Chapter 17. Biomedical Optical Imaging
Biomedical Optical Imaging
Academic Staff Professor James G. Fujimoto
Research Staff and Visiting Scientists Dr. Yueli Chen, Dr. Iwona Gorczynska, Dr. Ben Potsaid, Dr. Chao Zhou
Scientific Collaborators Dr. Jay S. Duker, M.D., Joseph Ho, Varsha Manjunath, (New England Eye Center) Dr. Joel Schuman, M.D. (University of Pittsburgh Medical Center) Dr. Allen Clermont, Dr. Edward Feener (Joslin Diabetes Center) Dr. Hiroshi Mashimo, M.D. (VA Medical Center) Dr. Joseph Schmitt (LightLab Imaging) Dr. David A. Boas, Lana Ruvinskaya, Dr. Anna Devor (MGH) Alex Cable, Dr. James Jiang, Dr. Ben Potsaid (Thorlabs, Inc.)
Graduate Students Desmond C. Adler, Aaron D. Aguirre, M.D., Hsiang-Chieh Lee, Jonathan J. Liu, Vivek J. Srinivasan, Tsung-Han Tsai
Technical and Support Staff Dorothy A. Fleischer, Donna L. Gale
Research Areas and Projects
1. Optical coherence tomography (OCT) technology 1.1 Overview of Optical Coherence Tomography 1.2 Spectral / Fourier domain OCT Imaging 1.3 Swept source / Fourier domain OCT Imaging using Swept Lasers 2. OCT in Ophthalmology 2.1 OCT in Ophthalmology 2.2 Technology Ophthalmic OCT 2.3 Ultrahigh Speed Spectral / Fourier Domain OCT Retinal Imaging 2.4 Swept Source / Fourier domain OCT Imaging at 1050 nm Wavelengths 2.5 Clinical OCT Studies Quantitative OCT measurements of retinal structure En Face projection OCT Interactive Science Publication (ISP) Clinical Studies of Retinal Disease 2.6 Functional OCT Imaging in Human Retina 2.7 Small Animal Retinal Imaging 3. High Speed Three-Dimensional OCT Endoscopic Imaging 3.1 OCT imaging of the Esophagus 3.2 OCT imaging of the Lower GI Tract 3.3 Assessment of Therapies in the GI Tract 3.5 Novel contrast agents for OCT 4. Optical Coherence Microscopy (OCM) for Imaging Pathology 4.1 Integrated OCT and OCM Imaging of Human Thyroid Pathology 4.2 OCT and OCM Imaging of Breast Pathology 4.3 Integrated OCT and OCM Imaging of Human Kidney Pathology 5. Functional Brain Imaging with OCT
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1. Optical Coherence Tomography (OCT) Technology
Sponsors National Institutes of Health – R01-CA075289-12, R01-EY11289-24, R01-EY013178-09, R01-EY013516-16 and R01-EY019029-02 National Science Foundation – BES-0522845, ECS-0501478 Air Force Office of Scientific Research – FA9550-07-1-0014, FA9550-07-1-0101 Natural Sciences and Engineering Research Council of Canada – CGS D2-331643-2006 The Whitaker Foundation National Science Council of Taiwan Center for Integration of Medicine and Innovation Technology (CIMIT)
Project Staff Prof. James G. Fujimoto, Dr. Desmond C. Adler, Dr. Yueli Chen, Dr. Iwona Gorczynska, Dr. Ben Potsaid, Dr. Vivek J. Srinivasan, Dr. Chao Zhou, Jonathan Liu, Tsung-Han Tsai, Hsiang-Chieh Lee Dr. Joseph Schmitt (LightLab Imaging)
Optical coherence tomography (OCT) is an emerging medical imaging and diagnostic technology developed by our research group and collaborators in 1991 [1]. Figure 1.1 shows a schematic of how OCT images are generated. OCT can perform cross sectional and three dimensional, micron scale imaging of tissue structure. It is analogous to ultrasound, measuring the intensity of backreflected or backscattered infrared light, rather than acoustical waves. OCT is attractive for biomedical research and clinical imaging for several reasons. Imaging can be performed in real time, allowing tissue microstructure to be visualized without the need to excise and process specimens as in conventional biopsy and histopathology. Image resolutions are 1 to 15 microns, enabling visualization of tissue architectural morphology. OCT can be performed with a wide range of instruments including ophthalmoscopes, small endoscopes, catheters, probes, needles, or other surgical instruments. OCT has had a dramatic impact in ophthalmology, where it has become a standard diagnostic instrument for retinal disease and glaucoma [2]. In addition OCT is an emerging technology for intravascular imaging, where it can identify unstable plaques that are prone to rupture, producing myocardial infarction [3]. OCT research combines multiple technologies including photonics, high speed electronics and signal processing, imaging processing, medical device development and biomedical engineering [4].
1.1 Overview of Optical Coherence Tomography Recent advances in OCT technology have yielding dramatic increases in performance. These new techniques measure the echo time delay of light by Fourier transforming the interference spectrum of the light signal and are, therefore known as Fourier domain OCT detection. Different echo time delays of light produce different frequencies of fringes in the interference spectrum. OCT Fourier domain detection techniques with spectrometer based systems (spectral / Fourier domain OCT) or frequency swept laser based systems (swept source / Fourier domain OCT) enabled OCT imaging to be performed with unprecedented sensitivities and speeds [5-12]. High speed imaging enables three dimensional OCT imaging (3D-OCT), generating volumetric data sets which contain comprehensive structural information. High speeds also enable the rapid survey of large areas on tissue as well as increased imaging throughput. In addition, high speeds allow multi-frame
17-2 RLE Progress Report 151 Chapter 17. Biomedical Optical Imaging averaging or acquisition of high-pixel-density images, which can be used to improve image quality or reduce speckle. Fourier domain OCT also has the advantage of providing direct access to the interference spectrum, enabling a wide range of phase sensitive applications such as Doppler imaging of blood flow [13-16]. Finally, Fourier domain OCT techniques are also well-suited for numerical dispersion compensation, supporting broad bandwidths and enabling ultrahigh axial image resolutions [8, 17]
1 D 2 D 3D Axial (Z) Scanning Axial (Z) Scanning Axial (Z) Scanning Transverse (X) Scanning XY Scanning Backscattered Intensity
Axial Position Position Axial
(Depth)
Figure 1. Principles of OCT imaging. OCT generates cross-sectional and three dimensional images of tissue microstructure and architectural morphology in vivo and in real time.
During the past years, our group demonstrated several new high speed spectral / Fourier domain OCT systems based on 850 nm and 1050 nm wavelength broadband light sources [18, 19] as well as swept source / Fourier domain OCT systems based on 1050 nm and 1310 nm wavelength Fourier domain mode locked (FDML) laser technology.[20-23] Using OCT systems with FDML laser technology, we achieved record imaging speeds [21, 22] and enabled new clinical applications for endoscopic [24-26] as well as ophthalmic imaging [27].
1.2 Spectral / Fourier Domain OCT Imaging
Spectral / Fourier domain detection techniques measure the echo time delay of light by using an interferometer with a broadband light source and a spectrometer with linescan camera. Figure 1.2 shows the schematic diagram of a spectral / Fourier-domain OCT system. A broadband light source is coupled into an interferometer with a sample and a reference arm. Backscattered or backreflected light from the sample interferes with light from the reference arm and is detected by the spectrometer and line scan camera. The spectrum at the interferometer output is acquired and processed. Back-reflection or backscattered light from tissue at different delays generates oscillations or fringes in the interference spectrum, as shown in Figure 1.2B. An increase in delay results in higher oscillation frequency in the interference spectrum. The magnitude and delay of the backscattered light can be measured by Fourier transforming the interference spectrum, as shown in Figure 1.2C.
Spectral / Fourier domain detection achieves a dramatic increase in sensitive because it essentially measures all of the echoes of light simultaneously [5-7]. In spectral / Fourier domain
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detection, the sensitivity, or one over the smallest detectable reflection RS is given by: 1/RS = ηPTexp /(hv), where P is the source power, Texp is the exposure time, η is the detection efficiency, and hv is the photon energy. With spectral / Fourier-domain detection, the exposure time is approximately the axial scan time TA-scan, therefore TA-scan ≈ Texp. In conventional time-domain OCT, light from different time delays is detected sequentially; therefore, assuming an axial scan time of TA-scan, the exposure time is approximately TA-scan /M, where M is the number of resolvable elements in one axial scan, which is defined as the total axial measurement range divided by the axial resolution. The sensitivity advantage of spectral domain detection ranges from 20 to 30 dB, enabling dramatic increases in imaging speed.
A B Interference spectrum
c/2∆L Reference
Sample
Broadband frequency Light C Beam Fourier transform Splitter ∆L
Spectrometer
frequency ~ distance Figure 1.2. Schematic of spectral / Fourier domain OCT detection. (A) A broadband light source illuminates a Michelson interferometer consisting of a reference and a sample arm. (B) The interference spectrum is recorded by the spectrometer. (C) The magnitude and echo time delay of backscattered or backreflected light is determined is measured by Fourier transformin the interference spectrum
Figure 1.3 shows an example of a high-speed, ultrahigh-resolution spectral / Fourier domain OCT system that we recently designed for ophthalmic imaging. This high-speed OCT prototype can be operated using either a femtosecond laser or a broadband superluminescent SLD as the imaging light source. In our early studies, we developed a low-threshold femtosecond Ti:Sapphire laser that was used in the ophthalmology clinic for three years. However, recent advances in multiplexed SLD light sources enable image resolutions of 3.5 μm. These broadband, multiplexed SLDs are relatively inexpensive and significantly easier to operate than femtosecond lasers, facilitating use in clinical OCT imaging.
The system consists of an interferometer with a spectrometer and line scan camera. Light in the reference arm is attenuated and reflected from a stationary mirror at a fixed delay. Light in the sample arm is directed through two galvanometer-actuated steering mirrors and then relay-imaged through the pupil onto the retina. The transverse spot size on the retina, which determined the
17-4 RLE Progress Report 151 Chapter 17. Biomedical Optical Imaging transverse image resolution, is ~20 um. The galvanometer-actuated mirrors can scan the OCT beam across the retina in any arbitrary pattern in order to perform cross-sectional imaging.
Light source
Figure 1.3. Schematic diagram of the high-speed ophthalmic OCT system using spectral / Fourier domain detection.
Cross-sectional and three dimensional OCT data is acquired by scanning the OCT beam on the retina under computer control. The incident light power on the eye is 750 μW, the same exposure used in commercial ophthalmic OCT systems and consistent with ANSI safety standards. The spectrum of the interferometer output is detected by using a spectrometer consisting of a collimating lens, transmission grating, imaging lens, and high speed line scan camera. The interference spectrum data from the camera is processed by computer where it is rescaled from wavelength to frequency, and Fourier transformed to generate axial measurements of the echo delay and magnitude of light from the retina.
Figure 1.4 shows a comparison of standard-resolution (a 10 um resolution image from the commercial Zeiss StratusOCT instrument) and a high-speed, ultrahigh-resolution image (from our research prototype spectral / Fourier domain OCT instrument) from a 65-year-old woman, two years after the surgical repair of a full-thickness macular hole in her left eye. Visual acuity improved to 20/25 OS. Both the standard-resolution StratusOCT image (Fig 1.4b) and the high-definition, 8192 axial scans, ultrahigh-resolution OCT image (Fig 1.4c) depict epiretinal membrane (yellow arrow). However, the hultrahigh-resolution OCT image enables better visualization of the membrane thickness and separation from the retina in the nasal portion of the image. A very small central disruption of the photoreceptor inner and outer segment IS/OS junction and photoreceptor outer segments in the fovea is visualized in the ultrahigh-resolution OCT image (white arrow). This abnormality in the photoreceptor signal, along with the epiretinal membrane, may explain the patient’s slight decrease in visual acuity.
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Figure 1.4 Macular hole repair: fundus photo (left top), cross-sectional image obtained by commercial instrument – Zeiss Stratus OCT (top right), cross-sectional image obtained by high-speed, ultrahigh-resolution OCT instrument. The high-quality image consists of 8100 axial scans (transverse pixels) with 1024 points (axial pixels) per scan and is measured in 0.35 sec. NFL – nerve fiber layer, IPL- inner plexiform layer, INL – inner nuclear layer, OPL – outer plexiform layer, ONL – outer nuclear layer, ELM – external limiting membrane, IS/OS – inner/outer photoreceptor junction, PR OS – photoreceptor outer segments, RPE – retinal pigment epithelium.
1.3 Swept source / Fourier Domain OCT Imaging using Swept Lasers Swept source / Fourier domain OCT is a complementary approach to spectral / Fourier domain OCT. Figure 1.5 shows a schematic of how swept source / Fourier domain detection works. Backreflected or backscattered light signals are measured using an interferometer with swept light source. Optical delays produce a beat frequency in the interference signal which is detected and Fourier transformed to measure the optical delay. Swept source OCT has a similar sensitivity advantage to spectral OCT and enables very high imaging speeds.
Swept source OCT has important advantages over spectral / Fourier domain OCT. Swept source OCT uses high speed detectors and does not require a spectrometer or line scan camera. Conventional silicon CCD or CMOS line scan cameras are sensitive only up to 1000 nm wavelengths. Although InGaAs line scan cameras are available and enable spectral OCT at longer wavelength, these camera have limited numbers of pixels and are relatively expensive. Swept source OCT can work at longer wavelengths such as 1050 nm or 1300 nm which is beyond the range of conventional line scan cameras. Imaging at long wavelengths is important for OCT applications in tissues other than the eye, where optical scattering limits image penetration.
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Swept source OCT also has several engineering advantages. Spectrometers have loss, are sensitive to alignment and are bulky. Since swept source OCT uses detectors rather than a spectrometer, it can be more compact and have higher sensitivity than spectral / Fourier domain OCT. Since imaging speeds are limited by sensitivity, swept source OCT could ultimately image faster than spectral / Fourier domain OCT. The frequency or wavelength resolution in a swept source system is determined by the laser linewidth and can be significantly better than a spectrometer based spectral / Fourier domain OCT system. This allows imaging to be performed with a greater depth range and higher number of axial pixels than possible with spectral / Fourier domain OCT. Finally, swept source OCT enables rapid imaging of larger fields of view than spectral / Fourier domain OCT because it does not have the fringe wash out problems which occur with rapid beam scanning in spectrometer based detection.
Frequency
Reference
Sample
Frequency time Sweep Beam Detector Output Splitter ∆L
Detector
time Figure 1.5. Swept source / Fourier domain OCT detection. A frequency swept light source is directed to an interferometer with a sample and reference path. Delayed light form the sample interfers with the reference beam and produces a beat signal which is measured by a high speed detector. The magnitude and time delay of the light can be measured by Fourier transforming the beat signal.
Figure 1.6 shows an experimental schematic of a swept source / Fourier-domain OCT instrument. A small portion (~5%) of the laser output is routed to an asymmetric Mach-Zehnder interferometer (MZI), measures the instantaneous optical frequency of the laser sweep. Prior to the Fourier transformation to form each axial line, the interference fringes must be evenly spaced in optical frequency. However, the frequency sweeps of swept laser sources are in generation nonlinear in time. Therefore, the frequency spacing of the MZI fringes are analyzed and used to resample the OCT fringes into linear frequency intervals. A high efficiency, dual-balanced Michelson interferometer detects the OCT signal. In this configuration, intensity noise from the laser source is cancelled out and the interferometric signal level is doubled by subtracting two out-of-phase interference fringes. The OCT beam is scanned over the sample by a pair of XY mirrors. A high speed 200MS/s, 2-channel, 14-bit A/D card is synchronized to the laser sweep and records the calibration and OCT signals. A computer then resamples the OCT signals, Fourier transforms the rescaled fringe signals to generate axial scan data and produces a final OCT image.
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Figure 1.6. Schematic diagram of a swept source / Fourier domain OCT system. The system requires a high speed swept laser and system performance depends directly on the laser performance. Imaging generation requires high speed detection and signal processing. Swept source / Fourier domain OCT utilizes many aspects of photonic communications technologies.
Swept lasers are a key technology for swept source OCT and many different types of lasers have been demonstrated. In swept-source / Fourier-domain OCT imaging, the imaging rate is the same as the sweep rate of the lasers. The imaging depth and axial resolution are related to the instantaneous linewidth and overall tuning range of the laser, respectively. Therefore, for high-quality, high-speed OCT imaging, it is desirable to use a laser with a high sweep rate, narrow instantaneous linewidth, and broad tuning range. Swept lasers incorporate a tunable, wavelength-selective filter element inside the cavity in order to produce a variable optical frequency over time. Two early studies were performed by our group used bulk optic designs and slow scan speeds, one using a Cr:Forsterite laser operating at 1250 nm with a sweep rate of 10 Hz , and another using an external cavity diode laser operating at 800 nm with a sweep rate of 2 kHz [28, 29]. However, only recently was it recognized that swept source OCT could be scaled to high imaging speeds. An all-fiber ring laser employing a fiber Fabry-Perot (FFP) tunable filter was demonstrated at a sweep rate of 200Hz in 2003 [5]. Hybrid bulk optic and fiber cavity designs using a fiber-coupled semiconductor amplifier as a gain medium and a diffraction grating for wavelength selection were developed and demonstrated to achieve high speeds [30, 31]. For these designs, frequency sweep rates of up to 115 kHz were achieved by using a polygon rotating mirror to sweep the operating wavelength [32].
Recently, we developed a new class of frequency-swept sources called Fourier-domain modelocked (FDML) lasers [20, 22]. These lasers precisely synchronize the wavelength selective element, typically an FFP filter, to the optical roundtrip time of the cavity. Each wavelength in the sweep perceives the filter to be stationary, thus allowing all wavelengths to build up and lase simultaneously within the cavity. This is termed quasi-continuous wave operation, and results in an unprecedented combination of sweep speed, instantaneous linewidth and tuning range. In comparison with traditional swept sources, the lasing does not need to build up from the gain medium each time while the filter is shifting. This non-continuous operation forces a tradeoff between sweep speed and the other performance characteristics [12].
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optical bandpass
RESONATOR “all” wavelengths are “stored” T = n*T simultaneously within sweep roundtrip the resonator optical delay optical
gain medium out-coupling
Figure 1.7. Fourier domain modelocked swept laser. High sweep speeds can be generated by using a long optical fiber delay line in the laser and storing the entire sweep and regerating it through the optical bandpass filter and gain. This approach overcomes tuning speed limits in standard lasers.
Our group achieved axial scan speeds of 370 kHz using FDML swept lasers in research OCT systems [21]. We also recently demonstrated ultrahigh speed ophthalmic swept source OCT imaging at 1050 nm [27]. In a recent study published in Nature Photonics [24] we demonstrated endoscopic imaging at 100 kHz axial scan speeds.
Figure 1.8 shows an example of swept source OCT imaging showing 3D-OCT imaging of the Drosophila at 42,000 A-scans per second. Drosophila is a widely accepted model in the study of developmental biology on inherited heart disease. Due the high speed of the OCT system, the rapid dynamics of the Drosophila heart could be captured. In additional to three-dimensional OCT images, M-mode OCT images can be continuously acquired to analyze the structural dynamics of the heart.
Figure 1.7. 3D-OCT imaging of the Drosophila using a high-speed swept-source / Fourier domain OCT system.
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References
[1] D. Huang, E. A. Swanson, C. P. Lin, J. S. Schuman, W. G. Stinson, W. Chang, M. R. Hee, T. Flotte, K. Gregory, C. A. Puliafito, and J. G. Fujimoto, "Optical Coherence Tomography," Science, vol. 254, pp. 1178-1181, Nov 22 1991. [2] J. S. Schuman, C. A. Puliafito, and J. G. Fujimoto, Optical coherence tomography of ocular diseases, 2nd edition. Thorofare, NJ: Slack Inc., 2004. [3] E. Regar, A. M. G. J. van Leeuwen, and P. W. Serruys, "Optical Coherence Tomography in Cardiovascular Research," Informa Healthcare, 2007. [4] W. Drexler and J. Fujimoto, "Optical Coherence Tomography: Technology and Applications " in (Biological and Medical Physics, Biomedical Engineering) Springer, 2008. [5] M. A. Choma, M. V. Sarunic, C. H. Yang, and J. A. Izatt, "Sensitivity advantage of swept source and Fourier domain optical coherence tomography," Optics Express, vol. 11, pp. 2183-2189, SEP 8 2003. [6] 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," Optics Letters, vol. 28, pp. 2067-2069, Nov 1 2003. [7] R. Leitgeb, C. K. Hitzenberger, and A. F. Fercher, "Performance of Fourier domain vs. time domain optical coherence tomography," Optics Express, vol. 11, pp. 889-894, 2003/04/21 2003. [8] B. Cense, N. Nassif, T. C. Chen, M. C. Pierce, S. Yun, B. H. Park, B. Bouma, G. Tearney, and J. F. de Boer, "Ultrahigh-resolution high-speed retinal imaging using spectral-domain optical coherence tomography," Optics Express, vol. 12, pp. 2435-2447, 2004. [9] N. A. Nassif, B. Cense, B. H. Park, M. C. Pierce, S. H. Yun, B. E. Bouma, G. J. Tearney, T. C. Chen, and J. F. de Boer, "In vivo high-resolution video-rate spectral-domain optical coherence tomography of the human retina and optic nerve," Optics Express, vol. 12, pp. 367-376, Feb 9 2004. [10] M. Wojtkowski, T. Bajraszewski, I. Gorczynska, P. Targowski, A. Kowalczyk, W. Wasilewski, and C. Radzewicz, "Ophthalmic imaging by spectral optical coherence tomography," Am J Ophthalmol, vol. 138, pp. 412-9, Sep 2004. [11] S. H. Yun, C. Boudoux, G. J. Tearney, and B. E. Bouma, "High-speed wavelength-swept semiconductor laser with a polygon-scanner-based wavelength filter," Optics Letters, vol. 28, pp. 1981-1983, Oct 15 2003. [12] R. Huber, M. Wojtkowski, K. Taira, J. G. Fujimoto, and K. Hsu, "Amplified, frequency swept lasers for frequency domain reflectometry and OCT imaging: design and scaling principles," Optics Express, vol. 13, pp. 3513-3528, May 2 2005. [13] R. A. 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," Optics Express, vol. 11, pp. 3116-3121, NOV 17 2003. [14] B. R. White, M. C. Pierce, N. Nassif, B. Cense, B. H. Park, G. J. Tearney, B. E. Bouma, T. C. Chen, and J. F. de Boer, "In vivo dynamic human retinal blood flow imaging using ultra-high-speed spectral domain optical Doppler tomography," Optics Express, vol. 11, pp. 3490-3497, DEC 15 2003. [15] B. J. Vakoc, S. H. Yun, J. F. de Boer, G. J. Tearney, and B. E. Bouma, "Phase-resolved optical frequency domain imaging," Optics Express, vol. 13, pp. 5483-5493, Jul 11 2005.
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[16] S. Makita, Y. Hong, M. Yamanari, T. Yatagai, and Y. Yasuno, "Optical coherence angiography," Optics Express, vol. 14, pp. 7821-7840, Aug 2006. [17] M. Wojtkowski, V. J. Srinivasan, T. H. Ko, J. G. Fujimoto, A. Kowalczyk, and J. S. Duker, "Ultrahigh-resolution, high-speed, Fourier domain optical coherence tomography and methods for dispersion compensation," Optics Express, vol. 12, pp. 2404-2422, MAY 31 2004. [18] B. Potsaid, I. Gorczynska, V. J. Srinivasan, Y. Chen, J. Liu, J. Jiang, A. Cable, J. S. Duker, and J. G. Fujimoto, "Ultrahigh speed spectral/Fourier domain OCT imaging in ophthalmology," in Optical Coherence Tomography and Coherence Techniques IV, Munich, Germany, 2009, pp. 73721P-9. [19] B. Potsaid, I. Gorczynska, V. J. Srinivasan, Y. L. Chen, J. Jiang, A. Cable, and J. G. Fujimoto, "Ultrahigh speed Spectral/Fourier domain OCT ophthalmic imaging at 70,000 to 312,500 axial scans per second," Optics Express, vol. 16, pp. 15149-15169, 2008. [20] R. Huber, M. Wojtkowski, and J. G. Fujimoto, "Fourier Domain Mode Locking (FDML): A new laser operating regime and applications for optical coherence tomography," Optics Express, vol. 14, pp. 3225-3237, Apr 17 2006. [21] D. C. Adler, R. Huber, and J. G. Fujimoto, "Phase-sensitive optical coherence tomography at up to 370,000 lines per second using buffered Fourier domain mode-locked lasers," Optics Letters, vol. 32, pp. 626-628, Mar 2007. [22] R. Huber, D. C. Adler, and J. G. Fujimoto, "Buffered Fourier domain mode locking: unidirectional swept laser sources for optical coherence tomography imaging at 370,000 lines/s," Optics Letters, vol. 31, pp. 2975-2977, Oct 2006. [23] R. Huber, D. C. Adler, V. J. Srinivasan, and J. G. Fujimoto, "Fourier domain mode locking at 1050 nm for ultra-high-speed optical coherence tomography of the human retina at 236,000 axial scans per second," Optics Letters, vol. 32, pp. 2049-2051, Jul 2007. [24] D. C. Adler, Y. Chen, R. Huber, J. Schmitt, J. Connolly, and J. G. Fujimoto, "Three-dimensional endomicroscopy using optical coherence tomography," Nature Photonics, vol. 1, pp. 709-716, Dec 2007. [25] D. C. Adler, C. Zhou, T. H. Tsai, H. C. Lee, L. Becker, J. M. Schmitt, Q. Huang, J. G. Fujimoto, and H. Mashimo, "Three-dimensional optical coherence tomography of Barrett's esophagus and buried glands beneath neosquamous epithelium following radiofrequency ablation," Endoscopy, vol. 41, pp. 773-776, 2009. [26] D. C. Adler, C. Zhou, T. H. Tsai, J. Schmitt, Q. Huang, H. Mashimo, and J. G. Fujimoto, "Three-dimensional endomicroscopy of the human colon using optical coherence tomography," Optics Express, vol. 17, pp. 784-796, 2009. [27] V. J. Srinivasan, D. C. Adler, Y. L. Chen, I. Gorczynska, R. Huber, J. S. Duker, J. S. Schuman, and J. G. Fujimoto, "Ultrahigh-Speed Optical Coherence Tomography for Three-Dimensional and En Face Imaging of the Retina and Optic Nerve Head," Investigative Ophthalmology & Visual Science, vol. 49, pp. 5103-5110, Nov 2008. [28] S. R. Chinn, E. A. Swanson, and J. G. Fujimoto, "Optical coherence tomography using a frequency-tunable optical source," Optics Letters, vol. 22, pp. 340-342, Mar 1 1997. [29] B. Golubovic, B. E. Bouma, G. J. Tearney, and J. G. Fujimoto, "Optical frequency-domain reflectometry using rapid wavelength tuning of a Cr4+:forsterite laser," Optics Letters, vol. 22, pp. 1704-1706, Nov 15 1997. [30] S. H. Yun, G. J. Tearney, B. E. Bouma, B. H. Park, and J. F. de Boer, "High-speed spectral-domain optical coherence tomography at 1.3 mu m wavelength," Optics Express,
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vol. 11, pp. 3598-3604, DEC 29 2003. [31] S. H. Yun, G. J. Tearney, J. F. de Boer, and B. E. Bouma, "Motion artifacts in optical coherence tomography with frequency-domain ranging," Optics Express, vol. 12, pp. 2977-2998, JUN 28 2004. [32] W. Y. Oh, S. H. Yun, G. J. Tearney, and B. E. Bouma, "115 kHz tuning repetition rate ultrahigh-speed wavelength-swept semiconductor laser," Optics Letters, vol. 30, pp. 3159-3161, DEC 1 2005.
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2. Ophthalmic Optical Coherence Tomography
Sponsors National Institutes of Health - RO1-EY11289-23, R01-EY13178-07, P30-EY008098 National Science Foundation - BES-0522845 Air Force Office of Scientific Research - FA9550-07-1-0101 and FA9550-07-1-0014
Project Staff Prof. James G. Fujimoto, Dr. Yueli Chen, Dr. Iwona Gorczynska, Dr. Vivek J. Srinivasan, Dr. Ben Potsaid, Jonathan J. Liu (MIT) Dr. Jay S. Duker, Varsha Manjunath, Joseph Ho (New England Eye Center) Dr. Joel Schuman (University of Pittsburgh Medical Center) Dr. Allen Clermont, Dr. Edward Feener (Joslin Diabetes Center)
2.1 OCT in Ophthalmology
Optical coherence tomography (OCT) has hard the largest clinical impact in ophthalmology. OCT is non-contact and can perform micron scale, cross sectional and three dimensional imaging of tissue morphology in real time. In ophthalmology, OCT provides information that is impossible to obtain by any other non-invasive technique. OCT has become a standard diagnostic tool in ophthalmology, enabling more sensitive diagnosis of disease, elucidating disease pathogenesis, progression, and response to treatment in major retinal diseases such as age-related macular degeneration, diabetic retinopathy, and glaucoma.
Our group and collaborators were responsible for the invention and initial development of OCT. The first report of OCT was published in Science in 1991 and demonstrated ex vivo imaging of the human retina and atherosclerotic plaque [1]. Our initial studies focused on ophthalmic imaging [2-4]. We developed a prototype clinical OCT system and in 1993 began clinical OCT imaging studies in collaboration with investigators Drs. Carmen Puliafito, M.D. and Joel Schuman, M.D. at the New England Eye Center (NEEC). Several thousand patients were imaged at the New England Eye Center using our prototype instrument during the 1990s. Our group performed many of the first cross-sectional and longitudinal studies of a wide range of ophthalmic diseases. For example, our group performed the first studies that suggested OCT measurements of nerve fiber layer (NFL) thickness will be useful for diagnosis and monitoring of glaucoma [5-7]. We also performed the first studies demonstrating OCT mapping of macular thickness in retinal edema [8]. We developed imaging protocols that became clinical standards used in commercial OCT instruments (StratusOCT from Carl Zeiss Meditec) [2-4] OCT technology was patented and our group in collaboration with Dr. Carmen Puliafito, M.D., (now Dean of the Keck School of Medicine at USC) and Eric Swanson (co-founder of Sycamore Networks) transferred the technology to Carl Zeiss Meditec. The first commercial clinical OCT instrument was introduced into the ophthalmic market in 1996. OCT gained widespread clinical acceptance with the introduction of the third generation instrument, the Stratus OCT (Carl Zeiss Meditec) in 2002 and is now a standard imaging method in ophthalmology.
2.2 Technology for Ophthalmic OCT
Recent advances in OCT imaging speed using spectral / Fourier domain detection techniques have enabled dramatic increases in imaging speed and performance [9-17]. Commercial development in ophthalmology proceeded rapidly with multiple companies introducing spectral / Fourier domain OCT instruments in 2006. Early studies demonstrated the generation of en face OCT fundus images from raster scanned three dimensional (3D-OCT) data sets which enable registration of cross sectional images to fundus features [17, 18], 3D rendering and visualization of
17-13 Chapter 17. Biomedical Optical Imaging the normal retina and retinal pathologies [19, 20] and thickness mapping of retinal NFL and intra-retinal layers [19, 21] .
Previous OCT systems were based on time-domain detection, where a low coherence light source is used with a Michelson interferometer with a sample arm and a reference arm with a scanning delay. Measurements of the echo time delay of backscattered or backreflected light are performed by using a Michelson interferometer with a mechanically scanned optical reference path (Figure 2.1A) [1]. Time-domain OCT has made a significant clinical impact in the field of ophthalmology and lead to the Stratus OCT (Carl Zeiss Meditec, Dublin, CA) system for retinal OCT imaging which gained widespread clinical use.
Fourier domain OCT measures echo time delays of light by Fourier transforming the interference spectrum of the light signal. Different echo time delays of light produce different frequencies of fringes in the interference spectrum. Fourier domain OCT detection can be performed in two ways: spectral / Fourier domain OCT using a spectrometer with a high speed linescan camera (Figure 2.1B) [9-13, 15, 17] or swept-source / Fourier domain OCT using a rapidly tunable laser source (Figure 2.1C) [12, 22-24]. The retinal scanning module is common to all three OCT technologies shown, thereby resulting in similar patient interfaces (Figure 2.1D).
(a) (b) Reference arm Femtosecond Reference arm Ti:Sapphire laser Ti:Sapphire laser or broadband SLD FC PC CL DC NDF Mirror FC1 PC CL DG CL PD1 RSDL Electronic FC2 RSM CL Numerical SOL and numerical PC data processing PC CL data processing RSM CCD PD2 Detection module Interferometer Object arm Detection module Interferometer Object arm
(c) Sweep trigger (d) Electronic Frequency tunable bandpass CSG laser filter FC PD-cal XY Scanning mirrors A/D converter Circulator Reference arm Scan 1 Numerical 2 lens data processing PD1 3 FC PC CL DC NDF Mirror Biomicroscope ocular RSM PD2 PC CL Dichroic Image Ocular Detection module Interferometer Object arm mirror plane lens
Figure 2.1. Schematic of OCT technologies used for ophthalmic imaging. A) Time-domain OCT using a low coherence light source and an interferometer with a scanning reference arm. B) Spectral / Fourier domain OCT using a low coherence light source and an interferometer with a spectrometer and high speed line scan camera. C) Swept source / Fourier domain OCT using a frequency swept laser and an interferometer with high speed detectors. D) Retinal scanning module common to all three methods of OCT. Fourier domain detection methods (B-C) enable dramatic increases in sensitivity and speed, enabling three dimensional OCT (3D-OCT) imaging.
In 2004, we built prototype instruments for use in the ophthalmology clinics of the New England Eye Center (NEEC) and the Eye Center of the University of Pittsburgh Medical Center (UPMC). Working in collaboration with Dr. Jay S. Duker, M.D., Chairman of Ophthalmology at the Tufts University School of Medicine and Dr. Joel Schuman, M.D., Chairman of Ophthalmology at the University of Pittsburgh Medical School, we began clinical studies two years before the commercial introduction of spectral / Fourier domain OCT instruments. We have imaged several
17-14 RLE Progress Report 151 Chapter 17. Biomedical Optical Imaging thousand patients to date and published many of the first studies using spectral / Fourier domain OCT in clinical ophthalmology [19, 25-32].
2.3 Ultrahigh Speed Spectral / Fourier Domain OCT Retinal Imaging
The current generation ophthalmic OCT systems use spectral / Fourier domain detection based on a spectrometer and a high speed line scan camera. Spectrometer based OCT systems can use superluminescent diode (SLD) light sources with broad bandwidths to achieve high axial resolutions, as well as leverage the existing infrastructure of high speed line scan cameras and frame grabbers. Recent advances in CMOS and InGaAs linescan camera technology now enable a new generation of ultrahigh speed spectral / Fourier domain OCT imaging systems, although tradeoffs between imaging speed, resolution, and sensitivity roll-off must still be carefully considered. We have developed and evaluated different configurations of ultrahigh speed spectral / Fourier domain ophthalmic imaging systems that operate at both 850 nm and 1050 nm.
Ultrahigh speed (70,000 - 315,000 axial scans per second) and high resolution (2.5 – 8 um) imaging at 850 nm are enabled by new CMOS linescan sensor technology for imaging [33]. These new CMOS cameras have the advantage that the have a very large number of pixels and therefore can support very high axial image resolutions. In addition, they can operate in different modes where varying numbers of pixels can be read, allowing multiple operating regimes that optimize either resolution or speed.
B A Figure 2.2. (A) Cross sectional images from a 3D volumetric acquisition of the macula acquired at 250,000 axial scans per second with an ultrahigh speed spectral / Fourier domain ophthalmic OCT imaging system using new CMOS line scan camera technology. (B) Volumetric rendering of the data from (A). (C) High density volumetric rendering of 200x256 um (100x128 pixel) region of the retina with two axial plane images at the depths of the capillaries above and below the INL layer. The zoomed view shows the capillary layers. Red arrows point to bright spheres along the capillary network that might be individual red blood cells.
Figure 2.2A shows selected cross sectional images from a 3D volumetric raster scanned data set acquired at 250,000 axial scans per second using CMOS linescan camera technology. The individual cross sectional images can be registered, enabling the generation of 3D volumetric renderings as shown in Figure 2.2B. In this volume, the ultrahigh acquisition speeds reduce motion artifacts, while post-processing registration methods corrected for residual eye motion to generate volumes that represent the true retinal contours. Figure 2.11(C) shows a small volume acquisition with high lateral sampling density. The fast speeds and high lateral resolution enable the visualization of retinal capillaries and improve visualization of small features. Zooming in on the capillaries reveals small spheres, which might be individual blood cells traveling within the capillary network.
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Volumetric acquisitions of the optic nerve head were acquired with an ultrahigh resolution (~3 um) configuration operating at 106,382 axial scans per second [33]. Figure 2.3a shows a cross sectional image highlighting the lamina cribrosa of the optic nerve head. Measuring changes in the lamina cribrosa may enable more sensitive assessment of glaucoma progression. The cross sectional image was formed by median filtering 5 adjacent B-scans from within the volume and shows enhanced contrast. A OCT fundus image of the disk generated by axially summing the 3D-OCT data set is shown in Figure 2.3b. Figures 2.3c-f show en face images of selected depth regions at increasing depth into the optic nerve head. The porous structure and fine detail of the lamina cribrosa can clearly be seen. The high acquisition speeds enable large data sets with high transverse resolution and also reduce motion artifacts which is especially important when imaging small features.
The results of this study suggest that ultrahigh speed OCT can achieve a significant improvement in performance for ophthalmic imaging. This technology promises to have a powerful impact in clinical applications, improving early diagnosis, reproducibility of quantitative measurements and enabling more sensitive assessment of disease progression or response to therapy.
Figure 2.3. Cross sectional and en face images from a 3D-OCT data set acquired at 106,382 axial scans per second with a spectral / Fourier domain OCT imaging system. (a) Cross sectional image of the optic nerve head. This image was formed by median filtering of 5 adjacent cross sectional scans. (b) OCT fundus image generated from the 3D-OCT of the optic nerve head. (c)-(f) Projection OCT en face view of the optic nerve head showing the porous structure of the lamina cribrosa at progressively increasing depths. All scale bars are 200 um.
Imaging at 1050 nm wavelengths
Recently there has been considerable interest in OCT imaging at longer, 1050 nm wavelengths [34-39]. Imaging at 1050 nm wavelengths has the advantage of reduced tissue scattering and deeper imaging penetration into the retina compared with 800 nm used in standard ophthalmic instruments. Although water absorption in the vitreous of the eye increases attenuation at 1050 nm,
17-16 RLE Progress Report 151 Chapter 17. Biomedical Optical Imaging ocular exposures can be higher than at 800 nm, yielding comparable sensitivities. The main limitation is that water absorption peaks at 1000 nm and 1100 nm limit the achievable axial resolutions to ~5-7 um. Long wavelength OCT enables improved imaging of choroidal thickness and vasculature, visualization of structures beneath the RPE and pigment epithelial detachments (PED) as well as structures inside the optic nerve head, such as the lamina cribrosa [34-39]. 3D-OCT volumetric data will enable mapping choroidal thickness and vasculature. The ability to image internal structure of the optic nerve head and lamina cribrosa may be useful for detecting glaucoma.
Our group has recently developed a 1050 nm spectral / Fourier domain OCT prototype using a new InGaAs line-scan camera operating at ~50,000 axial scans per second with ~9 um resolution. Figure 2.4 shows OCT data obtained with the prototype system. The high imaging speed reduces eye motion. Deep penetration into the optic nerve head and choroid are seen, enabled by the high instrument sensitivity and reduced scattering at this wavelength. The ability to acquire densely sampled volumetric data without motion artifacts at both 800 nm and 1050 nm, as well as to perform repeated volumetric imaging to measure dynamic functional processes, promise to be a powerful tools for ophthalmic research.
Figure 2.4. OCT retinal images with an InGaAs camera based spectral / Fourier domain OCT imaging system operating with a 1050 nm light source at 47,000 axial scans per second. (A) Cross sectional image of the disk created by averaging 8 registered cross sectional images consisting of 2000 axial scans per image collected from the same region of the retina. All scale bars represent 100 um. (B) 3D-OCT volumetric rendering showing deep penetration into the choroid.
2.4 Swept Source / Fourier domain OCT Imaging at 1050 nm Wavelengths
Swept source OCT is a complementary technology to spectral / Fourier domain OCT and has the advantage that it does not require a spectrometer and line scan camera. Therefore it is more readily scalable to imaging at longer wavelengths, without the need for costly InGaAs line scan cameras. We obtained record imaging speeds using new swept laser technology developed in our group, Fourier domain modelocked (FDML) lasers [40-42]. FDML lasers enable very high speed swept laser operation by storing the sweep in a long optical fiber delay line in the laser cavity. The cavity has a tunable filter which is swept at the round trip time of the laser cavity to generate high sweep repetition rates.
Using swept source / Fourier domain OCT with FDML laser technology, we demonstrated retinal imaging with 8 um axial resolutions at axial scan speeds of 250 kHz, 10x faster than standard commercial spectral / Fourier domain OCT instruments [39]. Volumetric 3D-OCT data sets of 512x425 axial scans can be acquired in only ~1 second and data sets of 512x800 axial scans cam
17-17 Chapter 17. Biomedical Optical Imaging be acquired in ~2 seconds. Figure 2.5 shows projection OCT fundus images from different depths which enable visualization of the lamina cribrosa in the optic nerve head, the nerve fiber layer, and other retinal layers and choroid in the macula. The high imaging speeds enable high transverse pixel densities to generate high resolution en face images. It was possible to identify fine retinal structures, such as thin fiberous nerve bundles and capillaries, by selectively displaying specific depths in the 3D-OCT volumetric data. OCT images of the lamina cribrosa in the optic nerve head are consistent with known histology [43] and three-dimensional assessment is possible, enabling measurement of the laminar pore size at different depths. Measurements such as these will be important in determining the pathophysiology of diseases such as glaucoma.
A Depth: 168 μm Depth: 420 μm
200 μm
B NFL GCL Vessels INL Capillaries Choroid Choroid
500 μm
Figure 2.5. Swept source OCT using Fourier domain modelocked (FDML) lasers enables extremely high imaging speeds of 250,000 axial scans per second at 1050 nm wavelengths. By processing a 3D-OCT data set (A), enhanced visualization of individual intraretinal layers is possible. Different layers are delineated and summed in the axial direction to produce projection OCT images. En face visualizations of internal structures such as the lamina cribrosa of the optic nerve head (top) are possible and correspond to reference histology (top, right). Structures such as the nerve fiber layer (NFL), blood vessels in the ganglion cell layer (GCL), and capillary network of the inner nuclear layer (INL) can be visualized. Selectively displaying deep layers behind the retinal pigment epithelium enables visualization of the vascular structure of the choroid (bottom right). All of these images are generated from a single 3D-OCT data set consisting of 512x850 axial scans.
In summary, long wavelength imaging at 1050 nm enables excellent image penetration and visualization of the structures such as the choroid, sclera, and lamina cribrosa. The ultrahigh imaging speeds enable the acquisition of large 3D-OCT data sets which are necessary to obtain high pixel densities for en face image generation. 3D-OCT data provide comprehensive volumetric structural information and allows novel methods for visualizing the anatomy of the retina and optic nerve head such as the nerve fiber layer bundles, intraretinal layer blood vessels and capillary network, photoreceptors, retinal pigment epithelium and the lamina cribrosa.
2.5 Clinical OCT Studies
Ultrahigh resolution spectral / Fourier domain OCT provides significantly increased sensitivity, imaging speed and image quality. The high speeds enabled raster scanning, which improves retinal coverage, thereby avoiding sampling errors in the detection of focal pathologies, and enables three-dimensional (3D-OCT) volumetric imaging while preserving retinal topography [19, 25]. 3D-OCT datasets provide comprehensive information about retinal structure and can be used
17-18 RLE Progress Report 151 Chapter 17. Biomedical Optical Imaging to extract retinal layer thickness maps, retinal nerve fiber layer thickness maps, and optic nerve head contour information. OCT fundus images that show features such as blood vessels can also be created by using 3D-OCT data. Individual cross-sectional OCT images are automatically registered to the OCT fundus image. This enables correlation of 3D-OCT findings with standard ophthalmic examination.
Clinical studies using several generations of prototype OCT instruments have been performed at the New England Eye Center, the University of Pittsburgh Medical Center and collaborating institutions. Our high-speed ultrahigh resolution OCT prototype provides new information about retinal structure that complements standard diagnostic techniques such as fluorescein angiography (FA), indocyanine green angiography (ICG) or fundus photography by providing cross-sectional and three dimensional images of micron-scale pathological changes. In order to take full advantage of this ability in ophthalmology, systematic survey and longitudinal studies of pathologies are necessary. These studies illustrate features that are characteristic of various retinal pathologies and aid ophthalmologists in the interpretation of OCT images.
Quantitative OCT measurements of retinal structure
In a recent study, we demonstrated thickness mapping of detailed photoreceptor outer segment morphology and investigated age related changes in the normative population [31]. Imaging was performed with a 2.8 um axial resolution, high-speed, ultrahigh resolution OCT research prototype instrument to visualize fine features in the outer retina and establish a baseline for interpreting ultrahigh resolution OCT. Figure 2.5 shows a papillomacular OCT image with outer retinal layers labeled. Comparison with known photoreceptor morphology and rod/cone distribution enables interpretation of outer retinal structures [44]. Rods are absent in the foveola, where cones extend to the RPE apical surface (Figure 2.5D). Cone outer segment (COS) length is greatest in the foveola and decreases with increasing eccentricity (Figure 2.5C), where the cone outer segment tips are displaced proximally from the RPE (Figure 2.5E). In addition, we characterized normal outer retinal morphology by automated segmentation of the outer retinal scattering bands in spectral / Fourier domain OCT images.
Figure 2.6. Ultrahigh resolution spectral / Fourier domain OCT enables detailed visualization of rod and cone outer segments and RPE. (A) Fundus photograph showing the OCT scan location. (B) Papillomacular OCT scan showing change in outer retinal appearance from the fovea to the near periphery. (C) Enlargement of boxed region in (B). OCT images showing rod and cone outer segments from the foveola (D) and near the periphery (E) compared to published histology. Cones and rods are labeled on the histology images for reference.
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To investigate variations in the normal population, imaging was performed with our clinical spectral / Fourier domain OCT prototype at 3.5 um axial resolution. Quantitative thickness mapping of the photoreceptor inner segments, outer segments, and the RPE was performed on 70 eyes of 43 subjects (mean age, 42.7+/-17.4 years; range 19-81 years) and quantitative results analyzed with a linear mixed effects model. Figure 2.7B,C show quantitative measurement of outer retinal features. Figure 2.7D shows individual retinal layer thicknesses can be calculated and displayed as color maps. Quantitative maps showed differences between the cone-dominated fovea and the rod-dominated parafovea and perifovea which correlate well with published histological studies [44]. Age-related changes in the measurements were found, suggesting age-related changes in the photoreceptors. These results established a normative baseline for outer retinal morphology and will aid in distinguishing disease.
Figure 2.7. Photoreceptor outer segments and RPE can be mapped with ultrahigh resolution spectral / Fourier domain OCT. (A) Fundus image showing scan pattern. (B) OCT image and zoom view (C) showing software segmentation of photoreceptor and RPE features. Segmentation software detects the external limiting membrane, the photoreceptor inner segment / outer segment junction inner and outer boundaries, the inner boundary of the cone outer segment tips, the outer boundary of Bruch’s membrane, and the vitreoretinal interface. (D) Individual retinal layer thicknesses can be calculated and displayed as color maps. Concentric circles with diameters of 0.75, 1.5, 2.25, and 3.0 mm are shown for reference.
These studies also suggest the potential to measure risk markers for progression of disease, such as RPE and Bruchs membrane thickening and photoreceptor changes in age related macular degeneration (AMD).
En Face projection OCT
High-speed spectral / Fourier domain OCT enables the acquisition of large 3D-OCT data sets, requiring analysis of numerous cross sectional images to identify subtle structural changes.
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Recently, our group developed image processing techniques to rapidly assess 3D-OCT data and enable comparison to standard retinal fundus imaging [32, 39]. Projection OCT generates en face fundus images which can be correlated with fundus photography and fluorescein angiography. This technique selectively displays specific depth ranges in the retina, enhancing the contrast to retinal structure alterations. Projection OCT fundus imaging visualizes retinal pathology in a small number of en face images, facilitating rapid analysis of the overall state of the fundus (Figure 2.8). This enhances the ability of ultrahigh resolution 3D-OCT to visualize microstructural changes in the retina providing information complementary to standard ophthalmic diagnostics. New ultrahigh speed OCT imaging systems enable high axial scan densities for projection OCT fundus (C-mode) imaging and can reduce eye motion artifacts to improve measurement reproducibility.
Fundus photo OCT fundus image Inner retina ONL and PR IS PR OS 1
2
RPE Choroid-vessels OCT crosscross-section sectional image 1 OCT cross sectional image 2 (B-scan) m m μ μ 100 100 300μm 300μm Figure 2.8. Projection OCT fundus imaging. The images show an example of soft, confluent drusen in age related macular degeneration AMD. The OCT fundus image correlates well with the fundus photo. The set of projection images from different retinal depth levels reveal more details of the pathology and show RPE and photoreceptor layer disruption which is difficult to see using conventional imaging. The cross-sectional OCT images can be registered to the en face images.
Interactive Science Publication (ISP)
The ISP is a collaborative project between the Optical Society of America (OSA) and National Library of Medicine to introduce a new paradigm for publication of large digital data sets. In a joint effort with the OSA, we helped develop a special issue on OCT in ophthalmology for the online journal, Optics Express (March 2009, co-edited by Wolfgang Drexler, James Fujimoto, Christoph Hitzenberger and Joel Schuman) where twenty invited papers from leading research groups were presented covering OCT in retinal disease, glaucoma, advances in technology and image processing. Our group published a case series showing examples of small hard drusen, larger confluent drusen, pigment epithelial detachments, geographic atrophy and wet AMD with choroidal neovascularization selected from over 400 AMD patients [45]. Providing open access to well documented clinical data sets can help support image processing research to develop new techniques for visualizing or analyzing data sets, as well as enable independent evaluation of new algorithms or testing of statistical findings.
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Clinical Studies of Retinal Disease
Clinical studies are being performed in collaboration with Dr. Jay S. Duker, M.D., Chairman of Ophthalmology at the Tufts University School of Medicine and Dr. Joel Schuman, M.D., Chairman of Ophthalmology at the University of Pittsburgh Medical School. We present brief highlights of these studies here.
Ultrahigh resolution spectral / Fourier domain OCT enables detailed assessment of the retinal photoreceptor layer and promises to have important applications for studies of diseases such as age related macular degeneration (AMD). AMD is the leading cause of blindness in the elderly in developed countries including the United States. AMD is generally classified into two subgroups: non-exudative (dry) and exudative (wet) AMD. Recently, vascular endothelial growth factor (VEGF) inhibiting therapies such as intravitreal injections of ranibizumab (Lucentis) and bevacizumab (Avastin) have shown remarkable clinical efficacy. Wet AMD was studied longitudinally before and after ranibizumab (anti-VEGF) injection in 12 eyes of 12 patients [46]. Figure 2.9 shows an example of OCT imaging of AMD before and after treatment. Volumetric spectral / Fourier domain OCT measurements showed a reduction in sub-RPE and sub-retinal fluid after injection (p=0.01), with no detectable change in fibrovascular lesion volume (p=0.26). Ultrahigh resolution spectral / Fourier domain OCT imaging showed photoreceptor IS/OS junction disruptions above the fibrovascular lesion in all 12 eyes which remained after treatment. These results suggest that while ranibizumab improves overall retinal architecture, some photoreceptor damage may be irreversible. Larger scale studies using ultrahigh resolution imaging would be of interest to assess details of photoreceptor preservation or impairment following treatment.
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Figure 2.9. Ultrahigh resolution spectral / Fourier domain OCT image of age related macular degeneration. (A) Color fundus photograph and (B) Late-phase fluorescein angiogram illustrating hard exudates in the inferior macula and a primarily occult lesion with a classic component near the fovea. OCT cross-sectional image before (C) and after ranibizumab (D) treatment showing improved retinal contour, primarily because of the resolution of subretinal fluid.
A survey study of glaucoma showed that ultrahigh resolution spectral / Fourier domain OCT compared to StratusOCT improved visualization of intraretinal layers relevant to the detection and management of glaucoma [30]. Ultrahigh resolution allowed visualization of individual retinal layers including the GCL, which is specifically prone to glaucomatous damage. Fast scanning and enhanced axial scan registration enabled by ultrahigh resolution spectral / Fourier domain OCT provided detailed maps of the macula and optic nerve head, including en face OCT fundus images and NFL thickness maps.
Several studies on reproducibility and error analysis in macular and retinal NFL thickness measurements were performed. The variability in mean NFL thickness measurements due to scan circle location was examined analyzing 3D-OCT datasets from 17 normal eyes acquired using the
17-23 Chapter 17. Biomedical Optical Imaging clinical prototype spectral / Fourier domain OCT system [29]. NFL thickness was re-sampled along a circle centered on the ONH, then along circles shifted horizontally, vertically and diagonally using custom-designed software. The results show that the location of the OCT scan circle affects NFL thickness measurements and accurate registration of OCT scans is essential for measurement reproducibility and longitudinal examination.
In addition to our prototype ultrahigh resolution system we also investigated commercial spectral / Fourier domain OCT systems including Zeiss Cirrus, Optovue RTVue, and Topcon OCT-1000. In one study, we examined the reproducibility of NFL measurements using the Cirrus OCT compared with Stratus OCT [47]. This study showed that 3D-OCT data (cube data) with post processing measurement of a circumpapillary scan significantly improved reproducibility over time domain Stratus OCT. This study also indicated that residual eye motion during the scanning causes registration errors within a 3D-OCT data set, suggesting that higher acquisition speeds and image processing to perform registration could further improve performance.
2.6 Functional OCT Imaging in Human Retina
In addition to imaging retinal morphology, OCT can also provide depth-resolved information on retinal physiology [48]. We previously reported investigations of functional OCT imaging performed in the rat and demonstrated the ability to image photoreceptor changes with light stimulus [49]. A white-light stimulus was applied to the dark-adapted retina and the average reflectivities from different intraretinal layers monitored as a function of time using rapid, repeated volumetric OCT scanning. A ~10% increase in the average amplitude reflectance of the photoreceptor outer segments was observed in response to the stimulus. The spatial distribution of the change in the OCT signal was consistent with an increase in backscatter from the photoreceptor outer segments. To our knowledge, this is the first in vivo demonstration of OCT functional imaging in the intact retina.
Recently, we demonstrated OCT functional imaging in the human eye [50]. This study measured stimulus-induced, intrinsic optical scattering changes in the human retina in vivo using an ultrahigh resolution spectral / Fourier domain OCT system at 50,000 axial scans per second and ~3 um axial resolution. A visible light stimulus was used and the near-infrared OCT beam monitored retinal reflectance by rapid volumetric scanning. A carefully designed stimulus and normalization protocol was used to control for effects such as eye motion and accommodation. Multiple trial averaging and statistical analysis were used to confirm stimulus-induced signals (figure 2.5). This study showed multiple intrinsic signals originating from different axial locations in the OCT image, the photoreceptor inner and outer segment IS/OS junction and the rod outer segment tip region, just proximal to the RPE. The measurement of inner retinal neural or hemodynamic intrinsic signals might be useful for assessing neural transduction and neurovascular coupling.
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Individual Trials Δγ(t) Average Response Δγ(t) C A 0.1 B 0.1 Stimulated 0.04 stimulate side 1 stimulate side 2 Illuminatedregion region 0.035 estimated local response 0.05 0.05 0.03
0.025 0 0 0.02
-0.05 -0.05 0.015 fractional change fractional change 0.01 Stimulus Stimulus -0.1 -0.1 0 0.5 1 1.5 2 0 0.5 1 1.5 2 0.005 t (seconds) t (seconds) Δγavg C 0.1 D Unwrapped, flattenedstimulate side 3D 1 OCT Data Set stimulate side 2
0.05 RPE IS / OS
0
-0.05
fractional change 100 200 300 400 500 axial position (microns) -0.1 0 5 10 15 trial number T - statistic r = r E Ref RPE 8 r Ref = r Tot 6 4 P = 0.01 2 0 -2 100 200 300 400 500 axial position (microns)
Figure 2.10. OCT functional imaging in the human retina. Stimulus induced changes in reflectivity are shown for individual trials (A) and averaged (B). Response is localized to the stimulated region of retina (C) during randomized trials. The response was statistically evaluated and localized to the photoreceptor IS/OS junction (E,F).
2.7 Small Animal Retinal Imaging
Research on ocular diseases is often limited by the restrictions on studying pathophysiologic processes in the human eye. Also, many ocular diseases in humans are genetic in origin, but often appropriate subjects are not available for genetic studies. Murine (rat and mouse) models of ocular disease provide powerful tools for the analysis and characterization of disease pathogenesis and response to treatment. While enucleation and histology provide the gold standard to characterize microstructural changes in animals, non-invasive structural imaging has the potential to reduce the need for sacrifice and histology in many studies [51].
In this study, a prototype ultrahigh resolution spectral / Fourier domain OCT prototype instrument using new, high-speed CMOS imaging technology was built. This technology can achieve imaging speeds >70,000 axial scans per second and axial image resolutions of ~3 um [33]. A microscope delivery system is used to focus and scan the OCT beam in the animal eye. In addition to 3D-OCT data sets of the rat retina, Doppler OCT analysis of blood flow in the rat retina was performed. Doppler OCT provides non-invasive in vivo quantitative measurements of retinal blood flow properties [52-54], and it may benefit studies involving glaucoma and diabetic retinopathy. Ultrahigh resolution spectral / Fourier domain OCT promises to enable novel protocols to measure retinal structure and retinal blood flow in small animals.
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Figure 2.11. Quantitative Doppler OCT measurement in the axial direction showing pulsatile blood flow. (A) Pulsatile blood flow showing a heart rate of ~300 beats/min. (B, C) Doppler OCT images (65x100 um2 region of interest) and blood flow measurements showing pulsatility during two cardiac cycles. Repeated Doppler OCT scans (512 axial scans) over a 250 u m cross section were acquired for ~1.8 seconds.
References
[1] D. Huang, E. A. Swanson, C. P. Lin, J. S. Schuman, W. G. Stinson, W. Chang, M. R. Hee, T. Flotte, K. Gregory, C. A. Puliafito, and J. G. Fujimoto, "Optical Coherence Tomography," Science, vol. 254, pp. 1178-1181, Nov 22 1991. [2] E. A. Swanson, J. A. Izatt, M. R. Hee, D. Huang, C. P. Lin, J. S. Schuman, C. A. Puliafito, and J. G. Fujimoto, "In vivo retinal imaging by optical coherence tomography," Optics Letters, vol. 18, pp. 1864-1866, 1993/11/01 1993. [3] M. R. Hee, J. A. Izatt, E. A. Swanson, D. Huang, J. S. Schuman, C. P. Lin, C. A. Puliafito, and J. G. Fujimoto, "Optical coherence tomography of the human retina," Archives of Ophthalmology, vol. 113, pp. 325-332, Mar 1995. [4] C. A. Puliafito, M. R. Hee, C. P. Lin, E. Reichel, J. S. Schuman, J. S. Duker, J. A. Izatt, E. A. Swanson, and J. G. Fujimoto, "Imaging of macular diseases with optical coherence tomography," Ophthalmology, vol. 102, pp. 217-229, Feb 1995. [5] J. S. Schuman, M. R. Hee, A. V. Arya, T. Pedut-Kloizman, C. A. Puliafito, J. G. Fujimoto, and E. A. Swanson, "Optical coherence tomography: a new tool for glaucoma diagnosis," Current Opinion in Ophthalmology, vol. 6, pp. 89-95, Apr 1995.
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[6] J. S. Schuman, M. R. Hee, C. A. Puliafito, C. Wong, T. Pedut-Kloizman, C. P. Lin, E. Hertzmark, J. A. Izatt, E. A. Swanson, and J. G. Fujimoto, "Quantification of nerve fiber layer thickness in normal and glaucomatous eyes using optical coherence tomography," Archives of Ophthalmology, vol. 113, pp. 586-596, May 1995. [7] J. S. Schuman, T. PedutKloizman, L. Pieroth, E. Hertzmark, M. R. Hee, J. R. Wilkins, J. G. Coker, C. A. Puliafito, J. G. Fujimoto, and E. A. Swanson, "Quantitation of nerve fiber layer thickness loss over time in the glaucomatous monkey model using optical coherence tomography," Investigative Ophthalmology & Visual Science, vol. 37, pp. 5255-5255, Feb 15 1996. [8] M. R. Hee, C. A. Puliafito, J. S. Duker, E. Reichel, J. G. Coker, J. R. Wilkins, J. S. Schuman, E. A. Swanson, and J. G. Fujimoto, "Topography of diabetic macular edema with optical coherence tomography," Ophthalmology, vol. 105, pp. 360-370, Feb 1998. [9] A. F. Fercher, C. K. Hitzenberger, G. Kamp, and S. Y. Elzaiat, "Measurement of Intraocular Distances by Backscattering Spectral Interferometry," Optics Communications, vol. 117, pp. 43-48, MAY 15 1995. [10] M. Wojtkowski, R. Leitgeb, A. Kowalczyk, T. Bajraszewski, and A. F. Fercher, "In vivo human retinal imaging by Fourier domain optical coherence tomography," Journal of Biomedical Optics, vol. 7, pp. 457-463, 2002/07/ 2002. [11] R. Leitgeb, C. K. Hitzenberger, and A. F. Fercher, "Performance of Fourier domain vs. time domain optical coherence tomography," Optics Express, vol. 11, pp. 889-894, 2003/04/21 2003. [12] M. A. Choma, M. V. Sarunic, C. H. Yang, and J. A. Izatt, "Sensitivity advantage of swept source and Fourier domain optical coherence tomography," Optics Express, vol. 11, pp. 2183-2189, SEP 8 2003. [13] 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," Optics Letters, vol. 28, pp. 2067-2069, Nov 1 2003. [14] N. Nassif, B. Cense, B. H. Park, S. H. Yun, T. C. Chen, B. E. Bouma, G. J. Tearney, and J. F. de Boer, "In vivo human retinal imaging by ultrahigh-speed spectral domain optical coherence tomography," Opt Lett, vol. 29, pp. 480-2, Mar 1 2004. [15] N. A. Nassif, B. Cense, B. H. Park, M. C. Pierce, S. H. Yun, B. E. Bouma, G. J. Tearney, T. C. Chen, and J. F. de Boer, "In vivo high-resolution video-rate spectral-domain optical coherence tomography of the human retina and optic nerve," Optics Express, vol. 12, pp. 367-376, Feb 9 2004. [16] R. A. Leitgeb, W. Drexler, A. Unterhuber, B. Hermann, T. Bajraszewski, T. Le, A. Stingl, and A. F. Fercher, "Ultrahigh resolution Fourier domain optical coherence tomography," Optics Express, vol. 12, pp. 2156-2165, MAY 17 2004. [17] M. Wojtkowski, T. Bajraszewski, I. Gorczynska, P. Targowski, A. Kowalczyk, W. Wasilewski, and C. Radzewicz, "Ophthalmic imaging by spectral optical coherence tomography," Am J Ophthalmol, vol. 138, pp. 412-9, Sep 2004. [18] S. Jiao, R. Knighton, X. Huang, G. Gregori, and C. A. Puliafito, "Simultaneous acquisition of sectional and fundus ophthalmic images with spectral-domain optical coherence tomography," Optics Express, vol. 13, 2005/01/24 2005. [19] M. Wojtkowski, V. Srinivasan, J. G. Fujimoto, T. Ko, J. S. Schuman, A. Kowalczyk, and J. S. Duker, "Three-dimensional retinal imaging with high-speed ultrahigh-resolution optical coherence tomography," Ophthalmology, vol. 112, pp. 1734-46, Oct 2005. [20] U. Schmidt-Erfurth, R. A. Leitgeb, S. Michels, B. Povazay, S. Sacu, B. Hermann, C. Ahlers, H. Sattmann, C. Scholda, A. F. Fercher, and W. Drexler, "Three-dimensional ultrahigh-resolution optical coherence tomography of macular diseases," Invest Ophthalmol Vis Sci, vol. 46, pp. 3393-402, Sep 2005. [21] M. Mujat, R. Chan, B. Cense, B. Park, C. Joo, T. Akkin, T. Chen, and J. de Boer, "Retinal nerve fiber layer thickness map determined from optical coherence tomography images," Opt Express, vol. 13, pp. 9480-91, Nov 14 2005.
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[22] S. R. Chinn, E. A. Swanson, and J. G. Fujimoto, "Optical coherence tomography using a frequency-tunable optical source," Optics Letters, vol. 22, pp. 340-342, Mar 1 1997. [23] B. Golubovic, B. E. Bouma, G. J. Tearney, and J. G. Fujimoto, "Optical frequency-domain reflectometry using rapid wavelength tuning of a Cr4+:forsterite laser," Optics Letters, vol. 22, pp. 1704-1706, Nov 15 1997. [24] S. H. Yun, G. J. Tearney, B. E. Bouma, B. H. Park, and J. F. de Boer, "High-speed spectral-domain optical coherence tomography at 1.3 mu m wavelength," Optics Express, vol. 11, pp. 3598-3604, DEC 29 2003. [25] V. J. Srinivasan, M. Wojtkowski, A. J. Witkin, J. S. Duker, T. H. Ko, M. Carvalho, J. S. Schuman, A. Kowalczyk, and J. G. Fujimoto, "High-definition and 3-dimensional imaging of macular pathologies with high-speed ultrahigh-resolution optical coherence tomography," Ophthalmology, vol. 113, pp. 2054-2065, Nov 2006. [26] V. Christopoulos, L. Kagemann, G. Wollstein, H. R. Ishikawa, M. L. Gabriele, M. Wojtkowski, V. Srinivasan, J. G. Fujimoto, J. S. Duker, D. K. Dhaliwal, and J. S. Schuman, "In vivo corneal high-speed, ultra-high-resolution optical coherence tomography," Archives of Ophthalmology, vol. 125, pp. 1027-1035, Aug 2007. [27] A. J. Witkin, M. Wojtkowski, E. Reichel, V. J. Srinivasan, J. G. Fujimoto, J. S. Schuman, and J. S. Duker, "Photoreceptor disruption secondary to posterior vitreous detachment as visualized using high-speed ultrahigh-Resolution optical coherence tomography," Archives of Ophthalmology, vol. 125, pp. 1579-1580, Nov 2007. [28] M. K. Yoon, R. W. Chen, T. R. Hedges, V. J. Srinivasan, W. Gorczynska, J. G. Fujimoto, M. Wojtkowski, J. S. Schuman, and J. S. Duker, "High-speed, Ultrahigh resolution optical coherence tomography of the retina in hunter syndrome," Ophthalmic Surgery Lasers & Imaging, vol. 38, pp. 423-428, Sep-Oct 2007. [29] M. L. Gabriele, H. Ishikawa, G. Wollstein, R. A. Bilonick, K. A. Townsend, L. Kagemann, M. Wojtkowski, V. J. Srinivasan, J. G. Fujimoto, J. S. Duker, and J. S. Schuman, "Optical coherence tomography scan circle location and mean retinal nerve fiber layer measurement variability," Invest Ophthalmol Vis Sci, vol. 49, pp. 2315-21, Jun 2008. [30] T. Mumcuoglu, G. Wollstein, M. Wojtkowski, L. Kagemann, H. Ishikawa, M. L. Gabriele, V. Srinivasan, J. G. Fujimoto, J. S. Duker, and J. S. Schuman, "Improved visualization of glaucomatous retinal damage using high-speed ultrahigh-resolution optical coherence tomography," Ophthalmology, vol. 115, pp. 782-789 e2, May 2008. [31] V. J. Srinivasan, B. K. Monson, M. Wojtkowski, R. A. Bilonick, I. Gorczynska, R. Chen, J. S. Duker, J. S. Schuman, and J. G. Fujimoto, "Characterization of outer retinal morphology with high-speed, ultrahigh-resolution optical coherence tomography," Invest Ophthalmol Vis Sci, vol. 49, pp. 1571-9, Apr 2008. [32] I. Gorczynska, V. J. Srinivasan, L. N. Vuong, R. W. S. Chen, J. J. Liu, E. Reichel, M. Wojtkowski, J. S. Schuman, J. S. Duker, and J. G. Fujimoto, "Projection OCT fundus imaging for visualising outer retinal pathology in non-exudative age-related macular degeneration," British Journal of Ophthalmology, vol. 93, pp. 603-609, 2009. [33] B. Potsaid, I. Gorczynska, V. J. Srinivasan, Y. L. Chen, J. Jiang, A. Cable, and J. G. Fujimoto, "Ultrahigh speed Spectral/Fourier domain OCT ophthalmic imaging at 70,000 to 312,500 axial scans per second," Optics Express, vol. 16, pp. 15149-15169, 2008. [34] B. Povazay, K. Bizheva, B. Hermann, A. Unterhuber, H. Sattmann, A. F. Fercher, W. Drexler, C. Schubert, P. K. Ahnelt, M. Mei, R. Holzwarth, W. J. Wadsworth, J. C. Knight, and P. S. Russel, "Enhanced visualization of choroidal vessels using ultrahigh resolution ophthalmic OCT at 1050 nm," Optics Express, vol. 11, pp. 1980-1986, Aug 25 2003. [35] A. Unterhuber, B. Povazay, B. Hermann, H. Sattmann, A. Chavez-Pirson, and W. Drexler, "In vivo retinal optical coherence tomography at 1040 nm-enhanced penetration into the choroid," Optics Express, vol. 13, pp. 3252-3258, May 2 2005. [36] E. C. W. Lee, J. F. de Boer, M. Mujat, H. Lim, and S. H. Yun, "In vivo optical frequency domain imaging of human retina and choroid," Optics Express, vol. 14, pp. 4403-4411, May 15 2006.
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[37] D. M. de Bruin, D. L. Burnes, J. Loewenstein, Y. Chen, S. Chang, T. C. Chen, D. D. Esmaili, and J. F. de Boer, "In vivo three-dimensional imaging of neovascular age-related macular degeneration using optical frequency domain imaging at 1050 nm," Invest Ophthalmol Vis Sci, vol. 49, pp. 4545-52, Oct 2008. [38] P. Puvanathasan, P. Forbes, Z. Ren, D. Malchow, S. Boyd, and K. Bizheva, "High-speed, high-resolution Fourier-domain optical coherence tomography system for retinal imaging in the 1060 nm wavelength region," Optics Letters, vol. 33, pp. 2479-2481, 2008. [39] V. J. Srinivasan, D. C. Adler, Y. L. Chen, I. Gorczynska, R. Huber, J. S. Duker, J. S. Schuman, and J. G. Fujimoto, "Ultrahigh-Speed Optical Coherence Tomography for Three-Dimensional and En Face Imaging of the Retina and Optic Nerve Head," Investigative Ophthalmology & Visual Science, vol. 49, pp. 5103-5110, Nov 2008. [40] R. Huber, K. Taira, and J. G. Fujimoto, "Mode Locking Methods and Apparatus," US, 2006. [41] R. Huber, D. C. Adler, and J. G. Fujimoto, "Buffered Fourier domain mode locking: unidirectional swept laser sources for optical coherence tomography imaging at 370,000 lines/s," Optics Letters, vol. 31, pp. 2975-2977, Oct 2006. [42] R. Huber, D. C. Adler, V. J. Srinivasan, and J. G. Fujimoto, "Fourier domain mode locking at 1050 nm for ultra-high-speed optical coherence tomography of the human retina at 236,000 axial scans per second," Optics Letters, vol. 32, pp. 2049-2051, Jul 2007. [43] J. B. Jonas, C. Y. Mardin, U. Schlotzerschrehardt, and G. O. H. Naumann, "Morphometry of the Human Lamina-Cribrosa Surface," Investigative Ophthalmology & Visual Science, vol. 32, pp. 401-405, Feb 1991. [44] C. A. Curcio, K. R. Sloan, R. E. Kalina, and A. E. Hendrickson, "Human photoreceptor topography," J Comp Neurol, vol. 292, pp. 497-523, Feb 22 1990. [45] Y. L. Chen, L. N. Vuong, J. Liu, J. Ho, V. J. Srinivasan, I. Gorczynska, A. J. Witkin, J. S. Duker, J. Schuman, and J. G. Fujimoto, "Three-dimensional ultrahigh resolution optical coherence tomography imaging of age-related macular degeneration," Optics Express, vol. 17, pp. 4046-4060, 2009. [46] A. J. Witkin, L. N. Vuong, V. J. Srinivasan, I. Gorczynska, E. Reichel, C. R. Baumal, A. H. Rogers, J. S. Schuman, J. G. Fujimoto, and J. S. Duker, "High-speed ultrahigh resolution optical coherence tomography before and after ranibizumab for age-related macular degeneration," Ophthalmology, vol. 116, pp. 956-63, May 2009. [47] J. S. Kim, H. Ishikawa, K. R. Sung, J. A. Xu, G. Wollstein, R. A. Bilonick, M. L. Gabriele, L. Kagemann, J. S. Duker, J. G. Fujimoto, and J. S. Schuman, "Retinal Nerve Fiber Layer Thickness Measurement Reproducibility Improved with Spectral Domain Optical Coherence Tomography," Br J Ophthalmol, May 7 2009. [48] K. K. Bizheva, "Non-invasive Spatially Resolved Probing of Retinal Physiology with Functional Ultrahigh Resolution Optical Coherence Tomography," presented at SPIE Photonics West Conference, San Jose, CA, 2005. [49] V. J. Srinivasan, M. Wojtkowski, J. G. Fujimoto, and J. S. Duker, "In vivo measurement of retinal physiology with high-speed ultrahigh-resolution optical coherence tomography," Opt Lett, vol. 31, pp. 2308-10, Aug 1 2006. [50] V. J. Srinivasan, Y. Chen, J. S. Duker, and J. G. Fujimoto, "In Vivo Functional Imaging of Intrinsic Scattering Changes in the Human Retina with High-speed Ultrahigh Resolution OCT," Optics Express, vol. 17, pp. 3861-3877, 2009. [51] V. J. Srinivasan, T. H. Ko, M. Wojtkowski, M. Carvalho, A. Clermont, S. E. Bursell, Q. H. Song, J. Lem, J. S. Duker, J. S. Schuman, and J. G. Fujimoto, "Noninvasive volumetric Imaging and morphometry of the rodent retina with high-speed, ultrahigh-resolution optical coherence tomography," Investigative Ophthalmology & Visual Science, vol. 47, pp. 5522-5528, Dec 2006. [52] R. A. 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," Optics Express, vol. 11, pp. 3116-3121, NOV 17 2003.
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[53] B. R. White, M. C. Pierce, N. Nassif, B. Cense, B. H. Park, G. J. Tearney, B. E. Bouma, T. C. Chen, and J. F. de Boer, "In vivo dynamic human retinal blood flow imaging using ultra-high-speed spectral domain optical Doppler tomography," Optics Express, vol. 11, pp. 3490-3497, DEC 15 2003. [54] S. Makita, Y. Hong, M. Yamanari, T. Yatagai, and Y. Yasuno, "Optical coherence angiography," Optics Express, vol. 14, pp. 7821-7840, Aug 2006.
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3. High Speed Three-Dimensional OCT Endoscopic Imaging
Sponsors National Institutes of Health – R01-CA075289-13 and R01-EY11289-24 National Science Foundation – BES-0522845, ECS-0501478 Air Force Office of Scientific Research – FA9550-07-1-0101, FA9550-040-07-1-0014 Natural Sciences and Engineering Research Council of Canada – CGS D2-331643-2006 The Whitaker Foundation National Science Council of Taiwan Center for Integration of Medicine and Innovation Technology (CIMIT)
Project Staff Prof. James G. Fujimoto, Dr. Chao Zhou, Hsiang-Chieh Lee, Tsung-Han Tsai (MIT) Dr. Desmond C. Adler (MIT and LightLab Imaging) Dr. Hiroshi Mashimo (VA Medical Center) Dr. Joseph Schmitt (LightLab Imaging)
New gastrointestinal (GI) cancers will be found in more than 275,7200 patients and will cause more than 135,830 deaths in the United States in 2009 [1]. When detected and treated early, the 5-year survival rate for colorectal cancer increases by a factor of 1.4 [1]. For esophageal cancer, the rate increases by a factor of 2 [1]. Unfortunately, many early-stage lesions are missed during standard endoscopic examination. Approximately 15-27% of small (<5 mm) lesions in the colon go undetected, with rates of flat lesions missed being ~2x worse than polypoid lesions [2]. The situation is worse in the esophagus, where 30-40% of relatively large, invasive cancers are missed [3]. An early cancer detection method for imaging the GI tract may reduce morbidity and mortality associated with the disease, thereby allowing physicians to intervene earlier using minimally invasive therapies.
Gastroenterology is an especially relevant application for OCT because of the high incidence rates of GI pathologies, the clinical benefits of early detection, and the need for pre- and post-treatment assessment of therapies. OCT imaging can be performed using fiber optics and miniaturized lens systems, enabling endoscopic OCT inside the human body in conjunction with conventional video endoscopy. An OCT probe can be inserted through the working channel of a standard endoscope, thus enabling two-dimensional (2D), depth-resolved imaging of tissue microstructure ranging over a linear dimension of several millimeters to several centimeters with micron-scale resolution [4].
The majority of GI cancers begin as small (<100 μm) lesions that are difficult to identify with conventional endoscopy. OCT is well-suited for detecting the changes in tissue microstructure associated with early GI cancers. Since the lesions are not visually apparent, however, it is necessary to survey a relatively large area of the GI tract with high-resolution OCT in order to detect the lesions. Tissue motion is a limiting factor in the GI tract, therefore in vivo imaging must be performed at extremely high speeds. Recent advances in ultrahigh speed OCT using Fourier domain detection techniques [5-7] have enabled in vivo 3D-OCT with imaging speeds of up to 370,000 axial lines per second [8]. By developing miniaturized probes that scan in two spatial dimensions, endoscopic 3D-OCT can be performed. 3D-OCT overcomes the limitations of 2D analysis by enabling comprehensive visualization of tissue microstructure over larger fields of view. Volumetric data sets enable the generation of en face images, thus providing precise registration of cross-sectional data with en face features. Projection techniques can be used to selectively display specific depths within the tissue, thereby enhancing image contrast for specific architectural features. Cross-sectional images with arbitration orientation can also be generated from the 3D data.
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Our group has developed an endoscopic imaging system that uses a Fourier domain modelocked (FDML) laser, a state-of-the-art data acquisition system, and a rapid, spiral-scanning fiberoptic endoscope probe [9-12]. This “3D endomicroscopy” system is capable of acquiring 3D-OCT data at unprecedented speeds and at 3D resolutions, thus enabling the detection of small GI structures that have been linked to Barrett’s esophagus and colon cancer. Three-dimensional acquisition also enables a variety of powerful visualization techniques, such as frame averaging for speckle reduction, en face image generation for comparison to microscopy or endoscopy, and the assessment of ablation therapies in the GI tract.
Figure 3.1 shows a schematic of this system and the fiberoptic probe. The system was developed in collaboration with LightLab Imaging and uses swept source / Fourier domain OCT detection to achieve fast imaging speeds and high sensitivity. An FDML laser with a center wavelength of 1310 nm, a total tuning range of 180 nm, a full-width-half-maximum bandwidth of 122 nm, and an average output power of 42 mW at a sweep rate of 62 kHz is used as the swept light source. The laser sweep rate is lower when compared to our previous system, reported in Nature Photonics [9], in order to improve the sensitivity and imaging range for human tissue. The laser supports an axial resolution of 6.5 μm in air (~5 μm in tissue). The maximum imaging depth is 1.5 mm in tissue. System sensitivity with 13 mW of power incident on the sample is 105 dB at short delays, and it drops by 7.8 dB at a ranging depth of 2 mm in air. The exposure level is within the guidelines established in ANSI standards and is consistent with optical power levels used in commercial endoscopic and cardiovascular OCT instruments.
Volumetric data is acquired at 60,000 axial lines per second and 60 frames per second by using a rotary fiberoptic probe. The probe is a spiral-scanning device that combines rapid rotary motion (up to 80 Hz rotation) with a linear pullback (0.5-5 mm/sec) to image 3D volumes. The optical fiber is placed inside a flexible polymer tube, which is necessary for mechanical stability. The tube can be water flushed using a syringe located outside the body in order to reduce specular reflection from the tissue surface and to wash debris from the imaging site. The proximal end of the fiber is attached to a patient interface unit (PIU) containing the rotary and push/pull actuators. The distal end of the fiber is attached to an angle-polished microlens and provides a 9 μm spot diameter. The total probe diameter is 0.83 mm, which allows it to pass through the working channel of a wide variety of commercial endoscopes.
FDML Laser 1 C 2 PIU 95/5 95/5 3 Probe Sample 1 C RM 3 2 MZI amplitude 50/50
time P P P P Δν Δν +DA- +DA -
OFC OCT Personal TRG Custom 200 MHz Computer DAQ / DSP System
Figure 3.1. OCT system for ultrahigh speed endoscopic 3D-OCT imaging. The system uses swept source / Fourier domain OCT with a high speed Fourier domain modelocked (FDML) laser. Volumetric data is using a rotary fiberoptic endoscope probe. The probe can be used in the working channel of a standard endoscope.
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3.1 OCT Imaging of the Esophagus
Endoscopic OCT has been applied extensively for GI studies [13-15] with a particular emphasis on imaging in Barrett’s esophagus patients [16-21]. Barrett’s esophagus is a condition associated with gastroesophageal reflux disease (GERD) where chronic exposure of the esophagus to stomach acid causes pre-cancerous changes of the esophagus. Conventional endoscopic imaging lacks sensitivity for detecting high grade dysplasia, the immediate precursor to esophageal cancer. Therefore there is considerable interest in developing new imaging techniques which can detect these changes. Our group works in collaboration with Dr. Hiroshi Mashimo, M.D., Ph.D. and clinicians at the VA Boston Medical Center to perform clinical studies of endoscopic OCT applications.
Figure 3.2 shows in vivo OCT images obtained from a volumetric data set taken in a patient with a normal esophagus. Volumetric data sets enable the generation of en face images, thereby enabling precise registration of cross-sectional data with en face features. Projection techniques can be used to display specific depths within the tissue selectively, thus enhancing image contrast for specific architectural features. Cross-sectional images with arbitration orientation can also be generated from the 3D data. An en face view of the normal esophagus is shown in Figure 3.2a and the normal layered structure of squamous epithelium can be clearly seen in the cross-sectional images (Figures 3.2b and c). Figure 3.2e shows the corresponding histology of the normal esophagus, which correlates well with the cross-sectional OCT views (Figure 3.2d).
Figure 3.2. 3D-OCT images in a normal esophagus. (a) En face image constructed by the axial summation of a thin slice (~20 μm) in the data set. (b) XZ cross section shows typical squamous structure. (c) YZ cross section shows typical squamous structure. (d) Close-up view of YZ cross-section. (e) Representative histology of a normal esophagus. (f) White-light video endoscopy image of region analyzed with 3D-OCT.
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Figure 3.3 shows OCT images from a volumetric data set in a patient with Barrett’s esophagus. The en face view (Figure 3.3a) and cross-sectional views (Figure 3.3b and c) illustrate the characteristic glandular structures associated with Barrett’s esophagus, which can be easily distinguished from the normal esophagus shown in Figure 3.2. The zoomed-in view of glandular structures (Figure 3.3d) correlate well with the histology of Barrett’s esophagus shown in Figure 3.3e). As shown in Figures 3.2 and 3.3, 3D-OCT endomicroscopy is capable of differentiating glandular and squamous epithelium in vivo. This ability could be important for applications such as the assessment of endoscopic therapies at multiple time points, since it provides an inherent positional registration that is difficult to obtain with cross sectional OCT imaging alone.
Figure 3.3. 3D-OCT images in Barrett’s esophagus. (a) En face image constructed by axial summation of a thin slice (~20 μm) in the data. (b) XZ cross section shows the characteristic glandular structures associated with Barrett’s esophagus. (c) YZ cross section shows the glandular structures. (d) Close-up view of YZ cross-section. (e) Representative histology of Barrett’s esophagus. (f) White-light video endoscopy image of region analyzed with 3D-OCT.
3.2 OCT Imaging of the Lower GI Tract
Our group and collaborators are also performing clinical studies using endoscopic 3D-OCT in the lower gastrointestinal tract. The 3D-OCT endomicroscopy system used is the same as used in the upper GI studies [9]. A range of tissue types are analyzed, including normal colon and ulcerative colitis [11]. Figure 3.4 shows 3D-OCT endomicroscopy images of glandular and squamous mucosa in the normal rectum and anal verge. This data was taken near the dentate line, the junction between the columnar epithelial mucosa of the proximal colon and squamous epithelial mucosa of the rectum. Squamous mucosa is smooth, crypt-free tissue that lines the anal verge. Figure 3.4a is an en face image formed by axial summation of the entire data set. Squamous epithelial tissue can be readily identified on the right-hand side of the image. Glandular epithelium
17-34 RLE Progress Report 151 Chapter 17. Biomedical Optical Imaging is visible on the left-hand side of the image. The squamo-columnar junction, or dentate line, is where the tissue transitions from anal squamous epithelium to rectal glandular (columnar) epithelium. Figure 3.4b shows an XZ cross section through the squamous region, thus illustrating regular, layered architecture with subepithelial anal vessels. Figure 3.4c shows a YZ cross section. Crypt-filled glandular tissue and layered squamous tissue are clearly distinguishable, in addition to a transition zone between the two regions. The region near the dentate line is shown under white-light video endoscopy in Figure 3.4d. Histology images of normal glandular mucosa and normal squamous mucosa are shown in Figure 3.4e and Figure 3.4f, respectively.
Figure 3.4. 3D-OCT images near the dentate line. (a) En face image constructed by axial summation of entire dataset. Dashed lines show locations of cross sections. (b) XZ cross section shows typical squamous structure. (c) YZ cross section shows shift from columnar C to squamous S epithelium over a transition zone T. (d) White-light video endoscopy image of region analyzed with 3D-OCT. (e) Representative cross-sectional histology of columnar epithelium. (f) Representative cross-sectional histology of squamous epithelium. Arrows in b and f indicate normal anal vessels.
Ulcerative colitis (UC) is a chronic inflammatory condition of the GI tract that produces abscesses, ulcerations, and bleeding. UC affects up to 780,000 individuals in the United States and Canada and is newly diagnosed in 7,000-46,000 individuals per year [1]. 3D-OCT endomicroscopy images acquired in the rectum near the anal verge are shown in Figure 3.5. The volume is 8x20x1.6 mm3 in dimension and was acquired in 20 seconds. Figure 3.5(a) shows an en face image formed by axial summation of a 20 μm-thick section centered 350 μm beneath the luminal surface. When compared to normal squamous and columnar mucosa shown in Figure 3.4, UC tissue appears highly irregular. Large subsurface voids and bands of hyperscattering tissue, possibly fibrotic, are apparent. A wedge of comparatively normal tissue is visible at the right of the image. Figure 3.5b shows an XZ cross section through the region that reveals a regular, layered architecture consistent with anal squamous mucosa. The epithelium is thicker when compared to healthy
17-35 Chapter 17. Biomedical Optical Imaging individuals, possibly as a result of healing in response to prior treatment with anti-inflammatory medications. The ulcerated region exhibits a loss of layered or columnar architecture, superficial edema, and a large subsurface abnormality consistent with submucosal fibrosis. Figure 3.5c shows a YZ cross section with UC and normal squamous tissue visible on the left and right sides of the image, respectively. Figure 3.5d shows enlarged regions of Figure 3.5c. Representative histology of UC in glandular mucosa is shown in Figure 3.5e. Lymphocytic mucosal infiltration is present along with submucosal fibrosis. Ulceration results in the formation of a pseudo-polyp as the epithelium is stripped away to expose the submucosa. Figure 3.5f shows a white-light video endoscopy image of a patient with active UC. The mucosa appears red, inflamed, and ulcerative. The 3D-OCT catheter is also shown in position prior to imaging.
Figure 3.5. 3D-OCT images of ulcerative colitis. (a) En face image constructed by summing a 20 μm axial section. Large, subsurface voids and ulcerations are present, while the regular crypt pattern is absent. Dashed lines show locations of cross-sectional images. (b) XZ cross section contains normal squamous epithelium S and ulcerative colitis U. (c) YZ cross section shows similar structure. (d) Close-up view of left portion of (c) shows disorganized structure and superficial voids. (e) Representative cross-sectional histology of UC shows an ulcerative pseudo-polyp. (f) White-light video endoscopy image of UC shows the 3D-OCT probe. The tissue surface is inflamed with ulcerations.
3D-OCT endomicroscopy enables visualization of microstructural differences between the UC and normal regions. Furthermore, the extended field of view allows the evaluation of macro-scale features, such as subsurface voids, as well as microstructural details such as superficial edema and the layered architecture of the normal region.
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3.3 Assessment of Therapies in the GI Tract
Ablative therapies including photodynamic therapy, argon plasma coagulation, and radiofrequency ablation (RFA) are increasingly performed for diseases in the gastrointestinal tract such as Barrett’s esophagus (BE) [9, 10, 22-25] and chronic radiation protitis (CRP) [26]. RFA with the BarRx Halo90 system is able to achieve superficial and broad fields of ablation, which suggests effective treatment can be performed in the GI tract [23, 25]. Endoscopic 3D-OCT is uniquely suited for the follow-up assessment of RFA treatment. Our group and collaborators investigated the use of 3D-OCT to assess treatment response by evaluating the presence of neosquamous epithelium and subsurface structures over the RFA treated field in the GI tract [9, 10, 24].
Thirteen patients with Barrett’s esophagus and six patients with bleeding from chronic radiation protitis were treated with RFA using the BarRx Halo90 system. Imaging was conducted before the treatment and up to 19 months after the treatment. 3D-OCT imaging was conducted with a spiral-scanning catheter. Eight-millimeter circumferential scans were acquired over an 18 mm pullback length in 20 seconds with a 1.7 mm depth penetration.
Figure 3.6. 3D-OCT orthoplanes of distal esophagus previously treated with RFA. (a) En face orthoplane of the epithelium at 390 μm tissue depth shows scattered, buried glands (arrows) beneath neo-squamous epithelium. (b) The cross-sectional XZ plane shows scattered glands buried 350-400 μm beneath the tissue surface. (c) The cross-sectional YZ plane shows gastric and neo-squamous regions. (d) Enlarged view of neosquamous regions in (c). (e) Representative cross-sectional histology of distal esophagus. (f) White-light video endoscopy image of region analyzed with 3D-OCT.
Figure 3.6 shows 3D-OCT images taken from a volumetric data set spanning the gastroesophageal junction (GEJ) from a patient who had received three RFA treatments. An En face iamge at a depth of 390 μm (Figure 3.6a) shows a clear delineation between gastric mucosa
17-37 Chapter 17. Biomedical Optical Imaging on the left (distal) and esophageal mucosa on the right (proximal), and was remarkable for scattered glandular structures of a size and shape consistent with Barrett’s esophagus glands. Cross-sectional XY and YZ image (Figures 3.6b and c) show deeply buried glands beneath ~350 μm (range 300-500 μm) of comparatively normal epithelium and lamina propria. Normal epithelium on top of glands suggests this is neosquamous epithelium that regenerated after RFA. Biopsy specimens (Figure 3.6e) from this area contain gastric mucosa and GEJ tissue with no evidence of buried Barrett’s esophagus glands. This is not surprising given the scattered and sparse nature of the glands visible with 3D-OCT. Since biopsy is a sampling procedure, it can miss focal areas of pathology. Conventional endoscopy of the distal esophagus (figure 3.6f) also showed a normal GEJ with no evidence of residual or buried Barrett’s esophagus.
Figure 3.7 shows 3D-OCT endomicroscopy images of a chronic radiation protitis patient 14 months after radiofrequency ablation therapy, acquired in the region of prior treatment. The volume is 7x11x1.6 mm3 in dimension and was acquired in 20 seconds. Figure 3.7a shows an axial summation of a 20 μm thick section centered at a depth of 350 μm beneath the luminal surface. The 20 μm summation reveals a series of smaller sub-surface cyst-like structures. En face scanning through the tissue volume reveals that the structures are interconnected, suggesting that they may be blood vessels or lymphatics.
Figure 3.7. 3D-OCT images of radiation proctitis 14 months after treatment. (a) 20 μm en face summation. Columnar epithelium proximal of the dentate line appears normal. Squamous epithelium is mostly normal, with probably former ectatic vessels shown by arrows. Dashed lines show locations of cross-sectional images. (b) XZ cross section shows regular squamous and columnar epithelium. (c) YZ cross sections show similar features. (d) Close-up view of (c) shows a former ecstatic blood vessel covered in neo-squamous tissue. (e) White-light video endoscopy image of region analyzed with 3D-OCT.
Figure 3.7b and c shows an XZ and YZ cross sections respectively with some small vascular features visible, also illustrating the transition from normal columnar to normal squamous mucosa. A number of large hypointense, weakly-scattering features buried beneath the epithelium are visible in the en face and cross-sectional images. The structures likely represent former large
17-38 RLE Progress Report 151 Chapter 17. Biomedical Optical Imaging ecstatic blood vessels that are covered in neo-squamous tissue following radiofrequency ablation. 3D-OCT can be used to evaluate the effectiveness of endoscopic therapies, to assess healing and check for disease recurrence. The ability of 3D-OCT to precisely co-register cross-sectional images to anatomic landmarks or other en face features could be valuable when imaging the same patient at multiple time points, since it enables the same tissue region to be imaged repeatedly to tracks changes.
References
[1] "Cancer Facts and Figures," American Cancer Society 2009 2009. [2] D. K. Rex, "Maximizing detection of adenomas and cancers during colonoscopy," American Journal of Gastroenterology, vol. 101, pp. 2866-2877, Dec 2006. [3] S. J. Spechler, "Dysplasia in Barrett's esophagus: limitations of current management strategies," Am J Gastroenterol, vol. 100, pp. 927-35, Apr 2005. [4] G. J. Tearney, M. E. Brezinski, J. F. Southern, B. E. Bouma, S. A. Boppart, and J. G. Fujimoto, "Optical biopsy in human gastrointestinal tissue using optical coherence tomography," The American journal of gastroenterology, vol. 92, pp. 1800-4, Oct 1997. [5] M. A. Choma, M. V. Sarunic, C. H. Yang, and J. A. Izatt, "Sensitivity advantage of swept source and Fourier domain optical coherence tomography," Optics Express, vol. 11, pp. 2183-2189, SEP 8 2003. [6] 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," Optics Letters, vol. 28, pp. 2067-2069, Nov 1 2003. [7] R. Leitgeb, C. K. Hitzenberger, and A. F. Fercher, "Performance of Fourier domain vs. time domain optical coherence tomography," Optics Express, vol. 11, pp. 889-894, 2003/04/21 2003. [8] R. Huber, D. C. Adler, and J. G. Fujimoto, "Buffered Fourier domain mode locking: unidirectional swept laser sources for optical coherence tomography imaging at 370,000 lines/s," Optics Letters, vol. 31, pp. 2975-2977, Oct 2006. [9] D. C. Adler, Y. Chen, R. Huber, J. Schmitt, J. Connolly, and J. G. Fujimoto, "Three-dimensional endomicroscopy using optical coherence tomography," Nature Photonics, vol. 1, pp. 709-716, Dec 2007. [10] D. C. Adler, C. Zhou, T. H. Tsai, H. C. Lee, L. Becker, J. M. Schmitt, Q. Huang, J. G. Fujimoto, and H. Mashimo, "Three-dimensional optical coherence tomography of Barrett's esophagus and buried glands beneath neosquamous epithelium following radiofrequency ablation," Endoscopy, vol. 41, pp. 773-776, 2009. [11] D. C. Adler, C. Zhou, T. H. Tsai, J. Schmitt, Q. Huang, H. Mashimo, and J. G. Fujimoto, "Three-dimensional endomicroscopy of the human colon using optical coherence tomography," Optics Express, vol. 17, pp. 784-796, 2009. [12] S. Zhou, Y. Li, A. T. H. Lu, P. F. Liu, M. L. Tang, S. C. Yiu, and D. Huang, "Reproducibility of Tear Meniscus Measurement by Fourier-Domain Optical Coherence Tomography: A Pilot Study," Ophthalmic Surgery Lasers & Imaging, vol. 40, pp. 442-447, 2009. [13] B. E. Bouma, G. J. Tearney, C. C. Compton, and N. S. Nishioka, "High-resolution imaging of the human esophagus and stomach in vivo using optical coherence tomography," Gastrointestinal endoscopy, vol. 51(4) Pt 1, pp. 467-74, Apr 2000. [14] S. Jäckle, N. Gladkova, F. Feldchtein, A. Terentieva, B. Brand, G. Gelikonov, V. Gelikonov, A. Sergeev, A. Fritscher-Ravens, J. Freund, U. Seitz, S. Schröder, and N. Soehendra, "In vivo endoscopic optical coherence tomography of esophagitis, Barrett's esophagus, and adenocarcinoma of the esophagus," Endoscopy, vol. 32, pp. 750-5, Oct 2000. [15] M. V. Sivak, Jr., K. Kobayashi, J. A. Izatt, A. M. Rollins, R. Ung-Runyawee, A. Chak, R. C. Wong, G. A. Isenberg, and J. Willis, "High-resolution endoscopic imaging of the GI tract using optical coherence tomography," Gastrointestinal endoscopy, vol. 51(4) Pt 1, pp. 474-9, Apr 2000.
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[16] X. D. Li, S. A. Boppart, J. Van Dam, H. Mashimo, M. Mutinga, W. Drexler, M. Klein, C. Pitris, M. L. Krinsky, M. E. Brezinski, and J. G. Fujimoto, "Optical coherence tomography: advanced technology for the endoscopic imaging of Barrett's esophagus," Endoscopy, vol. 32, pp. 921-30, Dec 2000. [17] J. M. Poneros, S. Brand, B. E. Bouma, G. J. Tearney, C. C. Compton, and N. S. Nishioka, "Diagnosis of specialized intestinal metaplasia by optical coherence tomography," Gastroenterology, vol. 120, pp. 7-12, Jan 2001. [18] G. Isenberg, M. V. Sivak, A. Chak, R. C. K. Wong, J. E. Willis, B. Wolf, D. Y. Rowland, A. Das, and A. Rollins, "Accuracy of endoscopic optical coherence tomography in the detection of dysplasia in Barrett's esophagus: a prospective, double-blinded study," Gastrointestinal Endoscopy, vol. 62, pp. 825-831, Dec 2005. [19] J. A. Evans, J. M. Poneros, B. E. Bouma, J. Bressner, E. F. Halpern, M. Shishkov, G. Y. Lauwers, M. Mino-Kenudson, N. S. Nishioka, and G. J. Tearney, "Optical coherence tomography to identify intramucosal carcinoma and high-grade dysplasia in Barrett's esophagus," Clinical Gastroenterology and Hepatology, vol. 4, pp. 38-43, Jan 2006. [20] X. Qi, M. V. Sivak, G. Isenberg, J. E. Willis, and A. M. Rollins, "Computer-aided diagnosis of dysplasia in Barrett's esophagus using endoscopic optical coherence tomography," Journal of Biomedical Optics, vol. 11, p. 10, Jul-Aug 2006. [21] Y. Chen, A. D. Aguirre, P. L. Hsiung, S. Desai, P. R. Herz, M. Pedrosa, Q. Huang, M. Figueiredo, S. W. Huang, A. Koski, J. M. Schmitt, J. G. Fujimoto, and H. Mashimo, "Ultrahigh resolution optical coherence tomography of Barrett's esophagus: preliminary descriptive clinical study correlating images with histology," Endoscopy, vol. 39, pp. 599-605, Jul 2007. [22] R. D. Odze and G. Y. Lauwers, "Histopathology of Barrett? esophagus after ablation and endoscopic mucosal resection therapy," Endoscopy, vol. 40, pp. 1008-1015, 2008. [23] V. K. Sharma, H. J. Kim, A. Das, P. Dean, G. DePetris, and D. E. Fleischer, "A prospective pilot trial of ablation of Barrett? esophagus with low-grade dysplasia using stepwise circumferential and focal ablation (HALO system)," Endoscopy, vol. 40, pp. 380-387, 2008. [24] D. Huang, E. A. Swanson, C. P. Lin, J. S. Schuman, W. G. Stinson, W. Chang, M. R. Hee, T. Flotte, K. Gregory, C. A. Puliafito, and J. G. Fujimoto, "Optical Coherence Tomography," Science, vol. 254, pp. 1178-1181, Nov 22 1991. [25] C. Zhou, D. C. Adler, L. Becker, Y. Chen, T.-H. Tsai, M. Figueiredo, J. M. Schmitt, J. G. Fujimoto, and H. Mashimo, "Effective treatment of chronic radiation proctitis using radiofrequency ablation " Therapeutic Advances in Gastroenterology, vol. 2, pp. 149-156, 2009. [26] S. Sebastian, O. C. Humphrey, O. M. Colm, and B. Martin, "Argon plasma coagulation as first-line treatment for chronic radiation proctopathy," Journal of Gastroenterology and Hepatology, vol. 19, pp. 1169-1173, 2004.
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4. Optical Coherence Microscopy for Imaging Pathology
Sponsors National Institutes of Health – R01-CA75289-13, R01-NS057476-02, R01HL095717-01 National Science Foundation – BES-0522845 Air Force Office of Scientific Research - FA9550-07-1-0101, FA9550-07-1-0014
Project Staff Professor James G. Fujimoto, Dr. Chao Zhou, Dr. Aaron D. Aguirre, M.D., Ph.D., Hsiang-Chieh Lee, Tsung-Han Tsai (MIT) Dr. James L. Connolly, M.D., Dr. Yihong Wang, M.D.,Dr. David W. Cohen, M.D., Dr. Amy Mondelblatt, M.D. (BIDMC)
4.1 Optical Coherence Microscopy (OCM) for Cellular Imaging
Achieving cellular level image resolution would enable a wide range of fundamental and clinical applications. Ultrahigh resolution OCT using broadband light sources can achieve 1-2 µm axial resolution in tissue [1]. However, transverse resolutions are still limited due to the low numerical aperture (NA) focusing required to maintain a sufficient depth of field to generate the cross-sectional images. The relatively low transverse resolution achievable with cross-sectional OCT is generally insufficient for resolving cellular features. In order to extend OCT to high transverse resolution, our group is developing optical coherence microscopy (OCM), which combines the coherent detection methods of OCT with confocal microscopy. Figure 4.1 compares the image penetration depth and resolution of OCM with that of OCT, confocal microscopy and ultrasound. OCM provides enhanced penetration depth compared to standard confocal microscopy, while dramatically improving the resolution over cross-sectional OCT imaging.
OCM overcomes the depth of field limitation in traditional OCT by imaging in the en face plane rather than the cross-sectional plane. To image en face, the optical path length of the reference arm is matched exactly to the focus of the sample arm microscope while scanning a transverse raster pattern on the tissue. This eliminates the need for path length scanning to generate an axial depth scan and allows the use of high NA lenses that provide very small focal spot sizes. Because of the high NA focusing used in OCM, the field of view in the images is necessarily smaller than in OCT. OCT images tissue architectural features over a field of view of 3-6 mm square, while OCM can image down to the cellular level, but with a reduced 100-500 µm square field of view.
OCM has the unique advantage of using two distinct optical sectioning techniques: confocal gating and coherence gating. While the confocal point spread function is determined by the numerical aperture of the final objective lens, the coherence gate is determined by the bandwidth of the light source. The degree of confocal rejection of unfocused scattered light can be varied by changing the NA of the objective lens, and the amount of coherence-gated sectioning can be varied by changing the bandwidth of the light source. The multiplicative effect of the two sectioning methods strengthens the overall optical sectioning power, thus allowing increased rejection of unwanted, out-of-focus scattered light. Our group and others have demonstrated that combined confocal and coherence gating can provide improved imaging depth when compared to confocal gating alone [2-4]. The addition of high-sensitivity coherence-gated detection which can operate at the shot noise limit, to confocal detection extends the imaging depth in scattering media by a factor of 2-3 over standard confocal microscopy. OCM techniques also allow considerable flexibility in system design for acquiring high-resolution cellular images. Broad-bandwidth light sources, such as those used in ultrahigh-resolution OCT, can provide thin optical sectioning by coherence gating, without the need for high NA focusing for confocal sectioning.
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The advantages of OCM can be understood from Figure 4.2 which compares the confocal axial and transverse imaging resolution as a function of the numerical aperture (NA) of the optics. The
Figure 4.1. Transverse resolution and image penetration in optical coherence microscopy (OCM). OCM can dramatically enhance image penetration when compared to confocal microscopy alone, while significantly improving transverse resolution in OCT to enable cellular-level imaging.
Figure 4.2. Numerical aperture requirement for OCM compared to confocal microscopy. OCM can image with a high transverse resolution at a much lower numerical aperture than confocal microscopy because it does not depend on high axial resolution for optical sectioning.
17-42 RLE Progress Report 151 Chapter 17. Biomedical Optical Imaging ability of confocal microscopy to perform axial sectioning degrades more rapidly as a function of NA than the transverse resolution. Therefore confocal microscopy requires high NA focusing to achieve optical sectioning. There are a range of lower NAs where the transverse resolution is sufficient for cellular imaging, but the axial resolution is insufficient to reject unwanted scattered light. The addition of a short coherence gate to provide tissue sectioning can, therefore, make cellular imaging possible with much lower NA than what is sufficient for confocal microscopy alone. This operating regime for OCM imaging has important clinical implications, since it promises cellular imaging with small diameter probes that are compatible with standard endoscopic and laparoscopic procedures.
Ex vivo imaging in the pathology lab is a powerful methodology to validate new imaging modalities. Pathology lab imaging studies enable the acquisition of comprehensive 3D-OCT and OCM data sets, as well as a more controlled comparison between optical imaging and histology. It also provides access to large numbers of specimens which would not be available outside the clinic. Integrated 3D-OCT and OCM also enables investigation of tissue structure at the architectural and cellular scale. The 3D-OCT data sets enable en face projection imaging, which provides a large field of view with uniform focus and signal level, while OCM provides high magnification that enables cellular-resolution imaging. Our group has an ongoing collaboration with Dr. James Connolly, MD at the Beth Israel Deaconess Medical Center and Harvard Medical School to investigate OCT and OCM for pathology. We are investigating a selection of pathologies from colon, esophagus/stomach, thyroid, breast, lymph nodes, female reproductive tract, prostate, kidney and others. These tissues represent a broad range of diseases where integrated 3D-OCT and OCM can serve as a useful imaging tool.
Recently, our group developed an improve OCM system for path lab imaging. Previous OCM systems were difficult to use outside the laboratory due to their complexity. Using theoretical modeling and experimental studies, our group developed compact laser sources for ultrahigh-resolution OCT and OCM by using commercially available femtosecond lasers and continuum generation in highly nonlinear optical fibers [5, 6]. These light sources provide axial resolutions of <5 µm and are suitable for use in the clinic. For OCM imaging, a novel fiber-based system using a broadband electro-optic phase modulator and novel dispersion control techniques was developed [7] (Figure 4.3). A computer interface controls the system, including a fiber optic scanning confocal microscope. The design also incorporates an active reference arm path length control, which is used for rapid, automated coordination of the optical coherence gate with the focal plane. This feature compensates for optical path length fluctuations from tissue heterogeneity. The control algorithm is analogous to auto-focusing strategies used in modern digital cameras, and ensures optimal image quality during real-time imaging. The confocal microscope in the sample arm uses high-speed, linear-scanning galvanometers to produce raster-scan line rates of up to 2.5 kHz. Transverse image resolution is measured at <2 um, and 400-500 µm fields of view are achieved. The electronic output is sampled at 5 MHz and digital demodulation, image processing, and display is performed. Detection sensitivity is -98 dB.
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Figure 4.3. Schematic of high-speed OCM system. OCM enables real-time cellular imaging and is complementary to OCT. A broadband femtosecond Nd:Glass laser light source enables high-resolution axial sectioning. Imaging is performed with a microscope interface having <2 μm transverse resolution.
4.1 Integrated OCT and OCM Imaging of Human Thyroid Pathology
Thyroid cancer is the most common malignancy of the endocrine system [8]. There are approximately 37,200 new cases and 1,630 thyroid cancer deaths expected in the United States in 2009 [9]. Various methods are used for the detection of and screening of malignant thyroid nodules. These include clinical examination, different imaging methods, and ultrasound-guided fine-needle aspiration (FNA). Thyroid cancer commonly presents as a cold (inactive) nodule on radio-isotope scanning. Up to 40% of adults have a thyroid nodule detected by either palpation or ultrasound [10-13]. Imaging techniques that can aid in differentiating between benign and malignant thyroid nodules, which may require surgery, are of great interest.
Our group and collaborators are investigating integrated OCT and OCM imaging to assess benign and malignant thyroid tissue [14]. Imaging is performed ex vivo based on intrinsic optical contrast in freshly excised human thyroid specimens. Images of normal and pathologic tissue were compared with histological sections in order to identify which histomorphologic features could be visualized by using integrated OCT and OCM imaging. The results provide a basis for interpretation of future OCT and OCM images of the thyroid tissues, and suggest the possibility for future in vivo evaluation of thyroid pathology.
OCT enables the acquisition of volumetric data sets which have comprehensive structural information. A raster scan is performed to acquire 640 2D-OCT cross-sectional images. The tissue surface is detected in post-processing in order to allow en face image planes to be viewed at constant depth (Figure 4.4). En face slices of OCT images (3 x 1.5 mm2) are generated from the 3D data sets by averaging over 10 um depth ranges in the axial direction in order to reduce speckle noise. The en face OCT images (Figure 4.4 right) have the advantage that the entire image plane is in focus and there is no exponential attenuation across the image (in depth) as there is in cross-sectional images (Figure 4.4 left).
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Figure 4.4. En face OCT image (right) is constructed from the 3D volumetric data set (left), which consists of 640 2D cross-sectional OCT images. The en face OCT images are from a single focal plane and therefore are in focus and have uniform signal intensity across the image.
Figure 4.5 shows images of a normal thyroid. Round or oval thyroid follicles, ranging from 50 to 500 µm in diameter, are observed. The follicles appear well organized in the en face OCT image (Figure 4.5A). A follicle lined by a single layer of epithelium is clearly seen in the OCM image (Figure 4.5B). The corresponding histology (Figures 4.5C and 4.5D) matches well with the OCT and OCM images. Figure 4.6 show examples OCT and OCM images of papillary thyroid carcinoma. Papillary carcinoma of the thyroid is the most common type of thyroid cancer (65 to 80% in US) [15]. Calcifications and dense fibrosis separating the papillary fronds are clearly identified in the en face OCT image (Figure 4.6A). The OCM image (Figure 4.6B) also shows Psammoma bodies, which are a pattern of calcification commonly associated with papillary carcinoma. These results show that OCT and OCM enable visualization of diagnostically significant features for classic-type papillary carcinoma.
Figure 4.5. Normal thyroid demonstrates well-organized round-to-oval thyroid follicles (F). Colloid with various densities is observed under en face OCT (A) and OCM (B) obtained ~ 100 µm and 50 µm below the tissue surface, respectively, at different signal strengths. The follicles are lined by a single layer of epithelium (arrows), which are clearly seen in the OCM image (B). (C) and (D) Corresponding H&E slides (4x and 20x, respectively). Scale bars, 500 µm in (A, C) and 100 µm in (B, D).
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Figure 4.6. An example of classic-type papillary carcinoma demonstrating features such as calcifications (C), clusters of papillae (P) and dense fibrosis (FI) in the en face OCT (A) and OCM (B,C) images obtained ~50 µm below the tissue surface. Psammoma bodies (arrows) are clearly identified by OCM (B). (D-F), corresponding H&E slides (4x and 20x, respectively). Scale bars, 500 µm in (A, D) and 100 µm in (B,C,E and F).
Figure 4.7 shows an example of the follicular variant of papillary carcinoma. In this case, the en face OCT image is performed at the interface between the tumor and normal tissue (Figure 4.7A). The tumor on the left is clearly distinguished as densely packed micro follicles separated from the adjacent normal thyroid tissue at the lower right corner by a dense fibrous capsule. OCM reveals details of micro follicles (Figure 4.7B) and normal follicles (Figure 4.7C) from the same specimen, which is consistent with the histology. Although the resolution of OCM is not at the level for cytologic diagnosis of this disease, OCT and OCM can clearly resolve the microfollicular pattern. This provides valuable information that suggests the follicular variant of papillary carcinoma. OCT and OCM provide higher resolutions than in any in vivo imaging modality currently used in clinical practice.
Figure 4.7. En face OCT (A) shows the tumor interface with normal thyroid tissue in papillary carcinoma, follicular variant. The tumor on the left side is clearly distinguished as densely packed micro follicles (MF) separated from the adjacent normal thyroid follicles (F) at the lower right corner by a dense fibrous (FI) capsule. Details of microfollicles and normal follicles are shown in the OCM images (B, C). The en face OCT and OCM images are obtained at depths of ~60 µm and 50 µm below the tissue surface, respectively. (D-F) Corresponding H&E slides (4x and 20x, respectively). Scale bars, 500 µm in (A,D) and 100 µm in (B,C,E, and F).
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4.2 OCT and OCM Imaging of Breast Pathology
Excluding skin cancers, breast cancer is the most diagnosed cancer in women in the United States. There are an estimated 182,460 new cases of invasive breast cancer and 67,770 new cases of in situ cancer in women in the United States in 2009 [9]. Breast cancer also ranks as the second leading cause of death in women, with 40,480 deaths estimated in 2009. In this study, our group and collaborators investigated OCT/OCM imaging of human breast tissue and lymph nodes in order to assess the ability to identify cancer pathologies. The ability to visualize tumor margins would have applications to breast cancer surgery, while the ability to assess metastasis in lymph nodes could reduce sampling errors associated with sentinel node biopsy.
These studies employed the integrated OCT and OCM system on freshly excised human breast tissue. Figure 4.8 illustrates characteristic patterns in normal human breast tissue. An en face projection is constructed from the 3D-OCT data set (A), therefore demonstrating uniform focus and signal level across a large field of view (~1.5x3 mm2). Fibrotic tissues, blood vessels and breast glands are clearly identified. Detailed structure of breast glands can be visualized using the higher magnification OCM imaging (B) and correlated well with histology (C,D).
Figure 4.8. (A) En face OCT image of normal breast tissue shows fibroti tissues “FI”, blood vessels “V”, and glands “G”. (B) OCM reveals details of breast glands. (C,D) Corresponding histology. Scale bars are 500 µm in (A,C) and 100 µm in (B,D).
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Figures 4.9. Lobular carcinoma of the breast. (A) En face OCT image generated from the 3D-OCT data. Linear infiltrative pattern consisting of a single row of cells is clearly visible (arrows). (B) OCM image of the linear infiltrative pattern in more detail. The corresponding histology is shown in (C) and (D).
Figure 4.9 illustrates the characteristic pattern of lobular carcinoma of the breast. En face images generated from 3D-OCT data are shown in Figure 4.9A. A linear infiltrative pattern consisting single row of cells is clearly identified from the image (arrows), thereby indicating a classic-type lobular carcinoma of the breast. The linear infiltrative pattern can be observed in more detail through magnification of the OCM imaging (Figure 4.9B). Images agree well with corresponding histology using H&E staining (Figure 4.9C and D).
Another potential application of OCT is to detect lymph node micro-metastasis, which is important for the staging of cancers. Our group and collaborators investigated imaging in freshly excised lymph nodes by using OCT through the intact capsule. A commercial swept-source OCT system (Thorlabs, Inc.) used for this study and provides 16 kHz axial line rate with an axial resolution of ~13 µm. OCT data was acquired over a 3x3 mm2 area of the lymph nodes to enable visualization of cross-sectional and en face images.
Figure 4.10 is an example of a normal lymph node. Structural information up to 1 mm deep in the highly scattering lymph node can be seen with OCT. The capsule and sub-capsule sinus, where micro-metastasis initially occurs are clearly visible (Figure 4.10A). The en face projection of the OCT data (Figure 4.10B) provides a view at constant depth showing germinal centers, in addition to the capsule and sinus at the edges of the node. Images at different depths can be generated from the volumetric data set. These preliminary data suggest that OCT can be used to visualize lymph nodes structures through the capsule, and it may have the potential to detect micro-metastasis in lymph nodes in vivo.
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Figure 4.10. (A) Cross-sectional OCT image of a normal lymph node. Capsule (C) and sub-capsule sinus (S) is clearly seen from the OCT image. (B) En face OCT image constructed from the 3D volumetric data set clearly shows the capsule, sub-capsule sinus, and germinal centers (GC) of the lymph node. Scale bar, 1 mm.
4.3 Integrated OCT and OCM Imaging of Human Kidney Pathology
The most common type of kidney cancer is (RCC), which accounts for approximately 85% of renal parenchyma malignancies. In the United States, more than 50,000 new cases of kidney cancer were diagnosed with 13,000 deaths each year [9]. Among new kidney cancer cases, 30,000 were diagnosed as renal cell carcinoma [16, 17]. Kidney cancer usually starts as a small mass without any pain, and becomes larger over time. Kidney cancer diagnosis includes various imaging methods such as CT scan, MRI, ultrasound, and PET to find and locate the position of the lesion.
Our group and collaborators explored the feasibility of OCT and OCM imaging of kidney cancer. The integrated OCT and OCM system was used to image freshly excised normal and malignant human kidney tissue. OCT/OCM image features were correlated with different pathologies to assess the feasibility of using OCT or OCM to guide fine needle aspiration (FNA) and reduce biopsy sampling errors.
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Figure 4.11. (A) En face OCT image of normal kidney, demonstrating the organized tissue structure composed of glomerulus (G) and a lot of tubules (T) surrounding each glomerulus. (B) OCM image reveals more detailed features of the glomerulus and also the surrounded tubules. (C,D) Corresponding histological images. Scale bars are 500 µm in (A,C) and 100 µm in (B,D).
Representative images of a normal kidney are shown in Figure 4.11. En face OCT images summing of 10 µm in depth were constructed from 640 2D-OCT images and demonstrated the larger field of view of OCT system (~1.5x3 mm2). Round spherical glomerulus structures (G), which consists of a convoluted network capillaries were observed in Figure 4.11A. Figure 4.11B shows OCM images in the same imaging regions as Figure 4.11A, and shows a clearer feature of glomerulus structure and the surrounding tubules (T). The average diameter of the glomerulus is approximately 150 to 200 µm. OCT and OCM images correspond well with histology (Figure 4.11C and D)). In the future OCT and OCM can be integrated with needle based imaging probes and coupled to fine needle aspiration to provide image guided biopsy.
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Figure 4.12. (A) En face OCT image of a normal human kidney over the regions between the cortex (Cx) and medulla (Md). (B) OCM image reveals the finer features of the tubules in the cortex regions. (C,D) Corresponding histologic images. Scale bars, 500 µm in (A,C) and 100 µm in (B,D).
Figure 4.12 shows OCT/OCM images at the boundary between the cortex and medulla of a normal human kidney. Figure 4.12A shows an en face OCT image generated from the 3D-OCT data set and it highlights the difference in tissue composition between cortex (Cx) and medulla (Md). Figure 4.12B shows the OCM image over the cortex regions and demonstrates tubule structures (T). These results are consistent with corresponding histology H&E slides (Figure 4.12C and D). The integrated OCT/OCM system can be used to study changes in size and shape of the glomerulus, which has been shown to be an indicator of glomerulus disease [18].
References
[1] W. Drexler, U. Morgner, F. X. Kartner, C. Pitris, S. A. Boppart, X. D. Li, E. P. Ippen, and J. G. Fujimoto, "In vivo ultrahigh-resolution optical coherence tomography," Optics Letters, vol. 24, pp. 1221-1223, 1 Sept. 1999 1999. [2] J. A. Izatt, M. R. Hee, G. M. Owen, E. A. Swanson, and J. G. Fujimoto, "Optical coherence microscopy in scattering media," Optics Letters, vol. 19, pp. 590-2, 1994/04/15 1994. [3] J. A. Izatt, M. D. Kulkarni, H.-W. Wang, K. Kobayashi, and M. V. Sivak, Jr., "Optical coherence tomography and microscopy in gastrointestinal tissues," IEEE Journal of Selected Topics in Quantum Electronics, vol. 2, pp. 1017-28, 1996/12/ 1996. [4] M. Kempe, W. Rudolph, and E. Welsch, "Comparative study of confocal and heterodyne microscopy for imaging through scattering media," Journal of the Optical Society of America a-Optics Image Science and Vision, vol. 13, pp. 46-52, JAN 1996. [5] S. Bourquin, A. D. Aguirre, I. Hartl, P. Hsiung, T. H. Ko, J. G. Fujimoto, T. A. Birks, W. J. Wadsworth, U. Bunting, and D. Kopf, "Ultrahigh resolution real time OCT imaging using a compact femtosecond Nd : Glass laser and nonlinear fiber," Optics Express, vol. 11, pp. 3290-3297, Dec 1 2003.
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[6] A. D. Aguirre, N. Nishizawa, J. G. Fujimoto, W. Seitz, M. Lederer, and D. Kopf, "Continuum generation in a novel photonic crystal fiber for ultrahigh resolution optical coherence tomography at 800 nm and 1300 nm," Optics Express, vol. 14, pp. 1145-1160, Feb 6 2006. [7] A. D. Aguirre, J. Sawinksi, S.-W. Huang, C. Zhou, W. Denk, and J. G. Fujimoto, "High Speed Optical Coherence Microscopy with Autofocus Adjustment and a Miniaturized Endoscopic Imaging Probe," Opt. Express, vol. forthcoming, 2009. [8] S. A. Hundahl, I. D. Fleming, A. M. Fremgen, and H. R. Menck, "A National Cancer Data Base Report on 53,856 Cases of Thyroid Carcinoma Treated in the US, 1985-1995," Cancer, vol. 83, pp. 2638-2648, Dec 15 1998. [9] "Cancer Facts and Figures," American Cancer Society 2009 2009. [10] P. W. Wiest, M. F. Hartshorne, P. D. Inskip, L. A. Crooks, B. S. Vela, R. J. Telepak, M. R. Williamson, R. Blumhardt, J. M. Bauman, and M. Tekkel, "Thyroid palpation versus high-resolution thyroid ultrasonography in the detection of nodules," Journal of Ultrasound in Medicine, vol. 17, pp. 487-496, Aug 1998. [11] B. A. Carroll, "Asymptomatic Thyroid-Nodules - Incidental Sonographic Detection," American Journal of Roentgenology, vol. 138, pp. 499-501, 1982. [12] A. Brander, P. Viikinkoski, J. Nickels, and L. Kivisaari, "Thyroid-Gland - Ultrasound Screening in a Random Adult-Population," Radiology, vol. 181, pp. 683-687, Dec 1991. [13] J. N. Bruneton, C. Balumaestro, P. Y. Marcy, P. Melia, and M. Y. Mourou, "Very High-Frequency (13 Mhz) Ultrasonographic Examination of the Normal Neck - Detection of Normal Lymph-Nodes and Thyroid-Nodules," Journal of Ultrasound in Medicine, vol. 13, pp. 87-90, Feb 1994. [14] C. Zhou, Y. H. Wang, A. D. Aguirre, T.-H. Tsai, J. L. Connolly, and J. G. Fujimoto, "Ex vivo Imaging of Human Thyroid Pathology Using Integrated Optical Coherence Tomography (OCT) and Optical Coherence Microscopy (OCM)," Journal of Biomedical Optics, vol. forthcoming, 2009. [15] S. H. Landis, T. Murray, S. Bolden, and P. A. Wingo, "Cancer statistics, 1999," Ca-a Cancer Journal for Clinicians, vol. 49, pp. 8-31, Jan-Feb 1999. [16] D. Pascual and A. Borque, "Epidemiology of kidney cancer," Adv Urol., p. 782381, 2008. [17] J. K. McLaughlin, L. Lipworth, and R. E. Tarone, "Epidemiologic aspects of renal cell carcinoma," Seminars in Oncology, vol. 33, pp. 527-533, Oct 2006. [18] S. Daimon and I. Koni, "Glomerular enlargement in the progression of mesangial proliferative glomerulonephritis," Clinical Nephrology, vol. 49, pp. 145-152, Mar 1998.
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5. Functional Brain Imaging with Optical Coherence Tomography
Sponsors Air Force Office of Scientific Research - FA9550-07-1-0101, FA9550-07-1-0014 National Institutes of Health - R01-EY11289-24, 5R01-NS057476-02, 5R01-CA75289-13
Project Staff Prof. James G. Fujimoto, Dr. Chao Zhou (MIT) Dr. Vivek J. Srinivasan (MIT, MGH) Prof. David A. Boas, Dr. Sava Sakadzic, Svetlana Ruvinskaya (MGH)
Functional brain imaging of neuronal and hemodynamic response to external stimuli is an active area of research. Several methods including, hemodynamic techniques, positron emission tomography (PET), single-photon emission computed tomography (SPECT), and functional magnetic resonance imaging (fMRI) can visualize spatial localization of neural activity, but have limited temporal resolution. Electrophysiological techniques, such as electroencephalography (EEG), can measure neural responses on the millisecond time scale, but have limited spatial resolution. Optical methods offer both high spatial and high temporal resolutions and are therefore particularly promising for making full-field measurements of hemodynamic, metabolic, and neuronal activities in vivo. Currently, most optical intrinsic signal imaging (OISI) methods present two-dimensional en face maps of brain activation and do not provide depth resolution of the functional response [1-4]. Depth-resolved images can be achieved by multiphoton fluorescence microscopy [5] and laminar optical tomography [6]. OCT enables cross sectional and three dimensional imaging and is becoming a powerful tool for research on functional imaging in the cerebral cortex [7-9].
Working in collaboration with Dr. David Boas at the Martinos Center for Biomedical Imaging of the Massachusetts General Hospital and Harvard Medical School, we are investigating OCT for functional brain imaging. OCT enables cross sectional and three dimensional measurements of subsurface scattering and blood flow changes due to functional activation in the rat somatosensory cortex. In a previous study, we performed simultaneous optical intrinsic signal imaging (OISI) and OCT imaging on anesthetized rat with a thinned-skull preparation [9]. Depth-resolved functional OCT imaging of the neurovascular response to somatosensory stimulation showed that the time-course of the OCT response correlates well with OISI, suggesting that the OCT signal may reflect changes in hemodynamics. OCT signals included both positive and negative OCT functional changes. Layer specific dynamic responses in the OCT signals, possibly indicating retrograde vessel dilation, were also observed [10].
Ongoing studies are focused on understanding the etiology of the OCT functional signal, changes in blood vessel diameter, flow, and total hemoglobin in rat somatosensory cortex during functional activation. Previous studies were performed with an earlier generation OCT system which used time domain detection. The system operated at 1060 nm center wavelengths using a femtosecond Nd:Glass laser light source and had an imaging speed of 3,000 axial scans per second, corresponding to the acquisition of 3 images (of 1000 axial scans each) per second. We have developed a high speed spectral / Fourier domain OCT microscope for in vivo imaging of the rat cerebral cortex with 3.7 um axial resolution in tissue and 22,000 axial scans per second. The light source consisted of a Ti:sapphire laser operating at 830 nm which was spectrally broadened in a nonlinear fiber. The high speeds enabled improved image quality as well as enhanced the ability to perform time dependent imaging required for functional studies.
Functional imaging was performed in the rat cortex using OISI and OCT imaging. Figure 5.1(A) shows the OISI change in reflectance at 570 nm during peak activation normalized to baseline. The OCT scan position is shown as a white arrow. Thirty trials of contralateral forepaw stimulation were performed, with 20 seconds between stimuli. Figure 5.1(B) shows a Doppler OCT image. Blood
17-53 Chapter 17. Biomedical Optical Imaging vessels up to a depth of greater than 500 um can be visualized. Artifacts are evident below large vessels because of scattering and attenuation. Figure 5.1(C) shows a Doppler OCT image of an arteriole at baseline (0–1 s) and during peak activation (4–6 s). Changes in both blood velocity and cross-sectional area of the vessel are evident. Figure 5.1(D) shows measurements of flow, diameter, and maximum velocity during functional activation. The flow and maximum velocity show significant covariance and have a higher variance than the diameter measurements. The relative flow change calculated directly by spatial summation over a region of interest containing the vessel agrees with the relative flow change obtained from the relative changes in maximum velocity and diameter. The peak change in velocity is approximately 10%, while the peak change in diameter is 15% and the peak change in flow is 40%. Separation of flow, velocity, and diameter changes based on the velocity profile is possible in large vessels.
Figure 5.1. (A) Differential optical intrinsic signal imaging (OISI) at peak activation and (B) Doppler OCT image at baseline. OCT scan position on the cortical surface is indicated by a white line. (C) Doppler OCT velocity image of a pial artery at baseline and during peak activation. (D) Relative flow, velocity and diameter time courses. (E) OCT amplitude image showing a region of interest (ROI) in a capillary bed, and a draining vein. (F) Time courses
of ∆μt measured by OCT (solid line), flow in the draining vein measured by OCT (dashed line), and ∆HBT measured by OISI (dotted line). Extinction coefficient change measured by OCT shows a time course that resembles total hemoglobin.
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Imaging of total hemoglobin concentration can be performed by measuring the change in extinction coefficient caused by functional activation. Figure 5.1(E) shows an OCT image with a region of interest around a capillary bed, and a draining vein (V) near the region of interest (ROI). Figure 5.1(F) shows the change in the extinction coefficient as a function of time with the OISI total hemoglobin change ∆HBT and the OCT flow in a vein as labeled in figure 5.1 E). Both the ∆HBT signal and the OCT flow signal match the peak of the ∆μt signal. The ∆HBT and ∆μt time course shapes are virtually identical. In contrast, the flow response shows a faster return to baseline than both the ∆HBT and the ∆μt responses. The increase in extinction coefficient is consistent with an increase in scattering resulting from a higher red-blood-cell concentration.
Compared to depth-integrated OISI, OCT has the unique advantage of resolving functional response in three dimensions. This capability is important when investigating the dynamic responses in different cortical layers. Our study results represent the first direct measurements of evoked hemodynamic changes due to functional activation with OCT. These results may help to elucidate the hemodynamic component of the functional response that is responsible for the BOLD (blood oxygen level-dependant) magnetic resonance imaging (MRI) signal at the microscopic level, thereby enabling more quantitative interpretation of functional MRI. In addition, measurements of blood flow are important for quantitative measurements of oxygen delivery and therefore oxygen consumption. Further studies using Doppler OCT methods promise to provide a quantitative assessment of changes in vascular flow with respect to depth. With further investigation, this technique has potential to become a new tool for basic and applied neuroscience research in animal models to measure stimulus-induced changes in blood flow.
References
[1] B. M. Ances, J. H. Greenberg, and J. A. Detre, "Laser doppler imaging of activation-flow coupling in the rat somatosensory cortex," Neuroimage, vol. 10, pp. 716-23, Dec 1999. [2] A. K. Dunn, A. Devor, A. M. Dale, and D. A. Boas, "Spatial extent of oxygen metabolism and hemodynamic changes during functional activation of the rat somatosensory cortex," Neuroimage, vol. 27, pp. 279-90, Aug 15 2005. [3] S. A. Sheth, M. Nemoto, M. W. Guiou, M. A. Walker, and A. W. Toga, "Spatiotemporal evolution of functional hemodynamic changes and their relationship to neuronal activity," J Cereb Blood Flow Metab, vol. 25, pp. 830-41, Jul 2005. [4] D. Y. Ts'o, R. D. Frostig, E. E. Lieke, and A. Grinvald, "Functional organization of primate visual cortex revealed by high resolution optical imaging," Science, vol. 249, pp. 417-20, Jul 27 1990. [5] D. Kleinfeld, P. P. Mitra, F. Helmchen, and W. Denk, "Fluctuations and stimulus-induced changes in blood flow observed in individual capillaries in layers 2 through 4 of rat neocortex," Proc Natl Acad Sci U S A, vol. 95, pp. 15741-6, Dec 22 1998. [6] E. M. Hillman, A. Devor, M. B. Bouchard, A. K. Dunn, G. W. Krauss, J. Skoch, B. J. Bacskai, A. M. Dale, and D. A. Boas, "Depth-resolved optical imaging and microscopy of vascular compartment dynamics during somatosensory stimulation," Neuroimage, vol. 35, pp. 89-104, Mar 2007. [7] A. D. Aguirre, Y. Chen, J. G. Fujimoto, L. Ruvinskaya, A. Devor, and D. A. Boas, "Depth-resolved imaging of functional activation in the rat cerebral cortex using optical coherence tomography," Optics Letters, vol. 31, pp. 3459-3461, Dec 2006. [8] R. U. Maheswari, H. Takaoka, H. Kadono, R. Homma, and M. Tanifuji, "Novel functional imaging technique from brain surface with optical coherence tomography enabling visualization of depth resolved functional structure in vivo," Journal of Neuroscience Methods, vol. 124, pp. 83-92, Mar 30 2003. [9] J. Seki, Y. Satomura, Y. Ooi, T. Yanagida, and A. Seiyama, "Velocity profiles in the rat cerebral microvessels measured by optical coherence tomography," Clinical Hemorheology and Microcirculation, vol. 34, pp. 233-239, 2006.
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[10] Y. Chen, A. D. Aguirre, L. Ruvinskaya, A. Devor, D. A. Boas, and J. G. Fujimoto, "Optical coherence tomography (OCT) reveals depth-resolved dynamics during functional brain activation," Journal of Neuroscience Methods, vol. 178, pp. 162-173, 2009.
Publications
1. A. Manassakorn, H. Ishikawa, J.S. Kim, G. Wollstein, R.A. Bilonick, L. Kagemann, M.L. Gabriele, K.R. Sung, T. Mumcuoglu, J.S. Duker, J.G. Fujimoto, and J.S. Schuman, “Comparison of optic disc margin identified by color disc photo and high-speed ultrahigh-resolution optical coherence tomography,” Arch. Ophthalmol. 126, 58-64, January 2008. 2. W. Drexler and J.G. Fujimoto, “State-of-the-art retinal optical coherence tomography,” Prog. Retin. Eye Res. 27, 45-88, January 2008. 3. Y. Chen, A.D. Aguirre, P.-L. Hsiung, S.-W. Huang, H. Mashimo, J.M. Schmitt, and J.G. Fujimoto, “Effects of axial resolution improvement on optical coherence tomography (OCT) imaging of gastrointestinal tissues,” Opt. Exp. 16, 2469-2485, February 2008. 4. U. Demirbas, A. Sennaroglu, F.X. Kãrtner, and J.G. Fujimoto, “Highly efficient, low-cost Cr3+:LiCAF laser pumped by single-mode diodes,” Opt. Lett. 33, 590-592, March 2008. 5. D.C. Adler, S.-W. Huang, R. Huber, and J.G. Fujimoto, “Photothermal detection of gold nanoparticles using phase-sensitive optical coherence tomography,” Opt. Exp. 16, 4376-4393, March 2008. 6. P.M. Andrews, Y. Chen, M.L. Onozato, S.-W. Huang, D.C. Adler, R.A. Huber, J. Jiang, S.E. Barry, A.E. Cable, and J.G. Fujimoto, “High-resolution optical coherence tomography imaging of the living kidney,” Lab. Invest. 88, 441-449, April 2008. 7. V.J. Srinivasan, B.K. Monson, M. Wojtkowski, R.A. Bilonick, I. Gorczynska, R. Chen, J.S. Duker, J.S. Schuman, and J.G. Fujimoto, “Characterization of outer retinal morphology with high-speed, ultrahigh-resolution optical coherence tomography,” Invest. Ophthalmol. and Vis. Sci. 49, 1571-1579, April 2008. 8. R.W. Chen, I. Gorczynska, V.J. Srinivasan, J.G. Fujimoto, J.S. Duker, and E. Reichel, “High-speed ultrahigh-resolution optical coherence tomography findings in chronic solar retinopathy,” Retin. Cases Brief Rep. 2, 103-105, spring 2008. 9. T. Mumcuoglu, G. Wollstein, M. Wojtkowski, L. Kagemann, H. Ishikawa, M.L. Gabrielle, V. Srinivasan, J.G. Fujimoto, J.S. Duker, and J.S. Schuman, “Improved visualization of glaucomatous retinal damage using high-speed ultrahigh-resolution optical coherence tomography,” Ophthalmology 115, 782-789, May 2008. 10. M.L. Gabriele, H. Ishikawa, G. Wollstein, R.A. Bilonick, K.A. Townsend, L. Kagemann, M. Wojtkowski, V.J. Srinivasan, J.G. Fujimoto, J.S. Duker, and J.S. Schuman, “Optical coherence tomography scan circle location and mean retinal nerve fiber layer measurement variability,” Invest. Ophthalmol. and Vis. Sci. 49, 2315-2321, June 2008. 11. L. Kagemann, T. Mumcuoglu, G. Wollstein, R. Bilonick, H. Ishikawa, K.A. Townsend, M. Gabriele, J.G. Fujimoto, and J.S. Schuman, “Sources of longitudinal variability in optical coherence tomography nerve-fibre layer measurements,” Br. J. Ophthalmol. 92, 806-809, June 2008. 12. B. Potsaid, I. Gorczynska, V. Srinivasan, Y. Chen, J. Jiang, A. Cable, and J.G. Fujimoto, “Ultrahigh speed spectral/Fourier domain optical coherence tomography ophthalmic imaging at 70,000-312,500 axial scans per second,” Opt. Exp. 16, 15149-15169, September 2008. 13. B.R. Biedermann, W. Wieser, C.M. Eigenwillig, G. Palte, D.C. Adler, V. Srinivasan, J.G. Fujimoto, and R. Huber, “Real time en face Fourier-domain optical coherence tomography with direct hardware frequency demodulation,” Opt. Lett. 33, 2556-2558, November 2008. 14. L. Kagemann, H. Ishikawa, J. Zou, P. Charukamnoetkanok, G. Wollstein, K.A. Townsend, M.L. Gabriele, N. Bahary, X. Wei, J.G. Fujimoto, and J.S. Schuman, “Repeated, noninvasive high resolution spectral domain optical coherence tomography imaging of zebrafish embryos,” Mol. Vis. 14, 2157-2170, November 2008.
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15. V.J. Srinivasan, D.C. Adler, Y. Chen, I. Gorczynska, R. Huber, J.S. Duker, J.S. Schuman, and J.G. Fujimoto, “Ultrahigh-speed optical coherence tomography for three-dimensional and en face imaging of the retina and optic nerve head,” Invest. Ophthalmol. and Vis. Sci. 49, 5103-5110, November 2008. 16. E.M. Frohman, J.G. Fujimoto, T.C. Frohman, P.A. Calabresi, G. Cutter, and L.J. Balcer, “Optical coherence tomography: a window into the mechanisms of multiple sclerosis,” Nat. Clin. Pract. Neurol. 4, 664-675, December 2008. 17. S. Sakadžić, U. Demirbas, T.R. Mempel, A. Moore, S. Ruvinskaya, D.A. Boas, A. Sennaroglu, F.X. Kärtner, and J.G. Fujimoto, “Multi-photon microscopy with a low-cost and highly efficient Cr:LiCAF laser,” Opt. Exp. 16, 20848-20863, December 2008. 18. D.C. Adler, C. Zhou, T.-H. Tsai, J. Schmitt, Q. Huang, H. Mashimo, and J.G. Fujimoto, “Three-dimensional endomicroscopy of the human colon using optical coherence tomography,” Opt. Exp. 17, 784-796, January 2009. 19. U. Demirbas, A. Sennaroglu, F.X. Kärtner, and J.G. Fujimoto, “Comparative investigation of diode pumping for continuous-wave and mode-locked Cr3+:LiCAF lasers,” JOSA B 16, 64-79, January 2009. 20. U. Demirbas, A. Sennaroglu, F.X. Kärtner, and J.G. Fujimoto, “Generation of 15-nJ pulses from a highly efficient, low-cost multipass-cavity Cr3+:LiCAF laser,” Opt. Lett. 34, 497-499, February 2009. 21. Y. Chen, A.D. Aguirre, L. Ruvinskaya, A. Devor, D.A. Boas, and J.G. Fujimoto, “Optical coherence tomography (OCT) reveals depth-resolved dynamics during functional brain activation,” J. Neurosci. Methods, 178, 162-173, March 2009. 22. Y. Chen, L.N. Vuong, J. Liu, J. Ho, V.J. Srinivasan, I. Gorczynska, A.J. Witkin, J.S. Duker, J. Schuman, and J.G. Fujimoto, “Three-dimensional ultrahigh resolution optical coherence tomography imaging of age-related macular degeneration,” Opt. Exp. 17, 4046-4060, March 2009. 23. H. Ishikawa, J. Kim, T.R. Friberg, G. Wollstein, L. Kagemann, M.L. Gabriele, K.A. Townsend, K.R. Sung, J.S. Duker, J.G. Fujimoto, and J.S. Schuman, “Three-dimensional optical coherence tomography (3D-OCT) image enhancement with segmentation-free contour modeling C-mode,” Invest. Ophthalmol. and Vis. Sci. 50, 1344-1349, March 2009. 24. J.J. Kaluźny, M. Wojtkowski, B.L. Sikorski, M. Szkulmowski, A. Szkulmowska, T. Bajraszewski, J.G. Fujimoto, J.S. Duker, J.S. Schuman, and A. Kowalczyk, “Analysis of the outer retina reconstructed by high-resolution, three-dimensional spectral domain optical coherence tomography,” Ophthalmic Surg. Lasers Imaging 40, 102-108 March/April 2009. 25. V.J. Srinivasan, Y. Chen, J.S. Duker, and J.G. Fujimoto, “In vivo functional imaging of intrinsic scattering changes in the human retina with high-speed ultrahigh resolution OCT,” Opt. Exp. 17, 3861-3877, March 2009. 26. M. Wojtkowski, B.L. Sikorski, I. Gorczynska, M. Gora, M. Szkulmowski, D. Bukowska, J. Kaluzny, J.G. Fujimoto, and A. Kowalczyk, “Comparison of reflectivity maps and outer retinal topography in retinal disease by 3-D Fourier domain optical coherence tomography,” Opt. Exp. 17, 4189-4207, March 2009. 27. I. Gorczynska, V.J. Srinivasan, L.N. Vuong, R.W.S. Chen, J.J. Liu, E. Reichel, M. Wojtkowski, J.S. Schuman, J.S. Duker, and J.G. Fujimoto, “Projection OCT fundus imaging for visualising outer retinal pathology in non-exudative age-related macular degeneration,” Br. J. Ophthalmol. 93, 603-609, May 2009. 28. A. Zhou, D.C. Adler, L. Becker, Y. Chen, T.-H. Tsai, M. Figueirdo, J.M. Schmitt, J.G. Fujimoto, and H. Mashimo, “Effective treatment of chronic radiation proctitis using radiofrequency ablation,” Ther. Adv. Gastroentrol. 2, 149-156, May 2009. 29. A.J. Witkin, L.N. Vuong, V.J. Srinivasan, I. Gorczynska, E. Reichel, C.R. Baumal, A.H. Rogers, J.S. Schuman, J.G. Fujimoto, and J.S. Duker, “High-speed ultrahigh resolution optical coherence tomography before and after ranibizumab for age-related macular degeneration,” Ophthalmology 116, 956-963, May 2009.
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30. K.R. Sung, G. Wollstein, R.A. Bilonick, K.A. Townsend, H. Ishikawa, L. Kagemann, R.J. Noecker, J.G. Fujimoto, and J.S. Schuman, “Effects of age on optical coherence tomography measurements of healthy retinal nerve fiber layer, macula, and optic nerve head,” Ophthalmology 116, 1119-1124, June 2009. 31. U. Demirbas, D. Li, J. Birge, A. Sennaroglu, G.S. Petrich, L.A. Kolodziejski, F.X. Kärtner, and J.G. Fujimoto, “Low-cost, single-mode diode-pumped Cr:Colquiriite lasers,” Opt. Exp. 17, 14374-14388, July 2009. 32. J.S. Kim, H. Ishikawa, K.R. Sung, J. Xu, G. Wollstein, R.A. Bilonick, M.L. Gabriele, L. Kagemann, J.S. Duker, J.G. Fujimoto, and J.S. Schuman, “Retinal nerve fiber layer thickness measurement reproducibility improved with spectral domain optical coherence tomography,” Br. J. Ophthalmol. 93, 1057-1063, August 2009. 33. D.C. Adler, C. Zhou, T.-H. Tsai, H.-C. Lee, L. Becker, J.M. Schmitt, Q. Huang, J.G. Fujimoto, and H. Mashimo, “Three-dimensional optical coherence tomography of Barrett’s esophagus and buried glands beneath neo-squamous epithelium following radiofrequency ablation,” Endoscopy 41, 773-776, September 2009. 34. J. Ho, A.C. Sull, L.N. Vuong, Y. Chen, J. Liu, J.G. Fujimoto, J.S. Schuman, and J.S. Duker, “Assessment of artifacts and reproducibility across spectral- and time-domain optical coherence tomography devices,” Ophthalmology 116, 1960-1970, October 2009. 35. V.J. Srinivasan, S. Sakadzić, I. Gorczynska, S. Ruvinskaya, W. Wu, J.G. Fujimoto, and D. Boas, “Depth-resolved microscopy of cortical hemodynamics with optical coherence tomography,” Opt. Lett. 34, 3086-3088, October 2009. 36. T.H. Tsai, C. Zhou, D.C. Adler, and J.G. Fujimoto, “Frequency comb swept lasers,” Opt. Exp. 17, 21257-21270, November 2009. 37. V.J. Srinivasan, J.Y. Jiang, M.A. Yaseen, H. Radhakrishnan, W. Wu, S. Barry, A.E. Cable, and D.A. Boas, “Rapid volumetric angiography of cortical microvasculature with optical coherence tomography,” Opt. Lett. 35, 43-45, January 2010. 38. A.D. Aguirre, J. Sawinski, S.-W. Huang, C. Zhou, W. Denk, and J.G. Fujimoto, “High-speed optical coherence microscopy with autofocus adjustment and a miniaturized endoscopic imaging probe,” Opt. Exp., forthcoming. 39. A.D. Aguirre, Y. Chen, B. Bryan, H. Mashimo, Q. Huang, J.L. Connolly, and J.G. Fujimoto, “Cellular resolution ex vivo imaging of gastrointestinal tissues with optical coherence microscopy,” J. Biomed. Opt., forthcoming. 40. U. Demirbas, K-H. Hong, J.G. Fujimoto, A. Sennaroglu, and F.X. Kärtner, “A low-cost cavity-dumped femtosecond Cr:LiSaF laser producing >100nJ pulses,” Opt. Lett., forthcoming. 41. J. Ho, A.J. Witkin, Y. Chen, J. Liu, C. Baumal, A.H. Rogers, J.G. Fujimoto, J.S. Schuman, and J.S. Duker, “Volumetric analysis of subretinal and sub-retinal pigment epithelium pathologies via commercial spectral domain optical coherence tomography devices,” Ophthalmology, forthcoming. 42. J.S. Kim, H. Ishikawa, M.L. Gabriele, G. Wollstein, R.A. Bilonick, L. Kagemann, J.G. Fujimoto, and J.S. Schuman, “Retinal nerve fiber layer thickness measurement comparability between time domain optical coherence tomography (OCT) and spectral domain OCT,” Invest. Ophthalmol. and Vis. Sci., forthcoming (epub September 2009). 43. A.C. Sull, L.N. Vuong, L.L. Price, V.J. Srinivasan, I. Gorczynska, J.G. Fujimoto, J.S. Schuman, and J.S. Duker, “Comparison of spectral Fourier domain optical coherence tomography instruments for assessment of normal macular thickness,” Retina, forthcoming (epub December 2009). 44. C. Zhou, Y. Wang, A.D. Aguirre, T.-H. Tsai, D.W. Cohen, J.L. Connolly, and J.G. Fujimoto, “Ex vivo imaging of human thyroid pathology using integrated optical coherence tomography (OCT) and optical coherence microscopy (OCM),” J. Biomed. Opt., forthcoming. 45. C. Zhou, T.-H. Tsai, D.C. Adler, H.C. Lee, D.W. Cohen, A. Mondelblatt, Y. Wang, J.L. Connolly, and J.G. Fujimoto, “Photothermal optical coherence tomography in ex vivo human breast tissues using gold nanoshells,” Opt. Lett., forthcoming.
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