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. Author manuscript; available in PMC: 2021 Mar 28.
Published in final edited form as: JAMA Ophthalmol. 2021 Jan 1;139(1):113–118. doi: 10.1001/jamaophthalmol.2020.4994

Development, Validation, and Innovation in Ophthalmic Laser-Based Imaging

Report From a US Food and Drug Administration–Cosponsored Forum

Frank Brodie 1, Michael Repka 1, Stephen Allan Burns 1, S Grace Prakalapakorn 1, Christie Morse 1, Joel S Schuman 1, Michael R Duenas 1, Natalie Afshari 1, John S Pollack 1, Jennifer E Thorne 1, Albert Vitale 1, H Nida Sen 1, David Myung 1, Mark S Blumenkranz 1, Elmer Tu 1, Daniel X Hammer 1, Michelle Tarver 1, Bradley Cunningham 1, Larry Kagemann 1, SriniVas Sadda 1, David Sarraf 1, Glenn J Jaffe 1, Malvina Eydelman 1
PMCID: PMC8005310  NIHMSID: NIHMS1674632  PMID: 33211074

Abstract

In April 2019, the US Food and Drug Administration, in conjunction with 11 professional ophthalmic, vision science, and optometric societies, convened a forum on laser-based imaging. The forum brought together the Food and Drug Administration, clinicians, researchers, industry members, and other stakeholders to stimulate innovation and ensure that patients in the US are the first in the world to have access to high-quality, safe, and effective medical devices. This conference focused on the technology, clinical applications, regulatory issues, and reimbursement issues surrounding innovative ocular imaging modalities. Furthermore, the emerging role of artificial intelligence in ophthalmic imaging was reviewed. This article summarizes the presentations, discussion, and future directions.


The advent of laser-based imaging, including scanning laser ophthalmoscopy (SLO) and optical coherence tomography (OCT, including time-domain and spectral-domain OCT using a superluminescent diode and swept-source OCT using a laser), is profoundly affecting the evaluation of patients in every eye care discipline. These technologies are evolving at a rapid pace, and clinicians, researchers, regulators, and industry members are working to determine the best ways to develop, evaluate, and translate cutting-edge imaging technology into clinical use. In April 2019, the US Food and Drug Administration (FDA), in conjunction with 11 professional societies (the American Academy of Ophthalmology, the American Academy of Optometry, the American Association for Pediatric Ophthalmology and Strabismus, the American Optometric Association, the American Society for Cataract and Refractive Surgery, the American Society of Retinal Specialists, the American Glaucoma Society, the American Uveitis Society, the Cornea Society, the Retina Society, and the Byers Eye Institute at Stanford University), convened the Forum on Laser-Based Imaging. This multi-disciplinary workshop focused on the regulatory and reimbursement issues surrounding laser-based imaging modalities, such as OCT and adaptive optics (AO), as well as the emerging role of artificial intelligence in ophthalmic imaging. Malvina Eydelman, MD, director of the Office of Ophthalmic, Anesthesia, Respiratory, ENT (Ear, Nose, and Throat), and Dental Devices in the Office of Product Evaluation and Quality at the FDA remarked that “proactively working with stakeholders in the medical device ecosystem to solve both shared problems and problems unique to others allows [the FDA] to serve the American public better and to achieve our vision [to] collaborate to address critical public health needs and bridge scientific gaps, thereby stimulating innovation in the products we regulate.” The goal of the workshop was to bring together stakeholders, including clinicians, researchers, industry members, and the FDA, to discuss approaches to shorten the time from medical device conception to market release, stimulate innovation, and ensure that patients in the US are the first in the world to have access to high-quality, safe, and effective medical devices. This article summarizes the workshop discussions and reviews the basic technology, clinical applications, limitations, and FDA comments for the innovative ocular imaging modalities discussed at this conference.

Overview Of OCT Technology

Optical coherence tomography is an invaluable tool in the diagnosis and management of ocular disease because of its ability to help clinicians visualize the layers of ocular tissue, particularly the retina, in a cross-sectional, depth-resolved manner. Worldwide, approximately 30 million OCT scans for ophthalmic imaging are performed annually.1 Based on the principles of the Michelson interferometer, the first OCT device was cleared for marketing in the US by the FDA in 1994 (510[k] number, K944523). The initial iteration was a time-domain OCT system that relied on a mechanically moving reference mirror to sample reflectance at different tissue depths. The development of a spectral-domain OCT eliminated the need for mechanical movement of the reference mirror and provided sample reflectance at every voxel within an A-scan to be made simultaneously, yielding a 50-fold to 100-fold increase in scan rates. The most recent–generation, swept-source OCT rapidly scans a narrow frequency line across a larger range of frequencies, enabling even greater scan rates.

From the first clearance in 1994 to the present day, OCT imaging devices are cleared for sale in the US via the premarket notification pathway (known as a 510[k] submission based on the procedures described under Section 510[k] of the Federal Food, Drug, and Cosmetic Act), which is a process that determines substantial equivalence to a legally marketed predicate device. Bradley Cunningham, RAC, associate director of the Office of Ophthalmic, Anesthesia, Respiratory, ENT and Dental Devices in the Office of Product Evaluation and Quality of the FDA noted that a device can be substantially equivalent if it “has the same intended use but different technological characteristics…so long as those new technological differences don’t raise new questions of safety and effectiveness and that those technological differences can be addressed through some type of performance testing or rationale.” Under the direction of Commander Cunningham, the FDA has developed and implemented a pilot program2 for assessment and premarket evaluation of OCT devices. Based on this pilot program, the FDA provides participants with recommendations for bench, nonclinical, and clinical testing, as well as relevant safety information to provide more clarity and consistency in the regulatory process surrounding OCT 510(k) submissions. Commander Cunningham described the FDA’s goal of OCT pilot program “to improve consistency and predictability of the 510(k) process, to reduce the total time to decision, and to increase the collaboration between FDA and stakeholders.”

Clinical Applications Of OCT

Mitchell Weikert, MD, MS, discussed 4 main applications of anterior segment OCT technology: clinical imaging, biometrics, biomechanical assessment, and intraoperative imaging. Optical coherence tomography can help characterize anterior segment anatomy and pathology, information that may be applied clinically for a variety of applications. Weikert provided examples of the many applications of OCT technology, both for diagnosis and to possibly determine whether a patient is suitable for a procedure. For example, OCT results are associated with the outcome of lens removal on subsequent intraocular pressure decrease3 and can even provide a more timely evaluation of ocular surface neoplasia.4,5 Also, evaluation of the biomechanical properties of the cornea may be possible with OCT elastography,6 and recent data suggest that evaluation of epithelial thickness is associated with post–laser in-situ keratomileusis ectasia.7 Finally, the introduction of intraoperative OCT (iOCT) has provided unique insights in challenging corneal transplant cases.8 For example, in the Determination of Feasibility of Intraoperative Spectral Domain Microscope Combined/Integrated OCT Visualization During en Face Retinal and Ophthalmic Surgery (DISCOVER) study9 of 62 corneal transplants, iOCT was shown to alter surgeon decision-making in approximately 40% of cases. Additionally, DISCOVER authors concluded that their study10 showed lower rates of complications and decreased operative time using iOCT.

Optical coherence tomography has had a tremendous influence on the diagnosis and management of glaucoma. Structural measurements of the optic nerve head, retinal nerve fiber layer, and ganglion cell layer are quantitative metrics associated with glaucomatous damage.1113 Newer systems evaluate the anterior segment and angle structures to provide prognostic information on intraocular pressure changes with surgical intervention3 and insight into aqueous outflow pathways.1417 Additionally, OCT provides structural and anatomical information that may lead to earlier detection of glaucoma, as well as monitoring progression over time.18

In the posterior segment, the influence of OCT is difficult to over-state. While early systems provided basic evaluation of retinal morphology,19 more advanced technology with rapid imaging and higher resolution provide detailed representations of the retina, choroid, and vitreous microstructures. Optical coherence tomography technology has revolutionized the evaluation and management of prevalent vitreoretinal diseases and enhanced our understanding and approach to other vitreoretinal conditions, for which OCT images can detect nanoscale anatomy and structural changes. In addition, OCT imaging is the gold standard for the detection of both intraretinal and subretinal fluid and the evaluation of the response to therapy. It offers a noninvasive method for assessing clinically significant neovascular activity in age-related macular degeneration20 and detecting and managing diabetic macular edema,21 leading to targeted treatment in both entities.

Emerging OCT Technologies

Beyond advances in resolution and scan speed, additional imaging modalities using OCT technology have been developed and are starting to arrive in clinical practice. For example, OCT angiography(OCTA) relies on a novel scanning algorithm with repeated B-scans to separate static and dynamic tissue scatter using speckle decorrelation—in effect, using motion as a contrast agent—to depict high-resolution, depth-resolved blood flow in the retina and choroid.22,23 Richard Spaide, MD, reviewed ultra-high-resolution images of the retinal vasculature and choroid produced by OCTA and discussed this application to evaluate diseases such as diabetic retinopathy24 and neovascular age-related macular degeneration.25,26

While OCTA provides visualization of flow, it does not provide direct information on oxygenation of the vascular tissue. The research group of Joel Schuman, MD, was the first (to our knowledge) to evaluate blood oxygen saturation using OCT spectroscopy.27 However, the near-infrared spectrum yields low signal-to-noise ratios and is not optimal for these measurements. Visible-light OCT refers to conventional OCT using light sources in the visible range. Applying the principles of spectroscopy and known absorption properties of hemoglobin, Schuman discussed using visible-light OCT to evaluate with very high resolution the oxygen saturation of the various layers of the eye attributable to the known absorption spectrum of hemoglobin.28 Used in conjunction with other technologies, such as OCTA or AO-SLO, structure and function can be evaluated simultaneously with visible-light OCT, providing powerful new insights into the pathology of eye disease.28,29

In the operating room, iOCT is evolving to include real-time volume-rendered imaging (4-dimensional OCT), which allows the surgeon to visualize the surgery at an offset, providing an additional intraoperative perspective.30,31 With microscope integration of this technology (microscope-integrated OCT), the surgeon is able to see the action of surgical instruments on tissues from various perspectives. In the era of subretinal drug delivery, this technique can help target and titrate drug dosing.32

Finally, artificial intelligence is being explored in conjunction with OCT in the anterior and posterior segments. Michael Abramoff, MD, PhD, described using OCT and artificial intelligence to anticipate visual fields in glaucoma and aid in diagnosis.33 Felipe Medeiros, MD, PhD, discussed use of artificial intelligence segmentation of anterior segment OCT images and showing improved grading reproducibility compared with manual segmentation. He described a study by Fu et al34 in which anterior segment OCT images were evaluated to diagnose angle closure; using deep learning (a subtype of artificial intelligence) to analyze the images proved to be highly accurate compared with gonioscopy. To close the session, Alastair Dennison, MD, PhD, discussed the progress made in automation of grading anterior chamber cell in uveitis using deep learning algorithms.35,36

Current Challenges In Use Of OCT Technology

The value of OCT and its importance in clinical trials was highlighted by SriniVas Sadda, MD, who noted that quantitative metrics derived from OCT allow for more detailed analysis. However, Sadda noted these measurements require accuracy and precision to be useful and reliable. Clinical validation of the accuracy of OCTA, for instance, has come from other imaging modalities, such as fluorescein and indocyanine green angiography, as well as histology, although histology is not devoid of artifact and can be challenging to interpret in some structures (eg, the choroid).37 Applications that span multiple imaging modalities pose additional challenges with respect to resolution and fidelity between modalities. Further clinical validation of measurement accuracy for OCT technologies can come from comparisons with other planar imaging modalities and known dimensions of intraocular implants, which can serve as intraocular rulers to provide gold standard measurements. However, validation using these types of en face measurements from OCT still relies on accurate segmentation of the retinal layers, which can be challenging, especially with pathology disrupting the normal retinal architecture.

In an effort to generate device performance metrics, Anant Agrawal, PhD, from the Office of Science and Engineering Laboratories at the FDA, discussed the use of a phantom, which he defined as an object with “known physical properties of the tissue of interest, the geometry, the dimensions, [and] the optical scattering and absorption characteristics of the tissue…[a] model with highly controlled properties, and [in] this way, you can do tissue-relevant performance characterization of an imaging device.” The phantom may allow for comparisons of performance between devices and modalities, as well as tracking performance over time. In particular, many of the panelists supported using phantoms to aid in standardization between multiple devices used by different sites participating in multicenter trials. However, the panelists cautioned that a device’s performance with a phantom could not be equated with its performance in a clinical setting and development of clinically accurate phantoms to simulate complex structures, such as the photoreceptor layer and other retinal layers, remains a challenge.38,39

To encourage development of phantoms and other tools for the validation and regulatory process, the FDA has developed the Medical Device Development Tools(MDDT) program. Captain Hilda Scharen, MSc, director of the MDDT program at the FDA, defined an MDDT as “a method, material, or measurement used to assess the effectiveness, safety, or performance of a medical device…[and] a scientifically validated tool qualified for a specific context of use…to use in device development and to support regulatory decision-making.” Captain Scharen noted that once an MDDT is qualified by the FDA, it can be used in the development and regulatory review process without having to reestablish its utility within the appropriate context of use.40

Beyond the issues of accuracy and precision, Yasmin Bradfield, MD, highlighted the importance of understanding normal variance across age, race, and sex, in addition to the environmental variance attributable to lighting conditions (which affect pupil dilation) and device variance from differences in both hardware and software, which has been shown in early reproducibility studies.41,42 Validation of the measurements can be achieved with alternate imaging modalities, such as ultrasound biomicroscopy43 and histopathology.44

Nadia Waheed, MD, noted that similar challenges exist within OCTA systems. She described significant variability when vessel density was measured on different OCTA devices, but good repeatability within an individual device.45 Issues of validation are also important in the development of visible-light OCT. Vivek Srinivasan, PhD, discussed the benefit of using animal and dye studies to validate the oxygenation measurements of visible-light OCT and noted that while these studies cannot provide precise validation at the target vessel, they offer a so-called sanity check to make sure the technology is behaving as expected.

A nonclinical challenge in the development of any new technology is maximizing commercial viability to offset the costs of development. Michael Repka, MD, and Rochelle Fink, MD, JD, discussed the mechanisms for imaging reimbursement of these technologies by Medicare. They both noted the challenge of obtaining increased reimbursements for advances in imaging, since the drivers for reimbursement are primarily physician effort and materials consumed—neither of which are increased directly by these new technologies. Moreover, the goal of many technologies, such as artificial intelligence, is to decrease physician effort and maximize efficiency. While reimbursement includes a component for capital expenses, it assumes fractional use and multiyear amortization, so the per-patient reimbursement remains quite low, even for an expensive piece of equipment, such as an OCT machine.

Adaptive Optics

While not a standalone laser-based imaging technology, adaptive optics (AO) is frequently used in conjunction with laser-based imaging modalities, such as OCT and SLO. Adaptive optics is a technique for dynamic sensing and correction of the optical aberrations in an individual’s eye (as well as those that arise in an imaging system itself). Alfredo Dubra, PhD, highlighted that AO is essentially an agnostic technology, because it can be applied to a variety of imaging modalities to improve transverse resolution, yielding vast improvements in the resolution of microscopic structures, such as parafoveal cones, and possibly providing more insight into subtle clinical findings associated with disease diagnosis and progression.

Jacque Duncan, MD, indicated that to evaluate novel therapies for slow-moving diseases, such as retinal degeneration, careful objective assessment is needed. Unfortunately, metrics such as visual acuity are subjective and prone to confounding by cataract and tear-film abnormalities. She presented several AO-SLO studies that tracked disease progression by evaluating changes in the cone photoreceptor mosaic and noted that cone spacing and regularity have been correlated with photoreceptor function.46 The subtle, cellular-level data gathered from the addition of AO can provide critical information on changes in retinal disease, ranging from rare retinal dystrophies47 to prevalent conditions, such as age-related macular degeneration.48 Moreover, AO-SLO can be coupled with other techniques, such as microperimetry, to measure both structure and function at the cellular level.49 Austin Roorda, PhD, concluded, “The cellular-level access that we get with AO drives the paradigm shift in how we use ophthalmoscopy to study eye disease. The systems that measure structure and function on the cellular scale continue to yield new results.”

Jessica Morgan, PhD, discussed the issues of accuracy that arose with the application of OCT early in the course of disease. She noted that many in the field of AO argue that the technology provides the opportunity to track disease progression and treatment response, but she cautioned that researchers also need “to take into account the limits of things like repeatability, reproducibility, and accuracy in our measurements…to understand how much disease progression, for instance, needs to occur before we can know that we’re outside of our measurement error.” Further challenges of this system include the limited scan area and the long acquisition times.

However, because there is not a legally marketed AO system for clinical use, AO remains, for now, in the vision research domain. Larry Kagemann, RAC, of the Division of Ophthalmic Devices in the Office of Ophthalmic, Anesthesia, Respiratory, ENT, and Dental Devices at the FDA, noted that there is no regulatory definition of AO. Kagemann also noted that, as with other imaging modalities, FDA evaluation of effectiveness of imaging systems with AO will include an assessment of AO-derived images, and the FDA is actively developing phantoms to assist in this evaluation. Agrawal discussed an active collaboration between the FDA and the National Eye Institute to develop a novel cone-spacing phantom to validate AO-assisted measurements.

Another crucial issue in the AO approval process is safety. The panelists agreed that the American National Safety Institute (ANSI) provided guidance on issues, such as radiation exposure from light, and that light safety for AO would ultimately rely on the underlying imaging technology (eg, SLO, OCT). However, as Jennifer Hunter, PhD, noted, some assumptions in the ANSI standards may not hold for AO. For example, the ANSI standard assumes aberrations will limit the retinal spot size to 30 μm, while AO systems regularly achieve spots sizes less than 5 μm. Also, ANSI assumes natural eye movement as a form of injury protection, but research AO systems often use high-precision eye tracking, which could overcome this protective mechanism. The AO session panel agreed that further work is needed to develop clear safety standards for AO technology.

Conclusions

Over the last 25 years, ophthalmic laser-based imaging has undergone a dramatic evolution. It has changed the diagnosis, management, and understanding of eye disease today, and with emerging technologies both in the clinical and research settings, it promises to deepen our knowledge and improve the care of patients living with eye disease. As with the development of any new technology, critical questions regarding accuracy, validation, and safety emerge for researchers, clinicians, industry, and regulators alike. This workshop served as a forum to bring key stakeholders together to discuss the direction and challenges faced in this evolving field and foster further innovation of these important technologies.50

Funding/Support:

The American Academy of Ophthalmology, the American Academy of Optometry, the American Association for Pediatric Ophthalmology and Strabismus, the American Optometric Association, the American Society for Cataract and Refractive Surgery, the American Society of Retinal Specialists, the American Glaucoma Society, the American Uveitis Society, the Cornea Society, and the Retina Society, as well as the Byers Eye Institute at Stanford University all contributed equally to the funding of the workshop. The development of this article was unfunded.

Role of the Funder/Sponsor: The funders of the forum had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; and decision to submit the manuscript for publication.

Footnotes

Publisher's Disclaimer: Disclaimer: This article reflects the views and discussion of the forum panelists and should not be construed to represent the US Food and Drug Administration’s views or policies.

Conflict of Interest Disclosures: Dr Pollack reported serving as a consultant and board member for Notal Vision, as well as owning stock options in Notal Vision. Dr Sarraf reported grants from Amgen, Genentech, and Regeneron; personal fees from Bayer and Novartis; nonfinancial support (research equipment grants) from Heidelberg and Topcon; and consultant fees, research equipment grants, and speaker fees from Optovue outside the submitted work. Dr Schuman report serving as a consultant/advisor to Aerie Pharmaceuticals Inc, Ocugenix, Ocular Therapeutix Inc, Opticient, and SLACK Incorporated; receiving grants from BrightFocus Foundation National Eye Institute; receiving patents or royalties from Carl Zeiss Meditec and Ocugenix; and being an equity owner of Ocular Therapeutix, Inc. Dr Brodie reported a patent pending to peripheral retinal OCT. Dr Repka reported serving as medical director for government affairs at the American Academy of Ophthalmology, interacting in that role with US Food and Drug Administration officials. Dr Prakalapakorn reported nonfinancial support from American Association for Pediatric Ophthalmology and Strabismus during the conduct of the study. Dr Schuman reported personal fees from Carl Zeiss Meditec outside the submitted work; in addition, Dr Schuman had patents to 9,514,513, 7,992,999, 10,575,723 B2, 8,831,304, US 8,184.885 B2, 8,712,505 B2, US 8,911,089 B2, US 10,136,808 B2, US 9,844,315 B2, 5,459,570, and 5,321,501 issued, as well as a patent to US 2018/0158182 A1 pending. Dr Thorne reported personal fees from AbbVie and Gilead and grants from Santen, the National Eye Institute, and Research to Prevent Blindness outside the submitted work. Dr Blumenkranz reported being health director with associated equity interest at Verana outside the submitted work; in addition, Dr Blumenkranz had a patent issued as a coauthor of Stanford University smartphone imaging (property of Stanford University). Dr Sadda reported personal fees and nonfinancial support from Heidelberg, Nidek, Carl Zeiss Meditec, Optos, and Centervue; nonfinancial support from Topcon; and personal fees from Allergan, Genentech/Roche, Regeneron, Novartis, and Merck outside the submitted work. No other disclosures were reported.

Meeting Presentations: This article is based on presentations and discussions from the Forum on Laser-Based Imaging; April 8, 2019; Silver Spring, Maryland.

REFERENCES

  • 1.Fujimoto J, Swanson E. The development, commercialization, and impact of optical coherence tomography. Invest Ophthalmol Vis Sci. 2016;57(9): OCT1–OCT13. doi: 10.1167/iovs.16-19963 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 2.Food and Drug Administration. Fostering medical innovation: voluntary pilot program to streamline review of premarket notification (510(k)) submissions for ophthalmic optical coherence tomography devices. Published October 23, 2020. Accessed October 14, 2020. https://www.federalregister.gov/documents/2018/10/23/2018-23059/fostering-medical-innovation-voluntary-pilot-program-to-streamline-review-of-premarket-notification
  • 3.Masis Solano M, Lin SC. Cataract, phacoemulsification and intraocular pressure: is the anterior segment anatomy the missing piece of the puzzle? Prog Retin Eye Res. 2018;64:77–83. doi: 10.1016/j.preteyeres.2018.01.003 [DOI] [PubMed] [Google Scholar]
  • 4.Nanji AA, Mercado C, Galor A, Dubovy S, Karp CL. Updates in ocular surface tumor diagnostics. Int Ophthalmol Clin. 2017;57(3):47–62. doi: 10.1097/IIO.0000000000000174 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 5.Venkateswaran N, Galor A, Wang J, Karp CL. Optical coherence tomography for ocular surface and corneal diseases: a review. Eye Vis (Lond). 2018;5(1):13. doi: 10.1186/s40662-018-0107-0 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 6.De Stefano VS, Ford MR, Seven I, Dupps WJ Jr. Live human assessment of depth-dependent corneal displacements with swept-source optical coherence elastography. PLoS One. 2018;13(12):e0209480. doi: 10.1371/journal.pone.0209480 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 7.Li Y, Chamberlain W, Tan O, Brass R, Weiss JL, Huang D. Subclinical keratoconus detection by pattern analysis of corneal and epithelial thickness maps with optical coherence tomography. J Cataract Refract Surg. 2016;42(2):284–295. doi: 10.1016/j.jcrs.2015.09.021 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 8.Pasricha ND, Shieh C, Carrasco-Zevallos OM, et al. Real-time microscope-integrated OCT to improve visualization in DSAEK for advanced bullous keratopathy. Cornea. 2015;34(12):1606–1610. doi: 10.1097/ICO.0000000000000661 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 9.Ehlers JP, Goshe J, Dupps WJ, et al. Determination of feasibility and utility of microscope-integrated optical coherence tomography during ophthalmic surgery: the DISCOVER study RESCAN results. JAMA Ophthalmol. 2015;133(10):1124–1132. doi: 10.1001/jamaophthalmol.2015.2376 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 10.Patel AS, Goshe JM, Srivastava SK, Ehlers JP. Intraoperative optical coherence tomography-assisted descemet membrane endothelial keratoplasty in the DISCOVER study: first 100 cases. Am J Ophthalmol. 2020;210:167–173. doi: 10.1016/j.ajo.2019.09.018 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 11.Schuman JS, Hee MR, Puliafito CA, et al. Quantification of nerve fiber layer thickness in normal and glaucomatous eyes using optical coherence tomography. Arch Ophthalmol. 1995;113 (5):586–596. doi: 10.1001/archopht.1995.01100050054031 [DOI] [PubMed] [Google Scholar]
  • 12.Pieroth L, Schuman JS, Hertzmark E, et al. Evaluation of focal defects of the nerve fiber layer using optical coherence tomography. Ophthalmology. 1999;106(3):570–579. doi: 10.1016/S0161-6420(99)90118-5 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 13.Tan O, Chopra V, Lu AT-H, et al. Detection of macular ganglion cell loss in glaucoma by Fourier-domain optical coherence tomography. Ophthalmology. 2009;116(12):2305–14.e1, 2. doi: 10.1016/j.ophtha.2009.05.025 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 14.Kagemann L, Wollstein G, Ishikawa H, et al. 3D visualization of aqueous humor outflow structures in-situ in humans. Exp Eye Res. 2011;93(3):308–315. doi: 10.1016/j.exer.2011.03.019 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 15.Kagemann L, Wollstein G, Ishikawa H, et al. Visualization of the conventional outflow pathway in the living human eye. Ophthalmology. 2012;119(8):1563–1568. doi: 10.1016/j.ophtha.2012.02.032 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 16.Pant AD, Kagemann L, Schuman JS, Sigal IA, Amini R. An imaged-based inverse finite element method to determine in-vivo mechanical properties of the human trabecular meshwork. J Model Ophthalmol. 2017;1(3):100–111. [PMC free article] [PubMed] [Google Scholar]
  • 17.Moroi SE, Reed DM, Sanders DS, et al. Precision medicine to prevent glaucoma-related blindness. Curr Opin Ophthalmol. 2019;30(3):187–198. doi: 10.1097/ICU.0000000000000564 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 18.Suda K, Akagi T, Nakanishi H, et al. Evaluation of structure-function relationships in longitudinal changes of glaucoma using the spectralis OCT follow-up mode. Sci Rep. 2018;8(1):17158. doi: 10.1038/s41598-018-35419-y [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 19.Huang D, Swanson EA, Lin CP, et al. Optical coherence tomography. Science. 1991;254(5035): 1178–1181. doi: 10.1126/science.1957169 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 20.Khurana RN, Hill L, Ghanekar A, Gune S. Agreement of spectral-domain OCT with fluorescein leakage in neovascular age-related macular degeneration: post hoc analysis of the HARBOR study. Ophthalmol Retina. 2020;S2468–6530(20)30169-X. Published online April, 2020. doi: 10.1016/j.oret.2020.04.016 [DOI] [PubMed] [Google Scholar]
  • 21.Elman MJ, Aiello LP, Beck RW, et al. ; Diabetic Retinopathy Clinical Research Network. Randomized trial evaluating ranibizumab plus prompt or deferred laser or triamcinolone plus prompt laser for diabetic macular edema. Ophthalmology. 2010;117(6):1064–1077.e35. doi: 10.1016/j.ophtha.2010.02.031 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 22.Schwartz DM, Fingler J, Kim DY, et al. Phase-variance optical coherence tomography: a technique for noninvasive angiography. Ophthalmology. 2014;121(1):180–187. doi: 10.1016/j.ophtha.2013.09.002 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 23.Gao SS, Jia Y, Zhang M, et al. Optical coherence tomography angiography. Invest Ophthalmol Vis Sci. 2016;57(9):OCT27–OCT36. doi: 10.1167/iovs.15-19043 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 24.Liu G, Xu D, Wang F. New insights into diabetic retinopathy by OCT angiography. Diabetes Res Clin Pract. 2018;142:243–253. doi: 10.1016/j.diabres.2018.05.043 [DOI] [PubMed] [Google Scholar]
  • 25.Lindner M, Fang PP, Steinberg JS, et al. OCT angiography-based detection and quantification of the neovascular network in exudative AMD. Invest Ophthalmol Vis Sci. 2016;57(14):6342–6348. doi: 10.1167/iovs.16-19741 [DOI] [PubMed] [Google Scholar]
  • 26.Jia Y, Bailey ST, Wilson DJ, et al. Quantitative optical coherence tomography angiography of choroidal neovascularization in age-related macular degeneration. Ophthalmology. 2014;121(7):1435–1444. doi: 10.1016/j.ophtha.2014.01.034 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 27.Kagemann L, Wollstein G, Wojtkowski M, et al. Spectral oximetry assessed with high-speed ultra-high-resolution optical coherence tomography. J Biomed Opt. 2007;12(4):041212. doi: 10.1117/1.2772655 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 28.Nesper PL, Soetikno BT, Zhang HF, Fawzi AA. OCT angiography and visible-light OCT in diabetic retinopathy. Vision Res. 2017;139:191–203. doi: 10.1016/j.visres.2017.05.006 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 29.Rossi EA, Granger CE, Sharma R, et al. Imaging individual neurons in the retinal ganglion cell layer of the living eye. Proc Natl Acad Sci U S A. 2017;114(3):586–591. doi: 10.1073/pnas.1613445114 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 30.Carrasco-Zevallos OM, Keller B, Viehland C, et al. Live volumetric (4D) visualization and guidance of in vivo human ophthalmic surgery with intraoperative optical coherence tomography. Sci Rep. 2016;6:31689. doi: 10.1038/srep31689 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 31.Seider MI, Carrasco-Zevallos OM, Gunther R, et al. Real-time volumetric imaging of vitreoretinal surgery with a prototype microscope-integrated swept-source OCT device. Ophthalmol Retina. 2018;2(5):401–410. doi: 10.1016/j.oret.2017.08.023 [DOI] [PubMed] [Google Scholar]
  • 32.Hsu ST, Gabr H, Viehland C, et al. Volumetric measurement of subretinal blebs using microscope-integrated optical coherence tomography. Transl Vis Sci Technol. 2018;7(2):19. doi: 10.1167/tvst.7.2.19 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 33.Guo Z, Kwon YH, Lee K, et al. Optical coherence tomography analysis based prediction of humphrey 24–2 visual field thresholds in patients with glaucoma. Invest Ophthalmol Vis Sci. 2017;58(10):3975–3985. doi: 10.1167/iovs.17-21832 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 34.Fu H, Baskaran M, Xu Y, et al. A deep learning system for automated angle-closure detection in anterior segment optical coherence tomography images. Am J Ophthalmol. 2019;203:37–45. doi: 10.1016/j.ajo.2019.02.028 [DOI] [PubMed] [Google Scholar]
  • 35.Choi WJ, Pepple KL, Wang RK. Automated three-dimensional cell counting method for grading uveitis of rodent eye in vivo with optical coherence tomography. J Biophotonics. 2018;11(9):e201800140. doi: 10.1002/jbio.201800140 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 36.Sharma S, Lowder CY, Vasanji A, Baynes K, Kaiser PK, Srivastava SK. Automated analysis of anterior chamber inflammation by spectral-domain optical coherence tomography. Ophthalmology. 2015;122(7):1464–1470. doi: 10.1016/j.ophtha.2015.02.032 [DOI] [PubMed] [Google Scholar]
  • 37.Spaide RF, Klancnik JM Jr, Cooney MJ. Retinal vascular layers imaged by fluorescein angiography and optical coherence tomography angiography. JAMA Ophthalmol. 2015;133(1):45–50. doi: 10.1001/jamaophthalmol.2014.3616 [DOI] [PubMed] [Google Scholar]
  • 38.Kedia N, Liu Z, Sochol RD, Tam J, Hammer DX, Agrawal A. 3-D printed photoreceptor phantoms for evaluating lateral resolution of adaptive optics imaging systems. Opt Lett. 2019;44(7):1825–1828. doi: 10.1364/OL.44.001825 [DOI] [PubMed] [Google Scholar]
  • 39.Baxi J, Calhoun W, Sepah YJ, et al. Retina-simulating phantom for optical coherence tomography. J Biomed Opt. 2014;19(2):21106. doi: 10.1117/1.JBO.19.2.021106 [DOI] [PubMed] [Google Scholar]
  • 40.United States Food and Drug Administration. Qualification of medical device development tools: guidance for industry, tool developers, and food and drug administration staff. Published August 10, 2017. Accessed September 13, 2020. https://www.fda.gov/media/87134/download
  • 41.Chansangpetch S, Nguyen A, Mora M, et al. Agreement of anterior segment parameters obtained from swept-source Fourier-domain and time-domain anterior segment optical coherence tomography. Invest Ophthalmol Vis Sci. 2018;59(3): 1554–1561. doi: 10.1167/iovs.17-23574 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 42.Xu BY, Mai DD, Penteado RC, Saunders L, Weinreb RN. Reproducibility and agreement of anterior segment parameter measurements obtained using the CASIA2 and Spectralis OCT2 optical coherence tomography devices. J Glaucoma. 2017;26(11):974–979. doi: 10.1097/IJG.0000000000000788 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 43.Wang D, Pekmezci M, Basham RP, He M, Seider MI, Lin SC. Comparison of different modes in optical coherence tomography and ultrasound biomicroscopy in anterior chamber angle assessment. J Glaucoma. 2009;18(6):472–478. doi: 10.1097/IJG.0b013e31818fb41d [DOI] [PubMed] [Google Scholar]
  • 44.Crowell EL, Baker L, Chuang AZ, et al. Characterizing anterior segment OCT angle landmarks of the trabecular meshwork complex. Ophthalmology. 2018;125(7):994–1002. doi: 10.1016/j.ophtha.2018.01.018 [DOI] [PubMed] [Google Scholar]
  • 45.Arya M, Rebhun CB, Alibhai AY, et al. Parafoveal retinal vessel density assessment by optical coherence tomography angiography in healthy eyes. Ophthalmic Surg Lasers Imaging Retina. 2018; 49(10):S5–S17. doi: 10.3928/23258160-20180814-02 [DOI] [PubMed] [Google Scholar]
  • 46.Foote KG, Loumou P, Griffin S, et al. Relationship between foveal cone structure and visual acuity measured with adaptive optics scanning laser ophthalmoscopy in retinal degeneration. Invest Ophthalmol Vis Sci. 2018;59(8):3385–3393. doi: 10.1167/iovs.17-23708 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 47.Georgiou M, Kalitzeos A, Patterson EJ, Dubra A, Carroll J, Michaelides M. Adaptive optics imaging of inherited retinal diseases. Br J Ophthalmol. 2018; 102(8):1028–1035. doi: 10.1136/bjophthalmol-2017-311328 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 48.Qin J, Rinella N, Zhang Q, et al. OCT angiography and cone photoreceptor imaging in geographic atrophy. Invest Ophthalmol Vis Sci. 2018;59(15):5985–5992. doi: 10.1167/iovs.18-25032 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 49.Foote KG, De la Huerta I, Gustafson K, et al. Cone spacing correlates with retinal thickness and microperimetry in patients with inherited retinal degenerations. Invest Ophthalmol Vis Sci. 2019;60(4):1234–1243. doi: 10.1167/iovs.18-25688 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 50.Center For Organizational Management. Forum on Laser-Based Imaging. Published 2019. Accessed January 17, 2020. http://www.cfom.info/meetings/LaserBasedImaging/index.html

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