The Asia-Pacific Journal of Ophthalmology

  • Current Issue

    March/April 2019 - Volume 8 - Issue 2
    Special Issue on Ocular Imaging
    pp: 97-194
    Guest Editors-in-Chief: Neeru Gupta, Christopher Leung
    Guest Editors: Carol Cheung, Ki Ho Park, Robert Weinreb, Tien Yin Wong

Editorial

Advances in Ocular Imaging Weinreb, Robert N.; Moghimi, Sasan
Judging by the increasing number of publications in scientific journals, the applications of ocular imaging to eye care continue to grow. Rapid advances in imaging technologies provide the clinician with tools for earlier diagnosis and enhanced monitoring of a plethora of eye diseases, as well as guidance for predicting disease outcome and assessing risk of vision loss. With high-speed imaging, for example, it is now possible to acquire high-definition images, as well as large, 3-dimensional visualization of various ocular structures. So it is appropriate to have an overview of some of these advances with the invited review articles in this special issue of the Asia-Pacific Journal of Ophthalmology from leading specialty groups in cornea, retina, cataract, and glaucoma.

Review Article

Advances in Whole-Eye Optical Coherence Tomography Imaging Kuo, Anthony N.; McNabb, Ryan P.; Izatt, Joseph A.
Contemporary anterior segment and retinal optical coherence tomography (OCT) systems only image their particular designated region of the eye and cannot image both areas of the eye at the same time. This separation is due to the differences in optical system design needed to properly image the front or back of the eye and also due to limitations in the imaging depth of current commercial OCT systems. More recently, research and commercial OCT systems capable of “whole-eye” imaging have been described. These whole-eye OCT systems enable applications such as ocular biometry for cataract surgery, ocular shape analysis for myopia, and others. Further, these whole-eye OCT systems allow us to image the eye as an integrated whole rather than as separate, independent divisions.
Advances in Corneal Imaging: Current Applications and Beyond Shih, Kendrick Co; Tse, Ryan Hin-Kai; Lau, Yumi Tsz-Ying; Chan, Tommy Chung-Yan
Recent advances in corneal imaging have allowed for more objective diagnosis and disease monitoring, as well as provided valuable guidance for treatment progress. However, there has been limited literature providing comprehensive insight into advances across different imaging modalities. The aim of this review was to provide a brief summary of significant advances in the field of corneal imaging over the past 5 years. A literature search in PubMed was performed on December 11, 2018, using the following key words in various and/or logic combinations: “cornea”, “development”, “advances”, “topography”, “Scheimpflug tomography”, “ultra-high-speed Scheimpflug”, “Corvis ST”, “densitometry”, “optical coherence tomography”, “UHR-OCT”, and “intraoperative OCT”. The initial search showed a total of 2910 articles. Filters were then applied to select original research studies on humans published in the last 5 years which are available in full text and written in English. A final 55 studies were included for analysis. This review looks into 5 key imaging modalities: topography, tomography, confocal microscopy, densitometry, and angiography. For each imaging modality, the underlying scientific principles and current applications are outlined. Existing limitations and potential future applications for each of them are also discussed in this review. Recent advances in the imaging modalities show immense potential in providing objective, high-resolution, and comprehensive visualization of corneal structures and pathologies. Application to different fields in the future is highly probable but technical, economic, and skill-based limitations must first be overcome. Any attempt to replace traditional imaging techniques with these newer techniques must also be supported with evidence from robust clinical studies.
Optical Coherence Tomography Angiography and Glaucoma: A Brief Review Moghimi, Sasan; Hou, Huiyuan; Rao, Harsha L.; Weinreb, Robert N.
Optical coherence tomography angiography (OCTA) is a new modality in ocular imaging which provides non-invasive assessment and measurement of the vascular structures in the retina and optic nerve head. This technique provides useful information in glaucoma, such as quantitative assessment of vessel density. Vessel density measurement can be affected by various subject-related, eye-related, and disease-related factors. Overall, OCTA has good repeatability and reproducibility, and can differentiate glaucoma eyes from normal eyes. It can also help detect early glaucoma, reach a floor effect at a more advanced disease stage than optical coherence tomography (OCT), and adds information about glaucoma patients at risk of progression. Although it has higher variability than OCT, it also promises to be useful for monitoring glaucoma by detecting progression throughout the glaucoma continuum.
Visual Assessment of Aqueous Humor Outflow Xie, Xiaobin; Akiyama, Goichi; Bogarin, Thania; Saraswathy, Sindhu; Huang, Alex S.
In the past decade, many new pharmacological and surgical treatments have become available to lower intraocular pressure (IOP) for glaucoma. The majority of these options have targeted improving aqueous humor outflow (AHO). At the same time, in addition to new treatments, research advances in AHO assessment have led to the development of new tools to structurally assess AHO pathways and to visualize where aqueous is flowing in the eye. These new imaging modalities have uncovered novel AHO observations that challenge traditional AHO concepts. New behaviors including segmental, pulsatile, and dynamic AHO may have relevance to the disease and the level of therapeutic response for IOP-lowering treatments. By better understanding the regulation of segmental, pulsatile, and dynamic AHO, it may be possible to find new and innovative treatments for glaucoma aiming at these new AHO behaviors.
Optical Coherence Tomography for the Diagnosis and Monitoring of Glaucoma Ha, Ahnul; Park, Ki Ho
Since its introduction to the field of ophthalmology, optical coherence tomography (OCT) has been markedly improved in terms of imaging protocols, algorithms, and new parameters that have enhanced its utility for the diagnosis and assessment of glaucoma progression. In this review, we examine the clinical utility of OCT in the diagnosis of glaucoma and monitoring of its progression, and emphasize the technological advances that facilitate both glaucoma research and the formulation of clinical management strategies.
Anterior Segment Optical Coherence Tomography: Applications for Clinical Care and Scientific Research Shan, Jing; DeBoer, Charles; Xu, Benjamin Y.
Anterior segment optical coherence tomography (AS-OCT) is a non-contact imaging technique that produces high-resolution images and quantitative measurements of the anterior segment and its anatomical structures. There has been rapid development of OCT technology over the past 2 decades, with the transition from time-domain to Fourier-domain OCT devices. By integrating these advancements in OCT technology, AS-OCT devices have evolved into versatile clinical and research tools for studies of the anterior segment and ocular surface. The primary purpose of this article was to review OCT technology and AS-OCT devices as well as applications of AS-OCT for clinical practice and scientific research. We first describe the different types of OCT technology, how they have been adapted for AS-OCT imaging, and differences between various AS-OCT devices. We then review the applications of AS-OCT for characterizing the anatomical structures of the anterior segment and aqueous outflow pathways, including the anterior chamber angle, trabecular meshwork, and Schlemm canal. We also describe glaucoma-related applications of AS-OCT imaging, which include evaluating patients for static and dynamic biometric risk factors of primary angle closure disease and assessing the efficacy of glaucoma interventions, such as laser peripheral iridotomy and glaucoma surgery. Finally, we review other clinical applications of AS-OCT imaging for detection and management of diseases of the ocular surface, cornea, and lens.
Artificial Intelligence in Diabetic Eye Disease Screening Cheung, Carol Y.; Tang, Fangyao; Ting, Daniel Shu Wei; Tan, Gavin Siew Wei; Wong, Tien Yin
Systematic or national screening programs for diabetic retinopathy (DR) and diabetic macular edema (DME), using digital fundus photography and optical coherence tomography (OCT), are currently implemented at primary care level, aiming to provide timely referral for vision-threatening DR and DME to ophthalmologists for timely treatment and vision loss prevention. However, interpretation of retinal images requires specialized knowledge and expertise in diabetic eye disease. Furthermore, current DR screening programs are capital- and labor-intensive, which makes it difficult to rapidly scale up and expand diabetic eye screening to meet the needs of this growing global epidemic. Deep learning (DL), a new branch of machine learning technology under the broad term of artificial intelligence (AI), has made remarkable breakthrough in medical imaging in particular for pattern recognition and image classification. In ophthalmology, AI and DL technology has been developed from big image datasets in assessment of retinal photographs for detection and screening of DR as well as the segmentation and assessment of OCT images for diagnosis and screening of DME. This review aimed to summarize the current progress and the development of using AI and DL technology for diabetic eye disease screening as well as current challenges in the actual implementation of DL in screening programs, and translating DL research into direct clinical applications of screening in a community setting.
New Concepts in Polypoidal Choroidal Vasculopathy Imaging: A Focus on Optical Coherence Tomography and Optical Coherence Tomography Angiography Teo, Kelvin Y.C.; Cheung, Gemmy C.M.
Polypoidal choroidal vasculopathy (PCV) is a variant of neovascular age-related macular degeneration. It is characterized by polypoidal dilatations at the terminus of branching vascular network located beneath the retinal pigment epithelium. These polypoidal lesions are best visualized on indocyanine green angiography. With recent advances in ocular imaging, optical coherence tomography (OCT) and OCT angiography (OCTA) have been increasingly used to aid in the diagnosis and monitoring of treatment responses in PCV. This review provides a summary of the current status of various imaging modalities in PCV, with special focus on OCT and OCTA.
Imaging of Pathologic Myopia Ohno-Matsui, Kyoko; Fang, Yuxin; Shinohara, Kosei; Takahashi, Hiroyuki; Uramoto, Kengo; Yokoi, Tae
Pathologic myopia (PM) is a major cause of irreversible visual impairment worldwide and especially in East Asian countries. The complications of PM include myopic maculopathy, myopic macular retinoschisis, dome-shaped macula, and myopic optic neuropathy. Posterior staphyloma is an important component of the diagnosis of PM and one of the hallmarks of PM. The photographic classification and grading system for myopic maculopathy has already been determined. Conventionally optical coherence tomography (OCT) was commonly used in PM and enabled investigators to image deeper tissue such as choroid and sclera. Today, the technological advances in OCT imaging including ultra-widefield OCT and 3-dimensional construction of OCT have given clinicians a novel insight on variable morphology in the PM.
Imaging in Retinopathy of Prematurity Valikodath, N.; Cole, E.; Chiang, M.F.; Campbell, J.P.; Chan, R.V.P.
Retinopathy of prematurity (ROP) is a leading cause of preventable childhood blindness worldwide. Barriers to ROP screening and difficulties with subsequent evaluation and management include poor access to care, lack of physicians trained in ROP, and issues with objective documentation. Digital retinal imaging can help address these barriers and improve our knowledge of the pathophysiology of the disease. Advancements in technology have led to new, non-mydriatic and mydriatic cameras with wider fields of view as well as devices that can simultaneously incorporate fluorescein angiography, optical coherence tomography (OCT), and OCT angiography. Image analysis in ROP is also being employed through smartphones and computer-based software. Telemedicine programs in the United States and worldwide have utilized imaging to extend ROP screening to infants in remote areas and have shown that digital retinal imaging can be reliable, accurate, and cost-effective. In addition, tele-education programs are also using digital retinal images to increase the number of healthcare providers trained in ROP. Although indirect ophthalmoscopy is still an important skill for screening, digital retinal imaging holds promise for more widespread screening and management of ROP.
Artificial Intelligence and Optical Coherence Tomography Imaging Kapoor, Rahul; Whigham, Benjamin T.; Al-Aswad, Lama A.
This review article aimed to highlight the application and use of artificial intelligence (AI) in optical coherence tomography (OCT) imaging in ophthalmology. Artificial intelligence programs seek to simulate intelligent human behavior in computers. With an abundance of patient data, especially with the advent and growing use of imaging modalities such as OCT, AI programs provide us with the unique opportunity to analyze this plethora of information and assist in making clinical decisions in the field of ophthalmology. Groups around the world have developed and evaluated AI programs that gather data from diagnostic modalities, such as OCT, that assist in the diagnosis and management of ophthalmological diseases with a high accuracy. Artificial intelligence programs using OCT have the potential to play a significant role in the diagnosis and management of ophthalmological disease in the near future. Incorporation of AI in medicine, however, is not without its pitfalls. Some limitations of AI in ophthalmology are also discussed in this review. These include the deskilling of physicians due to increase in reliance on automation, inability of AI programs to take a holistic approach to clinical encounters with patients, requirement of pre-existing strong datasets to train AI programs, and the inability of AI programs to incorporate the ambiguity and variability that is intrinsic to the nature of clinical medicine.
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