scan images. (d), (h) and (l), Combined PAT and OCT images. Red dotted lines in (a), (e) and (i) represent the scanning position. Corresponding black dashed curves in (b), (f) and (j) show the profile of simulated lipid core. Scale bar, 300 µm.
3.3 Vascular plaque phantoms experiment
To further validate the feasibility of dual-mode PAT-OCT technique for biomedical application, ex vivo experiments were conducted on vessels harvested from a 3-months high-fat/high-cholesterol diet feeding rabbit. Normal and atherosclerotic vessels were fixed in transparent gelatin. Figures 5(a) and 5(e) show the photoacoustic B-scan maps of normal and atherosclerotic vessels, respectively. Figure 5(a) demonstrates a low lipid aortic wall of a normal vessel, and Fig. 5(e) shows a high lipid content of an atherosclerotic vessel. The OCT B-scan images of normal and atherosclerotic vessels are shown in Figs. 5(b) and 5(f). The OCT image in the lipid-rich plaque appears as a region of low-intensity optical scattering and indistinct borders, but photoacoustic can extract lipid core completely. Combined PAT and OCT images are shown in Figs. 5(c) and 5(g). The results of these experiments were consistent with histology, and the samples were stained with Oil red O, a lipid-sensitive staining, and imaged using a stereo microscope, as shown in Figs. 5(d) and 5(h). The lipid-rich plaque in atherosclerotic vessel gave rise to high optical absorption and dense oil red staining. Examples of the intensity for normal and atherosclerotic plaque measured with PAT and OCT are shown in Fig. 5(i). The mean value and standard deviation of the PAT and OCT intensities were measured in the white dotted circles, which corresponds to the normal and lipid plaque areas. The results show that lipid-rich plaque have a higher photoacoustic signal intensity than normal vessel, whereas lipid optical scattering intensity is lower than normal vessel, because the normal vessel contains more collagen than lipid plaque. These results demonstrate that the dual-mode PAT-OCT imaging technique can be applied to both normal vessel and lipid-rich plaque. Moreover, the morphological characteristic and scattering difference of vascular plaque could be obtained by PAT and OCT, simultaneously.
Fig. 5 Imaging of normal and atherosclerotic rabbit vessels by using the dual-mode imaging technique. (a) Photoacoustic B-scan map of normal vessel. (b) OCT B-scan image. (c) Combined PAT and OCT image. (d) Section stained with Oil red O. (e) Photoacoustic B-scan map of atherosclerotic vessel. (f) OCT B-scan image. (g) Combined PAT and OCT image. (h) Section stained with Oil red O for an atherosclerotic vessel. (i) Normal and atherosclerotic vessels with PA signal intensity and OCT intensity. Scale bar, 200 µm.
4. Discussion and conclusion
We use the dual-mode imaging method to demonstrate the composition structure identification simultaneously for the first time. The experiments of phantoms and excised artery tissues with a table-top system are necessary, which verify the feasibility of this dual-mode imaging modality in atherosclerotic plaque detection before in vivo intravascular experiments. Our experimental results proved that the dual-mode imaging method has potential to visualize the morphological characteristics of fibrous cap and lipid core simultaneously. Generally, the lipid core and fibrous cap are the two major vulnerability factors in vulnerable plaques. Simultaneous imaging plaque composition and structure would help to identify fibrous cap and lipid core in vulnerable plaques and quantitatively detect vulnerable plaques with combined PAT and OCT, which can be derived from the limitations of other imaging modalities. Moreover, this dual mode imaging technique has the potential to be further developed as an intravascular probe for vulnerable plaques analysis. Despite the superiorities, there are still several further improvements that should be made. Firstly, it will be imperative to validate these results in intravascular in vivo conditions. A fully integrated method with a high transverse resolution endoscopic probe will be used in the future for in vivo and endoscopic detection of vulnerable plaques. Secondly, a rotary device is needed to replace the current bulky linear stage. Thirdly, in our rabbit models, the formed vascular plaques are almost lipid-rich plaques. In this study, we use rabbit normal and atherosclerotic vessels to prove the feasibility of the dual-mode PAT and OCT imaging. At present, we are finding fibrous cap vascular plaque to detect lipid core and fibrous cap simultaneously.
In conclusion, we have proposed a method for detecting vascular plaques in the vessel using a dual-mode PAT-OCT imaging technique, which can simultaneously image optical absorption and optical scattering information in atherosclerosis. The results suggest a prospect in understanding the effect of structural properties on plaque progression and visualizing coronary anatomy. The comprehensive information described in this study should be useful for both basic science and clinical research focused on diagnosing arterial atherosclerosis.
Funding
This research is supported by the National Natural Science Foundation of China (61627827; 61331001; 91539127; 81630046), The National High Technology Research and Development Program of China (2015AA020901), The Science and Technology Planning Project of Guangdong Province, China (2015B020233016; 2014B020215003; 2014A020215031; 2013B090500122); Distinguished Young Teacher Project in Higher Education of Guangdong, China (YQ2015049).
References and links
1. D. S. Celermajer, C. K. Chow, E. Marijon, N. M. Anstey, and K. S. Woo, “Cardiovascular disease in the developing world: prevalences, patterns, and the potential of early disease detection,” J. Am. Coll. Cardiol. 60(14), 1207–1216 (2012). [CrossRef] [PubMed]
2. F. D’Ascenzo, P. Agostoni, A. Abbate, D. Castagno, M. J. Lipinski, G. W. Vetrovec, G. Frati, D. G. Presutti, G. Quadri, C. Moretti, F. Gaita, and G. B. Zoccai, “Atherosclerotic coronary plaque regression and the risk of adverse cardiovascular events: a meta-regression of randomized clinical trials,” Atherosclerosis 226(1), 178–185 (2013). [CrossRef] [PubMed]
3. Z. Teng, A. J. Brown, P. A. Calvert, R. A. Parker, D. R. Obaid, Y. Huang, S. P. Hoole, N. E. West, J. H. Gillard, and M. R. Bennett, “Coronary plaque structural stress is associated with plaque composition and subtype and higher in acute coronary syndrome: the BEACON I (Biomechanical Evaluation of Atheromatous Coronary Arteries) study,” Circ Cardiovasc Imaging 7(3), 461–470 (2014). [CrossRef] [PubMed]
4. A. Gotschy, E. Bauer, C. Schrodt, G. Lykowsky, Y. X. Ye, E. Rommel, P. M. Jakob, W. R. Bauer, and V. Herold, “Local arterial stiffening assessed by MRI precedes atherosclerotic plaque formation,” Circ Cardiovasc Imaging 6(6), 916–923 (2013). [CrossRef] [PubMed]
5. S. Garg, P. W. J. C. Serruys, M. van der Ent, C. Schultz, F. Mastik, G. van Soest, A. F. van der Steen, M. A. Wilder, J. E. Muller, and E. Regar, “First use in patients of a combined near infra-red spectroscopy and intra-vascular ultrasound catheter to identify composition and structure of coronary plaque,” EuroIntervention 5(6), 755–756 (2010). [CrossRef] [PubMed]
6. W. Wei, X. Li, Q. Zhou, K. K. Shung, and Z. Chen, “Integrated ultrasound and photoacoustic probe for co-registered intravascular imaging,” J. Biomed. Opt. 16(10), 106001 (2011). [CrossRef] [PubMed]
7. S. Jiao, M. Jiang, J. Hu, A. Fawzi, Q. Zhou, K. K. Shung, C. A. Puliafito, and H. F. Zhang, “Photoacoustic ophthalmoscopy for in vivo retinal imaging,” Opt. Express 18(4), 3967–3972 (2010). [CrossRef] [PubMed]
8. B. Y. Hsieh, S. L. Chen, T. Ling, L. J. Guo, and P. C. Li, “All-optical scanhead for ultrasound and photoacoustic dual-modality imaging,” Opt. Express 20(2), 1588–1596 (2012). [CrossRef] [PubMed]
9. C. Li and L. V. Wang, “Photoacoustic tomography and sensing in biomedicine,” Phys. Med. Biol. 54(19), R59–R97 (2009). [CrossRef] [PubMed]
10. L. V. Wang and S. Hu, “Photoacoustic tomography: in vivo imaging from organelles to organs,” Science 335(6075), 1458–1462 (2012). [CrossRef] [PubMed]
11. H. Qin, T. Zhou, S. Yang, Q. Chen, and D. Xing, “Gadolinium(III)-gold nanorods for MRI and photoacoustic imaging dual-modality detection of macrophages in atherosclerotic inflammation,” Nanomedicine (Lond.) 8(10), 1611–1624 (2013). [CrossRef] [PubMed]
12. J. Chen, R. Lin, H. Wang, J. Meng, H. Zheng, and L. Song, “Blind-deconvolution optical-resolution photoacoustic microscopy in vivo,” Opt. Express 21(6), 7316–7327 (2013). [CrossRef] [PubMed]
13. Y. Yuan, S. Yang, and D. Xing, “Preclinical photoacoustic imaging endoscope based on acousto-optic coaxial system using ring transducer array,” Opt. Lett. 35(13), 2266–2268 (2010). [CrossRef] [PubMed]
14. X. Ji, K. Xiong, S. Yang, and D. Xing, “Intravascular confocal photoacoustic endoscope with dual-element ultrasonic transducer,” Opt. Express 23(7), 9130–9136 (2015). [CrossRef] [PubMed]
15. K. Jansen, M. Wu, A. F. W. van der Steen, and G. van Soest, “Photoacoustic imaging of human coronary atherosclerosis in two spectral bands,” Photoacoustics 2(1), 12–20 (2014). [CrossRef] [PubMed]
16. Y. Wang, D. Xu, S. Yang, and D. Xing, “Toward in vivo biopsy of melanoma based on photoacoustic and ultrasound dual imaging with an integrated detector,” Biomed. Opt. Express 7(2), 279–286 (2016). [CrossRef] [PubMed]
17. T. J. Allen, A. Hall, A. P. Dhillon, J. S. Owen, and P. C. Beard, “Spectroscopic photoacoustic imaging of lipid-rich plaques in the human aorta in the 740 to 1400 nm wavelength range,” J. Biomed. Opt. 17(6), 061209 (2012). [CrossRef] [PubMed]
18. J. Zhang, S. Yang, X. Ji, Q. Zhou, and D. Xing, “Characterization of lipid-rich aortic plaques by intravascular photoacoustic tomography: ex vivo and in vivo validation in a rabbit atherosclerosis model with histologic correlation,” J. Am. Coll. Cardiol. 64(4), 385–390 (2014). [CrossRef] [PubMed]
19. R. L. P. van Veen, H. J. C. M. Sterenborg, A. Pifferi, A. Torricelli, E. Chikoidze, and R. Cubeddu, “Determination of visible near-IR absorption coefficients of mammalian fat using time- and spatially resolved diffuse reflectance and transmission spectroscopy,” J. Biomed. Opt. 10(5), 054004 (2005). [CrossRef] [PubMed]
20. B. J. Tromberg, N. Shah, R. Lanning, A. Cerussi, J. Espinoza, T. Pham, L. Svaasand, and J. Butler, “Non-invasive in vivo characterization of breast tumors using photon migration spectroscopy,” Neoplasia 2(1-2), 26–40 (2000). [CrossRef] [PubMed]
21. S. A. Prahl, “Optical properties spectra compiled by Scott Prahl,” (2001), http://omlc.ogi.edu/spectra/.
22. S. Sethuraman, J. H. Amirian, S. H. Litovsky, R. W. Smalling, and S. Y. Emelianov, “Spectroscopic intravascular photoacoustic imaging to differentiate atherosclerotic plaques,” Opt. Express 16(5), 3362–3367 (2008). [CrossRef] [PubMed]
23. H. Sinclair, C. Bourantas, A. Bagnall, G. S. Mintz, and V. Kunadian, “OCT for the identification of vulnerable plaque in acute coronary syndrome,” JACC Cardiovasc. Imaging 8(2), 198–209 (2015). [CrossRef] [PubMed]
24. L. Xi, C. Duan, H. Xie, and H. Jiang, “Miniature probe combining optical-resolution photoacoustic microscopy and optical coherence tomography for in vivo microcirculation study,” Appl. Opt. 52(9), 1928–1931 (2013). [CrossRef] [PubMed]
25. I. K. Jang, G. J. Tearney, B. MacNeill, M. Takano, F. Moselewski, N. Iftima, M. Shishkov, S. Houser, H. T. Aretz, E. F. Halpern, and B. E. Bouma, “In vivo characterization of coronary atherosclerotic plaque by use of optical coherence tomography,” Circulation 111(12), 1551–1555 (2005). [CrossRef] [PubMed]
26. J. J. Rico-Jimenez, D. U. Campos-Delgado, M. Villiger, K. Otsuka, B. E. Bouma, and J. A. Jo, “Automatic classification of atherosclerotic plaques imaged with intravascular OCT,” Biomed. Opt. Express 7(10), 4069–4085 (2016). [CrossRef] [PubMed]
27. J. M. McCabe and K. J. Croce, “Optical coherence tomography,” Circulation 126(17), 2140–2143 (2012). [CrossRef] [PubMed]
28. X. Li, J. Li, J. Jing, T. Ma, S. Liang, J. Zhang, D. Mohar, A. Raney, S. Mahon, M. Brenner, P. Patel, K. K. Shung, Q. Zhou, and Z. Chen, “Integrated IVUS-OCT imaging for atherosclerotic plaque characterization,” IEEE J. Sel. Top. Quantum Electron. 20(2), 7100108 (2014). [PubMed]
29. J. Yin, H. C. Yang, X. Li, J. Zhang, Q. Zhou, C. Hu, K. K. Shung, and Z. Chen, “Integrated intravascular optical coherence tomography ultrasound imaging system,” J. Biomed. Opt. 15(1), 010512 (2010). [CrossRef] [PubMed]
30. B. Wang, J. L. Su, J. Amirian, S. H. Litovsky, R. Smalling, and S. Emelianov, “Detection of lipid in atherosclerotic vessels using ultrasound-guided spectroscopic intravascular photoacoustic imaging,” Opt. Express 18(5), 4889–4897 (2010). [CrossRef] [PubMed]
31. K. Jansen, G. van Soest, and A. F. W. van der Steen, “Intravascular photoacoustic imaging: a new tool for vulnerable plaque identification,” Ultrasound Med. Biol. 40(6), 1037–1048 (2014). [CrossRef] [PubMed]
32. B. Zabihian, J. Weingast, M. Liu, E. Zhang, P. Beard, H. Pehamberger, W. Drexler, and B. Hermann, “In vivo dual-modality photoacoustic and optical coherence tomography imaging of human dermatological pathologies,” Biomed. Opt. Express 6(9), 3163–3178 (2015). [CrossRef] [PubMed]
33. T. Berer, E. Leiss-Holzinger, A. Hochreiner, J. Bauer-Marschallinger, and A. Buchsbaum, “Multimodal noncontact photoacoustic and optical coherence tomography imaging using wavelength-division multiplexing,” J. Biomed. Opt. 20(4), 046013 (2015). [CrossRef] [PubMed]
34. Y. Yang, X. Li, T. Wang, P. D. Kumavor, A. Aguirre, K. K. Shung, Q. Zhou, M. Sanders, M. Brewer, and Q. Zhu, “Integrated optical coherence tomography, ultrasound and photoacoustic imaging for ovarian tissue characterization,” Biomed. Opt. Express 2(9), 2551–2561 (2011). [CrossRef] [PubMed]
35. X. Dai, L. Xi, C. Duan, H. Yang, H. Xie, and H. Jiang, “Miniature probe integrating optical-resolution photoacoustic microscopy, optical coherence tomography, and ultrasound imaging: proof-of-concept,” Opt. Lett. 40(12), 2921–2924 (2015). [CrossRef] [PubMed]
36. H. Yoo, J. W. Kim, M. Shishkov, E. Namati, T. Morse, R. Shubochkin, J. R. McCarthy, V. Ntziachristos, B. E. Bouma, F. A. Jaffer, and G. J. Tearney, “Intra-arterial catheter for simultaneous microstructural and molecular imaging in vivo,” Nat. Med. 17(12), 1680–1684 (2011). [CrossRef] [PubMed]
37. D. Lorenser, B. C. Quirk, M. Auger, W. J. Madore, R. W. Kirk, N. Godbout, D. D. Sampson, C. Boudoux, and R. A. McLaughlin, “Dual-modality needle probe for combined fluorescence imaging and three-dimensional optical coherence tomography,” Opt. Lett. 38(3), 266–268 (2013). [CrossRef] [PubMed]
38. J. A. Jo, J. Park, P. Pande, S. Shrestha, M. J. Serafino, J. D. J. Rico Jimenez, F. Clubb, B. Walton, L. M. Buja, J. E. Phipps, M. D. Feldman, J. Adame, and B. E. Applegate, “Simultaneous morphological and biochemical endogenous optical imaging of atherosclerosis,” Eur. Heart J. Card. Img. 8 (2015).
39. Z. Chen, S. Yang, Y. Wang, and D. Xing, “All-optically integrated photo-acoustic microscopy and optical coherence tomography based on a single Michelson detector,” Opt. Lett. 40(12), 2838–2841 (2015). [CrossRef] [PubMed]
40. Laser Institute of America, America Notional Standard for Safe Use of Lasers ANSI Z136.1–2007 (America Notional Standard Institute, 2007).
41. A. Somer, F. Camilotti, G. F. Costa, C. Bonardi, A. Novatski, A. V. C. Andrade, V. A. Kozlowski Jr, and G. K. Cruz, “The thermoelastic bending and thermal diffusion processes influence on photoacoustic signal generation using open photoacoustic cell technique,” J. Appl. Phys. 114(6), 063503 (2013). [CrossRef]
42. Z. Xie, S. Jiao, H. F. Zhang, and C. A. Puliafito, “Laser-scanning optical-resolution photoacoustic microscopy,” Opt. Lett. 34(12), 1771–1773 (2009). [CrossRef] [PubMed]
43. S. Jiao, Z. Xie, H. F. Zhang, and C. A. Puliafito, “Simultaneous multimodal imaging with integrated photoacoustic microscopy and optical coherence tomography,” Opt. Lett. 34(19), 2961–2963 (2009). [CrossRef] [PubMed]
