Skip Navigation LinksHome > May 2012 - Volume 89 - Issue 5 > Optical Coherence Tomography: Future Trends for Imaging in...
Optometry & Vision Science:
doi: 10.1097/OPX.0b013e31824eeb43
Imaging and Measurement of the Retina and Optic Nerve: Review

Optical Coherence Tomography: Future Trends for Imaging in Glaucoma

Folio, Lindsey S.*; Wollstein, Gadi; Schuman, Joel S.

Free Access
Article Outline
Collapse Box

Author Information

*BS

MD

Department of Ophthalmology, UPMC Eye Center, Eye and Ear Institute, Ophthalmology and Visual Science Research Center, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania (LSF, GW, JSS), and Department of Bioengineering, Swanson School of Engineering, University of Pittsburgh, Pittsburgh, Pennsylvania (LSF, JSS).

Received October 4, 2011; accepted December 13, 2011.

Gadi Wollstein UPMC Eye Center, Department of Ophthalmology University of Pittsburgh School of Medicine 203 Lothrop Street, Eye and Ear Institute, Suite 834 Pittsburgh, Pennsylvania 15213 e-mail: wollsteing@upmc.edu

Collapse Box

Abstract

ABSTRACT: Optical coherence tomography captures a major role in clinical assessment in eye care. Innovative hardware and software improvements in the technology would further enhance its usefulness. In this review, we present several promising initiatives currently in development or early phase of assessment that we expect to have a future impact on optical coherence tomography.

Ophthalmic imaging technologies have greatly shaped the current clinical practice of eye care. The commercial technologies available today provide clinicians with high-resolution, real-time images of the ocular structures involved in glaucoma and have the ability to quantify these structures. These capabilities are useful for identifying and monitoring diseases involving the retina111 and anterior segment.1214

The optical coherence tomography (OCT) technique was first published ∼20 years ago15 and much improvement to the technology has since been made. OCT is a non-invasive imaging technique that uses low-coherence interferometry to create cross-sectional images, using information from the echo time delay and reflected and backscattered light intensity. The most current iteration of OCT, spectral domain (SD)-OCT, has scanning speeds ∼40 to 110 times faster than its predecessor,16 time domain (TD)-OCT, because it does not require the use of a moving mirror in the reference arm. SD-OCT transforms the signal into its frequency components, allowing all points of an axial scan (A-scan), sampling the tissue depth, to be collected simultaneously. Multiple A-scans are collected and segmentation algorithms are used to determine tissue layer boundaries and quantify retinal tissue thicknesses such as the retinal nerve fiber layer (RNFL). OCT has been shown to be reproducible in measuring retinal structures1721 and has the ability to discriminate between healthy and glaucomatous eyes.2224 Because of the advanced capabilities of OCT, it has become a primary imaging device in eye care allowing clinicians to monitor the progression of disease,2527 visualize ocular structures in three dimensions (3D),2830 and determine the effectiveness of clinical treatments.31,32 Much of the current research in ophthalmic imaging focuses on improving SD-OCT and developing multimodal imaging systems that use other advanced optical techniques.

The focus of this article is to discuss the projected developmental path of the OCT technology. The predicted impact this progress will have on imaging in the eye care clinic will also be discussed.

Back to Top | Article Outline

OCT IN GLAUCOMA: WHERE WE ARE

The first retinal OCT images were presented in 1991 and allowed visualization of the retinal layers and the optic nerve head (ONH).15 In 1995, the first OCT images of diseased retina were published, revealing an improved resolution of 10 μm and showing the clinical utility of the device.5,7 These studies revealed OCT's ability to quantify the RNFL and showed non-invasive, non-contact visualization of macular pathologies such as epiretinal membranes, macular hole, and macular edema. In 2002, the first in vivo SD-OCT images of the lens, iris, retina, and ONH were published.2 Today, commercially available SD-OCT systems are capable of capturing images with scanning speeds of ∼27,000 A-scans/s and axial resolutions of ∼5 to 6 μm, compared with TD-OCT systems with scanning speeds of ∼400 A-scans/s and axial resolution of ∼10 μm. This improved performance allows SD-OCT to capture high-density images of the structures of the eye in 3D.

Both OCT technologies are available commercially and have shown the ability to reproducibly measure ocular tissue structures.17,18,21 In addition, measurements obtained with SD-OCT have been shown to offer improved reproducibility over TD-OCT measurements.33 These devices use normative databases that have the ability to highlight local defects,34,35 and offer clinicians a more intuitive method to monitor disease status. TD- and SD-OCT have also shown the ability to detect eyes defined as glaucomatous by visual fields.16,22,3639 These imaging devices have shown the ability to detect glaucomatous progression in longitudinal studies.2527,40 In longitudinal assessment of glaucoma, it is predicted that SD-OCT will offer more sensitivity and specificity for detecting change, compared with TD-OCT, because of the improved reproducibility and the ability to align scan location between visits. Further SD-OCT longitudinal studies need to be conducted before this can be confirmed.

Back to Top | Article Outline

PREDICTIONS FOR THE FUTURE

Imaging Methods
High Speed

The eye presents as a near perfect environment to enable the use of OCT imaging. The pupil serves as a direct window to image structures of the retina and ONH, which are suitable for OCT imaging because they are weakly scattering of light in the visible range. Even though the eye is very appropriate for the methodologies of OCT imaging, limitations continue to exist that may be overcome with improvements in image acquisition techniques. Currently, there has been an effort focused on increasing the scanning speed of OCT systems. Studies have shown OCT to be capable of achieving scanning speeds of up to 20.8 million A-scans/s.41 The benefits from increased scanning speeds are the reduction in eye movement associated with a shorter scanning time and the ability to use signal averaging, where adjacent A- or B-scans are averaged. This has been shown to improve scan quality by reducing speckle noise42 and allow better visualization of retinal structure within OCT images.43,44

High-speed imaging also enables fine structures to be captured in high density, revealing important clinical information in micron scale. Studies have shown that high-speed OCT systems are capable of presenting photoreceptor structures.45,46 For visualization of the photoreceptors, the use of high-speed OCT systems is required, otherwise small eye movements cause image distortion eliminating visualization of these microstructures. Faster scanning speeds would also allow the acquisition of 3-D cubes of data that enable advanced processing. It allows novel scanning patterns, such as orthogonal scanning, to be performed, which have been shown to aid in reducing eye movement artifact through processing.45 High-speed imaging of the anterior chamber, cornea, and lens, with a large imaging depth and high-axial resolution, showed the ability to image mechanical processes in the anterior chamber, such as blinking and dilation.47 This ability has potential for use in assessing the dynamics of the anterior segment.

Another form of Fourier domain OCT capable of scanning at high speed is swept source (SS)-OCT.42,4850 SS-OCT also makes use of the Fourier transform to capture signals in the frequency domain; however, it uses a tunable laser and a single photodetector instead of a CCD camera. The utilization of a tunable laser allows the light to rapidly scan through the different appropriate frequencies in a broad spectrum, where the reflectance can then be assessed by a photodetector. The advantages of SS-OCT are that it does not result in signal drop-off with depth,16 and the imaging technique results in a high acquisition speed.51 Wide-field imaging has been shown to be possible using an ultrahigh speed SS-OCT system. This method can capture images scanning a 12 × 12 mm area of retina at a sampling density of 1100 × 1100 A-scans.51 Wide-field imaging offers the benefit of capturing both the ONH and macula regions in one image, which could potentially simplify and standardize ophthalmic examination protocols.

Back to Top | Article Outline
Longer Wavelengths

Currently, clinical OCT imaging of the retina mainly occurs at wavelengths of the 800 to 870 nm range. In OCT imaging, to increase axial resolution, the central wavelength can be decreased, the bandwidth can be increased, or a combination of the two can be performed. A low central wavelength light source provides a high-axial resolution; however, it also leads to increased scattering of light, making deep penetration into the tissue difficult. An appropriate OCT light source must have a good balance between central wavelength and bandwidth to achieve the required axial resolution and scattering requirements. The current 800 to 870 nm range is appropriate for achieving highly detailed images of the retina; however, the melanin contained in the retinal pigment epithelial (RPE) is highly scattering and absorbing in this range,52 making it difficult to image structures below this tissue layer, such as the choroid and choriocapillaris. In addition, because of the rapid signal drop-off, the penetration of light into the ONH is limited. Current research is focused on exploring OCT imaging at wavelengths of 1000 to 1100 nm to achieve deeper imaging capabilities, and allow penetration below the RPE. Fig. 1 shows an SD-OCT image using a 1030 nm central wavelength light source, where C-mode segmentation highlights the lamina cribrosa pore structure. Long-wavelength imaging may also improve OCT signal quality in patients with media opacity.53,54 High-speed retinal OCT in the range of 1000 to 1100 nm wavelength has been shown to allow imaging the layers of the choroid, which might be useful in evaluation of glaucoma and age-related macular degeneration.55 Moreover, the use of high-speed SS-OCT combined with a long wavelength light source has shown the ability to produce promising images of deep structures of the posterior segment, such as the lamina cribrosa and sclera.42,49,56

Figure 1
Figure 1
Image Tools
Back to Top | Article Outline
Adaptive Optics

The transverse resolution of an OCT image is limited by the spot size of the beam of light, when focused on the retina. However, optical aberrations occur as light passes through the different media of the eye and limit the focusing power of the light. When OCT is combined with corrective optics techniques, such as adaptive optics (AO), the spot size can be reduced, thus improving the transverse resolution of the imaging system. AO imaging measures the monochromatic aberrations occurring in the eye and corrects them using sensing of wavefronts and deformable mirrors. This technique has been shown to improve retinal imaging capabilities and can be combined with SD-OCT.57,58 Here, the combination of the high-axial resolution of SD-OCT and enhanced transverse resolution of AO creates high-resolution images where visualization of retinal microvasculature and photoreceptors is possible.5962 Limitations of AO include both its narrow depth of focus and small field of view; however, the ability to align and stitch multiple AO frames together, creating a large mosaic retinal image has been shown.63 Further studies are required on large cohorts to demonstrate the clinical impact of this combination imaging technique.

Back to Top | Article Outline
Image Analysis
Segmentation Algorithms

Current research in SD-OCT image analysis has focused on developing automatic segmentation algorithms to determine the thickness of individual layers of the retina including the retinal nerve fiber, retinal ganglion cell, plexiform, nuclear, and photoreceptor layers.64 This microstructure can be visualized and quantified in SD-OCT images because of the superior axial resolution the device provides. With segmentation of the layers of the retina in SD-OCT scans, particularly in the macula region, improved glaucoma detection ability is realized. Additionally, when 3-D cube of data are captured and the retinal layers in each B-scan are segmented, a 2-D thickness map can be created to represent each layer. This is accomplished by representing the thickness of the layer at a given point in the cube by a specific color on the thickness map.

In addition to using the segmentation methods to quantify retinal layers, a method called C-mode analysis can also be used to manually visualize the inner layers of an OCT cube scan.65 This method of contour modeling provides the user with the ability to vary the thickness of the sampling plane and the contour the plane follows, as shown in Fig. 1. It allows the image to be sectioned in a plane perpendicular to the scanning axis at any thickness to enable visualization of embedded structures. Fig. 2 shows C-mode analysis of an eye with neuroretinal detachment, where the C-mode plane is shown at the RPE to highlight the damaged region. This method can also be useful in evaluating pathologies, such as macular edema and age-related macular degeneration, which may result in failure if segmented with an automated algorithm. It has also been shown to provide better visualization of laminar cribrosa pore structure when compared with optic disc photos,66 which in the future may be relevant in the clinical evaluation of glaucoma. Because retinal diseases, such as macular edema and age-related macular degeneration, greatly disrupt the architecture of the retina, conventional OCT segmentation algorithms fail. Studies have shown the ability to use automated algorithms to diagnose retinal pathologies based on 3D-OCT data.67,68

Figure 2
Figure 2
Image Tools
Back to Top | Article Outline
Three-Dimensional Data

The high acquisition speed of SD-OCT allows 3D datasets to be collected and evaluated for clinical use. Here, the volumetric structure of features such as the ONH and macula can be visualized and information obtained in the cube of data can be used in posthoc analysis. Eye movement within 3D scans can cause inappropriate image interpretation and analysis. A reference image, such as the scanning laser ophthalmoscope image, can be used to correct for eye motion, by registering the OCT image to the scanning laser ophthalmoscope image.69 An additional technique has been shown to correct for eye motion without the use of a reference image. This technique makes use of blood vessel location and aligns the A- and B-scans to remove eye movement by a particle filtering technique.70 The ability to correct for eye movement in SD-OCT images would greatly improve the quality of the measurement analysis, especially for children and nystagmus patients, prone to movement during scanning. In addition, it can be expected to reduce the variability among consecutive scans thus improving the ability to detect progression.

The 3.4 mm diameter circle continues to be used in glaucoma evaluation; however, with SD-OCT raster scans, the circle can be placed in any location within the cube of data. Clinically, glaucoma progression detection with SD-OCT should not be limited to the 3.4 mm circle, because local wedge defects could occur outside of this location, as shown in Fig. 3. The entire cube of structural information should be used in the initial clinical evaluation and longitudinal follow-up. One technique to make use of the 3-D data is to sum adjacent pixels into superpixels for comparison with normative superpixel data.71 These superpixel maps help highlight regions of decreased RNFL thickness, using the entire 3-D cube of data, as shown in Fig. 4. Further research is being performed to enhance the superpixel algorithms to maximize the sensitivity and specificity to detect glaucomatous damage and monitor change.

Figure 3
Figure 3
Image Tools
Figure 4
Figure 4
Image Tools

In addition to determining better use of 3D SD-OCT data, there is a need for better 3D-OCT viewing systems that offer cross-platform usability, so that OCT images from any commercially available device can be viewed on one monitor or hand-held device. There is also a need to allow clinicians to manipulate the 3-D images to highlight a region of interest, instead of just being presented with a 2-D screen shot of a 3-D image. The benefits offered through providing clinicians with the ability to virtually peel layers of the retina to highlight a certain pathology or disease cannot be quantified. An improved 3-D viewing system would provide clinicians the ability to use the complete benefits of SD-OCT imaging in their clinical practice.

Back to Top | Article Outline
Retinal Blood Flow

Another method to use SD-OCT to evaluate aspects of ocular disease is to measure retinal blood flow. The ability to measure retinal blood flow in vivo can provide insight on the pathogenesis of diseases, such as glaucoma and macular degeneration. Along with conventional structural scanning SD-OCT can acquire Doppler measurements from which flow velocities can be calculated and thus provide simultaneous structural and functional information. The light scattered from moving red blood cells creates a shift in the optical frequency of the light, which is related to the flow velocity. This provides a non-contact method to collect retinal flow information without the use of a contrast agent. Studies have shown SD-OCT's ability to monitor pulsatile blood flow in the retinal vessels.72,73 A major limiting factor in this technique is the required measurement of the angle between the light source and the flow direction. Multiple studies have shown methods to overcome this barrier,7476 however, eye movement may limit the reliability of the measurements. Current studies are underway using Doppler to assess blood flow involvement in diseases, such as glaucoma, branch retinal vein occlusion, and diabetic retinopathies.77,78 One study showed a trend in decreased blood flow velocity in eyes with retinal and optic nerve diseases when compared with normal eyes.78 Further improvements in the SD-OCT methods used to obtain blood flow measurements will be required before OCT parameters, such as blood flow velocity, can be used clinically.

Back to Top | Article Outline
OCT Imaging Applications
Animal Models

Using OCT imaging in animal models is an application of the technology that continues to expand along with the imaging capabilities. Animal models have shown to be important in studying retinal diseases.7983 Because OCT is non-invasive and allows tissue structure to be evaluated without histology, it makes longitudinal animal model evaluation possible and reduces the number of animals, a study requires. Studies have shown the OCTs ability to image rodent retina84,85 and follow changes to mouse retinal thickness86 and rat RNFL thickness87 longitudinally in a glaucoma model. Studies have described the ability to automatically quantify the thickness of retinal tissue layers in rodents88,89 and have evaluated the OCT en-face view of rats undergoing surgical elevation of intraocular pressure.90 In larger animal models, SD-OCT imaging of macaque eyes has been used to delineate ocular structures91 and evaluate the changes to the deep structures of the ONH longitudinally in an experimental glaucoma model.92 Further studies are required to truly realize the capabilities when combining animal models of disease with OCT imaging.

Back to Top | Article Outline
Surgical Guidance Systems

With the improved capabilities of SD-OCT also comes the ability to achieve high-resolution images of 3-D structures in real time. This ability has most recently been applied in developing OCT systems for use intraoperatively. Additionally, OCT units are now commercially available in handheld form enabling potential use during surgical ophthalmic manipulations. It has become standard practice for OCT images to be used in surgical planning for procedures such as those involving the anterior segment or macular holes, but now research is focused on developing OCT systems to use during surgical procedures. Improvement in the safety, ease, and efficacy of the surgical treatment and receiving immediate feedback on ocular tissue manipulation is the main objectives of this research.

The intraoperative use of OCT has been reported in various surgeries including corneal and retinal surgeries.9398 In addition to using OCT clinically to evaluate ocular structures, studies have focused on improving the imaging techniques to better integrate OCT in the intraoperative environment. One group has shown the ability to present a virtual OCT image directly on the tissue of interest during surgery, removing the need for a separate OCT display.99 Another group has developed a microscope-mounted OCT technique, where the OCT and microscope share the same ocular path, making OCT visualization easier on the surgeon. They demonstrated vitreoretinal manipulations in a porcine eye and evaluated the interference of different surgical tools in the OCT image.100 We expect to see rapid improvements in the techniques used to incorporate OCT visualization with ophthalmic surgery in the future.

Back to Top | Article Outline

CONCLUSIONS

Through this discussion, we have explored the predicted future clinical use of OCT in eye care. There is still more work to be done to advance image acquisition techniques and improve the use of the OCT data in postprocessing, but it is currently underway. As these areas progress, we expect to see the capabilities of OCT being used with their full advantage in the clinic. Overall, we hope these advancements will improve the sensitivity and specificity of disease detection and progression monitoring, so that more timely and effective treatments can be implemented.

Gadi Wollstein

UPMC Eye Center, Department of Ophthalmology

University of Pittsburgh School of Medicine

203 Lothrop Street, Eye and Ear Institute, Suite 834

Pittsburgh, Pennsylvania 15213

e-mail: wollsteing@upmc.edu

Back to Top | Article Outline
ACKNOWLEDGMENTS

This research was supported in part by National Eye Institute, National Institutes of Health contracts R01-EY013178, P30-EY008098 (Bethesda, MD); Eye and Ear Foundation (Pittsburgh, PA); and unrestricted grants from Research to Prevent Blindness (New York, NY).

The sponsor or funding organization had no role in the design or conduct of this research.

J.S.S. receives royalties for intellectual property licensed by Massachusetts Institute of Technology to Carl Zeiss Meditec.

Back to Top | Article Outline

REFERENCES

1. Hee MR, Izatt JA, Swanson EA, Huang D, Schuman JS, Lin CP, Puliafito CA, Fujimoto JG. Optical coherence tomography of the human retina. Arch Ophthalmol 1995;113:325–32.

2. Wojtkowski M, Leitgeb R, Kowalczyk A, Bajraszewski T, Fercher AF. In vivo human retinal imaging by Fourier domain optical coherence tomography. J Biomed Opt 2002;7:457–63.

3. Wollstein G, Paunescu LA, Ko TH, Fujimoto JG, Kowalevicz A, Hartl I, Beaton S, Ishikawa H, Mattox C, Singh O, Duker J, Drexler W, Schuman JS. Ultrahigh-resolution optical coherence tomography in glaucoma. Ophthalmology 2005;112:229–37.

4. Drexler W, Fujimoto JG. State-of-the-art retinal optical coherence tomography. Prog Retin Eye Res 2008;27:45–88.

5. Schuman JS, Hee MR, Arya AV, Pedut-Kloizman T, Puliafito CA, Fujimoto JG, Swanson EA. Optical coherence tomography: a new tool for glaucoma diagnosis. Curr Opin Ophthalmol 1995;6:89–95.

6. Drexler W, Sattmann H, Hermann B, Ko TH, Stur M, Unterhuber A, Scholda C, Findl O, Wirtitsch M, Fujimoto JG, Fercher AF. Enhanced visualization of macular pathology with the use of ultrahigh-resolution optical coherence tomography. Arch Ophthalmol 2003;121:695–706.

7. Puliafito CA, Hee MR, Lin CP, Reichel E, Schuman JS, Duker JS, Izatt JA, Swanson EA, Fujimoto JG. Imaging of macular diseases with optical coherence tomography. Ophthalmology 1995;102:217–29.

8. Hee MR, Baumal CR, Puliafito CA, Duker JS, Reichel E, Wilkins JR, Coker JG, Schuman JS, Swanson EA, Fujimoto JG. Optical coherence tomography of age-related macular degeneration and choroidal neovascularization. Ophthalmology 1996;103:1260–70.

9. Hee MR, Puliafito CA, Wong C, Duker JS, Reichel E, Rutledge B, Schuman JS, Swanson EA, Fujimoto JG. Quantitative assessment of macular edema with optical coherence tomography. Arch Ophthalmol 1995;113:1019–29.

10. Hee MR, Puliafito CA, Wong C, Reichel E, Duker JS, Schuman JS, Swanson EA, Fujimoto JG. Optical coherence tomography of central serous chorioretinopathy. Am J Ophthalmol 1995;120:65–74.

11. Hee MR, Puliafito CA, Wong C, Duker JS, Reichel E, Schuman JS, Swanson EA, Fujimoto JG. Optical coherence tomography of macular holes. Ophthalmology 1995;102:748–56.

12. Izatt JA, Hee MR, Swanson EA, Lin CP, Huang D, Schuman JS, Puliafito CA, Fujimoto JG. Micrometer-scale resolution imaging of the anterior eye in vivo with optical coherence tomography. Arch Ophthalmol 1994;112:1584–9.

13. Konstantopoulos A, Hossain P, Anderson DF. Recent advances in ophthalmic anterior segment imaging: a new era for ophthalmic diagnosis? Br J Ophthalmol 2007;91:551–7.

14. Radhakrishnan S, Rollins AM, Roth JE, Yazdanfar S, Westphal V, Bardenstein DS, Izatt JA. Real-time optical coherence tomography of the anterior segment at 1310 nm. Arch Ophthalmol 2001;119:1179–85.

15. Huang D, Swanson EA, Lin CP, Schuman JS, Stinson WG, Chang W, Hee MR, Flotte T, Gregory K, Puliafito CA, Fujimoto JG. Optical coherence tomography. Science 1991;254:1178–81.

16. Schuman JS. Spectral domain optical coherence tomography for glaucoma (an AOS thesis). Trans Am Ophthalmol Soc 2008;106:426–58.

17. Schuman JS, Pedut-Kloizman T, Hertzmark E, Hee MR, Wilkins JR, Coker JG, Puliafito CA, Fujimoto JG, Swanson EA. Reproducibility of nerve fiber layer thickness measurements using optical coherence tomography. Ophthalmology 1996;103:1889–98.

18. Blumenthal EZ, Williams JM, Weinreb RN, Girkin CA, Berry CC, Zangwill LM. Reproducibility of nerve fiber layer thickness measurements by use of optical coherence tomography. Ophthalmology 2000;107:2278–82.

19. Polito A, Del Borrello M, Isola M, Zemella N, Bandello F. Repeatability and reproducibility of fast macular thickness mapping with stratus optical coherence tomography. Arch Ophthalmol 2005;123:1330–7.

20. Paunescu LA, Schuman JS, Price LL, Stark PC, Beaton S, Ishikawa H, Wollstein G, Fujimoto JG. Reproducibility of nerve fiber thickness, macular thickness, and optic nerve head measurements using StratusOCT. Invest Ophthalmol Vis Sci 2004;45:1716–24.

21. Gonzalez-Garcia AO, Vizzeri G, Bowd C, Medeiros FA, Zangwill LM, Weinreb RN. Reproducibility of RTVue retinal nerve fiber layer thickness and optic disc measurements and agreement with Stratus optical coherence tomography measurements. Am J Ophthalmol 2009;147:1067–74.

22. Medeiros FA, Zangwill LM, Bowd C, Vessani RM, Susanna R Jr., Weinreb RN. Evaluation of retinal nerve fiber layer, optic nerve head, and macular thickness measurements for glaucoma detection using optical coherence tomography. Am J Ophthalmol 2005;139:44–55.

23. Bowd C, Zangwill LM, Berry CC, Blumenthal EZ, Vasile C, Sanchez-Galeana C, Bosworth CF, Sample PA, Weinreb RN. Detecting early glaucoma by assessment of retinal nerve fiber layer thickness and visual function. Invest Ophthalmol Vis Sci 2001;42:1993–2003.

24. Guedes V, Schuman JS, Hertzmark E, Wollstein G, Correnti A, Mancini R, Lederer D, Voskanian S, Velazquez L, Pakter HM, Pedut-Kloizman T, Fujimoto JG, Mattox C. Optical coherence tomography measurement of macular and nerve fiber layer thickness in normal and glaucomatous human eyes. Ophthalmology 2003;110:177–89.

25. Wollstein G, Schuman JS, Price LL, Aydin A, Stark PC, Hertzmark E, Lai E, Ishikawa H, Mattox C, Fujimoto JG, Paunescu LA. Optical coherence tomography longitudinal evaluation of retinal nerve fiber layer thickness in glaucoma. Arch Ophthalmol 2005;123:464–70.

26. Medeiros FA, Zangwill LM, Alencar LM, Bowd C, Sample PA, Susanna R Jr., Weinreb RN. Detection of glaucoma progression with stratus OCT retinal nerve fiber layer, optic nerve head, and macular thickness measurements. Invest Ophthalmol Vis Sci 2009;50:5741–8.

27. Leung CK, Cheung CY, Weinreb RN, Qiu K, Liu S, Li H, Xu G, Fan N, Pang CP, Tse KK, Lam DS. Evaluation of retinal nerve fiber layer progression in glaucoma: a study on optical coherence tomography guided progression analysis. Invest Ophthalmol Vis Sci 2010;51:217–22.

28. Wojtkowski M, Srinivasan V, Fujimoto JG, Ko T, Schuman JS, Kowalczyk A, Duker JS. Three-dimensional retinal imaging with high-speed ultrahigh-resolution optical coherence tomography. Ophthalmology 2005;112:1734–46.

29. Yasuno Y, Madjarova VD, Makita S, Akiba M, Morosawa A, Chong C, Sakai T, Chan KP, Itoh M, Yatagai T. Three-dimensional and high-speed swept-source optical coherence tomography for in vivo investigation of human anterior eye segments. Opt Express 2005;13:10652–64.

30. Srinivasan VJ, Wojtkowski M, Witkin AJ, Duker JS, Ko TH, Carvalho M, Schuman JS, Kowalczyk A, Fujimoto JG. High-definition and 3-dimensional imaging of macular pathologies with high-speed ultrahigh-resolution optical coherence tomography. Ophthalmology 2006;113:2054.e1–14.

31. Inoue M, Watanabe Y, Arakawa A, Sato S, Kobayashi S, Kadonosono K. Spectral-domain optical coherence tomography images of inner/outer segment junctions and macular hole surgery outcomes. Graefes Arch Clin Exp Ophthalmol 2009;247:325–30.

32. Shimozono M, Oishi A, Hata M, Kurimoto Y. Restoration of the photoreceptor outer segment and visual outcomes after macular hole closure: spectral-domain optical coherence tomography analysis. Graefes Arch Clin Exp Ophthalmol 2011;249:1469–76.

33. Kim JS, Ishikawa H, Sung KR, Xu J, Wollstein G, Bilonick RA, Gabriele ML, Kagemann L, Duker JS, Fujimoto JG, Schuman JS. Retinal nerve fibre layer thickness measurement reproducibility improved with spectral domain optical coherence tomography. Br J Ophthalmol 2009;93:1057–63.

34. Jeoung JW, Park KH, Kim TW, Khwarg SI, Kim DM. Diagnostic ability of optical coherence tomography with a normative database to detect localized retinal nerve fiber layer defects. Ophthalmology 2005;112:2157–63.

35. Vizzeri G, Balasubramanian M, Bowd C, Weinreb RN, Medeiros FA, Zangwill LM. Spectral domain-optical coherence tomography to detect localized retinal nerve fiber layer defects in glaucomatous eyes. Opt Express 2009;17:4004–18.

36. Medeiros FA, Zangwill LM, Bowd C, Weinreb RN. Comparison of the GDx VCC scanning laser polarimeter, HRT II confocal scanning laser ophthalmoscope, and stratus OCT optical coherence tomograph for the detection of glaucoma. Arch Ophthalmol 2004;122:827–37.

37. Leung CK, Chan WM, Yung WH, Ng AC, Woo J, Tsang MK, Tse RK. Comparison of macular and peripapillary measurements for the detection of glaucoma: an optical coherence tomography study. Ophthalmology 2005;112:391–400.

38. Wollstein G, Ishikawa H, Wang J, Beaton SA, Schuman JS. Comparison of three optical coherence tomography scanning areas for detection of glaucomatous damage. Am J Ophthalmol 2005;139:39–43.

39. Chang RT, Knight OJ, Feuer WJ, Budenz DL. Sensitivity and specificity of time-domain versus spectral-domain optical coherence tomography in diagnosing early to moderate glaucoma. Ophthalmology 2009;116:2294–9.

40. Leung CK, Chiu V, Weinreb RN, Liu S, Ye C, Yu M, Cheung CY, Lai G, Lam DS. Evaluation of retinal nerve fiber layer progression in glaucoma: a comparison between spectral-domain and time-domain optical coherence tomography. Ophthalmology 2011;118:1558–62.

41. Wieser W, Biedermann BR, Klein T, Eigenwillig CM, Huber R. Multi-megahertz OCT: high quality 3D imaging at 20 million A-scans and 4.5 GVoxels per second. Opt Express 2010;18:14685–704.

42. Srinivasan VJ, Adler DC, Chen Y, Gorczynska I, Huber R, Duker JS, Schuman JS, Fujimoto JG. Ultrahigh-speed optical coherence tomography for three-dimensional and en face imaging of the retina and optic nerve head. Invest Ophthalmol Vis Sci 2008;49:5103–10.

43. Sander B, Larsen M, Thrane L, Hougaard JL, Jorgensen TM. Enhanced optical coherence tomography imaging by multiple scan averaging. Br J Ophthalmol 2005;89:207–12.

44. Sakamoto A, Hangai M, Yoshimura N. Spectral-domain optical coherence tomography with multiple B-scan averaging for enhanced imaging of retinal diseases. Ophthalmology 2008;115:1071–8.

45. Potsaid B, Gorczynska I, Srinivasan VJ, Chen Y, Jiang J, Cable A, Fujimoto JG. Ultrahigh speed spectral/Fourier domain OCT ophthalmic imaging at 70,000 to 312,500 axial scans per second. Opt Express 2008;16:15149–69.

46. Fan N, Huang N, Lam DS, Leung CK. Measurement of photoreceptor layer in glaucoma: a spectral-domain optical coherence tomography study. J Ophthalmol 2011;2011:264803.

47. Grulkowski I, Gora M, Szkulmowski M, Gorczynska I, Szlag D, Marcos S, Kowalczyk A, Wojtkowski M. Anterior segment imaging with Spectral OCT system using a high-speed CMOS camera. Opt Express 2009;17:4842–58.

48. Lee EC, de Boer JF, Mujat M, Lim H, Yun SH. In vivo optical frequency domain imaging of human retina and choroid. Opt Express 2006;14:4403–11.

49. Yasuno Y, Hong Y, Makita S, Yamanari M, Akiba M, Miura M, Yatagai T. In vivo high-contrast imaging of deep posterior eye by 1-microm swept source optical coherence tomography and scattering optical coherence angiography. Opt Express 2007;15:6121–39.

50. Choma M, Sarunic M, Yang C, Izatt J. Sensitivity advantage of swept source and Fourier domain optical coherence tomography. Opt Express 2003;11:2183–9.

51. Potsaid B, Baumann B, Huang D, Barry S, Cable AE, Schuman JS, Duker JS, Fujimoto JG. Ultrahigh speed 1050 nm swept source/Fourier domain OCT retinal and anterior segment imaging at 100,000 to 400,000 axial scans per second. Opt Express 2010;18:20029–48.

52. Wolbarsht ML, Walsh AW, George G. Melanin, a unique biological absorber. Appl Opt 1981;20:2184–6.

53. Povazay B, Hermann B, Unterhuber A, Hofer B, Sattmann H, Zeiler F, Morgan JE, Falkner-Radler C, Glittenberg C, Blinder S, Drexler W. Three-dimensional optical coherence tomography at 1050 nm versus 800 nm in retinal pathologies: enhanced performance and choroidal penetration in cataract patients. J Biomed Opt 2007;12:041211.

54. Esmaeelpour M, Povazay B, Hermann B, Hofer B, Kajic V, Kapoor K, Sheen NJ, North RV, Drexler W. Three-dimensional 1060-nm OCT: choroidal thickness maps in normal subjects and improved posterior segment visualization in cataract patients. Invest Ophthalmol Vis Sci 2010;51:5260–6.

55. Povazay B, Hofer B, Torti C, Hermann B, Tumlinson AR, Esmaeelpour M, Egan CA, Bird AC, Drexler W. Impact of enhanced resolution, speed and penetration on three-dimensional retinal optical coherence tomography. Opt Express 2009;17:4134–50.

56. Yasuno Y, Miura M, Kawana K, Makita S, Sato M, Okamoto F, Yamanari M, Iwasaki T, Yatagai T, Oshika T. Visualization of sub-retinal pigment epithelium morphologies of exudative macular diseases by high-penetration optical coherence tomography. Invest Ophthalmol Vis Sci 2009;50:405–13.

57. Zhang Y, Rha J, Jonnal R, Miller D. Adaptive optics parallel spectral domain optical coherence tomography for imaging the living retina. Opt Express 2005;13:4792–811.

58. Zawadzki RJ, Jones SM, Olivier SS, Zhao M, Bower BA, Izatt JA, Choi S, Laut S, Werner JS. Adaptive-optics optical coherence tomography for high-resolution and high-speed 3D retinal in vivo imaging. Opt Express 2005;13:8532–46.

59. Zawadzki RJ, Choi SS, Jones SM, Oliver SS, Werner JS. Adaptive optics-optical coherence tomography: optimizing visualization of microscopic retinal structures in three dimensions. J Opt Soc Am (A) 2007;24:1373–83.

60. Cense B, Koperda E, Brown JM, Kocaoglu OP, Gao W, Jonnal RS, Miller DT. Volumetric retinal imaging with ultrahigh-resolution spectral-domain optical coherence tomography and adaptive optics using two broadband light sources. Opt Express 2009;17:4095–111.

61. Torti C, Povazay B, Hofer B, Unterhuber A, Carroll J, Ahnelt PK, Drexler W. Adaptive optics optical coherence tomography at 120,000 depth scans/s for non-invasive cellular phenotyping of the living human retina. Opt Express 2009;17:19382–400.

62. Wang Q, Kocaoglu OP, Cense B, Bruestle J, Jonnal RS, Gao W, Miller DT. Imaging retinal capillaries using ultrahigh-resolution optical coherence tomography and adaptive optics. Invest Ophthalmol Vis Sci 2011;52:6292–9.

63. Zawadzki RJ, Choi SS, Fuller AR, Evans JW, Hamann B, Werner JS. Cellular resolution volumetric in vivo retinal imaging with adaptive optics-optical coherence tomography. Opt Express 2009;17:4084–94.

64. Ishikawa H, Stein DM, Wollstein G, Beaton S, Fujimoto JG, Schuman JS. Macular segmentation with optical coherence tomography. Invest Ophthalmol Vis Sci 2005;46:2012–7.

65. Ishikawa H, Kim J, Friberg TR, Wollstein G, Kagemann L, Gabriele ML, Townsend KA, Sung KR, Duker JS, Fujimoto JG, Schuman JS. Three-dimensional optical coherence tomography (3D-OCT) image enhancement with segmentation-free contour modeling C-mode. Invest Ophthalmol Vis Sci 2009;50:1344–9.

66. Kagemann L, Ishikawa H, Wollstein G, Gabriele M, Schuman JS. Visualization of 3-D high speed ultrahigh resolution optical coherence tomographic data identifies structures visible in 2D frames. Opt Express 2009;17:4208–20.

67. Liu YY, Ishikawa H, Chen M, Wollstein G, Duker JS, Fujimoto JG, Schuman JS, Rehg JM. Computerized macular pathology diagnosis in spectral domain optical coherence tomography scans based on multiscale texture and shape features. Invest Ophthalmol Vis Sci 2011;52:8316–22.

68. Liu YY, Chen M, Ishikawa H, Wollstein G, Schuman JS, Rehg JM. Automated macular pathology diagnosis in retinal OCT images using multi-scale spatial pyramid and local binary patterns in texture and shape encoding. Med Image Anal 2011;15:748–59.

69. Ricco S, Chen M, Ishikawa H, Wollstein G, Schuman J. Correcting motion artifacts in retinal spectral domain optical coherence tomography via image registration. Med Image Comput Comput Assist Interv 2009;12:100–7.

70. Xu J, Ishikawa H, Wollstein G, Schuman JS. 3D OCT eye movement correction based on particle filtering. Conf Proc IEEE Eng Med Biol Soc 2010;2010:53–6.

71. Xu J, Ishikawa H, Wollstein G, Schuman JS. 3D optical coherence tomography super pixel with machine classifier analysis for glaucoma detection. Conf Proc IEEE Eng Med Biol Soc 2011;2011:3395–8.

72. Leitgeb R, Schmetterer L, Drexler W, Fercher A, Zawadzki R, Bajraszewski T. Real-time assessment of retinal blood flow with ultrafast acquisition by color Doppler Fourier domain optical coherence tomography. Opt Express 2003;11:3116–21.

73. White B, Pierce M, Nassif N, Cense B, Park B, Tearney G, Bouma B, Chen T, de Boer J. In vivo dynamic human retinal blood flow imaging using ultra-high-speed spectral domain optical coherence tomography. Opt Express 2003;11:3490–7.

74. Michaely R, Bachmann AH, Villiger ML, Blatter C, Lasser T, Leitgeb RA. Vectorial reconstruction of retinal blood flow in three dimensions measured with high resolution resonant Doppler Fourier domain optical coherence tomography. J Biomed Opt 2007;12:041213.

75. Werkmeister RM, Dragostinoff N, Pircher M, Gotzinger E, Hitzenberger CK, Leitgeb RA, Schmetterer L. Bidirectional Doppler Fourier-domain optical coherence tomography for measurement of absolute flow velocities in human retinal vessels. Opt Lett 2008;33:2967–9.

76. Wang Y, Bower BA, Izatt JA, Tan O, Huang D. Retinal blood flow measurement by circumpapillary Fourier domain Doppler optical coherence tomography. J Biomed Opt 2008;13:064003.

77. Wang Y, Fawzi A, Tan O, Gil-Flamer J, Huang D. Retinal blood flow detection in diabetic patients by Doppler Fourier domain optical coherence tomography. Opt Express 2009;17:4061–73.

78. Wang Y, Fawzi AA, Varma R, Sadun AA, Zhang X, Tan O, Izatt JA, Huang D. Pilot study of optical coherence tomography measurement of retinal blood flow in retinal and optic nerve diseases. Invest Ophthalmol Vis Sci 2011;52:840–5.

79. Hafezi F, Grimm C, Simmen BC, Wenzel A, Reme CE. Molecular ophthalmology: an update on animal models for retinal degenerations and dystrophies. Br J Ophthalmol 2000;84:922–7.

80. John SW, Smith RS, Savinova OV, Hawes NL, Chang B, Turnbull D, Davisson M, Roderick TH, Heckenlively JR. Essential iris atrophy, pigment dispersion, and glaucoma in DBA/2J mice. Invest Ophthalmol Vis Sci 1998;39:951–62.

81. Libby RT, Anderson MG, Pang IH, Robinson ZH, Savinova OV, Cosma IM, Snow A, Wilson LA, Smith RS, Clark AF, John SW. Inherited glaucoma in DBA/2J mice: pertinent disease features for studying the neurodegeneration. Vis Neurosci 2005;22:637–48.

82. Mittag TW, Danias J, Pohorenec G, Yuan HM, Burakgazi E, Chalmers-Redman R, Podos SM, Tatton WG. Retinal damage after 3 to 4 months of elevated intraocular pressure in a rat glaucoma model. Invest Ophthalmol Vis Sci 2000;41:3451–9.

83. Harwerth RS, Carter-Dawson L, Shen F, Smith EL III, Crawford ML. Ganglion cell losses underlying visual field defects from experimental glaucoma. Invest Ophthalmol Vis Sci 1999;40:2242–50.

84. Srinivasan VJ, Ko TH, Wojtkowski M, Carvalho M, Clermont A, Bursell SE, Song QH, Lem J, Duker JS, Schuman JS, Fujimoto JG. Noninvasive volumetric imaging and morphometry of the rodent retina with high-speed, ultrahigh-resolution optical coherence tomography. Invest Ophthalmol Vis Sci 2006;47:5522–8.

85. Ruggeri M, Wehbe H, Jiao S, Gregori G, Jockovich ME, Hackam A, Duan Y, Puliafito CA. In vivo three-dimensional high-resolution imaging of rodent retina with spectral-domain optical coherence tomography. Invest Ophthalmol Vis Sci 2007;48:1808–14.

86. Gabriele ML, Ishikawa H, Schuman JS, Ling Y, Bilonick RA, Kim JS, Kagemann L, Wollstein G. Optic nerve crush mice followed longitudinally with spectral domain optical coherence tomography. Invest Ophthalmol Vis Sci 2011;52:2250–4.

87. Nagata A, Higashide T, Ohkubo S, Takeda H, Sugiyama K. In vivo quantitative evaluation of the rat retinal nerve fiber layer with optical coherence tomography. Invest Ophthalmol Vis Sci 2009;50:2809–15.

88. Gabriele ML, Ishikawa H, Schuman JS, Bilonick RA, Kim J, Kagemann L, Wollstein G. Reproducibility of spectral-domain optical coherence tomography total retinal thickness measurements in mice. Invest Ophthalmol Vis Sci 2010;51:6519–23.

89. Ruggeri M, Tsechpenakis G, Jiao S, Jockovich ME, Cebulla C, Hernandez E, Murray TG, Puliafito CA. Retinal tumor imaging and volume quantification in mouse model using spectral-domain optical coherence tomography. Opt Express 2009;17:4074–83.

90. Guo L, Tsatourian V, Luong V, Podoleanu AG, Jackson DA, Fitzke FW, Cordeiro MF. En face optical coherence tomography: a new method to analyse structural changes of the optic nerve head in rat glaucoma. Br J Ophthalmol 2005;89:1210–6.

91. Strouthidis NG, Yang H, Fortune B, Downs JC, Burgoyne CF. Detection of optic nerve head neural canal opening within histomorphometric and spectral domain optical coherence tomography data sets. Invest Ophthalmol Vis Sci 2009;50:214–23.

92. Strouthidis NG, Fortune B, Yang H, Sigal IA, Burgoyne CF. Longitudinal change detected by spectral domain optical coherence tomography in the optic nerve head and peripapillary retina in experimental glaucoma. Invest Ophthalmol Vis Sci 2011;52:1206–19.

93. Geerling G, Muller M, Winter C, Hoerauf H, Oelckers S, Laqua H, Birngruber R. Intraoperative 2-dimensional optical coherence tomography as a new tool for anterior segment surgery. Arch Ophthalmol 2005;123:253–7.

94. Hayashi A, Yagou T, Nakamura T, Fujita K, Oka M, Fuchizawa C. Intraoperative changes in idiopathic macular holes by spectral-domain optical coherence tomography. Case Report Ophthalmol 2011;2:149–54.

95. Ray R, Baranano DE, Fortun JA, Schwent BJ, Cribbs BE, Bergstrom CS, Hubbard GB III, Srivastava SK. Intraoperative microscope-mounted spectral domain optical coherence tomography for evaluation of retinal anatomy during macular surgery. Ophthalmology 2011;118:2212–7.

96. Lee LB, Srivastava SK. Intraoperative spectral-domain optical coherence tomography during complex retinal detachment repair. Ophthalmic Surg Lasers Imaging 2011;42 Online:–.

97. Knecht PB, Kaufmann C, Menke MN, Watson SL, Bosch MM. Use of intraoperative fourier-domain anterior segment optical coherence tomography during descemet stripping endothelial keratoplasty. Am J Ophthalmol 2010;150:360–5.

98. Ide T, Wang J, Tao A, Leng T, Kymionis GD, O'Brien TP, Yoo SH. Intraoperative use of three-dimensional spectral-domain optical coherence tomography. Ophthalmic Surg Lasers Imaging 2010;41:250–4.

99. Galeotti J, Sajjad A, Wang B, Kagemann L, Shukla G, Siegel M, Wu B, Klatzky R, Wollstein G, Schuman JS, Stetten G. The OCT penlight: in-situ image guidance for microsurgery. In: Conference on Medical Imaging 2010—Visualization, Image-Guided Procedures, and Modeling Location, San Diego, CA, February 14–16, 2010. SPIE Vol. 7625. Bellingham, WA: SPIE Press; 2010:762502.

100. Tao YK, Ehlers JP, Toth CA, Izatt JA. Intraoperative spectral domain optical coherence tomography for vitreoretinal surgery. Opt Lett 2010;35:3315–7.

optical coherence tomography; OCT; image processing

Cited By:

This article has been cited 2 time(s).

Cell and Tissue Research
Optical properties of retinal tissue and the potential of adaptive optics to visualize retinal ganglion cells in vivo
Prasse, M; Rauscher, FG; Wiedemann, P; Reichenbach, A; Francke, M
Cell and Tissue Research, 353(2): 269-278.
10.1007/s00441-013-1602-1
CrossRef
Plos One
Three-Dimensional Spectral-Domain Optical Coherence Tomography Data Analysis for Glaucoma Detection
Xu, J; Ishikawa, H; Wollstein, G; Bilonick, RA; Folio, LS; Nadler, Z; Kagemann, L; Schuman, JS
Plos One, 8(2): -.
ARTN e55476
CrossRef
Back to Top | Article Outline

© 2012 American Academy of Optometry

Login

Search for Similar Articles
You may search for similar articles that contain these same keywords or you may modify the keyword list to augment your search.